weaknesses and strengths of qualitative research

23 Advantages and Disadvantages of Qualitative Research

Investigating methodologies. Taking a closer look at ethnographic, anthropological, or naturalistic techniques. Data mining through observer recordings. This is what the world of qualitative research is all about. It is the comprehensive and complete data that is collected by having the courage to ask an open-ended question.

Print media has used the principles of qualitative research for generations. Now more industries are seeing the advantages that come from the extra data that is received by asking more than a “yes” or “no” question.

The advantages and disadvantages of qualitative research are quite unique. On one hand, you have the perspective of the data that is being collected. On the other hand, you have the techniques of the data collector and their own unique observations that can alter the information in subtle ways.

That’s why these key points are so important to consider.

What Are the Advantages of Qualitative Research?

1. Subject materials can be evaluated with greater detail. There are many time restrictions that are placed on research methods. The goal of a time restriction is to create a measurable outcome so that metrics can be in place. Qualitative research focuses less on the metrics of the data that is being collected and more on the subtleties of what can be found in that information. This allows for the data to have an enhanced level of detail to it, which can provide more opportunities to glean insights from it during examination.

2. Research frameworks can be fluid and based on incoming or available data. Many research opportunities must follow a specific pattern of questioning, data collection, and information reporting. Qualitative research offers a different approach. It can adapt to the quality of information that is being gathered. If the available data does not seem to be providing any results, the research can immediately shift gears and seek to gather data in a new direction. This offers more opportunities to gather important clues about any subject instead of being confined to a limited and often self-fulfilling perspective.

3. Qualitative research data is based on human experiences and observations. Humans have two very different operating systems. One is a subconscious method of operation, which is the fast and instinctual observations that are made when data is present. The other operating system is slower and more methodical, wanting to evaluate all sources of data before deciding. Many forms of research rely on the second operating system while ignoring the instinctual nature of the human mind. Qualitative research doesn’t ignore the gut instinct. It embraces it and the data that can be collected is often better for it.

4. Gathered data has a predictive quality to it. One of the common mistakes that occurs with qualitative research is an assumption that a personal perspective can be extrapolated into a group perspective. This is only possible when individuals grow up in similar circumstances, have similar perspectives about the world, and operate with similar goals. When these groups can be identified, however, the gathered individualistic data can have a predictive quality for those who are in a like-minded group. At the very least, the data has a predictive quality for the individual from whom it was gathered.

5. Qualitative research operates within structures that are fluid. Because the data being gathered through this type of research is based on observations and experiences, an experienced researcher can follow-up interesting answers with additional questions. Unlike other forms of research that require a specific framework with zero deviation, researchers can follow any data tangent which makes itself known and enhance the overall database of information that is being collected.

6. Data complexities can be incorporated into generated conclusions. Although our modern world tends to prefer statistics and verifiable facts, we cannot simply remove the human experience from the equation. Different people will have remarkably different perceptions about any statistic, fact, or event. This is because our unique experiences generate a different perspective of the data that we see. These complexities, when gathered into a singular database, can generate conclusions with more depth and accuracy, which benefits everyone.

7. Qualitative research is an open-ended process. When a researcher is properly prepared, the open-ended structures of qualitative research make it possible to get underneath superficial responses and rational thoughts to gather information from an individual’s emotional response. This is critically important to this form of researcher because it is an emotional response which often drives a person’s decisions or influences their behavior.

8. Creativity becomes a desirable quality within qualitative research. It can be difficult to analyze data that is obtained from individual sources because many people subconsciously answer in a way that they think someone wants. This desire to “please” another reduces the accuracy of the data and suppresses individual creativity. By embracing the qualitative research method, it becomes possible to encourage respondent creativity, allowing people to express themselves with authenticity. In return, the data collected becomes more accurate and can lead to predictable outcomes.

9. Qualitative research can create industry-specific insights. Brands and businesses today need to build relationships with their core demographics to survive. The terminology, vocabulary, and jargon that consumers use when looking at products or services is just as important as the reputation of the brand that is offering them. If consumers are receiving one context, but the intention of the brand is a different context, then the miscommunication can artificially restrict sales opportunities. Qualitative research gives brands access to these insights so they can accurately communicate their value propositions.

10. Smaller sample sizes are used in qualitative research, which can save on costs. Many qualitative research projects can be completed quickly and on a limited budget because they typically use smaller sample sizes that other research methods. This allows for faster results to be obtained so that projects can move forward with confidence that only good data is able to provide.

11. Qualitative research provides more content for creatives and marketing teams. When your job involves marketing, or creating new campaigns that target a specific demographic, then knowing what makes those people can be quite challenging. By going through the qualitative research approach, it becomes possible to congregate authentic ideas that can be used for marketing and other creative purposes. This makes communication between the two parties to be handled with more accuracy, leading to greater level of happiness for all parties involved.

12. Attitude explanations become possible with qualitative research. Consumer patterns can change on a dime sometimes, leaving a brand out in the cold as to what just happened. Qualitative research allows for a greater understanding of consumer attitudes, providing an explanation for events that occur outside of the predictive matrix that was developed through previous research. This allows the optimal brand/consumer relationship to be maintained.

What Are the Disadvantages of Qualitative Research?

1. The quality of the data gathered in qualitative research is highly subjective. This is where the personal nature of data gathering in qualitative research can also be a negative component of the process. What one researcher might feel is important and necessary to gather can be data that another researcher feels is pointless and won’t spend time pursuing it. Having individual perspectives and including instinctual decisions can lead to incredibly detailed data. It can also lead to data that is generalized or even inaccurate because of its reliance on researcher subjectivisms.

2. Data rigidity is more difficult to assess and demonstrate. Because individual perspectives are often the foundation of the data that is gathered in qualitative research, it is more difficult to prove that there is rigidity in the information that is collective. The human mind tends to remember things in the way it wants to remember them. That is why memories are often looked at fondly, even if the actual events that occurred may have been somewhat disturbing at the time. This innate desire to look at the good in things makes it difficult for researchers to demonstrate data validity.

3. Mining data gathered by qualitative research can be time consuming. The number of details that are often collected while performing qualitative research are often overwhelming. Sorting through that data to pull out the key points can be a time-consuming effort. It is also a subjective effort because what one researcher feels is important may not be pulled out by another researcher. Unless there are some standards in place that cannot be overridden, data mining through a massive number of details can almost be more trouble than it is worth in some instances.

4. Qualitative research creates findings that are valuable, but difficult to present. Presenting the findings which come out of qualitative research is a bit like listening to an interview on CNN. The interviewer will ask a question to the interviewee, but the goal is to receive an answer that will help present a database which presents a specific outcome to the viewer. The goal might be to have a viewer watch an interview and think, “That’s terrible. We need to pass a law to change that.” The subjective nature of the information, however, can cause the viewer to think, “That’s wonderful. Let’s keep things the way they are right now.” That is why findings from qualitative research are difficult to present. What a research gleans from the data can be very different from what an outside observer gleans from the data.

5. Data created through qualitative research is not always accepted. Because of the subjective nature of the data that is collected in qualitative research, findings are not always accepted by the scientific community. A second independent qualitative research effort which can produce similar findings is often necessary to begin the process of community acceptance.

6. Researcher influence can have a negative effect on the collected data. The quality of the data that is collected through qualitative research is highly dependent on the skills and observation of the researcher. If a researcher has a biased point of view, then their perspective will be included with the data collected and influence the outcome. There must be controls in place to help remove the potential for bias so the data collected can be reviewed with integrity. Otherwise, it would be possible for a researcher to make any claim and then use their bias through qualitative research to prove their point.

7. Replicating results can be very difficult with qualitative research. The scientific community wants to see results that can be verified and duplicated to accept research as factual. In the world of qualitative research, this can be very difficult to accomplish. Not only do you have the variability of researcher bias for which to account within the data, but there is also the informational bias that is built into the data itself from the provider. This means the scope of data gathering can be extremely limited, even if the structure of gathering information is fluid, because of each unique perspective.

8. Difficult decisions may require repetitive qualitative research periods. The smaller sample sizes of qualitative research may be an advantage, but they can also be a disadvantage for brands and businesses which are facing a difficult or potentially controversial decision. A small sample is not always representative of a larger population demographic, even if there are deep similarities with the individuals involve. This means a follow-up with a larger quantitative sample may be necessary so that data points can be tracked with more accuracy, allowing for a better overall decision to be made.

9. Unseen data can disappear during the qualitative research process. The amount of trust that is placed on the researcher to gather, and then draw together, the unseen data that is offered by a provider is enormous. The research is dependent upon the skill of the researcher being able to connect all the dots. If the researcher can do this, then the data can be meaningful and help brands and progress forward with their mission. If not, there is no way to alter course until after the first results are received. Then a new qualitative process must begin.

10. Researchers must have industry-related expertise. You can have an excellent researcher on-board for a project, but if they are not familiar with the subject matter, they will have a difficult time gathering accurate data. For qualitative research to be accurate, the interviewer involved must have specific skills, experiences, and expertise in the subject matter being studied. They must also be familiar with the material being evaluated and have the knowledge to interpret responses that are received. If any piece of this skill set is missing, the quality of the data being gathered can be open to interpretation.

11. Qualitative research is not statistically representative. The one disadvantage of qualitative research which is always present is its lack of statistical representation. It is a perspective-based method of research only, which means the responses given are not measured. Comparisons can be made and this can lead toward the duplication which may be required, but for the most part, quantitative data is required for circumstances which need statistical representation and that is not part of the qualitative research process.

The advantages and disadvantages of qualitative research make it possible to gather and analyze individualistic data on deeper levels. This makes it possible to gain new insights into consumer thoughts, demographic behavioral patterns, and emotional reasoning processes. When a research can connect the dots of each information point that is gathered, the information can lead to personalized experiences, better value in products and services, and ongoing brand development.

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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Strengths and weaknesses of qualitative research in social science studies

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Content area

Qualitative Research, Quantitative Research, Constructivists, Positivist Paradigm, Critical Paradigm, Interpretative Paradigm

JEL Classification:

This study aimed at examining the strengths and weaknesses of qualitative research in social science studies. The study conducted a systematic literature review of 22 published journal articles to achieve the objective. The review revealed that the qualitative approach was flexible, offered in-depth and detailed information, allowed the use of multiple data collection methods and minimised the chance of having missing data. Moreover, the approach was found to integrate human touch, was cost-effective and was indeed the only option in some cases of research problems. On the other hand, the approach is prone to researchers' subjectivity, involves complex data analysis, makes anonymity difficult and has limited scope in its generalizability. Similarly, the approach makes replication of findings challenging, and the findings may be influenced by the researcher's bias. It is concluded, therefore, that researchers should take necessary precautions when using the approach to ensure that weaknesses of qualitative research do not bar them from achieving research objectives.

Introduction

In undertaking a scientific study, one begins with the dilemma of which research approach to employ. Mehrad and Zanganeh (2019) argue that the choice is usually between qualitative and quantitative research approaches. The two approaches, founded on constructivist and positivist schools of thought, respectively, have invited a never-ending debate (Kang & Evans, 2021).

Constructivists underscore the inductive meaning-making process that results in a subjective approach to theory building and research problem solving, and positivists emphasise theory testing, which, according to Coşkun (2020), provides an objective approach to problem-solving. Both approaches, however, have been used in different settings for varied reasons (Dawadi et al., 2021). A qualitative approach, for instance, is often preferred in social sciences studies as it is believed to suit the achievement of objectives in social sciences (Mohajan, 2018).

