a weakness of qualitative research can take the form of

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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Strengths and weaknesses of qualitative research in social science studies

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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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Limitations and Weaknesses Of Qualitative Research

• Post author: Edeh Samuel Chukwuemeka ACMC
• Post published: August 31, 2022
• Post category: Scholarly Articles

Limitations and Weaknesses Of Qualitative Research: To make informed conclusions, research involves obtaining data. The analysis is founded on logical thinking, as accuracy is one of the most important components of research. Research takes several forms and may serve various purposes, depending on the methodology used. There are primarily two main research methodologies: quantitative (focused on measurement and figures) and qualitative (concerned with understanding and words).

Anyone who has looked through a lot of figures, though, is aware of how impersonal it might feel. What do figures tell us about someone’s views, motivations, and thoughts? Even while it’s important to gather statistical data to spot company trends and inefficiencies, statistics don’t always provide the whole picture.

For a long time, qualitative research has been conducted using its guiding principles. Findings from this research approach have frequently been utilized by media and marketing to provide targeted content or provide a personalized brand message.

Data from qualitative research mostly comes from observations made by people. It can provide a deeper, more complete picture of consumer behavior by providing a window into audiences’ brains that quantitative data simply cannot. Customers appreciate hearing from businesses, so talking to them helps marketers better understand who their target market is. It also helps with customer service. This improves a company’s interaction with its customers and prepares the road for consumer endorsements.

As we’ve previously said, qualitative research is done to learn more about the underlying causes and motives in-depth. Qualitative research does have constraints, though. So, in this essay, we’ll talk about the Limitations and weaknesses of qualitative research.

Recommended: Limitations and Weaknesses Of Quantitative Research

Table of Contents

What is qualitative research?

A market research technique called qualitative research concentrates on gathering information through conversational and open-ended dialogue. This approach emphasizes “ why ” rather than “ what ” others think of you. Marketers like penetrating their target audience’s brains. But to achieve that, they must conduct a qualitative study. Qualitative observations, focus groups, and in-person interviews may all give you insightful information about your market, your goods, and the attitudes and motives of your consumers.

Consider that you operate a general audience web store. Demographic investigation reveals that the majority of your consumers are men. Naturally, you’ll be curious to know why ladies aren’t making purchases from you. And you’ll be able to discover it through qualitative research.

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Limitations and Weaknesses of Qualitative Research Methods

1. The data quality is very debatable: This is where the subjective aspect of data collection in qualitative research may potentially be a drawback. Another researcher may view data that one believes is relevant and necessary to collect as meaningless and choose not to pursue it.

Individual viewpoints and instinctive choices might result in very comprehensive data. Because of its dependence on researcher subjectivism, it can also result in data that is oversimplified or even erroneous.

2. It is based on the researcher’s experience: Only the experience of the researchers participating in the process will determine the quality of the data gathered through qualitative research. A researcher who is knowledgeable about the sector must gather data that is particular to that business.

For the data to be accurate, researchers must also be skilled at conducting effective interviews, brave enough to follow up with participants, and able to establish rapport with them on a professional level.

Also see: Advantages and Disadvantages of Being an Entrepreneur

3. It is more challenging to evaluate and prove data rigidity: It is more challenging to demonstrate rigidity in collective data since individual viewpoints frequently serve as the basis of data collected in qualitative research. The human mind frequently recalls information in the way that it desires. Because of this, even if the events themselves may have been rather upsetting at the time, recollections are frequently viewed with nostalgia.

Researchers find it challenging to show the veracity of their findings because of our fundamental tendency to see the bright side of things.

4. It could take a lot of time: Data collection takes longer since researchers go off in many different directions. Additionally, sorting through all of that additional data takes time. The value of every data point is never certain since it is appraised subjectively.

In contrast to data gathered via qualitative research, data gathered through other research forms are subject to strict criteria and expectations that enable it to be reviewed and used more quickly.

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5. Data with uncertain values are produced: Due to the diversity of their viewpoints, even researchers may disagree on the importance of the data being gathered. The qualitative research method depends on the researcher engaged to determine what is included and what is eliminated. Due to its very subjective nature, this data collecting procedure. It is always feasible to offer detailed data, but only in cases when the researcher can put their prejudice and viewpoint aside and present the material in its unprocessed state.

6. It is not statistically significant: Its absence of statistical representation is the one drawback of qualitative research that is always present. The replies provided are not quantified because it is a perspective-based research approach only.

Although it is possible to compare results and this may result in the necessary duplication. Most situations that call for statistical representation and are outside the scope of qualitative research need quantitative data.

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7. Repeated qualitative research periods may be necessary for difficult conclusions: For brands and enterprises that must make a difficult or possibly divisive decision, the smaller sample sizes of qualitative research may be both an advantage and a drawback.

Even though the people in the sample share a lot of characteristics, a small sample is not always indicative of wider general demography. This indicates that a follow-up with a bigger quantitative sample may be required to track data points with more precision and make a better overall judgment.

8. Qualitative research-generated data isn’t often taken seriously: Findings from qualitative research are not always embraced by the scientific community because of the subjective character of the data that is gathered. To start the process of community acceptability, it is frequently required to conduct a second independent qualitative research project that can yield comparable findings.

Also see: Differences Between Objective And Subjective

9. In the course of qualitative study, hidden facts may vanish: It is entrusted to the researcher with a great deal of faith that they will obtain and then compile the hidden data that a supplier makes available. The ability of the researcher to make all the connections is essential to the research’s success.

If the researcher is successful in doing this, the data will be significant and will aid brands in advancing their goals. Otherwise, until the initial findings are acquired, there is no ability to change the course of action. The next step is to start a fresh qualitative procedure.

10. Researcher influence may have a detrimental impact on the data gathered: Qualitative research relies heavily on the abilities and observation of the researcher to provide high-quality data. A researcher’s point of view will be integrated with the data gathered if they have a biased viewpoint, which will affect the results.

Controls must be in place to assist in removing the possibility of bias so that the data gathered may be examined honestly. Otherwise, a researcher might assert anything and then utilize their bias in qualitative research to support their claim.

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Any qualitative research project, in practice, has advantages and disadvantages. Thus, being aware of the constraints is essential to successful and relevant data collection. Qualitative research studies have the drawbacks of being more difficult to comprehend and are less likely to generalize to the entire community. It is essential to have a better understanding of how certain individuals and even groups think. But someone will always doubt the data’s dependability and truthfulness because of how subjective it is.

Edeh Samuel Chukwuemeka, ACMC, is a lawyer and a certified mediator/conciliator in Nigeria. He is also a developer with knowledge in various programming languages. Samuel is determined to leverage his skills in technology, SEO, and legal practice to revolutionize the legal profession worldwide by creating web and mobile applications that simplify legal research. Sam is also passionate about educating and providing valuable information to people.

Strengths and Weaknesses of Quantitative and Qualitative Research

There are few things more useful in developing and implementing strategies than reliable data. The only drawback is that this information can be difficult to understand, which results in many business owners knowing nothing about their own research.

When starting a company or building a product, most people ask themselves the question: qualitative or quantitative research? Given the importance of coming up with a good strategy, this is not an easy question to answer.

Here is a quick look at the strengths and weaknesses of quantitative research.

What Is Quantitative Research?

Quantitative research is a study of numerical data whose purpose is to measure the strength and direction of relationships between variables. Quantitative research uses statistics to make sense of numerical data.

Quantitative research is based on numerical data gathered from different types of research methods, such as questionnaires, structured interviews, and statistical analysis.

Quantitative research involves questions that can be answered by counting or measuring, such as, how many people purchased a product? How many people are satisfied with the customer service ? What are the demographics of customers in different age groups?

For your study to be quantitative, you need to use numerical data to either prove or disprove your hypothesis.

For example, a quantitative research about a new product launch could use data like the average consumption of products in the category among the target population, the number of competitors and their individual market share, pricing points, and the marketing budget required to launch a brand awareness campaign, to mention a few.

This type of research helps you to understand your market and target audience, so you can make informed decisions about your product or service.

The biggest advantage of quantitative research is the ability to analyze large volumes of data and make conclusions based on that data.

Difference Between Qualitative And Quantitative Research

The main difference is this – Qualitative research methods include the collection of data through the use of open-ended questions, unstructured interviews, or observations, whereas, Quantitative research focuses on gathering numerical data and making generalizations about groups of people, situations, or phenomena.

Understanding human behavior and its governing reasons are the ultimate goals of Qualitative research. The discipline explores the “why” and “how” of decision-making.

Quantitative data collection methods are more structured than qualitative data collection ones.

When you need to gather a large amount of information from a group of people, there are many ways to do so. In quantitative research, data can be collected using a variety of methods, including surveys, interviews, observation, and online polls.

A good researcher knows when to use qualitative research (to understand opinions) vs quantitative research (to test objectively). 

For example, if you want to know what people think about a particular topic, then qualitative research would be best; but if you want to determine how many people are aware of a particular issue, then quantitative research would be better.

When you use both qualitative and quantitative research methods in your surveys, you will gain results that reach a lot of people as well as deeper insights from those people. With the right question types and analysis, you can use quantitative research to gain statistically significant insights into your target audience’s attitudes and behaviors.

