Qualitative Research: Characteristics, Design, Methods & Examples
Lauren McCall
MSc Health Psychology Graduate
MSc, Health Psychology, University of Nottingham
Lauren obtained an MSc in Health Psychology from The University of Nottingham with a distinction classification.
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Qualitative research is a type of research methodology that focuses on gathering and analyzing non-numerical data to gain a deeper understanding of human behavior, experiences, and perspectives.
It aims to explore the “why” and “how” of a phenomenon rather than the “what,” “where,” and “when” typically addressed by quantitative research.
Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research involves researchers interpreting data to identify themes, patterns, and meanings.
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Qualitative research can be used to:
- Gain deep contextual understandings of the subjective social reality of individuals
- To answer questions about experience and meaning from the participant’s perspective
- To design hypotheses, theory must be researched using qualitative methods to determine what is important before research can begin.
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?
Characteristics
Naturalistic setting.
Individuals are studied in their natural setting to gain a deeper understanding of how people experience the world. This enables the researcher to understand a phenomenon close to how participants experience it.
Naturalistic settings provide valuable contextual information to help researchers better understand and interpret the data they collect.
The environment, social interactions, and cultural factors can all influence behavior and experiences, and these elements are more easily observed in real-world settings.
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).
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).
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 research setting (Scarduzio, 2017).
Interpretive analysis
In qualitative research, interpretive analysis is crucial in making sense of the collected data.
This process involves examining the raw data, such as interview transcripts, field notes, or documents, and identifying the underlying themes, patterns, and meanings that emerge from the participants’ experiences and perspectives.
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.
Phase | |
---|---|
1. Gather and transcribe data | Gather raw data, for example interviews or focus groups, and transcribe audio recordings fully |
2. Familiarization with data | Read and reread all your data from beginning to end; note down initial ideas |
3. Create initial codes | Start identifying preliminary codes which highlight important features of the data and may be relevant to the research question |
4. Create new codes which encapsulate potential themes | Review initial codes and explore any similarities, differences, or contradictions to uncover underlying themes; create a map to visualize identified themes |
5. Take a break then return to the data | Take a break and then return later to review themes |
6. Evaluate themes for good fit | Last opportunity for analysis; check themes are supported and saturated with 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.
1. 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).
2. 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).
3. 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).
4. 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.
The exploratory nature of qualitative research helps generate hypotheses that can be tested quantitatively (Busetto et al., 2020).
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.
While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions.
By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.
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.
What is narrative analysis?
Narrative analysis is a qualitative research method used to understand how individuals create stories from their personal experiences.
There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.
Researchers can use different methods together to explore a research question.
Some narrative researchers focus on the content of what is said, using thematic narrative analysis, while others focus on the structure, such as holistic-form or categorical-form structural narrative analysis. Others focus on how the narrative is produced and performed.
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- v.56(1); 2023 Jan
Qualitative Research in Healthcare: Necessity and Characteristics
1 Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
2 Ulsan Metropolitan City Public Health Policy’s Institute, Ulsan, Korea
3 Department of Nursing, Chung-Ang University, Seoul, Korea
Eun Young Choi
4 College of Nursing, Sungshin Women’s University, Seoul, Korea
Seung Gyeong Jang
5 Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea
Quantitative and qualitative research explore various social phenomena using different methods. However, there has been a tendency to treat quantitative studies using complicated statistical techniques as more scientific and superior, whereas relatively few qualitative studies have been conducted in the medical and healthcare fields. This review aimed to provide a proper understanding of qualitative research. This review examined the characteristics of quantitative and qualitative research to help researchers select the appropriate qualitative research methodology. Qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions. Qualitative research is conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants and data collection methods, (5) data analysis and description of findings, and (6) research validation. This review can contribute to the more active use of qualitative research in healthcare, and the findings are expected to instill a proper understanding of qualitative research in researchers who review qualitative research reports and papers.
Graphical abstract
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INTRODUCTION
The definition of research varies among studies and scholars, and it is difficult to devise a single definition. The Oxford English Dictionary defines research as “a careful study of a subject, especially in order to discover new facts or information about it” [ 1 ], while Webster’s Dictionary defines research as “studious inquiry or examination - especially: investigation or experimentation aimed at the discovery and interpretation of facts, revision of accepted theories or laws in the light of new facts, or practical application of such new or revised theories or laws” [ 2 ]. Moreover, research is broadly defined as the process of solving unsolved problems to broaden human knowledge [ 3 ]. A more thorough understanding of research can be gained by examining its types and reasons for conducting it.
The reasons for conducting research may include practical goals, such as degree attainment, job promotion, and financial profit. Research may be based on one’s own academic curiosity or aspiration or guided by professors or other supervisors. Academic research aims can be further divided into the following: (1) accurately describing an object or phenomenon, (2) identifying general laws and establishing well-designed theories for understanding and explaining a certain phenomenon, (3) predicting future events based on laws and theories, and (4) manipulating causes and conditions to induce or prevent a phenomenon [ 3 ].
The appropriate type of research must be selected based on the purpose and topic. Basic research has the primary purpose of expanding the existing knowledge base through new discoveries, while applied research aims to solve a real problem. Descriptive research attempts to factually present comparisons and interpretations of findings based on analyses of the characteristics, progression, or relationships of a certain phenomenon by manipulating the variables or controlling the conditions. Experimental or analytical research attempts to identify causal relationships between variables through experiments by arbitrarily manipulating the variables or controlling the conditions [ 3 ]. In addition, research can be quantitative or qualitative, depending on the data collection and analytical methods. Quantitative research relies on statistical analyses of quantitative data obtained primarily through investigation and experiment, while qualitative research uses specific methodologies to analyze qualitative data obtained through participant observations and in-depth interviews. However, as these types of research are not polar opposites and the criteria for classifying research types are unclear, there is some degree of methodological overlap.
What is more important than differentiating types of research is identifying the appropriate type of research to gain a better understanding of specific questions and improve problems encountered by people in life. An appropriate research type or methodology is essential to apply findings reliably. However, quantitative research based on the philosophical ideas of empiricism and positivism has been the mainstay in the field of healthcare, with academic advancement achieved through the application of various statistical techniques to quantitative data [ 4 ]. In particular, there has been a tendency to treat complicated statistical techniques as more scientific and superior, with few qualitative studies in not only clinical medicine, but also primary care and social medicine, which are relatively strongly influenced by the social sciences [ 5 , 6 ].
Quantitative and qualitative research use different ways of exploring various social phenomena. Both research methodologies can be applied individually or in combination based on the research topic, with mixed quantitative and qualitative research methodologies becoming more widespread in recent years [ 7 ]. Applying these 2 methods through a virtuous cycle of integration from a complementary perspective can provide a more accurate understanding of human phenomena and solutions to real-world problems.
This review aimed to provide a proper understanding of qualitative research to assist researchers in selecting the appropriate research methodology. Specifically, this review examined the characteristics of quantitative and qualitative research, the applicability of qualitative research, and the data sources collected and analyzed in qualitative research.
COMPARISON OF QUALITATIVE AND QUANTITATIVE RESEARCH
A clearer understanding of qualitative research can be obtained by comparing qualitative and quantitative research, with which people are generally familiar [ 8 , 9 ]. Quantitative research focuses on testing the validity of hypotheses established by the researcher to identify the causal relationships of a specific phenomenon and discovering laws to predict that phenomenon ( Table 1 ). Therefore, it emphasizes controlling the influence of variables that may interfere with the process of identifying causality and laws. In contrast, qualitative research aims to discover and explore new hypotheses or theories based on a deep understanding of the meaning of a specific phenomenon. As such, qualitative research attempts to accept various environmental factors naturally. In quantitative research, importance is placed on the researcher acting as an outsider to take an objective view by keeping a certain distance from the research subject. In contrast, qualitative research encourages looking inside the research subjects to understand them deeply, while also emphasizing the need for researchers to take an intersubjective view that is formed and shared based on a mutual understanding with the research subjects.
