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Qualitative Research – Methods, Analysis Types and Guide

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Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

• Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
• Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

• Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
• Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
• Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
• Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
• Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
• Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
• Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

• Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
• Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

• Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
• Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
• Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
• Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

• Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
• Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
• Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
• Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
• Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

• Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
• Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
• Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
• Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
• Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
• Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

• Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
• Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
• Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
• Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
• Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
• Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

• Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
• Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
• Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
• Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
• Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
• Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

Also see Research Methods

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“Not everything that can be counted counts, and not everything that counts can be counted“ (Albert Einstein)

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data (Punch, 2013). 

Qualitative research can be used to: (i) gain deep contextual understandings of the subjective social reality of individuals and (ii) to answer questions about experience and meaning from the participant’s perspective (Hammarberg et al., 2016).

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research focuses on thematic and contextual information.

Characteristics of Qualitative Research 

Reality is socially constructed.

Qualitative research aims to understand how participants make meaning of their experiences – individually or in social contexts. It assumes there is no objective reality and that the social world is interpreted (Yilmaz, 2013). 

The primacy of subject matter 

The primary aim of qualitative research is to understand the perspectives, experiences, and beliefs of individuals who have experienced the phenomenon selected for research rather than the average experiences of groups of people (Minichiello, 1990).

Variables are complex, interwoven, and difficult to measure

Factors such as experiences, behaviors, and attitudes are complex and interwoven, so they cannot be reduced to isolated variables , making them difficult to measure quantitatively.

However, a qualitative approach enables participants to describe what, why, or how they were thinking/ feeling during a phenomenon being studied (Yilmaz, 2013). 

Emic (insider’s point of view)

The phenomenon being studied is centered on the participants’ point of view (Minichiello, 1990).

Emic is used to describe how participants interact, communicate, and behave in the context of the research setting (Scarduzio, 2017).

Why Conduct Qualitative Research? 

In order to gain a deeper understanding of how people experience the world, individuals are studied in their natural setting. This enables the researcher to understand a phenomenon close to how participants experience it. 

Qualitative research allows researchers to gain an in-depth understanding, which is difficult to attain using quantitative methods. 

An in-depth understanding is attained since qualitative techniques allow participants to freely disclose their experiences, thoughts, and feelings without constraint (Tenny et al., 2022). 

This helps to further investigate and understand quantitative data by discovering reasons for the outcome of a study – answering the why question behind statistics. 

The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively (Busetto et al., 2020).

To design hypotheses, theory must be researched using qualitative methods to find out what is important in order to begin research. 

For example, by conducting interviews or focus groups with key stakeholders to discover what is important to them. 

Examples of qualitative research questions include: 

• How does stress influence young adults’ behavior?
• What factors influence students’ school attendance rates in developed countries?
• How do adults interpret binge drinking in the UK?
• What are the psychological impacts of cervical cancer screening in women?
• How can mental health lessons be integrated into the school curriculum? 

Collecting Qualitative Data

There are four main research design methods used to collect qualitative data: observations, interviews,  focus groups, and ethnography.

Observations

This method involves watching and recording phenomena as they occur in nature. Observation can be divided into two types: participant and non-participant observation.

In participant observation, the researcher actively participates in the situation/events being observed.

In non-participant observation, the researcher is not an active part of the observation and tries not to influence the behaviors they are observing (Busetto et al., 2020). 

Observations can be covert (participants are unaware that a researcher is observing them) or overt (participants are aware of the researcher’s presence and know they are being observed).

However, awareness of an observer’s presence may influence participants’ behavior. 

Interviews give researchers a window into the world of a participant by seeking their account of an event, situation, or phenomenon. They are usually conducted on a one-to-one basis and can be distinguished according to the level at which they are structured (Punch, 2013). 

Structured interviews involve predetermined questions and sequences to ensure replicability and comparability. However, they are unable to explore emerging issues.

Informal interviews consist of spontaneous, casual conversations which are closer to the truth of a phenomenon. However, information is gathered using quick notes made by the researcher and is therefore subject to recall bias. 

Semi-structured interviews have a flexible structure, phrasing, and placement so emerging issues can be explored (Denny & Weckesser, 2022).

The use of probing questions and clarification can lead to a detailed understanding, but semi-structured interviews can be time-consuming and subject to interviewer bias. 

Focus groups 

Similar to interviews, focus groups elicit a rich and detailed account of an experience. However, focus groups are more dynamic since participants with shared characteristics construct this account together (Denny & Weckesser, 2022).

A shared narrative is built between participants to capture a group experience shaped by a shared context. 

The researcher takes on the role of a moderator, who will establish ground rules and guide the discussion by following a topic guide to focus the group discussions.

Typically, focus groups have 4-10 participants as a discussion can be difficult to facilitate with more than this, and this number allows everyone the time to speak.

Ethnography

Ethnography is a methodology used to study a group of people’s behaviors and social interactions in their environment (Reeves et al., 2008).

Data are collected using methods such as observations, field notes, or structured/ unstructured interviews.

The aim of ethnography is to provide detailed, holistic insights into people’s behavior and perspectives within their natural setting. In order to achieve this, researchers immerse themselves in a community or organization. 

Due to the flexibility and real-world focus of ethnography, researchers are able to gather an in-depth, nuanced understanding of people’s experiences, knowledge and perspectives that are influenced by culture and society.

In order to develop a representative picture of a particular culture/ context, researchers must conduct extensive field work. 

This can be time-consuming as researchers may need to immerse themselves into a community/ culture for a few days, or possibly a few years.

Qualitative Data Analysis Methods

Different methods can be used for analyzing qualitative data. The researcher chooses based on the objectives of their study. 

The researcher plays a key role in the interpretation of data, making decisions about the coding, theming, decontextualizing, and recontextualizing of data (Starks & Trinidad, 2007). 

Grounded theory

Grounded theory is a qualitative method specifically designed to inductively generate theory from data. It was developed by Glaser and Strauss in 1967 (Glaser & Strauss, 2017).

 This methodology aims to develop theories (rather than test hypotheses) that explain a social process, action, or interaction (Petty et al., 2012). To inform the developing theory, data collection and analysis run simultaneously. 

There are three key types of coding used in grounded theory: initial (open), intermediate (axial), and advanced (selective) coding. 

Throughout the analysis, memos should be created to document methodological and theoretical ideas about the data. Data should be collected and analyzed until data saturation is reached and a theory is developed. 

Content analysis

Content analysis was first used in the early twentieth century to analyze textual materials such as newspapers and political speeches.

Content analysis is a research method used to identify and analyze the presence and patterns of themes, concepts, or words in data (Vaismoradi et al., 2013). 

This research method can be used to analyze data in different formats, which can be written, oral, or visual. 

The goal of content analysis is to develop themes that capture the underlying meanings of data (Schreier, 2012). 

Qualitative content analysis can be used to validate existing theories, support the development of new models and theories, and provide in-depth descriptions of particular settings or experiences.

The following six steps provide a guideline for how to conduct qualitative content analysis.

• Define a Research Question : To start content analysis, a clear research question should be developed.
• Identify and Collect Data : Establish the inclusion criteria for your data. Find the relevant sources to analyze.
• Define the Unit or Theme of Analysis : Categorize the content into themes. Themes can be a word, phrase, or sentence.
• Develop Rules for Coding your Data : Define a set of coding rules to ensure that all data are coded consistently.
• Code the Data : Follow the coding rules to categorize data into themes.
• Analyze the Results and Draw Conclusions : Examine the data to identify patterns and draw conclusions in relation to your research question.

Discourse analysis

Discourse analysis is a research method used to study written/ spoken language in relation to its social context (Wood & Kroger, 2000).

In discourse analysis, the researcher interprets details of language materials and the context in which it is situated.

Discourse analysis aims to understand the functions of language (how language is used in real life) and how meaning is conveyed by language in different contexts. Researchers use discourse analysis to investigate social groups and how language is used to achieve specific communication goals.

Different methods of discourse analysis can be used depending on the aims and objectives of a study. However, the following steps provide a guideline on how to conduct discourse analysis.

• Define the Research Question : Develop a relevant research question to frame the analysis.
• Gather Data and Establish the Context : Collect research materials (e.g., interview transcripts, documents). Gather factual details and review the literature to construct a theory about the social and historical context of your study.
• Analyze the Content : Closely examine various components of the text, such as the vocabulary, sentences, paragraphs, and structure of the text. Identify patterns relevant to the research question to create codes, then group these into themes.
• Review the Results : Reflect on the findings to examine the function of the language, and the meaning and context of the discourse. 

Thematic analysis

Thematic analysis is a method used to identify, interpret, and report patterns in data, such as commonalities or contrasts. 

Although the origin of thematic analysis can be traced back to the early twentieth century, understanding and clarity of thematic analysis is attributed to Braun and Clarke (2006).

Thematic analysis aims to develop themes (patterns of meaning) across a dataset to address a research question. 

In thematic analysis, qualitative data is gathered using techniques such as interviews, focus groups, and questionnaires. Audio recordings are transcribed. The dataset is then explored and interpreted by a researcher to identify patterns. 

This occurs through the rigorous process of data familiarisation, coding, theme development, and revision. These identified patterns provide a summary of the dataset and can be used to address a research question.

Themes are developed by exploring the implicit and explicit meanings within the data. Two different approaches are used to generate themes: inductive and deductive. 

An inductive approach allows themes to emerge from the data. In contrast, a deductive approach uses existing theories or knowledge to apply preconceived ideas to the data.

Phases of Thematic Analysis

Braun and Clarke (2006) provide a guide of the six phases of thematic analysis. These phases can be applied flexibly to fit research questions and data. 

Template analysis

Template analysis refers to a specific method of thematic analysis which uses hierarchical coding (Brooks et al., 2014).

Template analysis is used to analyze textual data, for example, interview transcripts or open-ended responses on a written questionnaire.

To conduct template analysis, a coding template must be developed (usually from a subset of the data) and subsequently revised and refined. This template represents the themes identified by researchers as important in the dataset. 

Codes are ordered hierarchically within the template, with the highest-level codes demonstrating overarching themes in the data and lower-level codes representing constituent themes with a narrower focus.

A guideline for the main procedural steps for conducting template analysis is outlined below.

• Familiarization with the Data : Read (and reread) the dataset in full. Engage, reflect, and take notes on data that may be relevant to the research question.
• Preliminary Coding : Identify initial codes using guidance from the a priori codes, identified before the analysis as likely to be beneficial and relevant to the analysis.
• Organize Themes : Organize themes into meaningful clusters. Consider the relationships between the themes both within and between clusters.
• Produce an Initial Template : Develop an initial template. This may be based on a subset of the data.
• Apply and Develop the Template : Apply the initial template to further data and make any necessary modifications. Refinements of the template may include adding themes, removing themes, or changing the scope/title of themes. 
• Finalize Template : Finalize the template, then apply it to the entire dataset. 

Frame analysis

Frame analysis is a comparative form of thematic analysis which systematically analyzes data using a matrix output.

Ritchie and Spencer (1994) developed this set of techniques to analyze qualitative data in applied policy research. Frame analysis aims to generate theory from data.

Frame analysis encourages researchers to organize and manage their data using summarization.

This results in a flexible and unique matrix output, in which individual participants (or cases) are represented by rows and themes are represented by columns. 

Each intersecting cell is used to summarize findings relating to the corresponding participant and theme.

Frame analysis has five distinct phases which are interrelated, forming a methodical and rigorous framework.

• Familiarization with the Data : Familiarize yourself with all the transcripts. Immerse yourself in the details of each transcript and start to note recurring themes.
• Develop a Theoretical Framework : Identify recurrent/ important themes and add them to a chart. Provide a framework/ structure for the analysis.
• Indexing : Apply the framework systematically to the entire study data.
• Summarize Data in Analytical Framework : Reduce the data into brief summaries of participants’ accounts.
• Mapping and Interpretation : Compare themes and subthemes and check against the original transcripts. Group the data into categories and provide an explanation for them.

Preventing Bias in Qualitative Research

To evaluate qualitative studies, the CASP (Critical Appraisal Skills Programme) checklist for qualitative studies can be used to ensure all aspects of a study have been considered (CASP, 2018).

The quality of research can be enhanced and assessed using criteria such as checklists, reflexivity, co-coding, and member-checking. 

Co-coding 

Relying on only one researcher to interpret rich and complex data may risk key insights and alternative viewpoints being missed. Therefore, coding is often performed by multiple researchers.

A common strategy must be defined at the beginning of the coding process  (Busetto et al., 2020). This includes establishing a useful coding list and finding a common definition of individual codes.

Transcripts are initially coded independently by researchers and then compared and consolidated to minimize error or bias and to bring confirmation of findings. 

Member checking

Member checking (or respondent validation) involves checking back with participants to see if the research resonates with their experiences (Russell & Gregory, 2003).

Data can be returned to participants after data collection or when results are first available. For example, participants may be provided with their interview transcript and asked to verify whether this is a complete and accurate representation of their views.

Participants may then clarify or elaborate on their responses to ensure they align with their views (Shenton, 2004).

This feedback becomes part of data collection and ensures accurate descriptions/ interpretations of phenomena (Mays & Pope, 2000). 

Reflexivity in qualitative research

Reflexivity typically involves examining your own judgments, practices, and belief systems during data collection and analysis. It aims to identify any personal beliefs which may affect the research. 

Reflexivity is essential in qualitative research to ensure methodological transparency and complete reporting. This enables readers to understand how the interaction between the researcher and participant shapes the data.

Depending on the research question and population being researched, factors that need to be considered include the experience of the researcher, how the contact was established and maintained, age, gender, and ethnicity.

These details are important because, in qualitative research, the researcher is a dynamic part of the research process and actively influences the outcome of the research (Boeije, 2014). 

Reflexivity Example

Who you are and your characteristics influence how you collect and analyze data. Here is an example of a reflexivity statement for research on smoking. I am a 30-year-old white female from a middle-class background. I live in the southwest of England and have been educated to master’s level. I have been involved in two research projects on oral health. I have never smoked, but I have witnessed how smoking can cause ill health from my volunteering in a smoking cessation clinic. My research aspirations are to help to develop interventions to help smokers quit.

Establishing Trustworthiness in Qualitative Research

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

Credibility in Qualitative Research

Credibility refers to how accurately the results represent the reality and viewpoints of the participants.

To establish credibility in research, participants’ views and the researcher’s representation of their views need to align (Tobin & Begley, 2004).

To increase the credibility of findings, researchers may use data source triangulation, investigator triangulation, peer debriefing, or member checking (Lincoln & Guba, 1985). 

Transferability in Qualitative Research

Transferability refers to how generalizable the findings are: whether the findings may be applied to another context, setting, or group (Tobin & Begley, 2004).

Transferability can be enhanced by giving thorough and in-depth descriptions of the research setting, sample, and methods (Nowell et al., 2017). 

Dependability in Qualitative Research

Dependability is the extent to which the study could be replicated under similar conditions and the findings would be consistent.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

Confirmability in Qualitative Research

Confirmability is concerned with establishing that there is a clear link between the researcher’s interpretations/ findings and the data.

Researchers can achieve confirmability by demonstrating how conclusions and interpretations were arrived at (Nowell et al., 2017).

This enables readers to understand the reasoning behind the decisions made. 

Audit Trails in Qualitative Research

An audit trail provides evidence of the decisions made by the researcher regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data. 

The researcher must provide a clear rationale to demonstrate how conclusions were reached in their study.

A clear description of the research path must be provided to enable readers to trace through the researcher’s logic (Halpren, 1983).

Researchers should maintain records of the raw data, field notes, transcripts, and a reflective journal in order to provide a clear audit trail. 

Discovery of unexpected data

Open-ended questions in qualitative research mean the researcher can probe an interview topic and enable the participant to elaborate on responses in an unrestricted manner.

This allows unexpected data to emerge, which can lead to further research into that topic. 

Flexibility

Data collection and analysis can be modified and adapted to take the research in a different direction if new ideas or patterns emerge in the data.

This enables researchers to investigate new opportunities while firmly maintaining their research goals. 

Naturalistic settings

The behaviors of participants are recorded in real-world settings. Studies that use real-world settings have high ecological validity since participants behave more authentically. 

Limitations

Time-consuming .

Qualitative research results in large amounts of data which often need to be transcribed and analyzed manually.

Even when software is used, transcription can be inaccurate, and using software for analysis can result in many codes which need to be condensed into themes. 

Subjectivity 

The researcher has an integral role in collecting and interpreting qualitative data. Therefore, the conclusions reached are from their perspective and experience.

Consequently, interpretations of data from another researcher may vary greatly. 

Limited generalizability

The aim of qualitative research is to provide a detailed, contextualized understanding of an aspect of the human experience from a relatively small sample size.

Despite rigorous analysis procedures, conclusions drawn cannot be generalized to the wider population since data may be biased or unrepresentative.

Therefore, results are only applicable to a small group of the population. 

Extraneous variables

Qualitative research is often conducted in real-world settings. This may cause results to be unreliable since extraneous variables may affect the data, for example:

• Situational variables : different environmental conditions may influence participants’ behavior in a study. The random variation in factors (such as noise or lighting) may be difficult to control in real-world settings.
• Participant characteristics : this includes any characteristics that may influence how a participant answers/ behaves in a study. This may include a participant’s mood, gender, age, ethnicity, sexual identity, IQ, etc.
• Experimenter effect : experimenter effect refers to how a researcher’s unintentional influence can change the outcome of a study. This occurs when (i) their interactions with participants unintentionally change participants’ behaviors or (ii) due to errors in observation, interpretation, or analysis. 

What sample size should qualitative research be?

The sample size for qualitative studies has been recommended to include a minimum of 12 participants to reach data saturation (Braun, 2013).

Are surveys qualitative or quantitative?

Surveys can be used to gather information from a sample qualitatively or quantitatively. Qualitative surveys use open-ended questions to gather detailed information from a large sample using free text responses.

The use of open-ended questions allows for unrestricted responses where participants use their own words, enabling the collection of more in-depth information than closed-ended questions.

In contrast, quantitative surveys consist of closed-ended questions with multiple-choice answer options. Quantitative surveys are ideal to gather a statistical representation of a population.

What are the ethical considerations of qualitative research?

Before conducting a study, you must think about any risks that could occur and take steps to prevent them. Participant Protection : Researchers must protect participants from physical and mental harm. This means you must not embarrass, frighten, offend, or harm participants. Transparency : Researchers are obligated to clearly communicate how they will collect, store, analyze, use, and share the data. Confidentiality : You need to consider how to maintain the confidentiality and anonymity of participants’ data.

What is triangulation in qualitative research?

Triangulation refers to the use of several approaches in a study to comprehensively understand phenomena. This method helps to increase the validity and credibility of research findings. 

Types of triangulation include method triangulation (using multiple methods to gather data); investigator triangulation (multiple researchers for collecting/ analyzing data), theory triangulation (comparing several theoretical perspectives to explain a phenomenon), and data source triangulation (using data from various times, locations, and people; Carter et al., 2014).

Why is qualitative research important?

Qualitative research allows researchers to describe and explain the social world. The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively.

In qualitative research, participants are able to express their thoughts, experiences, and feelings without constraint.

Additionally, researchers are able to follow up on participants’ answers in real-time, generating valuable discussion around a topic. This enables researchers to gain a nuanced understanding of phenomena which is difficult to attain using quantitative methods.

What is coding data in qualitative research?

Coding data is a qualitative data analysis strategy in which a section of text is assigned with a label that describes its content.

These labels may be words or phrases which represent important (and recurring) patterns in the data.

This process enables researchers to identify related content across the dataset. Codes can then be used to group similar types of data to generate themes.

What is the difference between qualitative and quantitative research?

Qualitative research involves the collection and analysis of non-numerical data in order to understand experiences and meanings from the participant’s perspective.

This can provide rich, in-depth insights on complicated phenomena. Qualitative data may be collected using interviews, focus groups, or observations.

In contrast, quantitative research involves the collection and analysis of numerical data to measure the frequency, magnitude, or relationships of variables. This can provide objective and reliable evidence that can be generalized to the wider population.

Quantitative data may be collected using closed-ended questionnaires or experiments.

What is trustworthiness in qualitative research?

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability. 

Credibility refers to how accurately the results represent the reality and viewpoints of the participants. Transferability refers to whether the findings may be applied to another context, setting, or group.

Dependability is the extent to which the findings are consistent and reliable. Confirmability refers to the objectivity of findings (not influenced by the bias or assumptions of researchers).

