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• What Is Purposive Sampling? | Definition & Examples

What Is Purposive Sampling? | Definition & Examples

Published on August 11, 2022 by Kassiani Nikolopoulou . Revised on June 22, 2023.

Purposive sampling refers to a group of non-probability sampling techniques in which units are selected because they have characteristics that you need in your sample. In other words, units are selected “on purpose” in purposive sampling.

Also called judgmental sampling, this sampling method relies on the researcher’s judgment when identifying and selecting the individuals, cases, or events that can provide the best information to achieve the study’s objectives.

Purposive sampling is common in qualitative research and mixed methods research . It is particularly useful if you need to find information-rich cases or make the most out of limited resources, but is at high risk for research biases like observer bias .

Table of contents

When to use purposive sampling, purposive sampling methods and examples, maximum variation sampling, homogeneous sampling, typical case sampling, extreme (or deviant) case sampling, critical case sampling, expert sampling, example: step-by-step purposive sampling, advantages and disadvantages of purposive sampling, other interesting articles, frequently asked questions about purposive sampling.

Purposive sampling is best used when you want to focus in depth on relatively small samples . Perhaps you would like to access a particular subset of the population that shares certain characteristics, or you are researching issues likely to have unique cases.

The main goal of purposive sampling is to identify the cases, individuals, or communities best suited to helping you answer your research question . For this reason, purposive sampling works best when you have a lot of background information about your research topic. The more information you have, the higher the quality of your sample.

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Depending on your research objectives, there are several purposive sampling methods you can use:

• Maximum variation (or heterogeneous) sampling

Maximum variation sampling , also known as heterogeneous sampling, is used to capture the widest range of perspectives possible.

To ensure maximum variation, researchers include both cases, organizations, or events that are considered typical or average and those that are more extreme in nature. This helps researchers to examine a subject from different angles, identifying important common patterns that are true across variations.

Homogeneous sampling, unlike maximum variation sampling, aims to reduce variation, simplifying the analysis and describing a particular subgroup in depth.

Units in a homogeneous sample share similar traits or specific characteristics—e.g., life experiences, jobs, or cultures. The idea is to focus on this precise similarity, analyzing how it relates to your research topic. Homogeneous sampling is often used for selecting focus group participants.

Typical case sampling is used when you want to highlight what is considered a normal or average instance of a phenomenon to those who are unfamiliar with it. Participants are generally chosen based on their likelihood of behaving like everyone else sharing the same characteristics or experiences.

Keep in mind that the goal of typical case sampling is to illustrate a phenomenon, not to make generalized statements about the experiences of all participants. For this reason, typical case sampling allows you to compare samples, not generalize samples to populations.

The idea behind extreme case sampling is to illuminate unusual cases or outliers. This can involve notable successes or failures, “top of the class vs. bottom of the class” scenarios, or any unusual manifestation of a phenomenon of interest.

This form of sampling, also called deviant case sampling, is often used when researchers are developing best practice guidelines or are looking into “what not to do.”

Critical case sampling is used when a single or very small number of cases can be used to explain other similar cases.  Researchers determine whether a case is critical by using this maxim: “if it happens here, it will happen anywhere.” In other words, a case is critical if what is true for one case is likely to be true for all other cases.

Although you cannot make statistical inferences with critical case sampling, you can apply your findings to similar cases. Researchers use critical case sampling in the initial phases of their research, in order to establish whether a more in-depth study is needed.

If you first ask local government officials and they do not understand them, then probably no one will. Alternatively, if you ask random passersby, and they do understand them, then it’s safe to assume most people will.

Expert sampling is used when your research requires individuals with a high level of knowledge about a particular subject. Your experts are thus selected based on a demonstrable skill set, or level of experience possessed.

This type of sampling is useful when there is a lack of observational evidence, when you are investigating new areas of research, or when you are conducting exploratory research .

Purposive sampling is widely used in qualitative research , when you want to focus in depth on a certain phenomenon. There are five key steps involved in drawing a purposive sample.

Step 1: Define your research problem

Start by deciding your research problem : a specific issue, challenge, or gap in knowledge you aim to address in your research. The way you formulate your problem determines your next steps in your  research design , as well as the sampling method and the type of analysis you undertake.

Step 2: Determine your population

You should begin by clearly defining the population from which your sample will be taken, since this is where you will draw your conclusions from.

Step 3: Define the characteristics of your sample

In purposive sampling, you set out to identify members of the population who are likely to possess certain characteristics or experiences (and to be willing to share them with you). In this way, you can select the individuals or cases that fit your study, focusing on a relatively small sample.

Alternatively, you may be interested in identifying common patterns, despite the variations in how the youth responded to the intervention. You can draw a maximum variation sample by including a range of outcomes:

• Youth who reported no effects after the intervention
• Youth who had an average response to the intervention
• Youth who reported significantly better outcomes than the average after the intervention

Step 4: Collect your data using an appropriate method

Depending on your research question and the type of data you want to collect, you can now decide which data collection method is best for you.

Step 5: Analyze and interpret your results

Purposive sampling is an effective method when dealing with small samples, but it is also an inherently biased method. For this reason, you need to document the research bias in the methodology section of your paper and avoid applying any interpretations beyond the sampled population.

Knowing the advantages and disadvantages of purposive sampling can help you decide if this approach fits your research design.

Advantages of purposive sampling

There are several advantages to using purposive sampling in your research.

• Although it is not possible to make statistical inferences from the sample to the population, purposive sampling techniques can provide researchers with the data to make other types of generalizations from the sample being studied. Remember that these generalizations must be logical, analytical, or theoretical in nature to be valid.
• Purposive sampling techniques work well in qualitative research designs that involve multiple phases, where each phase builds on the previous one. Purposive sampling provides a wide range of techniques for the researcher to draw on and can be used to investigate whether a phenomenon is worth investigating further.

Disadvantages of purposive sampling

However, purposive sampling can have a number of drawbacks, too.

• As with other non-probability sampling techniques, purposive sampling is prone to research bias . Because the selection of the sample units depends on the researcher’s subjective judgment, results have a high risk of bias, particularly observer bias .
• If you are not aware of the variations in attitudes, opinions, or manifestations of the phenomenon of interest in your target population, identifying and selecting the units that can give you the best information is extremely difficult.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

Purposive and convenience sampling are both sampling methods that are typically used in qualitative data collection.

A convenience sample is drawn from a source that is conveniently accessible to the researcher. Convenience sampling does not distinguish characteristics among the participants. On the other hand, purposive sampling focuses on selecting participants possessing characteristics associated with the research study.

The findings of studies based on either convenience or purposive sampling can only be generalized to the (sub)population from which the sample is drawn, and not to the entire population.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

When your population is large in size, geographically dispersed, or difficult to contact, it’s necessary to use a sampling method .

This allows you to gather information from a smaller part of the population (i.e., the sample) and make accurate statements by using statistical analysis. A few sampling methods include simple random sampling , convenience sampling , and snowball sampling .

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• What is purposive sampling?

Last updated

5 February 2023

Reviewed by

Cathy Heath

This type of sampling is often used in qualitative research , allowing the researcher to focus on specific areas of interest and gather in-depth data on those topics. In this article, we will explore the concept of purposive sampling in more detail and discuss the advantages and limitations of using this approach in research studies.

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Purposive sampling is a technique used in qualitative research to select a specific group of individuals or units for analysis. Participants are chosen “on purpose,” not randomly. It is also known as judgmental sampling or selective sampling.

In purposive sampling, the researcher has a specific purpose or objective in mind when selecting the sample. Therefore, the sample is selected based on the characteristics or attributes that the researcher is interested in studying. 

For example, suppose a researcher is interested in studying the experiences of individuals living with chronic pain. In that case, they might use purposive sampling to select a sample of individuals who have been diagnosed with chronic pain.

Purposive sampling is often used in qualitative research , as it allows the researcher to focus on specific areas of interest and gather in-depth data on those topics. It is also commonly used in small-scale studies with limited sample size.

• When to use purposive sampling

Purposive sampling should be used when you have a clear idea of the specific attributes you're interested in studying and want to select a sample that accurately represents those characteristics.

Purposive sampling can be particularly useful in the following situations:

When the population of interest is small

For interest in studying a specific subgroup within the population

To study a rare or unusual phenomenon

It's important to note that purposive sampling is not suitable for all research studies and should be used cautiously. As the sample is not selected randomly, the results of the study may not be generalizable to the larger population, and the researcher must consider the potential for bias in the sample selection.

• Principles of purposeful sampling

There are several important principles of purposive sampling that you should consider when using this approach in your research studies:

Clearly defined purpose - The purpose of the study should be clearly defined, and the sample should be selected based on the characteristics or attributes that you're interested in studying.

Representative sample - The sample should be representative of the characteristics or attributes being studied.

Bias - Biases can come into play when anything other than random sampling is used, so be aware of any potential biases and take steps to minimize them.

Expertise - Having expertise in the topic being studied is an important part of sample selection. Without a solid understanding of the characteristics being selected, the population might not be as representative as it should be.

• How is purposive sampling conducted?

The steps to conducting a study using purposive sampling will vary depending on the topic and preferences of the researchers involved. The five steps of purposive sampling as a general framework are:

Define the purpose of the study

Identify the sample of individuals or units

Obtain informed consent from individuals

Collect the data using appropriate research methods

Analyze the data

• Purposive sampling examples

Researchers can use several different types of purposive sampling methods , depending on what they're interested in studying and the specific research question they are trying to answer. In the list below, we'll discuss the various types of purposive sampling methods and provide examples of when each method might be used in research.

Maximum variation sampling

Maximum variation sampling involves selecting a sample of individuals or units representing the maximum range of variation within the characteristics or attributes the researcher is interested in studying. This type of sampling is used to understand the widest possible diversity of experiences or viewpoints within the population.

Homogeneous sampling

Homogeneous sampling involves selecting what is often a more narrow sample of individuals or units that are similar or have the same characteristics or attributes. This type of sampling is used to study a specific subgroup within the population in depth.

Typical case sampling

Typical case sampling involves selecting a sample of individuals or units that are representative of the typical experiences or characteristics of the population. This type of sampling is used to understand the most common or average experiences or characteristics within the population.

Extreme/deviant case sampling

Extreme case sampling involves selecting a sample of individuals or units that are considered extreme or unusual in the characteristics or attributes the researcher is interested in studying. This type of sampling is used to understand unusual or exceptional experiences or characteristics within the population and are often viewed as outliers in a wider population.

Critical case sampling

Critical case sampling involves selecting a sample of individuals or units that are important or central to the research question or the population being studied. This type of sampling is used to understand key experiences or characteristics within the population.

Expert sampling

Expert sampling involves selecting a sample of individuals or units that have specialized knowledge or expertise in the topic or issue being studied. This type of sampling is used to gather insights and understanding from experts in the field, which can be used to develop follow-up studies.

• Purposive sampling vs. convenience sampling

Purposive sampling and convenience sampling are similar in that both involve the selection of a sample based on the researcher's judgment rather than using a random sampling method. However, there are some key differences between the two approaches.

In purposive sampling, the sample is selected based on the defined purpose of the study and is intended to be representative of the characteristics or attributes in which the researcher is interested.

Convenience sampling, on the other hand, involves selecting a sample of individuals or units that are readily available or easily accessible to the researcher. The sample is not selected based on any particular characteristics or attributes, but rather in terms of convenience for the researcher.

• Advantages of purposive sampling

There are several advantages to using purposive sampling in research studies, including:

Representative sample - allows the researcher to select a sample highly representative of the characteristics or attributes they are interested in studying, relatively quickly, This can be particularly useful when the population of interest is small or when the researcher is interested in studying a specific subgroup within the population.

In-depth data - often used in qualitative research, which allows the researcher to gather in-depth data on specific topics or issues. This can provide valuable insights and understanding of the research question.

Practicality - practical and efficient in comparison to other sampling methods, particularly in small-scale studies with limited sample sizes.

Flexibility - flexibility in the selection of the sample, which can be useful when the researcher is studying a rare or unusual phenomenon.

Cost - can be less expensive than other sampling methods, as it does not require a random selection process.

• Disadvantages of purposive sampling

It's important to note that purposive sampling has limitations and should be used with caution. Some of the disadvantages of purposive sampling are listed below:

Limited generalizability -  As the sample is not selected randomly, the study’s results may not be generalizable to the larger population. Other risk factors are producing lop-sided research, where some subgroups are omitted or excluded.

Bias - Purposive sampling is subjective and relies on the researcher's judgment, which can introduce bias into the study. The researcher may unconsciously select individuals or units that fit their expectations or preconceived notions, which can affect the study’s validity. Participants can also manipulate the insights they give.

Sampling error - Sampling error, or the difference between the sample and the population, is more likely to occur in purposive sampling because the sample is not selected randomly. This can affect the reliability and accuracy of the study.

Limited sample size - Purposive sampling is often used in small-scale studies with limited sample sizes. This can affect the statistical power of the study and make it more difficult to detect significant differences or relationships.

Ethical considerations -  The researcher must ensure that the study is conducted ethically and that the rights of the participants are protected. This may require obtaining informed consent from the individuals in the sample and safeguarding their privacy.

• Challenges to the use of purposeful sampling

One of the main challenges to the use of purposive sampling in research studies is the limited generalizability of the findings. Because the sample is not selected randomly, it may not be representative of the broader population, and study results may not be applicable to other groups or populations. This can limit the usefulness and impact of the study, making it more challenging to draw conclusions about the larger population.

Each of the disadvantages listed in the previous section contributes to this problem. Researchers who wish to use purposive sampling need to be aware of the method’s weaknesses and actively take steps to avoid or mitigate them.

Why is purposive sampling used?

Purposive sampling is used in research studies when the researcher has a clear idea of the characteristics or attributes they are interested in studying and wants to select a sample that is representative of those characteristics. It is often used in qualitative research to gather in-depth data on specific topics or issues.

What is an example of purposive sampling?

An example of purposive sampling might be a researcher studying the experiences of individuals living with chronic pain, and therefore selecting a sample of individuals who have been diagnosed with chronic pain.

What type of research uses purposive sampling?

Purposive sampling is often used in qualitative research, as it allows the researcher to gather in-depth data on specific topics or issues. It may also be used in small-scale studies with a limited sample size.

What is a good sample size for purposive sampling?

The sample size for purposive sampling will depend on the research question and the characteristics or attributes the researcher is interested in studying. Generally, a sample size of 30 individuals is often considered sufficient for qualitative research, although larger sample sizes of 100 or more may be needed in some cases.

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• Technical advance
• Open access
• Published: 18 February 2016

The use of purposeful sampling in a qualitative evidence synthesis: A worked example on sexual adjustment to a cancer trajectory

• Charlotte Benoot 1 ,
• Karin Hannes 2 &
• Johan Bilsen 1  

BMC Medical Research Methodology volume  16 , Article number:  21 ( 2016 ) Cite this article

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An increasing number of qualitative evidence syntheses papers are found in health care literature. Many of these syntheses use a strictly exhaustive search strategy to collect articles, mirroring the standard template developed by major review organizations such as the Cochrane and Campbell Collaboration. The hegemonic idea behind it is that non-comprehensive samples in systematic reviews may introduce selection bias. However, exhaustive sampling in a qualitative evidence synthesis has been questioned, and a more purposeful way of sampling papers has been proposed as an alternative, although there is a lack of transparency on how these purposeful sampling strategies might be applied to a qualitative evidence synthesis. We discuss in our paper why and how we used purposeful sampling in a qualitative evidence synthesis about ‘sexual adjustment to a cancer trajectory’, by giving a worked example.

We have chosen a mixed purposeful sampling, combining three different strategies that we considered the most consistent with our research purpose: intensity sampling, maximum variation sampling and confirming/disconfirming case sampling.

The concept of purposeful sampling on the meta-level could not readily been borrowed from the logic applied in basic research projects. It also demands a considerable amount of flexibility, and is labour-intensive, which goes against the argument of many authors that using purposeful sampling provides a pragmatic solution or a short cut for researchers, compared with exhaustive sampling.

Opportunities of purposeful sampling were the possible inclusion of new perspectives to the line-of-argument and the enhancement of the theoretical diversity of the papers being included, which could make the results more conceptually aligned with the synthesis purpose.

Conclusions

This paper helps researchers to make decisions related to purposeful sampling in a more systematic and transparent way. Future research could confirm or disconfirm the hypothesis of conceptual enhancement by comparing the findings of a purposefully sampled qualitative evidence synthesis with those drawing on an exhaustive sample of the literature.

Peer Review reports

An increasing number of qualitative evidence synthesis papers are appearing in the health care literature [ 1 , 2 ]. Qualitative evidence synthesis methods have the potential to generate answers to complex questions that provide us with novel and valuable insights for theory development and clinical practice, hereby moving beyond review questions only related to the effectiveness of interventions and causation [ 3 , 4 ].

Over 20 different approaches to qualitative evidence synthesis have been developed [ 5 ]. Meta ethnography developed by Noblit and Hare (1988) is currently one of the most commonly used synthesis approaches [ 2 , 6 , 7 ]. Meta-ethnography enables a systematic and detailed understanding of how studies are related, through the comparison of findings within and across studies, ultimately providing an interpretation of the whole body of research [ 7 ]. It has known a considerable uptake in the field of healthcare [ 8 , 9 ]. Furthermore, it has the capacity to generate hypotheses for future testing or comparison with trial outcomes [ 10 ]. In our review project, we opted for a meta-ethnographic approach to synthesize findings on the sexual adjustment of cancer patients and their partners across a number of qualitative studies. It was expected that this would allow us to generate a comprehensive model to understand patients and their partners’ sexual adaptation after cancer.

We noticed that many of the meta-ethnographies published adopt a linear approach to synthesizing the literature, mirroring the standard template developed by major review organizations such as the Cochrane and Campbell Collaboration. Consequently, in most meta- ethnographic synthesis projects, a strictly exhaustive search and information retrieval strategy is used to collect data and relevant studies are assessed for quality before being included in the synthesis. The idea to work with comprehensive samples of the literature is strongly influenced by the risk of bias discourse, suggesting that non-comprehensive samples may introduce a selection bias in systematic reviews, for example [ 11 – 13 ].

However, the usefulness of the review strategy promoted by organizations such as Cochrane and Campbell, and thus of exhaustive search techniques and sampling, has been questioned by a substantial proportion of members of the qualitative research community. It has been argued that exhaustive sampling is a highly rigorous and formalistic approach that risks to be too time consuming because the searches often retrieve very large data sets that are impractical to screen [ 14 , 15 ]. Moreover, exhaustive sample risks to produce rather superficial synthesis findings, with a large number of studies that fail to go beyond the level of description [ 16 ].

Consequently, some authors are proposing a more purposeful way of sampling papers as an alternative for exhaustive sampling [ 17 ].

Purposeful sampling techniques for primary research have been well described by Patton (2002, p. 230) who has provided a definition of what purposeful sampling means [ 16 ].

“The logic and power of purposeful sampling lie in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling. Studying information-rich cases yields insights and in-depth understanding rather than empirical generalizations.”

Applied to the meta-level, purposeful sampling in a qualitative evidence synthesis has often been promoted as a solution for pragmatic constraints of time, resources, access to information and expertise [ 5 , 15 ]. However, several review authors specializing in qualitative evidence synthesis have also provided a more theoretical background to the choice for purposeful sampling. One of the core arguments supporting a purposeful sampling approach is that it is not meant to be comprehensive in terms of screening all potentially relevant papers, mainly because the interest of the authors is not in seeking a single ‘correct’ answer, but rather in examining the complexity of different conceptualizations. It follows that these types of reviews require variation to enable new conceptual understandings to be generated [ 11 , 17 , 18 ]. Booth (2011) further claims that authors of qualitative evidence syntheses are mainly concerned with ‘aiming to find sufficient cases to explore patterns and so are not necessarily attempting to be exhaustive in their searching’ [ 19 ]. To guarantee a sufficient level of conceptual richness, review directions may be divergent and iterative, rather than linear [ 20 ]. This thus contradicts the classic prospective approach of exhaustive searching [ 1 ].