The quantitative approach, conversely, is preferred in most natural sciences due to its ability to hypothesise objectively and reliably. However, qualitative research has been subject to more criticism than quantitative research (Borgstede & Scholz, 2021). Opponents of the qualitative approach, for example, are concerned about its appropriateness in yielding expected results (Coşkun, 2020; Noble & Smith, 2015).The criticism is usually grounded on the subjective nature of the process involving...

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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.

Learn about our Editorial Process

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

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.

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. 

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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Qualitative Data – Strengths and Limitations

Table of Contents

Last Updated on September 1, 2021 by Karl Thompson

A summary of the theoretical, practical and ethical strengths and weaknesses of qualitative data sources such as unstructured interviews, participant observation and documents.

Examples of Qualitative Data

Theoretical strengths, practical strengths, ethical strengths, theoretical limitations, practical limitations, ethical limitations, nature of topic – when would you use it, when would you avoid using it, signposting.

More in-depth versions of qualitative data topics can be found below…

The strengths and limitations of covert participant observation  

Interviews in Social Research  

Secondary Qualitative Data Analysis in Sociology  

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Strengths and Weaknesses of Quantitative and Qualitative Research

Insights from research, walking in your customers’ shoes.

Both qualitative and quantitative methods of user research play important roles in product development. Data from quantitative research—such as market size, demographics, and user preferences—provides important information for business decisions. Qualitative research provides valuable data for use in the design of a product—including data about user needs, behavior patterns, and use cases. Each of these approaches has strengths and weaknesses, and each can benefit from our combining them with one another. This month, we’ll take a look at these two approaches to user research and discuss how and when to apply them.

Quantitative Studies

Quantitative studies provide data that can be expressed in numbers—thus, their name. Because the data is in a numeric form, we can apply statistical tests in making statements about the data. These include descriptive statistics like the mean, median, and standard deviation, but can also include inferential statistics like t-tests, ANOVAs, or multiple regression correlations (MRC). Statistical analysis lets us derive important facts from research data, including preference trends, differences between groups, and demographics.

Multivariate statistics like the MRC or stepwise correlation regression break the data down even further and determine what factors—such as variances in preferences—we can attribute to differences between specific groups such as age groups. Quantitative studies often employ automated means of collecting data such as surveys, but we can also use other static methods—for example, examining preferences through two-alternative, forced-choice studies or examining error rates and time on task using competitive benchmarks.

Quantitative studies’ great strength is providing data that is descriptive—for example, allowing us to capture a snapshot of a user population—but we encounter difficulties when it comes to their interpretation. For example, Gallup polls commonly provide data about approval rates for the President of the United States, as shown in Figure 1, but don’t provide the crucial information that we would need to interpret that data.

In the absence of the data that would be necessary to interpret these presidential job-approval numbers, it’s difficult to say why people approve or disapprove of the job that President Obama is doing. Some respondents may feel that President Obama is too liberal, while others may feel that he is too conservative in his actions, but without the necessary data, there is no way to tell.

In a product-development environment, this data deficiency can lead to critical errors in the design of a product. For example, a survey might report that the majority of users like 3D displays, which may lead to a product team’s choosing to integrate a 3D display into their product. However, if most users like only autostereoscopic 3D displays—that is, 3D displays that don’t require their wearing glasses—or like 3D displays only for watching sports or action movies on a television, using a 3D display that requires glasses for data visualization on a mobile device might not be a sound design direction.

Basically, statistical significance tells you whether your findings are real, while effect size tells you how much they matter. For example, if you were investigating whether adding a feature would increase a product’s value, you could have a statistically significant finding, but the magnitude of the increase in value might very small—say a few cents. In contrast, a meaningful effect size might result in an increase in value of $10 per unit. Typically, if you are able to achieve statistical significance with a smaller sample size, the effect size is fairly substantial. It is important to take both statistical significance and effect size into account when interpreting your data.

Qualitative Studies

Data from qualitative studies describes the qualities or characteristics of something. You cannot easily reduce these descriptions to numbers—as you can the findings from quantitative research; though you can achieve this through an encoding process. Qualitative research studies can provide you with details about human behavior, emotion, and personality characteristics that quantitative studies cannot match. Qualitative data includes information about user behaviors, needs, desires, routines, use cases, and a variety of other information that is essential in designing a product that will actually fit into a user’s life.

While quantitative research requires the standardization of data collection to allow statistical comparison, qualitative research requires flexibility, allowing you to respond to user data as it emerges during a session. Thus, qualitative research usually takes the form of either some form of naturalistic observation such as ethnography or structured interviews. In this case, a researcher must observe and document behaviors, opinions, patterns, needs, pain points, and other types of information without yet fully understanding what data will be meaningful.

Following data collection, rather than performing a statistical analysis, researchers look for trends in the data. When it comes to identifying trends, researchers look for statements that are identical across different research participants. The rule of thumb is that hearing a statement from just one participant is an anecdote; from two, a coincidence; and hearing it from three makes it a trend. The trends that you identify can then guide product development, business decisions, and marketing strategies.

Because you cannot subject these trends to statistical analysis, you cannot validate trends by calculating a p-value or an effect size—as you could validate quantitative data—so you must employ them with care. Plus, you should continually verify such data through an ongoing qualitative research program.

Additionally, because it is not possible to automate qualitative-data collection as effectively as you can automate quantitative-data collection, it is usually extremely time consuming and expensive to gather large amounts of data, as would be typical for quantitative research studies. Therefore, it is usual to perform qualitative research with only 6 to 12 participants, while for quantitative research, it’s common for there to be hundreds or even thousands of participants. As a result, qualitative research tends to have less statistical power than quantitative research when it comes to discovering and verifying trends.

Using Quantitative and Qualitative Research Together

While quantitative and qualitative research approaches each have their strengths and weaknesses, they can be extremely effective in combination with one another. You can use qualitative research to identify the factors that affect the areas under investigation, then use that information to devise quantitative research that assesses how these factors would affect user preferences. To continue our earlier example regarding display preferences: if qualitative research had identified display type—such as TV, computer monitor, or mobile phone display—the researchers could have used that information to construct quantitative research that would let them determine how these variables might affect user preferences. At the same time, you can build trends that you’ve identified through quantitative research into qualitative data-collection methods and, thus verify the trends.

While this might sound contrary to what we’ve described above, the approach is actually quite straightforward. An example of a qualitative trend might be that younger users prefer autostereoscopic displays only on mobile devices, while older users prefer traditional displays on all devices. You may have discovered this by asking an open-ended, qualitative question along these lines: “What do you think of 3D displays?” This question would have opened up a discussion about 3D displays that uncovered a difference between stereoscopic displays, autostereoscopic displays, and traditional displays. In a subsequent quantitative study, you could address these factors through a series of questions such as: “Rate your level of preference for a traditional 3D display—which requires your using 3D glasses—on a mobile device,” with options ranging from strongly prefer to strongly dislike . An automated system assigns a numeric value to whatever option a participant chooses, allowing a researcher to quickly gather and analyze large amounts of data.

37 Comments

The quantitative approach is so vital, even in our daily lives, because in most, if not all things we do in life, we measure to see how much there is of something.

Quantitative method is part of our daily life, even from birth, data are constantly being collected, assessed, and re-assessed as we grow.

I also support the quantitative data because it is much used and almost whatever we do involves it.

Yes. Both quantitative and qualitative research are important on their own. It depends on the situation where a researcher conducts a particular research, or he can go for the mixed method, too. For now, I am in need of sampling and non-sampling errors. Please help me understand its applications and the ways that can be checked? Types of sampling and all related information on this chapter. Expecting someone will help me on this soon.

Quantitative data provides the facts, but facts about people are just another construct of our society. For example, is something luxurious because it’s expensive or is it expensive because it’s luxurious? Business understands that neither method should be relied upon exclusively, which is why they use both. Anyone who thinks this is a competition between the two methods to somehow win out needs to read the article again. If you want to find out what happens when you think the only tool you need to make decisions in the social world is statistics, just type ‘New Coke’ into Google.

I also think that the quantitative approach is more important than the qualitative approach because we use it more and more in our life time.

I would suggest using both quantitative and qualitative. Both are strong ways of getting information and hearing the views and suggestions of others. It would be wiser to go for a mixed research method.

This quantitative approach is the approach used to show the transparency that at the end shows the democracy in the Great lakes countries. Thanks

Both methods are useful in real life situations. Which to use depends on the situation, and it’s not bad to combine both methods as this gives better and more accurate results.

Quantitative research requires high levels of statistical understanding to enable the measurements of descriptive and inferential statistics to be computed and interpreted, whereas qualitative methods are critical to identifying gaps in underserved areas in the society. More significantly, the use of a combination of the two is perfect.

Hi, I am Mark Jonson, and I am from New York, USA. Thanks for the article and wonderful example.

I am more confused when a particular method is considered superior over the other. I am more at ease looking at all three methods as situational—in that, some decision making requires the use of a quantitative, qualitative, or mixed method to accomplish my goals. For instance, it is suitable to use the quantitative method in studying birth and death rates in Europe and Africa, whereas the qualitative method suits a study on students’ behaviour relating to a particular course of study.

I think both qualitative and quantitative are good to go by, because the demerits of one are settled by the merits of the other.

The lapses that one has are covered by the other, so I think, for better findings and more accurate results, a mixed method answers it all.

Wonderfully great to me

Good article, provides a good general overview. As a marketing-research consultant I want to stress that qualitative research helps you much more to collect insights for user stories—if you do SCRUM—get the reasons why that make you differ and not differ from competitors and that would allow you to positively stand out in the market. Quantification is great. I love the stats, measurements. Yet my clients get great stuff out of qual that quant could never deliver because it is tool for specific purposes—as qual is. If you have both in your toolbox and know how to handle them, you get a better product. Use them and use them wisely, know the strengths and weaknesses of both—or get someone who does—because your competitor might just do it right now.

Both methods play an equal role, especially in research, and may also influence each other. This will depend on time and the necessity for each method.

Both methods are relevant because they drive individuals to the same conclusions.

“On the other hand, if you achieve statistical significance with a small sample size, you don’t need to increase your sample size; the finding is true regardless.” This is not true! A significance level set to 0.05 (5%), implies that it is acceptable to have a 5% probability of incorrectly rejecting the null hypothesis. That is, one might observe statistical significance, regardless of sample size, but this may be a false positive—that is, the effect occurs by chance or due to the co-occurrence of other factors. Low statistical power—because of small sample sizes, small effects, or both—negatively affects the likelihood that a nominally statistically significant finding—that is, finding of a p-value of ~.05—actually reflects a true effect. See this example . In general, one should be cautious about making inferences based on results drawn from a small sample.

It must be remembered that the two methods are not competing. They complement each other. Employing both techniques is the surest way to get your research budget well spent.

Minini, Faith Harrison—In my opinion, all three research approaches—quantitative, qualitative, and mixed methods—are very useful in informing UX practice. However, I prefer qualitative research for the reasons that studies are cheaper to embark on and the means of data collection and analysis are less stressful. However, employing both research approaches in any given study—especially studies involving large populations in countries’ health issues—provides the best results.

Thanks for the article. Both methods are useful, but it depends on the goal of the research.

