qualitative research interview saturation

Sample sizes for saturation in qualitative research: A systematic review of empirical tests

Affiliations.

• 1 Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Rd, Atlanta, GA, 30322, USA. Electronic address: [email protected].
• 2 Department of Anthropology and Global Health Program, University of California San Diego, 9500 Gilman Drive 0532, La Jolla, CA, 92093, USA. Electronic address: [email protected].
• PMID: 34785096
• DOI: 10.1016/j.socscimed.2021.114523

Objective: To review empirical studies that assess saturation in qualitative research in order to identify sample sizes for saturation, strategies used to assess saturation, and guidance we can draw from these studies.

Methods: We conducted a systematic review of four databases to identify studies empirically assessing sample sizes for saturation in qualitative research, supplemented by searching citing articles and reference lists.

Results: We identified 23 articles that used empirical data (n = 17) or statistical modeling (n = 6) to assess saturation. Studies using empirical data reached saturation within a narrow range of interviews (9-17) or focus group discussions (4-8), particularly those with relatively homogenous study populations and narrowly defined objectives. Most studies had a relatively homogenous study population and assessed code saturation; the few outliers (e.g., multi-country research, meta-themes, "code meaning" saturation) needed larger samples for saturation.

Conclusions: Despite varied research topics and approaches to assessing saturation, studies converged on a relatively consistent sample size for saturation for commonly used qualitative research methods. However, these findings apply to certain types of studies (e.g., those with homogenous study populations). These results provide strong empirical guidance on effective sample sizes for qualitative research, which can be used in conjunction with the characteristics of individual studies to estimate an appropriate sample size prior to data collection. This synthesis also provides an important resource for researchers, academic journals, journal reviewers, ethical review boards, and funding agencies to facilitate greater transparency in justifying and reporting sample sizes in qualitative research. Future empirical research is needed to explore how various parameters affect sample sizes for saturation.

Keywords: Focus group discussions; Interviews; Qualitative research; Sample size; Saturation.

Copyright © 2021. Published by Elsevier Ltd.

Publication types

• Systematic Review
• Data Collection
• Focus Groups
• Qualitative Research
• Research Design*
• Sample Size

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Open-ended interview questions and saturation

Susan c. weller.

1 Department of Preventive Medicine & Community Health, University of Texas Medical Branch, Galveston, Texas, United States of America

Ben Vickers

H. russell bernard.

2 Institute for Social Research, Arizona State University, Tempe, Arizona/University of Florida, Gainesville, Florida, United States of America

Alyssa M. Blackburn

3 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America

Stephen Borgatti

4 Department of Management, University of Kentucky, Lexington, Kentucky, United States of America

Clarence C. Gravlee

5 Department of Anthropology, University of Florida, Gainesville, Florida, United States of America

Jeffrey C. Johnson

Associated data.

All relevant data are available as an Excel file in the Supporting Information files.

Sample size determination for open-ended questions or qualitative interviews relies primarily on custom and finding the point where little new information is obtained (thematic saturation). Here, we propose and test a refined definition of saturation as obtaining the most salient items in a set of qualitative interviews (where items can be material things or concepts, depending on the topic of study) rather than attempting to obtain all the items . Salient items have higher prevalence and are more culturally important. To do this, we explore saturation, salience, sample size, and domain size in 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains—like kinds of fruits (highly bounded) and things that mothers do (unbounded)—varied greatly in size. The datasets comprise 20–99 interviews each (1,147 total interviews). When saturation was defined as the point where less than one new item per person would be expected, the median sample size for reaching saturation was 75 (range = 15–194). Thematic saturation was, as expected, related to domain size. It was also related to the amount of information contributed by each respondent but, unexpectedly, was reached more quickly when respondents contributed less information. In contrast, a greater amount of information per person increased the retrieval of salient items. Even small samples ( n = 10) produced 95% of the most salient ideas with exhaustive listing, but only 53% of those items were captured with limited responses per person (three). For most domains, item salience appeared to be a more useful concept for thinking about sample size adequacy than finding the point of thematic saturation. Thus, we advance the concept of saturation in salience and emphasize probing to increase the amount of information collected per respondent to increase sample efficiency.

Introduction

Open-ended questions are used alone or in combination with other interviewing techniques to explore topics in depth, to understand processes, and to identify potential causes of observed correlations. Open-ended questions may produce lists, short answers, or lengthy narratives, but in all cases, an enduring question is: How many interviews are needed to be sure that the range of salient items (in the case of lists) and themes (in the case of narratives) are covered. Guidelines for collecting lists, short answers, and narratives often recommend continuing interviews until saturation is reached. The concept of theoretical saturation —the point where the main ideas and variations relevant to the formulation of a theory have been identified—was first articulated by Glaser and Strauss [ 1 , 2 ] in the context of how to develop grounded theory. Most of the literature on analyzing qualitative data, however, deals with observable thematic saturation —the point during a series of interviews where few or no new ideas, themes, or codes appear [ 3 – 6 ].

Since the goal of research based on qualitative data is not necessarily to collect all or most ideas and themes but to collect the most important ideas and themes, salience may provide a better guide to sample size adequacy than saturation. Salience (often called cultural or cognitive salience) can be measured by the frequency of item occurrence (prevalence) or the order of mention [ 7 , 8 ]. These two indicators tend to be correlated [ 9 ]. In a set of lists of birds, for example, robins are reported more frequently and appear earlier in responses than are penguins. Salient terms are also more prevalent in everyday language [ 10 – 12 ]. Item salience also may be estimated by combining an item’s frequency across lists with its rank/position on individual lists [ 13 – 16 ].

In this article, we estimate the point of complete thematic saturation and the associated sample size and domain size for 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains—like kinds of fruits (highly bounded) and things that mothers do (unbounded)—varied greatly in size. We also examine the impact of the amount of information produced per respondent on saturation and on the number of unique items obtained by comparing results generated by asking respondents to name all the relevant things they can with results obtained from a limited number of responses per question, as with standard open-ended questioning. Finally, we introduce an additional type of saturation based on the relative salience of items and themes— saturation in salience —and we explore whether the most salient items are captured at minimal sample sizes. A key conclusion is that saturation may be more meaningfully and more productively conceived of as the point where the most salient ideas have been obtained .

Recent research on saturation

Increasingly, researchers are applying systematic analysis and sampling theory to untangle the problems of saturation and sample size in the enormous variety of studies that rely on qualitative data—including life-histories, discourse analysis, ethnographic decision modeling, focus groups, grounded theory, and more. For example, Guest et al.[ 17 ] and others[ 18 – 19 ] found that about 12–16 interviews were adequate to achieve thematic saturation. Similarly, Hagaman and Wutich [ 20 ] found that they could reliably retrieve the three most salient themes from each of the four sites in the first 16 interviews.