What is data saturation in qualitative research?

Data saturation is a methodological principle used to guide the sample size of a qualitative research study.

Data saturation is proposed as a necessary methodological component in qualitative research (Saunders et al., 2018) as it is a vital criterion for discontinuing data collection and/or analysis. 

The intention of data saturation is to find “no new data, no new themes, no new coding, and ability to replicate the study” (Guest et al., 2006). Therefore, enough data has been gathered to make conclusions.

Why is sampling in qualitative research important?

In quantitative research, large sample sizes are used to provide statistically significant quantitative estimates.

This is because quantitative research aims to provide generalizable conclusions that represent populations.

However, the aim of sampling in qualitative research is to gather data that will help the researcher understand the depth, complexity, variation, or context of a phenomenon. The small sample sizes in qualitative studies support the depth of case-oriented analysis.

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The Oxford Handbook of Qualitative Research (2nd edn)

Patricia Leavy Independent Scholar Kennebunk, ME, USA

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The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research; ample discussion of the historical, theoretical, and methodological foundations of the field; and coverage of key issues including data collection, interpretation, representation, assessment, and teaching, this handbook aims to be a valuable text for students, professors, and researchers. This newly revised and expanded edition features up-to-date examples and topics, including seven new chapters on duoethnography, team research, writing ethnographically, creative approaches to writing, writing for performance, writing for the public, and teaching qualitative research.

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Qualitative Research : Definition

Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images.  In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use in-depth studies of the social world to analyze how and why groups think and act in particular ways (for instance, case studies of the experiences that shape political views).   

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Chapter 5. Sampling

Introduction.

Most Americans will experience unemployment at some point in their lives. Sarah Damaske ( 2021 ) was interested in learning about how men and women experience unemployment differently. To answer this question, she interviewed unemployed people. After conducting a “pilot study” with twenty interviewees, she realized she was also interested in finding out how working-class and middle-class persons experienced unemployment differently. She found one hundred persons through local unemployment offices. She purposefully selected a roughly equal number of men and women and working-class and middle-class persons for the study. This would allow her to make the kinds of comparisons she was interested in. She further refined her selection of persons to interview:

I decided that I needed to be able to focus my attention on gender and class; therefore, I interviewed only people born between 1962 and 1987 (ages 28–52, the prime working and child-rearing years), those who worked full-time before their job loss, those who experienced an involuntary job loss during the past year, and those who did not lose a job for cause (e.g., were not fired because of their behavior at work). ( 244 )

The people she ultimately interviewed compose her sample. They represent (“sample”) the larger population of the involuntarily unemployed. This “theoretically informed stratified sampling design” allowed Damaske “to achieve relatively equal distribution of participation across gender and class,” but it came with some limitations. For one, the unemployment centers were located in primarily White areas of the country, so there were very few persons of color interviewed. Qualitative researchers must make these kinds of decisions all the time—who to include and who not to include. There is never an absolutely correct decision, as the choice is linked to the particular research question posed by the particular researcher, although some sampling choices are more compelling than others. In this case, Damaske made the choice to foreground both gender and class rather than compare all middle-class men and women or women of color from different class positions or just talk to White men. She leaves the door open for other researchers to sample differently. Because science is a collective enterprise, it is most likely someone will be inspired to conduct a similar study as Damaske’s but with an entirely different sample.

This chapter is all about sampling. After you have developed a research question and have a general idea of how you will collect data (observations or interviews), how do you go about actually finding people and sites to study? Although there is no “correct number” of people to interview, the sample should follow the research question and research design. You might remember studying sampling in a quantitative research course. Sampling is important here too, but it works a bit differently. Unlike quantitative research, qualitative research involves nonprobability sampling. This chapter explains why this is so and what qualities instead make a good sample for qualitative research.

Quick Terms Refresher

• The population is the entire group that you want to draw conclusions about.
• The sample is the specific group of individuals that you will collect data from.
• Sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).
• Sample size is how many individuals (or units) are included in your sample.

The “Who” of Your Research Study

After you have turned your general research interest into an actual research question and identified an approach you want to take to answer that question, you will need to specify the people you will be interviewing or observing. In most qualitative research, the objects of your study will indeed be people. In some cases, however, your objects might be content left by people (e.g., diaries, yearbooks, photographs) or documents (official or unofficial) or even institutions (e.g., schools, medical centers) and locations (e.g., nation-states, cities). Chances are, whatever “people, places, or things” are the objects of your study, you will not really be able to talk to, observe, or follow every single individual/object of the entire population of interest. You will need to create a sample of the population . Sampling in qualitative research has different purposes and goals than sampling in quantitative research. Sampling in both allows you to say something of interest about a population without having to include the entire population in your sample.

We begin this chapter with the case of a population of interest composed of actual people. After we have a better understanding of populations and samples that involve real people, we’ll discuss sampling in other types of qualitative research, such as archival research, content analysis, and case studies. We’ll then move to a larger discussion about the difference between sampling in qualitative research generally versus quantitative research, then we’ll move on to the idea of “theoretical” generalizability, and finally, we’ll conclude with some practical tips on the correct “number” to include in one’s sample.

Sampling People

To help think through samples, let’s imagine we want to know more about “vaccine hesitancy.” We’ve all lived through 2020 and 2021, and we know that a sizable number of people in the United States (and elsewhere) were slow to accept vaccines, even when these were freely available. By some accounts, about one-third of Americans initially refused vaccination. Why is this so? Well, as I write this in the summer of 2021, we know that some people actively refused the vaccination, thinking it was harmful or part of a government plot. Others were simply lazy or dismissed the necessity. And still others were worried about harmful side effects. The general population of interest here (all adult Americans who were not vaccinated by August 2021) may be as many as eighty million people. We clearly cannot talk to all of them. So we will have to narrow the number to something manageable. How can we do this?

First, we have to think about our actual research question and the form of research we are conducting. I am going to begin with a quantitative research question. Quantitative research questions tend to be simpler to visualize, at least when we are first starting out doing social science research. So let us say we want to know what percentage of each kind of resistance is out there and how race or class or gender affects vaccine hesitancy. Again, we don’t have the ability to talk to everyone. But harnessing what we know about normal probability distributions (see quantitative methods for more on this), we can find this out through a sample that represents the general population. We can’t really address these particular questions if we only talk to White women who go to college with us. And if you are really trying to generalize the specific findings of your sample to the larger population, you will have to employ probability sampling , a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly. Why randomly? If truly random, all the members have an equal opportunity to be a part of the sample, and thus we avoid the problem of having only our friends and neighbors (who may be very different from other people in the population) in the study. Mathematically, there is going to be a certain number that will be large enough to allow us to generalize our particular findings from our sample population to the population at large. It might surprise you how small that number can be. Election polls of no more than one thousand people are routinely used to predict actual election outcomes of millions of people. Below that number, however, you will not be able to make generalizations. Talking to five people at random is simply not enough people to predict a presidential election.

In order to answer quantitative research questions of causality, one must employ probability sampling. Quantitative researchers try to generalize their findings to a larger population. Samples are designed with that in mind. Qualitative researchers ask very different questions, though. Qualitative research questions are not about “how many” of a certain group do X (in this case, what percentage of the unvaccinated hesitate for concern about safety rather than reject vaccination on political grounds). Qualitative research employs nonprobability sampling . By definition, not everyone has an equal opportunity to be included in the sample. The researcher might select White women they go to college with to provide insight into racial and gender dynamics at play. Whatever is found by doing so will not be generalizable to everyone who has not been vaccinated, or even all White women who have not been vaccinated, or even all White women who have not been vaccinated who are in this particular college. That is not the point of qualitative research at all. This is a really important distinction, so I will repeat in bold: Qualitative researchers are not trying to statistically generalize specific findings to a larger population . They have not failed when their sample cannot be generalized, as that is not the point at all.

In the previous paragraph, I said it would be perfectly acceptable for a qualitative researcher to interview five White women with whom she goes to college about their vaccine hesitancy “to provide insight into racial and gender dynamics at play.” The key word here is “insight.” Rather than use a sample as a stand-in for the general population, as quantitative researchers do, the qualitative researcher uses the sample to gain insight into a process or phenomenon. The qualitative researcher is not going to be content with simply asking each of the women to state her reason for not being vaccinated and then draw conclusions that, because one in five of these women were concerned about their health, one in five of all people were also concerned about their health. That would be, frankly, a very poor study indeed. Rather, the qualitative researcher might sit down with each of the women and conduct a lengthy interview about what the vaccine means to her, why she is hesitant, how she manages her hesitancy (how she explains it to her friends), what she thinks about others who are unvaccinated, what she thinks of those who have been vaccinated, and what she knows or thinks she knows about COVID-19. The researcher might include specific interview questions about the college context, about their status as White women, about the political beliefs they hold about racism in the US, and about how their own political affiliations may or may not provide narrative scripts about “protective whiteness.” There are many interesting things to ask and learn about and many things to discover. Where a quantitative researcher begins with clear parameters to set their population and guide their sample selection process, the qualitative researcher is discovering new parameters, making it impossible to engage in probability sampling.

Looking at it this way, sampling for qualitative researchers needs to be more strategic. More theoretically informed. What persons can be interviewed or observed that would provide maximum insight into what is still unknown? In other words, qualitative researchers think through what cases they could learn the most from, and those are the cases selected to study: “What would be ‘bias’ in statistical sampling, and therefore a weakness, becomes intended focus in qualitative sampling, and therefore a strength. The logic and power of purposeful sampling like in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling” ( Patton 2002:230 ; emphases in the original).

Before selecting your sample, though, it is important to clearly identify the general population of interest. You need to know this before you can determine the sample. In our example case, it is “adult Americans who have not yet been vaccinated.” Depending on the specific qualitative research question, however, it might be “adult Americans who have been vaccinated for political reasons” or even “college students who have not been vaccinated.” What insights are you seeking? Do you want to know how politics is affecting vaccination? Or do you want to understand how people manage being an outlier in a particular setting (unvaccinated where vaccinations are heavily encouraged if not required)? More clearly stated, your population should align with your research question . Think back to the opening story about Damaske’s work studying the unemployed. She drew her sample narrowly to address the particular questions she was interested in pursuing. Knowing your questions or, at a minimum, why you are interested in the topic will allow you to draw the best sample possible to achieve insight.

Once you have your population in mind, how do you go about getting people to agree to be in your sample? In qualitative research, it is permissible to find people by convenience. Just ask for people who fit your sample criteria and see who shows up. Or reach out to friends and colleagues and see if they know anyone that fits. Don’t let the name convenience sampling mislead you; this is not exactly “easy,” and it is certainly a valid form of sampling in qualitative research. The more unknowns you have about what you will find, the more convenience sampling makes sense. If you don’t know how race or class or political affiliation might matter, and your population is unvaccinated college students, you can construct a sample of college students by placing an advertisement in the student paper or posting a flyer on a notice board. Whoever answers is your sample. That is what is meant by a convenience sample. A common variation of convenience sampling is snowball sampling . This is particularly useful if your target population is hard to find. Let’s say you posted a flyer about your study and only two college students responded. You could then ask those two students for referrals. They tell their friends, and those friends tell other friends, and, like a snowball, your sample gets bigger and bigger.

Researcher Note

Gaining Access: When Your Friend Is Your Research Subject

My early experience with qualitative research was rather unique. At that time, I needed to do a project that required me to interview first-generation college students, and my friends, with whom I had been sharing a dorm for two years, just perfectly fell into the sample category. Thus, I just asked them and easily “gained my access” to the research subject; I know them, we are friends, and I am part of them. I am an insider. I also thought, “Well, since I am part of the group, I can easily understand their language and norms, I can capture their honesty, read their nonverbal cues well, will get more information, as they will be more opened to me because they trust me.” All in all, easy access with rich information. But, gosh, I did not realize that my status as an insider came with a price! When structuring the interview questions, I began to realize that rather than focusing on the unique experiences of my friends, I mostly based the questions on my own experiences, assuming we have similar if not the same experiences. I began to struggle with my objectivity and even questioned my role; am I doing this as part of the group or as a researcher? I came to know later that my status as an insider or my “positionality” may impact my research. It not only shapes the process of data collection but might heavily influence my interpretation of the data. I came to realize that although my inside status came with a lot of benefits (especially for access), it could also bring some drawbacks.

—Dede Setiono, PhD student focusing on international development and environmental policy, Oregon State University

The more you know about what you might find, the more strategic you can be. If you wanted to compare how politically conservative and politically liberal college students explained their vaccine hesitancy, for example, you might construct a sample purposively, finding an equal number of both types of students so that you can make those comparisons in your analysis. This is what Damaske ( 2021 ) did. You could still use convenience or snowball sampling as a way of recruitment. Post a flyer at the conservative student club and then ask for referrals from the one student that agrees to be interviewed. As with convenience sampling, there are variations of purposive sampling as well as other names used (e.g., judgment, quota, stratified, criterion, theoretical). Try not to get bogged down in the nomenclature; instead, focus on identifying the general population that matches your research question and then using a sampling method that is most likely to provide insight, given the types of questions you have.

There are all kinds of ways of being strategic with sampling in qualitative research. Here are a few of my favorite techniques for maximizing insight:

• Consider using “extreme” or “deviant” cases. Maybe your college houses a prominent anti-vaxxer who has written about and demonstrated against the college’s policy on vaccines. You could learn a lot from that single case (depending on your research question, of course).
• Consider “intensity”: people and cases and circumstances where your questions are more likely to feature prominently (but not extremely or deviantly). For example, you could compare those who volunteer at local Republican and Democratic election headquarters during an election season in a study on why party matters. Those who volunteer are more likely to have something to say than those who are more apathetic.
• Maximize variation, as with the case of “politically liberal” versus “politically conservative,” or include an array of social locations (young vs. old; Northwest vs. Southeast region). This kind of heterogeneity sampling can capture and describe the central themes that cut across the variations: any common patterns that emerge, even in this wildly mismatched sample, are probably important to note!
• Rather than maximize the variation, you could select a small homogenous sample to describe some particular subgroup in depth. Focus groups are often the best form of data collection for homogeneity sampling.
• Think about which cases are “critical” or politically important—ones that “if it happens here, it would happen anywhere” or a case that is politically sensitive, as with the single “blue” (Democratic) county in a “red” (Republican) state. In both, you are choosing a site that would yield the most information and have the greatest impact on the development of knowledge.
• On the other hand, sometimes you want to select the “typical”—the typical college student, for example. You are trying to not generalize from the typical but illustrate aspects that may be typical of this case or group. When selecting for typicality, be clear with yourself about why the typical matches your research questions (and who might be excluded or marginalized in doing so).
• Finally, it is often a good idea to look for disconfirming cases : if you are at the stage where you have a hypothesis (of sorts), you might select those who do not fit your hypothesis—you will surely learn something important there. They may be “exceptions that prove the rule” or exceptions that force you to alter your findings in order to make sense of these additional cases.

In addition to all these sampling variations, there is the theoretical approach taken by grounded theorists in which the researcher samples comparative people (or events) on the basis of their potential to represent important theoretical constructs. The sample, one can say, is by definition representative of the phenomenon of interest. It accompanies the constant comparative method of analysis. In the words of the funders of Grounded Theory , “Theoretical sampling is sampling on the basis of the emerging concepts, with the aim being to explore the dimensional range or varied conditions along which the properties of the concepts vary” ( Strauss and Corbin 1998:73 ).

When Your Population is Not Composed of People

I think it is easiest for most people to think of populations and samples in terms of people, but sometimes our units of analysis are not actually people. They could be places or institutions. Even so, you might still want to talk to people or observe the actions of people to understand those places or institutions. Or not! In the case of content analyses (see chapter 17), you won’t even have people involved at all but rather documents or films or photographs or news clippings. Everything we have covered about sampling applies to other units of analysis too. Let’s work through some examples.

Case Studies

When constructing a case study, it is helpful to think of your cases as sample populations in the same way that we considered people above. If, for example, you are comparing campus climates for diversity, your overall population may be “four-year college campuses in the US,” and from there you might decide to study three college campuses as your sample. Which three? Will you use purposeful sampling (perhaps [1] selecting three colleges in Oregon that are different sizes or [2] selecting three colleges across the US located in different political cultures or [3] varying the three colleges by racial makeup of the student body)? Or will you select three colleges at random, out of convenience? There are justifiable reasons for all approaches.

As with people, there are different ways of maximizing insight in your sample selection. Think about the following rationales: typical, diverse, extreme, deviant, influential, crucial, or even embodying a particular “pathway” ( Gerring 2008 ). When choosing a case or particular research site, Rubin ( 2021 ) suggests you bear in mind, first, what you are leaving out by selecting this particular case/site; second, what you might be overemphasizing by studying this case/site and not another; and, finally, whether you truly need to worry about either of those things—“that is, what are the sources of bias and how bad are they for what you are trying to do?” ( 89 ).

Once you have selected your cases, you may still want to include interviews with specific people or observations at particular sites within those cases. Then you go through possible sampling approaches all over again to determine which people will be contacted.

Content: Documents, Narrative Accounts, And So On

Although not often discussed as sampling, your selection of documents and other units to use in various content/historical analyses is subject to similar considerations. When you are asking quantitative-type questions (percentages and proportionalities of a general population), you will want to follow probabilistic sampling. For example, I created a random sample of accounts posted on the website studentloanjustice.org to delineate the types of problems people were having with student debt ( Hurst 2007 ). Even though my data was qualitative (narratives of student debt), I was actually asking a quantitative-type research question, so it was important that my sample was representative of the larger population (debtors who posted on the website). On the other hand, when you are asking qualitative-type questions, the selection process should be very different. In that case, use nonprobabilistic techniques, either convenience (where you are really new to this data and do not have the ability to set comparative criteria or even know what a deviant case would be) or some variant of purposive sampling. Let’s say you were interested in the visual representation of women in media published in the 1950s. You could select a national magazine like Time for a “typical” representation (and for its convenience, as all issues are freely available on the web and easy to search). Or you could compare one magazine known for its feminist content versus one antifeminist. The point is, sample selection is important even when you are not interviewing or observing people.

Goals of Qualitative Sampling versus Goals of Quantitative Sampling

We have already discussed some of the differences in the goals of quantitative and qualitative sampling above, but it is worth further discussion. The quantitative researcher seeks a sample that is representative of the population of interest so that they may properly generalize the results (e.g., if 80 percent of first-gen students in the sample were concerned with costs of college, then we can say there is a strong likelihood that 80 percent of first-gen students nationally are concerned with costs of college). The qualitative researcher does not seek to generalize in this way . They may want a representative sample because they are interested in typical responses or behaviors of the population of interest, but they may very well not want a representative sample at all. They might want an “extreme” or deviant case to highlight what could go wrong with a particular situation, or maybe they want to examine just one case as a way of understanding what elements might be of interest in further research. When thinking of your sample, you will have to know why you are selecting the units, and this relates back to your research question or sets of questions. It has nothing to do with having a representative sample to generalize results. You may be tempted—or it may be suggested to you by a quantitatively minded member of your committee—to create as large and representative a sample as you possibly can to earn credibility from quantitative researchers. Ignore this temptation or suggestion. The only thing you should be considering is what sample will best bring insight into the questions guiding your research. This has implications for the number of people (or units) in your study as well, which is the topic of the next section.

What is the Correct “Number” to Sample?

Because we are not trying to create a generalizable representative sample, the guidelines for the “number” of people to interview or news stories to code are also a bit more nebulous. There are some brilliant insightful studies out there with an n of 1 (meaning one person or one account used as the entire set of data). This is particularly so in the case of autoethnography, a variation of ethnographic research that uses the researcher’s own subject position and experiences as the basis of data collection and analysis. But it is true for all forms of qualitative research. There are no hard-and-fast rules here. The number to include is what is relevant and insightful to your particular study.

That said, humans do not thrive well under such ambiguity, and there are a few helpful suggestions that can be made. First, many qualitative researchers talk about “saturation” as the end point for data collection. You stop adding participants when you are no longer getting any new information (or so very little that the cost of adding another interview subject or spending another day in the field exceeds any likely benefits to the research). The term saturation was first used here by Glaser and Strauss ( 1967 ), the founders of Grounded Theory. Here is their explanation: “The criterion for judging when to stop sampling the different groups pertinent to a category is the category’s theoretical saturation . Saturation means that no additional data are being found whereby the sociologist can develop properties of the category. As he [or she] sees similar instances over and over again, the researcher becomes empirically confident that a category is saturated. [They go] out of [their] way to look for groups that stretch diversity of data as far as possible, just to make certain that saturation is based on the widest possible range of data on the category” ( 61 ).