Comparison of methodological characteristics between quantitative research and qualitative research
Characteristics | Quantitative research | Qualitative research |
---|---|---|
Research purpose | Test the validity of the hypotheses established by the researcher to identify the causal relationships and laws of the phenomenon and predict the phenomenon | Discover and explore new hypotheses or theories based on a deep understanding of the meaning of the phenomenon |
Perspective on variables | View factors other than the variables of interest as factors to be controlled and minimize the influence of confounding factors | View factors as natural and accept assessments in a natural environment |
Research view | Objective, outsider view | Intersubjective, insider view |
Data used | Quantifiable, measurable data | Narrative data that can be expressed by words, images and so on |
Data collection method | Primarily questionnaire surveys or tests | Primarily participant observation, in-depth interviews, and focus group discussions |
Nature of data and depth of analysis | Focus on superficial aspects of the phenomenon by using reliable data obtained through repeated measurements | The aim is to identify the specific contents, dynamics, and processes inherent within the phenomenon and situation using deep and rich data |
Strengths and weaknesses | High reliability and generalizability | High validity |
Difficulties with in-depth analysis of dynamic phenomena that cannot be expressed by numbers alone; difficulties in interpreting the results analyzed by numbers | Weak generalizability; interjection of subjectivity of the researcher is inevitable |
The data used in quantitative research can be expressed as numerical values, and data accumulated through questionnaire surveys and tests are often used in analyses. In contrast, qualitative research uses narrative data with words and images collected through participant observations, in-depth interviews, and focus group discussions used in the analyses. Quantitative research data are measured repeatedly to enhance their reliability, while the analyses of such data focus on superficial aspects of the phenomenon of interest. Qualitative research instead focuses on obtaining deep and rich data and aims to identify the specific contents, dynamics, and processes inherent within the phenomenon and situation.
There are clear distinctions in the advantages, disadvantages, and goals of quantitative and qualitative research. On one hand, quantitative research has the advantages of reliability and generalizability of the findings, and advances in data collection and analysis methods have increased reliability and generalizability. However, quantitative research presents difficulties with an in-depth analysis of dynamic phenomena that cannot be expressed by numbers alone and interpreting the results analyzed in terms numbers. On the other hand, qualitative research has the advantage of validity, which refers to how accurately or appropriately a phenomenon was measured. However, qualitative research also has the disadvantage of weak generalizability, which determines whether an observed phenomenon applies to other cases.
APPLICATIONS OF QUALITATIVE RESEARCH AND ITS USEFULNESS IN THE HEALTHCARE FIELD
Qualitative research cannot be the solution to all problems. A specific methodology should not be applied to all situations. Therefore, researchers need to have a good understanding of the applicability of qualitative research. Generally, qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions [ 7 ]. In particular, qualitative research is useful for opening new fields of research, such as important topics that have not been previously examined or whose significance has not been recognized. Moreover, qualitative research is advantageous for examining known topics from a fresh perspective.
In the healthcare field, qualitative research is conducted on various topics considering its characteristics and strengths. Quantitative research, which focuses on hypothesis validation, such as the superiority of specific treatments or the effectiveness of specific policies, and the generalization of findings, has been the primary research methodology in the field of healthcare. Qualitative research has been mostly applied for studies such as subjective disease experiences and attitudes with respect to health-related patient quality of life [ 10 - 12 ], experiences and perceptions regarding the use of healthcare services [ 13 - 15 ], and assessments of the quality of care [ 16 , 17 ]. Moreover, qualitative research has focused on vulnerable populations, such as the elderly, children, disabled [ 18 - 20 ], minorities, and socially underprivileged with specific experiences [ 21 , 22 ].
For instance, patient safety is considered a pillar of quality of care, which is an aspect of healthcare with increasing international interest. The ultimate goal of patient safety research should be the improvement of patient safety, for which it is necessary to identify the root causes of potential errors and adverse events. In such cases, qualitative rather than quantitative research is often required. It is also important to identify whether there are any barriers when applying measures for enhancing patient safety to clinical practice. To identify such barriers, qualitative research is necessary to observe healthcare workers directly applying the solutions step-by-step during each process, determine whether there are difficulties in applying the solutions to relevant stakeholders, and ask how to improve the process if there are difficulties.
Patient safety is a very broad topic, and patient safety issues could be categorized into preventing, recognizing, and responding to patient safety issues based on related metrics [ 23 ]. Responding to issues that pertain to the handling of patient safety incidents that have already occurred has received relatively less interest than other categories of research on this topic, particularly in Korea. Until 2017, almost no research was conducted on the experiences of and difficulties faced by patients and healthcare workers who have been involved in patient safety incidents. This topic can be investigated using qualitative research.
A study in Korea investigated the physical and mental suffering experienced during the process of accepting disability and medical litigation by a patient who became disabled due to medical malpractice [ 21 ]. Another qualitative case study was conducted with participants who lost a family member due to a medical accident and identified psychological suffering due to the incident, as well as secondary psychological suffering during the medical litigation process, which increased the expandability of qualitative research findings [ 24 ]. A quantitative study based on these findings confirmed that people who experienced patient safety incidents had negative responses after the incidents and a high likelihood of sleep or eating disorders, depending on their responses [ 25 ].
A study that applied the grounded theory to examine the second victim phenomenon, referring to healthcare workers who have experienced patient safety incidents, and presented the response stages experienced by second victims demonstrated the strength of qualitative research [ 26 ]. Subsequently, other studies used questionnaire surveys on physicians and nurses to quantify the physical, mental, and work-related difficulties experienced by second victims [ 27 , 28 ]. As such, qualitative research alone can produce significant findings; however, combining quantitative and qualitative research produces a synergistic effect. In the healthcare field, which remains unfamiliar with qualitative research, combining these 2 methodologies could both enhance the validity of research findings and facilitate open discussions with other researchers [ 29 ].
In addition, qualitative research has been used for diverse sub-topics, including the experiences of patients and guardians with respect to various diseases (such as cancer, myocardial infarction, chronic obstructive pulmonary disease, depression, falls, and dementia), awareness of treatment for diabetes and hypertension, the experiences of physicians and nurses when they come in contact with medical staff, awareness of community health environments, experiences of medical service utilization by the general public in medically vulnerable areas, the general public’s awareness of vaccination policies, the health issues of people with special types of employment (such as delivery and call center workers), and the unmet healthcare needs of persons with vision or hearing impairment.
GENERAL WORKFLOW OF QUALITATIVE RESEARCH
Rather than focusing on deriving objective information, qualitative research aims to discern the quality of a specific phenomenon, obtaining answers to “why” and “how” questions. Qualitative research aims to collect data multi-dimensionally and provide in-depth explanations of the phenomenon being researched. Ultimately, the purpose of qualitative research is set to help researchers gain an understanding of the research topic and reveal the implications of the research findings. Therefore, qualitative research is generally conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants (or participation target) and data collection methods, (5) data analysis and description of findings, and (6) research validation ( Figure 1 ) [ 30 ]. However, unlike quantitative research, in which hypothesis setting and testing take place unidirectionally, a major characteristic of qualitative research is that the process is reversible and research methods can be modified. In other words, the research topic and question could change during the literature analysis process, and theoretical and analytical methods could change during the data collection process.
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General workflow of qualitative research.