Galvin[ 21 ] and Fugard and Potts[ 22 ] framed the sample size problem for qualitative data in terms of the likelihood that a specific idea or theme will or will not appear in a set of interviews, given the prevalence of those ideas in the population. They used traditional statistical theory to show that small samples retrieve only the most prevalent themes and that larger samples are more sensitive and can retrieve less prevalent themes as well. This framework can be applied to the expectation of observing or not observing almost anything. Here it would apply to the likelihood of observing a theme in a set of narrative responses, but it applies equally well for situations such as behavioral observations, where specific behaviors are being observed and sampled[ 23 ]. For example, to obtain ideas or themes that would be reported by about one out of five people (0.20 prevalence) or a behavior with the same prevalence, there is a 95% likelihood of seeing those themes or behaviors at least once in 14 interviews—if those themes or behaviors are independent.

Saturation and sample size have also begun to be examined with multivariate models and simulations. Tran et al. [ 24 ] estimated thematic saturation and the total number of themes from open-ended questions in a large survey and then simulated data to test predictions about sample size and saturation. They assumed that items were independent and found that sample sizes greater than 50 would add less than one new theme per additional person interviewed.

Similarly, Lowe et al. [ 25 ] estimated saturation and domain size in two examples and in simulated datasets, testing the effect of various parameters. Lowe et al. found that responses were not independent across respondents and that saturation may never be reached. In this context, non-independence refers to the fact that some responses are much more likely than others to be repeated across people. Instead of complete saturation, they suggested using a goal such as obtaining a percentage of the total domain that one would like to capture (e.g., 90%) and the average prevalence of items one would like to observe to estimate the appropriate sample size. For example, to obtain 90% of items with an average prevalence of 0.20, a sample size of 36 would be required. Van Rijnsoever [ 26 ] used simulated datasets to study the accumulation of themes across sample size increments and assessed the effect of different sampling strategies, item prevalence, and domain size on saturation. Van Rijnsoever’s results indicated that the point of saturation was dependent on the prevalence of the items.

As modeling estimates to date have been based on only one or two real-world examples, it is clear that more empirical examples are needed. Here, we use 28 real-world examples to estimate the impact of sample size, domain size, and amount of information per respondent on saturation and on the total number of items obtained. Using the proportion of people in a sample that mentioned an item as a measure of salience, we find that even small samples may adequately capture the most salient items.

Materials and methods

The datasets comprise 20–99 interviews each (1,147 total interviews). Each example elicits multiple responses from each individual in response to an open-ended question (“Name all the … you can think of”) or a question with probes (“What other … are there?”).

Data were obtained by contacting researchers who published analyses of free lists. Examples with 20 or more interviews were selected so that saturation could be examined incrementally through a range of sample sizes. Thirteen published examples were obtained on: illness terms [ 27 ] (in English and in Spanish); birds, flowers, and fabrics [ 28 ]; recreational/street drugs and fruits [ 29 ]; things mothers do (online, face-to-face, and written administration) and racial and ethnic groups [ 30 ] (online, face-to-face, and written administration). Fifteen unpublished classroom educational examples were obtained on: soda pops (Weller, n.d.); holidays (two replications), things that might appear in a living room, characteristics of a good leader (two replications), a good team (two replications), and a good team player (Johnson, n.d.); and bad words, industries (two replications), cultural industries (two replications), and scary things (Borgatti, n.d.). (Original data appear online in S1 Appendix The Original Data for the 28 Examples.)

Some interviews were face to face, some were written responses, and some were administered on-line. Investigators varied in their use of prompts, using nonspecific (What other … are there?), semantic (repeating prior responses and then asking for others), and/or alphabetic prompts (going through the alphabet and asking for others). Brewer [ 29 ] and Gravlee et al. [ 30 ] specifically examined the effect of prompting on response productivity, although the Brewer et al. examples in these analyses contain results before extensive prompting and the Gravlee et al. examples contain results after prompting. The 28 examples, their topic, source, sample size, the question used in the original data collection, and the three most frequently mentioned items appear in Table 1 . All data were collected and analyzed without personal identifying information.

For each example, statistical models describe the pattern of obtaining new or unique items with incremental increases in sample size. Individual lists were first analyzed with Flame [ 31 , 32 ] to provide the list of unique items for each example and the Smith [ 14 ] and Sutrop [ 15 ] item salience scores. Duplicate items due to spelling, case errors, spacing, or variations were combined.

To help develop an interviewing stopping rule, a simple model was used to predict the unique number of items contributed by each additional respondent. Generalized linear models (GLM, log-linear models for count data) were used to predict the unique number of items added by each respondent (incrementing sample size), because number of unique items added by each respondent (count data) is approximately Poisson distributed. For each example, models were fit with ordinary least squares linear regression, Poisson, and negative binomial probability distributions. Respondents were assumed to be in random order, in the order in which they occurred in each dataset, although in some cases they were in the order they were interviewed. Goodness-of-fit was compared across the three models with minimized deviants (the Akaike Information Criterion, AIC) to find the best-fitting model [ 33 ]. Using the best-fitting model for each example, the point of saturation was estimated as the point where the expected number of new items was one or less. Sample size and domain size were estimated at the point of saturation, and total domain size was estimated for an infinite sample size from the model for each example as the limit of a geometric series (assuming a negative slope).

Because the GLM models above used only incremental sample size to predict the total number of unique items (domain size) and ignored variation in the number of items provided by each person and variation in item salience, an additional analysis was used to estimate domain size while accounting for subject and item heterogeneity. For that analysis, domain size was estimated with a capture-recapture estimation technique used for estimating the size of hidden populations. Domain size was estimated from the total number of items on individual lists and the number of matching items between pairs of lists with a log-linear analysis. For example, population size can be estimated from the responses of two people as the product of their number of responses divided by the number of matching items (assumed to be due to chance). If Person#1 named 15 illness terms and Person#2 named 31 terms and they matched on five illnesses, there would be 41 unique illness terms and the estimated total number of illness terms based on these two people would be (15 x 31) /5 = 93.

A log-linear solution generalizes this logic from a 2 x 2 table to a 2 K table [ 34 ]. the capture–recapture solution estimates total population size for hidden populations using the pattern of recapture (matching) between pairs of samples (respondents) to estimate the population size. An implementation in R with GLM uses a log-linear form to estimate population size based on recapture rates (Rcapture [ 35 , 36 ]). In this application, it is assumed that the population does not change between interviews (closed population) and models are fit with: (1) no variation across people or items (M 0 ); (2) variation only across respondents (M t ); (3) variation only across items (M h ); and (4) variation due to an interaction between people and items (M ht ). For each model, estimates were fit with binomial, Chao’s lower bound estimate, Poisson, Darroch log normal, and gamma distributions [ 35 ]. Variation among items (heterogeneity) is a test for a difference in the probabilities of item occurrence and, in this case, is equivalent to a test for a difference in item salience among the items. Due to the large number of combinations needed to estimate these models, Rcapture software estimates are provided for all four models only up to a sample of size 10. For larger sample sizes (all examples in this study had sample sizes of 20 or larger), only model 1 with no effects for people or items (the binomial model) and model 3 with item effects (item salience differences) were tested. Therefore, models were fit at size 10, to test all four models and then at the total available sample size.