Although several qualitative researchers have recommended purposeful sampling in the context of qualitative evidence synthesis, the published literature holds sparse discussion on how these strategies might be applied to a qualitative evidence synthesis [ 15 ]. Suri (2011) has made a worthwhile attempt to address this issue by examining the adaptability of the 16 purposeful sampling strategies in primary research described by Patton (2002) to the process of qualitative evidence synthesis (see Table  1 ).

Despite this promising effort by Suri (2011) to theoretically present the different options of sampling for synthesis, researchers who claim to have used a purposeful sampling approach often fail to create a transparent audit trail on the review process. In addition, early pioneers such as Campbell and colleagues (2003) who explored purposeful sampling remain close to a positivist sampling strategy, opting for an arbitrary, random sampling technique to select a subset of papers to extract [ 21 ]. Noblit and Hare (1988), the initiators of the meta-ethnographic approach, introduce the idea of sampling purposefully without developing it further [ 7 ].

This indicates that there is a unilateral focus on exhaustive sampling methods, as well as a lack of transparency on how to effectively use and report on purposeful sampling techniques. Therefore, we discuss in this paper why and how we have used purposeful sampling in our qualitative evidence synthesis. The following issues will be addressed: (a) how purposeful sampling procedures have been integrated into our review procedure; (b) how this purposeful sampling has led to the development of a line-of-argument, and (c) what sort of challenges and opportunities we encountered in the instrumental outline of the procedure.

We used Suri’s (2011) description of 16 possible purposeful sampling strategies for qualitative evidence synthesis as a starting point for deciding on which type of sampling strategy we would apply in our synthesis (see Table  1 ) [ 15 ]. Suri (2011) urges authors to carefully identify sampling strategies that are conceptually aligned with the synthesis purpose, that are credible, that sufficiently address the synthesis purpose, and that are feasible, ethical and efficient.

However, we found that Suri did not offer a ‘grab and go’ option that was the perfect match for building a theoretical model, which was the aim in our qualitative evidence synthesis about sexual adjustment after cancer. Little guidance is thus available for the practical implementation of theoretical sampling. Following the example of theoretical sampling guides in primary research, we choose to see theoretical sampling as an umbrella approach, i.e. a combination of different purposeful sampling techniques [ 22 , 23 ].

We have therefore chosen a combination consisting of (a) intensity sampling at first, then a (b) maximum variation sampling and finally (c) disconfirming case sampling. This combination of sampling techniques was chosen as these aligned with the different steps of analysing towards a theoretical construct, and in accordance with Corbin and Strauss, who also connected specific sampling strategies to different types of analysing [ 24 ].

In what follows, we describe and discuss how these sampling procedures have been integrated into our review procedure. As well we describe why we used the specific sampling technique in alliance with a specific step in the analysis.

Scoping review

Initially, we compiled a database of potentially relevant articles based on a scoping review. Scoping is an exploratory and systematic way of mapping the literature available on a topic [ 17 ]. Scoping exercises are perceived as the ideal way of doing preparatory work for an exhaustive systematic review. In our case, we have used them for building an archive of data for our qualitative evidence synthesis.

We searched 4 major databases: Medline, Psychinfo, Cinahl and Dissertation Abstracts. A search string was developed for each database with the support of a specialized team. For each database we added a methodological filter to these search strings in order to extract qualitative research articles [ 25 – 27 ]. For example, the research string we used in Medline was ((interview* or qualitative or experience*) and (cancer and sexual*). Studies included had to be written in English and be carried out between 1994 and 2014, for pragmatic reasons.

The qualitative studies retrieved were qualitative studies matched against the following inclusion criteria.

Type of studies

We considered all sorts of qualitative designs. Opinion pieces and editorials were excluded. The study reports should be qualitative in nature.

Phenomenon of interest

Studies should (partially) focus on the relational aspects of sexuality, namely the sexual intimacy of patient and partner, in a context of a cancer diagnosis.

Type of participants

We included articles where the cancer patient and/or the partner was the unit of analysis.

First one researcher (CB) applied the inclusion and exclusion criteria to the retrieved abstracts. A full text was requested for each of the relevant studies. These studies were further assessed by the same researcher, rechecking them against the same inclusion and exclusion criteria. As can be seen in Fig.  1 , a total of 58 articles were included in our pool/archive of data.

Flow chart of the scoping review

The quality of the 58 studies was appraised using the CASP (Critical Appraisal Skills Program) tool, as this proved to be the most feasible instrument to appraise qualitative studies (Hannes, Lockwood, & Pearson, 2010). The appraisal of the quality of the research articles was not meant as an inclusion tool in scoping, but was used later on as a parameter for intensity sampling (see further).

The pool of 58 data was used to initiate purposeful sampling –i.e. (a) intensity sampling, (b) maximum variation sampling, and (c) confirming/disconfirming case sampling (see Fig.  2 ).

Overview figure of the purposeful sampling guidance

In order to prepare for the purposeful sampling phase, we constructed a standardized extraction form for each of the 58 articles to highlight the specific characteristics identified, i.e. the data collection, method, research question/goal, sampling characteristics and main theoretical arguments. By summarizing the methodological and theoretical basis of the primary studies we could easily compare the differences between studies. This facilitated our choice in purposefully sampling papers. Table  2 shows an example of a descriptive data extraction sheet of one of the studies included.

• Purposeful sampling

Intensity sampling

“Intensity sampling in a research synthesis would involve selecting studies that are ‘excellent or rich examples of the phenomenon of interest, but not highly unusual cases [ 16 ]”.

The reason why we chose this sampling technique as the first technique is because we believed that the starting point of the literature synthesis would influence the further analysis, so it was important to choose rich examples of the phenomenon of interest, but not highly unusual cases.

The first task was to translate the theoretical definition of intensity sampling into some concrete inclusion factors. The first factor was the degree of overlap between the research question of the article and those of the qualitative evidence synthesis, because the content of the article had to parallel the intended content of our meta-ethnography closely. The second factor was the methodological quality of the paper, evaluated by means of the CASP. High-quality articles are usually more likely to provide rich, textual accounts to draw information from [ 28 ]. A third factor we assessed was the conceptual clarity of the article [ 29 ]. Conceptual clarity means the presence and clarity of concepts for translation, and is integral to a meta-ethnography which requires clear concepts as data.

We did this intensity sampling until a “jumping off point” was reached [ 30 ]. This point is reached when the concepts and categories emerging from the papers are saturated, meaning that no new concepts are derived from reading further articles. We retrieved this jumping off point after including 6 articles (see Fig.  2 ). From that point on, we wanted to deepen the concepts further by investigating the relation between the different concepts, by means of maximum variation sampling.

Maximum variation sampling

“A maximum variation sample is constructed by identifying key dimensions of variations and then finding cases that vary from each other as much as possible. This sampling yields: ‘(1) high-quality, detailed descriptions of each case, which are useful for documenting uniqueness, and (2) important shared patterns that cut across cases and derive their significance from having emerged out of heterogeneity [ 16 ].

Presuming that different study characteristics illuminate different aspects of a phenomenon, maximum variation sampling can be utilized to construct a holistic understanding of the phenomenon by synthesizing studies that differ in their study designs on several dimensions [ 15 ]. This type of sampling fits the stage of analysis as the aim is to uncover a many different key dimensions as possible.

The different concepts derived from the intensity sampling, defined the key dimensions that served as a basis for selecting additional papers. These papers vary from each other in these particular dimensions, e.g. theoretical underpinning of the articles (see further for an example of these key dimensions). Maximum variation sampling led us to the construction of a preliminary line-of-argument, after including 7 more articles (see Fig.  2 ) which was then further refined by using confirming/disconfirming case sampling.

disconfirming case sampling

“The disconfirming case sampling contains a selection of articles that do not fit [ the emerging patterns]. They are a source of rival interpretations as well as a way of placing boundaries around confirmed findings” [ 15 ].

Disconfirming case sampling fits this stage of analysis, as we want to verify and deepen the preliminary line of argument.

We selected new articles based on deviant theoretical assumptions. Disconfirming articles were thus also selected through the data extraction sheets of each paper, namely by reading through the main theoretical aspects of the studies. Papers that featured theories and concepts opposing the ones we had already included in our preliminary line-of-argument were further considered for in-depth analysis. We included 3 more articles for this sampling technique, which makes the total number of included articles 16 (see Fig.  2 ).

We have now addressed how to potentially introduce purposeful sampling into a review project. However, it has been suggested that a purposeful sampling procedure is subject to a permanent dialogue with the analysis of the data [ 31 , 32 ]. In what follows, we will discuss what sort of contribution purposeful sampling has made to our findings and the model we have developed, by means of a worked example.

Results: Illustration of the purposeful sampling techniques using a worked example

In a meta-ethnography, a popular way of analysing data is the translation of the concepts or metaphors of one study into another, while preserving the structure of relationships between concepts within any given study [ 33 ]. We will thus show how we sampled different studies and how this influenced the translation exercise based on an example of three example concepts from three articles included in our review. Note that the decision to work with three concepts only was taken to increase the clarity of the procedures we describe in this paper, not to describe all the actual results and complete line-of-argument.

First step: Arriving at a “jumping off point” through intensity sampling

We will illustrate these decisions of intensity sampling by describing the inclusion of 3 articles [ 34 – 36 ] which - according to our parameters described above - have a great degree of overlap with the research goal, a high methodological quality and strong conceptual clarity.

On the articles that were included through intensity sampling, we performed a reciprocal translation of the concepts, which is the translation of one study’s findings into another, using metaphors and overarching concepts. [ 7 ] In what follows, we give a worked example of how we did this reciprocal translation for 3 concepts identified in the initial set of studies considered for the synthesis, as this is a necessary step towards the illustration of the subsequent sampling methodology. In order to be explicit about how the concepts compared to one another, we created a table into which we placed and compared the concepts of each paper (See Table  3 ). Each row of the table represents a key concept. In the left collumn, we labelled the rows with concepts that encompassed all the relevant concepts from each paper.

The first concept we retrieved through intensity sampling is “sexual struggling”, encompassing the different ways of struggling with the sexual changes due to cancer. In Walker’s study (2011) it is formulated as having a sense of loss [ 35 ]. In the study of Gilbert (2013), this is formulated as patients having an altered body image [ 36 ]. In Juraskova’s study (2013) it is formulated as “reduced vaginal lubrification” [ 34 ].

Another overarching concept that we retrieved was “exacerbation of struggling”, encompassing strategies, situations, characteristics that were leading to an increasing struggling with the sexual changes. In Gilbert’s study (2013), this is formulated as “sticking to the coital imperative”, which means that intercourse is the most normal and natural form of heterosexuality, and condemns those who cannot perform as dysfunctional. In Walker’s study (2012), this is formulated as avoidance of communication about the sexual changes. In Juraskova (2003), exacerbation of struggling is the case when the patients are “ Receiving radiotherapy combined with external radiation and brachytherapy”.

A third overarching concept we found was the “sexual adjustment” to changes due to having cancer, encompassing the different ways of adaptation to sexual changes. Gilbert’s study (2010) describes that there is “a renegociation of the practices of sexual intimacy”, which means that the couple included sexual practices that had previously been marginalized in relation to sexual intercourse. Walker (2011) formulates this adjustment as “accepting the decision to stop sexuality”. Juraskove (2003) formulates it as “sexual adjustment and quality of life”.

The articles were sampled by the main author, but all articles included by intensity sampling were read and analysed by two authors (CB and MS). After a certain point which we call the “jumping off point”, we began to discover certain key dimensions of variation between the studies, which we explored further through maximum variation sampling. In the worked example that we explain here was the discovery that the studies varied on the scientific approach they took on, resulting in a different interpretation of the overarching concepts. To illustrate this: Gilbert (2010) used a social-constructionist lens to investigate sexual adjustment, Walker (2011) used a more psychological approach to investigate the subject, and Juraskova (2003) underscores more the biological aspects of sexual changes after cancer. Through the maximum variation sampling, we thus want to further explore how these different approaches lead to different interpretations of the phenomenon.

Second step: Apply a maximum variation sampling strategy to construct a preliminary line of argument

To explore the consequence of variation on the key dimension, we used maximum variation sampling to include studies that varied on the above cited dimension (i.e. scientific approach, socio-, psycho, or biological perspective). In this worked example, we show through the inclusion of three more papers [ 37 – 39 ] how we arrived – through comparison of the papers- at a preliminary line of argument.

The sampling was also done by one researcher, but the articles were read and analysed by 2 researchers. As a result of this maximum variation sampling and constant comparison between the papers, could develop relationships between the different concepts and constructing a preliminary line of argument (see Table  4 ).

First, with regard to the concept of struggling, we found that articles who work with a psychological approach, describe the concept of struggling on an emotional level, analog with the stages of grief (anger, depression,..) while the sociological articles describe it more on a level of identity, analog with the theory of biographical disruption. Articles who have a more biological approach reduce the struggling on a level of sexual dysfunction.

Second, with regard to the concept of exacerbation of struggling, articles who work with a psychological approach again describe a stage of the grief theory, which is denial. Sociological oriented articles work with the adherence to hegemonic discourses, and biological oriented articles use certain characteristics of the cancer treatment as barriers towards adjustment.

Third, with regard to the concept of sexual adjustment, articles who are psychological oriented again use a stage of the grief theory to encompass this adjustment, which is acceptance. Sociological oriented article worked with a “rediscovery” of what sexuality is. The changes are thus not merely accepted, rather they are incorporated in a new definition of the self and sexuality. Biological oriented articles worked with “sexual recovery”, which –in contrast to the sociological oriented articles- means that there is no difference in what sexuality means , but a reuptake of sexual activity , similar to what it was before the cancer.

Our preliminary line of argument consisted of three different pathways the articles worked with. First, there are articles following the grief theory to describe the adjustment process In this case, sexual changes are depicted in terms of losses, and the adjustment occurs through the process of grief and mourning.

Second, there are articles following the “restructuring theory” during illness. Unlike the case of grief theory, where the patient and partner are working through some emotional stages, in the restructuring pathway patient and partner are more cognitively dealing with sexuality after cancer through the development of a new sexual paradigm. Flexibility is the central aspect of this adjustment.

Thirdly, there are articles following the pathway of sexual rehabilitation. This pathway is embedded in a more positivistic paradigm where the adaptation does not emphasize psychological changes or cognitive restructuring, but sexual changes as a bodily dysfunction that needs treatment and behavioural strategies.

Refining the preliminary line of argument by means of disconfirming case sample.

To test, refine, and deepening our preliminary line-of-argument, , we included 3 articles out of the pool of 58 articles that consist of a theory and concepts opposing the preliminary line-of argument. We will give an example with including 1 article (see Table  5 ).

In this phase of sampling, we worked together with a researcher who was not involved in the analysis process before (JB). This is because we wanted to have a fresh and “unambiguous view” of our line of argument. This researcher, together with the first researcher, read the articles and tested them against the line of argument.

In our preliminary line-of-argument, we assumed that the three pathways of adjustment all followed a linear pattern from the struggling towards the adjustment. However, Ramirez (2009) counter argues this linear approach by stating that patients could refine their definition of sexuality, but could also return to it at a certain moment [ 40 ]. These disconfirming findings led us to re-analyse the included articles, where we came eventually to the conclusion that the sexual adjustment as a cognitive restructuring process does not have a linear pattern with an endpoint, but rather makes on oscillating movement between following hegemonic definitions of sexuality, and challenging them.

Challenges and opportunities

In the process of conducting a qualitative evidence synthesis through purposeful sampling, we encountered several challenges. But this process also created a few opportunities that would not have occurred if we had used an exhaustive sampling and analysis strategy. In what follows, we discuss how we have bridged obstacles and maximized benefits in terms of the opportunities arising.

First, it proved to be difficult to define what exactly to look for, since the concept of e.g. an intensity sample on the meta-level could not readily been borrowed from the logic applied in basic research projects. In an original research project, as opposed to a qualitative evidence synthesis project, purposeful sampling can often easily be conducted, for example by using a brief questionnaire as a screening tool to search for participants with specific characteristics [ 41 ]. However, with research reports, this is more difficult in practice. We chose to search for literature by means of electronic databases with the use of search strings. Finding a specific search string to detect a specific information-rich research report which meets the sampling criteria would be difficult, because the search terms are usually based on population and setting characteristics as well as the topic of interest, rather than on conceptual or theoretically interesting leads.

Therefore we decided to conduct a scoping of the literature prior to applying a purposeful sampling technique. The scoping review was intended to create a pool/or archive of primary research reports that are easily accessible and can be used later as material for purposeful sampling. In fact, our purposeful sampling strategy did not start at the level of data-collection. It was initiated at the level of data extraction and analysis. The consequence of this decision was that the sampling procedure was rather labour-intensive as we had to perform a scoping review before the actual mixed purposeful sampling could start.

We illustrated through our worked example that using purposeful sampling techniques also has several advantages.

First of all, although some researchers argued that reducing the number of included articles by means of purposeful sampling could result in neglecting important data [ 18 , 42 ], we showed throughout this worked example that the opposite can be true. With the use of this combination of three purposeful sampling techniques – intensity sampling, maximum variation sampling and confirming/disconfirming case sampling - we arrived at a line-of-argument.

Because of this emphasis on conceptual robustness instead of generalization of the data, we were more sensitive to “deviant data”, i.e. data that may not have been picked up when synthesizing information from an exhaustive sample of the literature, because review authors are generally more focused on detecting commonalities between articles. When using an exhaustive sampling technique, researchers will arrive at results that describe the “greatest common devisor” of all included papers.

Furthermore, deviant data that has been derived through maximum variation sampling and confirming/disconfirming case sampling may add new perspectives or a new space of understanding to the line-of-argument, while sampling randomly may run the risk of preventing enhanced insight and knowledge.

Moreover, the combination of sampling techniques – instead of a random sample or just one method of purposeful sampling- could enhance the quality and diversity of the papers being included, and could make the results more conceptually aligned with the synthesis purpose. This would further enhance the possible impact a qualitative evidence synthesis could have on informing healthcare practice [ 43 ].

Such an approach, however, demands a considerable amount of flexibility from review authors, mainly because inclusion criteria may change progressively during the process. This fact, together with the experience described above of doing a labour-intensive scope of the literature, goes against the argument of many authors [ 5 ] that using purposeful sampling provides a pragmatic solution or a short cut for reviewers who have limited time for searching and screening. However, we felt we did gain some time in the analytical process, since the number of articles from which data were extracted was modest in number. This strategy is therefore recommended for authors who are left with a high number of relevant articles after screening for inclusion.

However, the choice of using this particular combination of sampling techniques should also be motivated from a theoretical perspective. Authors who want to build a theoretical model out of the qualitative evidence synthesis could use this scheme of sampling methods, as it aligns well with the different stages of analysis, and is parallel to what Corbin and Strauss suggested for primary research [ 24 ].

In this paper, we addressed two different needs:

Firstly, we met the need for a transparent worked example of how to apply purposeful sampling techniques to a qualitative evidence synthesis. We believe that this paper can help other researchers to make decisions related to purposeful sampling in a more systematic and transparent way.

Secondly, we gave evidence for the beneficial effects of using purposeful sampling techniques in a qualitative evidence synthesis. Although purposeful sampling is a time-consuming activity that requires a lot of resources and flexibility from the researchers, it creates potential to arrive at a rich conceptual model that can be useful for clinical practice. Future research could confirm or disconfirm the hypothesis of conceptual enhancement by comparing the findings of a purposefully sampled qualitative evidence synthesis with those drawing on an exhaustive sample of the literature.

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Acknowledgements

We would like to thank Drs. Marlies Saelaert for making substantial contributions to the analysis and interpretation of the data of our meta-synthesis. We also would like to acknowledge the Flemish fund for Scientific research (FWO) for financially supporting this study.