Selection of a Research Topic and Question
As with any research, the first step in qualitative research is the selection of a research topic and question. Qualitative researchers can select a research topic based on their interests from daily life as a researcher, their interests in issues within the healthcare field, and ideas from the literature, such as academic journals. The research question represents a more specific aspect of the research topic. Before specifically starting to conduct research based on a research topic, the researcher should clarify what is being researched and determine what research would be desirable. When selecting a research topic and question, the research should ask: is the research executable, are the research topic and question worth researching, and is this a research question that a researcher would want to research?
Selection of Theoretical Framework and Methods
A theoretical framework refers to the thoughts or attitudes that a researcher has about the phenomenon being researched. Selecting the theoretical framework first could help qualitative researchers not only in selecting the research purpose and problem, but also in carrying out various processes, including an exploration of the precedent literature and research, selection of the data type to be collected, data analysis, and description of findings. In qualitative research, theoretical frameworks are based on philosophical ideas, which affect the selection of specific qualitative research methods. Representative qualitative research methods include the grounded theory, which is suitable for achieving the goal of developing a theory that can explain the processes involved in the phenomenon being researched; ethnographic study, which is suitable for research topics that attempt to identify and interpret the culture of a specific group; phenomenology, which is suitable for research topics that attempt to identify the nature of research participants’ experiences or the phenomenon being researched; case studies, which aim to gain an in-depth understanding of a case that has unique characteristics and can be differentiated from other cases; action research, which aims to find solutions to problems faced by research participants, with the researchers taking the same position as the participants; and narrative research, which is suitable for research topics that attempt to interpret the entire life or individual experiences contained within the stories of research participants. Other methodologies include photovoice research, consensual qualitative research, and auto-ethnographic research.
Literature Analysis
Literature analysis results can be helpful in specifically selecting the research problem, theoretical framework, and research methods. The literature analysis process compels qualitative researchers to contemplate the new knowledge that their research will add to the academic field. A comprehensive literature analysis is encouraged both in qualitative and quantitative research, and if the prior literature related to the subject to be studied is insufficient, it is sometimes evaluated as having low research potential or research value. Some have claimed that a formal literature review should not be performed before the collection of field data, as it could create bias, thereby interfering with the investigation. However, as the qualitative research process is cyclic rather than unidirectional, the majority believes that a literature review can be performed at any time. Moreover, an ethical review prior to starting the research is a requirement; therefore, the research protocol must be prepared and submitted for review and approval prior to conducting the research. To prepare research protocols, the existing literature must be analyzed at least to a certain degree. Nonetheless, qualitative researchers must keep in mind that their emotions, bias, and expectations may interject themselves during the literature review process and should strive to minimize any bias to ensure the validity of the research.
Selection of the Research Participants and Data Collection Methods
The subjects of qualitative research are not necessarily humans. It is more important to find the research subject(s) from which the most in-depth answers to the research problem can be obtained. However, the subjects in most qualitative studies are humans, as most research question focus on humans. Therefore, it is important to obtain research participants with sufficient knowledge, experience, and attitudes to provide the most appropriate answers to the research question. Quantitative research, which views generalizability as a key research goal, emphasizes the selection of research participants (i.e., the research sample that can represent the study’s population of interest), whereas qualitative research emphasizes finding research participants who can best describe and demonstrate the phenomenon of interest.
In qualitative research, the participant selection method is referred to as purposeful sampling (or purposive sampling), which can be divided into various types. Sampling methods have various advantages, disadvantages, and characteristics. For instance, unique sampling (extreme case sampling) has the advantage of being able to obtain interesting research findings by researching phenomena that have previously received little or no interest, and the disadvantage of deriving research findings that are interesting to only some readers if the research is conducted on an overly unique situation. Maximum variation sampling, also referred to as theoretical sampling, is commonly used in qualitative research based on the grounded theory. Selecting the appropriate participant sampling method that suits the purpose of research is crucial ( Table 2 ).
Sampling methods of selecting research participants in qualitative research
Sampling method | Explanation |
---|---|
Typical sampling | Selecting the most typical environment and people for the research topic |
Unique sampling (extreme case sampling) | Selecting unique and uncommon situations or subjects who satisfy the research purpose |
Maximum variation sampling | Selecting subjects showing maximum variation with a target population |
Convenience sampling | Selecting subjects who can be sampled most conveniently considering practical limitations, such as funding, time, and location |
Snowballing sampling | Selecting key research participants who satisfy the criteria established by the researcher and using their recommendations to recruit additional research participants |
Once the researcher has decided how to select study participants, the data collection methods must be determined. Just as with participant sampling, various data collection methods are available, all of which have various advantages and disadvantages; therefore, the method must be selected based on the research question and circumstances. Unlike quantitative research, which usually uses a single data source and data collection method, the use of multiple data sources and data collection methods is encouraged in qualitative research [ 30 ]. Using a single data source and data collection method could cause data collection to be skewed by researcher bias; therefore, using multiple data sources and data collection methods is ideal. In qualitative research, the following data types are commonly used: (1) interview data obtained through one-on-one in-depth interviews and focus group discussions, (2) observational data from various observation levels, (3) documented data collected from personal or public documents, and (4) image data, such as photographs and videos.
Interview data are the most commonly used data source in qualitative research [ 31 ]. In qualitative research, an interview refers to communication that takes place based on a clear sense of purpose of acquiring certain information, unlike conversations that typically take place in daily life. The level of data acquired through interviews varies significantly depending on the researcher’s personal qualifications and abilities, as well as his or her level of interest and knowledge regarding the research topic. Therefore, interviewers must be trained to go beyond simply identifying the clearly expressed experiences of research participants to exploring their inner experiences and emotions [ 32 ]. Interview data can be classified based on the level of structuralization of the data collection method, sample size, and interview method. The characteristics of each type of interview are given in Table 3 .
Detailed types of interview methods according to the characteristics of in-depth interviews and focus group discussion
Classification | Specific method | Characteristics |
---|---|---|
Level of structuralization | Structured interview | Data are collected by asking closed questions in the order provided by highly specific interview guidelines |
Useful for asking questions without omitting any details that should be checked with each research participant | ||
Leaves little room for different interpretations of the participant’s responses or expressing original thoughts | ||
Semi-structured interview | Between a structured and unstructured interview; interview guidelines are developed in advance, but the questions are not strictly set and may vary | |
The most widely used data collection method in qualitative research, as it allows interviews to be conducted flexibly depending on the characteristics and responses of the participants | ||
Researcher bias may influence the interview process | ||
Unstructured interview | The interview is conducted like a regular conversation, with extremely minimal prior information about the research topic and adherence to interview guidelines to exclude the intention for acquiring information needed for the research | |
Can obtain rich and realistic meaning and experiences of the research participants | ||
The quality of information acquired and length (duration) of interview may vary depending on the competency of the interviewer, such as conversational skills and reasoning ability | ||
Sample size | One-on-one in-depth interview | Excluding cases in which a guardian must accompany the research participant, such elderly or frail patients and children, a single participant discusses the research topic with one to two researchers during each interview session |
This data collection method is recommended for research topics that are difficult to discuss with others and suitable for obtaining in-depth opinions and experiences from individual participants | ||
The range of information that can be acquired may vary depending on the conversational skills and interview experience of the interviewer and requires a relatively large amount of effort to collect sufficient data | ||
Focus group discussion | At least 2 (generally 4–8) participants discuss the research topic during each interview session led by the researcher | |
This method is effective when conducting interviews with participants who may be more willing to open up about themselves in a group setting than when alone, such as children and adolescents | ||
Richer experiences and opinions can be derived by promoting interaction within the group | ||
While it can be an effective data collection method, there may be some limitations in the depth of the interview; some participants may feel left out or not share their opinion if 1 or 2 participants dominate the discussion | ||
Interview method | Face-to-face | The interviewer personally meets with the research participant to conduct the interview |
It is relatively easy to build rapport between the research participant and interviewer; can respond properly to the interview process by identifying non-verbal messages | ||
Cannot conduct interviews with research participants who are difficult to meet face-to-face | ||
Non-face-to-face | Interview between the interviewer and research participant is conducted through telephone, videoconferencing, or email | |
Suitable data collection method for topics that deal with political or ethical matters or intimate personal issues; in particular, email interviews allow sufficient time for the research participant to think before responding | ||
It is not easy to generate interactions between the research participant and interviewer; in particular, it is difficult to obtain honest experiences through email interviews, and there is the possibility of misinterpreting the responses |
Observations, which represent a key data collection method in anthropology, refer to a series of actions taken by the researcher in search of a deep understanding by systematically examining the appearances of research participants that take place in natural situations [ 33 ]. Observations can be categorized as participant and non-participant, insider and outsider, disguised and undisguised, short- and long-term, and structured and unstructured. However, a line cannot be drawn clearly to differentiate these categories, and the degree of each varies along a single spectrum. Therefore, it is necessary for a qualitative researcher to select the appropriate data collection method based on the circumstances and characteristics of the research topic.