Descriptive information for the examples appears in Table 2 . The first four columns list the name of the example, the sample size in the original study, the mean list length (with the range of the list length across respondents), and the total number of unique items obtained. For the Holiday1 example, interviews requested names of holidays (“Write down all the holidays you can think of”), there were 24 respondents, the average number of holidays listed per person (list length) was 13 (ranging from five to 29), and 62 unique holidays were obtained.

nbi = Negative binomial-identity, p = Poisson-log ; c = Chao’s Lower bound; g = gamma

Predicting thematic saturation from sample size

The free-list counts showed a characteristic descending curve where an initial person listed new themes and each additional person repeated some themes already reported and added new items, but fewer and fewer new items were added with incremental increases in sample size. All examples were fit using the GLM log-link and identity-link with normal, Poisson, and negative binomial distributions. The negative binomial model resulted in a better fit than the Poisson (or identity-link models) for most full-listing examples, providing the best fit to the downward sloping curve with a long tail. Of the 28 examples, only three were not best fit by negative binomial log-link models: the best-fitting model for two examples was the Poisson log-link model (GoodTeam1 and GoodTeam2Player) and one was best fit by the negative binomial identity-link model (CultInd1).

Sample size was a significant predictor of the number of new items for 21 of the 28 examples. Seven examples did not result in a statistically significant fit (Illnesses-US, Holiday2, Industries1, Industries2, GoodTLeader, GoodTeam2Player, and GoodTeam3). The best-fitting model was used to predict the point of saturation and domain size for all 28 examples ( S2 Appendix GLM Statistical Model Results for the 28 Examples).

Using the best-fitting GLM models we estimated the predicted sample size for reaching saturation. Saturation was defined as the point where less than one new item would be expected for each additional person interviewed. Using the models to solve for the sample size (X) when only one item was obtained per person (Y = 1) and rounding up to the nearest integer, provided the point of saturation (Y≤1.0). Table 2 , column five, reports the sample size where saturation was reached (N SAT ). For Holiday1, one or fewer new items were obtained per person when X = 16.98. Rounding up to the next integer provides the saturation point (N SAT = 17). For the Fruit domain, saturation occurred at a sample size of 15.

Saturation was reached at sample sizes of 15–194, with a median sample size of 75. Only five examples (Holiday1, Fruits, Birds, Flowers, and Drugs) reached saturation within the original study sample size and most examples did not reach saturation even after four or five dozen interviews. A more liberal definition of saturation, defined as the point where less than two new items would be expected for each additional person (solving for Y≤2), resulted in a median sample size for reaching saturation of 50 (range 10–146).

Some domains were well bounded and were elicited with small sample sizes. Some were not. In fact, most of the distributions exhibited a very long tail—where many items were mentioned by only one or two people. Fig 1 shows the predicted curves for all examples for sample sizes of 1 to 50. Saturation is the point where the descending curve crosses Y = 1 (or Y = 2). Although the expected number of unique ideas or themes obtained for successive respondents tends to decrease as the sample size increases, this occurs rapidly in some domains and slowly or not at all in other domains. Fruits, Holiday1, and Illness-G are domains with the three bottom-most curves and the steepest descent, indicating that saturation was reached rapidly and with small sample sizes. The three top-most curves are the Moms-F2F, Industries1, and Industries2 domains, which reached saturation at very large sample sizes or essentially did not reach saturation.

Estimating domain size

Because saturation appeared to be related to domain size and some investigators state that a percentage of the domain might be a better standard [ 25 ], domain size was also estimated. First, total domain size was estimated with the GLM models obtained above. Domain size was estimated at the point of saturation by cumulatively summing the number of items obtained for sample sizes n = 1, n = 2, n = 3, … to N SAT . For the Holiday1 sample, summing the number of predicted unique items for sample sizes n = 1 to n = 17 should yield 51 items ( Table 2 , Domain Size at Saturation, D SAT ). Thus, the model predicted that approximately 51 holidays would be obtained by the time saturation was reached.

The total domain size was estimated using a geometric series, summing the estimated number of unique items obtained cumulatively across people in an infinitely large sample. For the Holiday1 domain, the total domain size was estimated as 56 (see Table 2 , Total Domain Size D TOT ). So for the Holiday1 domain, although the total domain size was estimated to be 57, the model predicted that saturation occurred when the sample size reached 17, and at that point 51 holidays should be retrieved. Model predictions were close to the empirical data, as 62 holidays were obtained with a sample of 24.

Larger sample sizes were needed to reach saturation in larger domains; the largest domains were MomsF2F, Industries1, and Industries2 each estimated to have about 1,000 items and more than 100 interviews needed to approach saturation. Saturation (Y≤1) tended to occur at about 90% of the total domain size. For Fruits, the domain size at saturation was 51 and the total domain size was estimated at 53 (51/53 = 96%) and for MomsF2F, domain size at saturation was 904 and total domain size was 951 (95%).

Second, total domain size was estimated using a capture-recapture log-linear model with a parameter for item heterogeneity [ 35 , 36 ]. A descending, concave curve is diagnostic of item heterogeneity and was present in almost all of the examples. The estimated population sizes using R-Capture appear in the last column of Table 2 . When the gamma distribution provided the best fit to the response data, the domain size increased by an order of magnitude as did the standard error on that estimate. When responses fit a gamma distribution, the domain may be extremely large and may not readily reach saturation.

Inclusion of the pattern of matching items across people with a parameter for item heterogeneity (overlap in items between people due to salience) resulted in larger population size estimates than those above without heterogeneity. Estimation from the first two respondents was not helpful and provided estimates much lower than those from any of the other methods. The simple model without subject or item effects (the binomial model) did not fit any of the examples. Estimation from the first 10 respondents in each example suggested that more variation was due to item heterogeneity than to item and subject heterogeneity, so we report only the estimated domain size with the complete samples accounting for item heterogeneity in salience.

Overall, the capture–recapture estimates incorporating the effect of salience were larger than the GLM results above without a parameter for salience. For Fruits, the total domain size was estimated as 45 from the first two people; as 88 (gamma distribution estimate) from the first 10 people with item heterogeneity and as 67 (Chao lower bound estimate) with item and subject heterogeneity; and using the total sample ( n = 33) the binomial model (without any heterogeneity parameters) estimated the domain size as 62 (but did not fit the data) and with item heterogeneity the domain size was estimated as 73 (the best-fitting model used the Chao lower bound estimate). Thus, the total domain size for Fruits estimated with a simple GLM model was 53 and with a capture–recapture model (including item heterogeneity) was 73 ( Table 2 , last column). Similarly, the domain size for Holiday1 was estimated at 57 with the simple GLM model and 100 with capture-recapture model. Domain size estimates suggest that even the simplest domains can be large and that inclusion of item heterogeneity increases domain size estimates.