I think qualitative research is best because it involves face-to-face conversation with the respondents. It gives true and reliable data as compared to quantitative research, because those researchers obtain data only from a given source and quantify it.

I need the advantages and disadvantages of using the T-test data collection method for the United States Parcel Service about their competition. I am not sure which is better for this, t-test or not, since t-test deals in small samples whereas UPS is global. I still have to know some disadvantages and advantages though.

i think qualitative research gives you detailed information and really goes into knowing much about a phenomenon, unlike quantitative’s giving you statistics.

I think a qualitative approach is more imperative. It provides greater richness and more detailed information about a smaller number of people.

I think qualitative research is easier to make meaning from, as it simplifies the phenomena by giving details on the issues.

I beg to differ from most comments. I support qualitative research because of the quality of its results.

Good, indeed.

I now understand the concept of quantitative research. Thanks for your contribution.

This concept of quantitative research is good. Nice write-up. You can as well make a video of this and place it on Netflix for people to watch.

“While quantitative and qualitative research approaches each have their strengths and weaknesses, they can be extremely effective in combination with one another.” - very insightful and so true! Thanks for posting this post, it was, indeed, a very interesting read. However, I, personally, prefer the quantitative approach. It can provide a person with a higher quality of the result.

For the ultimate quality of both methods, a foolproof system has to be found to eliminate biases. It is almost impossible. This is the basic problem that has to be solved.

I think both qualitative and quantitative approaches are vital. The approach that the researcher will adopt should be informed by the research question that the researcher is trying to resolve.

Everyone’s story is unique. Where your story starts may not be up to you, but where it ends definitely is. Every twist and turn is an opportunity to choose what comes next. Make that choice authentically yours, and you can’t do anything but succeed. Your Rough Draft We all have a different way of finding out what will work for us. But no matter which route we take on the journey to success—however you define it—we have to get into the messy and the profound in equal measure. And once it all comes together, the structure will make sense: the who, the why, and the how.

I think both qualitative and quantitative approaches are vital. The approach that the researcher will adopt should be informed by the research question that the researcher is trying to solve.

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Demetrius madrigal.

VP, UX & Consumer Insights at 30sec.io

Co-Founder and VP of Research & Product Development at Metric Lab

Redwood City, California, USA

Bryan McClain

President & Co-Founder at Metric Lab

Strategic UX Adviser & Head of Business Development at 30sec.io

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• 1 University of Nebraska Medical Center
• 2 GDB Research and Statistical Consulting
• 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
• PMID: 29262162
• Bookshelf ID: NBK470395

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

• Introduction
• Issues of Concern
• Clinical Significance
• Enhancing Healthcare Team Outcomes
• Review Questions

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Strengths and Weaknesses of Quantitative and Qualitative Research

Research plays a crucial role when it comes to achieving success in the world of business. When it comes to good research, both quantitative and qualitative research matters the most in building marketing strategies. Data gained through quantitative research includes demographics, consumer growth, and market trends. All of these help businesses and marketers build new theories. Qualitative data, on the other hand, tests the existing strategies or theories based on the gathered data from open-ended sources. Organizations need both methods to run their business smoothly. Upon combining both quantitative and qualitative research, you can get more objective insights from data and achieve more impactful results.

Let’s discover more about the quantitative and qualitative research, including their strengths and weaknesses. But first let’s understand what these two types of researches are. Here we go…

What is Quantitative Research?

Quantitative research is a systematic investigation. It majorly focuses on quantifying relationships, behaviors, phenomena, or other variables by collecting and analyzing numerical data. This type of research is done to test hypotheses, measure outcomes, and determine patterns and trends. It provides theoretical analysis of statistical data, i.e. insights, calculations, and estimations. This research method significantly gathers quantifiable data to perform the systematic investigation. It employs statistical, computational, and mathematical techniques to provide accurate and reliable outcomes.

For this research study, the researcher often collects statistically authentic and valid information by conducting online surveys , questionnaires, and online polls. In addition, they use sampling methods. More often than not, this method is employed used in the fields of social sciences, economics, health, and marketing, among others to get unbiased results. It helps in drawing valid conclusions and making informed decisions to introduce transformative changes to society. Let’s now take a look at the strengths of this type of research.

Strengths of Quantitative Research

Now that you have understood what exactly quantitative research is, it’s time to look at the strengths of this research type. Here we go…

• Validity and Credibility : This type of research provide statistically valid and authentic results to help you make informed decisions.
• Objectivity and Unbiased : Data collection is structured. Therefore, researchers’ biases and preconceptions do not impact their findings.
• Broader Perspective : This allows for generalization and conclusions about a broader population. This makes the research findings more impactful and useful.
• Clear and Accurate Results : The theoretical analysis of statistical data is clear and accurate. This promotes its easy explanation to a wider audience.
• Forecast : This research study helps to forecast future trends. As a result of this, the researcher can make more informed decisions.
• Diversity : This research method allows researchers to collect quantifiable data from diverse sources such as online surveys, questionnaires, and more.
• Versatility : This is a versatile research method. It can be used in various organizations to benefit from data-driven decisions .

Let’s now take a look at the weaknesses of this type of research…

Weaknesses of Quantitative Data

Although quantitative research is versatile and its findings are very impactful, it has some weaknesses that you should know. Look at the following pointers to know the weaknesses of quantitative research:

• Alien to Real-Life Situations : Data collection is structural; however, it is often limited in nature. Since it is used to collect quantifiable data, often it is not related to real-life situations.
• Does Not Identify Causes : The objective of quantitative research is to find correlations between different variables. The researchers are concerned with how much and how many. However, they often avoid looking into the why part – why something happens.
• No New Idea : The quantitative research aims to test the hypothesis of existing concepts. It does not emphasize generating new ideas or discovering uncovered areas.
• No Subjectivity : It does not take into account human experience. There is no place for human opinions and feelings in this type of research.
• Time Consuming : It uses a larger sample size and complex data sets for analysis. Therefore, it is more time-consuming compared to the other research methods.
• Complex : The rigorous design of the study requires a high level of expertise to draw findings.

Common Types of Quantitative Research Methods

Go over the following types of quantitative research methods:

Image Source – freepik/@upklyak

Researchers often conduct surveys to gather a huge data set that can be analyzed to identify patterns, relationships, and trends. For example, you can conduct online surveys to analyze customers’ experience with products or services. This analysis helps you identify customer satisfaction levels. Furthermore, you can discover areas of improvement or change.

2. Correlation Research

This is a non-experimental method. As the name says, this method is used to discover a correlation between two variables. It does not let extraneous variables intervene in the research study. If the correlation is positive, it indicates both variables are in the same direction. On the other hand, the negative correlation suggests both variables go in a negative direction. Furthermore, this type of research method only uses existing sources to analyze the dataset. Therefore, it is considered cost-effective.

3. Causal-Comparative Research

Image Source – freepik

The casual-comparative method identifies cause and effect variables. Under this research method, one variable is dependent and another one is independent. Some researchers claim it to be similar to an experimental research method. However, this is not a complete experimental method.

4. Experimental Research

Experimental research method or true experimentation administers scientific techniques to test the hypothesis of the study. It aims to measure how independent variables impact dependent variables. Moreover, it controls extraneous variables to ensure the validity of the research design.

5. Result Analysis

Take a look at the following two methods to do the result analysis on the quantitative research:

Descriptive Analysis

This computes or calculates your datasets using mean, median, and mode to summarize the statistical dataset.

Inferential Analysis

As the name suggests, this includes inferences about what the data means. To ensure its effectiveness, researchers employ the three most common methods, including cross-tabulation, factor analysis, and T-tests.

Let’s now take a look at the important pointers you need to keep in mind when constructing surveys.

Pointers to Keep in Mind While Constructing Surveys

Check out the following pointers to know how to administer a perfect survey for quantitative research:

• The questions should be short and simple
• You should avoid asking for misleading information
• Images should be clear and legible
• Grammar and spelling mistakes can make data quality poor. So, avoid them.

Why Is Quantitative Research Important to Marketing?

Take a look at the following details to know how quantitative research is important to marketing:

Real-Time Insights

Quantitative research helps researchers gather real-time statistical data on market trends, consumer choice patterns, and the organization’s performance. Based on that, researchers compute or calculate complex datasets to gain insights into various aspects. Finally, the research insights help organizations understand the impact of their strategies. They can use this information to reform their business plans.

Improve Marketing Strategies

By gaining real-time data analytics reports on online marketing strategies , they can boost their brand visibility. This helps them determine new strategies for driving organic traffic to the website.

Competitor Analysis

Numeric data analysis helps organizations track competitors’ performance. Based on the in-depth analysis, they can compare their marketing strategies and performance with competitors. This helps them understand what they can do to increase their brand awareness.

Objectivity

The qualitative research method provides leaders with objective data. They can easily communicate this data with their team members. Furthermore, this objective data helps team members understand in which direction they should proceed to yield better results.

It’s now time to move on to another very crucial research type, i.e., Qualitative Research and understand it in detail. Here we go…

What is Qualitative Research

Qualitative research is an exploratory method. It primarily focuses on understanding human behavior, customer’s experiences, and social phenomena. It involves detailed and in-depth analysis. Unlike quantitative research, which emphasizes numerical data and statistical analysis, qualitative research strives to discover the causes of any problem by examining non-numerical data. Its main emphasis is on why rather than what. Essentially, it is subjective in nature because it typically relies on human experiences.

It employs open-ended techniques , including interviews, observations, focus groups, content analysis, and more, to collect rich data. This approach allows researchers to gain a deeper understanding of the context, motivations, and perspectives of participants. This method allows participants to express their issues and opinions in their own words. Based on the data, the researcher analyzes their attitudes, interests, behaviors, and motivations. It is often employed in the fields of education, sociology, psychology, and anthropology. The study focuses on the intricate and subtle aspects of human experiences. It often employs smaller sample sizes to facilitate an in-depth analysis of a problem. By capturing rich, detailed data, qualitative research offers a comprehensive view of the subject matter, highlighting themes, patterns, and relationships that cannot be gathered using quantitative research methods.

Strengths of Qualitative Research

Here are some of the noteworthy strengths of qualitative research that you must be aware of. Take a look…

• Data Collection : The qualitative research method is not restricted to participants’ pre-defined questions. It focuses on open-ended methods to enable data collection. Interviews/observations help a researcher gain a complete understanding of respondents. All in all, this research method focuses on collecting rich and detailed data.
• Novel Theories : This method allows researchers to generate new ideas/theories that can be opposite to conventional social beliefs and norms.
• Express in Numeric : The qualitative research method allows researchers to convert research findings into numeric data for a better understanding.
• Can combine with Quantitative Method : The researcher can combine qualitative research with quantitative research to gain incredible insights into the matter.
• Flexibility : This type of research is more flexible in nature than any other form of research, and it provides room for adaptability.
• Contextual Understanding : The researcher gains a deeper understanding of the social and cultural contexts of participants, resulting in more impactful findings.

Weaknesses of Qualitative Research

• Misleading Information : The researcher must adhere to rigorous standards when collecting and analyzing data. If they fail to do so, resources and expertise of low quality can lead to misleading results.
• Can Not Be Generalized : It is challenging to draw broad conclusions and generalize the data to a larger population using this research design.
• Time-consuming : In contrast to other research methods, the qualitative research method is time-consuming because it involves collecting data through multiple interviews and observations.
• Less Valid : Because of the human experience intervention, the qualitative research findings are believed less valid and less authentic.