Qualitative questions are useful for gathering detailed feedback on open-ended topics like:

Customer satisfaction. Qualitative questions let customers explain how they feel about your company’s products or services, and why they feel that way.

Employee engagement. Use open-ended questions to solicit employee feedback on company culture, management practices, benefits, and more.

Service performance. Learn why customers choose your brand over competitors’ by asking for the specific reasons for their decision.

Market research. Open-ended questions help you identify the most important factors that influence customers’ purchasing decisions in your market.

Quantitative research is ideal for:

• Collecting data at scale (e.g., using survey software)
• Reaching a large number of respondents in a short period of time
• Analyzing trends that apply to large groups of people (e.g., gender differences)
• Highlighting broad patterns or relationships between variables
• Predicting likelihoods based on certain factors (e.g., age, income)
• Driving the direction of future quantitative studies (i.e., hypothesis testing)

Importance Of Quantitative Research

The importance of quantitative research is that it provides an objective way to measure things, as well as a means of testing theories. Additionally, the results of quantitative research may be more easily replicated by other researchers.

Quantitative research is conducted in an effort to find numbers and statistical analysis to determine relationships between two or more variables. The process involves taking data from various sources and then organizing it into a format that can be used for statistical analysis.

One advantage of quantitative research is its ability to measure hard numbers and facts. This makes it much simpler to analyze data. 

For example, if you wanted to know the average income of people living in a certain area, all you would have to do is calculate the number of participants in your study who earn above and below a certain amount. You could also compare this data with other areas to see which has the highest average income levels.

Another advantage is that quantitative research allows researchers to replicate their findings using different samples or methods. The ability to replicate results ensures accuracy and consistency in results obtained from different studies conducted on similar topics over time. 

Furthermore, this type of research may reveal new insights into how something works because it focuses on measurable relationships rather than just observations about what happens in nature or human behavior itself.

Characteristics Of Quantitative Research

Quantitative research is the type of research that most people think about when they hear the word “research”. It involves creating statistical models, analyzing data, and using mathematical theories to understand how things work.

Quantitative research is used to identify factors that affect relationships between variables. Quantitative research is widely used in psychology, economics, demography, and marketing. It is often used in natural sciences, such as biology and chemistry, and in social sciences, such as sociology and psychology. Quantitative research involves the use of computational, mathematical, or statistical techniques.

For example, if a researcher believes that watching television makes people more violent, he or she may use quantitative methods to test this theory by counting the number of violent acts depicted in a week’s worth of programming and comparing it with the number of violent crimes committed for the same time period.

These are some essential characteristics of Quantitative research:

• The focus is on measurement, analysis, and prediction of phenomena through the use of mathematical models and theories.
• Quantitative research’s objective is to obtain information about the current status of a given phenomenon.
• The focus is on variables and the relationships between them.
• The researcher can manipulate variables, which is why experiments are often used in quantitative research.
• Quantitative research includes formal data collection methods.
• The results are based on large sample sizes, so the results have high statistical power and are more likely to be statistically significant (i.e., not due to chance).
• Data is analyzed using statistical techniques.
• Quantitative research typically uses deductive reasoning.
• Variables must be identified and measured using reliable instruments and procedures; using multiple methods of measurement increases the reliability and validity of results (triangulation).

The design of a quantitative research question must be structured or ‘closed’ so that it can be answered using a predetermined response format (usually dichotomous or multiple choice) or scaled responses. 

The design of the quantitative research question should not allow respondents to answer in their own words. This will make it impossible to use the data in any meaningful way. 

The quantitative design will measure whether a change has occurred from a specific point in time, but will not determine why a change has occurred.

Quantitative research questions are best for giving an overview or analysis of a particular business, industry, or topic. Therefore, they need to be researched in detail so that the researcher can be confident that enough information exists to answer the questions. If there is no literature available on the topic, then it is unlikely that you will have sufficient knowledge to investigate the topic effectively.

Conducting thorough industry research is crucial in ensuring that the quantitative research questions are well-informed and grounded in existing knowledge.

Strengths Of Quantitative Research

Quantitative research is often used to ask questions that can be answered with numerical data. It has a number of strengths:

• Standardized data collection

This means that the same instruments are used with all the participants in a study, and the data is collected in a uniform way. This makes it easier to compare results across groups of participants or to test hypotheses on a larger scale.

• Objectivity

The standardization of both data collection and analysis can make results from studies more objective than those with qualitative research methods. The use of statistics and hard numbers can also give your findings authority when you publish them online or in a print journal. This objectivity makes it easier for researchers to explain why their findings are reliable and true.

• Difficult Data Collection

Quantitative studies can also provide researchers with data about phenomena that are difficult or impossible to measure directly, such as attitudes, beliefs, and values.

Quantitative research allows for larger sample sizes, which increases the reliability of your results. It also moves quickly and can produce results that are easy to share with others, because they’re often presented as percentages.

• Generalizability

You might find that what you learn applies not only to your research participants but also to people who weren’t included in your study. For example, if you ask 1,000 people what’s important to them about their job, you might find out some things about how work affects happiness that could be true for other people as well.

• Evidence Collection

The design of a quantitative study allows the researcher to collect numerical data that can be analyzed using statistical tests. This provides an opportunity for the researcher to support or refute theories by collecting evidence that is statistically significant.

Weaknesses Of Quantitative Research

Quantitative research is a useful tool for measuring and describing the world as it exists, but it has its weaknesses as well.

Quantitative data is often criticized for being too detached from real-life situations; this criticism typically stems from the fact that the data collected tends to be structured and limited in nature. 

Some have argued that quantitative analysis does not provide people with a full picture of complex issues or human behavior since it is concerned with measuring and counting specific variables.

Quantitative researchers are concerned with how much and how many, but their methods don’t allow them to understand why something happens. They can find correlations between factors, but not necessarily causes. 

For example, they might discover that people who drink more coffee have higher rates of cardiovascular disease than people who drink less coffee, but they can’t conclude that drinking coffee causes heart problems.

Quantitative research doesn’t always take into account a human element. People make decisions based on more than just mathematical calculations, and that’s an important part of the human experience. It’s also difficult to account for the subjective nature of human experience in quantitative methods such as surveys and questionnaires.

Quantitative research tends to minimize the role of the researcher in the research process, thereby reducing the amount of information that can be obtained on contextual factors.

Quantitative research tends not to generate new ideas or shed light on unexplored areas because they focus on testing hypotheses derived from existing theories and concepts.

Types Of Quantitative Research

There are five main types of Quantitative research:

• Descriptive Research

Descriptive research produces a description of what already exists in a group or population. It usually involves taking a sample from the population in order to describe a certain characteristic of the entire group. 

It does not seek to explain why things are a certain way or how they came about but rather describes what is and what is not.

• Correlational Research

Correlational research investigates relationships between variables as well as how these variables interact with one another. 

Unlike descriptive research, correlational research goes beyond description by seeking to identify the strength, direction, and nature of relationships between two or more variables. 

While it cannot be used to determine causality due to its correlational nature, it can be used to predict outcomes based on the relationship that exists between variables.

• Experimental Research

Experimental research involves testing a hypothesis by conducting experiments using various methods such as controlled laboratory-based scenarios, field experiments, and randomized trials. 

Experimental design involves the manipulation and measurement of variables to observe their effect on each other. This enables researchers to determine cause-and-effect relationships between variables.

• Survey Research

Survey research is a quantitative method that involves the usage of different research instruments such as questionnaires or schedules to gather data. 

Surveys are usually done in cases where it is difficult to conduct an experiment such as in the case of social sciences. 

The most common forms of survey research include mail surveys, telephone interviews, and face-to-face interviews.

• Causal-Comparative Research

Causal-comparative research is a type of research that is used when the researcher has limited control over variables, such as in a field experiment. This type of research does not involve randomization of participants or experimental manipulation, as in true experimental studies.

The name causal-comparative research comes from two terms, causal and comparative. Causal implies that the study attempts to determine whether one variable causes another. Comparative indicates that groups are compared but not randomly assigned to groups by the researcher.

When To Use Quantitative Research

Quantitative research is a great way to collect data on a large scale when you have many respondents. 

This can be useful when you need a lot of data points and/or want to record responses for future analysis. It’s also good for surveys that are complex and/or have any questions. 

If your audience is large (across multiple locations, or across countries) or if you have a smaller audience but want them to complete your survey in their own language, quantitative research is the way to go.

If your business is just getting started with market research, quantitative methods will give you an excellent baseline of information upon which to build later qualitative research projects.

Qualitative research gets to the heart of your problem, giving you much more detailed data than quantitative methods would. 

Qualitative research is more appropriate for projects that:

• require more in-depth answers than “yes” or “no”
• have small sample sizes
• require detailed interviews or observations
• are exploratory in nature

Is Qualitative Or Quantitative Research Better?

A good thing to keep in mind is that there isn’t really a “right” answer – it all depends on what you are trying to find out!