It makes sense that the term was developed by grounded theorists, since this approach is rather more open-ended than other approaches used by qualitative researchers. With so much left open, having a guideline of “stop collecting data when you don’t find anything new” is reasonable. However, saturation can’t help much when first setting out your sample. How do you know how many people to contact to interview? What number will you put down in your institutional review board (IRB) protocol (see chapter 8)? You may guess how many people or units it will take to reach saturation, but there really is no way to know in advance. The best you can do is think about your population and your questions and look at what others have done with similar populations and questions.

Here are some suggestions to use as a starting point: For phenomenological studies, try to interview at least ten people for each major category or group of people . If you are comparing male-identified, female-identified, and gender-neutral college students in a study on gender regimes in social clubs, that means you might want to design a sample of thirty students, ten from each group. This is the minimum suggested number. Damaske’s ( 2021 ) sample of one hundred allows room for up to twenty-five participants in each of four “buckets” (e.g., working-class*female, working-class*male, middle-class*female, middle-class*male). If there is more than one comparative group (e.g., you are comparing students attending three different colleges, and you are comparing White and Black students in each), you can sometimes reduce the number for each group in your sample to five for, in this case, thirty total students. But that is really a bare minimum you will want to go. A lot of people will not trust you with only “five” cases in a bucket. Lareau ( 2021:24 ) advises a minimum of seven or nine for each bucket (or “cell,” in her words). The point is to think about what your analyses might look like and how comfortable you will be with a certain number of persons fitting each category.

Because qualitative research takes so much time and effort, it is rare for a beginning researcher to include more than thirty to fifty people or units in the study. You may not be able to conduct all the comparisons you might want simply because you cannot manage a larger sample. In that case, the limits of who you can reach or what you can include may influence you to rethink an original overcomplicated research design. Rather than include students from every racial group on a campus, for example, you might want to sample strategically, thinking about the most contrast (insightful), possibly excluding majority-race (White) students entirely, and simply using previous literature to fill in gaps in our understanding. For example, one of my former students was interested in discovering how race and class worked at a predominantly White institution (PWI). Due to time constraints, she simplified her study from an original sample frame of middle-class and working-class domestic Black and international African students (four buckets) to a sample frame of domestic Black and international African students (two buckets), allowing the complexities of class to come through individual accounts rather than from part of the sample frame. She wisely decided not to include White students in the sample, as her focus was on how minoritized students navigated the PWI. She was able to successfully complete her project and develop insights from the data with fewer than twenty interviewees. [1]

But what if you had unlimited time and resources? Would it always be better to interview more people or include more accounts, documents, and units of analysis? No! Your sample size should reflect your research question and the goals you have set yourself. Larger numbers can sometimes work against your goals. If, for example, you want to help bring out individual stories of success against the odds, adding more people to the analysis can end up drowning out those individual stories. Sometimes, the perfect size really is one (or three, or five). It really depends on what you are trying to discover and achieve in your study. Furthermore, studies of one hundred or more (people, documents, accounts, etc.) can sometimes be mistaken for quantitative research. Inevitably, the large sample size will push the researcher into simplifying the data numerically. And readers will begin to expect generalizability from such a large sample.

To summarize, “There are no rules for sample size in qualitative inquiry. Sample size depends on what you want to know, the purpose of the inquiry, what’s at stake, what will be useful, what will have credibility, and what can be done with available time and resources” ( Patton 2002:244 ).

How did you find/construct a sample?

Since qualitative researchers work with comparatively small sample sizes, getting your sample right is rather important. Yet it is also difficult to accomplish. For instance, a key question you need to ask yourself is whether you want a homogeneous or heterogeneous sample. In other words, do you want to include people in your study who are by and large the same, or do you want to have diversity in your sample?

For many years, I have studied the experiences of students who were the first in their families to attend university. There is a rather large number of sampling decisions I need to consider before starting the study. (1) Should I only talk to first-in-family students, or should I have a comparison group of students who are not first-in-family? (2) Do I need to strive for a gender distribution that matches undergraduate enrollment patterns? (3) Should I include participants that reflect diversity in gender identity and sexuality? (4) How about racial diversity? First-in-family status is strongly related to some ethnic or racial identity. (5) And how about areas of study?

As you can see, if I wanted to accommodate all these differences and get enough study participants in each category, I would quickly end up with a sample size of hundreds, which is not feasible in most qualitative research. In the end, for me, the most important decision was to maximize the voices of first-in-family students, which meant that I only included them in my sample. As for the other categories, I figured it was going to be hard enough to find first-in-family students, so I started recruiting with an open mind and an understanding that I may have to accept a lack of gender, sexuality, or racial diversity and then not be able to say anything about these issues. But I would definitely be able to speak about the experiences of being first-in-family.

—Wolfgang Lehmann, author of “Habitus Transformation and Hidden Injuries”

Examples of “Sample” Sections in Journal Articles

Think about some of the studies you have read in college, especially those with rich stories and accounts about people’s lives. Do you know how the people were selected to be the focus of those stories? If the account was published by an academic press (e.g., University of California Press or Princeton University Press) or in an academic journal, chances are that the author included a description of their sample selection. You can usually find these in a methodological appendix (book) or a section on “research methods” (article).

Here are two examples from recent books and one example from a recent article:

Example 1 . In It’s Not like I’m Poor: How Working Families Make Ends Meet in a Post-welfare World , the research team employed a mixed methods approach to understand how parents use the earned income tax credit, a refundable tax credit designed to provide relief for low- to moderate-income working people ( Halpern-Meekin et al. 2015 ). At the end of their book, their first appendix is “Introduction to Boston and the Research Project.” After describing the context of the study, they include the following description of their sample selection:

In June 2007, we drew 120 names at random from the roughly 332 surveys we gathered between February and April. Within each racial and ethnic group, we aimed for one-third married couples with children and two-thirds unmarried parents. We sent each of these families a letter informing them of the opportunity to participate in the in-depth portion of our study and then began calling the home and cell phone numbers they provided us on the surveys and knocking on the doors of the addresses they provided.…In the end, we interviewed 115 of the 120 families originally selected for the in-depth interview sample (the remaining five families declined to participate). ( 22 )

Was their sample selection based on convenience or purpose? Why do you think it was important for them to tell you that five families declined to be interviewed? There is actually a trick here, as the names were pulled randomly from a survey whose sample design was probabilistic. Why is this important to know? What can we say about the representativeness or the uniqueness of whatever findings are reported here?

Example 2 . In When Diversity Drops , Park ( 2013 ) examines the impact of decreasing campus diversity on the lives of college students. She does this through a case study of one student club, the InterVarsity Christian Fellowship (IVCF), at one university (“California University,” a pseudonym). Here is her description:

I supplemented participant observation with individual in-depth interviews with sixty IVCF associates, including thirty-four current students, eight former and current staff members, eleven alumni, and seven regional or national staff members. The racial/ethnic breakdown was twenty-five Asian Americans (41.6 percent), one Armenian (1.6 percent), twelve people who were black (20.0 percent), eight Latino/as (13.3 percent), three South Asian Americans (5.0 percent), and eleven people who were white (18.3 percent). Twenty-nine were men, and thirty-one were women. Looking back, I note that the higher number of Asian Americans reflected both the group’s racial/ethnic composition and my relative ease about approaching them for interviews. ( 156 )

How can you tell this is a convenience sample? What else do you note about the sample selection from this description?

Example 3. The last example is taken from an article published in the journal Research in Higher Education . Published articles tend to be more formal than books, at least when it comes to the presentation of qualitative research. In this article, Lawson ( 2021 ) is seeking to understand why female-identified college students drop out of majors that are dominated by male-identified students (e.g., engineering, computer science, music theory). Here is the entire relevant section of the article:

Method Participants Data were collected as part of a larger study designed to better understand the daily experiences of women in MDMs [male-dominated majors].…Participants included 120 students from a midsize, Midwestern University. This sample included 40 women and 40 men from MDMs—defined as any major where at least 2/3 of students are men at both the university and nationally—and 40 women from GNMs—defined as any may where 40–60% of students are women at both the university and nationally.… Procedure A multi-faceted approach was used to recruit participants; participants were sent targeted emails (obtained based on participants’ reported gender and major listings), campus-wide emails sent through the University’s Communication Center, flyers, and in-class presentations. Recruitment materials stated that the research focused on the daily experiences of college students, including classroom experiences, stressors, positive experiences, departmental contexts, and career aspirations. Interested participants were directed to email the study coordinator to verify eligibility (at least 18 years old, man/woman in MDM or woman in GNM, access to a smartphone). Sixteen interested individuals were not eligible for the study due to the gender/major combination. ( 482ff .)

What method of sample selection was used by Lawson? Why is it important to define “MDM” at the outset? How does this definition relate to sampling? Why were interested participants directed to the study coordinator to verify eligibility?

Final Words

I have found that students often find it difficult to be specific enough when defining and choosing their sample. It might help to think about your sample design and sample recruitment like a cookbook. You want all the details there so that someone else can pick up your study and conduct it as you intended. That person could be yourself, but this analogy might work better if you have someone else in mind. When I am writing down recipes, I often think of my sister and try to convey the details she would need to duplicate the dish. We share a grandmother whose recipes are full of handwritten notes in the margins, in spidery ink, that tell us what bowl to use when or where things could go wrong. Describe your sample clearly, convey the steps required accurately, and then add any other details that will help keep you on track and remind you why you have chosen to limit possible interviewees to those of a certain age or class or location. Imagine actually going out and getting your sample (making your dish). Do you have all the necessary details to get started?

Table 5.1. Sampling Type and Strategies

Further Readings

Fusch, Patricia I., and Lawrence R. Ness. 2015. “Are We There Yet? Data Saturation in Qualitative Research.” Qualitative Report 20(9):1408–1416.

Saunders, Benjamin, Julius Sim, Tom Kinstone, Shula Baker, Jackie Waterfield, Bernadette Bartlam, Heather Burroughs, and Clare Jinks. 2018. “Saturation in Qualitative Research: Exploring Its Conceptualization and Operationalization.”  Quality & Quantity  52(4):1893–1907.

• Rubin ( 2021 ) suggests a minimum of twenty interviews (but safer with thirty) for an interview-based study and a minimum of three to six months in the field for ethnographic studies. For a content-based study, she suggests between five hundred and one thousand documents, although some will be “very small” ( 243–244 ). ↵

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

The actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).  Sampling frames can differ from the larger population when specific exclusions are inherent, as in the case of pulling names randomly from voter registration rolls where not everyone is a registered voter.  This difference in frame and population can undercut the generalizability of quantitative results.

The specific group of individuals that you will collect data from.  Contrast population.

The large group of interest to the researcher.  Although it will likely be impossible to design a study that incorporates or reaches all members of the population of interest, this should be clearly defined at the outset of a study so that a reasonable sample of the population can be taken.  For example, if one is studying working-class college students, the sample may include twenty such students attending a particular college, while the population is “working-class college students.”  In quantitative research, clearly defining the general population of interest is a necessary step in generalizing results from a sample.  In qualitative research, defining the population is conceptually important for clarity.

A sampling strategy in which the sample is chosen to represent (numerically) the larger population from which it is drawn by random selection.  Each person in the population has an equal chance of making it into the sample.  This is often done through a lottery or other chance mechanisms (e.g., a random selection of every twelfth name on an alphabetical list of voters).  Also known as random sampling .

The selection of research participants or other data sources based on availability or accessibility, in contrast to purposive sampling .

A sample generated non-randomly by asking participants to help recruit more participants the idea being that a person who fits your sampling criteria probably knows other people with similar criteria.

Broad codes that are assigned to the main issues emerging in the data; identifying themes is often part of initial coding . 

A form of case selection focusing on examples that do not fit the emerging patterns. This allows the researcher to evaluate rival explanations or to define the limitations of their research findings. While disconfirming cases are found (not sought out), researchers should expand their analysis or rethink their theories to include/explain them.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

The result of probability sampling, in which a sample is chosen to represent (numerically) the larger population from which it is drawn by random selection.  Each person in the population has an equal chance of making it into the random sample.  This is often done through a lottery or other chance mechanisms (e.g., the random selection of every twelfth name on an alphabetical list of voters).  This is typically not required in qualitative research but rather essential for the generalizability of quantitative research.

A form of case selection or purposeful sampling in which cases that are unusual or special in some way are chosen to highlight processes or to illuminate gaps in our knowledge of a phenomenon.   See also extreme case .

The point at which you can conclude data collection because every person you are interviewing, the interaction you are observing, or content you are analyzing merely confirms what you have already noted.  Achieving saturation is often used as the justification for the final sample size.

The accuracy with which results or findings can be transferred to situations or people other than those originally studied.  Qualitative studies generally are unable to use (and are uninterested in) statistical generalizability where the sample population is said to be able to predict or stand in for a larger population of interest.  Instead, qualitative researchers often discuss “theoretical generalizability,” in which the findings of a particular study can shed light on processes and mechanisms that may be at play in other settings.  See also statistical generalization and theoretical generalization .

A term used by IRBs to denote all materials aimed at recruiting participants into a research study (including printed advertisements, scripts, audio or video tapes, or websites).  Copies of this material are required in research protocols submitted to IRB.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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Qualitative Research Methods: Types, Analysis + Examples

Qualitative research is based on the disciplines of social sciences like psychology, sociology, and anthropology. Therefore, the qualitative research methods allow for in-depth and further probing and questioning of respondents based on their responses. The interviewer/researcher also tries to understand their motivation and feelings. Understanding how your audience makes decisions can help derive conclusions in market research.

What is qualitative research?

Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication .

This method is about “what” people think and “why” they think so. For example, consider a convenience store looking to improve its patronage. A systematic observation concludes that more men are visiting this store. One good method to determine why women were not visiting the store is conducting an in-depth interview method with potential customers.

For example, after successfully interviewing female customers and visiting nearby stores and malls, the researchers selected participants through random sampling . As a result, it was discovered that the store didn’t have enough items for women.

So fewer women were visiting the store, which was understood only by personally interacting with them and understanding why they didn’t visit the store because there were more male products than female ones.

Gather research insights

Types of qualitative research methods with examples

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience with reference to a particular topic. There are different types of qualitative research methods, such as in-depth interviews, focus groups, ethnographic research, content analysis, and case study research that are usually used.

The results of qualitative methods are more descriptive, and the inferences can be drawn quite easily from the obtained data .

Qualitative research methods originated in the social and behavioral research sciences. Today, our world is more complicated, and it is difficult to understand what people think and perceive. Online research methods make it easier to understand that as it is a more communicative and descriptive analysis .

The following are the qualitative research methods that are frequently used. Also, read about qualitative research examples :

1. One-on-one interview

Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time. This is purely a conversational method and invites opportunities to get details in depth from the respondent.

One of the advantages of this method is that it provides a great opportunity to gather precise data about what people believe and their motivations . If the researcher is well experienced, asking the right questions can help him/her collect meaningful data. If they should need more information, the researchers should ask such follow-up questions that will help them collect more information.

These interviews can be performed face-to-face or on the phone and usually can last between half an hour to two hours or even more. When the in-depth interview is conducted face to face, it gives a better opportunity to read the respondents’ body language and match the responses.

2. Focus groups

A focus group is also a commonly used qualitative research method used in data collection. A focus group usually includes a limited number of respondents (6-10) from within your target market.

The main aim of the focus group is to find answers to the “why, ” “what,” and “how” questions. One advantage of focus groups is you don’t necessarily need to interact with the group in person. Nowadays, focus groups can be sent an online survey on various devices, and responses can be collected at the click of a button.

Focus groups are an expensive method as compared to other online qualitative research methods. Typically, they are used to explain complex processes. This method is very useful for market research on new products and testing new concepts.

3. Ethnographic research

Ethnographic research is the most in-depth observational research method that studies people in their naturally occurring environment.

This method requires the researchers to adapt to the target audiences’ environments, which could be anywhere from an organization to a city or any remote location. Here, geographical constraints can be an issue while collecting data.

This research design aims to understand the cultures, challenges, motivations, and settings that occur. Instead of relying on interviews and discussions, you experience the natural settings firsthand.

This type of research method can last from a few days to a few years, as it involves in-depth observation and collecting data on those grounds. It’s a challenging and time-consuming method and solely depends on the researcher’s expertise to analyze, observe, and infer the data.

4. Case study research

T he case study method has evolved over the past few years and developed into a valuable quality research method. As the name suggests, it is used for explaining an organization or an entity.

This type of research method is used within a number of areas like education, social sciences, and similar. This method may look difficult to operate; however , it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in new research. This is similar to going to a library. There, one can go over books and other reference material to collect relevant data that can likely be used in the research.

6. Process of observation

Qualitative Observation is a process of research that uses subjective methodologies to gather systematic information or data. Since the focus on qualitative observation is the research process of using subjective methodologies to gather information or data. Qualitative observation is primarily used to equate quality differences.

Qualitative observation deals with the 5 major sensory organs and their functioning – sight, smell, touch, taste, and hearing. This doesn’t involve measurements or numbers but instead characteristics.

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide us with detailed insight. For reaching such conclusions the data that is collected should be holistic, rich, and nuanced and findings to emerge through careful analysis.

• Whatever method a researcher chooses for collecting qualitative data, one aspect is very clear the process will generate a large amount of data. In addition to the variety of methods available, there are also different methods of collecting and recording the data.

For example, if the qualitative data is collected through a focus group or one-to-one discussion, there will be handwritten notes or video recorded tapes. If there are recording they should be transcribed and before the process of data analysis can begin.

• As a rough guide, it can take a seasoned researcher 8-10 hours to transcribe the recordings of an interview, which can generate roughly 20-30 pages of dialogues. Many researchers also like to maintain separate folders to maintain the recording collected from the different focus group. This helps them compartmentalize the data collected.
• In case there are running notes taken, which are also known as field notes, they are helpful in maintaining comments, environmental contexts, environmental analysis , nonverbal cues etc. These filed notes are helpful and can be compared while transcribing audio recorded data. Such notes are usually informal but should be secured in a similar manner as the video recordings or the audio tapes.

B. Qualitative data analysis

Qualitative data analysis such as notes, videos, audio recordings images, and text documents. One of the most used methods for qualitative data analysis is text analysis.

Text analysis is a  data analysis method that is distinctly different from all other qualitative research methods, where researchers analyze the social life of the participants in the research study and decode the words, actions, etc. 

There are images also that are used in this research study and the researchers analyze the context in which the images are used and draw inferences from them. In the last decade, text analysis through what is shared on social media platforms has gained supreme popularity.

Characteristics of qualitative research methods

• Qualitative research methods usually collect data at the sight, where the participants are experiencing issues or research problems . These are real-time data and rarely bring the participants out of the geographic locations to collect information.
• Qualitative researchers typically gather multiple forms of data, such as interviews, observations, and documents, rather than rely on a single data source .
• This type of research method works towards solving complex issues by breaking down into meaningful inferences, that is easily readable and understood by all.
• Since it’s a more communicative method, people can build their trust on the researcher and the information thus obtained is raw and unadulterated.

Qualitative research method case study

Let’s take the example of a bookstore owner who is looking for ways to improve their sales and customer outreach. An online community of members who were loyal patrons of the bookstore were interviewed and related questions were asked and the questions were answered by them.

At the end of the interview, it was realized that most of the books in the stores were suitable for adults and there were not enough options for children or teenagers.

By conducting this qualitative research the bookstore owner realized what the shortcomings were and what were the feelings of the readers. Through this research now the bookstore owner can now keep books for different age categories and can improve his sales and customer outreach.

Such qualitative research method examples can serve as the basis to indulge in further quantitative research , which provides remedies.

When to use qualitative research

Researchers make use of qualitative research techniques when they need to capture accurate, in-depth insights. It is very useful to capture “factual data”. Here are some examples of when to use qualitative research.

• Developing a new product or generating an idea.
• Studying your product/brand or service to strengthen your marketing strategy.
• To understand your strengths and weaknesses.
• Understanding purchase behavior.
• To study the reactions of your audience to marketing campaigns and other communications.
• Exploring market demographics, segments, and customer care groups.
• Gathering perception data of a brand, company, or product.