Saturation and the number of responses per person

The original examples used an exhaustive listing of responses to obtain about a half dozen (GoodLeader and GoodTeam2Player) to almost three dozen responses per person (Industries1 and Industries2). A question is whether saturation and the number of unique ideas obtained might be affected by the number of responses per person. Since open-ended questions may obtain only a few responses, we limited the responses to a maximum of three per person, truncating lists to see the effect on the number of items obtained at different sample sizes and the point of saturation.

When more information (a greater number of responses) was collected per person, more unique items were obtained even at smaller sample sizes ( Table 3 ). The amount of information retrieved per sample can be conceived of in terms of bits of information per sample and is roughly the average number of responses per person times the sample size so that, with all other things being equal, larger sample sizes with less probing should approach the same amount of information obtained with smaller samples and more probing. So, for a given sample size, a study with six responses per person should obtain twice as much information as a study with three responses per person. In the GoodLeader, GoodTeam1, and GoodTeam2Player examples, the average list length was approximately six and when the sample size was 10 (6 x 10 = 60 bits of information), approximately twice as many items were obtained as when lists were truncated to three responses (3 x 10 = 30 bits of information).

Increasing the sample size proportionately increases the amount of information, but not always. For Scary Things, 5.6 bits more information were collected per person with full listing (16.9 average list length) than with three or fewer responses per person (3.0 list length); and the number of items obtained in a sample size of 10 with full listing (102) was roughly 5.6 times greater than that obtained with three responses per person (18 items). However, at a sample size of 20 the number of unique items with free lists was only 4.5 times larger (153) than the number obtained with three responses per person (34). Across examples , interviews that obtained more information per person were more productive and obtained more unique items overall even with smaller sample sizes than did interviews with only three responses per person .

Using the same definition of saturation (the point where less than one new item would be expected for each additional person interviewed), less information per person resulted in reaching saturation at much smaller sample sizes. Fig 2 shows the predicted curves for all examples when the number of responses per person is three (or fewer). The Holiday examples reached saturation (fewer than one new item per person) with a sample size of 17 (Holiday1) with 13.0 average responses per person and 87 (Holiday2) with 17.8 average responses ( Table 2 ), but reached saturation with a sample size of only 9 (Holiday 1 and Holiday2) when there were a maximum of three responses per person ( Table 3 , last column). With three or fewer responses per person, the median sample size for reaching saturation was 16 (range: 4–134). Thus, fewer responses per person resulted in reaching saturation at smaller sample sizes and resulted in fewer domain items.

Salience and sample size

Saturation did not seem to be a useful guide for determining a sample size stopping point, because it was sensitive both to domain size and the number of responses per person. Since a main goal of open-ended interviews is to obtain the most important ideas and themes, it seemed reasonable to consider item salience as an alternative guide to assist with determining sample size adequacy. Here, the question would be: Whether or not complete saturation is achieved, are the most salient ideas and themes captured in small samples?

A simple and direct measure of item salience is the proportion of people in a sample that mentioned an item [ 37 ]. However, we examined the correlation between the sample proportions and two salience indices that combine the proportion of people mentioning an item with the item’s list position [ 13 – 15 ]. Because the item frequency distributions have long tails—there are many items mentioned by only one or two people—we focused on only those items mentioned by two or more people (24–204 items) and used the full lists provided by each respondent. The average Spearman correlation between the Smith and Sutrop indices in the 28 examples was 0.95 (average Pearson correlation 0.96, 95%CI: 0.92, 0.98), between the Smith index and the sample proportions was 0.89 (average Pearson 0.96, 95%CI: 0.915, 0.982), and between the Sutrop index and the sample proportions was 0.86 (average Pearson 0.88 95%CI: 0.753, 0.943). Thus, the three measures were highly correlated in 28 examples that varied in content, number of items, and sample size—validating the measurement of a single construct.

To test whether the most salient ideas and themes were captured in smaller samples or with limited probing, we used the sample proportions to estimate item salience and compared the set of most salient items across sample sizes and across more and less probing. Specifically, we defined a set of salient items for each example as those mentioned by 20% or more in the sample of size 20 (because all examples had at least 20) with full-listing (because domains were more detailed). We compared the set of salient items with the set of items obtained at smaller sample sizes and with fewer responses per person.

The set size for salient items (prevalence ≥ 20%) was not related to overall domain size, but was an independent characteristic of each domain and whether there were core or prototypical items with higher salience. Most domains had about two dozen items mentioned by 20% or more of the original listing sample ( n = 20), but some domains had only a half dozen or fewer items (GoodLeader, GoodTeam2Player, GoodTeam3). With full listing, 26 of 28 examples captured more than 95% of the salient ideas in the first 10 interviews: 18 examples captured 100%, eight examples captured 95–99%, one example captured 91%, and one captured 80% ( Table 4 ). With a maximum of three responses per person, about two-thirds of the salient items (68%) were captured with 20 interviews and about half of the items (53%) were captured in the first 10 interviews. With a sample size of 20, a greater number of responses per person resulted in approximately 50% more items than with three responses per person. Extensive probing resulted in a greater capture of salient items even with smaller sample sizes.

Summary and discussion

The strict notion of complete saturation as the point where few or no new ideas are observed is not a useful concept to guide sample size decisions, because it is sensitive to domain size and the amount of information contributed by each respondent. Larger sample sizes are necessary to reach saturation for large domains and it is difficult to know, when starting a study, just how large the domain or set of ideas will be. Also, when respondents only provide a few responses or codes per person, saturation may be reached quickly. So, if complete thematic saturation is observed, it is difficult to know whether the domain is small or whether the interviewer did only minimal probing.

Rather than attempting to reach complete saturation with an incremental sampling plan, a more productive focus might be on gaining more depth with probing and seeking the most salient ideas. Rarely do we need all the ideas and themes, rather we tend to be looking for important or salient ideas. A greater number of responses per person resulted in the capture of a greater number of salient items. With exhaustive listing, the first 10 interviews obtained 95% of the salient ideas (defined here as item prevalence of 0.20 or more), while only 53% of those ideas were obtained in 10 interviews with three or fewer responses per person.

We used a simple statistical model to predict the number of new items added by each additional person and found that complete saturation was not a helpful concept for free-lists, as the median sample size was 75 to get fewer than one new idea per person. It is important to note that we assumed that interviews were in a random order or were in the order that the interviews were conducted and were not reordered to any kind of optimum. The reordering of respondents to maximally fit a saturation curve may make it appear that saturation has been reached at a smaller sample size [ 31 ].