Qualitative and Quantitative research is often seen as opposing approaches to research, but they both have their advantages and disadvantages. While there is a lot of debate between these two types of studies, they are not mutually exclusive and can work together to generate meaningful results.

Qualitative research gathers information that seeks to describe a topic more than measure it. Qualitative research is often used to conduct market analysis and identify consumer trends, motivations and behaviors.

Quantitative research is the best way to reveal and prove a cause-and-effect relationship. If you want to make an argument about why something is happening, quantitative research can help you do that. 

For example, if you wanted to say that more guns in the hands of private citizens lowered crime rates, you could run a study with data on crime rates and gun ownership across states and find statistical correlations between them.

Qualitative research describes and interprets what people say and do. Instead of using numbers to describe some phenomenon, it uses words and pictures instead. It’s best for exploring questions that don’t have clear answers yet, like how people feel about a new product or how they respond to a new marketing campaign.

For example, if you wanted to know how people reacted when they saw your new TV commercial, the best way would probably be to show it to people in a focus group and tape their reactions. The group moderator might ask some follow-up questions and people might comment on each other’s reactions, but the goal is less about making an argument than understanding what’s happening.

Is Survey Qualitative Or Quantitative Research?

A survey can be considered qualitative or quantitative depending on the type of questions asked. 

Quantitative surveys ask closed-ended questions – those requiring a “yes” or “no”, a number rating, or a selection from a predetermined list of answers (e.g., choose from “Excellent”, “Good”, etc.). These kinds of questions allow for analysis that can be statistically inferred across the entire population being surveyed.

Qualitative surveys (also known as unstructured interviews) ask open-ended questions that require respondents to provide free-form answers, which cannot be statistically inferred across the entire population being surveyed and therefore may not scale well if the sample size is very large.

Is Questionnaire A Quantitative Research?

A questionnaire is a series of questions or other prompts for gathering information about a subject. Although many researchers use questionnaires for statistical analysis, this is not always the case. So, yes, a questionnaire can be both, qualitative as well as quantitative, depending on the type of questions it contains.

The questionnaire is an integral part of survey research. It is a written or verbal series of questions pertaining to a specific topic, to which the respondent provides answers. 

Questionnaires are usually designed to obtain information from a large number of respondents on one or more occasions. 

The structured interview is normally used where it is necessary to keep close control over the questioning and to ensure that all respondents are asked exactly the same questions in precisely the same way.

The design process can be complex and time-consuming and many aspects need to be decided by the researcher before starting to write up the questionnaire:

• How will you distribute it? By hand? By mail? Online?
• What type of language will you use? Formal? Informal? Will it be general, or will specific jargon be included?
• How long will your questionnaire be?

Is Statistics Quantitative Research?

Quantitative research involves statistical analysis, such as calculating averages or percentages in surveys. In its most basic form, you count things, and then you make conclusions based on the numbers — usually about how common something is.

Statistics is a quantitative research method. It is used to quantify opinions, attitudes, and behaviors. This method involves the statistical analysis of data collected through polls, questionnaires, or surveys. The survey could be administered through personal interviews, telephone conversations, or the use of online survey forms.

This method is the most widely used method in business research. Most businesses make decisions based on quantitative methods. It is easy to administer with a large population size by using computers for ease of calculation and preparation of reports. It is also easy to understand and implement because it uses statistical terms that are easy to understand and interpret. This method is also used in both small and large businesses to make decisions based on quantified data.

Is Quasi-Experimental Quantitative Research?

Quasi-Experimental research is another type of experimental research design. Therefore, it is quantitative research. The difference between them is that the quasi-experimental design does not include a random sample. With this type of design, a researcher will create an experimental group and a control group, but not through random selection. Instead, the researcher will identify participants in each group based on criteria such as specific characteristics or behavior.

One advantage of Quasi-Experimental research is that it is easier to carry out than randomized experiments. It can also be less expensive because it does not require random assignment to groups. 

However, the researcher may have trouble determining whether the results from these groups are credible because there could be mitigating factors impacting the results that were not controlled for in the study’s design.

Does Quantitative Research Have Hypothesis?

Yes, quantitative research methods do have hypotheses. In fact, the whole idea of quantitative research is to test a hypothesis.

The hypothesis of quantitative research must always be stated in a clear manner. This is because the hypothesis helps to explain the relationship that exists between the different variables that have been used for the study.

However, quantitative research does not have a single hypothesis; it always has more than one hypothesis. The number and nature of these hypotheses will depend on the scope and coverage of the study or even research. The researcher will use these hypotheses to conclude whether there was any correlation between the variables that were used, or rather whether one variable had an effect on another variable.

Does Quantitative Research Use Interviews?

Interviews in quantitative research are often structured. This means that the interviewer asks the same questions, in the same order, of every respondent.

This is so that researchers are able to make comparisons between groups of people and draw conclusions about them.

For example, if a survey was looking at how many hours a week people spend on homework, it would be useful to know the subject they are studying and their level of education. These questions would be asked before asking about study time specifically so that any differences between groups can be explored further.

Respondents are also given a limited number of response options to choose from, for example, 1-5 hours 6-10 hours 11-15 hours 16-20 hours 20+ hours. 

Structured interviews also make it easier for data to be analyzed by computer programs or entered into databases.

Does Quantitative Research Focus On Human Experiences?

Quantitative research focuses on human experiences and looks into why people do certain things while others do not carry out the same actions at all. 

Quantitative research is also known as positivist research. 

It is a systematic process of collecting, organizing, analyzing, and interpreting numerical data. 

Quantitative researchers are involved in the entire research process from defining the problem to shaping the findings for presentation. 

They use probability sampling techniques, which refer to selecting samples from a population in such a way that each individual has an equal chance of being selected.

How To Determine Sample Size For Quantitative Research?

There are several methods you can use to determine the sample size. Some methods include using statistic tables and online calculators. Other methods involve using formulas to estimate sample size.

1. Using Statistic Tables

The first method you can use to calculate sample size involves using statistic tables. You need two parameters to do this; they include a confidence level and margin of error.

2. Online Calculators

The second method is by using online calculators like Survey Monkey or Raosoft Sample Size Calculator. To use these calculators, you need to fill out information such as the population, confidence interval, and margin of error among others, and click on calculate button.

3. Using Formulas

A sample size formula can be used to calculate the appropriate sample size based on factors such as population size, the margin of error, and confidence level. There are various formulas you can choose from.

Cochran’s Sample Size Formula is a common one: 

This formula can be used when one needs to determine the appropriate sample size for estimating a proportion or a percentage. 

The formula is: n = (Z 2 *p*q)/e 2 ; 

where n = sample size; p = estimated proportion; q = 1-p; e = margin of error; Z = z-score for confidence level selected. For example, 0.05 for 95% confidence interval.

Is Quantitative Research Objective?

Quantitative research focuses on measurable concepts and uses precise measurements and analysis to answer a specific question. It is thoroughly objective in nature. 

This type of research aims at testing theories by examining the relationship among variables with the help of different research tools. The relationship between variables can be causal or correlational.

In other words, quantitative researchers are more interested in determining whether the data gathered shows a true representation of the population under study.

Is Quantitative Research Scientific And Measurable?

The scientific and measurable characteristic of quantitative research is one of its greatest strengths. In fact, it’s the reason why so many scientists prefer quantitative research over qualitative research. Quantitative research can be reproduced and validated by other researchers, which makes the results generalizable and very reliable.

Because quantitative research is so reliable, it can be used to create a theory or model that accurately describes a phenomenon. 

For example, because Newton’s laws of motion have been verified by countless experiments, we can use them to develop complex models for predicting how objects will behave in different situations.

The data can be obtained using various instruments such as questionnaires and surveys. Quantitative research gathers information that is measurable, such as age, number of hours worked, and so on.

The main objective of quantitative research is to measure phenomena. It allows for the collection of numerical data that can be analyzed in order to explain what is being measured. This type of research aims at verifying theories and hypotheses by means of observation and measurements of variables.

Quantitative research does not deal with subjective ideas or opinions, but with measurable facts. It uses a deductive approach to gather information from a large sample, which then can be used to infer conclusions about the population from which it was drawn.

It can be quite useful to understand what quantitative research is, particularly when you are doing some research of your own. By understanding more about the process, you will be better prepared to make quantitative research and turn it into useful information.

Quantitative research is one of the more scientific/technical forms of market research. It’s a good way to get specific and detailed data (hence quantitative). Not only will you get statistics, numbers, etc., but you’ll actually truly learn something. It’s a great way to find out exactly what your audience wants.

Ultimately, both types of research complement one another. If you don’t have enough data yet, qualitative research can help you identify potential problems in your quantitative study. Even if you have an abundance of data from a previous research project, conducting a qualitative study prior to analyzing your quantitative data and drawing conclusions can lead to better results.

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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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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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The Strengths and Weaknesses of Research Methodology: Comparison and Complimentary between Qualitative and Quantitative Approaches

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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.