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CB carried out the qualitative evidence synthesis and wrote the first draft. KH guided the philosophic discussion that contributed to the methodological development of the paper. JB conceived of the study, participated in its design and helped to draft the manuscript. All authors read and approved the final manuscript.

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Benoot, C., Hannes, K. & Bilsen, J. The use of purposeful sampling in a qualitative evidence synthesis: A worked example on sexual adjustment to a cancer trajectory. BMC Med Res Methodol 16 , 21 (2016). https://doi.org/10.1186/s12874-016-0114-6

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Purposive Sampling in Qualitative Research

Introduction

What is the purposive sampling method, what is purposive sampling used to identify, when to use purposive sampling, types of sampling methods, advantages of purposive sampling, disadvantages of purposive sampling, how to conduct purposive sampling.

In qualitative research studies that involve methods such as interviews , focus groups , and surveys , purposive sampling is useful when the researcher wants to collect qualitative data from a specific population with particular characteristics.

Purposive sampling or judgmental sampling stands in contrast to random sampling or probability sampling, which aims to collect data randomly to ensure the generalization of findings across an entire population. Instead, the objective in purposive sampling is to target a specific subset of people to more deeply understand the unique or diverse variations in a culture or context.

In this article, we'll examine the different kinds of purposive sampling and the considerations involved with conducting research through purposive sampling.

Purposive sampling, also known as judgmental or selective sampling, is a non-probabilistic sampling technique used extensively in qualitative research . This method involves deliberately choosing participants based on the characteristics of a population and the objectives of the study. Unlike random probability sampling , where every member of the population has an equal chance of being selected, purposive sampling allows researchers to use their judgment to select cases that will best contribute to the data collection and the objectives of the research.

The essence of purposive sampling lies in selecting information-rich cases. These can be individuals, groups, or occurrences that are relevant to the issue being studied. For example, if a study aims to understand the experiences of cancer survivors, purposive sampling would involve selecting individuals who have lived through cancer, as they can provide depth and insight into the research question .

This method is widely preferred in exploratory studies, where detailed understanding rather than generalization is the goal. It enables researchers to focus on specific characteristics, conditions, or phenomena that are central to the research question. The idea is not to randomly select cases in a way that mirrors the population, but rather to select cases that will illuminate the topic of interest more richly and in depth.

Ultimately, purposive sampling is a strategic choice by researchers to select participants who can provide the most informative data, rather than aiming for a broad representation of the entire population. This approach is crucial when the researcher aims to explore specific themes, patterns, or phenomena within a subset of a population, which requires detailed and nuanced insights.

Purposive sampling is primarily used to identify specific characteristics, trends, or insights within a targeted subset of a population. This method is particularly effective in identifying unique or exceptional cases that are not readily observable in the broader population. By focusing on particular characteristics or experiences, purposive sampling allows researchers to delve into the depth and complexity of the subject matter, providing rich, detailed insights.

The key objective of purposive sampling is to gain a deep understanding of phenomena from a specific perspective or within a specific context. For instance, in a study about educational practices, researchers might use purposive sampling to select teachers who are implementing innovative teaching methods. Here, the focus is not on how common these practices are, but on understanding the nature, challenges, and impacts of these innovations in depth.

Furthermore, purposive sampling is instrumental in identifying and exploring patterns or themes that emerge within a particular group. This can include exploring the experiences of a minority group, understanding behaviors in a specific cultural setting, or examining the impacts of a policy on a targeted demographic. The method ensures that the sample provides the necessary information to answer the research questions, even if it does not statistically represent the larger population.

In essence, purposive sampling is used to extract meaningful and in-depth information from a selected group of participants, providing qualitative insights that are often unattainable through more generalized sampling methods.

Purposive sampling is most appropriate in qualitative research when the aim is to gain detailed and nuanced understanding of specific phenomena, rather than to generalize findings to a larger population. This approach is particularly useful in several scenarios:

Exploratory research

When little is known about a phenomenon and the goal is to develop propositions or theories, purposive sampling helps in selecting cases rich in information. It is ideal for initial explorations where specific insights are needed to form a basis for further study.

Studying unique or specific cases

In cases where the research focuses on specific types of individuals, events, or phenomena, purposive sampling allows researchers to deliberately target these instances. For example, studying the experiences of a particular professional group or examining rare events can be realized through purposive sampling.

Context-dependent knowledge

When the research question requires deep understanding of the context or the environment, purposive sampling enables the selection of participants who have experienced or are immersed in that context.

Resource constraints

In situations where resources, such as time and money, are limited, purposive sampling offers a practical approach to focus on key informants or critical cases that provide the most valuable data.

Theory or concept testing

When testing theories or concepts, purposive sampling can be used to select cases that are most likely to challenge or support these theories.

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Purposive sampling encompasses various methods, each tailored to specific research objectives and contexts. These methods allow researchers to strategically select participants based on particular criteria, ensuring the collected data is most relevant to the study.

Below is an overview of the different types of purposive sampling methods. Each of these purposive sampling methods offers unique advantages and is suited to specific research scenarios, enabling researchers to gather rich, targeted data for their qualitative studies .

Convenience sampling

This method involves selecting participants who are easily accessible to the researcher. It's often used for preliminary or exploratory studies where convenience and speed are prioritized over representativeness.

Snowball sampling

Snowball sampling is used when potential participants are hard to locate. Researchers start with a few known subjects who then refer others, creating a 'snowball' effect in participant recruitment.

Cluster sampling

In cluster sampling , the population is divided into clusters, and then a few clusters are chosen at random for research. This method is beneficial when studying a large population dispersed over a wide area.

Heterogeneous sampling

Also known as maximum variation sampling, this approach focuses on capturing a wide range of perspectives by selecting participants with varied characteristics. It's ideal for exploring the breadth of a phenomenon.

Homogeneous sampling

In contrast to heterogeneous sampling, this method selects participants with similar characteristics or experiences, facilitating an in-depth study of a particular subgroup.

Typical case sampling

Researchers select 'typical' cases that are average or representative of the population. This method is useful for providing an illustrative snapshot of the norm.

Critical case sampling

This method involves selecting cases that are crucial for the research question , often because they can make or break a theory or hypothesis .

Extreme case sampling

This approach focuses on unusual or rare cases that are different from the norm, providing insights into atypical phenomena.

Stratified sampling

Stratified sampling involves dividing the population into subgroups and selecting samples from each subgroup. This can ensure representation across key characteristics or variables.

Purposive sampling offers several significant advantages in qualitative research , particularly when the focus is on gaining deep, contextualized insights rather than generalizable data. Let's look at some of the key advantages.

Purposive sampling allows for the selection of participants who are most relevant to the research question. This targeted approach ensures that the data collected is rich and directly pertinent to the study's objectives, leading to more meaningful and focused findings.

Since this method often involves selecting participants with specific experiences or knowledge, it facilitates the collection of in-depth information. Researchers can delve into complex topics with participants who offer detailed insights, making it possible to explore nuances and subtleties that might be missed with a more generalized approach.

Purposive sampling is highly adaptable to the needs of a study. Researchers can adjust their sampling strategy as they learn more about their subject, allowing for a responsive and evolving research process. This flexibility is particularly valuable in exploratory studies or when new themes emerge during the research.

By focusing on specific individuals or groups, purposive sampling can be more time and resource-efficient compared to probability sampling methods. It reduces the need for a large sample size while still providing rich, valuable data.

This method is especially advantageous when studying hard-to-reach, specialized, or vulnerable populations. Purposive sampling allows researchers to carefully select participants who can provide insights into these unique groups, which might be difficult to achieve with random sampling .

Finally, purposive sampling is conducive to theory development. By selecting cases that are particularly informative for understanding the research question , this method can significantly contribute to theoretical insights and advancements.

While purposive sampling is highly beneficial for certain qualitative research studies, it also has several disadvantages that researchers must consider.

The most significant drawback of purposive sampling is the limited ability to generalize findings to the broader population. Since samples are specifically selected based on certain criteria or characteristics, they may not adequately represent the diversity and variability present in the larger population.

This method relies heavily on the researcher's judgment in selecting participants. This inherent subjectivity can introduce bias , as the researcher's perspectives and preconceptions may influence the choice of sample, potentially leading to skewed or one-sided data.

The subjective nature of sample selection in purposive sampling also makes it challenging to replicate studies. Different researchers might choose different participants, which can result in varying findings and conclusions, potentially limiting the reliability of the research.

In purposive sampling, there is a risk of overemphasizing particular viewpoints, especially those of more vocal or articulate participants, while underrepresenting less prominent perspectives. This can skew the research outcomes and reduce the depth of understanding.

Finally, the non-random selection process increases the risk of sampling errors. The sample might not adequately capture the complexity or nuances of the broader population, leading to partial or incomplete findings.

Conducting purposive sampling in qualitative research demands a structured and thoughtful approach that closely aligns with the study's objectives. The process begins with a clear articulation of these objectives and the establishment of criteria for participant selection. This crucial first step involves identifying specific characteristics, experiences, or knowledge that the participants need to possess to provide relevant insights into the research question .

Once the research goals and criteria are defined, the next task is to identify the broader population relevant to the study. From this larger group, participants who meet the established criteria are selected. The selection of the appropriate purposive sampling method is a critical decision that should be based on the specific aims of the research. Various methods , such as homogeneous sampling for in-depth exploration of a specific group or critical case sampling for testing a theory, can be chosen depending on what aligns best with the study's goals.

The recruitment of participants is a dynamic process. It may involve directly reaching out to specific individuals, employing snowball techniques to find suitable participants, or collaborating with organizations or communities. While focusing on specific criteria, it's important to ensure a diverse range of participants within those parameters to provide a comprehensive understanding of the topic.

Throughout the sampling process, continually evaluating the adequacy of the sample size and composition is essential. The focus should be on the richness of the data , which often dictates the adequacy of the sample size, rather than merely the number of participants.

Lastly, documenting every decision and rationale throughout the process is vital for the credibility of the research. This transparency allows others to understand the hows and whys of participant selection, reinforcing the integrity of the study.

By meticulously following these guidelines, researchers can effectively implement purposive sampling, ensuring that their sample provides rich, targeted data that is in line with the study's objectives.

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Home » Purposive Sampling – Methods, Types and Examples

Purposive Sampling – Methods, Types and Examples

Table of Contents

Purposive Sampling

Definition:

Purposive sampling is a non-probability sampling technique used in research to select individuals or groups of individuals that meet specific criteria relevant to the research question or objective.

This sampling technique is also known as judgmental sampling or selective sampling, and it is often used when the population being studied is too small, too difficult to access, or too heterogeneous to use probability sampling methods.

Purposive Sampling Methods

Purposive Sampling Methods are as follows:

• Expert sampling: In expert sampling, the researcher selects participants who are experts in a particular field or subject matter. This can be useful when studying a specialized or technical topic, as experts are likely to have a deeper understanding of the subject matter and can provide valuable insights.
• Maximum variation sampling: Maximum variation sampling involves selecting participants who represent a wide range of characteristics or perspectives. This can be useful when the researcher wants to capture a diverse range of experiences or viewpoints.
• Homogeneous sampling : In homogeneous sampling, the researcher selects participants who have similar characteristics or experiences. This can be useful when studying a specific subpopulation that shares common traits or experiences.
• Critical case sampling : Critical case sampling involves selecting participants who are likely to provide important or unique insights into the research question. This can be useful when the researcher wants to focus on cases that are particularly relevant or informative.
• Snowball sampling : Snowball sampling involves selecting participants based on referrals from other participants in the study. This can be useful when studying hard-to-reach or hidden populations, as it allows the researcher to gain access to individuals who may not be easily identifiable or accessible.

How to Conduct Purposive Sampling

Here are the general steps involved in conducting purposive sampling:

• Identify the research question or objective: The first step in conducting purposive sampling is to clearly define the research question or objective. This will help you determine the criteria for participant selection.
• Determine the criteria for participant selection : Based on the research question or objective, determine the specific criteria for selecting participants. These criteria should be relevant to the research question and should help you identify individuals who are most likely to provide valuable insights.
• Identify potential participants: Once you have determined the criteria for participant selection, identify potential participants who meet these criteria. Depending on the sampling method you are using, this may involve reaching out to experts in the field, identifying individuals who share certain characteristics or experiences, or asking for referrals from existing participants.
• Select participants: Based on the identified potential participants, select the individuals who will participate in the study. Make sure to select a sufficient number of participants to ensure that you have a representative sample.
• Collect data: After selecting participants, collect data using the appropriate research methods. Depending on the research question and objectives, this may involve conducting interviews, administering surveys, or collecting observational data.
• Analyze data: After collecting data, analyze it to answer the research question or objective. This may involve using statistical analysis, qualitative analysis, or a combination of both.

Examples of Purposive Sampling

Here are some examples of how purposive sampling might be used in research:

• Studying the experiences of cancer survivors : A researcher might use maximum variation sampling to select a diverse group of cancer survivors, with the aim of capturing a range of experiences and perspectives on the impact of cancer on their lives.
• Exploring the perspectives of teachers on a new curriculum : A researcher might use expert sampling to select teachers who are experts in a particular subject area or who have experience teaching the new curriculum. These teachers can provide valuable insights on the strengths and weaknesses of the new curriculum.
• Investigating the impact of a new therapy on a specific population: A researcher might use homogeneous sampling to select participants who share certain characteristics, such as a particular diagnosis or age group. This can help the researcher assess the effectiveness of the new therapy on this specific population.
• Examining the experiences of refugees resettling in a new country : A researcher might use critical case sampling to select participants who have experienced particularly challenging resettlement experiences, such as those who have experienced discrimination or faced significant barriers to accessing services.
• Understanding the experiences of homeless individuals : A researcher might use snowball sampling to identify and select homeless individuals to participate in the study. This method allows the researcher to gain access to a hard-to-reach population and capture a range of experiences and perspectives on homelessness.

Applications of Purposive Sampling

Purposive sampling has a wide range of applications across different fields of research. Here are some examples of how purposive sampling can be used:

• Medical research: Purposive sampling is commonly used in medical research to study the experiences of patients with specific medical conditions. Researchers might use homogeneous sampling to select patients who share specific medical characteristics, such as a particular diagnosis or treatment history.
• Market research: In market research, purposive sampling can be used to select participants who represent a particular demographic or consumer group. This might involve using quota sampling to select participants based on age, gender, income, or other relevant criteria.
• Education research: Purposive sampling can be used in education research to select participants who have specific educational experiences or backgrounds. For example, researchers might use maximum variation sampling to select a diverse group of students who have experienced different teaching styles or classroom environments.
• Social science research : In social science research, purposive sampling can be used to select participants who have specific social or cultural backgrounds. Researchers might use snowball sampling to identify and select participants from hard-to-reach or marginalized populations.
• Business research: In business research, purposive sampling can be used to select participants who have specific job titles, work in particular industries, or have experience with specific products or services

Purpose of Purposive Sampling

The purpose of purposive sampling is to select participants based on specific criteria relevant to the research question or objectives. Unlike probability sampling techniques, which rely on random selection to ensure representativeness, purposive sampling allows researchers to select participants who are most relevant to their research question or objectives.

Purposive sampling is often used when the population of interest is rare, hard to reach, or has specific characteristics that are important to the research question. By selecting participants who meet specific criteria, researchers can gather valuable insights that can help inform their research.

The ultimate goal of purposive sampling is to increase the validity and reliability of research findings by selecting participants who are most relevant to the research question or objectives. This can help researchers to make more accurate inferences about the population of interest and to develop more effective interventions or solutions based on their findings.

When to use Purposive Sampling

Purposive sampling is appropriate when researchers need to select participants who meet specific criteria relevant to their research question or objectives. Here are some situations where purposive sampling might be appropriate:

• Rare populations: Purposive sampling is often used when the population of interest is rare, such as people with a particular medical condition or individuals who have experienced a particular event or phenomenon.
• Hard-to-reach populations: Purposive sampling is also useful when the population of interest is hard to reach, such as homeless individuals or individuals who have experienced trauma or abuse.
• Specific characteristics: Purposive sampling is appropriate when researchers need to select participants with specific characteristics that are relevant to the research question, such as age, gender, or ethnicity.
• Expertise : Purposive sampling is useful when researchers need to select participants with particular expertise or knowledge, such as teachers or healthcare professionals.
• Maximum variation : Purposive sampling can be used to select participants who represent a range of perspectives or experiences, such as individuals from different socio-economic backgrounds or who have different levels of education.

Characteristics of Purposive Sampling

Purposive sampling has several characteristics that distinguish it from other sampling methods:

• Non-random selection : Purposive sampling involves the deliberate selection of participants based on specific criteria, rather than random selection. This allows researchers to select participants who are most relevant to their research question or objectives.
• Small sample sizes: Purposive sampling typically involves smaller sample sizes than probability sampling methods, as the focus is on selecting participants who meet specific criteria, rather than ensuring representativeness of the larger population.
• Heterogeneous or homogeneous samples : Purposive sampling can involve selecting participants who are either similar to each other (homogeneous) or who are diverse and represent a range of perspectives or experiences (heterogeneous).
• Multiple sampling strategies: Purposive sampling involves a range of sampling strategies that can be used to select participants, including maximum variation sampling, expert sampling, quota sampling, and snowball sampling.
• Flexibility : Purposive sampling is a flexible method that can be adapted to suit different research questions and objectives. It allows researchers to select participants based on specific criteria, making it a useful method for exploring complex phenomena or researching hard-to-reach populations.

Advantages of Purposive Sampling

Purposive sampling has several advantages over other sampling methods:

• Relevant participants: Purposive sampling allows researchers to select participants who are most relevant to their research question or objectives, ensuring that the data collected is of high quality and useful for the research.
• Efficient : Purposive sampling is an efficient method of sampling, as it allows researchers to select participants based on specific criteria, rather than randomly selecting a large number of participants. This can save time and resources, especially when the population of interest is rare or hard to reach.
• Representative : Purposive sampling can produce samples that are representative of the population of interest, as researchers can use a range of sampling strategies to select participants who are diverse and represent a range of perspectives or experiences.
• Ethical considerations : Purposive sampling can be used to ensure that vulnerable or marginalized populations are included in research studies, ensuring that their voices and experiences are heard and taken into account.

Disadvantages of Purposive Sampling

Some Disadvantages of Purposive Sampling are as follows:

• Sampling bias: Purposive sampling is susceptible to sampling bias, as the participants are not randomly selected from the population. This means that the sample may not be representative of the larger population, and the findings may not be generalizable to other populations.
• Limited generalizability: The findings obtained from purposive sampling may be limited in their generalizability due to the small sample size and the specific selection criteria used. Therefore, it may not be possible to make broad generalizations based on the findings of a purposive sample.
• Lack of transparency : The selection criteria used in purposive sampling may not be transparent, and this can limit the ability of other researchers to replicate the study.
• Reliance on researcher judgment : Purposive sampling relies on the researcher’s judgment to select participants based on specific criteria, which can introduce bias into the selection process.
• Potential for researcher subjectivity : The researcher’s subjectivity and bias may influence the selection process and the interpretation of the data collected.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Different Types of Sampling Techniques in Qualitative Research

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Key Takeaways:

• Sampling techniques in qualitative research include purposive, convenience, snowball, and theoretical sampling.
• Choosing the right sampling technique significantly impacts the accuracy and reliability of the research results.
• It’s crucial to consider the potential impact on the bias, sample diversity, and generalizability when choosing a sampling technique for your qualitative research.

Qualitative research seeks to understand social phenomena from the perspective of those experiencing them. It involves collecting non-numerical data such as interviews, observations, and written documents to gain insights into human experiences, attitudes, and behaviors. While qualitative research can provide rich and nuanced insights, the accuracy and generalizability of findings depend on the quality of the sampling process. Sampling is a critical component of qualitative research as it involves selecting a group of participants who can provide valuable insights into the research questions.