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

The basic differences between qualitative research methods and quantitative research methods are simple and straightforward. They differ in:

• Their analytical objectives
• Types of questions asked
• Types of data collection instruments
• Forms of data they produce
• Degree of flexibility

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An Introduction to Qualitative Research

Student resources, part 1 (chapters 1 – 5): foundations of qualitative research.

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• Knowledge Base
• Methodology
• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organisation?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

Prevent plagiarism, run a free check.

Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalisability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .

• Labour-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organisation to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organise your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Pritha Bhandari

Qualitative Research: An Overview

• First Online: 24 April 2019

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• Liang Shang 4  

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Qualitative research is one of the most commonly used types of research and methodology in the social sciences. Unfortunately, qualitative research is commonly misunderstood. In this chapter, we describe and explain the misconceptions surrounding qualitative research enterprise, why researchers need to care about when using qualitative research, the characteristics of qualitative research, and review the paradigms in qualitative research.

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Qualitative research is defined as the practice used to study things –– individuals and organizations and their reasons, opinions, and motivations, beliefs in their natural settings. It involves an observer (a researcher) who is located in the field , who transforms the world into a series of representations such as fieldnotes, interviews, conversations, photographs, recordings and memos (Denzin and Lincoln 2011 ). Many researchers employ qualitative research for exploratory purpose while others use it for ‘quasi’ theory testing approach. Qualitative research is a broad umbrella of research methodologies that encompasses grounded theory (Glaser and Strauss 2017 ; Strauss and Corbin 1990 ), case study (Flyvbjerg 2006 ; Yin 2003 ), phenomenology (Sanders 1982 ), discourse analysis (Fairclough 2003 ; Wodak and Meyer 2009 ), ethnography (Geertz 1973 ; Garfinkel 1967 ), and netnography (Kozinets 2002 ), among others. Qualitative research is often synonymous with ‘case study research’ because ‘case study’ primarily uses (but not always) qualitative data.

The quality standards or evaluation criteria of qualitative research comprises: (1) credibility (that a researcher can provide confidence in his/her findings), (2) transferability (that results are more plausible when transported to a highly similar contexts), (3) dependability (that errors have been minimized, proper documentation is provided), and (4) confirmability (that conclusions are internally consistent and supported by data) (see Lincoln and Guba 1985 ).

We classify research into a continuum of theory building — >   theory elaboration — >   theory testing . Theory building is also known as theory exploration. Theory elaboration refers to the use of qualitative data and a method to seek “confirmation” of the relationships among variables or processes or mechanisms of a social reality (Bartunek and Rynes 2015 ).

In the context of qualitative research, theory/ies usually refer(s) to conceptual model(s) or framework(s) that explain the relationships among a set of variables or processes that explain a social phenomenon. Theory or theories could also refer to general ideas or frameworks (e.g., institutional theory, emancipation theory, or identity theory) that are reviewed as background knowledge prior to the commencement of a qualitative research project.

For example, a qualitative research can ask the following question: “How can institutional change succeed in social contexts that are dominated by organized crime?” (Vaccaro and Palazzo 2015 ).

We have witnessed numerous cases in which committed positivist methodologists were asked to review qualitative papers, and they used a survey approach to assess the quality of an interpretivist work. This reviewers’ fallacy is dangerous and hampers the progress of a field of research. Editors must be cognizant of such fallacy and avoid it.

A social enterprises (SE) is an organization that combines social welfare and commercial logics (Doherty et al. 2014 ), or that uses business principles to address social problems (Mair and Marti 2006 ); thus, qualitative research that reports that ‘social impact’ is important for SEs is too descriptive and, arguably, tautological. It is not uncommon to see authors submitting purely descriptive papers to scholarly journals.

Some qualitative researchers have conducted qualitative work using primarily a checklist (ticking the boxes) to show the presence or absence of variables, as if it were a survey-based study. This is utterly inappropriate for a qualitative work. A qualitative work needs to show the richness and depth of qualitative findings. Nevertheless, it is acceptable to use such checklists as supplementary data if a study involves too many informants or variables of interest, or the data is too complex due to its longitudinal nature (e.g., a study that involves 15 cases observed and involving 59 interviews with 33 informants within a 7-year fieldwork used an excel sheet to tabulate the number of events that occurred as supplementary data to the main analysis; see Chandra 2017a , b ).

As mentioned earlier, there are different types of qualitative research. Thus, a qualitative researcher will customize the data collection process to fit the type of research being conducted. For example, for researchers using ethnography, the primary data will be in the form of photos and/or videos and interviews; for those using netnography, the primary data will be internet-based textual data. Interview data is perhaps the most common type of data used across all types of qualitative research designs and is often synonymous with qualitative research.

The purpose of qualitative research is to provide an explanation , not merely a description and certainly not a prediction (which is the realm of quantitative research). However, description is needed to illustrate qualitative data collected, and usually researchers describe their qualitative data by inserting a number of important “informant quotes” in the body of a qualitative research report.

We advise qualitative researchers to adhere to one approach to avoid any epistemological and ontological mismatch that may arise among different camps in qualitative research. For instance, mixing a positivist with a constructivist approach in qualitative research frequently leads to unnecessary criticism and even rejection from journal editors and reviewers; it shows a lack of methodological competence or awareness of one’s epistemological position.

Analytical generalization is not generalization to some defined population that has been sampled, but to a “theory” of the phenomenon being studied, a theory that may have much wider applicability than the particular case studied (Yin 2003 ).

There are different types of contributions. Typically, a researcher is expected to clearly articulate the theoretical contributions for a qualitative work submitted to a scholarly journal. Other types of contributions are practical (or managerial ), common for business/management journals, and policy , common for policy related journals.

There is ongoing debate on whether a template for qualitative research is desirable or necessary, with one camp of scholars (the pluralistic critical realists) that advocates a pluralistic approaches to qualitative research (“qualitative research should not follow a particular template or be prescriptive in its process”) and the other camps are advocating for some form of consensus via the use of particular approaches (e.g., the Eisenhardt or Gioia Approach, etc.). However, as shown in Table 1.1 , even the pluralistic critical realism in itself is a template and advocates an alternative form of consensus through the use of diverse and pluralistic approaches in doing qualitative research.

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Chandra, Y., Shang, L. (2019). Qualitative Research: An Overview. In: Qualitative Research Using R: A Systematic Approach. Springer, Singapore. https://doi.org/10.1007/978-981-13-3170-1_1

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Barriers to equitable healthcare services for under-five children in Ethiopia: a qualitative exploratory study

• Hailu Fekadu 1 ,
• Wubegzier Mekonnen 2 ,
• Aynalem Adugna 3 ,
• Helmut Kloos 4 &
• Damen Hailemariam 2  

BMC Health Services Research volume  24 , Article number:  613 ( 2024 ) Cite this article

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Disparities in child healthcare service utilization are unacceptably high in Ethiopia. Nevertheless, little is known about underlying barriers to accessing child health services, especially among low socioeconomic subgroups and in remote areas. This study aims to identify barriers to equity in the use of child healthcare services in Ethiopia.

Data were obtained from 20 key- informant interviews (KII) and 6 focus group discussions (FGD) with mothers and care givers. This study was conducted in Oromia Region, Arsi Zone, Zuway Dugda District from June 1–30, 2023. The study participants for this research were selected purposively. The information was collected based on the principle of saturation after sixteen consecutives interview were conducted. Both KII and FGD were audio-recorded and complementary notes were taken to record observations about the participants’ comments and their interactions. Each interview and FGD data were transcribed word-for-word in the local Afaan Oromo and Amaharic languages and then translated to English language. Finally, the data were analyzed thematically using NVivo 14 software and narrated in the linked pattern of child health service utilization.

This study identified six major themes which emerged as barriers to healthcare utilization equity for caregivers and their -under-five children. Barriers related to equity in low level of awareness regarding need, low socioeconomic status, geographical inaccessibility, barriers related to deficient healthcare system, community perception and cultural restrictions, and barriers of equity related to political instability and conflict . The most commonly recognized barriers of equity at the community level were political instability, conflict, and a tremendous distance to a health facility. Transportation challenges, poor functional services, closure of the health facility in working hours, and lack of proper planning to address the marginalized populations were identified barriers of equity at organizational or policy level.

This study showed that inequity in child healthcare utilization is an important challenge confronting Ethiopia. To achieve equity, policy makers and planners need to change health policy and structure to be pro-poor. It is also necessary to improve the healthcare system to increase service utilization and access for impoverished women, individuals with lower levels of education, and residents of isolated rural areas. Furthermore, context specific information pertaining to cultural barriers and political ecology are required.

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Over the last few decades, the issue of equitable distribution and utilization of healthcare services has captured the attention of scholars, governments, and policy makers. While some countries have made much improvement in this regard, others have lagged behind. Child healthcare service use is no exception, and it has recently become a global concern [ 1 ].

Equity in health and health service utilization is a focus in the global health discourse as one of the cornerstones of primary health care (PHC) [ 2 ]. The United Nations has set a goal to reduce global neonatal deaths from 25 per 1,000 live births to 12 per 1,000 by the year 2030 [ 3 ]. Achieving this target will require strong commitment from both service providers as well as financiers of the health sector, including government and community leaders [ 3 ]. Among the World Health Organization’s main focus areas for under-five health, is the reduction of inequities in accordance with the universal health coverage principles. This includes addressing the health needs of children in poor and remote communities. Many countries have implemented various programs aimed at minimizing unnecessary disparities in health service utilization [ 4 ]. Community based health services in particular have been found to be effective in minimizing inequities in health status and health service utilization [ 4 ]. For instance, the Ethiopian government is committed to improve equity through the health extension program and other initiatives [ 5 ]. Moreover, Ethiopia included the equity objective in its health sector transformation plan [ 6 ]. Nevertheless, inequities in service coverage and difference in maternal and child health outcomes remain a challenge [ 7 , 8 ]. The coverage of child health services and basic child immunizations has favored wealthier, more educated, and urban populations. [ 9 ]. For instance, despite significant decline is observed in under five mortality from 123 per 1,000 live births in 2005 to 59 in 2019, still there exists a disparity between different population groups [ 9 ].

Ethiopia met the MDGS for child mortality rate (CMR) in 2013 [ 10 ]. However, the gains made between 1990 and 2013 were not uniformly distributed among Ethiopians; inequity indicators of mortality by wealth had not significantly decreased. During this 23-year period, the mortality among the poorest was unchanged. Even though child health services are supposed to be provided free of charge at public facilities, the disparity in access to or utilization of the services is high in Ethiopia. Like mortality disparity, there is a considerable disparity in coverage of life-saving interventions by wealth status and place of residence [ 11 ].

Addressing equity is a significant challenge in healthcare delivery in Ethiopia. The barriers that were reported to be significantly associated with service utilization included geographical access as a function of distance; financial barriers; and socio-cultural factors such as language, cultural norms, health beliefs and perceptions, maternal education and decision making power and lack of knowledge and awareness, which in the aggregate can lead to low demand for and use of services, particularly by the poor [ 12 , 13 ]. Long distances and extended travel times remain key barriers to access health facilities in many rural communities in Ethiopia [ 11 , 14 ]. For instance, in Indonesia proximity to healthcare facilities significantly decreases child mortality [ 15 ]. Furthermore, according to a study from Uganda, Nigeria and Ethiopia long distances to health care facilities cause delays seeking care [ 16 , 17 , 18 ]. Even where health care services are available, the cost of seeking care may delay or prevent poor households from accessing them. This problem is particularly discriminating in rural areas where the density of modern health care facilities is low and in settings where transportation systems and road infrastructures are poor [ 18 ]. Furthermore, over the last five years, Ethiopia has faced internal conflict and political instability which exacerbated inequity in the utilization of child health services among the poor and in rural communities. Both insecurity and scarce resources are critical issues in child healthcare accessibility for women living in conflict zones and socioeconomically unstable settings [ 19 ].

Political instability disrupts electricity, water, and food supplies, destabilizes social and welfare systems, including the health and transportation systems, and increases unemployment, homelessness, and poverty—all of which have a negative impact on the use of maternal and child health services [ 20 ]. Hence, these issues did not addressed in any of the studies done so far.

Thus, while many studies have been conducted on the utilization of healthcare services, there is insufficient comprehensive evidence on the barriers of equity in accessing and in utilization of healthcare services for under-five children from policy makers and community level perspective. Therefore, the objective of this study is to examine the context of specific barriers to achieving equity in child health-care services utilization in Ethiopia.

Inequity in child health care service is a major public health problem in developing countries, including Ethiopia. Accordingly, the study explored barriers to equitable healthcare services for under-five children, their health seeking behavior, geographical variation, their awareness, perceptions, attitude and political impact and policy contents of the country. The findings will benefit program leaders, policy makers on health inequality reduction and serve as an input to policy documents related to the new health sector strategic plan. Moreover, mothers and under-five children’s are directly benefited from the finding. Conceptual framework shows how different barriers affect equity in utilization of child health services (Fig.  1 ).

Modified Andersen and WHO conceptual framework, on social determinants of health inequity

The study setting and approach

This study was conducted in Oromia Region, Arsi Zone, Zuway Dugda District from June 1–30, 2023. The Ethiopian healthcare system is three-tiered, comprising primary, secondary, and tertiary care [Fig.  2 ]. The primary level healthcare system is responsible for providing child health services, such as immunizations, and the treatment of sick children. The primary care unit includes primary hospitals, health centers, and health posts which are responsible for providing services to rural communities ([ 17 ]; Arsi Zone Health Department report, Unpublished data, 2022). Women's development armies (WDAs) provide support to health extension workers (HEWs) by organizing and connecting women and their children with healthcare facilities. Based on 2022, the Arsi Zone report, Zuway Dugda district was low in utilization of child healthcare services and the population is low in socioeconomic status and mostly depends on the Safety Net program for nutritional and financial needs (Arsi Zone Health Department report, Unpublished data, 2022). The goal of the Safety Net program is to preserve family assets while generating new ones for the community. To achieve this, the program offers food or cash incentives in exchange for public works projects that improve the environment or create local infrastructure, like roads (e.g. terracing).

Ethiopian health care system [ 17 ]

Participant selection

The study includes 20 in-depth interviews of key informants (KII) and six focus group discussions (FGD). By taking into account various factors that contribute to variations in the use of child healthcare services, study participants were selected from a variety of demographic subgroups. The study participants were drawn from different segments of the population by considering different dimensions that explain disparities in utilization of child healthcare services. The selection of participants was based on their experience of child healthcare services as well as the information they possessed. For the purposes of this research, to ensure representativeness, and to understand the multifaceted levels of the study framework within society and how individuals and the environment interact within a social system, we used maximum variations sampling technique and we classified the participants into four groups. They were “mothers or caregivers who have under- five children”, “males who have under-five children”, “healthcare leaders at different levels” and “healthcare providers at different health facility”. The first group,, “women” refers to mothers who were gave birth prior to the study period and currently having under-five children. The second group were “males or husbands of the women who have under-five children”. The third groups, “healthcare leaders” like; heads of the health centers, district health office, expertise working on child health programs in district, Zonal, regional or national level. The fourth group, “health-care providers”, refers to health professionals, including doctors, health officers, nurses, midwives, and health extension workers working at different health facilities in Arsi Zone and having direct relation with child healthcare services.

Participants in the focus group discussions (FGDs) could be women and their partners who had under-five children at the time of the study. The participant mothers or caregivers were recruited by the HEWs and kebe le (neighborhood associations) leaders. They were identified on a purposive basis with the help of health extension workers and were contacted a few days before the planned FGD to explain the objectives of the study and request their participation. For the key informant interviews, the study participants were contacted by the principal investigator two weeks before the interviews. The information was collected based on the principle of saturation; for our case at least 16 interviewees were needed to reach information saturation principles. Then, data collection was terminated when no new information was generated.

An interview guide was prepared for both the key informant interviews (KII) and FGDs. First, the guides were prepared in English language and then translated into the local language [ 21 ]. Then, the guides were pre-tested and problems relating to the sequence of questions, conceptually similar questions, and sensitive wording were corrected. The data collectors for the KII and FGD were professionals with the background in health and health related fields with master and who are experienced in collecting qualitative data. Moreover, they are fluent in the local language and familiar with the culture of the local community. Key informant interviews were conducted at the office or at the health facility where the interviewee worked and FGDs were conducted in community halls or public rooms. Both key informant-interviews and focus group discussions were audio-recorded. Additionally, complementary observations and notes regarding the remarks made by the participants and their interactions were made.

Data analysis

The principal investigator and the moderator transcribed each interview and FGD word-for-word in the local Afaan Oromo and Amaharic languages and then translated the transcripts back into English. The translations were verified by listening to the recordings while re-reading the transcripts. The data were analyzed thematically using NVivo 12 software and narrated in the pattern linked to child health service utilization. Major themes representing the FGD participants and in-depth interviews are presented in the findings section, with illustrative quotes included to support the main findings.

Trustworthiness

In qualitative research, trustworthiness is determined by credibility, dependability, conformability and transferability. Establishing credibility involved the primary researcher spending a considerable amount of time at the study site to get a feel for the environment, receiving ongoing feedback from peers during peer debriefing, and applying negative case analysis. Dependability was demonstrated by providing an in-depth explanation of the techniques employed, keeping careful interview records, and recording the analytical procedure. All events that took place in the field, the researchers' personal reflections on the study, any phenomena that emerged during the investigation, and pertinent details of their personal histories were documented in order to verify that the interpretations of the findings were derived from the data and were not the product of their imagination. The investigators attempted to build rapport and trust with the informants by developing a long-term attachment because they were skeptical or doubtful if the information felt off. Triangulation of data sources was also employed. A thorough description that includes explaining each step of the research process was employed to aid in the transferability of research findings. At the end of each qualitative data collection session, the data collectors rephrased the collected information by summarizing major points and obtained approval from the participants for the corrected summary.

Characteristics of the study participants

A total of six focus group discussions (FGD)- three with mothers and three with fathers of under five children were conducted. And 20 key informant interview (KII) were held. The number of FGD participants ranged from 8 -12 in each groups. The majorities of women’s participating in FGDs were housewives and had at least one child under the age of 5 years in their care at the time of the FGD. The key informant interviews were conducted with leaders and policy makers at different levels of the health care system and a healthcare worker, including FMoH child health directors, Regional Health bureaus experts, Zonal Health office child health experts, woreda health office heads, Health center heads and health extension workers at health posts were involved. In all, 28 men and 30 women took part in the FGDs. In contrast, six HEW, three heads of health centers, one head of the district health office and with ten experts participated in the key informant interview. Each FGD took on average 42 min (38–52 min), while the key informant interviews took about 36 min (19 to 55 min) (Tables 1 and 2 ).

Barriers to equitable healthcare services for under-five children

Six major themes emerged from the findings.

These include; barriers related to low awareness, low socioeconomic status, geographical inaccessibility, barriers related to deficient healthcare system, cultural and behavioral constraints, and political instability and conflict, all of which lead to unmet healthcare needs such as delay in receiving appropriate care and inability to obtain healthcare services (Table  3 ).

Lack of awareness about benefits of the services

Lack of awareness and misconceptions were one of the top reasons raised by KII and FGD participants for not using healthcare services for under-five children especially in rural communities. Recognition of illness and the potential benefits of treatment are pre-requisites for health care demand. Communities who lived in remote areas and are undereducated tend to have little knowledge concerning health issues. Rural people have insufficient exposure to the media, attending low level of schooling to grasp and understand health related information. The key-informant interviewees and FGD discussants reported that because of low health literacy, rural community and the poor households have less access to health facilities to get treatment for childhood diseases, and for immunization services. One of the key informants mentioned that there are variation or differences among urban and rural rich and poor, literate and uneducated people in child health care service utilization.

“… . Children who visited our health center with malnutrition were from remote and far to reach areas and were brought to our health facility only after these cases were seriously complicated. So there is great variation among urban and rural, rich and poor, literate and illiterate communities in child health care service utilization in our district .” Male , KII, age 34years

One FGD discussant from women group added her experience and her awareness of immunization and availability of free service in health post in such ways;

“Yes, if I had been aware of the benefit of immunization and informed that they were given free of charge, I would have used these services for my sick child from health posts, not from traditional healers” Female FGD discussant, age 35 years, Seeking care from traditional healer

The health extension workers at health posts also approved the lack of awareness among mothers and caregivers on the availability of health service which jeopardizes health- seeking and utilization of health service for their under-five children. One worker said that.