Various types of document data can be used in qualitative research. Personal documents include diaries, letters, and autobiographies, while public documents include legal documents, public announcements, and civil documents. Online documents include emails and blog or bulletin board postings, while other documents include graffiti. All these document types may be used as data sources in qualitative research. In addition, image data acquired by the research participant or researcher, such as photographs and videos, serve as useful data sources in qualitative research. Such data sources are relatively objective and easily accessible, while they contain a significant amount of qualitative meaning despite the low acquisition cost. While some data may have been collected for research purposes, other data may not have been originally produced for research. Therefore, the researcher must not distort the original information contained in the data source and must verify the accuracy and authenticity of the data source in advance [ 30 ].
This review examined the characteristics of qualitative research to help researchers select the appropriate qualitative research methodology and identify situations suitable for qualitative research in the healthcare field. In addition, this paper analyzed the selection of the research topic and problem, selection of the theoretical framework and methods, literature analysis, and selection of the research participants and data collection methods. A forthcoming paper will discuss more specific details regarding other qualitative research methodologies, such as data analysis, description of findings, and research validation. This review can contribute to the more active use of qualitative research in the healthcare field, and the findings are expected to instill a proper understanding of qualitative research in researchers who review and judge qualitative research reports and papers.
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Ethics Statement
Since this study used secondary data source, we did not seek approval from the institutional review board. We also did not have to ask for the consent of the participants.
Acknowledgments
CONFLICT OF INTEREST
The authors have no conflicts of interest associated with the material presented in this paper.
AUTHOR CONTRIBUTIONS
Conceptualization: Pyo J, Lee W, Choi EY, Jang SG, Ock M. Data curation: Pyo J, Ock M. Formal analysis: Pyo J, Ock M. Funding acquisition: None. Validation: Lee W, Choi EY, Jang SG. Writing - original draft: Pyo J, Ock M. Writing - review & editing: Pyo J, Lee W, Choi EY, Jang SG, Ock M.
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Strengths and weaknesses
Strengths of qualitative research.
- Qualitative methods tend to collect very rich data in an efficient manner: rather than being limited to the responders to a set of pre-defined questions, it is possible to explore interesting concepts that can lead to novel theory by analysing the entirety of a participant’s interview/story/interaction.
- Qualitative methods can lead to the generation of new theory from unexpected findings that go against “conventional” public health understanding
- When combined with quantitative methods, qualitative research can provide a much more complete picture. For example, a well-designed process evaluation of a trial may provide important insights into participant attitudes, beliefs, and thoughts about the intervention and its acceptability, which may not be evident from the quantitative outcome evaluation.
Weaknesses of qualitative research
- It is important that qualitative researchers adhere to robust methodology in order to ensure high quality research. Poor quality qualitative work can lead to misleading findings.
- Qualitative research alone is often insufficient to make population-level summaries. The research is not designed for this purpose, as the aim is not to generate summaries generalisable to the wider population.
- Policy makers may not understand or value the interpretive position and therefore may not recognize the importance of qualitative research.
- Qualitative research can be time and labour-intensive. Conducting multiple interviews and focus groups can be logistically difficult to arrange and time consuming. Furthermore, tranalysanscription and analysis of the data (comparing, coding, and inducting) requires intense concentration and full immersion in the data – a process that can be far more time-consuming than a descriptive statistical analysis.
© I Crinson & M Leontowitsch 2006, G Morgan 2016
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Qualitative Research - SOCI8170
Looking for a different module?
Module delivery information
Location | Term | Level | Credits (ECTS) | Current Convenor | 2024 to 2025 |
---|---|---|---|---|---|
Canterbury | Spring Term | 7 | 20 (10) | Veronika Stoyanova |
This module focuses on the theory and practice of qualitative research. It explores the various aspects of using and collecting qualitative data. The aim of the module is to illustrate a range of practical techniques while considering related problems of evidence and inference in qualitative analyses. Students will be versed in a range of techniques and will have the opportunity to practice some of them, this includes • the theory and practice of interviewing and different varieties of interview; • focus groups; • oral history; • case study methods; • ethnographic theory and method; • action research; • critical discourse analysis; • narrative analysis; • visual methods.
Contact hours
Total contact hours: 22 Private study hours: 178 Total study hours: 200
Availability
Methods of Social Research MA – compulsory module Two year Master's in Methods of Social Research MA – compulsory module Option module for other SSPSR taught MA programmes
Method of assessment
Main assessment methods Coursework assignment 1- essay (2500 words) – 50% Coursework assignment 2 – essay (2500 words) – 50% Reassessment methods Reassessment instrument- 100% coursework
Indicative reading
Barnard, M. (2001) Approaches to understanding visual culture, Palgrave. Bryman, A. (2004) Social Research Methods, Oxford University Press. Hammersley, M (1990) Reading Ethnographic Research: A Critical Guide, Longman Hesse-Bibber, S. N. & Leavy, P. (2005) Approaches to Qualitative Research; Sage. Hesse-Bibber, S. N. & Leavy, P. (2006) The Practice of Qualitative Research; Sage May, T. (2001) Social Research, Maidenhead: Open University Press. Miles, M and Huberman, M (1994) Qualitative Data Analysis: An Expanded Sourcebook, Sage. Plummer, K. (2005) Documents of life 2: An invitation to a critical humanism, Sage. Perks, R. & Thomson, A. (eds.) (1998) The Oral History Reader, Routledge. McKee, A. (2003) Textual Analysis: A beginners guide, Sage. Reason, P. and Bradbury, H. (eds.) (2001) Handbook of action research: participative inquiry and practice. Sage. Riessman, C. K. (1993). Narrative analysis, Sage. Silverman, D. (2004) Qualitative Research. Theory, Method and Practice, Sage.
See the library reading list for this module (Canterbury)
Learning outcomes
The intended subject specific learning outcomes. On successfully completing the module students will be able to: 8.1 Identify different epistemological approaches used within social science and assess their strengths and weaknesses); 8.2 Assess the generic strengths/weaknesses of qualitative methods as compared with other methodologies in social science 8.3 Understand some widely-used techniques of qualitative data collection and analysis in the social sciences, know when it is appropriate to use them and be able to assess their strengths and weaknesses 8.4 Evaluate and criticise qualitative analyses they encounter in the literature in their field 8.5 Deploy a range of qualitative techniques effectively 8.6 Present their research results in a form acceptable for publication The intended generic learning outcomes. On successfully completing the module students will be able to: 9.1 The ability to communicate research results to academic and general audiences in both written and oral media 9 9.2 The ability to manage their time, prioritise workloads and manage stress as well taking responsibility for their learning and professional development 9.3 The ability to identify and solve common problems in social research 9.4 The ability to access and evaluate ICT and library based resources appropriate for postgraduate study; make critical judgments about their merits and use the available evidence to construct a developed argument to be presented orally or in writing 9.5 Knowledge of career opportunities in their field and ability to plan for their future
Progression
This is a compulsory module for the MA in Methods of Social Research, Faculty Research Training Programme.