Common Types of Qualitative Research Methods

Here are some common types of qualitative research methods to know:

One-on-one Interview

One-on-one interviews have emerged as one of the most popular qualitative research methods. It involves face-to-face or online interviews of the participants. This research method aims to understand and analyze the opinions, ideas, and experiences of the interviewee.

Focus Groups

This research method involves the researcher organizing a small discussion or interview with a group of participants. All of the participants need to discuss a specific topic under this method. The objective of this study is to gain an understanding of the beliefs and considerations of the participants regarding a particular topic.

Discussion Boards

Online discussion boards have replaced traditional discussion boards . Under this research method, researchers provide students with a set of questions to make them participate in the debate. This is a highly efficient way to understand their perspectives, beliefs, and ideas in different situations.

Case study is yet another kind of method used for qualitative research. This method is primarily employed to gain in-depth information about the subject. It is important to note that the subject can encompass a wide range of entities, including organizations, countries, events, or individuals. A lot of researchers view the case study method as highly explanatory.

Pictures and Videos

Pictures and videos are also used as qualitative research methods to understand human experience through image or video analysis. They enhance the richness of data by allowing participants to express themselves in a non-verbal way. Based on visual elements analysis, a researcher reveals insights into social, cultural, or psychological phenomena.

Record-Keeping or Logging

Under this research method, the researcher collects authentic and valid documents from various sources. Further, the information is used as data. The findings of this research method are considered valid and impactful.

Ethnographic Study

Under the ethnographic study, the researchers act as an active participant or observer to study participants in their natural settings. This allows them to understand their social context, culture, and behavior in a much better way.

Observation Method

The observation methods involve the researcher’s subjective interpretation to observe and analyze the attributes and characteristics of a phenomenon. The data collection relies heavily on the researcher’s keen senses of taste, smell, sight, and hearing. He conducts thorough data collection and carefully analyses the entire event.

Result Analysis

Here are the two methods that researchers often employ for the result analysis of the qualitative research:

Deductive Analysis

Deductive analysis is often used to test existing theories, ideas, or beliefs. In qualitative research, deductive analysis is the process of applying predetermined codes to the data. The codes are often generated from literature, theory, or propositions that the researcher has developed. Furthermore, this is a structured method because it applies already decided research design.

Inductive Analysis

Inductive analysis builds up new theories based on specific observations or patterns. The basis of these theories is what has been seen and how it has been seen. Furthermore, it is a flexible analysis that is open to new information.

Some people claim that surveys can only be used in quantitative research. But this is not true. You can conduct surveys in qualitative research as well to make informed decisions.

Check out the following pointers to learn what you should keep in mind while constructing surveys:

• Use appropriate language
• Avoid unnecessary capitalization in words or phrases
• Use the correct format of the questions
• Make sure that multiple-answer questions do not have conflicting answer choices.

Why Is Qualitative Research Important to Marketing?

Qualitative research is ideal for marketing because it helps organizations acquire trustworthy information regarding their consumers’ changing demands, preferences, or tastes. Go over the following pointers to understand why qualitative research is important in today’s marketing scenario. Take a look…

Build Strategies

Image Source – freepik/@storyset

In this era of cut-throat competition, knowing about your customers is crucial. This is because based on that information only you can make right marketing decisions. Qualitative research helps organizations understand customers’ preferences and needs. Information gathered using qualitative research methods help businesses build new strategies to enhance customer’s experience. Strategies that businesses design using research data help them attract their target customers and improve their bottom lines.

Rebrand Products and Services

Often, researchers find this method very helpful. The information gathered using qualitative research helps businesses rebrand their products and services. Based on the results of the research, they come to know what their products and services lack. Also, they can determine what they can do to improve their products and services to attract their target customers.

Prevents the Risk of Customer Churning

Customer churning happens when a customer stops using a company’s products or services. However, qualitative research findings help companies understand their customer’s experience with their products and know what consumers want from their products or services. This reduces the risk of customer churning to a great extent.

Get Feedback from Customers

This method helps organizations get feedback on their products or services from customers. The feedback analysis makes a lot of sense in accelerating the organization’s growth.

The Bottom Line

So, this is all about the strengths and weaknesses of quantitative and qualitative research methodologies. Both quantitative and qualitative research methods showcase unique strengths, making them ideal for collecting data for different sectors. However, both methods do exhibit some weaknesses as well. Quantitative research excels in providing precise, measurable, and generalizable data through statistical analysis, while qualitative research offers rich, detailed insights into participants’ experiences, emotions, and social interactions. Quantitative research is considered best for testing hypotheses and identifying patterns across large populations.

At the same time, qualitative research is considered ideal for gaining a deeper understanding of underlying motivations and meanings. Quantitative research methodologies have a structured approach; however, they often avoid the complexities of human behavior and context. Well, that’s not the case with qualitative research methods. You can choose to use any of the research methods to write my essay for me online based on the industry you are serving. However, you can even combine both approaches to enjoy the benefits of both methods.

Thanks for reading!

Stay tuned for more such insightful posts!

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Conducting and Writing Quantitative and Qualitative Research

Edward barroga.

1 Department of Medical Education, Showa University School of Medicine, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

Atsuko Furuta

Makiko arima, shizuma tsuchiya, chikako kawahara, yusuke takamiya.

Comprehensive knowledge of quantitative and qualitative research systematizes scholarly research and enhances the quality of research output. Scientific researchers must be familiar with them and skilled to conduct their investigation within the frames of their chosen research type. When conducting quantitative research, scientific researchers should describe an existing theory, generate a hypothesis from the theory, test their hypothesis in novel research, and re-evaluate the theory. Thereafter, they should take a deductive approach in writing the testing of the established theory based on experiments. When conducting qualitative research, scientific researchers raise a question, answer the question by performing a novel study, and propose a new theory to clarify and interpret the obtained results. After which, they should take an inductive approach to writing the formulation of concepts based on collected data. When scientific researchers combine the whole spectrum of inductive and deductive research approaches using both quantitative and qualitative research methodologies, they apply mixed-method research. Familiarity and proficiency with these research aspects facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Graphical Abstract

INTRODUCTION

Novel research studies are conceptualized by scientific researchers first by asking excellent research questions and developing hypotheses, then answering these questions by testing their hypotheses in ethical research. 1 , 2 , 3 Before they conduct novel research studies, scientific researchers must possess considerable knowledge of both quantitative and qualitative research. 2

In quantitative research, researchers describe existing theories, generate and test a hypothesis in novel research, and re-evaluate existing theories deductively based on their experimental results. 1 , 4 , 5 In qualitative research, scientific researchers raise and answer research questions by performing a novel study, then propose new theories by clarifying their results inductively. 1 , 6

RATIONALE OF THIS ARTICLE

When researchers have a limited knowledge of both research types and how to conduct them, this can result in substandard investigation. Researchers must be familiar with both types of research and skilled to conduct their investigations within the frames of their chosen type of research. Thus, meticulous care is needed when planning quantitative and qualitative research studies to avoid unethical research and poor outcomes.

Understanding the methodological and writing assumptions 7 , 8 underpinning quantitative and qualitative research, especially by non-Anglophone researchers, is essential for their successful conduct. Scientific researchers, especially in the academe, face pressure to publish in international journals 9 where English is the language of scientific communication. 10 , 11 In particular, non-Anglophone researchers face challenges related to linguistic, stylistic, and discourse differences. 11 , 12 Knowing the assumptions of the different types of research will help clarify research questions and methodologies, easing the challenge and help.

SEARCH FOR RELEVANT ARTICLES

To identify articles relevant to this topic, we adhered to the search strategy recommended by Gasparyan et al. 7 We searched through PubMed, Scopus, Directory of Open Access Journals, and Google Scholar databases using the following keywords: quantitative research, qualitative research, mixed-method research, deductive reasoning, inductive reasoning, study design, descriptive research, correlational research, experimental research, causal-comparative research, quasi-experimental research, historical research, ethnographic research, meta-analysis, narrative research, grounded theory, phenomenology, case study, and field research.

AIMS OF THIS ARTICLE

This article aims to provide a comparative appraisal of qualitative and quantitative research for scientific researchers. At present, there is still a need to define the scope of qualitative research, especially its essential elements. 13 Consensus on the critical appraisal tools to assess the methodological quality of qualitative research remains lacking. 14 Framing and testing research questions can be challenging in qualitative research. 2 In the healthcare system, it is essential that research questions address increasingly complex situations. Therefore, research has to be driven by the kinds of questions asked and the corresponding methodologies to answer these questions. 15 The mixed-method approach also needs to be clarified as this would appear to arise from different philosophical underpinnings. 16

This article also aims to discuss how particular types of research should be conducted and how they should be written in adherence to international standards. In the US, Europe, and other countries, responsible research and innovation was conceptualized and promoted with six key action points: engagement, gender equality, science education, open access, ethics and governance. 17 , 18 International ethics standards in research 19 as well as academic integrity during doctoral trainings are now integral to the research process. 20

POTENTIAL BENEFITS FROM THIS ARTICLE

This article would be beneficial for researchers in further enhancing their understanding of the theoretical, methodological, and writing aspects of qualitative and quantitative research, and their combination.

Moreover, this article reviews the basic features of both research types and overviews the rationale for their conduct. It imparts information on the most common forms of quantitative and qualitative research, and how they are carried out. These aspects would be helpful for selecting the optimal methodology to use for research based on the researcher’s objectives and topic.

This article also provides information on the strengths and weaknesses of quantitative and qualitative research. Such information would help researchers appreciate the roles and applications of both research types and how to gain from each or their combination. As different research questions require different types of research and analyses, this article is anticipated to assist researchers better recognize the questions answered by quantitative and qualitative research.

Finally, this article would help researchers to have a balanced perspective of qualitative and quantitative research without considering one as superior to the other.

TYPES OF RESEARCH

Research can be classified into two general types, quantitative and qualitative. 21 Both types of research entail writing a research question and developing a hypothesis. 22 Quantitative research involves a deductive approach to prove or disprove the hypothesis that was developed, whereas qualitative research involves an inductive approach to create a hypothesis. 23 , 24 , 25 , 26

In quantitative research, the hypothesis is stated before testing. In qualitative research, the hypothesis is developed through inductive reasoning based on the data collected. 27 , 28 For types of data and their analysis, qualitative research usually includes data in the form of words instead of numbers more commonly used in quantitative research. 29

Quantitative research usually includes descriptive, correlational, causal-comparative / quasi-experimental, and experimental research. 21 On the other hand, qualitative research usually encompasses historical, ethnographic, meta-analysis, narrative, grounded theory, phenomenology, case study, and field research. 23 , 25 , 28 , 30 A summary of the features, writing approach, and examples of published articles for each type of qualitative and quantitative research is shown in Table 1 . 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43

QUANTITATIVE RESEARCH

Deductive approach.

The deductive approach is used to prove or disprove the hypothesis in quantitative research. 21 , 25 Using this approach, researchers 1) make observations about an unclear or new phenomenon, 2) investigate the current theory surrounding the phenomenon, and 3) hypothesize an explanation for the observations. Afterwards, researchers will 4) predict outcomes based on the hypotheses, 5) formulate a plan to test the prediction, and 6) collect and process the data (or revise the hypothesis if the original hypothesis was false). Finally, researchers will then 7) verify the results, 8) make the final conclusions, and 9) present and disseminate their findings ( Fig. 1A ).