“Most of the women’s and care givers did not know about the availability of treatment at the health post, especially for diarrhea and pneumonia. Those women’s who live near a health facility, are educated and young have more awareness about childhood illnesses and seek care from health posts than uneducated mothers; this may result in inequitable utilization of health services by illiterate care givers ” KII, Female 35 years

In some areas there is a mix of knowledge about utilization of healthcare services for under-five children. Health professionals used abbaa gadaa, or hadha sinqee (male and female cultural leaders) and members of the female development army (FDA) to raise the level of awareness in the community. One key informant interviewee shared the experience of his districts in utilizing women’s development army and these cultural leaders to increase the knowledge of the community as follows;

“We improve the awareness of our community on child healthcare utilization through women’s development army and cultural leaders, we trained these women about early recognition of maternal and child health danger sign. we provide them local COC for them. By now in our district, women’s development armies have equivalent knowledge with HEW and, we used them to teach the community”. Male, Key informant, age 42 year.

Socioeconomic barriers

Lack of sufficient income at household level and low level of maternal and paternal education were identified as major barriers for equity in utilization of healthcare services for under-five children. As part of its HSDP II strategic objectives, the Ethiopian Government intends to address equity in maternal and child health, particularly for the impoverished and rural communities, by providing free health services to these subgroups and allocating a sufficient budget. However, the actual and perceived cost of seeking care keeps some people from traveling to medical facilities. Out-of- pocket costs of health care, cost of transportation and living cost may prevent poor people from using services, leading to untreated childhood illness.

For instance after they reached to health facility, they obligated to pay for medical treatment or drugs they used to treat their children. In this case some advanced diagnosis and treatment is not available in governmental health facilities.. For example, CT scan and MRI to diagnose severe childhood diseases and some essential drugs to treat pneumonia, sepsis and diarrhea were not available in health centers and in health posts. They were advised to get this treatment from private clinics and to buy the drugs from private pharmacies. However, or mothers could not afford to purchase them from private clinic.

A woman from FGD discussant explained her experience of an availability of certain services in Government health facility and high cost of services in private clinic as follows:

“Yes, nowadays, the cost of drugs and treatment for childhood illness is increasing, when I used to get treatment for my sick child from a health center or health post the health professional referred me to a private clinic to be seen or diagnosed by a highly expensive machine; I am unable to afford for this machine. Moreover there were no drugs at the health post and the health center. They told us to purchase them from private clinics. So, how can the poor people get treatment from Governmental health facility?” Female FGD discussant age, 34 years, with low income.

Another FGD discussant described this problem as follows:

“Yes, getting treatment in this health facility is good but sometimes you go here and there to get examined and prescribed for drugs and you need money for those drugs. If you don’t have money, then you remain with the illness” Female FGD discussant, age 29 years.

The study participants suggested that, socioeconomic healthcare inequity must be addressed by healthcare system revisions such as the provision of health insurance, fee retention; waiving and exemptions from fees for poor people, and subsiding the cost of the transportation were considered as solution to reduce inequity in health care services.

Geographical barriers

Distance of health facilities from home and unavailability of motorized transportation were another major barrier to health services utilization. Pit the fact that availability of some community based services should increase health service utilization to caregivers, distance from homes to health facilities, poor roads and unavailability of motorized transport were major barriers for many people. Distance from health centers and health posts and lack of transportation and cost of transportation were cited as barberries of equity for child health service utilization by rural and the poor communities. Long distances, shoddy road construction, and a shortage of ambulances make it difficult for residents of remote communities and low-income families to get to medical facilities and thus have fewer opportunities to vaccinate their children. One key informant said that.

“…the primary issue facing this district is the lack of transportation and the distance between the residential area and the medical facilities . The caregivers were unable to get transportation service easily. In some areas the distance between health facilities and residential areas of the community is too far, besides there is no road to get access to health facility. We need more vehicles at health center level; moreover, the transportation issue cannot be solved unless quality roads will be constructed for the community.”Male, key-informant interview, age 40 years.

Another FGD discussant said that.

“ Yaa, we move more than 30 km on foot to access health facilities, especially health centers, there is no road for cars., we carry our sick child on our backs to get treatment from this health facility” FGD, Male, age 44 years.

One FGD described the transportation problem a follows:

“…even though roads were constructed, there is no reliable transportation system in our area. Ambulance service is not available in our area, no mobile network to call to ambulance service. Moreover, if we were hardly access the ambulance, we are requested to pay 1000 Birr for fuel. Therefore, the Government and concerned body has to understand and solve our situation related to distance and transportation problem.” Male, FGD discussant, Age 49 year.

The study participant also suggested that geographical and financial accessibility barriers have to be addressed by bringing services closer to homes or residential areas.

Healthcare system barriers

Certain aspects of healthcare system were identified as barriers to equitable healthcare services for under-five children. In Ethiopia, important deterrents include unavailability, unaffordability of the service, and closure of health posts during working hours and issues related to behaviors of the health professionals were the emerged theme from this study.

One of the important barriers of equity in utilization of child healthcare services especially by poor were unavailability of child care services at health posts. Even though the health posts are supposed to give services for the rural and poor populations, it was closed on many working days and at weekends. In addition, absence of health extension workers from the duty during working hours, services inconsistently and unavailability of drugs in the health posts were barberries of equity raised by KII and FGD discussants. One of key informant interviewees explained his observations as follows;

“Even though, the health posts are expected to give maternal and child health services for the rural community free of charge, how the poor and the rural community get these services, the health posts were closed during working hours, most of the time the HEW workers are in another duty, they were assigned to collect taxes and insurance from the community, so the richest household will get these services from private health institution but the poor and the rural community is in problem in accessing these services” Key-informant interview, Male, 45 years.

Besides giving health services, in some rural areas the health extension workers are assigned to other administrative and political activities. A health extension worker in health post acknowledged the absence of health services during working hour in such ways;

“ How can we give health services for the poor community, we are assigned to collect insurance, taxes and to register member for the political parties, if we say no we will be fired, most of the time the health posts were closed, all services were intercepted, mothers from rural area repeatedly came for immunization, but they did not get us in the health post, those mothers who were educated and have the money for transportation may went to health centers and Hospitals to get immunization service, but the poor mother were waiting us till the health post is opened” Female, Age 39 year.

One woman from FGD participant also explains her experience as follows;

“One day my 3 years old child was sick and I came to consult the HEW, but, the door is closed and she was not around” Female, FGD discussant, Age 38year, rural community

Another important finding from this qualitative study was issue of marginalized populations. The health services do not cover marginalized and poor people, like, beggars, around churches, mosques and along roads on child health services especially immunization . Key informant participants from the one woreda health office described this issue as follows;

“Here is the gap, now the health facilities have no plan and willing to give immunization services to marginalized poor people like; beggars around the mosque, church, and on roads. These poor people are totally forgotten, the motivation of health workers to serve this community is almost zero or near to nil. All vaccination mandates are given to HEW, but now health centers and health posts are not connected to these people and their children’s are not vaccinated at all. There is no supervision or support from higher officials, no accountability among HEW “KII M ale, 45yer.

Lack of adequate supply of medicines and other medical supplies emerged as a recurring theme in FGDs and KII at both the policy and service delivery levels. The health posts do not have all basic medicines available and end up giving inadequate drugs, no separate budget is allocated for child health by Ministry of Health or the regional health bureaus. Donors, NGO,s and partners have reduced their budgets and support of child health programs.

One KII participant shared his perceived cause of inadequate supplies and budgeting for health facility as follows:

“…Currently only limited budgets are allocated to the health sector, especially for maternal and child health. There are no donors and partners who support the healthcare system; this is probably linked to the current Ethiopian political upheavals. This creates problems for free services for maternal and child care. In my opinion this is the cause of an availability of materials and some drugs at health facility” key-informant-interview, age 44 year.

Disrespectful care and treatment was the issue raised as barriers to equity by caregivers for their under-five children. Ethiopian communities pay attention to respectful and quality of care, therefore giving preference to urban health centers, which generally meet patient expectation. But urban health facilities also discriminate against poor people. A female FGD discussant raised the issue of non-compassionate and disrespectful care given to her at an urban health facility, as follows:

“Yes, we looked unclean and came from rural areas, the health professionals treated us as not as humans and gave us poor care. They did not touch us by their hands or used apparatus to examine our problem. They simply asked us about our illness and gave us prescription to buy drugs” Female, FGD, 42 years.

Respondents suggest that, the government need to ensure the availability of adequate essential vaccines, drugs and supplies in health facilities. The FGD discussants further emphasized that, both central and local healthcare systems need to allocate adequate financial resources and procure adequate logistic and material supplies towards effective implementation of quality healthcare services.

Cultural and behavioral barriers

Low demand and utilization of modern health interventions often derives from deep-rooted attitudes that reflect culture, social norms and traditions of the community. Few FGD participants mentioned that cultural barriers such as using traditional medicines at home and taking the children to traditional healers were barriers to using child health services, especially in rural areas. In some areas peoples believed that the cause of the illness is caused by supernatural agents, exposure to cold, wind or the devil eye. Therefore they do not bring their children to health facilities. Many poor mothers and care givers in rural areas use traditional medicine or religious interventions such as payer as the first treatment for childhood illness because of their ready accessibility and low cost, as stated by one father:

“I have encountered people in some districts who delayed treatment because of traditional beliefs. One of them said … If my child gets sick, I will not bring it to a health facility immediately, I will wait until the disease matures and shows full blown sign can l be observed or till it will resolved by itself” key-informant interview, Male 42 years.

There are also other traditions, customs and beliefs among some rural communities which are barriers to equity of child health services. For instance haamachisaa is a kind of blessing used as the first treatment by traditional healers for neonates aged less than 3 months before seeking care services from health facilities. They believe that haamachisaa prevent malicious birds or the evil eye to inflict illness on neonates, as described by one mother:

“ in our area some of the rural communities will not send their “ children below three months of age” to get immunization services from health facilities before they practice haamchisaa or blessing services from a traditional healer because a bird or the evil eye may see the neonate “ Female, key- informant, 39 years.

In some rural districts, obstacles to child health care service utilization include the use of traditional uvulectomy, getting treatment for measles from traditional healers and using holy water (tsebel) at churches when children fall ill.

“In our area, when their child develops measles some of them refuse to take their children to health facility because they believe that the treatment there will cause girsha, the dissemination of the rash to different organ systems” Male, key-informant, 30 years head of HC.

Another FGD discussant described her preference of traditional healers for her sick child because of cost of the drug as follows;

“I visited a traditional healer for my child when he had tonsil, because drugs and repeated treatment from a health facility are expensive; After the tonsils are removed by a traditional healer there is no recurrence, so it is less costly for me” Female, FG, Age 40 year.

In another way less attention was given for morbidity and mortality of the child by rural community, especially to the neonate (if a neonate died) the funeral ceremony will not be practice in the church or mosque. The burial or funeral ceremony is accomplished at near house of the parents; the dead body is not brought to church or mosque. The community did not consider a neonatal death as a death of human being or adult death but, is concealed, as described by a male key-informant:

“ Here in the community less attention is given to child health, especially for the newborns; if the newborn dies the dead body will not brought to a church or mosque but it will be buried around the home. Nobody will go to that home to morn with the parents” Male key-informant, 42 years.

In many Ethiopian communities, women’s have low autonomy to decide for her own and their children’s health in Ethiopia. They need the permission of their husbands to seek care for their children, because of economic, psychological and material dependence. The norms and values of the community also reinforce this behavior.

One of the important finding of this study was inequity related to ethnicity. Almost all KII and FGD participants stated that there is no disparity in healthcare service utilization because of ethnicity.

“…..Even though Ethiopia is having a diversified ethnic group still there is no marginalization or inequity in utilization of child health services from health facility because of ethnicity; rather they encounter barriers related to language in understanding and to get consultation from service providers” Key-informant, Male, Age 39 year.

The study participants further suggested that barriers related to health illiteracy or mistrust of the healthcare system have to be addressed by involving different stakeholders such as community leaders, traditional healers and religious leaders .

Politics, conflict and security issues

Over the last few years, Ethiopia is suffering from different types of military conflicts between the Ethiopian government and insurgent forces in most regions and administrative areas. This protracted conflict hinders maternal and child health service delivery affected communities, especially in isolated rural areas. As a result, health services could not operate safely in the war zone, Increasing the incidence of vaccine-preventable diseases and malnutrition. A male FGD discussant explained the effects of conflict on maternal and children service utilization as follows:

“ In our district there is continuous military conflict between the government and rebel forces; most of the time the health facilities were closed, there is diversion of supplies for maternal and child health services to the armed forces, no immunization services was given to the community during this conflict period, roads were closed, the health professionals fled health facilities because they felt insecure, even ambulances assigned to MCH services were used for military purposes;, the rich may get the service from private clinic, the poor did not get anything, simply waiting an interventions from God,, or simply wait to die or migrate to other places” Male, FGD, age 45 years.

One key-informant interview participant reported his observation of security problem on child health services in his district as follows:

“Regarding the issue of security problem, currently in our area there is a military conflict between government and rebellions. Due to this there is no maternal and child healthcare services, 24 h ambulance was served for political purposes, as a result mothers and children are dying from severe anemia and severe pneumonia at their home, therefore, politically instability and conflict among Government and armed rebellion force exacerbate the existed disparity in utilization of healthcare services for mothers and children in our district”. Key –informant, male, age 41 years.

The research participant added that communication between opposing groups is necessary to resolve political unrest and conflict which has direct impact on child healthcare utilization.

This study aimed at exploring barriers of equity that mothers and their children face in accessing and utilization of healthcare services for under-five children. The findings point out multiple dynamics of barriers of equity to care-seeking and utilization of healthcare services in Ethiopia.

In this study the barriers and challenges linked with access and utilization of equitable healthcare services for under-five children were found to fall under six themes ; lack of awareness about availability of the service, socioeconomic barriers, geographic barriers, health system related barriers, cultural and behavioral barriers and political instability and military conflict related barriers. These barriers are inter-related and complex in nature. As key-informants and FGD discussants reported that lack of awareness was one of the top barriers for not using healthcare services for under-five children, especially in rural communities. Populations who have settled in far to reach areas and uneducated have no equal awareness about health related issues compared to urban and well educated populations. Their reasons are people leave in rural area has insufficient exposure to media, attending low level of schooling to grasp and understand health related information. Most studies reported that because of low health related literacy, rural community and the poor household had delayed to access health facility to get treatment for most of childhood illnesses, and vaccination services [ 22 ]. In this study having participants confirm that there is a gap in knowledge regarding the causes of childhood illness and regarding the availability of treatments at health posts, it is clear that a campaign to educate and mobilize community members will be necessary. The need for transmission of information about the availability of services was also highlighted by several other studies [ 23 ]. Studies in Ethiopia reported that, HEW home visits were reportedly valuable for increasing awareness and use of services and mothers of under-fives who received health information [ 24 ]. Different studies suggest that community education and mobilization campaigns may increase level of awareness of communities. One study also reported that HEWs and HDA were credible sources of health-related information [ 25 , 26 ]. For example, the HEW increased the awareness of communities during pregnant woman conferences, vaccination campaigns, and other community meetings.

This study further highlights that, socioeconomic barriers to health care utilization are strong deterrents that increase under-five mortality in Ethiopia. Limited financial resources for medical treatment and low educational level of parents are barriers to the use of healthcare services for children among disadvantaged populations. In this regard, the Ethiopian government plans to provide free health services for women and under-five children, through the HSTP. II but our finding revealed that low household income, low level of maternal education, and out-of- pocket payments for health care prevent poorer people from using services for under-five children. Furthermore it should be noted that the government of Ethiopia has adopted a waiver fee policy for the vulnerable groups. However, cost of services still play a major role in access to service since the exemption from paying for the services is unevenly applied.

Several studies corroborate our findings of the socioeconomic impact on health service utilization [ 27 , 28 ]. A study conducted by Daniel et al. confirmed that the levels of household income and health literacy affect access to healthcare services [ 27 ]. Moreover, indirect costs such as loss of work time, loss of income and transportation cost have a significant economic impact on poorer families [ 28 ]. Implementing health insurance scheme and waiving user fees may shield the poor from these charges and weaken household health budget constraints.

Our findings of the negative impact of low education of parents is corroborated by several studies. [ 29 , 30 ]. Pregnant mothers with higher education are more aware of the significance of good nutrition and child care as well as the prerequisites for being healthy [ 31 ]. Education plays a vital role in shaping attitudes, opinions, customs, and norms and also promotes the adoption of new ideas and values.

The result of our study revealed that, distance from health facility, lack of transportation and uncomfortable road topography especially in summer were mentioned as an important barriers of equity in healthcare service utilization for under –five children. Previous studies in Ethiopia confirmed that far to reach regions, districts and areas often face special issues and problems compared to non-far to reach areas [ 32 , 33 ]. Several studies in other countries also showed that travelling to a health center was challenging for caregivers of children residing in far to reach areas and cost of transportation, unreliability and its unavailability of services were the main impairments of equity in accessing healthcare services [ 34 , 35 , 36 , 37 , 38 ]. For example, a study of measles vaccination coverage in various African countries found that distance was a key factor in determining the level of immunization coverage [ 39 , 40 , 41 ]. In addition to the inverse relationship between distance and health services utilization, geographical location of health facilities in isolated rural areas also jeopardizes the staffing of health facilities. Doctors, midwifes and nurses are less eager to serve in such areas than in urban communities and vaccines and flooding may prevent the delivery of vaccines and drugs to distant mountain communities during the rainy season.

Respondents highlighted the need to ensure reliable availability of HEWs at the health post during opening hours and extending the hours of the health post so that services would be available working hours and on weekends. Such closures have been shown to be a major challenge in previous studies [ 42 ]. HEWs travel for activities such as collecting taxes registering political membership from the residential and payment for health insurance from the community should be stunned by the community and so that there is at least one HEW in each health post to give services for the community . Another important finding from this study was issue of marginalized populations. Some key-informant and FGD discussant cited that, the health facility is not have especial plan to address the services to marginalized poor people, like, baggers around the church, mosques and around roads on child health services especially for immunization services. Hence this may create critical inequity in child healthcare service utilization among the poor.

Barriers to equity in access and utilization of services extend beyond accessibility and availability issues, disrespectful care and negative attitude acts as a barrier to accessing health care services. Negative attitude of health workers in the form of verbal expression, represented a theme of recurrence as a barrier of equity in utilization of the services. Female FGD discussant raised the issue of non-compassionate and disrespectful care given to them by health professionals at health facility and they were receiving poor quality of care, and there is no companionate care for the poor. Improving quality and outcomes at health centers offers an incentive for the utilization of a service. In many African countries, low quality of health services has been identified as a hindrance to equitable access of services [ 43 ]. In the current study, few participants mentioned that cultural factors like home remedies taking the children to traditional healers were obstacles to utilization equity. Other studies from Sub-Saharan Africa show similar results [ 44 ]. This shows that, traditional beliefs and norms of the community impede from seeking-care modern healthcare and utilization of the services from health facility.

One of the promising finding in this study was, even though Ethiopia have a diversified ethnic group there is no report related disparity or inequity in utilization of child health services because of his/her ethnicity, rather they encounter barrier related to language in understanding and to get consultation from service provider.

Our finding revealed that, war and political instability disrupt health services accessibility and utilization. There was also reported from several other countries, including Afghanistan, the Democratic Republic of Congo, Pakistan, and Somalia [ 45 ]. Key impacts include disrupted infrastructure and supply chain; violence against health workers; difficulties retaining health workers; delivery service interruptions; and displacement and migration [ 46 ]. For populations affected by military conflict, adopting flexibility surrounding age and eligibility criteria can increase immunization coverage.

Strength and limitation of this study

Strengths of this study include the collection of data by experienced interviewers, efforts made to increase trustworthiness of the study, checking transcripts against audio-records and field notes by two independent experts, and use of the participants’ own language for data collection. In addition, inclusion of participants from all levels of the healthcare system and caregivers (both mothers and father) of the children broadened the range of experiences and opinions on inequity in child health services accessibility and utilization. The major limitation of this qualitative study is that its findings are may not be generalized to other settings. Furthermore, since the study was only conducted in one district, it might not be representative of the entire nation.