- Credit level 7 . Undergraduate or postgraduate masters level module.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer .
Practical Research 1 Module: Qualitative Research and Its Importance in Daily Life
This Senior High School Practical Research 1 Self-Learning Module (SLM) is prepared so that you, our dear learners, can continue your studies and learn while at home. Activities, questions, directions, exercises, and discussions are carefully stated for you to understand each lesson.
Conducting qualitative research is as significant as the necessities of human existence. It paves way to understanding the current issues and natural phenomena that greatly contribute to the lives of the people.
As a researcher, it is imperative to realize the importance of qualitative research in everyday life for this will serve as sustenance to finish the course of the study. Further, this will truly inspire anyone to pursue the fulfillment of research in the context of providing answers to questions and set a trend to the rest of the researchers.
This lesson will brace you with knowledge on kinds, characteristics, uses, strengths, and weaknesses of qualitative research. These topics are necessary as you get closer to choosing the field of research you will focus on.
Every day of our lives is a challenge. We face so many questions that sometimes cannot be answered by merely asking our neighbors or even the experts we know. As a result, we attempt to investigate about these problems ourselves. In this scenario, our knowledge in research is very important.
Among the steps we take is asking ourselves, “Why do I need to pursue the answers to these questions? Well, for that matter, you must realize that research plays a big role in the lives of the people-your family, friends, and neighbors.
TABLE OF CONTENTS
Learning Objectives:
After studying this module, you are expected to:
- describe the characteristics, strengths and weaknesses of qualitative research (CS_RS11-IIIb-1) ;
- identify the kinds of qualitative research (CS_RS11-IIIb-1) ;
- familiarize the qualitative research in different fields (CS_RS11-IIIb-2) ; and
- determine the importance of qualitative research in different fields (CS_RS11-IIIb 2) .
Senior High School Quarter 1 Self-Learning Module Practical Research 2 – Qualitative Research and Its Importance in Daily Life
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- —Qualitative Research and Its Importance in Daily Life
Self-Learning Module- Quarter 2 Practical Research 1: SHS, Modules 4-7 View Download
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Education Type | K to 12 |
Grade Level | Grade 11, Grade 12 |
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Content/Topic | Qualitative Research and Its Importance in Daily Life Understanding Data and Ways to Systematically Collect Data Analyzing the Meaning of the Data and Drawing Conclusions Reporting and Sharing the Findings |
Intended Users | Educators, Learners |
Competencies | Describes characteristics, strengths, weaknesses, and kinds of qualitative research Describes characteristics, strengths, weaknesses, and kinds of qualitative research Illustrates the importance of qualitative research across fields Chooses appropriate qualitative research design Plans data collection and analysis procedures Infers and explain patterns and themes from data Relates the findings with pertinent literature |
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Chapter 10: Qualitative Data Collection & Analysis Methods
10.7 Strengths and Weaknesses of Qualitative Interviews
As the preceding sections have suggested, qualitative interviews are an excellent way to gather detailed information. Whatever topic is of interest to the researcher can be explored in much more depth by employing this method than with almost any other method. Not only are participants given the opportunity to elaborate in a way that is not possible with other methods, such as survey research, but, in addition, they are able share information with researchers in their own words and from their own perspectives, rather than attempting to fit those perspectives into the perhaps limited response options provided by the researcher. Because qualitative interviews are designed to elicit detailed information, they are especially useful when a researcher’s aim is to study social processes, or the “how” of various phenomena. Yet another, and sometimes overlooked, benefit of qualitative interviews that occurs in person is that researchers can make observations beyond those that a respondent is orally reporting. A respondent’s body language, and even her or his choice of time and location for the interview, might provide a researcher with useful data.
As with quantitative survey research, qualitative interviews rely on respondents’ ability to accurately and honestly recall whatever details about their lives, circumstances, thoughts, opinions, or behaviors are being examined. Qualitative interviewing is also time-intensive and can be quite expensive. Creating an interview guide, identifying a sample, and conducting interviews are just the beginning of the process. Transcribing interviews is labor-intensive, even before coding begins. It is also not uncommon to offer respondents some monetary incentive or thank-you for participating, because you are asking for more of the participants’ time than if you had mailed them a questionnaire containing closed-ended questions. Conducting qualitative interviews is not only labor intensive but also emotionally taxing. Researchers embarking on a qualitative interview project with a subject that is sensitive in nature should keep in mind their own abilities to listen to stories that may be difficult to hear.
Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
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- Open access
- Published: 22 July 2024
Characteristics and quality of reporting qualitative nursing research related to the COVID-19 pandemic: a systematic search and critical review
- Ian-In Vong 1 ,
- Monique Rothan-Tondeur 1 , 2 &
- Rita Georges Nohra 1
BMC Nursing volume 23 , Article number: 498 ( 2024 ) Cite this article
153 Accesses
Metrics details
The COVID-19 (Coronavirus disease of 2019) pandemic caused major disruption to nursing research, especially qualitative research. Researchers had to overcome numerous challenges that potentially impacted the quality of the studies carried out.
The aim of this study is to assess the characteristics and quality of reporting qualitative nursing articles on the COVID-19 pandemic.
A systematic search and critical review using content analysis was conducted on published nurse-led articles using a qualitative approach related to the COVID-19 pandemic. A combination of the Consolidated Criteria for Reporting Qualitative Research (COREQ) and Standards for Reporting Qualitative Research (SRQR) checklists and additional items identified from the literature were used to assess the characteristics and overall quality of reporting of qualitative research.
Out of 63,494 articles screened, 444 met the inclusion criteria. Most studies were published in high-impact, Quartile 1 journals, with the majority originating from the USA. Common themes included workforce experiences and the impact of pandemic restrictions. Methodological quality varied, with a notable underuse of standardized reporting checklists. Despite pandemic-induced challenges in data collection, interviews remained the predominant method. However, the adoption of remote research methods and analysis software was limited.
The findings underscore the resilience and adaptability of nursing researchers during the pandemic. High-quality publications in top-tier journals indicate rigorous academic standards. However, the low utilization of reporting checklists suggests a need for greater emphasis on methodological transparency and adherence to established quality guidelines. This review highlights the importance of enhancing qualitative research practices to improve the rigor and reliability of studies, particularly in crisis contexts.
Peer Review reports
Introduction
The COVID-19 pandemic has threatened the health and well-being of global citizens which has led to a significant change in the attitude, lifestyle, and behavior of people from diverse professions [ 1 ]. Nurses have been and remain central to the pandemic––nurses are central to preventative, curative and palliative activities associated with COVID-19, and have taken these roles on in addition to their usual roles [ 2 ]. Nurses reported low job satisfaction, high levels of burnout, stress, and anxiety [ 3 ]. Researchers have experienced a decline in research motivation [ 4 ]. Scientific productivity, particularly among female academics, has suffered due to increased childcare responsibilities and psychological distress [ 5 ]. And parent researchers struggled to balance work and family responsibilities during the pandemic [ 6 ].