Most of the examples examined in this study needed sample sizes larger than most qualitative researchers use to reach saturation. Mason’s [ 6 ] review of 298 PhD dissertations in the United Kingdom, all based on qualitative data, found a mean sample size of 27 (range 1–95). Here, few of the examples reached saturation with less than four dozen interviews. Even with large sample sizes, some domains may continue to add new items. For very large domains, an incremental sampling strategy may lead to dozens and dozens of interviews and still not reach complete saturation. The problem is that most domains have very long tails in the distribution of observed items, with many items mentioned by only one or two people. A more liberal definition of complete saturation (allowing up to two new items per person) allowed for saturation to occur at smaller sample sizes, but saturation still did not occur until a median sample size of 50.

In the examples we studied, most domains were large and domain size affected when saturation occurred. Unfortunately, there did not seem to be a good or simple way at the outset to tell if a domain would be large or small. Most domains were much larger than expected, even on simple topics. Domain size varied by substantive content, sample, and degree of heterogeneity in salience. Domain size and saturation were sample dependent, as the holiday examples showed. Also, domain size estimates did not mean that there are only 73 fruits, rather the pattern of naming fruits—for this particular sample—indicated a set size of 73.

It was impossible to know, when starting, if a topic or domain was small and would require 15 interviews to reach saturation or if the domain was large and would require more than 100 interviews to reach saturation. Although eight of the examples had sample sizes of 50–99, sample sizes in qualitative studies are rarely that large. Estimates of domain size were even larger when models incorporated item heterogeneity (salience). The Fruit example had an estimated domain size of 53 without item heterogeneity, but 73 with item heterogeneity. The estimated size of the Fabric domain increased from 210 to 753 when item heterogeneity was included.

The number of responses per person affected both saturation and the number of obtained items. A greater number of responses per person resulted in a greater yield of domain items. The bits of information obtained in a sample can be approximated by the product of the average number of responses per person (list length) and the number of people in a sample. However, doubling the sample size did not necessarily double the unique items obtained because of item salience and sampling variability. When only a few items are obtained from each person, only the most salient items tend to be provided by each person and fewer items are obtained overall.

Brewer [ 29 ] explored the effect of probing or prompting on interview yield. Brewer examined the use of a few simple prompts: simply asking for more responses, providing alphabetical cues, or repeating the last response(s) and asking again for more information. Semantic cueing, repeating prior responses and asking for more information, increased the yield by approximately 50%. The results here indicated a similar pattern. When more information was elicited per person , about 50% more domain items were retrieved than when people provided a maximum of three responses.

Interviewing to obtain multiple responses also affects saturation. With few responses per person, complete saturation was reached rapidly. Without extensive interview probing, investigators may reach saturation quickly and assume they have a sample sufficient to retrieve most of the domain items. Unfortunately, different degrees of salience among items may cause strong effects for respondents to repeat similar ideas—the most salient ideas—without elaborating on less salient or less prevalent ideas, resulting in a set of only the ideas with the very highest salience. If an investigator wishes to obtain most of the ideas that are relevant in a domain , a small sample with extensive probing (listing) will prove much more productive than a large sample with casual or no probing .

Recently, Galvin [ 21 ] and Fugard and Potts [ 22 ] framed sample size estimation for qualitative interviewing in terms of binomial probabilities. However, results for the 28 examples with multiple responses per person suggest that this may not be appropriate because of the interdependencies among items due to salience. The capture–recapture analysis indicated that none of the 28 examples fit the binomial distribution. Framing the sample size problem in terms that a specific idea or theme will or will not appear in a set of interviews may facilitate thinking about sample size, but such estimates may be misleading.

If a binomial distribution is assumed, sample size can be estimated from the prevalence of an idea in the population, from how confident you want to be in obtaining these ideas, and from how many times you would like these ideas to minimally appear across participants in your interviews. A binomial estimate assumes independence (no difference in salience across items) and predicts that if an idea or theme actually occurs in 20% of the population, there is a 90% or higher likelihood of obtaining those themes at least once in 11 interviews and a 95% likelihood in 14 interviews. In contrast, our results indicated that the heterogeneity in salience across items causes these estimates to underestimate the necessary sample size as items with ≥20% prevalence were captured in 10 interviews in only 64% of the samples with full listing and in only 4% (one) of samples with three or fewer responses.

Lowe et al. [ 25 ] also found that items were not independent and that binomial estimates significantly underestimated sample size. They proposed sample size estimation from the desired proportion of items at a given average prevalence. Their formula predicts that 36 interviews would be necessary to capture 90% of items with an average prevalence of 0.20, regardless of degree of heterogeneity in salience, domain size, or amount of information provided per respondent. Although they included a parameter for non-independence, their model does not seem to be accurate for cases with limited responses or for large domains.

Conclusions

In general , probing and prompting during an interview seems to matter more than the number of interviews . Thematic saturation may be an illusion and may result from a failure to use in-depth probing during the interview. A small sample ( n = 10) can collect some of the most salient ideas, but a small sample with extensive probing can collect most of the salient ideas. A larger sample ( n = 20) is more sensitive and can collect more prevalent and more salient ideas, as well as less prevalent ideas, especially with probing. Some domains, however, may not have items with high prevalence. Several of the domains examined had only a half dozen or fewer items with prevalence of 20% or more. The direct link between salience and population prevalence offers a rationale for sample size and facilitates study planning. If the goal is to get a few widely held ideas, a small sample size will suffice. If the goal is to explore a larger range of ideas, a larger sample size or extensive probing is needed. Sample sizes of one to two dozen interviews should be sufficient with exhaustive probing (listing interviews), especially in a coherent domain. Empirically observed stabilization of item salience may indicate an adequate sample size.

A next step would be to test whether these conclusions and recommendations hold for other types of open-ended questions, such as narratives, life histories, and open-ended questions in large surveys. Open-ended survey questions are inefficient and result in thin or sparse data with few responses per person because of a lack of prompting. Tran et al. [ 24 ] reported item prevalence of 0.025 in answers in a large Internet survey suggesting few responses per person. In contrast, we used an item prevalence of 0.20 and higher to identify the most salient items in each domain and the highest prevalence in each domain ranged from 0.30 to 0.80 ( Table 1 ). Inefficiency in open-ended survey questions is likely due to the dual purpose of the questions: They try to define the range of possible answers and get the respondent’s answer. A better approach might be to precede survey development with a dozen free-listing interviews to get the range of possible responses and then use that content to design structured survey questions.