This article explores different types of sampling techniques used in qualitative research. First, we’ll provide a comprehensive overview of four standard sampling techniques used in qualitative research. and then compare and contrast these techniques to provide guidance on choosing the most appropriate method for a particular study. Additionally, you’ll find best practices for sampling and learn about ethical considerations researchers need to consider in selecting a sample. Overall, this article aims to help researchers conduct effective and high-quality sampling in qualitative research.

In this Article:

• Purposive Sampling
• Convenience Sampling
• Snowball Sampling
• Theoretical Sampling

Factors to Consider When Choosing a Sampling Technique

Practical approaches to sampling: recommended practices, final thoughts, get expert guidance on your sample needs.

Want expert input on the best sampling technique for your qualitative research project? Book a consultation for trusted advice.

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4 Types of Sampling Techniques and Their Applications

Sampling is a crucial aspect of qualitative research as it determines the representativeness and credibility of the data collected. Several sampling techniques are used in qualitative research, each with strengths and weaknesses. In this section, let’s explore four standard sampling techniques used in qualitative research: purposive sampling, convenience sampling, snowball sampling, and theoretical sampling. We’ll break down the definition of each technique, when to use it, and its advantages and disadvantages.

1. Purposive Sampling

Purposive sampling, or judgmental sampling, is a non-probability sampling technique commonly used in qualitative research. In purposive sampling, researchers intentionally select participants with specific characteristics or unique experiences related to the research question. The goal is to identify and recruit participants who can provide rich and diverse data to enhance the research findings.

Purposive sampling is used when researchers seek to identify individuals or groups with particular knowledge, skills, or experiences relevant to the research question. For instance, in a study examining the experiences of cancer patients undergoing chemotherapy, purposive sampling may be used to recruit participants who have undergone chemotherapy in the past year. Researchers can better understand the phenomenon under investigation by selecting individuals with relevant backgrounds.

Purposive Sampling: Strengths and Weaknesses

Purposive sampling is a powerful tool for researchers seeking to select participants who can provide valuable insight into their research question. This method is advantageous when studying groups with technical characteristics or experiences where a random selection of participants may yield different results.

One of the main advantages of purposive sampling is the ability to improve the quality and accuracy of data collected by selecting participants most relevant to the research question. This approach also enables researchers to collect data from diverse participants with unique perspectives and experiences related to the research question.

However, researchers should also be aware of potential bias when using purposive sampling. The researcher’s judgment may influence the selection of participants, resulting in a biased sample that does not accurately represent the broader population. Another disadvantage is that purposive sampling may not be representative of the more general population, which limits the generalizability of the findings. To guarantee the accuracy and dependability of data obtained through purposive sampling, researchers must provide a clear and transparent justification of their selection criteria and sampling approach. This entails outlining the specific characteristics or experiences required for participants to be included in the study and explaining the rationale behind these criteria. This level of transparency not only helps readers to evaluate the validity of the findings, but also enhances the replicability of the research.

2. Convenience Sampling  

When time and resources are limited, researchers may opt for convenience sampling as a quick and cost-effective way to recruit participants. In this non-probability sampling technique, participants are selected based on their accessibility and willingness to participate rather than their suitability for the research question. Qualitative research often uses this approach to generate various perspectives and experiences.

During the COVID-19 pandemic, convenience sampling was a valuable method for researchers to collect data quickly and efficiently from participants who were easily accessible and willing to participate. For example, in a study examining the experiences of university students during the pandemic, convenience sampling allowed researchers to recruit students who were available and willing to share their experiences quickly. While the pandemic may be over, convenience sampling during this time highlights its value in urgent situations where time and resources are limited.

Convenience Sampling: Strengths and Weaknesses

Convenience sampling offers several advantages to researchers, including its ease of implementation and cost-effectiveness. This technique allows researchers to quickly and efficiently recruit participants without spending time and resources identifying and contacting potential participants. Furthermore, convenience sampling can result in a diverse pool of participants, as individuals from various backgrounds and experiences may be more likely to participate.

While convenience sampling has the advantage of being efficient, researchers need to acknowledge its limitations. One of the primary drawbacks of convenience sampling is that it is susceptible to selection bias. Participants who are more easily accessible may not be representative of the broader population, which can limit the generalizability of the findings. Furthermore, convenience sampling may lead to issues with the reliability of the results, as it may not be possible to replicate the study using the same sample or a similar one.

To mitigate these limitations, researchers should carefully define the population of interest and ensure the sample is drawn from that population. For instance, if a study is investigating the experiences of individuals with a particular medical condition, researchers can recruit participants from specialized clinics or support groups for that condition. Researchers can also use statistical techniques such as stratified sampling or weighting to adjust for potential biases in the sample.

3. Snowball Sampling

Snowball sampling, also called referral sampling, is a unique approach researchers use to recruit participants in qualitative research. The technique involves identifying a few initial participants who meet the eligibility criteria and asking them to refer others they know who also fit the requirements. The sample size grows as referrals are added, creating a chain-like structure.

Snowball sampling enables researchers to reach out to individuals who may be hard to locate through traditional sampling methods, such as members of marginalized or hidden communities. For instance, in a study examining the experiences of undocumented immigrants, snowball sampling may be used to identify and recruit participants through referrals from other undocumented immigrants.

Snowball Sampling: Strengths and Weaknesses

Snowball sampling can produce in-depth and detailed data from participants with common characteristics or experiences. Since referrals are made within a network of individuals who share similarities, researchers can gain deep insights into a specific group’s attitudes, behaviors, and perspectives.

4. Theoretical Sampling

Theoretical sampling is a sophisticated and strategic technique that can help researchers develop more in-depth and nuanced theories from their data. Instead of selecting participants based on convenience or accessibility, researchers using theoretical sampling choose participants based on their potential to contribute to the emerging themes and concepts in the data. This approach allows researchers to refine their research question and theory based on the data they collect rather than forcing their data to fit a preconceived idea.

Theoretical sampling is used when researchers conduct grounded theory research and have developed an initial theory or conceptual framework. In a study examining cancer survivors’ experiences, for example, theoretical sampling may be used to identify and recruit participants who can provide new insights into the coping strategies of survivors.

Theoretical Sampling: Strengths and Weaknesses

One of the significant advantages of theoretical sampling is that it allows researchers to refine their research question and theory based on emerging data. This means the research can be highly targeted and focused, leading to a deeper understanding of the phenomenon being studied. Additionally, theoretical sampling can generate rich and in-depth data, as participants are selected based on their potential to provide new insights into the research question.

Participants are selected based on their perceived ability to offer new perspectives on the research question. This means specific perspectives or experiences may be overrepresented in the sample, leading to an incomplete understanding of the phenomenon being studied. Additionally, theoretical sampling can be time-consuming and resource-intensive, as researchers must continuously analyze the data and recruit new participants.

To mitigate the potential for bias, researchers can take several steps. One way to reduce bias is to use a diverse team of researchers to analyze the data and make participant selection decisions. Having multiple perspectives and backgrounds can help prevent researchers from unconsciously selecting participants who fit their preconceived notions or biases.

Another solution would be to use reflexive sampling. Reflexive sampling involves selecting participants aware of the research process and provides insights into how their biases and experiences may influence their perspectives. By including participants who are reflexive about their subjectivity, researchers can generate more nuanced and self-aware findings.

Choosing the proper sampling technique is one of the most critical decisions a researcher makes when conducting a study. The preferred method can significantly impact the accuracy and reliability of the research results.

For instance, purposive sampling provides a more targeted and specific sample, which helps to answer research questions related to that particular population or phenomenon. However, this approach may also introduce bias by limiting the diversity of the sample.

Conversely, convenience sampling may offer a more diverse sample regarding demographics and backgrounds but may also introduce bias by selecting more willing or available participants.

Snowball sampling may help study hard-to-reach populations, but it can also limit the sample’s diversity as participants are selected based on their connections to existing participants.

Theoretical sampling may offer an opportunity to refine the research question and theory based on emerging data, but it can also be time-consuming and resource-intensive.

Additionally, the choice of sampling technique can impact the generalizability of the research findings. Therefore, it’s crucial to consider the potential impact on the bias, sample diversity, and generalizability when choosing a sampling technique. By doing so, researchers can select the most appropriate method for their research question and ensure the validity and reliability of their findings.

Tips for Selecting Participants

When selecting participants for a qualitative research study, it is crucial to consider the research question and the purpose of the study. In addition, researchers should identify the specific characteristics or criteria they seek in their sample and select participants accordingly.

One helpful tip for selecting participants is to use a pre-screening process to ensure potential participants meet the criteria for inclusion in the study. Another technique is using multiple recruitment methods to ensure the sample is diverse and representative of the studied population.

Ensuring Diversity in Samples

Diversity in the sample is important to ensure the study’s findings apply to a wide range of individuals and situations. One way to ensure diversity is to use stratified sampling, which involves dividing the population into subgroups and selecting participants from each subset. This helps establish that the sample is representative of the larger population.

Maintaining Ethical Considerations

When selecting participants for a qualitative research study, it is essential to ensure ethical considerations are taken into account. Researchers must ensure participants are fully informed about the study and provide their voluntary consent to participate. They must also ensure participants understand their rights and that their confidentiality and privacy will be protected.

A qualitative research study’s success hinges on its sampling technique’s effectiveness. The choice of sampling technique must be guided by the research question, the population being studied, and the purpose of the study. Whether purposive, convenience, snowball, or theoretical sampling, the primary goal is to ensure the validity and reliability of the study’s findings.

By thoughtfully weighing the pros and cons of each sampling technique, researchers can make informed decisions that lead to more reliable and accurate results. In conclusion, carefully selecting a sampling technique is integral to the success of a qualitative research study, and a thorough understanding of the available options can make all the difference in achieving high-quality research outcomes.

If you’re interested in improving your research and sampling methods, Sago offers a variety of solutions. Our qualitative research platforms, such as QualBoard and QualMeeting, can assist you in conducting research studies with precision and efficiency. Our robust global panel and recruitment options help you reach the right people. We also offer qualitative and quantitative research services to meet your research needs. Contact us today to learn more about how we can help improve your research outcomes.

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Purposive sampling

Purposive sampling (also known as  judgment, selective or subjective sampling) is a sampling technique in which researcher relies on his or her own judgment when choosing members of population to participate in the study.

Purposive sampling is a non-probability sampling method and it occurs when “elements selected for the sample are chosen by the judgment of the researcher. Researchers often believe that they can obtain a representative sample by using a sound judgment, which will result in saving time and money”. [1]

TV reporters stopping certain individuals on the street in order to ask their opinions about certain political changes constitutes the most popular example of this sampling method. However, it is important to specify that the TV reporter has to apply certain judgment when deciding who to stop on the street to ask questions; otherwise it would be the case of  random sampling  technique.

Alternatively, purposive sampling method may prove to be effective when only limited numbers of people can serve as primary data sources due to the nature of research design and aims and objectives. For example, for a research analysing affects of personal tragedy such as family bereavement on performance of senior level managers the researcher may use his/her own judgment in order to choose senior level managers who could particulate in in-depth interviews.

In purposive sampling personal judgment needs to be used to choose cases that help answer research questions or achieve research objectives.

According to the type of cases, purposive sampling can be divided into the following six categories [1] :

• Typical case . Explains cases that are average and normal.
• Extreme or deviant case . Deriving samples from cases that are perceived as unusual or rare such as exploring the reasons for corporate failure by interviewing executives that have been fired by shareholders.
• Critical case sampling focuses on specific cases that are dramatic or very important.
• Heterogeneous or maximum variation sampling relies on researcher’s judgment to select participants with diverse characteristics. This is done to ensure the presence of maximum variability within the primary data.
• Homogeneous sampling focuses on “focuses on one particular subgroup in which all the sample members are similar, such as a particular occupation or level in an organization’s hierarchy” [2]
• Theoretical sampling is a special case of purposive sampling that is based on an inductive method of Grounded Theory.

Application of Purposive Sampling (Judgment Sampling): an Example

Suppose, your dissertation topic has been approved as the following:

A study into the impact of tax scandal on the brand image of Starbucks Coffee in the UK

If you decide to apply questionnaire primary data collection method with use of purposive sampling, you can go out to Oxford Street and stop what seems like a reasonable cross-section of people in the street to survey.

Another example. Your research objective is to determine the patterns of use of social media by global IT consulting companies based in the US. Rather than applying random sampling and choosing subjects who may not be available, you can use purposive sampling to choose IT companies whose availability and attitude are compatible with the study.

Advantages of Purposive Sampling (Judgment Sampling)

• Purposive sampling is one of the most cost-effective and time-effective sampling methods available
• Purposive sampling may be the only appropriate method available if there are only limited number of primary data sources who can contribute to the study
• This sampling technique can be effective in exploring anthropological situations where the discovery of meaning can benefit from an intuitive approach

Disadvantages of Purposive Sampling (Judgment Sampling)

• Vulnerability to errors in judgment by researcher
• Low level of reliability and high levels of bias.
• Inability to generalize research findings

Because of these disadvantages purposive sampling (judgment sampling) method is not very popular in business studies, and the majority of dissertation supervisors usually do advice selecting alternative sampling methods with higher levels of reliability and low bias such as  quota ,  cluster , and  systematic  sampling methods…

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach  contains a detailed, yet simple explanation of  sampling methods . The e-book explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  research design ,  methods of data collection  and  data analysis  are explained in this e-book in simple words.

John Dudovskiy

[1] Black, K. (2010) “Business Statistics: Contemporary Decision Making” 6 th  edition, John Wiley & Sons

[2] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited

[3] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited p.288

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The use of purposeful sampling in a qualitative evidence synthesis: A worked example on sexual adjustment to a cancer trajectory

Charlotte benoot.

Mental Health and Wellbeing Research Group (MENT), Vrije Universiteit Brussel, Laarbeeklaan 103, Brussels, 1050 Belgium

Karin Hannes

Centre for Sociological Research, Catholic University of Leuven, Parkstraat 45, Leuven, 3000 Belgium

Johan Bilsen

An increasing number of qualitative evidence syntheses papers are found in health care literature. Many of these syntheses use a strictly exhaustive search strategy to collect articles, mirroring the standard template developed by major review organizations such as the Cochrane and Campbell Collaboration. The hegemonic idea behind it is that non-comprehensive samples in systematic reviews may introduce selection bias. However, exhaustive sampling in a qualitative evidence synthesis has been questioned, and a more purposeful way of sampling papers has been proposed as an alternative, although there is a lack of transparency on how these purposeful sampling strategies might be applied to a qualitative evidence synthesis. We discuss in our paper why and how we used purposeful sampling in a qualitative evidence synthesis about ‘sexual adjustment to a cancer trajectory’, by giving a worked example.

We have chosen a mixed purposeful sampling, combining three different strategies that we considered the most consistent with our research purpose: intensity sampling, maximum variation sampling and confirming/disconfirming case sampling.

The concept of purposeful sampling on the meta-level could not readily been borrowed from the logic applied in basic research projects. It also demands a considerable amount of flexibility, and is labour-intensive, which goes against the argument of many authors that using purposeful sampling provides a pragmatic solution or a short cut for researchers, compared with exhaustive sampling.

Opportunities of purposeful sampling were the possible inclusion of new perspectives to the line-of-argument and the enhancement of the theoretical diversity of the papers being included, which could make the results more conceptually aligned with the synthesis purpose.

Conclusions

This paper helps researchers to make decisions related to purposeful sampling in a more systematic and transparent way. Future research could confirm or disconfirm the hypothesis of conceptual enhancement by comparing the findings of a purposefully sampled qualitative evidence synthesis with those drawing on an exhaustive sample of the literature.

An increasing number of qualitative evidence synthesis papers are appearing in the health care literature [ 1 , 2 ]. Qualitative evidence synthesis methods have the potential to generate answers to complex questions that provide us with novel and valuable insights for theory development and clinical practice, hereby moving beyond review questions only related to the effectiveness of interventions and causation [ 3 , 4 ].

Over 20 different approaches to qualitative evidence synthesis have been developed [ 5 ]. Meta ethnography developed by Noblit and Hare (1988) is currently one of the most commonly used synthesis approaches [ 2 , 6 , 7 ]. Meta-ethnography enables a systematic and detailed understanding of how studies are related, through the comparison of findings within and across studies, ultimately providing an interpretation of the whole body of research [ 7 ]. It has known a considerable uptake in the field of healthcare [ 8 , 9 ]. Furthermore, it has the capacity to generate hypotheses for future testing or comparison with trial outcomes [ 10 ]. In our review project, we opted for a meta-ethnographic approach to synthesize findings on the sexual adjustment of cancer patients and their partners across a number of qualitative studies. It was expected that this would allow us to generate a comprehensive model to understand patients and their partners’ sexual adaptation after cancer.

We noticed that many of the meta-ethnographies published adopt a linear approach to synthesizing the literature, mirroring the standard template developed by major review organizations such as the Cochrane and Campbell Collaboration. Consequently, in most meta- ethnographic synthesis projects, a strictly exhaustive search and information retrieval strategy is used to collect data and relevant studies are assessed for quality before being included in the synthesis. The idea to work with comprehensive samples of the literature is strongly influenced by the risk of bias discourse, suggesting that non-comprehensive samples may introduce a selection bias in systematic reviews, for example [ 11 – 13 ].

However, the usefulness of the review strategy promoted by organizations such as Cochrane and Campbell, and thus of exhaustive search techniques and sampling, has been questioned by a substantial proportion of members of the qualitative research community. It has been argued that exhaustive sampling is a highly rigorous and formalistic approach that risks to be too time consuming because the searches often retrieve very large data sets that are impractical to screen [ 14 , 15 ]. Moreover, exhaustive sample risks to produce rather superficial synthesis findings, with a large number of studies that fail to go beyond the level of description [ 16 ].

Consequently, some authors are proposing a more purposeful way of sampling papers as an alternative for exhaustive sampling [ 17 ].

Purposeful sampling techniques for primary research have been well described by Patton (2002, p. 230) who has provided a definition of what purposeful sampling means [ 16 ].

“The logic and power of purposeful sampling lie in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling. Studying information-rich cases yields insights and in-depth understanding rather than empirical generalizations.”

Applied to the meta-level, purposeful sampling in a qualitative evidence synthesis has often been promoted as a solution for pragmatic constraints of time, resources, access to information and expertise [ 5 , 15 ]. However, several review authors specializing in qualitative evidence synthesis have also provided a more theoretical background to the choice for purposeful sampling. One of the core arguments supporting a purposeful sampling approach is that it is not meant to be comprehensive in terms of screening all potentially relevant papers, mainly because the interest of the authors is not in seeking a single ‘correct’ answer, but rather in examining the complexity of different conceptualizations. It follows that these types of reviews require variation to enable new conceptual understandings to be generated [ 11 , 17 , 18 ]. Booth (2011) further claims that authors of qualitative evidence syntheses are mainly concerned with ‘aiming to find sufficient cases to explore patterns and so are not necessarily attempting to be exhaustive in their searching’ [ 19 ]. To guarantee a sufficient level of conceptual richness, review directions may be divergent and iterative, rather than linear [ 20 ]. This thus contradicts the classic prospective approach of exhaustive searching [ 1 ].

Although several qualitative researchers have recommended purposeful sampling in the context of qualitative evidence synthesis, the published literature holds sparse discussion on how these strategies might be applied to a qualitative evidence synthesis [ 15 ]. Suri (2011) has made a worthwhile attempt to address this issue by examining the adaptability of the 16 purposeful sampling strategies in primary research described by Patton (2002) to the process of qualitative evidence synthesis (see Table  1 ).

Purposeful sampling strategies by Patton (2002), adapted by Suri (2011)

Despite this promising effort by Suri (2011) to theoretically present the different options of sampling for synthesis, researchers who claim to have used a purposeful sampling approach often fail to create a transparent audit trail on the review process. In addition, early pioneers such as Campbell and colleagues (2003) who explored purposeful sampling remain close to a positivist sampling strategy, opting for an arbitrary, random sampling technique to select a subset of papers to extract [ 21 ]. Noblit and Hare (1988), the initiators of the meta-ethnographic approach, introduce the idea of sampling purposefully without developing it further [ 7 ].