Types of quantitative research

The common types of quantitative research include (a) descriptive, (b) correlational, c) experimental research, and (d) causal-comparative/quasi-experimental. 21

Descriptive research is conducted and written by describing the status of an identified variable to provide systematic information about a phenomenon. A hypothesis is developed and tested after data collection, analysis, and synthesis. This type of 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 employed variables or controlling the involved conditions. 44 Here, the researcher examines, observes, and describes a situation, sample, or variable as it occurs without investigator interference. 31 , 45 To be meaningful, the systematic collection of information requires careful selection of study units by precise measurement of individual variables 21 often expressed as ranges, means, frequencies, and/or percentages. 31 , 45 Descriptive statistical analysis using ANOVA, Student’s t -test, or the Pearson coefficient method has been used to analyze descriptive research data. 46

Correlational research is performed by determining and interpreting the extent of a relationship between two or more variables using statistical data. This involves recognizing data trends and patterns without necessarily proving their causes. The researcher studies only the data, relationships, and distributions of variables in a natural setting, but does not manipulate them. 21 , 45 Afterwards, the researcher establishes reliability and validity, provides converging evidence, describes relationship, and makes predictions. 47

Experimental research is usually referred to as true experimentation. The researcher establishes the cause-effect relationship among a group of variables making up a study using the scientific method or process. This type of research attempts to identify the causal relationships between variables through experiments by arbitrarily controlling the conditions or manipulating the variables used. 44 The scientific manuscript would include an explanation of how the independent variable was manipulated to determine its effects on the dependent variables. The write-up would also describe the random assignments of subjects to experimental treatments. 21

Causal-comparative/quasi-experimental research closely resembles true experimentation but is conducted by establishing the cause-effect relationships among variables. It may also be conducted to establish the cause or consequences of differences that already exist between, or among groups of individuals. 48 This type of research compares outcomes between the intervention groups in which participants are not randomized to their respective interventions because of ethics- or feasibility-related reasons. 49 As in true experiments, the researcher identifies and measures the effects of the independent variable on the dependent variable. However, unlike true experiments, the researchers do not manipulate the independent variable.

In quasi-experimental research, naturally formed or pre-existing groups that are not randomly assigned are used, particularly when an ethical, randomized controlled trial is not feasible or logical. 50 The researcher identifies control groups as those which have been exposed to the treatment variable, and then compares these with the unexposed groups. The causes are determined and described after data analysis, after which conclusions are made. The known and unknown variables that could still affect the outcome are also included. 7

QUALITATIVE RESEARCH

Inductive approach.

Qualitative research involves an inductive approach to develop a hypothesis. 21 , 25 Using this approach, researchers answer research questions and develop new theories, but they do not test hypotheses or previous theories. The researcher seldom examines the effectiveness of an intervention, but rather explores the perceptions, actions, and feelings of participants using interviews, content analysis, observations, or focus groups. 25 , 45 , 51

Distinctive features of qualitative research

Qualitative research seeks to elucidate about the lives of people, including their lived experiences, behaviors, attitudes, beliefs, personality characteristics, emotions, and feelings. 27 , 30 It also explores societal, organizational, and cultural issues. 30 This type of research provides a good story mimicking an adventure which results in a “thick” description that puts readers in the research setting. 52

The qualitative research questions are open-ended, evolving, and non-directional. 26 The research design is usually flexible and iterative, commonly employing purposive sampling. The sample size depends on theoretical saturation, and data is collected using in-depth interviews, focus groups, and observations. 27

In various instances, excellent qualitative research may offer insights that quantitative research cannot. Moreover, qualitative research approaches can describe the ‘lived experience’ perspectives of patients, practitioners, and the public. 53 Interestingly, recent developments have looked into the use of technology in shaping qualitative research protocol development, data collection, and analysis phases. 54

Qualitative research employs various techniques, including conversational and discourse analysis, biographies, interviews, case-studies, oral history, surveys, documentary and archival research, audiovisual analysis, and participant observations. 26

Conducting qualitative research

To conduct qualitative research, investigators 1) identify a general research question, 2) choose the main methods, sites, and subjects, and 3) determine methods of data documentation access to subjects. Researchers also 4) decide on the various aspects for collecting data (e.g., questions, behaviors to observe, issues to look for in documents, how much (number of questions, interviews, or observations), 5) clarify researchers’ roles, and 6) evaluate the study’s ethical implications in terms of confidentiality and sensitivity. Afterwards, researchers 7) collect data until saturation, 8) interpret data by identifying concepts and theories, and 9) revise the research question if necessary and form hypotheses. In the final stages of the research, investigators 10) collect and verify data to address revisions, 11) complete the conceptual and theoretical framework to finalize their findings, and 12) present and disseminate findings ( Fig. 1B ).

Types of qualitative research

The different types of qualitative research include (a) historical research, (b) ethnographic research, (c) meta-analysis, (d) narrative research, (e) grounded theory, (f) phenomenology, (g) case study, and (h) field research. 23 , 25 , 28 , 30

Historical research is conducted by describing past events, problems, issues, and facts. The researcher gathers data from written or oral descriptions of past events and attempts to recreate the past without interpreting the events and their influence on the present. 6 Data is collected using documents, interviews, and surveys. 55 The researcher analyzes these data by describing the development of events and writes the research based on historical reports. 2

Ethnographic research is performed by observing everyday life details as they naturally unfold. 2 It can also be conducted by developing in-depth analytical descriptions of current systems, processes, and phenomena or by understanding the shared beliefs and practices of a particular group or culture. 21 The researcher collects extensive narrative non-numerical data based on many variables over an extended period, in a natural setting within a specific context. To do this, the researcher uses interviews, observations, and active participation. These data are analyzed by describing and interpreting them and developing themes. A detailed report of the interpreted data is then provided. 2 The researcher immerses himself/herself into the study population and describes the actions, behaviors, and events from the perspective of someone involved in the population. 23 As examples of its application, ethnographic research has helped to understand a cultural model of family and community nursing during the coronavirus disease 2019 outbreak. 56 It has also been used to observe the organization of people’s environment in relation to cardiovascular disease management in order to clarify people’s real expectations during follow-up consultations, possibly contributing to the development of innovative solutions in care practices. 57

Meta-analysis is carried out by accumulating experimental and correlational results across independent studies using a statistical method. 21 The report is written by specifying the topic and meta-analysis type. In the write-up, reporting guidelines are followed, which include description of inclusion criteria and key variables, explanation of the systematic search of databases, and details of data extraction. Meta-analysis offers in-depth data gathering and analysis to achieve deeper inner reflection and phenomenon examination. 58

Narrative research is performed by collecting stories for constructing a narrative about an individual’s experiences and the meanings attributed to them by the individual. 9 It aims to hear the voice of individuals through their account or experiences. 17 The researcher usually conducts interviews and analyzes data by storytelling, content review, and theme development. The report is written as an in-depth narration of events or situations focused on the participants. 2 , 59 Narrative research weaves together sequential events from one or two individuals to create a “thick” description of a cohesive story or narrative. 23 It facilitates understanding of individuals’ lives based on their own actions and interpretations. 60

Grounded theory is conducted by engaging in an inductive ground-up or bottom-up strategy of generating a theory from data. 24 The researcher incorporates deductive reasoning when using constant comparisons. Patterns are detected in observations and then a working hypothesis is created which directs the progression of inquiry. The researcher collects data using interviews and questionnaires. These data are analyzed by coding the data, categorizing themes, and describing implications. The research is written as a theory and theoretical models. 2 In the write-up, the researcher describes the data analysis procedure (i.e., theoretical coding used) for developing hypotheses based on what the participants say. 61 As an example, a qualitative approach has been used to understand the process of skill development of a nurse preceptor in clinical teaching. 62 A researcher can also develop a theory using the grounded theory approach to explain the phenomena of interest by observing a population. 23

Phenomenology is carried out by attempting to understand the subjects’ perspectives. This approach is pertinent in social work research where empathy and perspective are keys to success. 21 Phenomenology studies an individual’s lived experience in the world. 63 The researcher collects data by interviews, observations, and surveys. 16 These data are analyzed by describing experiences, examining meanings, and developing themes. The researcher writes the report by contextualizing and reporting the subjects’ experience. This research approach describes and explains an event or phenomenon from the perspective of those who have experienced it. 23 Phenomenology understands the participants’ experiences as conditioned by their worldviews. 52 It is suitable for a deeper understanding of non-measurable aspects related to the meanings and senses attributed by individuals’ lived experiences. 60

Case study is conducted by collecting data through interviews, observations, document content examination, and physical inspections. The researcher analyzes the data through a detailed identification of themes and the development of narratives. The report is written as an in-depth study of possible lessons learned from the case. 2

Field research is performed using a group of methodologies for undertaking qualitative inquiries. The researcher goes directly to the social phenomenon being studied and observes it extensively. In the write-up, the researcher describes the phenomenon under the natural environment over time with no implantation of controls or experimental conditions. 45

DIFFERENCES BETWEEN QUANTITATIVE AND QUALITATIVE RESEARCH

Scientific researchers must be aware of the differences between quantitative and qualitative research in terms of their working mechanisms to better understand their specific applications. This knowledge will be of significant benefit to researchers, especially during the planning process, to ensure that the appropriate type of research is undertaken to fulfill the research aims.

In terms of quantitative research data evaluation, four well-established criteria are used: internal validity, external validity, reliability, and objectivity. 23 The respective correlating concepts in qualitative research data evaluation are credibility, transferability, dependability, and confirmability. 30 Regarding write-up, quantitative research papers are usually shorter than their qualitative counterparts, which allows the latter to pursue a deeper understanding and thus producing the so-called “thick” description. 29

Interestingly, a major characteristic of qualitative research is that the research process is reversible and the research methods can be modified. This is in contrast to quantitative research in which hypothesis setting and testing take place unidirectionally. This means that in qualitative research, the research topic and question may change during literature analysis, and that the theoretical and analytical methods could be altered during data collection. 44

Quantitative research focuses on natural, quantitative, and objective phenomena, whereas qualitative research focuses on social, qualitative, and subjective phenomena. 26 Quantitative research answers the questions “what?” and “when?,” whereas qualitative research answers the questions “why?,” “how?,” and “how come?.” 64

Perhaps the most important distinction between quantitative and qualitative research lies in the nature of the data being investigated and analyzed. Quantitative research focuses on statistical, numerical, and quantitative aspects of phenomena, and employ the same data collection and analysis, whereas qualitative research focuses on the humanistic, descriptive, and qualitative aspects of phenomena. 26 , 28

Structured versus unstructured processes

The aims and types of inquiries determine the difference between quantitative and qualitative research. In quantitative research, statistical data and a structured process are usually employed by the researcher. Quantitative research usually suggests quantities (i.e., numbers). 65 On the other hand, researchers typically use opinions, reasons, verbal statements, and an unstructured process in qualitative research. 63 Qualitative research is more related to quality or kind. 65

In quantitative research, the researcher employs a structured process for collecting quantifiable data. Often, a close-ended questionnaire is used wherein the response categories for each question are designed in which values can be assigned and analyzed quantitatively using a common scale. 66 Quantitative research data is processed consecutively from data management, then data analysis, and finally to data interpretation. Data should be free from errors and missing values. In data management, variables are defined and coded. In data analysis, statistics (e.g., descriptive, inferential) as well as central tendency (i.e., mean, median, mode), spread (standard deviation), and parameter estimation (confidence intervals) measures are used. 67