Another avenue for investigation is how our findings on thematic saturation compare to theoretical saturation in grounded theory studies [ 2 , 38 , 39 ]. Grounded theory studies rely on theoretical sampling–-an iterative procedure in which a single interview is coded for themes; the next respondent is selected to discover new themes and relationships between themes; and so on, until no more relevant themes or inter-relationships are discovered and a theory is built to explain the facts/themes of the case under study. In contrast this study examined thematic saturation, the simple accumulation of ideas and themes, and found that saturation in salience was more attainable–-perhaps more important—than thematic saturation.

Supporting information

S1 appendix, s2 appendix, acknowledgments.

We would like to thank Devon Brewer and Kristofer Jennings for providing feedback on an earlier version of this manuscript. We would also like to thank Devon Brewer for providing data from his studies on free-lists.

Funding Statement

This project was partially supported by the Agency for Healthcare Research and Quality (R24HS022134). Funding for the original data sets was from the National Science Foundation (#BCS-0244104) for Gravlee et al. (2013), from the National Institute on Drug Abuse (R29DA10640) for Brewer et al. (2002), and from the Air Force Office of Scientific Research for Brewer (1995). Content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

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What is data saturation in qualitative research.

8 min read A crucial milestone in qualitative research, data saturation means you can end the data collection phase and move on to your analysis. Here we explain exactly what it means, the telltale signs that you’ve reached it, and how to get there as efficiently as possible.

Author:  Will Webster

Subject Matter Expert:  Jess Oliveros

Data saturation is a point in data collection when new information no longer brings fresh insights to the research questions.

Reaching data saturation means you’ve collected enough data to confidently understand the patterns and themes within the dataset – you’ve got what you need to draw conclusions and make your points. Think of it like a conversation where everything that can be said has been said, and now it’s just repetition.

Why is data saturation most relevant to qualitative research? Because qualitative research is about understanding something deeply, and you can reach a critical mass when trying to do that. Quantitative research, on the other hand, deals in numbers and with predetermined sample sizes , so the concept of data saturation is less relevant.

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How to know when data saturation is reached

At the point of data saturation, you start to notice that the information you’re collecting is just reinforcing what you already know rather than providing new insights.

Knowing when you’ve reached this point is fairly subjective – there’s no formula or equation that can be applied. But there are some telltale signs that can apply to any qualitative research project .

When one or multiple of these signs are present, it’s a good time to begin finalizing the data collection phase and move on to a more detailed analysis.

Recurring themes

You start to notice that new data doesn’t bring up new themes or ideas. Instead, it echoes what you’ve already recorded.

This is a sign that you’ve likely tapped into all the main ideas related to your research question.

No new data

When interviews or surveys start to feel like you’re reading from the same script with each participant, you’ve probably reached the limit of diversity in responses. New participants will probably only confirm what you already know.

You’ve collected enough instances and evidence for each category of your analysis that you can support each theme with multiple examples. In other words, your data has become saturated with a depth and richness that illustrates each finding.

Full understanding

You reach a level of familiarity with the subject matter that allows you to accurately predict what your participants will say next. If this is the case, you’ve likely reached data saturation.

Consistency

The data starts to show consistent patterns that support a coherent story. Crucially, inconsistencies and outliers don’t challenge your thinking and significantly alter the narrative you’ve formed.

This consistency across the data set strengthens the validity of your findings.

Is data saturation the goal of qualitative research?

In a word, no. But it’s often a critical milestone.

The true goal of qualitative research is to gain a deep understanding of the subject matter; data saturation indicates that you’ve gathered enough information to achieve that understanding.

That said, working to achieve data saturation in the most efficient way possible should be a goal of your research project.

How can a qualitative research project reach data saturation?

Reaching data saturation is a pivotal point in qualitative research as a sign that you’ve generated comprehensive and reliable findings.

There’s no exact science for reaching this point, but it does consistently demand two things: an adequate sample size and well-screened participants.

Adequate sample size

Achieving data saturation in qualitative research heavily relies on determining an appropriate sample size .

This is less about hitting a specific number and more about ensuring that the range of participants is broad enough to capture the diverse perspectives your research needs – while being focused enough to allow for thorough analysis.

Flexibility is crucial in this process. For example, in a study exploring patient experiences in a hospital, starting with a small group of patients from various departments might be the initial plan. However, as the interviews progress, if new themes continue to emerge, it might indicate the need to broaden the sample size to include more patients or even healthcare providers for a more comprehensive understanding.

An iterative approach like this can help your research to capture the complexity of people’s experiences without overwhelming the research with redundant information. The goal is to reach a point where additional interviews yield little new information, signaling that the range of experiences has been adequately captured.

While yes, it’s important to stay flexible and iterate as you go, it’s always wise to make use of research solutions that can make recommendations on suggested sample size . Such tools can also monitor crucial metrics like completion rate and audience size to keep your research project on track to reach data saturation.

Well-screened participants

In qualitative research, the depth and validity of your findings are of course totally influenced by your participants. This is where the importance of well-screened participants becomes very clear.

In any research project that addresses a complex social issue – from public health strategy to educational reform – having participants who can provide a range of lived experiences and viewpoints is crucial. Generating the best result isn’t about finding a random assortment of individuals, but instead about forming a carefully selected research panel whose experiences and perspectives directly relate to the research questions.

Achieving this means looking beyond surface criteria, like age or occupation, and instead delving into qualities that are relevant to the study, like experiences, attitudes or behaviors. This ensures that the data collected is rich and deeply rooted in real-world contexts, and will ultimately set you on a faster route to data saturation.

At the same time, if you find that your participants aren’t providing the depth or range of insights expected, you probably need to reevaluate your screening criteria. It’s unlikely that you’ll get it right first time – as with determining sample size, don’t be afraid of an iterative process.

To expedite this process, researchers can use digital tools to build ever-richer pictures of respondents , driving more targeted research and more tailored interactions.

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What is Data Saturation? Grasp its uses in Qualitative Research

Have you ever wondered what is data saturation? Learn its importance, and how it enhances the trustworthiness of findings.

In the realm of qualitative research, data saturation plays a crucial role in ensuring the validity and trustworthiness of findings. It is a concept that researchers employ to determine the point at which collecting additional data no longer provides new insights or information. In this article, we will delve into the meaning of data saturation, explore its significance in qualitative research, discuss factors influencing saturation, and highlight approaches to measuring and assessing it. By understanding data saturation, researchers can enhance the quality and rigor of their studies.

What is Data Saturation?

Data saturation refers to the point in qualitative research where collecting new data ceases to generate novel insights or themes. It is the stage where researchers achieve a sufficient depth and breadth of information, enabling them to confidently draw conclusions and develop theories from their data. In other words, it represents the saturation of themes or categories within the dataset, indicating that little or no new information is emerging.