• Open access
• Published: 16 September 2024

“ You close the door , wipe your sadness and put on a smiling face ”: a qualitative study of the emotional labour of healthcare professionals providing palliative care in nursing homes in France

• Benoite Umubyeyi 1 ,
• Danièle Leboul 1 &
• Emmanuel Bagaragaza 1  

BMC Health Services Research volume  24 , Article number:  1070 ( 2024 ) Cite this article

Metrics details

Palliative care provided to frail and dying older persons in nursing homes results in intense emotions for residents and their relatives as well as for healthcare professionals. In France, scant attention has been given to how nursing home professionals manage their emotions when providing palliative care. This study analysed the emotional demands of providing palliative care in the nursing home context, the emotional strategies used by healthcare professionals to navigate such demands, and how these demands affect their emotional wellbeing.

This qualitative study used a multiple case study approach. We purposively selected nine nursing homes from three geographical provinces in France with diverse ownership statuses (public, private, associative). Individual interviews and focus group discussions were held with 93 healthcare professionals from various occupational groups employed in the participating nursing homes. Data was collected from April 2021 to September 2022 and was analysed using thematic content analysis.

Data revealed that providing palliative care to dying residents within the nursing home context results in intertwined rewarding and exhausting emotional experiences for healthcare professionals. Professionals have to utilize multifaceted emotional strategies to navigate these experiences, including suppressing and modifying emotions and distancing themselves emotionally from residents to protect themselves from emotional suffering. Participants noted a lack of formal space to express emotions. Unrecognized emotional labour undermines the wellbeing of healthcare professionals in nursing homes, whereas acknowledging emotions enhances satisfaction and gives enhanced meaning to their crucial role in resident care.

Acknowledging emotional labour as an inevitable component of providing palliative care in nursing homes is critical to supporting healthcare professional wellbeing, resilience, and retention, which may ultimately improve the quality of care for dying residents. Ensuring quality care and supporting the emotional wellbeing of nursing home professionals requires an organisational culture that considers emotional expression a collective strength-building resource rather than an individual responsibility, in hopes of shaping a new culture that fully acknowledges their humanity alongside their professional skills.

Trial registration

ClinicalTrials.gov ID: NCT04708002; National registration: ID-RCB number: 2020-A01832-37, Registration date: 2020-12-03.

Peer Review reports

The steady increase in the number of older persons affected by multiple and complex health needs has led to a growing number of nursing home (NH) residents worldwide spending their final moments of life and dying within these settings [ 1 ]. In turn, this trend has generated heightened attention for the necessity of integrating palliative care within the NH, an approach that has not traditionally been an area of focus [ 2 , 3 , 4 ].

The core philosophy and values of the NH are to provide a home-like environment for residents. When residents require palliative and end-of-life care, the focus shifts from supporting quality living to facilitating quality dying [ 5 ]. Such a shift is accompanied by intense emotions for residents, their relatives, and NH professionals who have had intimate interactions with residents and built strong ties and long-lasting relationships with them during the extended caregiving process. The process becomes even more emotionally laden for professionals, as they often see themselves as holding a professional caring role while also taking on the emotional work of a family member role [ 6 ]. When confronted with providing quality living while simultaneously supporting quality dying [ 5 ], NH professionals have to perform significant emotional labour to provide quality care and preserve the professional-resident therapeutic relationship, all the while maintaining their own health and emotional wellbeing [ 7 ].

In France, as in many other countries, the provision of palliative care in NHs relies heavily on a multidisciplinary staff mainly composed of nursing assistants, personal support workers, registered nurses, and other regulated professionals, under the supervision of a medical coordinator. A medical coordinator in the French nursing home context is a physician, generally with geriatric competences, who has an overall coordination and medical advisory role for nursing home and external provider team for enhanced quality care. Moreover, as elsewhere, NHs in France suffer significant staff shortages due to professional fatigue, burnout, and professional turnover [ 8 ]. The recent COVID-19 pandemic has worsened the situation in NHs, with increased COVID-19-related deaths, augmented workloads, expanded isolation, and added psychological burden among care workers [ 9 , 10 ]. There is a pressing need for NH organisations to acknowledge the emotional labour endured by healthcare professionals during the caregiving process, particularly when it involves providing palliative and end-of-life care to residents.

Current evidence has demonstrated a strong link between burnout, job satisfaction, performance, staff retention, and attrition and the emotional labour of caring [ 11 , 12 ]. When healthcare professionals have to suppress or modify their emotions, they experience dissonance between feelings and performance, which in the long term can result in emotional distress, burnout, and intention to leave the profession [ 12 , 13 ]. Other studies have noted that when emotions are freely expressed and supported, they may have a positive impact on professional-patient interpersonal relationships, staff member wellbeing, and the quality of patient care [ 14 ]. However, most studies that have explored the emotional labour involved in providing palliative care have focused on hospital, hospice, or palliative care unit settings. Rarely have these studies been conducted in NH contexts. In fact, the physical labor associated with caring in NHs and the economic aspects of the work, such as wages and scheduling, receive more attention than does emotional labour [ 15 ]. In addition, emotional intelligence is an expected competency of healthcare professionals, particularly an individual’s ability to manage their own emotions to the point that failing to do so is viewed as an individual weakness and professional failure [ 16 ]. Yet, it has been documented that the effectiveness of emotional labour depends on various factors, including the nature of the service and the organisational culture [ 13 ]. This requires situated knowledge to better understand the emotional work performed by healthcare professionals in specific contexts, such as NHs.

Emotional labour in palliative care and in nursing homes

Emotional labour has been defined as the process through which healthcare professionals suppress or change their feelings to align with organisational rules and guidelines while still conveying to others a sense of being cared for [ 17 ]. Emotional labour involves three strategies: surface acting, deep acting, and displaying genuine emotions [ 18 ]. Surface acting entails suppressing or hiding felt emotions or faking unfelt emotions to alter outwards expression. Deep acting entails a conscious attempt to modify inner feelings and felt emotions to match expected emotions [ 18 , 19 ]. Displaying genuine emotions entails the expression of natural emotions that are congruent with felt feelings without any adjustment [ 18 ]. In this study, we conceptualize emotional labour as the efforts deployed by healthcare professionals to manage their emotions when providing palliative care to NH residents.

Nurse scholars have expanded the concept of emotional labour to nursing, emphasizing the emotional component and the demand associated with caring in nursing [ 19 ]. Nurses perform emotional labour when they have to induce or suppress their feelings to align them with what is expected by their institutions to make patients feel cared for and safe, irrespective of their own actual feelings [ 20 , 21 ]. For example, when nurses are confronted with death but feel unable to facilitate a ‘good death’, they may have complex feelings of guilt and anger but may have to suppress these feelings to continue attending to patients and their relatives [ 22 , 23 ].

Emotions are inherently linked to caring, as they are essential to the development of effective and meaningful relationships with patients, their relatives, and other professionals [ 24 ]. Studies that have explored the emotional labour associated with providing palliative care highlight the complexities of the emotionally demanding experiences healthcare professionals encounter in their practice [ 6 , 23 ]. The cumulative emotional effects of grief and sadness experienced by NH professionals attending to dying individuals require them to deploy significant effort to balance the demands of the healthcare organization, the emotional needs of others, and their own wellbeing [ 23 ].

The limited available literature on emotional labour in NHs illuminates the critical influence that the physical and social environments of NHs have on shaping care providers’ emotional experiences of caring for dying residents [ 7 ]. Caring for ill, disoriented residents with aggressive behaviours as well as dying residents in their last stages of life requires NH professionals to regulate their emotions, often masking their true feelings to prioritize the emotional needs of residents and their families above their own [ 6 , 15 ]. Additionally, ethical and moral concerns that professionals face during end-of-life-care provision, such as preserving residents’ dignity, engaging in end-of-life conversations, respecting end-of-life preferences, life-prolonging treatment or treatment withdrawal, likely play a role in emotional regulation and strategies undertaken by professionals [ 23 , 25 ]. All these may affect healthcare professionals’ capacity to interact effectively with residents and co-workers, nurture their sense of self, and provide optimal care [ 7 , 22 ]. However, it is important to note that the regulation of emotions may also produce positive effects, such as facilitating caring and forming the bonds necessary to foster a home-like NH environment [ 5 , 15 ].

Despite the crucial role that emotions play in providing care in NHs, the emotional labour undertaken by NH care professionals remains an invisible aspect of job requirements [ 15 ]. Notwithstanding the critical role that healthcare professionals play in supporting quality living and quality dying for residents in the French NH context, little is known about how they manage their emotions amidst the complex situations they encounter in their practice or how they continue to provide care without jeopardizing their own emotional wellbeing. This study aimed to help fill this gap in the research by (1) analysing the emotional dimensions of providing palliative care in the NH context as well as the strategies used by healthcare professionals to manage the emotional aspects of caring for dying residents and (2) exploring the effects of emotional labour on NH professionals’ wellbeing. To this end, this study sought to answer the following research questions: (1) How do NH professionals manage the emotional demands of caring for residents requiring palliative care? (2) What effects do emotional demands have on professional-resident interactions and the emotional wellbeing of NH professionals? This study’s findings will inform NH management on strategies and interventions to not only reduce the emotional exhaustion and burnout of healthcare professionals but also improve their resilience and wellbeing at work, ensuring that they are best equipped to provide optimal care to residents and their relatives.