Conclusions and recommendations

We conclude that inequity in child healthcare utilization continues to be an important challenge confronting Ethiopia. Constraints such as poor community awareness of the availability of curative healthcare services, geographic inaccessibility, inadequate healthcare resources, socioeconomic barriers, and constraints related to the functioning of the healthcare system and political instability and military conflict were the most cited barriers to equity.

To achieve equity, Ethiopian policymakers and partners need to invest in health infrastructure, including bringing services closer to people by constructing new health posts, health centers and roads in rural areas, and increasing the quality of services. In addition, context-specific cultural barriers such as the use of traditional medicines and illness beliefs need to be addressed through health promotion and military conflict needs to be solved through dialog between opposing bodies.

Availability of data and materials

The data that support the finding of this study are available and attached as related files.

Abbreviations

Certificate of competency

Compassionate respectful care

Focus group discussion

Federal Ministry of Health

Health care workers

Health extension workers

Key-informant interview

Maternal and child health

Millennium developmental goals

Oromia Regional Health Bureau

Primary health care

United Nations

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Acknowledgements

The authors would like to thank the study participants, the Federal Ministry of Health, regional health bureaus, and zonal and district level health leaders. We also acknowledge Addis Ababa University and Professor Helmut Kloos for funding this study.

Addis Ababa University School of Public Health, and support from Professor Helmut Kloos.

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H.F and D.H contributed to the design and conception of the study and analyzed and interpreted the data. W.M, H.K, and A.A participated in data analysis, interpretation and revision of the manuscript. All authors read and revised the draft of this manuscript and approved the final version.

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Nursing students’ stressors and coping strategies during their first clinical training: a qualitative study in the United Arab Emirates

• Jacqueline Maria Dias 1 ,
• Muhammad Arsyad Subu 1 ,
• Nabeel Al-Yateem 1 ,
• Fatma Refaat Ahmed 1 ,
• Syed Azizur Rahman 1 , 2 ,
• Mini Sara Abraham 1 ,
• Sareh Mirza Forootan 1 ,
• Farzaneh Ahmad Sarkhosh 1 &
• Fatemeh Javanbakh 1  

BMC Nursing volume  23 , Article number:  322 ( 2024 ) Cite this article

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Understanding the stressors and coping strategies of nursing students in their first clinical training is important for improving student performance, helping students develop a professional identity and problem-solving skills, and improving the clinical teaching aspects of the curriculum in nursing programmes. While previous research have examined nurses’ sources of stress and coping styles in the Arab region, there is limited understanding of these stressors and coping strategies of nursing students within the UAE context thereby, highlighting the novelty and significance of the study.

A qualitative study was conducted using semi-structured interviews. Overall 30 students who were undergoing their first clinical placement in Year 2 at the University of Sharjah between May and June 2022 were recruited. All interviews were recorded and transcribed verbatim and analyzed for themes.

During their first clinical training, nursing students are exposed to stress from different sources, including the clinical environment, unfriendly clinical tutors, feelings of disconnection, multiple expectations of clinical staff and patients, and gaps between the curriculum of theory classes and labatories skills and students’ clinical experiences. We extracted three main themes that described students’ stress and use of coping strategies during clinical training: (1) managing expectations; (2) theory-practice gap; and (3) learning to cope. Learning to cope, included two subthemes: positive coping strategies and negative coping strategies.

Conclusions

This qualitative study sheds light from the students viewpoint about the intricate interplay between managing expectations, theory practice gap and learning to cope. Therefore, it is imperative for nursing faculty, clinical agencies and curriculum planners to ensure maximum learning in the clinical by recognizing the significance of the stressors encountered and help students develop positive coping strategies to manage the clinical stressors encountered. Further research is required look at the perspective of clinical stressors from clinical tutors who supervise students during their first clinical practicum.

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Nursing education programmes aim to provide students with high-quality clinical learning experiences to ensure that nurses can provide safe, direct care to patients [ 1 ]. The nursing baccalaureate programme at the University of Sharjah is a four year program with 137 credits. The programmes has both theoretical and clinical components withs nine clinical courses spread over the four years The first clinical practicum which forms the basis of the study takes place in year 2 semester 2.

Clinical practice experience is an indispensable component of nursing education and links what students learn in the classroom and in skills laboratories to real-life clinical settings [ 2 , 3 , 4 ]. However, a gap exists between theory and practice as the curriculum in the classroom differs from nursing students’ experiences in the clinical nursing practicum [ 5 ]. Clinical nursing training places (or practicums, as they are commonly referred to), provide students with the necessary experiences to ensure that they become proficient in the delivery of patient care [ 6 ]. The clinical practicum takes place in an environment that combines numerous structural, psychological, emotional and organizational elements that influence student learning [ 7 ] and may affect the development of professional nursing competencies, such as compassion, communication and professional identity [ 8 ]. While clinical training is a major component of nursing education curricula, stress related to clinical training is common among students [ 9 ]. Furthermore, the nursing literature indicates that the first exposure to clinical learning is one of the most stressful experiences during undergraduate studies [ 8 , 10 ]. Thus, the clinical component of nursing education is considered more stressful than the theoretical component. Students often view clinical learning, where most learning takes place, as an unsupportive environment [ 11 ]. In addition, they note strained relationships between themselves and clinical preceptors and perceive that the negative attitudes of clinical staff produce stress [ 12 ].

The effects of stress on nursing students often involve a sense of uncertainty, uneasiness, or anxiety. The literature is replete with evidence that nursing students experience a variety of stressors during their clinical practicum, beginning with the first clinical rotation. Nursing is a complex profession that requires continuous interaction with a variety of individuals in a high-stress environment. Stress during clinical learning can have multiple negative consequences, including low academic achievement, elevated levels of burnout, and diminished personal well-being [ 13 , 14 ]. In addition, both theoretical and practical research has demonstrated that increased, continual exposure to stress leads to cognitive deficits, inability to concentrate, lack of memory or recall, misinterpretation of speech, and decreased learning capacity [ 15 ]. Furthermore, stress has been identified as a cause of attrition among nursing students [ 16 ].

Most sources of stress have been categorized as academic, clinical or personal. Each person copes with stress differently [ 17 ], and utilizes deliberate, planned, and psychological efforts to manage stressful demands [ 18 ]. Coping mechanisms are commonly termed adaptation strategies or coping skills. Labrague et al. [ 19 ] noted that students used critical coping strategies to handle stress and suggested that problem solving was the most common coping or adaptation mechanism used by nursing students. Nursing students’ coping strategies affect their physical and psychological well-being and the quality of nursing care they offer. Therefore, identifying the coping strategies that students use to manage stressors is important for early intervention [ 20 ].

Studies on nursing students’ coping strategies have been conducted in various countries. For example, Israeli nursing students were found to adopt a range of coping mechanisms, including talking to friends, engaging in sports, avoiding stress and sadness/misery, and consuming alcohol [ 21 ]. Other studies have examined stress levels among medical students in the Arab region. Chaabane et al. [ 15 ], conducted a systematic review of sudies in Arab countries, including Saudi Arabia, Egypt, Jordan, Iraq, Pakistan, Oman, Palestine and Bahrain, and reported that stress during clinical practicums was prevalent, although it could not be determined whether this was limited to the initial clinical course or occurred throughout clinical training. Stressors highlighted during the clinical period in the systematic review included assignments and workload during clinical practice, a feeling that the requirements of clinical practice exceeded students’ physical and emotional endurance and that their involvement in patient care was limited due to lack of experience. Furthermore, stress can have a direct effect on clinical performance, leading to mental disorders. Tung et al. [ 22 ], reported that the prevalence of depression among nursing students in Arab countries is 28%, which is almost six times greater than the rest of the world [ 22 ]. On the other hand, Saifan et al. [ 5 ], explored the theory-practice gap in the United Arab Emirates and found that clinical stressors could be decreased by preparing students better for clinical education with qualified clinical faculty and supportive preceptors.

The purpose of this study was to identify the stressors experienced by undergraduate nursing students in the United Arab Emirates during their first clinical training and the basic adaptation approaches or coping strategies they used. Recognizing or understanding different coping processes can inform the implementation of corrective measures when students experience clinical stress. The findings of this study may provide valuable information for nursing programmes, nurse educators, and clinical administrators to establish adaptive strategies to reduce stress among students going clinical practicums, particularly stressors from their first clinical training in different healthcare settings.

A qualitative approach was adopted to understand clinical stressors and coping strategies from the perspective of nurses’ lived experience. Qualitative content analysis was employed to obtain rich and detailed information from our qualitative data. Qualitative approaches seek to understand the phenomenon under study from the perspectives of individuals with lived experience [ 23 ]. Qualitative content analysis is an interpretive technique that examines the similarities and differences between and within different areas of text while focusing on the subject [ 24 ]. It is used to examine communication patterns in a repeatable and systematic way [ 25 ] and yields rich and detailed information on the topic under investigation [ 23 ]. It is a method of systematically coding and categorizing information and comprises a process of comprehending, interpreting, and conceptualizing the key meanings from qualitative data [ 26 ].

Setting and participants

This study was conducted after the clinical rotations ended in April 2022, between May and June in the nursing programme at the College of Health Sciences, University of Sharjah, in the United Arab Emirates. The study population comprised undergraduate nursing students who were undergoing their first clinical training and were recruited using purposive sampling. The inclusion criteria for this study were second-year nursing students in the first semester of clinical training who could speak English, were willing to participate in this research, and had no previous clinical work experience. The final sample consisted of 30 students.

Research instrument

The research instrument was a semi structured interview guide. The interview questions were based on an in-depth review of related literature. An intensive search included key words in Google Scholar, PubMed like the terms “nursing clinical stressors”, “nursing students”, and “coping mechanisms”. Once the questions were created, they were validated by two other faculty members who had relevant experience in mental health. A pilot test was conducted with five students and based on their feedback the following research questions, which were addressed in the study.

How would you describe your clinical experiences during your first clinical rotations?

In what ways did you find the first clinical rotation to be stressful?

What factors hindered your clinical training?

How did you cope with the stressors you encountered in clinical training?

Which strategies helped you cope with the clinical stressors you encountered?

Data collection

Semi-structured interviews were chosen as the method for data collection. Semi structured interviews are a well-established approach for gathering data in qualitative research and allow participants to discuss their views, experiences, attitudes, and beliefs in a positive environment [ 27 ]. This approach allows for flexibility in questioning thereby ensuring that key topics related to clinical learning stressors and coping strategies would be explored. Participants were given the opportunity to express their views, experiences, attitudes, and beliefs in a positive environment, encouraging open communication. These semi structured interviews were conducted by one member of the research team (MAS) who had a mental health background, and another member of the research team who attended the interviews as an observer (JMD). Neither of these researchers were involved in teaching the students during their clinical practicum, which helped to minimize bias. The interviews took place at the University of Sharjah, specifically in building M23, providing a familiar and comfortable environment for the participant. Before the interviews were all students who agreed to participate were provided with an explanation of the study’s purpose. The time and location of each interview were arranged. Before the interviews were conducted, all students who provided consent to participate received an explanation of the purpose of the study, and the time and place of each interview were arranged to accommodate the participants’ schedules and preferences. The interviews were conducted after the clinical rotation had ended in April, and after the final grades had been submitted to the coordinator. The timings of the interviews included the month of May and June which ensured that participants have completed their practicum experience and could reflect on the stressors more comprehensively. The interviews were audio-recorded with the participants’ consent, and each interview lasted 25–40 min. The data were collected until saturation was reached for 30 students. Memos and field notes were also recorded as part of the data collection process. These additional data allowed for triangulation to improve the credibility of the interpretations of the data [ 28 ]. Memos included the interviewers’ thoughts and interpretations about the interviews, the research process (including questions and gaps), and the analytic progress used for the research. Field notes were used to record the interviewers’ observations and reflections on the data. These additional data collection methods were important to guide the researchers in the interpretation of the data on the participants’ feelings, perspectives, experiences, attitudes, and beliefs. Finally, member checking was performed to ensure conformability.

Data analysis

The study used the content analysis method proposed by Graneheim and Lundman [ 24 ]. According to Graneheim and Lundman [ 24 ], content analysis is an interpretive technique that examines the similarities and differences between distinct parts of a text. This method allows researchers to determine exact theoretical and operational definitions of words, phrases, and symbols by elucidating their constituent properties [ 29 ]. First, we read the interview transcripts several times to reach an overall understanding of the data. All verbatim transcripts were read several times and discussed among all authors. We merged and used line-by-line coding of words, sentences, and paragraphs relevant to each other in terms of both the content and context of stressors and coping mechanisms. Next, we used data reduction to assess the relationships among themes using tables and diagrams to indicate conceptual patterns. Content related to stress encountered by students was extracted from the transcripts. In a separate document, we integrated and categorized all words and sentences that were related to each other in terms of both content and context. We analyzed all codes and units of meaning and compared them for similarities and differences in the context of this study. Furthermore, the emerging findings were discussed with other members of the researcher team. The final abstractions of meaningful subthemes into themes were discussed and agreed upon by the entire research team. This process resulted in the extraction of three main themes in addition to two subthemes related to stress and coping strategies.

Ethical considerations

The University of Sharjah Research Ethics Committee provided approval to conduct this study (Reference Number: REC 19-12-03-01-S). Before each interview, the goal and study procedures were explained to each participant, and written informed consent was obtained. The participants were informed that participation in the study was voluntary and that they could withdraw from the study at any time. In the event they wanted to withdraw from the study, all information related to the participant would be removed. No participant withdrew from the study. Furthermore, they were informed that their clinical practicum grade would not be affected by their participation in this study. We chose interview locations in Building M23that were private and quiet to ensure that the participants felt at ease and confident in verbalizing their opinions. No participant was paid directly for involvement in this study. In addition, participants were assured that their data would remain anonymous and confidential. Confidentiality means that the information provided by participants was kept private with restrictions on how and when data can be shared with others. The participants were informed that their information would not be duplicated or disseminated without their permission. Anonymity refers to the act of keeping people anonymous with respect to their participation in a research endeavor. No personal identifiers were used in this study, and each participant was assigned a random alpha-numeric code (e.g., P1 for participant 1). All digitally recorded interviews were downloaded to a secure computer protected by the principal investigator with a password. The researchers were the only people with access to the interview material (recordings and transcripts). All sensitive information and materials were kept secure in the principal researcher’s office at the University of Sharjah. The data will be maintained for five years after the study is completed, after which the material will be destroyed (the transcripts will be shredded, and the tapes will be demagnetized).

In total, 30 nursing students who were enrolled in the nursing programme at the Department of Nursing, College of Health Sciences, University of Sharjah, and who were undergoing their first clinical practicum participated in the study. Demographically, 80% ( n  = 24) were females and 20% ( n  = 6) were male participants. The majority (83%) of study participants ranged in age from 18 to 22 years. 20% ( n  = 6) were UAE nationals, 53% ( n  = 16) were from Gulf Cooperation Council countries, while 20% ( n  = 6) hailed from Africa and 7% ( n  = 2) were of South Asian descent. 67% of the respondents lived with their families while 33% lived in the hostel. (Table  1 )

Following the content analysis, we identified three main themes: (1) managing expectations, (2) theory-practice gap and 3)learning to cope. Learning to cope had two subthemes: positive coping strategies and negative coping strategies. An account of each theme is presented along with supporting excerpts for the identified themes. The identified themes provide valuable insight into the stressors encountered by students during their first clinical practicum. These themes will lead to targeted interventions and supportive mechanisms that can be built into the clinical training curriculum to support students during clinical practice.

Theme 1: managing expectations

In our examination of the stressors experienced by nursing students during their first clinical practicum and the coping strategies they employed, we identified the first theme as managing expectations.

The students encountered expectations from various parties, such as clinical staff, patients and patients’ relatives which they had to navigate. They attempted to fulfil their expectations as they progressed through training, which presented a source of stress. The students noted that the hospital staff and patients expected them to know how to perform a variety of tasks upon request, which made the students feel stressed and out of place if they did not know how to perform these tasks. Some participants noted that other nurses in the clinical unit did not allow them to participate in nursing procedures, which was considered an enormous impediment to clinical learning, as noted in the excerpt below:

“…Sometimes the nurses… They will not allow us to do some procedures or things during clinical. And sometimes the patients themselves don’t allow us to do procedures” (P5).

Some of the students noted that they felt they did not belong and felt like foreigners in the clinical unit. Excerpts from the students are presented in the following quotes;

“The clinical environment is so stressful. I don’t feel like I belong. There is too little time to build a rapport with hospital staff or the patient” (P22).

“… you ask the hospital staff for some guidance or the location of equipment, and they tell us to ask our clinical tutor …but she is not around … what should I do? It appears like we do not belong, and the sooner the shift is over, the better” (P18).

“The staff are unfriendly and expect too much from us students… I feel like I don’t belong, or I am wasting their (the hospital staff’s) time. I want to ask questions, but they have loads to do” (P26).

Other students were concerned about potential failure when working with patients during clinical training, which impacted their confidence. They were particularly afraid of failure when performing any clinical procedures.

“At the beginning, I was afraid to do procedures. I thought that maybe the patient would be hurt and that I would not be successful in doing it. I have low self-confidence in doing procedures” (P13).

The call bell rings, and I am told to answer Room No. XXX. The patient wants help to go to the toilet, but she has two IV lines. I don’t know how to transport the patient… should I take her on the wheelchair? My eyes glance around the room for a wheelchair. I am so confused …I tell the patient I will inform the sister at the nursing station. The relative in the room glares at me angrily … “you better hurry up”…Oh, I feel like I don’t belong, as I am not able to help the patient… how will I face the same patient again?” (P12).

Another major stressor mentioned in the narratives was related to communication and interactions with patients who spoke another language, so it was difficult to communicate.

“There was a challenge with my communication with the patients. Sometimes I have communication barriers because they (the patients) are of other nationalities. I had an experience with a patient [who was] Indian, and he couldn’t speak my language. I did not understand his language” (P9).

Thus, a variety of expectations from patients, relatives, hospital staff, and preceptors acted as sources of stress for students during their clinical training.

Theme 2: theory-practice gap

Theory-practice gaps have been identified in previous studies. In our study, there was complete dissonance between theory and actual clinical practice. The clinical procedures or practices nursing students were expected to perform differed from the theory they had covered in their university classes and skills lab. This was described as a theory–practice gap and often resulted in stress and confusion.

“For example …the procedures in the hospital are different. They are different from what we learned or from theory on campus. Or… the preceptors have different techniques than what we learned on campus. So, I was stress[ed] and confused about it” (P11).

Furthermore, some students reported that they did not feel that they received adequate briefing before going to clinical training. A related source of stress was overload because of the volume of clinical coursework and assignments in addition to clinical expectations. Additionally, the students reported that a lack of time and time management were major sources of stress in their first clinical training and impacted their ability to complete the required paperwork and assignments:

“…There is not enough time…also, time management at the hospital…for example, we start at seven a.m., and the handover takes 1 hour to finish. They (the nurses at the hospital) are very slow…They start with bed making and morning care like at 9.45 a.m. Then, we must fill [out] our assessment tool and the NCP (nursing care plan) at 10 a.m. So, 15 only minutes before going to our break. We (the students) cannot manage this time. This condition makes me and my friends very stressed out. -I cannot do my paperwork or assignments; no time, right?” (P10).

“Stressful. There is a lot of work to do in clinical. My experiences are not really good with this course. We have a lot of things to do, so many assignments and clinical procedures to complete” (P16).

The participants noted that the amount of required coursework and number of assignments also presented a challenge during their first clinical training and especially affected their opportunity to learn.

“I need to read the file, know about my patient’s condition and pathophysiology and the rationale for the medications the patient is receiving…These are big stressors for my learning. I think about assignments often. Like, we are just focusing on so many assignments and papers. We need to submit assessments and care plans for clinical cases. We focus our time to complete and finish the papers rather than doing the real clinical procedures, so we lose [the] chance to learn” (P25).

Another participant commented in a similar vein that there was not enough time to perform tasks related to clinical requirements during clinical placement.

“…there is a challenge because we do not have enough time. Always no time for us to submit papers, to complete assessment tools, and some nurses, they don’t help us. I think we need more time to get more experiences and do more procedures, reduce the paperwork that we have to submit. These are challenges …” (P14).