In qualitative research, the researcher uses an unstructured process for collecting data. These non-statistical data may be in the form of statements, stories, or long explanations. Various responses according to respondents may not be easily quantified using a common scale. 66

Composing a qualitative research paper resembles writing a quantitative research paper. Both papers consist of a title, an abstract, an introduction, objectives, methods, findings, and discussion. However, a qualitative research paper is less regimented than a quantitative research paper. 27

Quantitative research as a deductive hypothesis-testing design

Quantitative research can be considered as a hypothesis-testing design as it involves quantification, statistics, and explanations. It flows from theory to data (i.e., deductive), focuses on objective data, and applies theories to address problems. 45 , 68 It collects numerical or statistical data; answers questions such as how many, how often, how much; uses questionnaires, structured interview schedules, or surveys 55 as data collection tools; analyzes quantitative data in terms of percentages, frequencies, statistical comparisons, graphs, and tables showing statistical values; and reports the final findings in the form of statistical information. 66 It uses variable-based models from individual cases and findings are stated in quantified sentences derived by deductive reasoning. 24

In quantitative research, a phenomenon is investigated in terms of the relationship between an independent variable and a dependent variable which are numerically measurable. The research objective is to statistically test whether the hypothesized relationship is true. 68 Here, the researcher studies what others have performed, examines current theories of the phenomenon being investigated, and then tests hypotheses that emerge from those theories. 4

Quantitative hypothesis-testing research has certain limitations. These limitations include (a) problems with selection of meaningful independent and dependent variables, (b) the inability to reflect subjective experiences as variables since variables are usually defined numerically, and (c) the need to state a hypothesis before the investigation starts. 61

Qualitative research as an inductive hypothesis-generating design

Qualitative research can be considered as a hypothesis-generating design since it involves understanding and descriptions in terms of context. It flows from data to theory (i.e., inductive), focuses on observation, and examines what happens in specific situations with the aim of developing new theories based on the situation. 45 , 68 This type of research (a) collects qualitative data (e.g., ideas, statements, reasons, characteristics, qualities), (b) answers questions such as what, why, and how, (c) uses interviews, observations, or focused-group discussions as data collection tools, (d) analyzes data by discovering patterns of changes, causal relationships, or themes in the data; and (e) reports the final findings as descriptive information. 61 Qualitative research favors case-based models from individual characteristics, and findings are stated using context-dependent existential sentences that are justifiable by inductive reasoning. 24

In qualitative research, texts and interviews are analyzed and interpreted to discover meaningful patterns characteristic of a particular phenomenon. 61 Here, the researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences. 4

Qualitative hypothesis-generating research involves collecting interview data from study participants regarding a phenomenon of interest, and then using what they say to develop hypotheses. It involves the process of questioning more than obtaining measurements; it generates hypotheses using theoretical coding. 61 When using large interview teams, the key to promoting high-level qualitative research and cohesion in large team methods and successful research outcomes is the balance between autonomy and collaboration. 69

Qualitative data may also include observed behavior, participant observation, media accounts, and cultural artifacts. 61 Focus group interviews are usually conducted, audiotaped or videotaped, and transcribed. Afterwards, the transcript is analyzed by several researchers.

Qualitative research also involves scientific narratives and the analysis and interpretation of textual or numerical data (or both), mostly from conversations and discussions. Such approach uncovers meaningful patterns that describe a particular phenomenon. 2 Thus, qualitative research requires skills in grasping and contextualizing data, as well as communicating data analysis and results in a scientific manner. The reflective process of the inquiry underscores the strengths of a qualitative research approach. 2

Combination of quantitative and qualitative research

When both quantitative and qualitative research methods are used in the same research, mixed-method research is applied. 25 This combination provides a complete view of the research problem and achieves triangulation to corroborate findings, complementarity to clarify results, expansion to extend the study’s breadth, and explanation to elucidate unexpected results. 29

Moreover, quantitative and qualitative findings are integrated to address the weakness of both research methods 29 , 66 and to have a more comprehensive understanding of the phenomenon spectrum. 66

For data analysis in mixed-method research, real non-quantitized qualitative data and quantitative data must both be analyzed. 70 The data obtained from quantitative analysis can be further expanded and deepened by qualitative analysis. 23

In terms of assessment criteria, Hammersley 71 opined that qualitative and quantitative findings should be judged using the same standards of validity and value-relevance. Both approaches can be mutually supportive. 52

Quantitative and qualitative research must be carefully studied and conducted by scientific researchers to avoid unethical research and inadequate outcomes. Quantitative research involves a deductive process wherein a research question is answered with a hypothesis that describes the relationship between independent and dependent variables, and the testing of the hypothesis. This investigation can be aptly termed as hypothesis-testing research involving the analysis of hypothesis-driven experimental studies resulting in a test of significance. Qualitative research involves an inductive process wherein a research question is explored to generate a hypothesis, which then leads to the development of a theory. This investigation can be aptly termed as hypothesis-generating research. When the whole spectrum of inductive and deductive research approaches is combined using both quantitative and qualitative research methodologies, mixed-method research is applied, and this can facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Data curation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Formal analysis: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C.
• Investigation: Barroga E, Matanguihan GJ, Takamiya Y, Izumi M.
• Methodology: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Project administration: Barroga E, Matanguihan GJ.
• Resources: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Supervision: Barroga E.
• Validation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Visualization: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.

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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, Data Collection and Ethics 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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Qualitative Data Collection & Analysis Methods

59 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 employing this method can be explored in much more depth 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 they also are able share information with researchers in their own words and from their own perspectives rather than being asked to fit those perspectives into the perhaps limited response options provided by the researcher. And 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.

Of course, all these benefits do not come without some drawbacks. 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 behaviours are being asked about. Further, as you may have already guessed, qualitative interviewing is time intensive and can be quite expensive. Creating an interview guide, identifying a sample, and conducting interviews are just the beginning. Transcribing interviews is labour intensive—and that is before coding even begins. It is also not uncommon to offer respondents some monetary incentive or thank-you for participating. Keep in mind that you are asking for more of the participants’ time than if you would have simply mailed them a questionnaire containing closed-ended questions. Conducting qualitative interviews is not only labour 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.

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• This chapter is an adaptation of Chapter 9.2 in Principles of Sociological Inquiry , which was adapted by the Saylor Academy without attribution to the original authors or publisher, as requested by the licensor. © Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License .

An Introduction to Research Methods in Sociology Copyright © 2019 by Valerie A. Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• Volume 25, Issue 1
• Critical appraisal of qualitative research: necessity, partialities and the issue of bias
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• http://orcid.org/0000-0001-5660-8224 Veronika Williams ,
• Anne-Marie Boylan ,
• http://orcid.org/0000-0003-4597-1276 David Nunan
• Nuffield Department of Primary Care Health Sciences , University of Oxford, Radcliffe Observatory Quarter , Oxford , UK
• Correspondence to Dr Veronika Williams, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK; veronika.williams{at}phc.ox.ac.uk

https://doi.org/10.1136/bmjebm-2018-111132

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• qualitative research

Introduction

Qualitative evidence allows researchers to analyse human experience and provides useful exploratory insights into experiential matters and meaning, often explaining the ‘how’ and ‘why’. As we have argued previously 1 , qualitative research has an important place within evidence-based healthcare, contributing to among other things policy on patient safety, 2 prescribing, 3 4 and understanding chronic illness. 5 Equally, it offers additional insight into quantitative studies, explaining contextual factors surrounding a successful intervention or why an intervention might have ‘failed’ or ‘succeeded’ where effect sizes cannot. It is for these reasons that the MRC strongly recommends including qualitative evaluations when developing and evaluating complex interventions. 6

Critical appraisal of qualitative research

Is it necessary.

Although the importance of qualitative research to improve health services and care is now increasingly widely supported (discussed in paper 1), the role of appraising the quality of qualitative health research is still debated. 8 10 Despite a large body of literature focusing on appraisal and rigour, 9 11–15 often referred to as ‘trustworthiness’ 16 in qualitative research, there remains debate about how to —and even whether to—critically appraise qualitative research. 8–10 17–19 However, if we are to make a case for qualitative research as integral to evidence-based healthcare, then any argument to omit a crucial element of evidence-based practice is difficult to justify. That being said, simply applying the standards of rigour used to appraise studies based on the positivist paradigm (Positivism depends on quantifiable observations to test hypotheses and assumes that the researcher is independent of the study. Research situated within a positivist paradigm isbased purely on facts and consider the world to be external and objective and is concerned with validity, reliability and generalisability as measures of rigour.) would be misplaced given the different epistemological underpinnings of the two types of data.

Given its scope and its place within health research, the robust and systematic appraisal of qualitative research to assess its trustworthiness is as paramount to its implementation in clinical practice as any other type of research. It is important to appraise different qualitative studies in relation to the specific methodology used because the methodological approach is linked to the ‘outcome’ of the research (eg, theory development, phenomenological understandings and credibility of findings). Moreover, appraisal needs to go beyond merely describing the specific details of the methods used (eg, how data were collected and analysed), with additional focus needed on the overarching research design and its appropriateness in accordance with the study remit and objectives.

Poorly conducted qualitative research has been described as ‘worthless, becomes fiction and loses its utility’. 20 However, without a deep understanding of concepts of quality in qualitative research or at least an appropriate means to assess its quality, good qualitative research also risks being dismissed, particularly in the context of evidence-based healthcare where end users may not be well versed in this paradigm.

How is appraisal currently performed?

Appraising the quality of qualitative research is not a new concept—there are a number of published appraisal tools, frameworks and checklists in existence. 21–23  An important and often overlooked point is the confusion between tools designed for appraising methodological quality and reporting guidelines designed to assess the quality of methods reporting. An example is the Consolidate Criteria for Reporting Qualitative Research (COREQ) 24 checklist, which was designed to provide standards for authors when reporting qualitative research but is often mistaken for a methods appraisal tool. 10

Broadly speaking there are two types of critical appraisal approaches for qualitative research: checklists and frameworks. Checklists have often been criticised for confusing quality in qualitative research with ‘technical fixes’ 21 25 , resulting in the erroneous prioritisation of particular aspects of methodological processes over others (eg, multiple coding and triangulation). It could be argued that a checklist approach adopts the positivist paradigm, where the focus is on objectively assessing ‘quality’ where the assumptions is that the researcher is independent of the research conducted. This may result in the application of quantitative understandings of bias in order to judge aspects of recruitment, sampling, data collection and analysis in qualitative research papers. One of the most widely used appraisal tools is the Critical Appraisal Skills Programme (CASP) 26 and along with the JBI QARI (Joanna Briggs Institute Qualitative Assessment and Assessment Instrument) 27 presents examples which tend to mimic the quantitative approach to appraisal. The CASP qualitative tool follows that of other CASP appraisal tools for quantitative research designs developed in the 1990s. The similarities are therefore unsurprising given the status of qualitative research at that time.

Frameworks focus on the overarching concepts of quality in qualitative research, including transparency, reflexivity, dependability and transferability (see box 1 ). 11–13 15 16 20 28 However, unless the reader is familiar with these concepts—their meaning and impact, and how to interpret them—they will have difficulty applying them when critically appraising a paper.