This indicates that there is a unilateral focus on exhaustive sampling methods, as well as a lack of transparency on how to effectively use and report on purposeful sampling techniques. Therefore, we discuss in this paper why and how we have used purposeful sampling in our qualitative evidence synthesis. The following issues will be addressed: (a) how purposeful sampling procedures have been integrated into our review procedure; (b) how this purposeful sampling has led to the development of a line-of-argument, and (c) what sort of challenges and opportunities we encountered in the instrumental outline of the procedure.

We used Suri’s (2011) description of 16 possible purposeful sampling strategies for qualitative evidence synthesis as a starting point for deciding on which type of sampling strategy we would apply in our synthesis (see Table  1 ) [ 15 ]. Suri (2011) urges authors to carefully identify sampling strategies that are conceptually aligned with the synthesis purpose, that are credible, that sufficiently address the synthesis purpose, and that are feasible, ethical and efficient.

However, we found that Suri did not offer a ‘grab and go’ option that was the perfect match for building a theoretical model, which was the aim in our qualitative evidence synthesis about sexual adjustment after cancer. Little guidance is thus available for the practical implementation of theoretical sampling. Following the example of theoretical sampling guides in primary research, we choose to see theoretical sampling as an umbrella approach, i.e. a combination of different purposeful sampling techniques [ 22 , 23 ].

We have therefore chosen a combination consisting of (a) intensity sampling at first, then a (b) maximum variation sampling and finally (c) disconfirming case sampling. This combination of sampling techniques was chosen as these aligned with the different steps of analysing towards a theoretical construct, and in accordance with Corbin and Strauss, who also connected specific sampling strategies to different types of analysing [ 24 ].

In what follows, we describe and discuss how these sampling procedures have been integrated into our review procedure. As well we describe why we used the specific sampling technique in alliance with a specific step in the analysis.

• Scoping review

Initially, we compiled a database of potentially relevant articles based on a scoping review. Scoping is an exploratory and systematic way of mapping the literature available on a topic [ 17 ]. Scoping exercises are perceived as the ideal way of doing preparatory work for an exhaustive systematic review. In our case, we have used them for building an archive of data for our qualitative evidence synthesis.

We searched 4 major databases: Medline, Psychinfo, Cinahl and Dissertation Abstracts. A search string was developed for each database with the support of a specialized team. For each database we added a methodological filter to these search strings in order to extract qualitative research articles [ 25 – 27 ]. For example, the research string we used in Medline was ((interview* or qualitative or experience*) and (cancer and sexual*). Studies included had to be written in English and be carried out between 1994 and 2014, for pragmatic reasons.

The qualitative studies retrieved were qualitative studies matched against the following inclusion criteria.

• We considered all sorts of qualitative designs. Opinion pieces and editorials were excluded. The study reports should be qualitative in nature.
• Studies should (partially) focus on the relational aspects of sexuality, namely the sexual intimacy of patient and partner, in a context of a cancer diagnosis.
• C. Type of participants

We included articles where the cancer patient and/or the partner was the unit of analysis.

First one researcher (CB) applied the inclusion and exclusion criteria to the retrieved abstracts. A full text was requested for each of the relevant studies. These studies were further assessed by the same researcher, rechecking them against the same inclusion and exclusion criteria. As can be seen in Fig.  1 , a total of 58 articles were included in our pool/archive of data.

Flow chart of the scoping review

The quality of the 58 studies was appraised using the CASP (Critical Appraisal Skills Program) tool, as this proved to be the most feasible instrument to appraise qualitative studies (Hannes, Lockwood, & Pearson, 2010). The appraisal of the quality of the research articles was not meant as an inclusion tool in scoping, but was used later on as a parameter for intensity sampling (see further).

The pool of 58 data was used to initiate purposeful sampling –i.e. (a) intensity sampling, (b) maximum variation sampling, and (c) confirming/disconfirming case sampling (see Fig.  2 ).

Overview figure of the purposeful sampling guidance

In order to prepare for the purposeful sampling phase, we constructed a standardized extraction form for each of the 58 articles to highlight the specific characteristics identified, i.e. the data collection, method, research question/goal, sampling characteristics and main theoretical arguments. By summarizing the methodological and theoretical basis of the primary studies we could easily compare the differences between studies. This facilitated our choice in purposefully sampling papers. Table  2 shows an example of a descriptive data extraction sheet of one of the studies included.

• Intensity sampling

“Intensity sampling in a research synthesis would involve selecting studies that are ‘excellent or rich examples of the phenomenon of interest, but not highly unusual cases [ 16 ]”.

Example of descriptive data extraction sheet

The reason why we chose this sampling technique as the first technique is because we believed that the starting point of the literature synthesis would influence the further analysis, so it was important to choose rich examples of the phenomenon of interest, but not highly unusual cases.

The first task was to translate the theoretical definition of intensity sampling into some concrete inclusion factors. The first factor was the degree of overlap between the research question of the article and those of the qualitative evidence synthesis, because the content of the article had to parallel the intended content of our meta-ethnography closely. The second factor was the methodological quality of the paper, evaluated by means of the CASP. High-quality articles are usually more likely to provide rich, textual accounts to draw information from [ 28 ]. A third factor we assessed was the conceptual clarity of the article [ 29 ]. Conceptual clarity means the presence and clarity of concepts for translation, and is integral to a meta-ethnography which requires clear concepts as data.

We did this intensity sampling until a “jumping off point” was reached [ 30 ]. This point is reached when the concepts and categories emerging from the papers are saturated, meaning that no new concepts are derived from reading further articles. We retrieved this jumping off point after including 6 articles (see Fig.  2 ). From that point on, we wanted to deepen the concepts further by investigating the relation between the different concepts, by means of maximum variation sampling.

• b. Maximum variation sampling

“A maximum variation sample is constructed by identifying key dimensions of variations and then finding cases that vary from each other as much as possible. This sampling yields: ‘(1) high-quality, detailed descriptions of each case, which are useful for documenting uniqueness, and (2) important shared patterns that cut across cases and derive their significance from having emerged out of heterogeneity [ 16 ].

Presuming that different study characteristics illuminate different aspects of a phenomenon, maximum variation sampling can be utilized to construct a holistic understanding of the phenomenon by synthesizing studies that differ in their study designs on several dimensions [ 15 ]. This type of sampling fits the stage of analysis as the aim is to uncover a many different key dimensions as possible.

The different concepts derived from the intensity sampling, defined the key dimensions that served as a basis for selecting additional papers. These papers vary from each other in these particular dimensions, e.g. theoretical underpinning of the articles (see further for an example of these key dimensions). Maximum variation sampling led us to the construction of a preliminary line-of-argument, after including 7 more articles (see Fig.  2 ) which was then further refined by using confirming/disconfirming case sampling.

• c. disconfirming case sampling

“The disconfirming case sampling contains a selection of articles that do not fit [ the emerging patterns]. They are a source of rival interpretations as well as a way of placing boundaries around confirmed findings” [ 15 ].

Disconfirming case sampling fits this stage of analysis, as we want to verify and deepen the preliminary line of argument.

We selected new articles based on deviant theoretical assumptions. Disconfirming articles were thus also selected through the data extraction sheets of each paper, namely by reading through the main theoretical aspects of the studies. Papers that featured theories and concepts opposing the ones we had already included in our preliminary line-of-argument were further considered for in-depth analysis. We included 3 more articles for this sampling technique, which makes the total number of included articles 16 (see Fig.  2 ).

We have now addressed how to potentially introduce purposeful sampling into a review project. However, it has been suggested that a purposeful sampling procedure is subject to a permanent dialogue with the analysis of the data [ 31 , 32 ]. In what follows, we will discuss what sort of contribution purposeful sampling has made to our findings and the model we have developed, by means of a worked example.

Results: Illustration of the purposeful sampling techniques using a worked example

In a meta-ethnography, a popular way of analysing data is the translation of the concepts or metaphors of one study into another, while preserving the structure of relationships between concepts within any given study [ 33 ]. We will thus show how we sampled different studies and how this influenced the translation exercise based on an example of three example concepts from three articles included in our review. Note that the decision to work with three concepts only was taken to increase the clarity of the procedures we describe in this paper, not to describe all the actual results and complete line-of-argument.

• First step: Arriving at a “jumping off point” through intensity sampling

We will illustrate these decisions of intensity sampling by describing the inclusion of 3 articles [ 34 – 36 ] which - according to our parameters described above - have a great degree of overlap with the research goal, a high methodological quality and strong conceptual clarity.

On the articles that were included through intensity sampling, we performed a reciprocal translation of the concepts, which is the translation of one study’s findings into another, using metaphors and overarching concepts. [ 7 ] In what follows, we give a worked example of how we did this reciprocal translation for 3 concepts identified in the initial set of studies considered for the synthesis, as this is a necessary step towards the illustration of the subsequent sampling methodology. In order to be explicit about how the concepts compared to one another, we created a table into which we placed and compared the concepts of each paper (See Table  3 ). Each row of the table represents a key concept. In the left collumn, we labelled the rows with concepts that encompassed all the relevant concepts from each paper.

Intensity sampling: Example of reciprocal translation of 3 concepts

The first concept we retrieved through intensity sampling is “sexual struggling”, encompassing the different ways of struggling with the sexual changes due to cancer. In Walker’s study (2011) it is formulated as having a sense of loss [ 35 ]. In the study of Gilbert (2013), this is formulated as patients having an altered body image [ 36 ]. In Juraskova’s study (2013) it is formulated as “reduced vaginal lubrification” [ 34 ].

Another overarching concept that we retrieved was “exacerbation of struggling”, encompassing strategies, situations, characteristics that were leading to an increasing struggling with the sexual changes. In Gilbert’s study (2013), this is formulated as “sticking to the coital imperative”, which means that intercourse is the most normal and natural form of heterosexuality, and condemns those who cannot perform as dysfunctional. In Walker’s study (2012), this is formulated as avoidance of communication about the sexual changes. In Juraskova (2003), exacerbation of struggling is the case when the patients are “ Receiving radiotherapy combined with external radiation and brachytherapy”.

A third overarching concept we found was the “sexual adjustment” to changes due to having cancer, encompassing the different ways of adaptation to sexual changes. Gilbert’s study (2010) describes that there is “a renegociation of the practices of sexual intimacy”, which means that the couple included sexual practices that had previously been marginalized in relation to sexual intercourse. Walker (2011) formulates this adjustment as “accepting the decision to stop sexuality”. Juraskove (2003) formulates it as “sexual adjustment and quality of life”.

The articles were sampled by the main author, but all articles included by intensity sampling were read and analysed by two authors (CB and MS). After a certain point which we call the “jumping off point”, we began to discover certain key dimensions of variation between the studies, which we explored further through maximum variation sampling. In the worked example that we explain here was the discovery that the studies varied on the scientific approach they took on, resulting in a different interpretation of the overarching concepts. To illustrate this: Gilbert (2010) used a social-constructionist lens to investigate sexual adjustment, Walker (2011) used a more psychological approach to investigate the subject, and Juraskova (2003) underscores more the biological aspects of sexual changes after cancer. Through the maximum variation sampling, we thus want to further explore how these different approaches lead to different interpretations of the phenomenon.

• 2. Second step: Apply a maximum variation sampling strategy to construct a preliminary line of argument

To explore the consequence of variation on the key dimension, we used maximum variation sampling to include studies that varied on the above cited dimension (i.e. scientific approach, socio-, psycho, or biological perspective). In this worked example, we show through the inclusion of three more papers [ 37 – 39 ] how we arrived – through comparison of the papers- at a preliminary line of argument.

The sampling was also done by one researcher, but the articles were read and analysed by 2 researchers. As a result of this maximum variation sampling and constant comparison between the papers, could develop relationships between the different concepts and constructing a preliminary line of argument (see Table  4 ).

Maximum variation sampling

Note 1: The discursive parts are the concepts coming from the included papers as a result of maximum variation sampling

Note 2: The bold parts are new findings resulting from maximum variation sampling

First, with regard to the concept of struggling, we found that articles who work with a psychological approach, describe the concept of struggling on an emotional level, analog with the stages of grief (anger, depression,..) while the sociological articles describe it more on a level of identity, analog with the theory of biographical disruption. Articles who have a more biological approach reduce the struggling on a level of sexual dysfunction.

Second, with regard to the concept of exacerbation of struggling, articles who work with a psychological approach again describe a stage of the grief theory, which is denial. Sociological oriented articles work with the adherence to hegemonic discourses, and biological oriented articles use certain characteristics of the cancer treatment as barriers towards adjustment.

Third, with regard to the concept of sexual adjustment, articles who are psychological oriented again use a stage of the grief theory to encompass this adjustment, which is acceptance. Sociological oriented article worked with a “rediscovery” of what sexuality is. The changes are thus not merely accepted, rather they are incorporated in a new definition of the self and sexuality. Biological oriented articles worked with “sexual recovery”, which –in contrast to the sociological oriented articles- means that there is no difference in what sexuality means , but a reuptake of sexual activity , similar to what it was before the cancer.

Our preliminary line of argument consisted of three different pathways the articles worked with. First, there are articles following the grief theory to describe the adjustment process In this case, sexual changes are depicted in terms of losses, and the adjustment occurs through the process of grief and mourning.

Second, there are articles following the “restructuring theory” during illness. Unlike the case of grief theory, where the patient and partner are working through some emotional stages, in the restructuring pathway patient and partner are more cognitively dealing with sexuality after cancer through the development of a new sexual paradigm. Flexibility is the central aspect of this adjustment.

Thirdly, there are articles following the pathway of sexual rehabilitation. This pathway is embedded in a more positivistic paradigm where the adaptation does not emphasize psychological changes or cognitive restructuring, but sexual changes as a bodily dysfunction that needs treatment and behavioural strategies.

• 3. Refining the preliminary line of argument by means of disconfirming case sample.

To test, refine, and deepening our preliminary line-of-argument, , we included 3 articles out of the pool of 58 articles that consist of a theory and concepts opposing the preliminary line-of argument. We will give an example with including 1 article (see Table  5 ).

Disconfirming case sampling

In this phase of sampling, we worked together with a researcher who was not involved in the analysis process before (JB). This is because we wanted to have a fresh and “unambiguous view” of our line of argument. This researcher, together with the first researcher, read the articles and tested them against the line of argument.

In our preliminary line-of-argument, we assumed that the three pathways of adjustment all followed a linear pattern from the struggling towards the adjustment. However, Ramirez (2009) counter argues this linear approach by stating that patients could refine their definition of sexuality, but could also return to it at a certain moment [ 40 ]. These disconfirming findings led us to re-analyse the included articles, where we came eventually to the conclusion that the sexual adjustment as a cognitive restructuring process does not have a linear pattern with an endpoint, but rather makes on oscillating movement between following hegemonic definitions of sexuality, and challenging them.

• 4. Challenges and opportunities

In the process of conducting a qualitative evidence synthesis through purposeful sampling, we encountered several challenges. But this process also created a few opportunities that would not have occurred if we had used an exhaustive sampling and analysis strategy. In what follows, we discuss how we have bridged obstacles and maximized benefits in terms of the opportunities arising.

First, it proved to be difficult to define what exactly to look for, since the concept of e.g. an intensity sample on the meta-level could not readily been borrowed from the logic applied in basic research projects. In an original research project, as opposed to a qualitative evidence synthesis project, purposeful sampling can often easily be conducted, for example by using a brief questionnaire as a screening tool to search for participants with specific characteristics [ 41 ]. However, with research reports, this is more difficult in practice. We chose to search for literature by means of electronic databases with the use of search strings. Finding a specific search string to detect a specific information-rich research report which meets the sampling criteria would be difficult, because the search terms are usually based on population and setting characteristics as well as the topic of interest, rather than on conceptual or theoretically interesting leads.

Therefore we decided to conduct a scoping of the literature prior to applying a purposeful sampling technique. The scoping review was intended to create a pool/or archive of primary research reports that are easily accessible and can be used later as material for purposeful sampling. In fact, our purposeful sampling strategy did not start at the level of data-collection. It was initiated at the level of data extraction and analysis. The consequence of this decision was that the sampling procedure was rather labour-intensive as we had to perform a scoping review before the actual mixed purposeful sampling could start.

We illustrated through our worked example that using purposeful sampling techniques also has several advantages.

First of all, although some researchers argued that reducing the number of included articles by means of purposeful sampling could result in neglecting important data [ 18 , 42 ], we showed throughout this worked example that the opposite can be true. With the use of this combination of three purposeful sampling techniques – intensity sampling, maximum variation sampling and confirming/disconfirming case sampling - we arrived at a line-of-argument.

Because of this emphasis on conceptual robustness instead of generalization of the data, we were more sensitive to “deviant data”, i.e. data that may not have been picked up when synthesizing information from an exhaustive sample of the literature, because review authors are generally more focused on detecting commonalities between articles. When using an exhaustive sampling technique, researchers will arrive at results that describe the “greatest common devisor” of all included papers.

Furthermore, deviant data that has been derived through maximum variation sampling and confirming/disconfirming case sampling may add new perspectives or a new space of understanding to the line-of-argument, while sampling randomly may run the risk of preventing enhanced insight and knowledge.

Moreover, the combination of sampling techniques – instead of a random sample or just one method of purposeful sampling- could enhance the quality and diversity of the papers being included, and could make the results more conceptually aligned with the synthesis purpose. This would further enhance the possible impact a qualitative evidence synthesis could have on informing healthcare practice [ 43 ].

Such an approach, however, demands a considerable amount of flexibility from review authors, mainly because inclusion criteria may change progressively during the process. This fact, together with the experience described above of doing a labour-intensive scope of the literature, goes against the argument of many authors [ 5 ] that using purposeful sampling provides a pragmatic solution or a short cut for reviewers who have limited time for searching and screening. However, we felt we did gain some time in the analytical process, since the number of articles from which data were extracted was modest in number. This strategy is therefore recommended for authors who are left with a high number of relevant articles after screening for inclusion.

However, the choice of using this particular combination of sampling techniques should also be motivated from a theoretical perspective. Authors who want to build a theoretical model out of the qualitative evidence synthesis could use this scheme of sampling methods, as it aligns well with the different stages of analysis, and is parallel to what Corbin and Strauss suggested for primary research [ 24 ].

In this paper, we addressed two different needs:

Firstly, we met the need for a transparent worked example of how to apply purposeful sampling techniques to a qualitative evidence synthesis. We believe that this paper can help other researchers to make decisions related to purposeful sampling in a more systematic and transparent way.

Secondly, we gave evidence for the beneficial effects of using purposeful sampling techniques in a qualitative evidence synthesis. Although purposeful sampling is a time-consuming activity that requires a lot of resources and flexibility from the researchers, it creates potential to arrive at a rich conceptual model that can be useful for clinical practice. Future research could confirm or disconfirm the hypothesis of conceptual enhancement by comparing the findings of a purposefully sampled qualitative evidence synthesis with those drawing on an exhaustive sample of the literature.

Acknowledgements

We would like to thank Drs. Marlies Saelaert for making substantial contributions to the analysis and interpretation of the data of our meta-synthesis. We also would like to acknowledge the Flemish fund for Scientific research (FWO) for financially supporting this study.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

CB carried out the qualitative evidence synthesis and wrote the first draft. KH guided the philosophic discussion that contributed to the methodological development of the paper. JB conceived of the study, participated in its design and helped to draft the manuscript. All authors read and approved the final manuscript.

Contributor Information

Charlotte Benoot, Email: eb.ca.buv@toonebc .

Karin Hannes, Email: [email protected] .

Johan Bilsen, Email: eb.ca.buv@toonebc .