On the other hand, the travel restrictions and lockdown during the pandemic have undoubtedly affected all aspects of research, including qualitative research [ 7 , 8 ]. Qualitative nursing research is essential and important for understanding patient experiences, exploring complex healthcare phenomena, and guiding patient-centered care [ 9 ]. It provides insights into the subjective experiences, perceptions, and emotions of patients, families, and providers [ 10 ], bringing a holistic perspective to understanding the phenomena under study [ 11 ]. With qualitative methodologies, insight can be gained regarding the social responses to this pandemic, they are also the best methods to help explain, address, and plan for emergencies and pandemics, such as COVID-19 [ 7 , 12 , 13 ]. Restrictions during the pandemics made traditional data collection methods challenging [ 1 , 14 ]. Nurse researchers had to adapt to perform data collection in a virtual environment, shifting from face-to-face interviews to telephone or online meetings [ 1 ]; research participants were unwilling to show their faces at virtual meetings, and face-to-face interviews were only allowed with masks on [ 7 , 8 ]. These changes affected the quality and richness of data collection, missing important non-verbal elements such as attitude, gesture, and context [ 15 , 16 ].
Given the disruptive impact of the COVID-19 pandemic on nursing qualitative research activities, and deleterious effects on nurses, like emotional exhaustion [ 17 ], psychological distress [ 18 ], and burnout [ 3 , 19 ], but nurse researchers have also been very responsive to the pandemic, the Journal of Advanced Nursing has received hundreds of manuscripts focused on the pandemic, and more than 200 papers published on the COVID-19 pandemic in 2 years [ 2 ]. We doubted the quality of the publication. Scholarly journals are the most important media source for the dissemination of such research findings and information related to connecting this new evidence to practice [ 20 ] and nursing publication plays an essential role in improving nurses’ knowledge of new information and interesting this knowledge into nursing practice [ 21 ]. Together these phenomena might run the risk of producing poor quality qualitative research. Current literature provides two bibliometric analyses of COVID-19 research published in nursing journal, these provide the readers with only objective information on nursing publication related to COVID-19. The existing literature lacks comprehensive reviews that specifically focus on the characteristics and reporting quality of qualitative nursing research related to COVID-19. This study addresses this gap by providing a thorough analysis, which is crucial for guiding future research efforts and improving the overall quality of qualitative studies in nursing. By emphasizing the importance of maintaining high research quality, this study aims to contribute valuable insights that can inform future research, policymaking, and practice in nursing.
Providing a critical review of COVID-19 qualitative nursing research is an unmet need. To achieve this goal, we designed a systematic literature search including all available COVID-19 nursing qualitative articles using a large task force dedicated to the analysis of high-volume articles. We aimed at investigating the characteristics and the methodological quality assessment of reporting COVID-19 qualitative nursing publications.
We conducted a systematic literature search and a critical review using content analysis. This type of content analysis was to enable the production of measurements, occurrences, or comparisons through statistical or quantitative methods [ 22 ]. This review builds upon the methods utilized in two similar reviews [ 23 , 24 ], which assessed the characteristics of articles and described the methodological quality of the articles by presenting the percentage of compliance with each item of a standardized methodological reporting quality checklist. Our study adopted a pre-established checklist which was designed based on the Consolidated Criteria for Reporting Qualitative Research (COREQ) [ 25 ] and the Standards for Reporting Qualitative Research (SRQR) [ 26 ], along with other items identified in the literature to examine the quality of reporting in qualitative research.
This study is an ancillary study that extracted articles related to COVID-19 from the database of a large study aims to assess the characteristics and reporting quality using a qualitative approach in the field of nursing from 2012 to January 2023.
Search strategy
Several databases were consulted to ensure the inclusion of relevant studies in the field of nursing. The main databases are academic and medical databases, such as PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cairn, Embase, Web of science and Scopus. Document search strategies are developed using the MeSH thesaurus (Medical subject headings) and related keywords. The MEDLINE strategy has been developed and tested by the research team: “nursing research“[MH] OR “nursing research“[TW] OR (“nursing research“[Title/Abstract:~2]) OR nurs*[affiliation]) AND (“qualitative research“[MH] OR “qualitative research“[TIAB] OR “qualitative study“[TIAB] OR “qualitative studies“[TIAB] OR “grounded theory“[TIAB] OR “phenomenology“[TIAB] OR “ethnography“[TIAB] OR (“qualitative study“[Title/Abstract:~2] OR “qualitative studies“[Title/Abstract:~2] OR “qualitative research“[Title/Abstract:~2] OR “qualitative theory“[Title/Abstract:~2] OR “qualitative theories“[Title/Abstract:~2] OR “grounded study“[Title/Abstract:~2] OR “grounded studies“[Title/Abstract:~2] OR “grounded theory“[Title/Abstract:~2] OR “grounded theories“[Title/Abstract:~2] OR “grounded research“[Title/Abstract:~2] OR “ethnological study“[Title/Abstract:~2] OR “ethnological studies“[Title/Abstract:~2] OR “ethnological theory“[Title/Abstract:~2] OR “ethnological theories“[Title/Abstract:~2] OR “ethnological research“[Title/Abstract:~2] OR “phenomenological study“[Title/Abstract:~2] OR “phenomenological studies“[Title/Abstract:~2] OR “phenomenological theory“[Title/Abstract:~2] OR “phenomenological theories“[Title/Abstract:~2] OR “phenomenological research“[Title/Abstract:~2]. Then, a hand search was conducted to identified articles related to COVID-19. The literature search was performed between June 2023 to August 2023.
Inclusion and exclusion criteria
Any qualitative nursing research related to COVID-19 was included. The first authors must be nurses. The language was limited to English and French. Both peer-reviewed and pre-prints articles were included.
Articles related to non-human samples and full-text unavailable were excluded.
Article screening
We followed the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for article selection. All articles yielded through an initial search from the databases were exported into Rayyan Software, a web-based tool designed to conduct and coordinate systematic literature reviews. Hand search was performed to identify articles related to COVID-19, and duplicates were removed. Next, affiliations were examined to determine if the first author was a nurse, and then titles and abstracts were reviewed to determine if the publication met inclusion and exclusion criteria. Two researchers finished the screening independently. Any discrepant result was discussed by the two reviewers and resolved by consensus, or where necessary, a third researcher was involved. Finally, the articles that met the inclusion and exclusion criteria were selected for full-text reading.
Data extraction and data analysis
We used the pre-established checklist combining items from the SRQR and COREQ checklists and adding other items identified in the literature to answer the objective of this study. The checklist included 33 items seen in Tables 1 and 9 items regarding characteristics of the articles, and 24 items regarding methodological quality assessment. The checklist was pilot-tested and revised. Revisions were made after discussion among the researchers and included clarification of checklist items and the response of researchers to each item. For items of the characteristics of the articles, data were extracted to Excel (Excel 2020, Microsoft Excel, Redmond, WA, USA) for categorization. For items of methodological quality assessment, ATLAS.ti software (version 23.2.1) was used. All identified articles were imported into the software for content analysis with the use of a coding function, codes were created according to the items on the data extraction checklist, researcher read the content of the full-text articles one by one, then identified and coded the phrases according to the codes. For example, the code “field note” was created, and the researcher identified and coded the content if it is mentioned in the article. The frequency of each code was calculated to identify the methodological quality of the included articles.
Ethical considerations
This study is a review based on published articles; ethical approval was not required.
A total of 63,494 articles were registered in Rayyan software. Of these, 918 articles (1.44%) were related to COVID-19. After the exclusion of 56 articles due to duplication, the titles, and abstracts of all the articles were examined and 393 articles were excluded due to affiliations in which the first author was not a nurse. The remaining studies were reviewed in full-text. There were 20 articles excluded due to articles with a non-qualitative approach, 4 articles written in a foreign language were excluded, and 1 article was excluded because of full-texted unavailable. A total of 444 full-text articles related to COVID-19 were analyzed. The flowchart is presented in Fig. 1 .
![strengths and weaknesses of qualitative research module figure 1](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig1_HTML.png)
Flowchart of articles screening
Characteristics of the COVID-19 qualitative nursing research
The 444 included articles were published in 196 different journals, one of which was published on MedRxiv, an online pre-print platform for non-peer-reviewed research, with the most articles being published in the International Journal of Environmental Research and Public Health ( n = 28, 14.3%).