The main issue concerning currently available checklist and framework appraisal methods is that they take a broad brush approach to ‘qualitative’ research as whole, with few, if any, sufficiently differentiating between the different methodological approaches (eg, Grounded Theory, Interpretative Phenomenology, Discourse Analysis) nor different methods of data collection (interviewing, focus groups and observations). In this sense, it is akin to taking the entire field of ‘quantitative’ study designs and applying a single method or tool for their quality appraisal. In the case of qualitative research, checklists, therefore, offer only a blunt and arguably ineffective tool and potentially promote an incomplete understanding of good ‘quality’ in qualitative research. Likewise, current framework methods do not take into account how concepts differ in their application across the variety of qualitative approaches and, like checklists, they also do not differentiate between different qualitative methodologies.

On the need for specific appraisal tools

Current approaches to the appraisal of the methodological rigour of the differing types of qualitative research converge towards checklists or frameworks. More importantly, the current tools do not explicitly acknowledge the prejudices that may be present in the different types of qualitative research.

Concepts of rigour or trustworthiness within qualitative research 31

Transferability: the extent to which the presented study allows readers to make connections between the study’s data and wider community settings, ie, transfer conceptual findings to other contexts.

Credibility: extent to which a research account is believable and appropriate, particularly in relation to the stories told by participants and the interpretations made by the researcher.

Reflexivity: refers to the researchers’ engagement of continuous examination and explanation of how they have influenced a research project from choosing a research question to sampling, data collection, analysis and interpretation of data.

Transparency: making explicit the whole research process from sampling strategies, data collection to analysis. The rationale for decisions made is as important as the decisions themselves.

However, we often talk about these concepts in general terms, and it might be helpful to give some explicit examples of how the ‘technical processes’ affect these, for example, partialities related to:

Selection: recruiting participants via gatekeepers, such as healthcare professionals or clinicians, who may select them based on whether they believe them to be ‘good’ participants for interviews/focus groups.

Data collection: poor interview guide with closed questions which encourage yes/no answers and/leading questions.

Reflexivity and transparency: where researchers may focus their analysis on preconceived ideas rather than ground their analysis in the data and do not reflect on the impact of this in a transparent way.

The lack of tailored, method-specific appraisal tools has potentially contributed to the poor uptake and use of qualitative research for informing evidence-based decision making. To improve this situation, we propose the need for more robust quality appraisal tools that explicitly encompass both the core design aspects of all qualitative research (sampling/data collection/analysis) but also considered the specific partialities that can be presented with different methodological approaches. Such tools might draw on the strengths of current frameworks and checklists while providing users with sufficient understanding of concepts of rigour in relation to the different types of qualitative methods. We provide an outline of such tools in the third and final paper in this series.

As qualitative research becomes ever more embedded in health science research, and in order for that research to have better impact on healthcare decisions, we need to rethink critical appraisal and develop tools that allow differentiated evaluations of the myriad of qualitative methodological approaches rather than continuing to treat qualitative research as a single unified approach.

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• ↵ CASP (Critical Appraisal Skills Programme). date unknown . http://www.phru.nhs.uk/Pages/PHD/CASP.htm .
• ↵ The Joanna Briggs Institute . JBI QARI Critical appraisal checklist for interpretive & critical research . Adelaide : The Joanna Briggs Institute , 2014 .
• Stephens J ,

Contributors VW and DN: conceived the idea for this article. VW: wrote the first draft. AMB and DN: contributed to the final draft. All authors approve the submitted article.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Correction notice This article has been updated since its original publication to include a new reference (reference 1.)

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André Queirós Higher Polytechnic Institute of Gaya, V. N. Gaia, Portugal

Daniel Faria Higher Polytechnic Institute of Gaya, V. N. Gaia, Portugal

Fernando Almeida Faculty of Engineering of Oporto University, INESC TEC, Porto, Portugal

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STRENGTHS AND LIMITATIONS OF QUALITATIVE AND QUANTITATIVE RESEARCH METHODS

Scientific research adopts qualitative and quantitative methodologies in the modeling and analysis of numerous phenomena. The qualitative methodology intends to understand a complex reality and the meaning of actions in a given context. On the other hand, the quantitative methodology seeks to obtain accurate and reliable measurements that allow a statistical analysis. Both methodologies offer a set of methods, potentialities and limitations that must be explored and known by researchers. This paper concisely maps a total of seven qualitative methods and five quantitative methods. A comparative analysis of the most relevant and adopted methods is done to understand the main strengths and limitations of them. Additionally, the work developed intends to be a fundamental reference for the accomplishment of a research study, in which the researcher intends to adopt a qualitative or quantitative methodology. Through the analysis of the advantages and disadvantages of each method, it becomes possible to formulate a more accurate, informed and complete choice.

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SWOT analysis of the dental hygiene profession in Pakistan—past, present, and future

• Iqra Damani 1 ,
• Shazia Taimoor 1 ,
• Fahad Umer   ORCID: orcid.org/0000-0003-3817-5941 1 ,
• Rashna Hoshang Sukhia   ORCID: orcid.org/0000-0001-9210-6432 1 &
• Ali Sadiq   ORCID: orcid.org/0000-0003-3336-3513 1  

BDJ Open volume  10 , Article number:  71 ( 2024 ) Cite this article

Metrics details

• Preventive dentistry

Pakistan faces a significant burden of oral diseases, which can be effectively reduced through preventive measures. Dentistry in Pakistan predominantly focuses on corrective dental procedures, increasing the treatment costs and widens disparities in oral healthcare access. To address this gap and meet the country’s oral health needs, Aga Khan University initiated a Dental Hygiene program aimed to expand and diversify the oral health workforce and improving access to quality care in various healthcare settings. Due to limited awareness of this profession in the country, the program encounters significant challenges.

This article aims to present a SWOT analysis of the Dental Hygiene profession in Pakistan and propose evidence-based strategic changes to address these challenges and improve future outcomes.

A SWOT analysis was conducted to identify the internal strengths, weaknesses, external opportunities, and threats related to the Dental Hygiene profession, gathering both quantitative and qualitative data through a survey of relevant stakeholders (Consultants, Dental hygiene graduates, dental auxiliaries, fresh dental graduates, and prospective students) using Research Electronic Data Capture (REDCap).

A total of 267 respondents participated in the survey, providing insights into the current state of the Dental Hygiene profession.

The analysis reveals that the Dental Hygiene profession in Pakistan requires robust advocacy, increased collaboration with dentists, opportunities for higher education, and the establishment of proper legislative frameworks to prevent professional transgression beyond the scope of practice.

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Introduction.

Noncommunicable Diseases (NCDs) are a major healthcare burden worldwide [ 1 ]. In oral health, Dental caries and Periodontal disease are two primary NCDs globally [ 2 ]. According to systematic reviews conducted in 2021 and 2022, the prevalence of Dental caries is more than 60% and Periodontal Disease is 56% across all provinces of Pakistan [ 3 , 4 ]. Untreated carious lesions can be painful and may lead to functional limitation [ 3 ]. Conversely, untreated periodontal disease along with having intraoral consequences is correlated with other systemic diseases such as stroke, cardiovascular disease, and preterm birth in pregnant women [ 5 ]. The incidence of oral disease in Pakistan compounds the significant burden of NCDs [ 6 ]. Additionally, there is a high prevalence of oral cancer and oral submucous fibrosis [ 7 ]. Thus, the oral disease burden in Pakistan is notably high.

Dentistry in Pakistan predominantly focuses on corrective procedures such as drilling and filling. This approach increases treatment costs and widens oral healthcare disparities. According to Khan 2019, less than 3% of treatments in government dental institutions were preventive services such as examination, scaling, and prophylaxis, while over 90% were tooth extractions [ 8 , 9 ]. The practicing dentist-to-population ratios (DPR) vary widely among countries. As per WHO, the DPR in most Western countries is 1:2000. As per 2018 estimates, the DPR for Pakistan was around 1:10,000. This shows the DPR to remain far below the accepted value [ 8 ]. Furthermore, the country has a dire insufficient supply of quality dental professionals. According to 2018 estimates, only 21,000 licensed dentists are registered with the Pakistan Medical Commission (PMC), which is inadequate for a population of over 235 million people. The unmet oral needs of the population are intensified further as oral diseases become more progressive and cumulative, increasing the complexity of issues over time [ 8 ].

The Dental Hygiene program in Pakistan was initiated by the Aga Khan University (AKU) to address this gap. The aim of the vocation is to expand and diversify the oral health workforce, enabling access to quality care in the public and private sectors. Regular checkups by these well-trained professionals can prevent painful and severe dental problems and help in early detection of oral health issues, including pre-cancerous lesions [ 5 ].

To date, fifty-one students have graduated with a Diploma in Dental Hygiene (DDH), which was later upgraded into the Associate of Science in Dental Hygiene (ASDH). The graduates provide services in primary, secondary and tertiary healthcare settings, private dental clinics, academia, and research. Till 2022, this program had reached 300,000 people through community outreach activities. ( https://www.aku.edu/mcpk/undergraduate/Documents/Dental%20Hygiene%20Program%20Report%202022.pdf ).

But not being a widely known profession to the population, this vocation faces several challenges such as acceptance from dentists and community, absence of legislation and regulatory body, and avenues of completing higher education. To systematically identify the strengths, weaknesses, opportunities, and threats a SWOT analysis was conducted to address and mitigate the challenges faced by this profession.

Materials and methods

The study was approved by the Aga Khan University Ethical Review Committee, ERC number 2023-9467-27282.

This study explicitly focused on relevant stakeholders involved with the Dental Hygiene Profession. The five stakeholders identified were the AKU dental hygiene graduates, dental consultants, dental auxiliaries (dental assistants and technicians), fresh dental graduates and prospective students. The survey forms were created on the software Research Electronic Data Capture (REDCap). The sample size was calculated as considering a population size (Dentist, Dental Auxiliaries, Alumni, Dental Graduates, and Prospective students) of 5000, with a hypothesized percentage frequency of outcome factor in the population of 50%, a confidence limit of 5%, and a design effect of, a total sample size of 357 individuals will be required to achieve a confidence level of 95%.

Data collection

All the survey administration and data collection were done online. The participants were approached through the existing program office database, social media groups, and word of mouth. The e-consent was taken from all the participants at the beginning of the survey. Intense efforts were made to ensure the representation of participants from diverse geographic regions within Pakistan to capture a comprehensive perspective. Participant’s selection criteria are provided in Supplementary Table  1 .

The results are presented in five sections: first, the results from AKU dental hygiene graduates; second, the responses of dental consultants; third, the responses of dental auxiliaries; fourth, the responses of final-year dental students/house officers; and fifth, the prospective students.

A total of n  = 267 respondents participated in the survey. The study included five different surveys which were distributed among relevant stakeholders. This included n  = 32 AKU dental hygiene graduates, n  = 42 dental auxiliaries, n  = 41 dental consultants, n  = 94 final year dental students and house officers, and n  = 58 prospective students (refer Fig.  1 ).

illustrate the participants distribution across all groups. n  = 32 AKU dental hygiene graduates, n  = 42 dental auxiliaries, n  = 41 dental consultants, n  = 94 final year dental students and house officers, and n  = 58 prospective students.

AKU dental hygiene graduates

In this survey, 32 AKU dental graduates participated. Of these, 60% ( n  = 19) reported working as Dental Hygienists, 18% ( n  = 6) were working in other fields (such as business analysts, research associates, and program officers), and 13% ( n  = 4) were pursuing higher education. Only 9% ( n  = 3) were neither working nor studying. Additionally, 94.3% ( n  = 29) expressed a strong desire to pursue higher education.