There were expectations that the students should be able to carry out their nursing duties without becoming ill or adversely affected. In addition, many students reported that the clinical environment was completely different from the skills laboratory at the college. Exposure to the clinical setting added to the theory-practice gap, and in some instances, the students fell ill.

One student made the following comment:

“I was assisting a doctor with a dressing, and the sight and smell from the oozing wound was too much for me. I was nauseated. As soon as the dressing was done, I ran to the bathroom and threw up. I asked myself… how will I survive the next 3 years of nursing?” (P14).

Theme 3: learning to cope

The study participants indicated that they used coping mechanisms (both positive and negative) to adapt to and manage the stressors in their first clinical practicum. Important strategies that were reportedly used to cope with stress were time management, good preparation for clinical practice, and positive thinking as well as engaging in physical activity and self-motivation.

“Time management. Yes, it is important. I was encouraging myself. I used time management and prepared myself before going to the clinical site. Also, eating good food like cereal…it helps me very much in the clinic” (P28).

“Oh yeah, for sure positive thinking. In the hospital, I always think positively. Then, after coming home, I get [to] rest and think about positive things that I can do. So, I will think something good [about] these things, and then I will be relieved of stress” (P21).

Other strategies commonly reported by the participants were managing their breathing (e.g., taking deep breaths, breathing slowly), taking breaks to relax, and talking with friends about the problems they encountered.

“I prefer to take deep breaths and breathe slowly and to have a cup of coffee and to talk to my friends about the case or the clinical preceptor and what made me sad so I will feel more relaxed” (P16).

“Maybe I will take my break so I feel relaxed and feel better. After clinical training, I go directly home and take a long shower, going over the day. I will not think about anything bad that happened that day. I just try to think about good things so that I forget the stress” (P27).

“Yes, my first clinical training was not easy. It was difficult and made me stressed out…. I felt that it was a very difficult time for me. I thought about leaving nursing” (P7).

I was not able to offer my prayers. For me, this was distressing because as a Muslim, I pray regularly. Now, my prayer time is pushed to the end of the shift” (P11).

“When I feel stress, I talk to my friends about the case and what made me stressed. Then I will feel more relaxed” (P26).

Self-support or self-motivation through positive self-talk was also used by the students to cope with stress.

“Yes, it is difficult in the first clinical training. When I am stress[ed], I go to the bathroom and stand in the front of the mirror; I talk to myself, and I say, “You can do it,” “you are a great student.” I motivate myself: “You can do it”… Then, I just take breaths slowly several times. This is better than shouting or crying because it makes me tired” (P11).

Other participants used physical activity to manage their stress.

“How do I cope with my stress? Actually, when I get stressed, I will go for a walk on campus” (P4).

“At home, I will go to my room and close the door and start doing my exercises. After that, I feel the negative energy goes out, then I start to calm down… and begin my clinical assignments” (P21).

Both positive and negative coping strategies were utilized by the students. Some participants described using negative coping strategies when they encountered stress during their clinical practice. These negative coping strategies included becoming irritable and angry, eating too much food, drinking too much coffee, and smoking cigarettes.

“…Negative adaptation? Maybe coping. If I am stressed, I get so angry easily. I am irritable all day also…It is negative energy, right? Then, at home, I am also angry. After that, it is good to be alone to think about my problems” (P12).

“Yeah, if I…feel stress or depressed, I will eat a lot of food. Yeah, ineffective, like I will be eating a lot, drinking coffee. Like I said, effective, like I will prepare myself and do breathing, ineffective, I will eat a lot of snacks in between my free time. This is the bad side” (P16).

“…During the first clinical practice? Yes, it was a difficult experience for us…not only me. When stressed, during a break at the hospital, I will drink two or three cups of coffee… Also, I smoke cigarettes… A lot. I can drink six cups [of coffee] a day when I am stressed. After drinking coffee, I feel more relaxed, I finish everything (food) in the refrigerator or whatever I have in the pantry, like chocolates, chips, etc” (P23).

These supporting excerpts for each theme and the analysis offers valuable insights into the specific stressors faced by nursing students during their first clinical practicum. These insights will form the basis for the development of targeted interventions and supportive mechanisms within the clinical training curriculum to better support students’ adjustment and well-being during clinical practice.

Our study identified the stressors students encounter in their first clinical practicum and the coping strategies, both positive and negative, that they employed. Although this study emphasizes the importance of clinical training to prepare nursing students to practice as nurses, it also demonstrates the correlation between stressors and coping strategies.The content analysis of the first theme, managing expectations, paves the way for clinical agencies to realize that the students of today will be the nurses of tomorrow. It is important to provide a welcoming environment where students can develop their identities and learn effectively. Additionally, clinical staff should foster an environment of individualized learning while also assisting students in gaining confidence and competence in their repertoire of nursing skills, including critical thinking, problem solving and communication skills [ 8 , 15 , 19 , 30 ]. Another challenge encountered by the students in our study was that they were prevented from participating in clinical procedures by some nurses or patients. This finding is consistent with previous studies reporting that key challenges for students in clinical learning include a lack of clinical support and poor attitudes among clinical staff and instructors [ 31 ]. Clinical staff with positive attitudes have a positive impact on students’ learning in clinical settings [ 32 ]. The presence, supervision, and guidance of clinical instructors and the assistance of clinical staff are essential motivating components in the clinical learning process and offer positive reinforcement [ 30 , 33 , 34 ]. Conversely, an unsupportive learning environment combined with unwelcoming clinical staff and a lack of sense of belonging negatively impact students’ clinical learning [ 35 ].

The sources of stress identified in this study were consistent with common sources of stress in clinical training reported in previous studies, including the attitudes of some staff, students’ status in their clinical placement and educational factors. Nursing students’ inexperience in the clinical setting and lack of social and emotional experience also resulted in stress and psychological difficulties [ 36 ]. Bhurtun et al. [ 33 ] noted that nursing staff are a major source of stress for students because the students feel like they are constantly being watched and evaluated.

We also found that students were concerned about potential failure when working with patients during their clinical training. Their fear of failure when performing clinical procedures may be attributable to low self-confidence. Previous studies have noted that students were concerned about injuring patients, being blamed or chastised, and failing examinations [ 37 , 38 ]. This was described as feeling “powerless” in a previous study [ 7 , 12 ]. In addition, patients’ attitudes towards “rejecting” nursing students or patients’ refusal of their help were sources of stress among the students in our study and affected their self-confidence. Self-confidence and a sense of belonging are important for nurses’ personal and professional identity, and low self-confidence is a problem for nursing students in clinical learning [ 8 , 39 , 40 ]. Our findings are consistent with a previous study that reported that a lack of self-confidence was a primary source of worry and anxiety for nursing students and affected their communication and intention to leave nursing [ 41 ].

In the second theme, our study suggests that students encounter a theory-practice gap in clinical settings, which creates confusion and presents an additional stressors. Theoretical and clinical training are complementary elements of nursing education [ 40 ], and this combination enables students to gain the knowledge, skills, and attitudes necessary to provide nursing care. This is consistent with the findings of a previous study that reported that inconsistencies between theoretical knowledge and practical experience presented a primary obstacle to the learning process in the clinical context [ 42 ], causing students to lose confidence and become anxious [ 43 ]. Additionally, the second theme, the theory-practice gap, authenticates Safian et al.’s [ 5 ] study of the theory-practice gap that exists United Arab Emirates among nursing students as well as the need for more supportive clinical faculty and the extension of clinical hours. The need for better time availability and time management to complete clinical tasks were also reported by the students in the study. Students indicated that they had insufficient time to complete clinical activities because of the volume of coursework and assignments. Our findings support those of Chaabane et al. [ 15 ]. A study conducted in Saudi Arabia [ 44 ] found that assignments and workload were among the greatest sources of stress for students in clinical settings. Effective time management skills have been linked to academic achievement, stress reduction, increased creativity [ 45 ], and student satisfaction [ 46 ]. Our findings are also consistent with previous studies that reported that a common source of stress among first-year students was the increased classroom workload [ 19 , 47 ]. As clinical assignments and workloads are major stressors for nursing students, it is important to promote activities to help them manage these assignments [ 48 ].

Another major challenge reported by the participants was related to communicating and interacting with other nurses and patients. The UAE nursing workforce and population are largely expatriate and diverse and have different cultural and linguistic backgrounds. Therefore, student nurses encounter difficulty in communication [ 49 ]. This cultural diversity that students encounter in communication with patients during clinical training needs to be addressed by curriculum planners through the offering of language courses and courses on cultural diversity [ 50 ].

Regarding the third and final theme, nursing students in clinical training are unable to avoid stressors and must learn to cope with or adapt to them. Previous research has reported a link between stressors and the coping mechanisms used by nursing students [ 51 , 52 , 53 ]. In particular, the inability to manage stress influences nurses’ performance, physical and mental health, attitude, and role satisfaction [ 54 ]. One such study suggested that nursing students commonly use problem-focused (dealing with the problem), emotion-focused (regulating emotion), and dysfunctional (e.g., venting emotions) stress coping mechanisms to alleviate stress during clinical training [ 15 ]. Labrague et al. [ 51 ] highlighted that nursing students use both active and passive coping techniques to manage stress. The pattern of clinical stress has been observed in several countries worldwide. The current study found that first-year students experienced stress during their first clinical training [ 35 , 41 , 55 ]. The stressors they encountered impacted their overall health and disrupted their clinical learning. Chaabane et al. [ 15 ] reported moderate and high stress levels among nursing students in Bahrain, Egypt, Iraq, Jordan, Oman, Pakistan, Palestine, Saudi Arabia, and Sudan. Another study from Bahrain reported that all nursing students experienced moderate to severe stress in their first clinical placement [ 56 ]. Similarly, nursing students in Spain experienced a moderate level of stress, and this stress was significantly correlated with anxiety [ 30 ]. Therefore, it is imperative that pastoral systems at the university address students’ stress and mental health so that it does not affect their clinical performance. Faculty need to utilize evidence-based interventions to support students so that anxiety-producing situations and attrition are minimized.

In our study, students reported a variety of positive and negative coping mechanisms and strategies they used when they experienced stress during their clinical practice. Positive coping strategies included time management, positive thinking, self-support/motivation, breathing, taking breaks, talking with friends, and physical activity. These findings are consistent with those of a previous study in which healthy coping mechanisms used by students included effective time management, social support, positive reappraisal, and participation in leisure activities [ 57 ]. Our study found that relaxing and talking with friends were stress management strategies commonly used by students. Communication with friends to cope with stress may be considered social support. A previous study also reported that people seek social support to cope with stress [ 58 ]. Some students in our study used physical activity to cope with stress, consistent with the findings of previous research. Stretching exercises can be used to counteract the poor posture and positioning associated with stress and to assist in reducing physical tension. Promoting such exercise among nursing students may assist them in coping with stress in their clinical training [ 59 ].

Our study also showed that when students felt stressed, some adopted negative coping strategies, such as showing anger/irritability, engaging in unhealthy eating habits (e.g., consumption of too much food or coffee), or smoking cigarettes. Previous studies have reported that high levels of perceived stress affect eating habits [ 60 ] and are linked to poor diet quality, increased snacking, and low fruit intake [ 61 ]. Stress in clinical settings has also been linked to sleep problems, substance misuse, and high-risk behaviors’ and plays a major role in student’s decision to continue in their programme.

Implications of the study

The implications of the study results can be grouped at multiple levels including; clinical, educational, and organizational level. A comprehensive approach to addressing the stressors encountered by nursing students during their clinical practicum can be overcome by offering some practical strategies to address the stressors faced by nursing students during their clinical practicum. By integrating study findings into curriculum planning, mentorship programs, and organizational support structures, a supportive and nurturing environment that enhances students’ learning, resilience, and overall success can be envisioned.

Clinical level

Introducing simulation in the skills lab with standardized patients and the use of moulage to demonstrate wounds, ostomies, and purulent dressings enhances students’ practical skills and prepares them for real-world clinical scenarios. Organizing orientation days at clinical facilities helps familiarize students with the clinical environment, identify potential stressors, and introduce interventions to enhance professionalism, social skills, and coping abilities Furthermore, creating a WhatsApp group facilitates communication and collaboration among hospital staff, clinical tutors, nursing faculty, and students, enabling immediate support and problem-solving for clinical situations as they arise, Moreover, involving chief nursing officers of clinical facilities in the Nursing Advisory Group at the Department of Nursing promotes collaboration between academia and clinical practice, ensuring alignment between educational objectives and the needs of the clinical setting [ 62 ].

Educational level

Sharing study findings at conferences (we presented the results of this study at Sigma Theta Tau International in July 2023 in Abu Dhabi, UAE) and journal clubs disseminates knowledge and best practices among educators and clinicians, promoting awareness and implementation of measures to improve students’ learning experiences. Additionally we hold mentorship training sessions annually in January and so we shared with the clinical mentors and preceptors the findings of this study so that they proactively they are equipped with strategies to support students’ coping with stressors during clinical placements.

Organizational level

At the organizational we relooked at the available student support structures, including counseling, faculty advising, and career advice, throughout the nursing program emphasizing the importance of holistic support for students’ well-being and academic success as well as retention in the nursing program. Also, offering language courses as electives recognizes the value of communication skills in nursing practice and provides opportunities for personal and professional development.

For first-year nursing students, clinical stressors are inevitable and must be given proper attention. Recognizing nursing students’ perspectives on the challenges and stressors experienced in clinical training is the first step in overcoming these challenges. In nursing schools, providing an optimal clinical environment as well as increasing supervision and evaluation of students’ practices should be emphasized. Our findings demonstrate that first-year nursing students are exposed to a variety of different stressors. Identifying the stressors, pressures, and obstacles that first-year students encounter in the clinical setting can assist nursing educators in resolving these issues and can contribute to students’ professional development and survival to allow them to remain in the profession. To overcome stressors, students frequently employ problem-solving approaches or coping mechanisms. The majority of nursing students report stress at different levels and use a variety of positive and negative coping techniques to manage stress.

The present results may not be generalizable to other nursing institutions because this study used a purposive sample along with a qualitative approach and was limited to one university in the Middle East. Furthermore, the students self-reported their stress and its causes, which may have introduced reporting bias. The students may also have over or underreported stress or coping mechanisms because of fear of repercussions or personal reasons, even though the confidentiality of their data was ensured. Further studies are needed to evaluate student stressors and coping now that measures have been introduced to support students. Time will tell if these strategies are being used effectively by both students and clinical personnel or if they need to be readdressed. Finally, we need to explore the perceptions of clinical faculty towards supervising students in their first clinical practicum so that clinical stressors can be handled effectively.

Data availability

The data sets are available with the corresponding author upon reasonable request.

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The authors are grateful to all second year nursing students who voluntarily participated in the study.

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Jacqueline Maria Dias, Muhammad Arsyad Subu, Nabeel Al-Yateem, Fatma Refaat Ahmed, Syed Azizur Rahman, Mini Sara Abraham, Sareh Mirza Forootan, Farzaneh Ahmad Sarkhosh & Fatemeh Javanbakh

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JMD conceptualized the idea and designed the methodology, formal analysis, writing original draft and project supervision and mentoring. MAS prepared the methodology and conducted the qualitative interviews and analyzed the methodology and writing of original draft and project supervision. NY, FRA, SAR, MSA writing review and revising the draft. SMF, FAS, FJ worked with MAS on the formal analysis and prepared the first draft.All authors reviewed the final manuscipt of the article.

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Dias, J.M., Subu, M.A., Al-Yateem, N. et al. Nursing students’ stressors and coping strategies during their first clinical training: a qualitative study in the United Arab Emirates. BMC Nurs 23 , 322 (2024). https://doi.org/10.1186/s12912-024-01962-5

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• Volume 14, Issue 5
• Hungarian general practice paediatricians’ antibiotic prescribing behaviour for suspected respiratory tract infections: a qualitative study
• Article Text
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• http://orcid.org/0000-0002-8853-8547 Balázs Babarczy 1 , 2 ,
• Ágnes Hajdu 2 ,
• Ria Benko 3 ,
• Mária Matuz 3 ,
• Renáta Papp 4 ,
• http://orcid.org/0000-0003-3602-6993 Pantelis Antoniou 5 ,
• http://orcid.org/0009-0000-7551-2199 Ketevan Kandelaki 5 ,
• Danilo Lo Fo Wong 5 ,
• http://orcid.org/0000-0002-0600-4235 Sahil Khan Warsi 5
• 1 Syreon Research Institute , Budapest , Hungary
• 2 National Center for Public Health and Pharmacy , Budapest , Hungary
• 3 Department of Clinical Pharmacy , University of Szeged , Szeged , Hungary
• 4 Centre of Science & Innovation Vice-rector and Business Development , Semmelweis University , Budapest , Hungary
• 5 WHO Regional Office for Europe , Copenhagen , Denmark
• Correspondence to Ketevan Kandelaki; kandelakik{at}who.int

Objectives Inappropriate antibiotic prescribing is a major cause of antimicrobial resistance (AMR). The aim of this study was to explore paediatric general practitioners’ (GP Peds) antibiotic prescription practice in suspected respiratory tract infections (RTIs), using the capability–opportunity–motivation–behaviour framework.

Design The design is a qualitative study based on individual, semistructured telephone or virtual interviews.

Setting Paediatric general practice in Hungary. We applied stratified maximum variation sampling to cover the categories of age, sex and geographical location of participants.

Participants We interviewed 22 GP Peds. Nine were male and 13 were female: 2 of them were less than 40 years old, 14 were between 40 and 60 years, and 6 were above 60 years. 10 worked in low-antibiotic prescription areas, 5 in areas with medium levels of antibiotic prescription, 3 in high-antibiotic prescription areas, and 4 in and around the capital city.

Results Study participants had varying antibiotic prescription preferences. Personal experience and physical examination play a central role in GP Peds’ diagnostic and treatment practice. Participants emphasised the need to treat children in their entirety, taking their personal medical record, social background and sometimes parents’ preferences into account, besides the acute clinical manifestation of RTI. Most respondents were confident they apply the most effective therapy even if, in some cases, this meant prescribing medicines with a higher chance of contributing to the development of AMR. Some participants felt antibiotic prescription frequency has decreased in recent years.

Conclusions Our findings suggest that a more prudent attitude toward antibiotic prescribing may have become more common but also highlight relevant gaps in both physicians’ and public knowledge of antibiotics and AMR. To reinforce awareness and close remaining gaps, Hungary should adopt its national AMR National Action Plan and further increase its efforts towards active professional communication and feedback for primary care physicians.

• Health policy
• Public health
• GENERAL MEDICINE (see Internal Medicine)

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No data are available. With regard to confidentiality required for the ethical approval of this study, the research data are not directly available.

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https://doi.org/10.1136/bmjopen-2023-081574

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STRENGTHS AND LIMITATIONS OF THIS STUDY

The study followed a rigorous qualitative methodology anchored in behaviour change theory.

Our stratified maximum variance sampling strategy assured breadth in terms of representing different situations.

The relatively small sample size precludes generalisability.

As participation was voluntary, there could be possible selection bias where participants choosing to participate were already aware of and interested in antimicrobial resistance.

The misuse of antibiotics, including unnecessary or suboptimal treatment, can cause patient harm. In addition, inappropriate antibiotic use is a leading cause of development of antimicrobial resistance (AMR). 1 Known as the silent pandemic, AMR represents 1 of the 10 major global threats to humanity today. AMR endangers antibiotics’ therapeutic benefit and imposes an avoidable cost burden on healthcare systems. 2

While Hungary has developed, but is still to adopt its National Action Plan on AMR, recommended by the WHO, an evidence brief for policy on antibiotic misuse in Hungary identified multiple contributing factors including inappropriate prescribing practices, public misconceptions, prescribing pressure from patients, unavailability of certain narrow-spectrum antibiotics, healthcare system resource deficiencies and marketing by pharmaceutical companies. 3 One policy solution advanced in the brief is increasing the awareness of health practitioners and the general public about rational antibiotic use and AMR. This is in line with the priorities of the WHO Global Action Plan on AMR. 4

Analysis of Hungarian health insurance data on publicly reimbursed antibiotics (circa 95% of the total dispensed) shows children as the highest consumers of antibiotics, mostly prescribed broad-spectrum antibiotics. Children are an important patient group, as they often suffer from viral infections, particularly viral respiratory tract infections (RTIs) not requiring antibiotic therapy. More than 70% of community antibiotic prescriptions in Hungary are written by general practitioners (GPs). GPs in Hungary work in three types of practices: adult-only, mixed (adult–paediatric) and paediatric practices. Adult-only and mixed practices are served by physicians with general practice or related specialisations (eg, internal medicine). On the other hand, general practice paediatricians (GP Peds) specialise in paediatrics before starting to work in dedicated paediatric practices. Adult practice GPs have the highest share of all antibiotic prescriptions in the country (35%), but GP Peds and GPs in mixed adult and paediatric practices prescribe the most antibiotics per doctor. Antibiotic dispensing data analysis details are presented in online supplemental file 1 . 5

Supplemental material

In light of the antibiotic prescribing data and policy brief findings, research was conducted on Hungarian GP Peds’ prescribing behaviour. The WHO Regional Office for Europe supported this pilot study under the Tailoring Antimicrobial Resistance Programmes (TAP) process, developed to support Member States in developing interventions to address the spread of AMR.