Study overview and design

The findings presented in this manuscript originate from a broader implementation study that evaluated the effectiveness of a timely and integrated palliative care approach in 21 NH facilities in France. The initial study used a mixed-method [ 26 ] approach and was segmented into three phases: pre-implementation, implementation, and post-implementation. The current manuscript reports materials from the pre-implementation phase. A detailed methodological description of the broader study has been reported elsewhere [ 27 ]. The qualitative component of the study follows a multiple case study approach [ 28 ]. Among the aims of the qualitative study were to explore NH professionals’ experiences and quality of life at work and to understand how they navigate the emotional demands associated with providing palliative care to residents.

Participants and settings

This manuscript presents qualitative findings from nine out of the 21 NHs that participated in the broader study. The nine NHs were purposively selected to ensure a balanced sample of three NHs per geographical region (Iles de France, Nouvelle Aquitaine, Provence-Alpes-Côte d’Azur) as well as diversity in terms of ownership status (public, private, and private non-profit).

For this study, we purposively included healthcare professionals from various occupational groups employed on a fixed contract in the selected NHs. Participants had to have a minimum of five months of experience and had experience providing palliative care to residents in the same NH. Casual and non-fixed contractual professionals were excluded from the study.

Data collection

A combination of focus group discussions and individual in-depth interviews was used to collect data. This was to achieve an enhanced understanding of the phenomenon of emotional labour within a NH context by exploring views at individual and social contexts [ 29 ]. Nine focus group discussions were conducted with various healthcare professionals who provide direct care to residents. Each focus group was composed of seven to eleven professionals. Given the purpose of the study which was to explore how different professionals navigate the emotional demands of providing palliative care within a NH context, group composition brought together all professionals involved at varying degrees in providing such a type of care. However, to allow participants to share their experiences freely and to avoid any status distinction or hierarchical influence [ 30 ], professionals in the managerial roles were not included in the focus groups. They were involved in individual interviews.

Prior to data collection, a meeting was organized at each participating NH to introduce the broader interventional study to professionals and invite them to take part in the study. The focus group sessions were held at a predetermined location within the NH at a time convenient to the participants and facility and lasted between 90 and 120 min. Individual in-depth interviews were conducted with the supervisory teams, namely the nurse coordinators and medical coordinators. Each individual interview lasted approximately 45 min and was held at a time and place convenient to participants. We used the interview guide developed by the researchers for the purpose of this study (supplementary material 1). The same interview guide was used for individual and focus group discussions, with slights changes on the phrasing of questions for interviews with the management team. Focus group and individual interview questions inquired about experiences of providing palliative and end-of-life care to residents, the emotional dimensions associated with such a type of care, how professionals navigate those experiences and the perceived consequences on professional wellbeing. Examples of questions included the following: How would you describe your experience of caring for dying residents in NHs? What are the emotional aspects of providing palliative care to residents, and how do you navigate those experiences? The last author conducted most of the individual interviews and some focus group discussions, while a trained research assistant under the supervision of the last author moderated the remaining focus groups. Both hold PhD degrees and have experience in conducting qualitative interviews for health research. All interviews and focus group discussions were conducted from April 2021 to September 2022. The interviews were audio-recorded after the participants granted permission. Regular field notes were written immediately after interviews and focus groups. Data collection continued until we have gained adequate and in-depth understanding [ 31 ] of emotional experiences of providing palliative care in NH.

Data analysis

Thematic content analysis following the analytical approach of Paillé and Mucchielli [ 32 ] guided the analysis. The level of analysis was a NH, with each NH considered a case. After verbatim transcription of all the data from the nine cases, two authors (BU & DL) became acquainted with the data by rereading the transcribed interviews, examining participants’ narratives from each case separately, and then developed a list of codes. From the code list, they created a thematization journal using code subdivision, integration, and hieararchization [ 32 ]. Next, the same two authors grouped related codes from all the cases, with a third team member (BE) resolving any discrepancies between the previous analysts. At the end of this stage, a thematic tree of three themes and eight subthemes was constructed. NVivo 14 software assisted with data management and facilitated the coding process.

To ensure methodological rigor, the authors used the recommended strategies for trustworthiness of qualitative data [ 33 ]. To ensure the reliability of the findings, two analysts completed the coding of transcripts, organized peer debriefing meetings throughout the analysis, and kept a reflexive journal recording all the steps taken and decisions made. A third analyst resolved any disagreements through consensus. To ensure credibility of findings, the authors triangulated methods (individual in-depth interviews and focus groups) and collected participant perspectives from various healthcare professions (nurses, nurse assistants, personal support workers, psychologists, occupational therapists, physiotherapists, medical doctors). The writing of the manuscript followed the “consolidated criteria for reporting qualitative research (COREQ)” [ 34 ] (Supplementary material 2).

Ethical considerations

The French Committee of Protection of Person (CPP) granted ethical approval for this study (Approval number: 2020.09.06 bis_20.07.31.64318). All focus groups and interviews respected the rights of participants to choose to participate in the study through informed consent. To ensure confidentiality and anonymity of the collected data, the reporting used codes instead of names.

Demographic characteristics of participants

All NH professionals who met the inclusion criteria and who were available on the day of the focus group were included in the study. In total, 93 professionals participated, including 79 participants in nine focus groups and 14 participants in individual interviews. Tables  1 and 2 provide the detailed characteristics of the settings and demographic characteristics of participants.

Quotes from individual interviews are followed by an acronym designating the profession of the participant (for example NC for Nurse Coordinator, MedCo for Medical Coordinator) as well as the code number of the NH. Quotes from focus groups are designated by the acronym FG, followed by an acronym for the location of the NH (IDF for Ile de France, NA for Nouvelle Aquitaine, PACA for Provence-Alpes-Côte d’Azur), and the code number of the NH.

Analysis of participants’ narratives revealed three overarching themes related to the emotional dimensions of providing palliative care in NHs: (1) intertwined emotionally rewarding and challenging experiences; (2) multifaceted emotional strategies; and (3) switching between emotional engagement, detachment and exhaustion. Supplementary material 3 illustrates the generation of themes and subthemes with illustrative quotes.

Theme 1. Intertwined emotionally rewarding and challenging experiences

Participants’ narratives revealed two intertwined and simultaneous emotional dimensions of providing palliative care to dying residents in NHs: (1) emotionally rewarding experiences and (2) emotionally challenging experiences. The emotionally rewarding dimension of the experiences was supported by the individual professionals’ intrinsic commitment, devotion, and engagement with older persons under their care and a professional duty to provide them with the “best possible care” they deserve. On the other hand, the NH context as a place of living and of care, with its organisational constraints, rendered the experience of providing palliative care to residents emotionally challenging. Specifically, it hindered the care providers’ ability to facilitate what they perceived to be a “dignified death,” leaving them with feelings of distress, frustration, guilt, and uselessness.

Caring for dying residents: emotionally rewarding experiences

Numerous participants described working in NH as a deliberate professional choice and vocation, stemming from their sense of commitment and engagement to offer dependant older people the care they deserve. The relational dimension associated with caring for NH residents gives meaning to their work and becomes a source of pleasure, satisfaction, and self-worth, as illustrated by the following registered nurse:

“Helping older persons is my passion. I find that there is less invasive care in NHs , and there is a relationship that develops and that I enjoy” (NC , NA , 751).

For the majority of healthcare professionals, this deliberate choice to work in NHs implies that confronting death on an ongoing basis is a professional responsibility. Despite the emotional challenges that come with multiple exposures to death, the participants affirmed their commitment to confront death as part of caring for residents. They held the belief that dying is part of living and that accompanying death is a normal process that comes with caring for the living. The devotion to accompanying residents until the end was perceived by NH professionals as a rewarding experience when they felt they had fulfilled their responsibility of facilitating a dignified death:

“It feels so rewarding to see a resident dying the way they should: with dignity , respect , free of pain and with the best possible comfort. That is what we are here for” (FG , PACA , 935).

Although death is considered an expected life trajectory in NHs, participants recognized that dying older persons are often overlooked as a category of the population requiring adequate palliative care. Their perceived duty to accompany residents until the end demonstrates their commitment to ensuring that dying residents experience comfort and dignity equal to that experienced by individuals dying in settings outside the NH.

Similarly, for some residents, NH professionals are the sole individuals they can bond with at a human level and who can meet their diverse emotional needs. Participants believed their role goes beyond that of care providers. Their drive to go above and beyond and make a difference in the end-of-life trajectory of residents becomes a rewarding experience that provides a sense of pride and self-worth. The NH professionals expressed feeling honoured to be the ones to accompany residents in that ultimate moment, even if it means forgetting themselves:

“Aging comes with many losses and emotional needs: most of them do not want to be here [in the NH]; they feel abandoned by their families , they lose their autonomy over things they used to do , they need to feel cared for. Being there for them through the most important moments of their stay here is very rewarding to us. Basically , in the first place , if they are put here , it is so they do not die alone” (FG , PACA , 931). “It’s truly a phase full of emotions where everything comes out: their past traumas , their anxiety , their worries. We try to hold it together , to forget ourselves a little so we can give them what they deserve…” (FG , NA , 755).