• Open access
• Published: 08 April 2024

Patient and pharmacist perspectives on opioid misuse screening and brief interventions in community pharmacies

• Deepika Rao   ORCID: orcid.org/0000-0003-2927-7639 1 , 2 ,
• James H. Ford 1 &
• Olayinka O. Shiyanbola 1  

Addiction Science & Clinical Practice volume  19 , Article number:  27 ( 2024 ) Cite this article

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Metrics details

Pharmacy-based screening and brief interventions (SBI) offer opportunities to identify opioid misuse and opioid safety risks and provide brief interventions that do not overly burden pharmacists. Currently, such interventions are being developed without patient input and in-depth contextual data and insufficient translation into practice. The purpose of this study is to qualitatively explore and compare patient and pharmacist perceptions and needs regarding a pharmacy-based opioid misuse SBI and to identify relevant SBI features and future implementation strategies.

Using the Consolidated Framework for Implementation Research, we conducted semi-structured interviews with 8 patients and 11 pharmacists, to explore needs and barriers to participating in a pharmacy-based SBI. We recruited a purposive sample of English-speaking patients prescribed opioids for chronic or acute pain and pharmacists practicing in varied pharmacies (small independent, large-chain, specialty retail) settings. We used an inductive content analysis approach to analyze patient interview data. Then through a template analysis approach involving comparison of pharmacist and patient themes, we developed strategies for SBI implementation.

Most patient participants were white, older, described living in suburban areas, and were long-term opioid users. We identified template themes related to individual, interpersonal, intervention, and implementation factors and inferred applications for SBI design or potential SBI implementation strategies. We found that patients needed education on opioid safety and general opioid use, regardless of opioid use behaviors. Pharmacists described needing patient-centered training, protocols, and scripts to provide SBI. A short-self-reported screening and brief interventions including counseling, naloxone, and involving prescribers were discussed by both groups.

Conclusions

Through this implementation-focused qualitative study, we identified patient needs such as opioid safety education delivered in a private and convenient format and pharmacist needs including training, workflow integration, protocols, and a time-efficient intervention for effective pharmacy-based SBI. Alternate formats of SBI using digital health technologies may be needed for effective implementation. Our findings can be used to develop patient-centered pharmacy-based SBI that can be implemented within actual pharmacy practice.

Introduction

Although opioid prescribing rates are decreasing, 16,706 overdose deaths involving a prescription opioid occurred in 2021 in the United States, a trend driven by combination with synthetic opioids such as fentanyl [ 1 ]. To take preventative actions to reduce overdose deaths and the risk of developing an opioid use disorder (OUD), healthcare professionals must recognize opioid misuse behaviors early. Efforts to address opioid misuse must not lead to inadequate pain management, especially among groups that receive disproportionately fewer opioid prescriptions, such as African American adults [ 2 ]. These issues can be addressed by leveraging community pharmacists who are highly accessible healthcare professionals, especially in rural areas with underinsured patients. Pharmacists have training in medication counseling, believe that screening for opioid misuse is important, and are interested in providing screening interventions [ 3 , 4 ]. However, patients are not screened for opioid misuse behaviors when picking up their prescription opioids at the pharmacy. In the US, the role of the community pharmacist in OUD prevention and treatment has been mostly limited to dispensing medications for OUD and even then not at optimal levels [ 5 ]. There is a need to expand the role of the pharmacist in providing prevention interventions for OUD.

Nationally, calls to leverage community pharmacists as a resource in all types of OUD prevention, including screening and brief interventions (SBI), have increased [ 6 ]. Screening using prescription drug monitoring programs (PDMP) [ 7 , 8 ] and brief interventions such as naloxone dispensing [ 9 , 10 ] or opioid counseling [ 11 ] have been studied in pharmacy settings, but are rarely incorporated into one comprehensive SBI model [ 12 ]. Using a comprehensive SBI model to implement the interventions would increase their effectiveness and be more patient-centered. However, issues such as lack of clinical information and discomfort in talking to patients can act as intervention barriers [ 13 ].

We conducted a scoping review of pharmacy-based opioid misuse SBI and identified a few pilot-stage interventions and exploratory observational studies on this topic as well as two main research gaps [ 14 ]. While pharmacists were surveyed in development of these SBI, patient perspectives were not explored. Issues regarding private space, stigma, and method (in-person or digital) of the intervention as well as comfort with a pharmacist providing such interventions, all of which can impact SBI effectiveness, were not studied [ 14 ]. Patient-centered interventions that include individual patient preferences and values are holistic, respect patient’s autonomy, and empower them to make decisions about their own care [ 15 ]. Using a patient-centered approach to SBI development begins with exploring patient preferences and needs regarding participation. Our review also identified five qualitative studies that explored pharmacist perspectives regarding opioid misuse SBI but only one of the five studies had high credibility and trustworthiness [ 14 ]. There is a lack of in-depth, contextual information about pharmacist and patient perspectives of SBI, which is a significant limitation in development of effective interventions. Conducting qualitative exploration as the first step to designing the pharmacy-based opioid misuse SBI would help overcome this drawback.

To improve translation of SBI research into practice, it is useful to consider future implementation barriers at the design stage itself. The ‘designing for dissemination’ principles identify key actions in the process of designing interventions and the subsequent products [ 16 ]. These actions include engaging key stakeholders as early as possible, using implementation frameworks and dissemination constructs, documenting implementation barriers and outcomes [ 16 ]. Utilizing designing for dissemination and implementation principles at the development stage allows for more context-relevant interventions that addresses stakeholder needs and priorities.

The purpose of this study is to qualitatively explore and compare patient and pharmacist perceptions and needs regarding a pharmacy-based opioid misuse SBI and to identify relevant SBI features and future implementation strategies.

Consolidated framework for implementation research (CFIR)

The constructs under the CFIR domains that were appropriate for intervention design have been bolded (Additional file 1 ). The CFIR interview guide [ 17 ] was used to develop specific interview questions and the accompanying codebook template was used for initial deductive coding of interview data.

Study sample

Generally, 10–25 participants are considered sufficient for theory/model based qualitative studies using content analysis approaches [ 18 , 19 ]. Our interviews had higher information power gained by sample specificity (purposive sampling [ 20 ] by targeting different pharmacy experiences and pain conditions rather than convenience sampling), using an applied conceptual framework (CFIR), the strong quality of dialogue (lengthy, in-depth interviews), and the exploratory nature of analysis (identifying patterns/themes rather than in-depth phenomenological description) [ 19 ]. Thus, interviews were conducted until data saturation was achieved, i.e. no new dimensions regarding the topic emerged [ 21 ] We conducted interviews with a purposive sample of adult, English speaking patients, living in a Midwestern state, who have been prescribed an opioid medication at least once in their lifetime for acute or chronic non-cancer pain. Patients diagnosed with an OUD, receiving opioids for cancer-related pain, or unable to participate in the interview (hospitalized, in hospice care, suffering from debilitating pain) were excluded from the sample. A purposive sample of English-speaking community pharmacists (those practicing in a non-clinical, community setting such as large national chain pharmacies, independent pharmacies, or specialty pharmacies) practicing in the same Midwestern state were included in the sample.

Data collection

For patients, recruitment initially occurred through regional pain clinics and primary care providers. To increase recruitment of individuals using in-person pharmacy services, pharmacists who completed study interviews were also asked to share study information with their patients. A study flyer describing interview procedures and other study information was sent to healthcare professionals to share with eligible patients. We briefed the healthcare professionals on the study purpose (i.e. exploring patient perspectives on SBI) and the larger goal of our research (i.e. designing a patient-centered opioid misuse SBI for pharmacy settings). We asked healthcare professionals to purposefully select individuals who may be good candidates for SBI. To recruit individuals with acute pain, we used the emergency department research coordinators. Patients were given the option to contact the study team themselves or allow their contact information to be shared with the study team. Pharmacists were recruited through emails sent to a practice-based research network and an informal list curated by the study team. Emails included study information and a screening and a contact information form.

Eligible and interested patients and pharmacists were contacted to schedule interviews conducted via telephone, web-conferencing software, or in-person. The lead researcher (DR) with training and prior experience in qualitative methods conducted all the interviews. Verbal informed consent was solicited prior to beginning the interview. The patient interviews were 30 min long and pharmacist interviews were 60-min long. Patients received $30 compensation and pharmacists received $50 compensation for completing interviews. All interviews were audio-recorded and transcribed, and transcriptions were used for further data analysis. The patient interviews focused on patient experiences in pharmacy and needs regarding their opioid medications in addition to the more SBI-specific questions. The pharmacist interviews were longer to accommodate additional questions focused on characteristics of their particular setting not directly related to patient care such as: organization goals and feedback, colleague networks and communication, and workplace culture. These data have been reported separately [ 22 ]. The interview guides were piloted in the first couple of interviews and probing questions were added as appropriate (ex. opioid experiences for patients, OUD prevention experiences for pharmacists). Patients were also prompted with examples of different types of interventions that pharmacists could potentially provide within the SBI model to generate richer discussions. The sample interview questions linked to the CFIR constructs for both pharmacists and patients are provided in Additional file 2 . The Institutional Review Board at the author’s institution approved the study procedures after expedited review.

Data analysis

While a deductive analysis approach (based on CFIR) was planned initially, it was not suitable for the patient interview data as very little information could be coded using the CFIR constructs. Therefore, an inductive open coding approach was utilized for patient interviews. Two coders independently coded each interview transcript and discussed their coding in detail with DR as primary analyst and an undergraduate student as a secondary coder. Any conflicts in the coding were resolved at this stage. Finally, DR abstracted all categories into themes. Following content analysis of the patient interview data, a template approach was utilized to compare data from the patient and pharmacist interviews. The template was created based on the patient interviews first by listing the major themes resulting from the content analysis. Then pharmacist transcripts were analyzed using this template as the coding structure. Then, salient quotes from the two groups corresponding to the template themes were included in a matrix. This matrix was used to make comparisons and meta-inferences regarding pharmacists and patient perceptions of the SBI as well as report findings. Opposing views regarding the same themes across the two groups were also presented in the matrix. MAXQDA software was used for all qualitative analyses. DR created the template, conducted the analysis, and produced the matrix independently. Two researchers (OS, JF) who were not involved in the data collection process reviewed the final matrix to improve credibility and trustworthiness of the findings.

Qualitative rigor was achieved by establishing credibility and confirmability through purposive sampling [ 20 ], achieving data saturation [ 21 ], using multiple coders for analysis (analyst triangulation), template analysis with patient and pharmacist data (triangulation of data sources), and peer debriefing [ 23 ]. The ‘Consolidated Criteria for Reporting Qualitative Studies (COREQ)’ checklist [ 24 ] has been completed for this study (Additional file 3 ).

Sample characteristics

Eight semi-structured interviews were completed from May to October of 2021 virtually, over the phone, or face-to-face with patients taking opioid medications for non-cancer related acute (n = 2) or chronic (n = 6) pain. Patients used in-person pharmacy services, mail order, or drive through pharmacy services for their opioid medications. Most patient participants were white, older, and described living in suburban areas. Both men and women were recruited in the sample. Participants with chronic pain had used opioids consistently for 5–30 years, while participants with acute pain had used opioids after surgeries in the past 5 years. All participants were taking a combination of short -acting and long-acting opioids. While we did not ask participants to report opioid misuse behaviors directly, our recruitment method through healthcare professionals resulted in inclusion of individuals who had high opioid safety risks such as: requests for higher doses due to tolerance, development of hyperalgesia, family history of substance use disorders, possession of large quantities of unused opioids, and fills of prescriptions at different pharmacies. Eleven pharmacist interviews were completed from March to August of 2021 virtually. Pharmacists practiced in a variety of settings (large-chain, small independent, specialty) and roles (manager, owner, full-time, part-time pharmacist).

Template analysis findings

The results of the template analysis are presented in Table  1 . The template consists of 14 themes including individual factors such as experiences with opioids/care, knowledge, beliefs, needs, and self-efficacy interpersonal factors such as stigma and patient- pharmacist-provider relationships, intervention factors that describe beliefs and views on intervention components, and implementation factors such as implementation needs and challenges. The template themes, summaries of the themes from patient and pharmacists interviews, exemplar quotes, and our interpretations for applications to future SBI design and potential implementation strategies are included in Table  1 .

Summary of results

Overall, we identified the following key findings related to individual, interpersonal, intervention, and implementation factors.

Individual factors

Experience with Opioids/Care: While providers used clinical judgement to taper opioids, patients did not trust them and perceived it as an access barrier to medications. Pharmacists were aware of these issues and tried providing education and counseling to patients. These findings indicate that patients may perceive SBI as another barrier to accessing medications rather than an opportunity to receive education about opioid use and safety.

Knowledge about Opioid safety: Patients had large knowledge gaps regarding opioid use (especially long-term use), opioid dependence, and opioid safety and the only directions given to them were to ‘take as prescribed’. Pharmacists were aware of these gaps and believed patient counseling would help. Therefore, patient education on chronic opioid use and opioid safety are important for the design of brief interventions (BI).

Beliefs about Opioid Safety and OUD: Patients believed that they were not at risk of opioid misuse, overdose, or developing OUD because it occurred among people who used opioids recreationally only. Pharmacists described these beliefs as barriers to opioid safety and naloxone dispensing. Addressing such common misperceptions and beliefs should be part of SBI design.

Opioid Care Needs: Patients discussed needs including recognizing tolerance, dependence, consequences of intentional and unintended misuse, non-opioid alternatives, managing an accidental overdose, and contra-indicated substances. Pharmacists suggested additional topics including pain management expectations and risk of addiction or accidental overdose, especially in patients who are older, are co-prescribed other medications, or have co-morbid conditions. Pharmacists also believed BI could help deliver this much-needed education. This indicates that BI could be beneficial to patients regardless of opioid misuse behaviors if education on long-term opioid use is included.

Self-efficacy: Patients’ confidence in taking opioids safely due to many years of experience made them reluctant to participate in SBI, indicating that SBI may be ideally delivered at index prescription. While pharmacists agreed with this, they had higher self-efficacy in providing SBI for established patients than new patients.

Interpersonal factors

Stigma: While only some pharmacists described being biased towards patients using opioids, most patients perceived stigma from healthcare professionals including pharmacists. This is huge barrier to potential SBI participation. Patient centered education and anti-bias training to address stigma against OUD may be necessary for pharmacists.

Patient-Pharmacist-Prescriber Relationships: Patients used informal sources such as the internet for medication questions or talked to prescribers rather than pharmacists who were not viewed as clinical healthcare providers. Some pharmacists had reservations about counselling patients. Pharmacists in our sample indicated they needed training. To overcome these role perceptions, marketing SBI as a clinical service is a potential implementation strategy that will need to be tested in future research.

Intervention factors

Beliefs about SBI: Despite the interpersonal challenges discussed above, patients were interested in pharmacy based SBI as long as it was focused on patient autonomy. While all patients found a short screening acceptable, some patients stated that individuals may not self-report opioid misuse. Their motivation to participate was primarily to obtain education about opioid use and safety. Pharmacists believed SBI would be helpful but were wary of stigmatizing the patients. Pharmacists described needing training and a protocol to provide SBI such that the interventions are integrated into routine care. They also suggested introducing SBI as personalized clinical care.

Screening Component: Both groups recommended short (< 5 min), standardized, self-reported screening and discussed potential screening formats such as online, in-person, or telephonic methods. Pharmacists also suggested using pharmacy technicians to help conduct the screening. However, feasibility perceptions among pharmacists and patient preferences for these methods varied.

Brief Intervention Components: Naloxone dispensing, patient counseling, and contacting prescribers (with non-stigmatizing scripts, handouts, and protocols) were discussed as potential BI.

Implementation factors

Implementation Needs: Patients wanted SBI implemented in a manner that offered privacy and autonomy. Multiple formats of SBI may be needed to offer patients the individualized service they are seeking. Pharmacists needed training and protocols that fit within workflow. If contacting prescribers were part of SBI, pharmacists suggested engaging prescribers as stakeholders.

Implementation Challenges: Three potential implementation challenges that were discussed included time, stigma, and pharmacist roles. Both patients and pharmacists were interested in an intervention no longer than 15 min. Alternate formats and using technicians may help reduce time burden. Offering SBI in a private space where available, integrating SBI into telehealth services, or using digital health technologies could potentially provide privacy and reduce perceived stigma. Marketing SBI as a clinical service provided by pharmacists and involving prescribers as stakeholders may help address pharmacist role challenges.

Our study is an initial exploration of pharmacist and patient needs regarding opioid misuse SBI for pharmacy settings. A short-self-reported screening and brief interventions including counseling, naloxone, and involving prescribers were discussed by both groups. We found that patients needed education on opioid safety and general opioid use in a private and convenient format, regardless of opioid use behaviors. Pharmacists described needing patient-centered training, protocols, and scripts to increase comfort in providing SBI. Through this qualitative study, we have obtained critical stakeholder data that can be used to design SBI in future research.

Patients in our sample had long-term experience with opioids, with issues related to medication access. This is similar to other study findings that show recent opioid prescribing guidelines [ 25 ] may have led to inadequate pain management [ 2 ]. Patients in our study did not trust healthcare professionals when they discussed opioid tapering. Research suggests that lack of trust in healthcare professionals does not promote optimal pain care [ 26 ] and may be exacerbated by prevention interventions that are not patient-centered and focus solely on reducing prescribing rates [ 27 ]. These are important considerations for future SBI design.

Despite their long-term experience taking opioids, there was a severe lack of knowledge regarding opioid safety among patients, with ‘take as prescribed’ being the only direction provided to them. Patients reported using informal and unverified sources of information such as the internet or other patients. Research indicates that this lack of opioid safety knowledge, especially related to overdose risks and naloxone, is very common among patients with chronic pain [ 28 , 29 ]. As most harm reduction efforts are targeted towards people using illicit drugs, patients using prescribed opioids may have lower knowledge regarding opioid safety [ 30 ]. These findings indicate that patient education, irrespective of opioid misuse behaviors, is important for future SBI design.

Beliefs such as not being at risk of opioid misuse, overdose, or developing OUD were also very common. Pharmacists believed this led to patients practicing risky behaviors such as storing large quantities of opioids and refusing naloxone. Research suggests that individuals who believe that opioid addiction risk is personally irrelevant have a higher risk of opioid misuse [ 31 ]. However, patients in our sample were comfortable with pharmacists providing information about opioid safety as part of SBI, if done in a non-stigmatizing manner.

Patients described needing education on long-term opioid use and recognizing opioid dependence along with patient-centered opioid safety knowledge. These needs could be met as part of patient-centered counseling (BI), ideally at index prescription when patients may be most receptive. A recent web-based digital intervention that met some of these needs increased patient knowledge and was rated as highly acceptable by patients [ 32 ].

Most patients described being stigmatized by healthcare professionals, including pharmacists when accessing opioid medications. Although few pharmacists openly discussed having bias towards patients in our interviews, many mentioned concerns about coming across as stigmatizing. Research indicates that pharmacists commonly distance themselves from patients who misuse opioids and hesitate to form therapeutic relationships with them [ 33 ]. While all patients were comfortable with the pharmacist providing opioid related information, very few had the experience of receiving patient-centered counseling regarding opioid safety. Research suggests that stigma is a barrier to participation in opioid-related interventions for both groups because patients are wary of feeling interrogated or labeled, and pharmacists are wary of making patients uncomfortable [ 34 ]. Pharmacists may require anti-bias training and patient-centered education. Such trainings have been shown to increase pharmacist knowledge about opioid misuse and decrease stigma [ 35 ]. Packaging SBI as a value added clinical service for all patients taking opioids may also help improve the patient-pharmacist interaction. Future studies should evaluate these strategies to design effective SBI.