Study goals and objectives

The study aimed to identify factors affecting GP Peds’ behaviour of prescribing antibiotics for suspected RTIs and drivers and barriers to appropriate prescribing.

Research objectives were to collect data on GP Peds’:

Diagnostic process for suspected RTIs.

Decision-making on antibiotic prescribing.

Choice of active agent prescribed.

Views on appropriate interventions to improve antibiotic prescription behaviour.

This article reports results for the first three objectives related directly to antibiotic prescribing behaviour.

Following the TAP approach, research was built on the Behaviour Change Wheel (BCW) model to develop public health interventions to target identified health behaviour barriers and drivers. BCW is grounded in the capability–opportunity–motivation–behaviour (COM-B) theory, 6 which holds that individuals’ performance of specific public health behaviours is influenced by three inter-related factors: capability, availability and motivation. Capability refers to individuals’ knowledge or skill to perform the behaviour, such as a GP’s awareness of antibiotic resistance. Opportunity addresses contextual factors external to the individual, such as the availability of narrow-spectrum antibiotics or social attitudes toward antibiotics. Motivation concerns individuals’ decision-making on behaviour performance, such as a GP’s consideration of workload, patient demands and personal attitudes.

Sampling and recruitment

Existing data showed GP Peds’ prescription habits differed across groups. A maximum variation, stratified sampling strategy 7 was thus used to increase the diversity of responses. Quotas were set to aim for equal distribution by strata of sex and geographical location, and distribution by age to reflect national statistics of GP Peds’ prescription ratios. All GP practices in Hungary are funded by the National Health Insurance Fund, which randomly sampled GP Peds in their contracting database from lists created according to the strata mentioned above. As privacy protection rules precluded access to data on age, the year of graduation was used as a proxy, assuming the average age of graduation as being 24 years.

The randomly selected GPs were contacted by researchers using a publicly available contact database. Non-respondents were replaced with a similar-profile GP from the list. Those agreeing to participate were contacted directly by the interviewers via telephone or email to make an appointment for an interview.

Data collection

Data were collected via semistructured interviews. The interview guide ( online supplemental file 2 ) was based on a review of guides from other qualitative studies on antibiotic prescribing/use. 8–16 The WHO Regional Office for Europe supported interview guide development and researcher training on conducting qualitative data collection and analysis. Interview guides explored factors influencing GP Peds’ prescribing, namely: their knowledge and experience; external actors, such as parents, peers, pharmaceutical sales representatives or public policy; and their personal considerations. Interviews were conducted in Hungarian, tape-recorded and transcribed verbatim. Due to the COVID-19 pandemic, interviews were conducted via telephone or other virtual platforms instead of face-to-face.

Data analysis

This study was conducted in accordance with the Consolidated criteria for Reporting Qualitative research statement 17 ( online supplemental file 3 ). Transcripts were analysed using a deductive framework approach to identify emerging themes. 18 19 Data in the form of participants’ words, statements and ideas were analysed to recognise themes relating to GP Peds’ prescribing behaviour. Data were analysed by five researchers, using a coding framework that was developed based on an initial sample of transcripts, and continuously updated through a consensus. Coded transcript segments were copied into a shared document, organised by themes derived from the COM-B theory, and subheadings were developed through a consensus based on emerging themes. Each finding was represented through exemplary quotations taken from participant responses.

Following initial thematic data analysis, a second COM-B analysis was conducted to consider findings on barriers and drivers to GP Peds’ prescribing behaviour. One researcher reviewed initial findings and identified COM-B themes in the data. Results were verified and refined by researchers who conducted data collection and initial analysis.

Study population

22 GP Ped interviews were conducted between July and December 2021. The participant breakdown is presented in table 1 . Original strata quotas could not be exactly met due to participant refusals (n=20). Female participants were in a slight majority (59.1%). The majority of participants were mid-career doctors (63.6%), which did not deviate significantly from the envisioned 55% quota. The number of early-career doctors interviewed (n=2) was below the envisioned target of 15%. The maximum variation sample was originally composed to represent even distribution among low-prescription, medium-prescription and high-prescription counties, and the capital region of Budapest and Pest County. However, low-prescription counties were over-represented (n=10, 45.5%) in the final sample compared with high-prescription counties (n=3, 13.6%).

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Participant breakdown by sex, age and geography

Findings on prescribing behaviour

GP Peds’ antibiotic prescription behaviour was analysed thematically around: (1) the diagnostic process to assess the presence of a bacterial infection; (2) the choice of when to prescribe or not to prescribe antibiotics; and (3) the choice of which antibiotic agent to use. There was a high level of diversity in prescription behaviour among participants. Some patterns were identified, but did not always correlate with participants’ age, sex or geographical location. The main thematic findings on behaviour are summarised in table 2 .

Summary of main themes relative to prescription behaviour

Diagnostic process

Diagnostics are key to accurately determine disease aetiology (ie, viral infections or bacterial infections indicating the need for antibiotic use). Physical examination took precedence for all participants and was almost the only method of diagnosis for some, especially older GP Peds relying on decades-long clinical experience.

I examine [the children], listen to them, look at them, and put that couple of years’ experience in it. (late-career male doctor, Budapest/Pest County) OK, there are these [point-of-care] tests for laboratory examination, but I don’t have such a machine, but with 41-years experience, I look at [the child’s] tonsil, and … can estimate if it is Streptococcus , Haemophilus , or another infection. (late-career male doctor, high-prescription county)

In a minority of cases, physical examination was complemented with laboratory blood testing and/or microbiological testing. Laboratory blood testing was mainly used for targeted mononucleosis diagnosis, but some participants used it for more general purposes, such as C reactive protein testing or long-lasting infections diagnosis. Microbiological testing was mentioned less frequently. Some respondents used it for pathogen determination. Point-of-care testing (POCT) was also rare. Several participants indicated the availability of, and having used, POCT equipment in the past, but having given it up or seldomly using it due to a lack of time or financial reasons. In the case of suspected community-acquired pneumonia, some respondents referred to ambulatory X-ray examination, while others preferred direct reference to a hospital ward.

Decision to prescribe antibiotics

All participants claimed not to prescribe antibiotics for presumably viral infections, with some also specifying when they refrain from prescribing. Several claimed prescribing antibiotics only on few occasions, and some emphasised that their antibiotic prescribing had decreased in recent years. Some mentioned specific symptoms considered in deciding on antibiotic prescription, though symptoms listed differed between respondents.

I don’t immediately start an antibiotic when I don’t see patches, and only a red, swollen tonsil. Sinusitis is excluded below five and upper respiratory tract infections are mostly viral, so I give a lot of consideration to whether an antibiotic is needed or not. (mid-career female doctor, low-prescription county) …for tonsillitis follicularis, we usually give an antibiotic without delay… If we’ve heard something [in the respiratory tract], then we almost always prescribe antibiotics. (late-career male doctor, medium-prescription county)

Almost all participants said they waited a couple of days from symptom onset before prescribing antibiotics, allowing for an immune system response to infection. Some referred children to diagnostics or recommend symptomatic treatment. Some also issue delayed prescriptions to parents in specific cases.

[for] lengthy viral infection… parents can tolerate [waiting], so let’s have a blood test first… and we can manage 2 days for results [without antibiotics]. (mid-career male doctor, medium-prescription county)

Choice of antibiotic agent

Most participants decided on an antibiotic agent considering the type and severity of symptoms, generally starting with narrow-spectrum penicillin, followed by extended-spectrum penicillin combinations, cephalosporins (mainly second and sometimes third generation), and finally macrolides and other antibiotics. There was individual variation in importance ascribed to these groups of antibiotics.

For tonsillitis, we always start with [narrow-spectrum] penicillin… If the penicillin was not initially appropriate, or then for otitis, I usually choose amoxicillin-clavulanic acid or cefixime… These last years, in cases [of atypical pathogens], I prefer [medicines] containing azithromycin taken once a day, and if [children] get on well, a 3-day course may be enough… (early-career female doctor, low-prescription county).

Some GP Peds, especially in low-prescription counties, reported using narrow-spectrum penicillin often, while others started treatment with amoxicillin or amoxicillin–clavulanic acid combinations. Some GPs were open to using cephalosporins, while others said they used them less compared with when first introduced on the market. While most respondents only used macrolides for atypical infections, some reported using them more frequently. Respondents also indicated the decision on active agents could be influenced by factors such as the child’s age or frequency of administration, which could influence compliance.

For upper respiratory tract [infections], [I use] cephalosporines and [maybe] ampicillin clavulanic acid combinations… [for] bronchitis, or in the viral winter period with all sorts of bronchitis and laryngitis, then I like using sulphonamides… Then Suprax [cefixime, third generation cephalosporine] in tablets or as syrup, for renal or respiratory things. (late-career female doctor, medium-prescription county) Obviously, the child’s age is a criterion, especially if less than 1 year-old, because there are antibiotics I cannot give below 6 or 3 months… (mid-career male doctor, low-prescription county). At second place, maybe [I prescribe] cephalosporins, mainly because they should be administered once a day and the course is short… 5 days… (mid-career male doctor, high-prescription county).

Findings on COM-B factors affecting prescribing behaviour

Findings presented some potential COM-B-related barriers and drivers to appropriate prescribing behaviour.

Participants’ belief that their experience grants them sufficient expertise to diagnose and treat RTIs could both be a driver and a barrier. This confidence could be leveraged to encourage appropriate prescribing but could also indicate knowledge gaps on AMR and in prescribing guidelines. It should be noted that clinical protocols for outpatient antibiotic treatment exist for eight common types of infection in Hungary. However, these protocols are not officially promulgated, so some practitioners rely on international guidelines instead. Participants’ widely varying attitudes toward different antibiotics could also indicate gaps in knowledge and/or use of existing guidelines. Regarding sources of information, participants reported receiving information via conferences, continuing education, professional newsletters and websites, and outreach from medical sales representatives, which reinforced their existing perceptions.

The knowledge I have is completely sufficient, so I don’t feel a need for anything [like additional education or training]. (late-career female doctor, medium-prescription county) I read these guidelines, but to be honest, the last one I read was about 5 years ago. (mid-career male doctor, low-prescription county) [Amoxicillin] is recommended in the [national] protocols, and sometimes I also consult international guidelines… [like] the European Paediatric Association… [and an] English paediatric website, I don’t remember its name. (mid-career female doctor, Budapest/Pest County)

Opportunity

A significant finding related to opportunity concerns barriers to using laboratory blood testing, microbiological testing and POCT. Respondents indicated they were not used frequently due to the long turnaround times and, in the case of POCT, the lack of time during appointments and lack of reimbursement. A social opportunity barrier was identified in the form of social attitudes to antibiotics and compliance with doctors’ recommendations. Participants indicated parents could influence prescription behaviour based on economic grounds, such as not having sick leave, or because of a lack of awareness or education. However, several respondents noted a post-pandemic trend following the period of telemedicine, with parental attitudes moving away from antibiotics and the majority of parents accepting doctors’ recommendations.

There is… [a] social class for whom it’s difficult to explain that the child can heal even after 1 week, and that it can be a viral infection. But otherwise even with them, with time… one can make progress. (early-career female doctor in a low-prescription county) Parents today don’t like unnecessary antibiotic prescription. They even condemn the doctor who immediately prescribes an antibiotic, saying they don’t like it, they don’t agree with it. There’s no more pressure to give antibiotics like there was, say, 15 years ago. (mid-career female doctor, low-prescription county)

Participants’ responses presented two motivation-related findings. First, respondents are focused on effective treatment and make risk-averse decisions to avoid complications or ineffective treatment in the short term. In this case, awareness of the problem of AMR was reported by some as a reason to prescribe wide-spectrum antibiotics to avoid treatment failure. This barrier is related to a knowledge gap, where patient outcomes’ connection to AMR can seem distant and difficult to grasp. Second, participants make prescription decisions based on personal views of symptoms and antibiotics, taking into account the individual nature of each patient (eg, potential consequences regarding side effects, deterioration of the microbiome, tastes).

I don’t really prescribe simple penicillin. I also don’t give, like some guidelines recommend, a small dose of amoxicillin first, and then if [the infection] doesn’t respond to that, give a higher [dose]. I find this quite risky… With pneumonia, after 3 days I increase, and after 6 days I have therapeutic failure. I don’t really see the point in this. We know that some Pneumococci only respond to a higher dose, so I give a normal [dose of] beta-lactam, and then I know there won’t be such a problem. (mid-career male doctor, medium-prescription county)

Consideration on findings

The study’s findings on GP Peds’ antibiotic prescribing for suspected RTIs revealed that practitioners rely mainly on physical examination of the patient for making diagnosis, with mid-career and late-career doctors having high confidence in this method, based on their experience. Despite availability, fewer participants reported using laboratory blood testing, microbiological testing or POCT, though early-career doctors were more likely to use targeted blood and microbiological testing. The lack of time is a contextual barrier that was identified, contributing to the lack of uptake of available testing options, which could suggest a need for further training or adjustments to practices to facilitate and encourage testing use. In other recent studies, time and patient pressure were similarly found to impact prescribing behaviour, particularly by favouring more frequent prescribing of broad-spectrum antibiotics. 20 21

Most participants indicated prescribing very few antibiotics, prescribing less over the last few years and not prescribing antibiotics for viral infections. A decreasing trend can also be seen in national data for antibiotic consumption in the community (primary and secondary outpatient care combined), but the rate of this was moderate until the COVID-19 pandemic. 22 Some studies suggest that public health awareness campaigns, clinical guidelines and continuing education resources for clinicians can help combat overprescribing among early-career physicians, especially in cases of conflicting prescribing practices and advice from more senior colleagues. 23 Additionally, while the COVID-19 pandemic has led to an increase in the use of broad-spectrum antibiotics in some cases, research shows that, in some primary care settings, antimicrobial consumption decreased during the first wave in multiple countries. 24 25 Similar trends of a decrease in antibiotic use at the community level have been reported in Hungary. 26 Risk avoidance and diagnostic uncertainty have been noted as important themes for the prescription of antibiotics in multiple cases in several countries, 21 which is in line with early-career doctors’ tendency to rely on diagnostic testing compared with mid-career and late-career doctors who reported high confidence in their diagnostic capabilities.

The decision to prescribe antibiotics was reportedly made several days after symptoms appear, though variation was found in the symptoms for which respondents would prescribe, as well as in the choice of antibiotic prescribed. Many participants made prescribing decisions based on their perceptions of the children’s context, potential compliance and consideration of the short-term effectiveness of treatment. These findings could suggest barriers in the form of knowledge gaps, and a risk-averse approach to patient treatment, focusing on a patient’s short-term outcomes, as observed in other contexts. 27 28 Potential ways to address such barriers include training and education on appropriate prescribing, balancing longer-term AMR and shorter-term effectiveness considerations. 29

Strengths and weaknesses of the study

This study fills an important gap, as no prior qualitative research on the determinants of prescribing behaviour among a high-prescribing population has been conducted in Hungary. One strength of the study is the use of rigorous qualitative methodology in following behaviour change theory to inform study design and data collection and analysis.

While our stratified maximum variance sampling strategy assured breadth in terms of different situations represented, the relatively small sample size precludes generalisability. However, the robust adherence to theory-based methodology ensures that results express relevant dynamics affecting practitioners’ behaviour, which raises further questions for enquiry relevant to policy decisions. As participation was voluntary, there could be a possible selection bias with participants who are already aware of and interested in AMR choosing to participate. An additional limitation is that research had been planned prior to, but conducted during, the global COVID-19 pandemic.

We cannot assert that thematic saturation was achieved; hence, there is a possibility of additional themes that were not identified in this study. Another limitation is that research participants were not given the opportunity to provide feedback on the conclusions of this paper, which raises the possibility of misinterpretation of some of their statements. However, a separate and more detailed research report in Hungarian will be disseminated among the research participants for their comments. Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Hungarian GP Peds participating in this qualitative study demonstrated varying antibiotic prescription preferences for children with RTI. Their knowledge about antibiotics and the treatment of infections stems from diverse sources, but personal experience has a key role. They also reported different levels of access to diagnostic tools, including laboratory blood testing, microbiological testing and POCT, but physical examination was the key element of their diagnostic approach, in any case. They put great emphasis on treating children in their entirety, taking into account their personal medical record, social background and, sometimes, their preferences. Most of them are also confident that they apply the most effective therapy, despite eventual pressure from parents. Importantly, several doctors have the impression that antibiotic prescription is less frequent than it used to be and that parents themselves are less likely to ask for it. These findings reflect positive trends in the attitudes of both physicians and the general population, but also reveal gaps in knowledge and opportunity. To reinforce this trend and close remaining gaps, in accordance with the WHO Global Action Plan on AMR, Hungary should adopt its National Action Plan on AMR, publish official guidelines on antibiotic use, and further increase its efforts towards active professional communication and feedback for primary care physicians.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

Participation was voluntary and all participants provided written consent prior to research. All transcripts were anonymised using pseudonyms, preventing participant identification. Audio recordings and transcripts were respectively deleted upon transcription and analysis. Research was conducted in accordance with the Declaration of Helsinki as well as national and European Union regulation. Ethical approval was granted by the Hungarian Health Sciences Council Scientific and Research Ethics Committee (30752-2/2019/EKU) and WHO Research Ethics Review Committee (ERC.0003230).

Acknowledgments

The authors would like to thank Katalin Szeberényi, Katalin Szőnyi, Pálma Sipos and Éva Jónyer for the preparation of transcripts; Ponnu Padiyara (WHO HQ) for her support in training the research team in qualitative research methods; and Szabolcs Szigeti (WHO Country Office Hungary), as well as Andrea Kurcz and the leadership of the National Public Health Center (currently National Center for Public Health and Pharmacy) for their coordination and support to the project. Additionally, they would like to thank Paul Csagoly for his contributions to editing of the manuscript.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1
• Data supplement 2
• Data supplement 3
• Data supplement 4

Contributors BB—analysing exploratory data, preparing the study protocol, conducting and analysing interviews, drafting the manuscript. ÁH—preparing the study protocol, conducting and analysing interviews, reviewing the manuscript. RB—analysing exploratory data, conducting interviews, reviewing the manuscript. MM—analysing exploratory data, conducting interviews, reviewing the manuscript. ESzSz—analysing interviews. RP—analysing exploratory data, preparing the study protocol. PA—reviewing and complementing the manuscript. KK—technical oversight, protocol revision, project coordination. DLFW—technical oversight, protocol revision, project coordination. SKW—training researchers and interviewers, supervising the project, reviewing and complementing the study protocol, reviewing and complementing the manuscript. BB is the guarantor.

Funding This work was funded by grants provided by the Ministries of Health of Germany and the Kingdom of the Netherlands, and by the European Commission. The WHO Control of Antimicrobial Resistance Programme, under the Division of Country Health Programmes, was the recipient of these grants and coordinated the development of this work in cooperation with the National Public Health Center (currently National Center for Public Health and Pharmacy) of Hungary.

Disclaimer The author is a staff member of the World Health Organization. The author alone is responsible for the views expressed in this publication and they do not necessarily represent the views, decisions or policies of the World Health Organization.

The funders had no role in data collection, analysis or interpretation of data. Some of the authors are members of the World Health Organization. These authors alone are responsible for the views expressed in this publication and theydo not necessarily represent the views, decisions or policies of the World Health Organization.

Competing interests The National Center for Public Health and Pharmacy received funding and language editing support from the WHO Regional Office for Europe, for conducting this piece of research and preparing this manuscript.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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