Participants’ accounts bring to the forefront that despite the emotionally laden experience of providing palliative care in an NH context, their commitment and determination to accompany residents in their last living moments make this experience emotionally rewarding.

A living and dying space: emotionally challenging experience

Narratives from healthcare professionals emphasized the context of the NH as being initially designed to serve as a living space. Such a home-like living environment that progressively becomes a place of care and ultimately a place of dying leads to the development of close bonds between NH professionals and residents for an extended period. The emotional and physical closeness formed with residents during their stay transcends the caregiver-resident therapeutic relationship. Healthcare professionals have to navigate these different aspects of the NH and remain professional caregivers, all the while providing a home-like environment. One participant explained:

“I’m here from 8am to 8 pm; we live with them [residents]. I do not call some of them by their names anymore. I call them grandpa , grandma. By living with and caring for them for an extended period , they end up becoming like family. When they die , it breaks our hearts” (FG , PACA , 931).

Boundary-setting issues such as these make the relational dimension of care especially difficult, as NH professionals can become too close to residents, which naturally complicates the transition to end-of-life care. Accompanying death for older persons who they have accompanied for living represented a challenging transition for participants who considered residents like their own relatives, as expressed by the following medical coordinator:

“They’re not just people we care for; we live with them. These are the people for whom we’ve fought for every minute to make life worth living. Professionals look after them almost as if they were their parents. Accompanying someone who is going to die , while you have accompanied them so they can live , is in itself emotionally hard” (MedCo , IDF , 116).

Their strong emotional bond with residents became a challenge for NH professionals when discussing the residents’ end-of-life preferences and the palliative decisions that needed to be made in preparation for the end-of-life care plan. Many shared avoiding these discussions, even when residents prompted them, as they did not feel ready to engage in such emotionally charged conversations.

“Palliative care supposes that we should help them think about their death , but we are unable to do that. We are primarily a place of life , and at the end , there is always death. That’s the complexity of [providing] palliative care in NHs” (NC , NA , 753).

The experience of providing palliative care in NHs was also challenged by structural and organisational constraints such as heavy workloads, a lack of time, and unmanaged pain. As a result, some participants reported that they were unable to provide dying residents with the required relief, which caused NH professionals lingering regret even after the death of the resident.

“That resident who died last week , I would have wished to have been able to stay with them a little longer , hold their hand , put on some music , so that there is a presence , like putting life into the end of life. Unfortunately , I was not able to free myself. And it is difficult to live with such a feeling” (FG , IDF , 116).

Theme 2. Multifaceted emotional strategies

When asked how they cope with the emotional demands of providing palliative care to residents, participants highlighted a diversity of emotional strategies they deployed to protect themselves and to continue fulfilling their caring roles. These ranged from genuinely expressing their emotions to modifying and suppressing their emotions to fit the moment. Modification and suppression of emotions were cited as the most commonly used strategies as opposed to the authentic expression of emotions.

“We shed tears”, “We’ve laughed with” : genuine display of emotions

Participants used expressions such as “We cry with” , “We’ve shed tears” , “We’ve laughed with” to convey the authentic emotional strategies put in place. They genuinely expressed their emotions in situations when they felt a deep connection with residents. Most of these genuine emotional strategies occurred in the moments approaching death or following death.

“All the residents on the floor are like my family. Last time I went to see Mrs. B , when my colleague told me she was dead , I was shocked , truly shocked. It was quick. I cried all my tears. I was so sad. I was unable to continue work because I was crying” (FG , IDF , 111).

In some situations, the NH professional’s personal history prompted the authentic expression of feelings. For example, if a resident’s death mirrored the death of their own loved ones, it made it difficult for them to conceal their true feelings as they usually do. Some referred to it as not being able to pretend to have no feelings.

“I accompanied my dying father in palliative care. Every time there is a death of a resident , it echoes my father’s. We had a resident death not long ago. When I saw him , I completely broke down. I cannot pretend anymore” (FG , IDF , 117).

The authenticity of emotions also manifested through allowing oneself time to grieve the death of a resident. A participant discussed requesting a day off to grieve, but some NHs also provided space for grieving the deceased residents.

“I was truly attached to Mr G. When he died , I took a day off. Everyone else [colleagues] continued living their life… laughing. For me , I could not come to work because I was grieving his death” (FG , IDF , 116).

Other participants also recognized a need for the authentic expression of emotions and requested emotional management support for the team.

“For a resident we’d known for a long time to whom we were very attached , we felt helpless with her end-of-life care , and so we genuinely asked for help. We held a round table… , and we asked for help from an external person” (FG , NA , 751).

While some participants expressed their genuine feelings, many participants across focus groups were in favour of emotions being unnoticed and noted a lack of formalized organisational strategies to deal with emotions. Many NH professionals admitted to frequently modifying their feelings to display emotions that are “acceptable.”

“ You wipe your sadness and put a smile on your face ”: modification of displayed emotions

Some NH professionals described their emotional work as involving frequent switching between sadness and joy to respond to the needs of the moment. Many shared trying to display emotions that were not what they truly felt because the situation at hand required them to convey different, often contradictory emotions; for the participants, this constituted difficult emotional labour.

“On one hand , you’ve got one person who is dying and next to them residents who are living. It is very difficult because you have to go into the room [and] take care of someone who is dying. You are sad because you know you will not see that person again. Nevertheless , the moment you see this person for a few minutes , you have to close the door , wipe your sadness , and put a smile on your face to accompany the next-door resident with a serene face. It is difficult to manage all these emotions at the same time. In one day , you have to give contradictory feelings. You are sad for one person , but at the same time , you have to bring joy to the other resident. You have to show them a different face , and that is not easy” (FG , IDF , 117).

The modification of emotions was compounded in the NH environment for some participants who not only adopted an expression in accordance with what was expected but also tried to set limits and find the appropriate time and space for revealing their true feelings when out of the NH. Participants described this ability to emotionally detach as protective:

“The moment I remove my uniform , I immediately put a different face…. When I reach home , if I have situations that have been painful , I allow myself to be restless and sad; I vent my true feelings…” (FG , PACA , 933).

“ You become numb and move on ”: suppression of feelings

Participants discussed the organisational expectation to suppress emotions in order to continue providing effective care. In a quest to fit into institutional norms, many NH professionals who describe themselves as normally prone to showing their emotions had to learn to suppress them.

“By nature , I am a very sensitive person , but now I keep all my emotions inside of me , and at the end , it becomes difficult to unload. Here , it is not common to open up and show emotions or talk about them. We are expected to keep it to ourselves and move on” (FG , PACA , 933).

Multiple exposures to death and a lack of time and a safe space to grieve deceased residents forced NH professionals to suppress their feelings in an attempt to cope with the distress and to continue providing care to residents.

“How can you display feelings when you have four successive deaths? You become numb and move on. Tomorrow you will have another one. You pretend as if everything is fine but there is a problem…” (FG , IDF , 117).

Theme 3. Switching between emotional engagement, detachment and exhaustion

Participants reported that the emotional labour of providing palliative care in NHs results in both negative and positive consequences. The majority of NH professionals noted that the negative consequences of emotional labour resulted in an inability to provide effective care, and the lack of supportive space to express their feelings caused emotional distress, feelings of guilt, and a sense of failure and powerlessness. Some participants accepted emotions as essential to their caring role and mentioned that they give meaning to their work.

“ Everyone was satisfied ”: enhanced satisfaction and meaning of work

Only a few NHs involved in the study had formalized procedures in place to support the emotional wellbeing of their healthcare professionals. These procedures included formal debriefs, a consultation with a psychologist, and massage therapy. In the majority of the NHs, informal peer-to-peer support was mentioned. In settings where emotions are acknowledged and supported, both professionals and managers reported increased satisfaction when accompanying dying residents.

“We had a resident to whom the team was so emotionally involved. When the end was approaching , emotions were high for both professionals and the resident. We [the supervisory team] requested the intervention of the external palliative care team to introduce a third party in the relationship and gently distance the team without completely disengaging them. At the end , everyone was satisfied , and the resident was properly accompanied. It ended up being one of the memorable end-of-life care for the staff” (NC , NA , 751).

When participants believed that they gave their best up to the end and that the outcome was a peaceful death, they gained a sense of pride and accomplishment. They felt they had attained their mission, which, for many, was one of the reasons they remained working in the NH despite the stressful environment.

“On his passing , the resident was so peaceful , so were relatives. It was a real sense of satisfaction. It is the kind of end-of-life care where you feel you have done the right care and that gives you motivation to stay” (FG , NA , 753).

“ It is heart-breaking ”: a sense of guilt and powerlessness

Suppression or modification of emotions affected the wellbeing of participants as well as the care they provided to residents. Different constraints such as time pressure and competing tasks added to their frustration. Their emotional distress manifested itself as constant feelings of guilt, powerlessness, and a sense of failure for not providing adequate care to residents. One of the most common sources of guilty feelings was when the NH professionals believed that they were unable to offer a peaceful, quality presence during end-of-life moments and that the resident died alone. Dying alone was considered inhumane by participants, as they believed that residents were placed in NHs mainly to ensure they do not die alone.