Factors Influencing Data Saturation

Several factors influence data saturation in qualitative research. These factors can vary depending on the research context and the nature of the data collected. Some key factors to consider include:

Sample size

The size of the participant sample plays a role in achieving data saturation. Generally, a larger sample size increases the likelihood of reaching saturation as it allows for a wider range of perspectives and experiences to capture.

Data collection methods

The choice of data collection methods, such as interviews, focus groups, or observations, can influence data saturation. Each method has its strengths and limitations in terms of generating rich and diverse data.

Researcher expertise

The knowledge and expertise of the researcher can influence data saturation. A skilled researcher who is well versed in the research topic can recognize patterns and themes more effectively, potentially reaching saturation sooner.

Hybrid Forms of Data Saturation

In some cases, researchers employ hybrid forms of saturation to enhance the validity and reliability of their findings. These approaches involve combining multiple data sources or methods to gather a comprehensive understanding of the research topic. By triangulating data from different sources, such as interviews, observations, and document analysis, researchers can strengthen their conclusions and ensure data saturation from various angles.

When and How to Seek Data Saturation

Seek for Data saturation begins after the collection of a substantial amount of data. Researchers must continuously analyze and interpret the data during the research process to identify emerging themes and to reach saturation. It is important to note that data saturation is not always a predetermined goal but rather a point of confidence where the researcher feels that additional data will not significantly contribute to the findings.

To seek saturation effectively, researchers can:

• Engage in iterative data collection and analysis : Iterative processes of collecting and analyzing data allow researchers to refine their research questions and sampling strategies as new insights emerge. This iterative approach helps in reaching saturation by ensuring that diverse perspectives and experiences are adequately represented.
• Conduct member checks : Member checks involve sharing findings or interpretations with participants to validate the accuracy and comprehensibility of the data. This process helps ensure that the researchers’ understanding aligns with the participants’ experiences, enhancing the trustworthiness of the data.

Measuring Data Saturation

While data saturation is a qualitative concept, researchers often seek ways to measure and demonstrate saturation in their studies. Although there is no standardized method for quantifying saturation, researchers can employ various strategies to provide evidence of saturation:

Theoretical saturation

This approach involves determining saturation based on the degree of theoretical insights obtained from the data. Researchers assess whether the emerging themes and patterns adequately explain the phenomenon under investigation.

Saturation grids or matrices

Researchers can create grids or matrices to track the appearance and recurrence of themes across different data sources. This visual representation allows them to identify when saturation is achieved for specific themes or categories.

Assessing Saturation: Different Approaches

Assessing saturation involves evaluating the quality and sufficiency of the data to draw meaningful conclusions. Researchers can employ different approaches to assess saturation:

Peer debriefing

Researchers can engage in discussions with colleagues or experts in the field to review and validate their interpretations. This external feedback helps ensure that saturation has been adequately achieved and enhances the credibility of the research.

Methodological transparency

Clearly documenting the data collection and analysis processes helps establish the trustworthiness of the findings. Researchers should provide detailed descriptions of the steps taken to reach saturation, allowing others to assess the rigor of the study.

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• Open access
• Published: 13 May 2024

Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes

• Léa Solh Dost   ORCID: orcid.org/0000-0001-5767-1305 1 , 2 ,
• Giacomo Gastaldi   ORCID: orcid.org/0000-0001-6327-7451 3 &
• Marie P. Schneider   ORCID: orcid.org/0000-0002-7557-9278 1 , 2  

BMC Health Services Research volume  24 , Article number:  620 ( 2024 ) Cite this article

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Continuity of care is under great pressure during the transition from hospital to outpatient care. Medication changes during hospitalization may be poorly communicated and understood, compromising patient safety during the transition from hospital to home. The main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Patients with type 2 diabetes, with at least two comorbidities and who returned home after discharge, were recruited during their hospitalization. A descriptive qualitative longitudinal research approach was adopted, with four in-depth semi-structured interviews per participant over a period of two months after discharge. Interviews were based on semi-structured guides, transcribed verbatim, and a thematic analysis was conducted.

Twenty-one participants were included from October 2020 to July 2021. Seventy-five interviews were conducted. Three main themes were identified: (A) Medication management, (B) Medication understanding, and (C) Medication adherence, during three periods: (1) Hospitalization, (2) Care transition, and (3) Outpatient care. Participants had varying levels of need for medication information and involvement in medication management during hospitalization and in outpatient care. The transition from hospital to autonomous medication management was difficult for most participants, who quickly returned to their routines with some participants experiencing difficulties in medication adherence.

Conclusions

The transition from hospital to outpatient care is a challenging process during which discharged patients are vulnerable and are willing to take steps to better manage, understand, and adhere to their medications. The resulting tension between patients’ difficulties with their medications and lack of standardized healthcare support calls for interprofessional guidelines to better address patients’ needs, increase their safety, and standardize physicians’, pharmacists’, and nurses’ roles and responsibilities.

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Introduction

Continuity of patient care is characterized as the collaborative engagement between the patient and their physician-led care team in the ongoing management of healthcare, with the mutual objective of delivering high-quality and cost-effective medical care [ 1 ]. Continuity of care is under great pressure during the transition of care from hospital to outpatient care, with a risk of compromising patients’ safety [ 2 , 3 ]. The early post-discharge period is a high-risk and fragile transition: once discharged, one in five patients experience at least one adverse event during the first three weeks following discharge, and more than half of these adverse events are drug-related [ 4 , 5 ]. A retrospective study examining all discharged patients showed that adverse drug events (ADEs) account for up to 20% of 30-day hospital emergency readmissions [ 6 ]. During hospitalization, patients’ medications are generally modified, with an average of nearly four medication changes per patient [ 7 ]. Information regarding medications such as medication changes, the expected effect, side effects, and instructions for use are frequently poorly communicated to patients during hospitalization and at discharge [ 8 , 9 , 10 , 11 ]. Between 20 and 60% of discharged patients lack knowledge of their medications [ 12 , 13 ]. Consideration of patients’ needs and their active engagement in decision-making during hospitalization regarding their medications are often lacking [ 11 , 14 , 15 ]. This can lead to unsafe discharge and contribute to medication adherence difficulties, such as non-implementation of newly prescribed medications [ 16 , 17 ].

Patients with multiple comorbidities and polypharmacy are at higher risk of ADE [ 18 ]. Type 2 diabetes is one of the chronic health conditions most frequently associated with comorbidities and patients with type 2 diabetes often lack care continuum [ 19 , 20 , 21 ]. The prevalence of patients hospitalized with type 2 diabetes can exceed 40% [ 22 ] and these patients are at higher risk for readmission due to their comorbidities and their medications, such as insulin and oral hypoglycemic agents [ 23 , 24 , 25 ].