Both groups were comfortable with a short self-reported screening tool, in addition to routine practice (using PDMP and technician help). This model that has been studied previously [ 36 ], where standardized tools such as the Prescription Opioid Misuse Index, [ 36 , 37 ] the Opioid Risk Tool [ 38 , 39 , 40 , 41 ], or the Routine Opioid Outcome Monitoring tool [ 42 , 43 ] were used. These studies also show promising potential for effectiveness of pharmacy-based SBI for opioids. Both groups also expressed support for pharmacy-based SBI focused on patient education regarding both opioid safety as well as general chronic opioid use, regardless of misuse behaviors. Since most opioid safety initiatives are not designed to be universal prevention [ 30 ], such SBI could potentially fill the gap in a patient population that is often overlooked. However, in busy large-chain pharmacies or those without private space, alternate formats of counseling such as telephone-based, telehealth, or digital applications may be more feasible and acceptable [ 44 , 45 ].

Participants also discussed naloxone and contacting prescribers as potential brief interventions. A recent pharmacy-based SBI has found some success in increasing naloxone uptake [ 38 , 39 , 40 , 41 ]. However, pharmacists may need non-stigmatizing scripts focused on patient autonomy [ 46 ]. While pharmacists contacting prescribers could potentially reduce inappropriate prescriptions, research indicates that prescriber-pharmacist relationships and communication are often tense, ineffective, and a barrier to improving pharmacist roles in OUD prevention and treatment [ 47 , 48 ]. Pharmacists in our study suggested that stakeholder engagement with prescribers to ensure their support of SBI may be needed.

Patients described needing a SBI delivery format that offers privacy and autonomy. Pharmacists needed a protocol and training to be able to efficiently provide SBI. Lack of time, role limitations, and stigma/privacy were the main implementation challenges. Research suggests that these role limitations hamper pharmacists’ self-efficacy in providing opioid safety services [ 13 ]. These challenges could potentially be overcome by offering alternative formats such as digital SBI, training pharmacists, fitting intervention within pharmacy workflows, and marketing SBI as a clinical service. Such strategies can be included in designing SBI in future research.

This study has some limitations. Patient interviews were conducted with a sample diverse in terms of pain chronicity and pharmacy experience but most patients were white, had insurance, and lived in suburban areas. As health disparities regarding opioids and OUD treatment are common in racial and ethnic minority groups, underinsured, and more rural populations, involving patients from these groups could lead to different themes. Therefore, findings from the patient interviews cannot be transferred to all patients using opioids. Future research should focus on engaging these groups individually and developing SBI that target their specific needs rather than a one-size-fits-all approach. Our study focused only on the screening and brief intervention portion of the SBIRT model. Referral to treatment is an important component that was not explored thoroughly in our study.

In this implementation-focused qualitative study comparing patient and pharmacist views on opioid misuse SBI, we found that patients needed education on opioid safety and general opioid use, regardless of misuse behaviors. Pharmacists described the need for patient-centered training, protocols, and scripts to provide SBI. A short-self-reported screening and brief interventions including counseling, naloxone, and involving prescribers were discussed by both groups. Alternate formats of SBI using digital health technologies may be needed for effective design and implementation.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Acknowledgements

We would like to thank Meg Mercy and Christine McAttee for helping with data analysis. This study was conducted in collaboration with the Pharmacy Practice Enhancement and Action Research Link (PearlRx) of Wisconsin, a statewide pharmacist practice-based research network which is in part supported by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR002373, the UW School of Medicine and Public Health from the Wisconsin Partnership Program, and the Pharmacy Society of Wisconsin.

This work was funded by Sonderegger Research Center for Improved Medication Outcomes. DR also received the Joseph B. Wiederholt Fellowship, 2021 to support this project. Supporting organizations had no further role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

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DR originated the project and obtained funding with the support of OS and JF. DR led data collection and analysis and drafted the initial manuscript. All authors participated in interpreting the results, contributed to the writing of the manuscript, provided critical feedback to the manuscript, and approved the final manuscript draft for submission.

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Supplementary Information

Additional file 1:.

CFIR Constructs.

Additional file 2:

Sample interview questions.

Additional file 3:

COREQ Checklist.

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Rao, D., Ford, J.H. & Shiyanbola, O.O. Patient and pharmacist perspectives on opioid misuse screening and brief interventions in community pharmacies. Addict Sci Clin Pract 19 , 27 (2024). https://doi.org/10.1186/s13722-024-00460-y

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Non-probability sampling ; Theoretical sampling

Purposive sampling is intentional selection of informants based on their ability to elucidate a specific theme, concept, or phenomenon.

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As utilized in qualitative and mixed methods research, purposive sampling involves an iterative process of selecting research subjects rather than starting with a predetermined sampling frame . Akin to grounded theory, the selection process involves identifying themes, concepts, and indicators through observation and reflection (Schutt, 2006 : 348). Schutt places particular emphasis on the importance of each sampling element occupying a unique position relative to the research endeavor (2006: 155). Along these lines, researchers often utilize a purposeful sampling technique to select informants based on their particular knowledge of, and/or experience with, the focus of empirical inquiry.

Purposive sampling is a sampling design that is not intended to offer a representative...

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Robinson, R.S. (2014). Purposive Sampling. In: Michalos, A.C. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0753-5_2337

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• Published: 11 April 2024

Barriers and facilitators to care for agitation and/or aggression among persons living with dementia in long-term care

• Britney Wong 1 , 2 ,
• Zahinoor Ismail 2 , 3 , 4 , 5 ,
• Jennifer Watt 6 , 7 ,
• Jayna Holroyd-Leduc 1 , 8 &
• Zahra Goodarzi 1 , 8 , 9 , 2 , 3  

BMC Geriatrics volume  24 , Article number:  330 ( 2024 ) Cite this article

Metrics details

Agitation and/or aggression affect up to 60% of persons living with dementia in long-term care (LTC). It can be treated via non-pharmacological and pharmacological interventions, but the former are underused in clinical practice. In the literature, there is currently a lack of understanding of the challenges to caring for agitation and/or aggression among persons living with dementia in LTC. This study assesses what barriers and facilitators across the spectrum of care exist for agitation and/or aggression among people with dementia in LTC across stakeholder groups.

This was a qualitative study that used semi-structured interviews among persons involved in the care and/or planning of care for people with dementia in LTC. Participants were recruited via purposive and snowball sampling, with the assistance of four owner-operator models. Interviews were guided by the Theoretical Domains Framework and transcribed and analyzed using Framework Analysis.

Eighteen interviews were conducted across 5 stakeholder groups. Key identified barriers were a lack of agitation and/or aggression diagnostic measures, limited training for managing agitation and/or aggression in LTC, an overuse of physical and chemical restraints, and an underuse of non-pharmacological interventions. Facilitators included using an interdisciplinary team to deliver care and having competent and trained healthcare providers to administer non-pharmacological interventions.

Conclusions

This study advances care for persons living with dementia in LTC by drawing attention to unique and systemic barriers present across local and national Canadian LTC facilities. Findings will support future implementation research endeavours to eliminate these identified barriers across the spectrum of care, thus improving care outcomes among people with dementia in LTC.

Peer Review reports

Up to 60% of persons living with dementia (PLWD) in LTC experience agitation and/or aggression symptoms, with the prevalence varying based on dementia pathology and severity [ 1 ]. Although agitation and aggression are separate constructs, they are often presented together among PLWD in LTC [ 2 ]. Agitation consist of three main domains outlined by the International Psychogeriatric Association criteria for Agitation in Cognitive Disorders: 1) excessive motor activity, 2) verbal aggression, and 3) physical aggression [ 3 ]. Aggression refers to verbal and physical behaviours (e.g. hitting, throwing, etc.) that are highly likely to cause harm among the resident and others [ 4 , 5 , 6 ]. Agitation and/or aggression can adversely impact residents’ quality of life by increasing the likelihood of falls, fractures, and developing additional neuropsychiatric symptoms, as well as increasing the cost of care and the rate of institutionalization [ 1 , 7 ]. Corresponding caregivers often experience increased burnout, lower job satisfaction, stress, and worse psychological health [ 8 ]. Given the burden that agitation and/or aggression have among PLWD in LTC and their caregivers, more emphasis is needed on treatment strategies.

Agitation and/or aggression can be treated via either pharmacological (drug) or non-pharmacological (non-drug) interventions. The former consists of psychotropic medications, such as antipsychotics (e.g. risperidone or olanzapine) or antidepressants (e.g. citalopram). However, psychotropic medications can lead to adverse side effects including stroke and decreased cognitive function [ 9 , 10 ]. For example, antipsychotics confer a higher risk of adverse events, such as falls, fractures and deaths [ 11 ]. Moreover, the efficacy of psychotropic medications to alleviate agitation symptoms is contested [ 9 ]. In comparison, non-pharmacological approaches include sensory practices (e.g., aromatherapy), psychosocial practices (e.g., validation therapy), and structured care protocols (e.g., bathing) [ 12 ]. Non-pharmacological approaches are considered first-line treatment strategies to address agitation among PLWD because they confer less side effects and are efficacious [ 13 ]. For example, Watt et al. (2019) ranked outdoor activities as highest in efficacy to address combined aggression and agitation, along with physical aggression independently [ 11 ]. Despite this knowledge, non-pharmacological treatment approaches are under-used in clinical practice [ 9 ].

Many challenges exist to managing agitation and/or aggression in LTC, but prior qualitative studies focus on understanding only nursing and physician perspectives, and lack qualitative perspective on the care needs of PLWD experiencing agitation and/or aggression [ 9 , 14 ]. As such, there is a lack of understanding on the perceived barriers and facilitators to care for other key stakeholders involved in the care and/or planning of care for PLWD in LTC (e.g., patients, families, allied healthcare workers, etc.). The purpose of this study is to assess what barriers and facilitators to care exist for agitation and/or aggression among PLWD in LTC centres, as perceived by all key stakeholder groups.

Ethics approval was acquired through the Conjoint Health Research Ethics Board (REB-22–1100), and permission was granted from all organizations.

Participants

The sampling frame consisted of persons involved in the care or planning of care of PLWD in LTC. Specifically: (1) physicians (e.g., family doctors, psychiatrists, and geriatricians), (2) nurse practitioners, (3) administrators and decision makers, (4) nursing staff (e.g., registered nurses, licensed practical nurses), (5) allied healthcare workers (e.g., recreational therapists, occupational therapists, physiotherapists, social workers), (6) care aides, and (7) LTC residents and family members. Participants were all 18 years or older, and English-speaking. No other restrictions were used.

Participant recruitment

Rolling, snowball and purposive sampling of participants were used, with the latter ensuring representation of diverse sex, gender, race/ethnicity, and urban/rural perspectives. We recruited persons working across healthcare disciplines (e.g., physicians, nurses, allied healthcare workers, etc.). 70% of the total resident population, and an estimated 89% of care staff, are female in LTC [ 15 , 16 ]. Therefore, to ensure fair representation, male participants were purposively recruited across all disciplines [ 15 ]. Participants were recruited from urban, suburban and rural sites to increase understanding of the organizational differences and similarities between geographical regions.

Recruitment posters and email advertisements were sent out across four local LTC facilities. The study team further recruited participants via our own networks. To ensure representation at a national level, advertisements were posted to social media platforms (e.g., Twitter). Lastly, persons who consented to participate in a previous Delphi panel study developing a novel care pathway for agitation and/or aggression among PLWD in LTC could also consent to being contacted about participating in a semi-structured interview [ 17 ]. In the Delphi study, panelists were recruited to complete several rounds of a Delphi survey to create a clinical care pathway suitable for the identification, diagnosis, and management of agitation and/or aggression symptoms among PLWD in LTC [ 17 ]. Panelists were recruited via the same 4 LTC centres via purposive and snowball sampling using poster and email advertisements [ 17 ]. They were also recruited via research team contacts and networks [ 17 ].

Semi-structured interviews (45 to 60 min) were conducted one-on-one with participants until thematic saturation was reached. No compensations were offered to participants of the study.

Data collection, storage and management

Interviews occurred online using a password-protected meeting using the platform “Zoom” in a confidential environment. Participants’ personal information was not shared outside of the research team. All interviews were conducted, transcribed, and verified by one researcher. The interviewer is a cis female graduate student. The interviews were audio recorded using an audio recorder, de-identified using pseudonyms, and transcribed verbatim using the A.I software “Otter.ai”. If audio recordings had identifying information, they were transcribed by hand. Each transcript was verified against the corresponding audio recordings for accuracy. All original recording files will be kept on the password-protected university server for a minimum of 5 years following transcription, in accordance with [redacted] data retention policies.

Interview guide development

Interview guides were developed by the research team based on existing evidence, expert experience and framed with the Theoretical Domains Framework (TDF), as it identifies influences on healthcare providers’ and patients’ behaviours relative to evidence-based recommendations [ 18 ]. The TDF was chosen over other frameworks because it comprehensively captures a range of mechanisms that influence behaviours, creating a foundation for prospective behaviour change interventions [ 19 ]. The TDF can be mapped to the Capacity, Opportunity, Motivation Model of Behaviour (COM-B) within the Behaviour Change Wheel (BCW) [ 20 ]. The COM-B can then be used as a stepping stone to link these sources of behaviour to behaviour change interventions and clinical implementation [ 21 ].

Two separate interview guides were created for: 1) healthcare practitioners (e.g., physicians, nurses, allied healthcare workers) and; 2) caregivers and family members. Questions covered all 14 domains of the TDF (e.g., knowledge, skills, etc.). The interview guides can be found in Additional File 2 . The aforementioned definitions of agitation and aggression were followed when creating the interview guide. Barriers/facilitators that may exist at diagnosis/detection, care management and coordination, and treatment (mild/moderate and severe/acute) of agitation and/or aggression were explored among PLWD in LTC. The guide was adapted for suitability and/or appropriateness to ensure both caregivers and healthcare practitioners could answer.

Data analysis

Descriptive statistics.

Demographic data was summarized from all interview participants. Characteristics included sex, gender, age, place of birth, languages spoken, racial identity, occupation or role in LTC, and length of career or number of years in their role. These data were reported in a table, providing rich, descriptive context of the interview participants overall (Table  1 ).

Framework analysis

The transcribed interviews were coded using Framework Analysis, based on the TDF. Framework analysis determined how interview discussions fit within the TDF. It follows 7 steps described by Gale et al [ 22 ].

An inductive, ground-up coding process was conducted by two independent researchers by analyzing each line of transcript one-by-one. Codes emerged as the data were analyzed. Codes were then deductively analyzed by one researcher, by grouping them into themes and assigning TDF domains to them. Each code could be associated with one or more TDF domain. The themes were further grouped into categories of care for agitation and/or aggression: 1) Detection/diagnosis, 2) Care coordination and management, and; 3) Treatment (mild/moderate and acute/severe). Further interpretation was made on what domains of the TDF were contributing the most as barriers/facilitators to care.

Data saturation was considered reached when no new themes regarding barriers and facilitators to agitation care emerged from the discussions [ 18 ]. As new themes continued to arise with coding, more participants from the respective stakeholders were recruited via purposive and snowball sampling until data saturation was achieved, and possible themes were exhausted.

Reporting criteria

Results were reported as per the 32-item COREQ checklist for explicit reporting of qualitative studies involving semi-structured interviews [ 23 ]. A reflexivity statement is shown in Additional File 1 .

Participant information

Semi-structured interviews were conducted between December 2022 and February 2023. 18 participants were interviewed across the 4 LTC centres, with the majority being female ( n  = 15), between the ages of 35–64, born in Canada ( n  = 15), White ( n  = 15) and English-speaking ( n  = 18) (Table  1 ). Participants held a variety of roles within LTC: family caregivers and spouses ( n  = 5), family physicians ( n  = 4), nurses (registered nurses, licensed practical nurses) ( n  = 4), healthcare aides, executive medical directors and quality practice leads ( n  = 4), and other allied healthcare workers (i.e., recreational therapists, occupational therapists and spiritual care practitioners) ( n  = 5).

Organization of Findings

Results are presented as barriers and/or facilitators across several larger categories (Fig.  1 ): (1) detection and diagnosis, (2) Care coordination and management, (3) Mild-to-moderate Treatment, and (4) Acute/Severe treatment. Themed codes and associated interviewee quotes are indicated by italics as shown below. Tables 2 , 3 and 4 demonstrate all codes and categorized themes which depict all barriers and facilitators to care identified during the interviews, with detailed quotes in Additional File 3 . Participant roles were anonymized to protect participant confidentiality, but Participant ID is shown to represent diverse participant perspectives.

The most common facilitators and barriers to ( a ) the detection and diagnosis of agitation and/or aggression in LTC, ( b ) the care coordination and management of agitation and/or aggression in LTC, ( c ) the treatment of mild-to-moderate agitation and/or aggression in LTC, and ( d ) the treatment of acute/severe agitation and/or aggression in LTC

Barriers and facilitators to care at detection and diagnosis of agitation and/or aggression

Several main facilitators were described at detection and diagnosis. Agitation diagnostic tools were reported as advantageous because they can be easily administered by different healthcare professionals and produce easy-to-understand results . As well, using agitation diagnostic tests were considered useful because they allow healthcare practitioners to compare agitation between residents and keep assessments objective . Interview participants also advocated for increased training among healthcare providers to use agitation screening tools. Lastly, allied healthcare workers praised using the Resident Assessment Instrument (RAI) along with counting the number of aggressive or agitated incidents as facilitators to diagnose agitation.

“Well, the advantage is, it actually outlines the signs and symptoms […] so that it's readily available and reproducible […] and somebody who's unskilled can actually use a lot of these tools.” (Participant 3)

Several barriers to care at detection and diagnosis were identified. Firstly, certain diagnostic tests may prove difficult to administer because they are not adapted for persons with cognitive impairment. Interviewees reported difficulties in understanding how agitation diagnostic tests work. And, differing levels of healthcare provider familiarity with agitation diagnostic tools may affect how comfortable and competent they are with administering them. There were logistical challenges to using agitation tools because tools were commonly time consuming , and required adequate healthcare provider availability . As well, diagnosis of cognitive issues took a long time, which delays diagnosis of agitation and/or aggression:

“ [T]he whole process of diagnosis took about three years, and the cognitive neurologist was seeing us every six months, and she would test him every time with different mental tests… ” (Participant 1)

Furthermore, diagnosis of agitation and/or aggression took a long time, which can delay the onset of treatment. Another caregiver described a lack of available diagnostic tests for agitation for PLWD in LTC. Diagnostic care practices also commonly overlook hypoactive behaviours in dementia that are comorbid to agitation and/or aggression:

“ The hyperactive [resident] usually attracts the attention of everybody because they're distressed, yelling, screaming, fidgeting, wandering, moving, so they're active, whereas the hypoactive – that's where people can be missed ” (Participant 3).

Although cognitive impairment and hypoactive behaviours are not specific to agitation and/or aggression, a delay in diagnosis of cognitive impairment was interpreted by participants to consequently delay the detection of associated agitated and/or aggressive behaviours.

Barriers and facilitators to coordination and management of care of agitation and/or aggression

A key facilitator to the coordination and management of care was using family members to help provide care , to help calm residents and direct the course of care. Secondly, interviewees supported using personalized and interdisciplinary approaches to care to improve confidence in care plans . Components of personalized care included having a supportive and personalized environment for the resident to physically live, and having a checklist of precipitants to consider (e.g., basic needs, food, etc .) for each resident. As well, specialized or interdisciplinary care teams were needed to develop care plans and management strategies:

“ [W]e do have our interdisciplinary team that regularly debates and we discuss each resident several times a year, and then more so if needs arise. And so it's anywhere from HCA to physio, TRT, social work, dietary, the entire interdisciplinary team. ” (Participant 10)

In terms of barriers, several participants reported a lack of action among care workers to address agitation and/or aggression concerns among residents, and a lack of staff-to-staff and staff-to-family caregiver communication as a barrier to consistent and quality care for agitation. There were cultural and language barriers to care for residents identifying as persons of colour, and constantly changing directives in LTC facilities or a lack of existing directives to address agitation and/or aggression. Environmental barriers included the presence of constant loud noises and unideal room configurations for PLWD in LTC. Finally, a lack of available resources to provide care was raised as a crucial barrier to care, with a particular focus on the cost of care , staffing issues and limited time for healthcare providers to provide care .