“Very often you tell yourself , ‘Well , I could have been by her side , tell her a comforting word , play the music she loved , rub her forehands , make sure she had a presence… , but no , she is gone and all alone’. It is not human at all , and you carry this with you for long” (FG , PACA , 933).

Participants also expressed feeling powerless when they saw residents in pain and discomfort, and their inability to provide the required comfort to the dying residents left them with an immense sense of failure and uselessness, which negatively affected their wellbeing and their satisfaction with the work done.

“It breaks your heart to see people suffering like this and little is done about it. It’s heart-breaking to think , ‘We are here to help them , but in fact we’re not even doing that’. We are useless” (FG , NA , 755).

“ You finally give up ”: distancing and exhaustion

To protect themselves from the distress associated with multiple exposures to death and a lack of institutional support, some participants admitted that they banalized death to emotionally distance themselves from dying residents, a strategy that the NH professionals recognized as inadequate.

“We give , we give , one day we can’t take it anymore and we banalize death. We don’t see death anymore. It does not affect us any longer , it becomes a commonplace gesture , mundane. Someone dies today; you attend to the next person who will be gone tomorrow , and so forth and so on. You keep accumulating and one day you explode” (FG , IDF , 117).

Other NH professionals adopted a superficial attitude in an attempt to distance themselves and detach themselves from their true feelings. They chose to involve themselves less in the therapeutic relationship by concentrating more on carrying out instrumental and technical care and less on offering a caring and relational presence.

“I go in [the room] , I give the injection and I get out. Not because I do not want to stay , but because I am thinking of the others. I cannot stay with the one who is dying while I have 70 others who are still alive. I have to look after those who are not dying” (NC , PACA , 935).

Some participants dealt with emotionally challenging situations by refusing to accept the palliative care plan of residents with whom they had strong ties. They would ignore the team’s decisions when it involved withdrawing feeding and restricting movement and instead provide the usual care such as taking blood pressure, providing hydration, and mobilizing residents, irrespective of the futile outcome or the risk of causing more suffering. In this way, they felt more useful towards the residents.

“We had a staff meeting , and they said Mrs X was in end-of-life care…that we should avoid mobilizing her and emphasize comfort care. When I arrived in the room , I did not do anything they said. Rather , I got her up from bed , I washed her , I dressed her , I brought the wheelchair , and I was about to take her out. When the nurse coordinator arrived , she could not understand what I was doing. I was in denial. I could not believe she was dying” (FG , IDF , 116).

Several participants reported feeling emotionally strained, exhausted, and lacking the energy to accomplish their mission. Some of them even resigned or verbalized their intentions to resign from their posts. Their emotional exhaustion reportedly stemmed from an accumulation of frustration, discouragement and a lack of accomplishment, feeling incompetent, and a lack of support, which prompted them to resign rather than form a negative view of the residents and fail to deliver effective care.

“You fight , you try your best to keep going , you get discouraged and finally you give up. That is why I want to do something else. Eventually , I want to take care of people and give them what they deserve. Here , I do not give them what they deserve , which frustrates me , and I accumulate. I resigned. I would rather leave the job to someone who wants to do it the way it is done. As for me , I am going to hold onto something else. I do not want to become a bitter caregiver….” (FG , PACA , 933).

The findings from this study illustrate that providing palliative care to dying residents within the NH context exposes healthcare professionals to intertwined rewarding and exhausting emotional experiences. This emotionally demanding work results in a constant switching between feelings of pride and accomplishment on the one hand and guilt, distress, and grief on the other, and it prompts healthcare professionals to identify and distance themselves from the residents to protect themselves from emotional suffering. These findings lead to greater insights into how NH professionals navigate these emotionally laden situations to meet the needs of the residents and the NH as well as their own needs. Drawing from these important findings, our discussion focuses on three key insights from the study: (1) Caring for dying residents results in both emotionally rewarding and emotionally exhausting experiences, (2) NH professionals have to perform emotional labour to navigate the experiences associated with providing palliative care, and (3) Unrecognized emotional labour undermines the wellbeing of NH professionals.

Caring for dying residents results in both emotionally rewarding and emotionally exhausting experiences

Genuine interest in caring for frail older persons is at the heart of the engagement and commitment demonstrated by the participants in our study. Participants described becoming emotionally attached to residents they care for as “unavoidable and the right thing to do,” especially given the expected “home-like” environment of the NH. In that sense, the affective dimension of working in NH and the internal motivation of the healthcare professionals aligned and helped them navigate the emotional labour of caring for dying residents and added meaning to their work. In line with other studies, the unique characteristics of NH, where care providers and residents engage repeatedly in deep personal and intimate exchanges for an extended time, forged closer and more trusting reciprocal relationships than are typically found within acute care setting nurse-patient interactions [ 35 , 36 ].

A majority of participants recalled the emotionally rewarding experiences associated with caring for frail and dying residents. The NH professionals described accompanying residents as their professional duty and took pride in making their last days as dignified, comfortable, home-like, and respectful as possible. Moreover, accompanying residents in their final moments was considered a moral responsibility by participants. The positive experiences and feelings stemming from close and trusting relationships with residents have been recognized by previous studies as central to the emotional wellbeing of NH professionals [ 15 ]. Direct caregivers for dying residents characterize those particular moments as the rare moments they feel appreciated, noticed, and like they are making a difference in settings where they generally feel unseen [ 36 ]. In particular, our participants expressed positive emotions such as engagement, pride, accomplishment, and self-worth in situations where they felt they had achieved dignity in caring for the dying residents. This is relevant because dignity represents an essential part of caring in NHs and in palliative care [ 37 , 38 ]. These personal characteristics and intrinsic motives constitute the internal resources and resilience attributes that allow healthcare professionals to cope with distressing situations surrounding accompanying death in NHs [ 10 ]. Future interventions and training should aim to reinforce the internal resources of NH professionals with a strong focus on building resilience.

Although participants perceived caring for dying residents as a rewarding experience, when the challenging working conditions within NH hindered them from achieving their moral and professional responsibility, it turned the experience into difficult emotional labour. The current NH working environment fails to provide necessary organisational resources and subsequently creates discrepancies between the ideals held by NH professionals on what constitutes the right comfort care to provide and the current practices. Under severe labour shortages, NHs prioritize technical and task-oriented activities over relational moments [ 39 ]. However, for participants in this study, not being present to hold the hands of the dying resident left them feeling guilty of failing their moral responsibility and their professional duty. Consistent with previous studies, the NH culture was found to prioritize tasks and expect healthcare professionals to be consistently “doing something” for residents versus “being” with residents [ 13 , 40 ]. This dissonance creates the most difficult emotional challenges, moral concerns, and distress for NH professionals [ 25 ]. That perceived inability to facilitate a “good death” due to organisational constraints results in moral distress for NH professionals and complicates their grieving process [ 23 , 41 ]. Echoing this, participants in our study shared how emotionally burdensome it was to constantly feel guilty of devoting less time to the “dying resident” because they were required to attend to the “living residents” instead. NH managers and policymakers should take measures to build a culture that enables healthcare professionals to prioritize the emotional needs of residents alongside their physical care needs, as both are equally important to end-of-life care.

Professionals have to perform emotional labour to navigate the experiences associated with providing palliative care

Participants in the current study used different emotional labour strategies to navigate the rewarding and challenging aspects of caring for dying residents in the NH context. Some adopted distancing strategies, such as focusing on task-based care and mechanical actions as well as avoiding feelings and emotional involvement, while others trivialized death or denied the impending death of residents. This process of strategy switching between engagement and detachment is prevalent among palliative care professionals as a way of coping with emotional demands and preventing grief [ 13 , 23 ].

Numerous participants reported that they tended to modify their feelings by displaying emotions that were different from those they felt. For example, some noted “wiping [their] face and showing a smiley face,” while others suppressed their feelings to “become numb and move on” in an attempt to display composure in the moment and comply with institutional rules. Attempting to modify one’s felt emotions to match displayed emotions is known as deep acting, whereas displaying fake, unfelt emotions and suppressing one’s felt emotions indicates a surface acting strategy [ 18 ]. The emotional strategies used by the participants in our study are similar to those commonly used by healthcare professionals in different care contexts [ 12 ]. Particularly in the NH context, emotional labour is intensified by the long-term therapeutic relationship, as the longer the therapeutic relationship the more complicated the emotional labour [ 7 , 15 ]. Participants in our study shared that the stronger and the closer the bond with the resident, the harder it was to navigate the emotional labour associated with witnessing their suffering and providing them with end-of-life care. Debates persist on the appropriate emotional distance to take when accompanying a resident with whom the healthcare professional has formed a close bond. It is noteworthy, however, that healthcare professionals who try to convey caring while remaining emotionally detached may experience increased emotional dissonance and potentially negative effects [ 23 ]. This phenomenon resonates particularly within the NH care context, where professional boundaries are blurred and difficult to respect [ 6 ].