Table 2 shows the most productive journals in terms of COVID-19 nursing qualitative publications. With regard to the quartile of the journals, the studies were published most frequently in Q1 journals ( n = 260, 58.6%), followed by Q2 ( n = 118, 26.6%), Q3 ( n = 49, 11.0%), Q4 ( n = 12, 2.7%). The impact factors for each journal are grouped into 6 categories: Of the 444 articles, impact factor below 1 ( n = 54, 12.2%), impact factor between 1 and 1.999 ( n = 72, 16.2%). In addition, impact factor between 2 and 2.999 ( n = 107, 24.1%), impact factor between 3 and 3.999 ( n = 92, 20.7%), impact factor between 4 and 4.999 ( n = 87, 19.6%), and impact factor of 5 or higher ( n = 29, 6.5%). And 3 articles published in journals with an impact factor which is not applicable.
We then assessed the distribution of countries among all the included publications. The top 10 publishing countries were the United States ( n = 64, 14.4%), Iran ( n = 57, 12.8%), China ( n = 35, 7.9%), Turkey ( n = 33, 7.4%), Spain ( n = 32, 7.2%), Canada ( n = 22, 5.0%), Indonesia ( n = 19, 4.3%), Italy ( n = 16, 3.6%) and the United Kingdom ( n = 16, 3.6%) respectively, and South Korea ( n = 14, 3.2%), see Fig. 2 . Regarding the year of publication, 27 articles (6.1%) were published in 2020, 170 articles (38.3%) in 2021, and 240 articles (54.1%) in 2022.
![strengths and weaknesses of qualitative research module figure 2](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig2_HTML.png)
Distribution of countries of COVID-19 related qualitative nursing research published
The academic qualifications of the first authors were reported in 150 (33.8%) of the 444 articles. Of these, 113 (75.3%) first authors have a Ph.D degree ( n = 113, 75.3%), Ph.D. candidates ( n = 3, 2.0%), Ph.D. students ( n = 7, 4.7%), Master degree ( n = 23, 15.3%), Master students ( n = 2, 1.3%), and Bachelor degree ( n = 2, 1.3%). The affiliations of the first author were the universities ( n = 395, 89.7%), the hospitals ( n = 34, 7.7%), research centers ( n = 12, 2.7%), and independent researchers ( n = 1, 0.2%).
The focuses on COVID-19 qualitative nursing publications were categorized into 7 groups: workforce experience ( n = 213, 48.0%), pandemic restrictions experience ( n = 100, 22.5%), learning experience ( n = 44, 9.9%), infected COVID-19 experience ( n = 32, 7.2%), hospitalized experience ( n = 30, 6.8%), psychological perception ( n = 24, 5.4%), and guideline analysis ( n = 1, 0.2%) during the COVID-19 pandemic, see Fig. 3 . The population was mainly clinical nurses ( n = 197, 44.4%), nursing managers ( n = 15, 3.4%), nurse educators ( n = 5, 1.1%), nursing students ( n = 50, 11.3%), other healthcare professionals ( n = 18, 4.1%), COVID-19 patients ( n = 31, 7.0%), other patients ( n = 36, 8.1%), family members / caregivers ( n = 24, 5.4%), and public ( n = 68, 15.3%). Figures 4 and 5 shows the population distribution of the included articles.
![strengths and weaknesses of qualitative research module figure 3](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig3_HTML.png)
Focuses of COVID-19 qualitative nursing research
![strengths and weaknesses of qualitative research module figure 4](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig4_HTML.png)
Target population of COVID-19 qualitative nursing research
![strengths and weaknesses of qualitative research module figure 5](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig5_HTML.png)
Distribution of clinical nurses
Methodological quality assessment of COVID-19 qualitative nursing research
Table 3 shows the prevalence of the items for reporting the methodological quality assessment of the included articles.
Methodological orientation
Of the 444 articles, the most adopted approach was the descriptive approach ( n = 165, 37.1%), Fig. 6 shows the types of approach adopted. Additionally, 84 (18.9%) of the articles only mentioned “qualitative study” without specifying which approach was being adopted.
![strengths and weaknesses of qualitative research module figure 6](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig6_HTML.png)
Types of approach adopted
Only one-third of the analyzed articles ( n = 135, 30.4%) mentioned employing standardized reporting quality checklists. Among these, the COREQ checklist was the most utilized ( n = 119, 26.8%), followed by the SRQR checklist ( n = 16, 3.6%).
Data collection
Among the articles included, 382 (86%) used interviews/discussions as a data collection method, 20 articles (4.5%) used mixed methods for data collection, and 42 articles (9.5%) that used methods other than interviews/discussions, 2.7% used surveys with open questions, 2.03% carried out document analysis, 1.8% examined diaries, 1.6% analyzed comments on social media, 0.5% used the photovoice method, and finally 0.2% carried out an analysis of audio-newspapers, an analysis of video diaries, an analysis of media interviews, only 1 article used observation as data collection method.
With the articles using interview/discussion methods, 261 articles (64.9%) specified who conducted the interviews. And 78 of them (19.4%) provided detailed information on their professional profiles. Most articles ( n = 327, 81.3%) mentioned the setting of data collection, with 65.4% ( n = 214) conducted remotely, 28.4% ( n = 93) conducted face-to-face, and 6.1% ( n = 20) indicated that the interviews were conducted whether remotely or face-to-face depending on participants’ wishes. The remoted interviews were conducted by teleconference ( n = 134, 57.3%), by telephone ( n = 66, 28.2%), and by teleconference or telephone ( n = 34, 14.5%), depending on the choice of participants. The software commonly used for teleconferencing was Zoom (44.5%), WhatsApp (11%), and Microsoft Teams (9.2%), while 35% did not mention which software was used, Fig. 7 shows the characteristics of data collection. Most articles ( n = 340, 84.8%) specified the duration of the interviews, they were described in two ways: mean duration ( n = 87, 25.6) or minimum and maximum duration ( n = 253, 74.4%). Audio recording was most used (86.7%), followed by visual recording (13.0%), and a few (0.3%) mentioned whether audio/visual recording was used. Most articles ( n = 351, 87.3%) provided interview guidelines, while only 16.9% ( n = 68) pre-tested them.
![strengths and weaknesses of qualitative research module figure 7](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig7_HTML.png)
Characteristics of data collection
Participants
Most articles ( n = 434, 97.7%) mentioned the number of samples. Almost all the articles ( n = 443, 99.9%) provided a detailed description of the samples. The most common sampling method was purposive sampling ( n = 244, 66.8%), followed by convenience sampling ( n = 34, 9.3%) and snowball sampling ( n = 33, 9.0%). Some articles ( n = 54, 14.8%) used mixed sampling methods.
Data analysis
The commonly used methods of analysis were content analysis ( n = 149, 36.0%) and thematic analysis ( n = 143, 34.4%) (Fig. 8 ). And some articles did not specify which method was used ( n = 14, 3.4%). And the most common software chosen by the authors were NVivo (46.9%), MAXQDA (26.7%), and ATLAS.ti (16.0%).
![strengths and weaknesses of qualitative research module figure 8](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12912-024-02138-x/MediaObjects/12912_2024_2138_Fig8_HTML.png)
Methods of data analysis
Presentation of results
All the articles (100%) presented their results in narrative form. The majority (90.3%) presented quotations in their results. Only 4.7% presented code recurrence. 18.7% used graphics to present their results, and 9.2% mentioned participants checking reports.