“ So there was one LPN [licensed practical nurse] , and three healthcare aides for 30 patients with dementia. It wasn't enough. ” (Participant 1)

Barriers and facilitators to treatment for mild/moderate agitation and/or aggression

There were several reported facilitators to administering medications including routine monitoring of medications , having an interdisciplinary team available to prescribe medications , and an easy access to prescriptions for agitation medications:

“ And so how [medications are] actually prescribed is, it becomes the doctor's orders, ultimately, but the doctor does rely on feedback from the nursing staff as well on what's been effective or not .” (Participant 9)

Various barriers to using medication to treat mild-to-moderate agitation and/or aggression included barriers due to biological mechanisms , presentation of severe agitation, and drug shortages and availability . There were also challenges in identifying side effects from the drugs , in monitoring the medications , and in physically administering medication to residents:

“ Challenges in administration. Challenges if there is not enough monitoring to see the effects of these drugs. Challenges in explaining to the caregivers what to look for in terms of side effects or other effects from the drugs. ” (Participant 6)

Facilitators to using non-pharmacological interventions included incorporating intentional use of non-pharmacological treatment strategies, routine monitoring of non-pharmacological approaches , and having familiar and trustable healthcare providers with the competence and training to administer non-pharmacological treatment approaches:

“They use different activities - recreational activities. […] So they would try to redirect him with activities.” (Participant 1)

In terms of barriers to using non-pharmacological interventions for agitation and/or aggression, interviewees reported a lack of training specifically for non-pharmacological treatment approaches among healthcare providers, and a lack of non-pharmacological interventions available in LTC. A logistical challenge included difficulty coordinating timing for interventions among groups of residents. Treatment strategies often relied on medication because it is convenient , with an easy access to prescriptions for agitation medications, thus non-pharmacological interventions were underused. The need to use trial and error to select a non-pharmacological intervention was also inconvenient.

“ I think the only thing is that [non-pharmacological treatments are] actually not used [that] often. The default is drugs, […] because drugs are the easiest. Given the staffing shortage, it seems to be the default. ” (Participant 6)

Barriers and facilitators to treatment for acute/severe agitation and/or aggression

A key facilitator to non-pharmacological treatment for acute/severe agitation and/or aggression was having non-pharmacological options available for acute/severe agitation and having a least restraint policy in LTC . A facilitator to pharmacological treatment was choosing to use chemical restraints because agitation and/or aggression symptoms are too severe due to safety concerns for the resident and healthcare providers:

“ We need something to work quickly because somebody else will get hurt if we don't act sooner. ” (Participant 8)

An overall barrier for acute/severe agitation treatment was the reliance on physical and/or chemical restraints . As well, agitation symptoms being too severe served as a barrier to using non-pharmacological interventions for acute/severe agitation and/or aggression:

“ When a person is in that extreme agitation [...] you've determined that this is the immediate course of action [...] to get Haldol [or] Seroquel, whatever, into that person. ” (Participant 10)

Several codes arose regarding barriers and/or facilitators to care at a systemic and policy level in LTC. An unclear awareness or availability of geriatric medicine or geriatric psychiatry services in LTC served as a barrier at the detection and diagnosis of agitation and/or aggression. Conversly, having physicians more actively involved in care in LTC centres resulted in less referrals and was a facilitator to care at detection and diagnosis. Lastly, as previously mentioned, interviewees reported that having a least restraint policy in LTC was a facilitator to providing non-pharmacological interventions.

This study identifies key barriers and facilitators to care behaviours for agitation and/or aggression among PLWD in LTC, across 4 major categories: (1) Detection and Diagnosis, (2) Care Coordination and Management, (3) Treatment for mild-to-moderate agitation and, (4) Treatment for acute/severe agitation. Key barriers across the spectrum of care included a limited number of agitation and/or aggression diagnostic measures, a lack of training for managing agitation and/or aggression in LTC, an overuse of physical and chemical restraints among acutely/severely agitated and/or aggressive residents, and an underuse of non-pharmacological interventions. Facilitators included using an interdisciplinary team to deliver care and having competent and trained healthcare providers to administer non-pharmacological interventions. Ultimately, these results advance the care for PLWD in LTC by highlighting key issues needing to be addressed. The findings will support future implementation research endeavours to combat these barriers through targeted interventions to improve the quality of care across Canada.

Detection and diagnosis

Specific tools used to detect and diagnose agitation and/or aggression among plwd in ltc.

The most frequently reported methods of diagnosing and monitoring agitation and/or aggression symptoms in LTC centres was through two main charting means: the Behaviour and Symptom Mapping Tools and the RAI (RAI-Minimum Data Set (MDS) 2.0). Interestingly, no interviewee mentioned the use of an agitation and/or aggression psychometric tool, bringing the availability of agitation and/or aggression diagnostic tools in LTC into question. This barrier relates to issues with availability of resources in LTC. Most of the psychometric tools examined in a recent systematic review were not compared to a reference standard, and there were no studies that examined the BSMT or RAI-MDS 2.0 questions [ 25 ]. Therefore, there are no reported sensitivity, specificity, or minimally clinical important difference measures seen for these tools. In turn, it is unclear how these tools perform clinically. There are many reasons for this – agitation and aggression are very prominent observable symptoms, and their reporting needs to be tied to antecedent events through informant accounts to be useful to healthcare providers [ 26 ]. As well, behavioural and psychological symptoms of dementia (BPSD) often overlap, with agitation and aggression often expressed together, resulting in conflation between symptoms [ 2 ]. Beyond tools, there are also other comprehensive approaches to assessing agitation and/or aggression described in the literature, such as the “Describe, Investigate, Create, and Evaluate” (DICE) method [ 27 ]. These approaches were also not mentioned in the interviews. To ensure residents are receiving the best means of agitation and/or aggression detection and diagnosis, more research is needed to validate current tools among PLWD in LTC, and determine whether psychometric tools should be implemented in regular practice.

Using an interdisciplinary care team to diagnose agitation and/or aggression among PLWD in LTC

The diagnosis for agitation and/or aggression is typically finalized by physicians in LTC, using aggregated information collected from members of the interdisciplinary care team. The collaborative approach to care, where all interdisciplinary healthcare providers and/or friends and family caregivers have input into resident care plans, is crucial to the diagnosis and management of agitation and/or aggression. This facilitator demonstrates strengths pertaining to reinforcement of practices, healthcare providers’ perceived identity, and creating goals of care. A collaborative, interdisciplinary approach effectively offsets physician time and increases confidence among physicians to make diagnoses [ 28 , 29 ]. As well, residents receive a comprehensive assessment outside of a physician’s diagnosis, using the maximized complementary strengths of the entire care team [ 28 , 29 ]. Interdisciplinary care teams uphold person-centred care values, by addressing the unique needs of each resident whilst giving shared decision making to healthcare providers, residents and family and/or friend caregivers [ 28 , 29 ]. Given the benefits, any chosen method to detect or diagnose symptoms of agitation and/or aggression should account for interdisciplinary teams and family and/or friend caregivers.

In a recent systematic review, the majority of agitation and/or aggression tools lacked a comprehensive, interdisciplinary assessment of residents [ 25 ]. The Behavioral Pathology in Alzheimer’s Disease Rating Scale (BEHAVE-AD) and the Neuropsychiatric Inventory (NPI) were the only tools that seemed to account for multiple stakeholder perspectives (i.e., assessing caregiver distress along with resident symptoms). A potential reason for this is that agitation and/or aggression symptoms are predominantly detected via the observation of residents, or through informant reports of the frequency of symptoms, resulting in only observation-based and informant-rated tools available [ 26 ]. However, these assessment methods are limiting, where only observable points of contact with the resident can be evaluated [ 26 ]. More research is thus needed to determine whether incorporating an interdisciplinary evaluation approach into current assessment methods is more clinically beneficial to residents.

Care coordination and management

Lack of training for managing agitation and/or aggression.

Family/friend caregivers and allied healthcare workers felt that training in LTC is inconsistent, lacks staff-to-staff and staff-to-family caregiver communication, and does not properly address resident needs. These issues relate to several challenges, including issues with knowledge and skills among healthcare providers, limited resources, and challenges in staff’s perceived identity. Ultimately, training standards within LTC settings vary province-to-province across Canada [ 30 ]. Training for crucial healthcare practitioners in LTC (e.g., physicians, nurses) is not standardized, and often does not embrace a geriatric-focused lens [ 30 ]. In the analyses, interviewees raised concerns that these variable care protocols for agitation and/or aggression do not meet residents’ needs. The variability seen in training adversely impacts management of agitation and/or aggression among PLWD in LTC. There is a need for standardized practices for addressing agitation and/or aggression symptoms among PLWD in LTC among healthcare practitioners in LTC, to improve the efficiency and quality of care.

Mild-to-moderate agitation and/or aggression

Underusage of non-pharmacological interventions:.

Non-pharmacological interventions are considered more efficacious than pharmacological for agitation and/or aggression due to less adverse side effects, greater cost efficiency, and because they address underlying resident needs [ 11 , 31 ]. Despite this knowledge, healthcare providers lacked education and training on how to administer different non-pharmacological interventions, thus serving as a crucial barrier to agitation care. This barrier reflects issues in resources along with knowledge and skills among healthcare providers. One reason for why knowledge and training are lacking is that processes of selecting and administering non-pharmacological interventions are largely unsystematic and reportedly based on trial-and-error [ 32 ]. Consequently, due to time constraints, healthcare practitioners interviewed in this study often resided to using pharmacological interventions rather than non-pharmacological, out of convenience. This issue was corroborated by Janzen et al.’s (2013) findings, where unpredictable environmental factors and healthcare provider and/or resident personal traits (i.e. personality) resulted in arbitrary selection of non-pharmacological approaches [ 9 ].

Through the discussions, a key theme that emerged was a need for better upstream, person-centred approaches for the prevention of agitation and/or aggression. For example, one participant noted that physicians are active in LTC and respond quickly to behaviours, but a separate participant pointed out that such responses typically resort to using chemical restraints (Additional File 3 ). This issue highlights how agitation and/or aggression are currently being addressed in a downstream manner, after behaviours have manifested. Ultimately, person-centred approaches to prevent agitation and/or aggression use individual unique characteristics, strengths, and weaknesses to recognize and meet individual unmet needs, thus preventing agitation and/or aggression prior to their onset [ 33 ]. A previous meta-analysis demonstrated that using person-centred care interventions significantly reduces agitation amongst other neuropsychiatric symptoms [ 33 ]. For example, the “Treatment Routes for Exploring Agitation” (TREA) program, along with other therapeutic recreation programs, provide tailored activities to residents, and have demonstrated a reduction of agitation between 10–14 days following completion of these interventions [ 33 ]. Therefore, a greater emphasis on person-centred, upstream interventions is needed in LTC to prevent the onset of agitation and/or aggression among residents.

Another issue brought up by family and/or friend caregivers, was the limited number of available non-pharmacological interventions in LTC. Non-pharmacological interventions follow a person-centred approach to address unique behavioural needs of each resident [ 34 ]. However, to tailor approaches to each resident, non-pharmacological interventions require extensive time and staffing resources to implement – both of which are lacking in LTC [ 9 ]. Both factors are common barriers to implementing non-pharmacological interventions across a range of behavioural symptoms in LTC [ 24 ]. For example, Hussin et al. (2021) noted several barriers to implementing non-pharmacological interventions for BPSD in LTC, including limited staff time and training [ 35 ]. Likewise, Oldenburger et al. (2022) reported that, although residents require approximately 4.1 h of care time per day to meet needs, they are only receiving about 2.45 h to 3.73 h of care per day [ 36 ]. The onset of COVID-19 has further exacerbated issues in staffing and time to provide care [ 36 ]. Due to these constraints, a restricted number of non-pharmacological interventions are offered in LTC, thus negatively impacting the quality of care for residents experiencing a variety of health conditions. Given the widespread negative impacts, upstream implementation research is needed to counteract these time and resource constraints, allowing space for more non-pharmacological intervention strategies in LTC.

Acute/Severe agitation treatment

Overuse of physical and chemical restraints for acute/severe agitation and/or aggression.

A key barrier at acute/severe treatment for agitation and/or aggression was the reliance on physical and chemical (i.e., fast-acting medications) restraints to contain an acutely agitated and/or aggressive resident. This issue relates to challenges in regulating resident behaviours and reinforcement of practices. Acutely agitated and/or aggressive residents were considered at risk of harming themselves or others, thus as needed antipsychotic medications (e.g., Haldol) and mechanical restraints (e.g., chair with a seatbelt) were used. These measures carry significant risks to residents including a loss of dignity, social isolation, shame, and physical harm [ 37 , 38 ].

Many LTC institutions across Canada have implemented a “Restraint as a Last Resort” policy, where the least restrictive pharmacological, environmental, mechanical, and physical restraints are administered as a last resort practice [ 39 ]. Across provinces, similar policies have been implemented by LTC organizers, including Alberta Health Services, Health Prince Edward Island, and the College of Nurses of Ontario [ 39 , 40 , 41 ]. Despite least restraints being a shared goal across Canadian LTC centres, the discussions seemed to highlight an increased use of them among residents. Future studies should evaluate whether current uses of restraints across Canadian LTC centres are appropriate.

Several interviewees highlighted redirection, resident isolation and Gentle Persuasive Approach training. Other non-pharmacological approaches seen in the literature for acute/severe agitation and/or aggression include, but are not limited to, non-coercive verbal de-escalation or self-soothing techniques [ 42 , 43 ]. However, there are barriers to the use of these interventions.

This study featured a myriad of perspectives from persons of differing roles in LTC (Table  1 ). Due to these diverse roles, different interviewees focused on different points of discussion. For example, physicians presented a clinical lens during discussions on the detection and diagnosis of agitation and/or aggression, along with corresponding pharmacological interventions. In terms of the latter, physicians spoke to barriers in using pharmacological interventions from the pathophysiological aspect, including drug-drug interactions, and biological mechanisms (Additional File 3 ). In comparison, nurses and allied healthcare workers focused on challenges in the administration of medications, while family caregivers and spouses focused on education barriers surrounding medication use. Furthermore, allied healthcare workers and nurses provided shared experiences regarding the coordination of care for agitation and/or aggression. In particular, allied healthcare workers (E.g.; occupational therapists, recreational therapists) had notable experience conducting non-pharmacological interventions with residents in LTC, and could speak to the barriers and facilitators they had encountered. Lastly, caregivers and spouses presented ideas throughout their interviews from the residents’ perspectives, with themes surrounding their perceived quality of life in LTC.

Few qualitative studies are currently available on the barriers and facilitators to neuropsychiatric care among Canadian LTC centres. Current qualitative literature identifies barriers and facilitators to small-scale implementations in Canadian LTC centres, such as the PIECES education framework [ 44 ], but broad-scale qualitative behavioural research has not been conducted. One systematic review exists on the barriers and facilitators to complex interventions for PLWD in LTC, but this study does not focus on widescale barriers to neuropsychiatric care in LTC, and only features 2 studies with a Canadian setting [ 45 ]. Taken together, this gap in research can have negative clinical implications, as key barriers to care in Canadian LTC centres are missed. This study thus serves as a crucial step in improving understanding of agitation and/or aggression care in LTC, accounting for a broad range of lived experiences and perspectives.

At a broader context, several findings consistent with studies conducted at a global scale were acquired. For example, interviewees detailed cost barriers, disproportionate staff-to-resident ratios, and limited time to provide care as barriers to coordinating and managing care in Albertan LTC facilities. These findings were also reported by Janzen et al. (2013) and McArthur et al. (2021), where limited time to deliver care and inadequate staffing were also systematic and pervasive issues [ 9 , 30 ]. Similarly, environmental barriers to agitation care were found, including loud noises and unideal room configurations. This finding is corroborated by Cohen-Mansfield et al.’s (2012) study, where environmental conditions also served as barriers to administering non-pharmacological interventions for a range of behavioral symptoms [ 24 ]. Taken together, each of these barriers have served as perpetual challenges over the last decade in diverse LTC settings across North America. These findings thus demonstrate the need for a substantial global knowledge-to-action plan to address these pervasive challenges.

Limitations and Generalizability

There were several limitations in this study. Despite aiming to interview participants from a broad array of backgrounds and disciplines, the majority (83.3%) of participants identified as White. The lack of diversity in our sample may not reflect the perspectives of persons of colour working or engaging in LTC. Likewise, cultural or spiritual barriers and/or facilitators may have been missed, that more often impact racial minorities across Canada. This bias could potentially impact the generalizability of our results to racialized Canadian communities [e.g., Indigenous, Black, Indigenous, Persons of Colour, etc.].

Future directions

Several key barriers and facilitators to care for agitation and/or aggression among PLWD in LTC facilities were identified, at detection/diagnosis, care coordination/management, and mild-to-moderate and acute/severe treatment. Given that these barriers were mapped to the TDF, future research efforts can form a substantial knowledge-to-action plan by mapping these TDF domains to the COM-B and subsequently the Behaviour Change Wheel. Therefore, appropriate implementation strategies can be created to change behaviours in LTC to eliminate these barriers to care.

This qualitative study used semi-structured interviews to identify the main barriers and facilitators to care for agitation and/or aggression among PLWD in LTC found that key barriers included a lack of validated tools to detect agitation and/or aggression, inconsistent and variable training practices among healthcare providers, and a limited number of non-pharmacological interventions available in LTC. Key facilitators were using an interdisciplinary team approach and having competent and trained healthcare providers to administer non-pharmacological interventions. Future research should look towards creating feasible implementation strategies to eliminate the identified barriers, in order to improve care outcomes among PLWD in LTC.

Availability of data and materials

The dataset generated and analyzed are not publicly available as individual participant interview transcripts cannot be shared beyond the research team listed on the ethics agreement held with the University of Calgary’s Conjoint Health Research Ethics Board. Thematically analyzed data and associated participant quotes are available in Additional File 3 . For data requests or inquiries please contact Dr. Zahra Goodarzi at [email protected].

Abbreviations

Behavioral Pathology in Alzheimer’s Disease Rating Scale

• Long-term care

Minimum Data Set

Neuropsychiatric Inventory

Persons living with dementia

Resident Assessment Instrument

Theoretical Domains Framework

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Acknowledgements

We would like to acknowledge and thank the long-term care facilities who assisted in recruiting participants for our study: Bethany Seniors Care, Brenda Strafford Foundation, Alberta Health Services, and AgeCare Facilities.

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Britney Wong, Jayna Holroyd-Leduc & Zahra Goodarzi

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Contributions

All authors (BW, JW, ZI, JH-L, and ZG) were involved in the conceptualization of the study, participant recruitment, and manuscript revisions and editing. BW conducted all participant interviews. BW and ZG completed the coding and analysis of the interview data as well as prepared the first draft of the manuscript.

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Correspondence to Zahra Goodarzi .

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The present interview study was approved by the University of Calgary Conjoint Health Research Ethics Board (ethics approval ID number (REB-22–1100)). All study participants completed an informed consent process and signed a written informed consent form in adherence to the University of Calgary Conjoint Health Research Ethics Board.

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BW was funded by the Cumming School of Medicine Department of Medicine Graduate Scholarship and the Canada Graduate Scholarship – Masters. No conflict of interests are reported for JW, or JH-L. ZG holds independent peer-reviewed project funding from the Canadian Institutes of Health Research (CIHR), Brenda Strafford Foundation, Hotchkiss Brain Institute (HBI) and O’Brien Institute of Public Health at the University of Calgary. ZI holds voluntary positions as Chair of the Canadian Conference on Dementia, and the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia, but no conflict of interests are associated with either position.

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Wong, B., Ismail, Z., Watt, J. et al. Barriers and facilitators to care for agitation and/or aggression among persons living with dementia in long-term care. BMC Geriatr 24 , 330 (2024). https://doi.org/10.1186/s12877-024-04919-0

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Received : 23 October 2023

Accepted : 25 March 2024

Published : 11 April 2024

DOI : https://doi.org/10.1186/s12877-024-04919-0

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