On a scale of 1–10, the mean rating for the overall quality of the dental hygiene academic program was 6.73, while the mean satisfaction level with the program’s clinical training and experience was 7.27. Furthermore, 51.3% ( n  = 19) agreed that they were happy with their career choice in dental hygiene. 21.6% ( n  = 8) were not happy with dental hygiene as their career choice, where 27% ( n  = 10) remained neutral about it.

A notable 72% of dental hygiene graduates who responded highlighted the need for licensing and regulation of the profession in Pakistan. The survey also revealed that 10.8% ( n  = 4) strongly disagreed and 29.7% ( n  = 11) were neutral about their ability to apply their dental hygiene education in their current workplace. Lastly, 48.6% strongly believed that additional training and education are needed to enhance their skills as dental hygienists. 83.8% ( n  = 31) strongly advocated for four years degree instead of two years (refer Table  1 ).

Dental consultants

This survey included n  = 41 consultant dentists from various specialties (Prosthodontist, Periodontist, Orthodontist, Endodontist, and Maxillofacial Surgeon) representing both private and institutional practices; 92.8% ( n  = 37) agreed that dental hygienists contribute positively to their practice and 87.8% ( n  = 35) acknowledged their role in revenue generation, with 68.3% ( n  = 27) willing to hire dental hygienists, while 24.4% ( n  = 10) were not sure.

However, 12.1% ( n  = 5) consultants also raised a concern on professional transgression beyond the scope of practice as a threat. Other highlighted points in the survey were reported as economic feasibility 2.4% ( n  = 1), collaboration between dental hygienists and dentists 2.4% ( n  = 1) and need for dental hygiene regulatory body in Pakistan 4.8% ( n  = 2). (refer Table  2 ) (Supplementary Table  2 ).

Dental auxiliaries (dental assistants/nurses and dental hygienists)

65% ( n  = 26) dental auxiliaries were not aware of the dental hygiene profession. However, after the survey a considerable proportion of the respondents 73.2% ( n  = 30) showed a desire to further their careers by pursuing dental hygiene. Furthermore, 76% ( n  = 29) of dental assistants showed interest in enrolling in a four-year bachelor’s program instead of a two-year associate degree (Supplementary Table  3 ).

Final-year dental students and house officers

Among the 94 fresh dental graduates and students, 71.7% ( n  = 29) expressed interest in pursuing an Associate of Science in Dental Hygiene (ASDH). 94.3% ( n  = 88) of dental students and house officers showed interest in higher education, supporting the introduction of advanced educational programs, and 85.7% ( n  = 80) of final year dental students advocated for a bachelor’s degree in dental hygiene (Supplementary Table  4 ).

Prospective students

There was n  = 58 respondents for the prospective student’s survey. Pre-medical high school students accounted for 75.4% ( n  = 43) of the respondents, and 58.6% ( n  = 34) of this subgroup were not aware of the dental hygiene program/profession. In terms of dental hygiene degree preferences, 19.0% ( n  = 11) stated they had no preference, 36.2% ( n  = 21) preferred an Associate of Science in Dental Hygiene, while 44.8% ( n  = 26) preferred a Bachelor of Science in Dental Hygiene. 15.5% ( n  = 9) of responded that they would be willing to consider a new career despite limited job opportunities, 44.8% ( n  = 26) said that they would choose a career with secure job prospects, and 39.7% ( n  = 23) responded that they were unsure.

The findings of the SWOT analysis are summarized in Table  3 , providing a comprehensive overview of the results.

According to WHO, the overall NCD burden in Pakistan is high ( https://www.who.int/publications/m/item/oral-health-pak-2022-country-profile ) [ 9 ]. The current healthcare system faces several challenges, including lack of access and resources [ 10 ]. This is further compounded by the fact that there is heavy emphasis on curative procedures rather than prevention. A recent white paper by the European Federation of Periodontology (EFP) recommended diversifying the oral health workforce by including dental hygienists and therapists to tackle the disease burden [ 2 ]. Strengthening the dental hygiene profession, which heavily focuses on prevention, could reduce the strain on tertiary care facilities and decrease the incidence of oral diseases [ 11 ]. Oral diseases like dental caries, gingivitis, periodontitis, and oral cancers are preventable through increased public education and awareness initiatives, oral health therapies and regular oral screenings [ 11 ]. In countries with successful dental hygiene programs there has been a notable decline in oral disease [ 12 ].

An analysis of the dental hygiene profession in Pakistan incorporated insights from five key stakeholder groups to evaluate its strengths, weaknesses, opportunities, and threats. AKU dental hygiene graduates provided firsthand insights into professional challenges, while dental consultants offered crucial perspectives since dental hygienists must work under their supervision. Dental assistants, as core members of dental practices, represent potential candidates for career progression into dental hygiene. Additionally, dental students, house officers, and prospective students contributed valuable insights into external opportunities and the profession’s future potential. This comprehensive understanding of the current state and future possibilities for dental hygiene in Pakistan was achieved using a SWOT approach, chosen for its broad narrative overview [ 13 ]. A systematic review was not considered due to the limited number of relevant articles and diverse, state-specific nature of global dental hygiene literature, with no specific studies on Pakistan. Therefore, the most meaningful insights come from stakeholders discussing the profession’s past, present, and future in Pakistan.

The AKU dental hygiene graduates survey identified that the majority of the graduates (60%) are working as Dental Hygienists, which shows a strong initial uptake of the profession. Additionally, the presence of graduates working in other fields (18%) or pursuing further education (13%) suggests a more diverse career pathway and opportunities within this field. This pattern is also seen in North American and European countries where this profession is more established. A study conducted in Canada reported that 45% respondents worked outside the traditional clinic practice settings, specifically in education, public health, and research [ 14 ].

The dental hygiene profession in Pakistan still is in infancy and lacks awareness and acceptability among the population and healthcare providers. This may contribute to the divided opinions on career satisfaction, with 51.3% content with their choice, while 27% remain neutral and 21.6% are dissatisfied. Additionally, the lack of awareness of other career pathways also leads to dissatisfaction. In the dental hygiene survey, respondents expressed concerns about the associate degree (two-years), highlighting the need for a bachelor’s degree (four-year) as it is more known and acceptable in Pakistan.

Both the dental consultant and dental hygiene surveys highlighted the strong need for licensing and regulatory bodies. Like National Health Services (NHS), the licensing and regulatory body in Pakistan will help in bringing this profession in the National healthcare framework. It will also help in standardizing and monitoring the scope of practice of dental hygiene. Such body would provide guidelines and Standard Operating Procedures (SoP), preventing professional domain transgression beyond the scope of practice and giving the profession the required legitimacy. Furthermore, this will create societal trust and create positive impact on job opportunities for dental hygienists.

In our survey, dental consultants acknowledged the positive contribution of dental hygienists in dental care. The inclusion of dental hygienist allows dentists to focus on more complex procedures, enhancing the overall effectiveness and efficiency of dental care delivery. This model ensures comprehensive care that addresses both preventive and curative needs, improving overall patient outcomes [ 15 , 16 ].

One of the biggest threats to the dental hygiene profession is the lack of awareness among prospective students about the field. This lack of awareness is hindering the profession’s growth and sustainability. Therefore, strong advocacy is essential for this profession to put its foot in society and become a viable career choice. This can be done via educational campaigns in high school, promotion through mainstream media, and social media. Strong advocacy is important to sustain this profession. (The study’s findings are synthesized in Table  3 , providing a comprehensive overview of the key results discussed).

The progression of dental hygiene profession can also help mitigate one of the Pakistan’s longstanding healthcare challenges: malpractice and quackery. Many untrained dental professionals (quacks), who are practicing without any formal education in dentistry [ 17 , 18 ]. Treatment from these un-trained quacks often lead to serious transmissible infectious diseases such as human immunodeficiency virus/acquired immunodeficiency syndrome, Hepatitis B, and C [ 18 ]. People often resort to these quacks because they are inexpensive and often only accessible option in certain areas, especially rural regions. In many of these rural areas, there is a complete lack of formal oral healthcare infrastructure. Implementing effective use of qualified dental hygienists in primary, secondary, tertiary care practices would be highly beneficial. Placing them in these centers could enhance the practice of by provision of basic dental care services, while referring patients with advanced conditions to qualified dentists. This preventive approach aims to have a long-term positive effect on the overall health status of society at large.

Strengths of the study

According to our research, no previous study has examined the dental profession in Pakistan in this manner. This study involved multiple stakeholders to identify the strengths, weaknesses, opportunities, and threats facing the profession. It serves as a foundational analysis to reflect on and address the challenges within Pakistan’s dental sector. Additionally, this study provides evidence-based insights that can inform policy changes and help predict future outcomes.

Limitations of the study

The findings related to AKU dental hygiene graduates cannot be generalized to all practicing dental hygienists. Although the survey forms were distributed to participants nationwide, the forms did not collect information about the respondents’ provinces, which would have allowed for a more accurate provincial representation. There was response bias, as only the most motivated individuals participated in the survey. Therefore, it may not accurately reflect the views of all hygienists, consultants, and dental auxiliaries. Furthermore, there was sampling bias, as not all population segments had equal access to the internet or the survey platform. Only thirty two out of fifty-one AKU dental hygiene graduates responded.

In our study, we identified four key factors crucial to advancing the dental hygiene profession in Pakistan: career pathways, legalization and regulatory body, scope of practice, and advocacy. Establishing clear and diverse career pathways is essential for professional growth and attracting talent to the field. Implementing robust legal frameworks and establishing a dedicated regulatory body are necessary to standardize practices, ensure quality, and protect both practitioners and patients. Defining and expanding the scope of practice for dental hygienists can enhance their role within the healthcare system, enabling them to perform a broader range of preventive and therapeutic procedures. Promoting advocacy efforts to raise awareness about the importance of dental hygiene and the contributions of dental hygienists can help garner support from policymakers, stakeholders, and the public. Addressing these factors can lead to significant improvements in the dental hygiene profession in Pakistan, ultimately contributing to better oral health outcomes and overall public health.

Data availability

The data analyzed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

We want to thank Noureen Shah; Program Associate, Junaid Hunzai; Dental Hygienist in data collection, Fakeha Azhar Syed for her assistance in survey form creation on REDCap. Special thanks to those who spared their time to fill out the survey.

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Iqra Damani, Shazia Taimoor, Fahad Umer, Rashna Hoshang Sukhia & Ali Sadiq

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AS: Contributed to conception, design, data acquisition and interpretation, and critically revised the manuscript. ID: contributed to design, data acquisition and interpretation, and drafted the manuscript. ST: data acquisition and writeup. RHS: Sample size calculation, statistical analysis and interpretation. FU: Writeup and critically revised the manuscript.

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Correspondence to Ali Sadiq .

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Ethical approval

The study was approved by the Aga Khan University Ethical Review Committee, ERC number 2023-9467-27282. Consent was taken from all the participants at the beginning of the survey.

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Damani, I., Taimoor, S., Umer, F. et al. SWOT analysis of the dental hygiene profession in Pakistan—past, present, and future. BDJ Open 10 , 71 (2024). https://doi.org/10.1038/s41405-024-00255-y

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DOI : https://doi.org/10.1038/s41405-024-00255-y

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