This study focused on the identification of the characteristics and reporting quality of qualitative nursing published research related to COVID-19 pandemic. We used a systematic search approach to identify qualitative nursing studies published related to the COVID-19 and then carried out a critical review with the use of content analysis of the identified articles, relying on a checklist created based on two standardized checklists (SRQR and COREQ). A total of 444 published studies were included and critically reviewed. The most productive country was the USA, which corresponds with a bibliometric analysis of COVID-19 research published in a nursing journal. This can be explained by the fact that the USA is one of the most impacted countries by COVID-19 [ 27 ] and is one of the most prolific countries regarding nursing research [ 28 ]. A significant finding of our study is that the majority of articles were published in journals ranked within Quartile 1. This suggests that the research produced during this period not only addressed urgent topics but also met high academic standards.
In addition, the findings revealed that the most represented topics and target population were related to the workforce experience and clinical nurses respectively, this is consistent with an article that focused on the reflections on nursing research during the pandemic COVID-19 [ 2 ]. Interestingly, clinical nurses were the predominant target population of the articles reviewed, this is possibly attributable to the challenge of conducting research with patients and the public due to pandemic-related restrictions. This thematic focus is likely driven by the critical challenge and changes by clinical nurses during the pandemic, highlighting their significant role in the frontline response and the need to understand and support them.
It was surprising to see that the use of standardized checklists to guide research studies by the researchers was notably low, with only 30.4% mentioning the use of standardized checklists. This finding is particularly noteworthy in the context of qualitative nursing research during the COVID-19 pandemic, a period that demanded high-quality evidence to inform rapidly changing clinical practices. The low adoption rate of standardized checklists may reflect gaps in researchers’ awareness or accessibility to these tools, or perhaps a broader issue in the research culture that undervalues structured guidance in study design and reporting, as these checklists aim to improve the quality of reporting these study types and allow readers to better understand the design, conduct, analysis and findings of published studies [ 25 ].
Traditional qualitative research data collection methods like interviews and discussions were supposed to be most impacted by the pandemic. Surprisingly, 86% ( n = 382) of the included articles used interviews or discussions as the data collection methods, and 28% of the researchers remained choosing the face-to-face interview method. We questioned how communication and facial expression were observed if facemasks were worn during the interview. Among the included studies that used the interview method in data collection, a significant proportion with 66% of these interviews were conducted remotely, either by telephone or online. These findings align with the literature reviewed, where nursing researchers in the USA reported an increase in the use of online platforms, as well as sending emails and phone calls for data collection, a trend which has seen a significant increase [ 8 ]. Researchers in Japan also reported having to adapt their research methods according to changes in the research environment, moving from in-person interviews to remote telephone interviews, collecting data while maintaining the social distancing, and online data collection [ 8 ]. A randomized research study comparing online interviews to in-person interviews person to assess health conditions was conducted in Australia. The results of this study showed that online interviews were preferred by a greater proportion of participants than in-person interviews, and then those assigned to the online group had a lower dropout rate. Additionally, the use of online interviews did not result in a loss of data quality [ 29 ]. Another study also indicated that online modalities for conducting qualitative research did not lead to substantially different thematic findings than in-person data collection [ 30 ]. These suggest that remote data collection methods would be a good choice for researchers, especially in situations where face-to-face interactions are challenging or not possible. The success of remote interviews in maintaining data quality, participant engagement, and lower dropout rates indicates their viability as a robust alternative to traditional methods. This shift not only ensures the continuity of research during crises like the COVID-19 pandemic but also offers a flexible and efficient approach for future qualitative studies. Embracing remote data collection can enhance the adaptability of research designs and potentially broaden the reach and inclusivity of participant recruitment, making it a valuable methodological option for qualitative nursing researchers.
The adoption of software tools in data analysis was surprisingly low, with only 37% of studies utilizing such resources. This finding suggests a potential area for further development in qualitative research practices, particularly to enhance efficiency and collaboration, especially in scenarios necessitating remote work and data sharing, especially during the pandemic when social contact was limited. In addition, there are other benefits of using qualitative data analysis software, including freedom from manual and administrative tasks, saving time, greater flexibility, and improved validity and reliability, and traceability of qualitative research [ 31 ].
In summary, this study carried out an in-depth analysis of data relating to the journals, articles, researchers, and methods used, identifying both strengths and areas requiring improvement. It highlighted the editorial quality of the publications and the methodological diversity observed in qualitative nursing studies linked to the COVID-19 pandemic. We found that many articles demonstrated commendable transparency in explicitly detailing their research approach, data collection processes, sampling methods, and data analysis techniques. However, some areas need improvement. A key aspect is the insufficient representation of strategies to ensure study rigor, such as triangulation and validation by respondents. It is essential to include critical reflection on the role of researchers, potential biases and their influence during the analysis and selection of data for presentation. Additionally, discussions about data saturation and sequential analysis can significantly strengthen the quality of qualitative research reporting. It is important that authors not only explain the methods or techniques they used but also provide clear and detailed justifications for their choices.
The effective translation of nursing research into clinical practice is critical, especially as healthcare professionals heavily depend on the latest research to guide their practices and decisions. The variability in the quality and reliability of research articles can lead to the adoption of clinical practices that may not be supported by strong evidence, potentially affecting patient care and hindering the advancement of nursing practice [ 32 ]. Therefore, improving the transparency and rigor of research methodology reporting is essential to ensure that clinical practices are based on reliable and robust evidence. Our study highlights the importance of methodological clarity and the use of standardized checklists in guiding research, This is increasingly relevant as nursing research evolves to meet global health challenges. By ensuring the high quality of reporting qualitative research, we can better bridge the gap between research and clinical practice, leading to improved patient outcomes and more effective healthcare delivery.
Limitations
It is also essential to recognize that our research method may have some limitations. The diversity of qualitative research methods restricted our assessment to an overview of overall research reporting quality. Additionally, our inclusion criterion based on the first author as a nurse may have excluded studies conducted by nurse-led teams, but where academic conventions led to a different first author. The time limit of the database prevented us from including articles published after January 2023. Finally, we excluded articles not published in English or French, meaning that relevant articles in other languages may have been omitted.
Conclusions
In conclusion, we urge researchers to provide detailed information in their articles, thereby allowing audiences to carefully evaluate the effectiveness and adequacy of the methods and materials used to produce credible and useful results. We also recommend researchers to adopt validated critical appraisal checklists when conducting their studies. This study highlights the importance of continued reflection on qualitative research practices with a view to improving the reporting quality of future studies in the field of nursing, especially during the special period of a pandemic. Additionally, we plan to compare these results with ancillary studies to assess the characteristics and reporting quality of qualitative nursing research before the COVID-19 pandemic. In the future, we wish to open the way for future studies aimed at exploring the relationships between the different criteria identified and each qualitative approach.
Data availability
The data as well as detailed descriptions of the literature search and search outcome (including excluded articles) are available from the corresponding author upon request.
Abbreviations
Coronavirus disease of 2019
Consolidated Criteria for Reporting Qualitative Research
Standards for Reporting Qualitative Research
Medical Subject Heading
Cumulative Index to Nursing and Allied Health Literature
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
United States of America
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Ian-In Vong (I.I.V.) and Rita Georges Nohra (R.G.N.) independently conducted the article screening. Monique Rothan-Tondeur (M.R.T.) was consulted to resolve any discrepancies that arose during the screening process. I.I.V. and R.G.N. were primarily responsible for writing the main manuscript text. M.R.T. provided critical revisions and contributed intellectual content to the manuscript draft. All authors have read and approved the final manuscript.
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Vong, II., Rothan-Tondeur, M. & Nohra, R.G. Characteristics and quality of reporting qualitative nursing research related to the COVID-19 pandemic: a systematic search and critical review. BMC Nurs 23 , 498 (2024). https://doi.org/10.1186/s12912-024-02138-x
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