Some participants in this study identified the importance of safe spaces where they can freely express their emotions without faking and without feeling judged, such as spending time informally with colleagues during breaks or with relatives at home. Researchers classify this as the backstage area of emotional expression, owing to the lack of formal recognition and poor appreciation of emotional labour in practice [ 42 , 43 ]. Given the complexity of emotional labour associated with providing palliative and end-of-life care in NHs, scholars recommend more strengthened, explicit, and structured backstage areas to recognize the emotional needs of healthcare professionals and support their emotional growth and resilience [ 43 ]. Unfortunately, findings from our study reiterate the inadequate support available in the NH context for their mental and emotional wellbeing.

In a few instances, some participants in our study allowed themselves to express naturally felt emotions. The close bond they had formed with residents prompted those who adopted the genuine manifestation of feelings to view the resident’s death as a parallel of their own loved one’s death; hence, they allowed themselves to react accordingly. Some took a leave of absence to process the grief, while others requested formal support as they struggled to come to terms with the death of the resident. Studies have shown that adopting naturally felt emotions as an emotional labour strategy can protect healthcare professionals from burnout, as it allows for authenticity and empathy expressions in care [ 12 ]. Genuine emotions have also been found to support nurses in the provision of compassionate care and to inspire cooperation from less-cooperative residents [ 6 ]. In our study, however, the absence of a formal supportive space within the NH to vent emotions discouraged the genuine expression of feelings. Even in the few NHs where opportunities for emotional sharing existed through support groups and psychologist interventions, the participants were reluctant to take advantage of these opportunities. One possible explanation could be that openly expressing emotions might be seen as a sign of weakness, incompetency, and inability to respect professional boundaries. Yet, organisational studies have shown that when grief and emotional suffering are acknowledged and collectively shared as a team, emotional distress is no longer perceived as an individual weakness but rather a collective suffering that requires collective measures to address. However, this cultural shift is only possible when it is supported by the institution through the provision of time, space, and opportunity to debrief and grieve [ 44 ].

Unrecognized emotional labour undermines the wellbeing of nursing home professionals

This study revealed that the emotions experienced by professionals receive relatively little attention within the NH context. This finding supports other studies that have highlighted the invisible nature of the emotional labour endured by healthcare professionals in end-of-life and palliative care within NHs [ 7 , 15 ]. Current institutional rules reinforced by professional norms such as the self-imposed emotional strategies used by healthcare professionals implicitly discourage the open expression of emotions and position genuine displays of emotion as incompetence [ 6 ]. Considering the expression of emotions as weak and a sign of a problem to be addressed leads to emotional labour being unrecognized, professionally undervalued, and even discriminated against [ 24 ]. This is deeply problematic, as unrecognized emotional labour can lead to personal, professional, and organisational negative outcomes.

The effect of emotional labour on a healthcare professional varies depending on the frequency, intensity, diversity, and length of the needed emotional displays as well as the degree of emotional dissonance between the emotions experienced and those anticipated [ 14 ]. Evidence demonstrates that a constant mismatch between felt feelings and displayed emotions leads to emotional dissonance, an internal state of conflict that can cause healthcare professionals to experience difficulty in patient interactions, high levels of stress and burnout [ 12 ], emotional “estrangement” (p.443) [ 13 ], and increased intention to leave [ 45 ]. Consistent with these studies, participants in our study felt drained and worn out by the emotional efforts associated with caring for the dying residents. They experienced guilt and feelings of powerlessness and failure, and a significant number expressed their intention to leave the NH.

At the organisational level, studies have demonstrated that poor patient outcomes and poor quality of care, including missing care opportunities and mistreating residents, are potential negative outcomes of emotional exhaustion and unrecognized emotional labour, as well as lower levels of staff recruitment and retention [ 46 ]. In contrast, emerging evidence suggests that when institutional expectations allow and support authentic emotional expression, positive effects can result for healthcare professionals, care recipients, and the healthcare system [ 12 , 14 ].

Implications for policy, practice, and research

The findings from this study expand our understanding of the complex emotional demands associated with caring for dying residents in NHs. Caring for frail older persons requires extensive time, effort, and mental and physical energy, and it involves the interplay of physical and emotional tasks and skills [ 13 ]. These findings represent a valuable contribution to the NH care system, a system that has been predominated by instrumental-focused care. The data highlights the need for a paradigm shift toward valuing the emotional labour involved in accompanying life and death in contexts that are not palliative-care specialised. Upholding quality care alongside the wellbeing of healthcare professionals requires an organisational culture that does not separate instrumental acts from the emotional labour at the very heart of the caring profession. Instead, it requires organisational changes that result in emotional support seen as a collective routine practice that strengthens the team rather than as an individual responsibility and weakness. This will allow NH professionals to regularly share their feelings and emotions, leading to emotional openness and acceptance [ 40 ].

Regular in-service training initiatives should be put in place in NHs to equip healthcare professionals with effective emotional management skills. In particular, the nursing assistants and personal support workers in our study appeared to be most affected by the negative impact of emotional labour. These categories of professional groups require tailored training to help bridge their skill gap. Capacity building approaches such as critical companionship have been proven to equip healthcare professionals with skills on the effective use of emotions in therapeutic relationships and to allow them to reflect on the use of self in caring [ 19 ]. As a lack of institutional support and peer support discourages emotional expression, NH settings should reinforce work environments in which leadership, supervisor, and co-worker support are an integral part of routine practices.

Structural deficiencies such as inadequate staffing, heavy workloads, and competing tasks leave NH healthcare professionals with inadequate time to provide optimal care. This underpins most of the challenges healthcare professionals experience in the NH context and is a primary factor in the emotional burden they experience when they fail to provide quality palliative care to dying residents. There is a need to adapt resource allocation to the complexity of providing palliative care within NHs. Further studies are needed to design interventions that support emotional regulation while increasing the resilience and emotional intelligence of healthcare professionals in NHs.

A strength of our study was the use of individual and focus groups interviews, which enabled a comprehensive exploration of individual and group views on emotional labour of NH professionals. Including professionals involved in direct care and leaders, i.e. nurse and medical coordinators, enabled to capture a diverse set of experiences and perspectives across professional categories and roles. This study did not intend to establish the levels of influence of factors such as professional category, years of work experience, level of interaction with residents or settings characteristics on emotional labour and strategies used. This may constitute the focus of future research.

This study brought to the forefront the complex emotional labour performed by NH professionals while caring for residents requiring palliative care. The results demonstrated that emotions are an undeniable part of caring for frail and dying older persons in the context of a home-like environment; however, current NH culture discourages genuine emotional sharing and emphasizes emotional suppression. Unrecognized emotions undermine the wellbeing of healthcare professionals, leading to negative individual and organisational outcomes. Understanding and acknowledging the emotional labour of NH professionals is critical to supporting their wellbeing, resilience, and retention, and it ultimately may improve the quality of care for dying residents. The stigma surrounding the emotional labour of caring can be broken by decision makers who design healthy workplace environments that celebrate emotional transparency as a strength as well as by each and every healthcare worker who bravely displays their genuine emotions in hopes to shape a new culture that fully acknowledges their humanity alongside their professional skills.

Data availability

The datasets used in this study are available on a reasonable request from the corresponding author.

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Acknowledgements

The authors of this article sincerely thank the funders of this study cited above and the scientific committee members for their valuable support. We acknowledge the contributions of all members of the Padi-Palli team. We are also grateful to the nursing homes and professionals who participated in the study. The authors thank Professor Margaret Fitch for her valuable insights into the manuscript.

This study was supported by the French Ministry of Health and Solidarity through a call for projects PREPS (Healthcare System Performance Research Program): grant number PREPS 19–0066, by the Association des Dames du Calvaire (ADC) and by the Regional Health Agencies (Agence Régionale de Santé) of Ile de France (ARS IDF) and Provence-Alpes-Côte d’Azur (ARS PACA). The funders had no role or responsibilities in the study design, data collection, data management, analysis and interpretation, or publication of this manuscript.

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EB conceptualized and designed the study, collected and analysed the data, and revised the manuscript. BU analysed the data and drafted and revised the manuscript. DL analysed the data and revised the manuscript. All authors have reviewed and approved the final manuscript.

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Research ethics approval for this study was granted by the French Committee of Protection of Person, approval number 2020.09.06 bis 20.07.31.64318. The study is registered in the National Study Database as ID-RCB 2020-A01832-37. The use of databases and data processing were implemented in accordance with French law (“Informatique et Libertés” dated January 6, 1978 and amended June 20, 2018) and European regulations (General Data Protection Regulation - GDPR dated April 27, 2016). All participants provided their informed consent in writing before their inclusion in the study. Confidentiality was ensured using codes and pseudonyms.

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Umubyeyi, B., Leboul, D. & Bagaragaza, E. “ You close the door , wipe your sadness and put on a smiling face ”: a qualitative study of the emotional labour of healthcare professionals providing palliative care in nursing homes in France. BMC Health Serv Res 24 , 1070 (2024). https://doi.org/10.1186/s12913-024-11550-7

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Received : 28 May 2024

Accepted : 05 September 2024

Published : 16 September 2024

DOI : https://doi.org/10.1186/s12913-024-11550-7

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