Interventions and strategies to improve patient care and safety at transition have shown mixed results worldwide in reducing cost, rehospitalization, ADE, and non-adherence [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. However, interventions that are patient-centered, with a patient follow-up and led by interprofessional healthcare teams showed promising results [ 34 , 35 , 36 ]. Most of these interventions have not been implemented routinely due to the extensive time to translate research into practice and the lack of hybrid implementation studies [ 37 , 38 , 39 , 40 , 41 ]. In addition, patient-reported outcomes and perspectives have rarely been considered, yet patients’ involvement is essential for seamless and integrated care [ 42 , 43 ]. Interprofessional collaboration in which patients are full members of the interprofessional team, is still in its infancy in outpatient care [ 44 ]. Barriers and facilitators regarding medications at the transition of care have been explored in multiple qualitative studies at one given time in a given setting (e.g., at discharge, one-month post-discharge) [ 8 , 45 , 46 , 47 , 48 ]. However, few studies have adopted a holistic methodology from the hospital to the outpatient setting to explore changes in patients’ perspectives over time [ 49 , 50 , 51 ]. Finally, little is known about whether, how, and when patients return to their daily routine following hospitalization and the impact of hospitalization weeks after discharge.

In Switzerland, continuity of care after hospital discharge is still poorly documented, both in terms of contextual analysis and interventional studies, and is mainly conducted in the hospital setting [ 31 , 35 , 52 , 53 , 54 , 55 , 56 ]. The first step of an implementation science approach is to perform a contextual analysis to set up effective interventions adapted to patients’ needs and aligned to healthcare professionals’ activities in a specific context [ 41 , 57 ]. Therefore, the main aims of this study were to investigate the perspectives of patients with type 2 diabetes and multimorbidities on their medications from hospital discharge to outpatient care, and on their healthcare journey through the outpatient healthcare system. In this article, we present the results focusing on patients’ perspectives of their medications from hospital to two months after discharge.

Study design

This qualitative longitudinal study, conducted from October 2020 to July 2021, used a qualitative descriptive methodology through four consecutive in-depth semi-structured interviews per participant at three, 10-, 30- and 60-days post-discharge, as illustrated in Fig.  1 . Longitudinal qualitative research is characterized by qualitative data collection at different points in time and focuses on temporality, such as time and change [ 58 , 59 ]. Qualitative descriptive studies aim to explore and describe the depth and complexity of human experiences or phenomena [ 60 , 61 , 62 ]. We focused our qualitative study on the 60 first days after discharge as this period is considered highly vulnerable and because studies often use 30- or 60-days readmission as an outcome measure [ 5 , 63 ].

This qualitative study follows the Consolidated Criteria for Reporting Qualitative Research (COREQ). Ethics committee approval was sought and granted by the Cantonal Research Ethics Commission, Geneva (CCER) (2020 − 01779).

Recruitment took place during participants’ hospitalization in the general internal medicine divisions at the Geneva University Hospitals in the canton of Geneva (500 000 inhabitants), Switzerland. Interviews took place at participants’ homes, in a private office at the University of Geneva, by telephone or by secure video call, according to participants’ preference. Informal caregivers could also participate alongside the participants.

Study flowchart

Researcher characteristics

All the researchers were trained in qualitative studies. The diabetologist and researcher (GG) who enrolled the patients in the study was involved directly or indirectly (advice asked to the Geneva University Hospital diabetes team of which he was a part) for most participants’ care during hospitalization. LS (Ph.D. student and community pharmacist) was unknown to participants and presented herself during hospitalization as a “researcher” and not as a healthcare professional to avoid any risk of influencing participants’ answers. This study was not interventional, and the interviewer (LS) invited participants to contact a healthcare professional for any questions related to their medication or medical issues.

Population and sampling strategy

Patients with type 2 diabetes were chosen as an example population to describe polypharmacy patients as these patients usually have several health issues and polypharmacy [ 20 , 22 , 25 ]. Inclusions criteria for the study were: adult patients with type 2 diabetes, with at least two other comorbidities, hospitalized for at least three days in a general internal medicine ward, with a minimum of one medication change during hospital stay, and who self-managed their medications once discharged home. Exclusion criteria were patients not reachable by telephone following discharge, unable to give consent (patients with schizophrenia, dementia, brain damage, or drug/alcohol misuse), and who could not communicate in French. A purposive sampling methodology was applied aiming to include participants with different ages, genders, types, and numbers of health conditions by listing participants’ characteristics in a double-entry table, available in Supplementary Material 1 , until thematic saturation was reached. Thematic saturation was considered achieved when no new code or theme emerged and new data repeated previously coded information [ 64 ]. The participants were identified if they were hospitalized in the ward dedicated to diabetes care or when the diabetes team was contacted for advice. The senior ward physician (GG) screened eligible patients and the interviewer (LS) obtained written consent before hospital discharge.

Data collection and instruments

Sociodemographic (age, gender, educational level, living arrangement) and clinical characteristics (reason for hospitalization, date of admission, health conditions, diabetes diagnosis, medications before and during hospitalization) were collected by interviewing participants before their discharge and by extracting participants’ data from electronic hospital files by GG and LS. Participants’ pharmacies were contacted with the participant’s consent to obtain medication records from the last three months if information regarding medications before hospitalization was missing in the hospital files.

Semi-structured interview guides for each interview (at three, 10-, 30- and 60-days post-discharge) were developed based on different theories and components of health behavior and medication adherence: the World Health Organization’s (WHO) five dimensions for adherence, the Information-Motivation-Behavioral skills model and the Social Cognitive Theory [ 65 , 66 , 67 ]. Each interview explored participants’ itinerary in the healthcare system and their perspectives on their medications. Regarding medications, the following themes were mentioned at each interview: changes in medications, patients’ understanding and implication; information on their medications, self-management of their medications, and patients’ medication adherence. Other aspects were mentioned in specific interviews: patients’ hospitalization and experience on their return home (interview 1), motivation (interviews 2 and 4), and patient’s feedback on the past two months (interview 4). Interview guides translated from French are available in Supplementary Material 2 . The participants completed self-reported and self-administrated questionnaires at different interviews to obtain descriptive information on different factors that may affect medication management and adherence: self-report questionnaires on quality of life (EQ-5D-5 L) [ 68 ], literacy (Schooling-Opinion-Support questionnaire) [ 69 ], medication adherence (Adherence Visual Analogue Scale, A-VAS) [ 70 ] and Belief in Medication Questionnaire (BMQ) [ 71 ] were administered to each participant at the end of selected interviews to address the different factors that may affect medication management and adherence as well as to determine a trend of determinants over time. The BMQ contains two subscores: Specific-Necessity and Specific-Concerns, addressing respectively their perceived needs for their medications, and their concerns about adverse consequences associated with taking their medication [ 72 ].

Data management

Informed consent forms, including consent to obtain health data, were securely stored in a private office at the University of Geneva. The participants’ identification key was protected by a password known only by MS and LS. Confidentiality was guaranteed by pseudonymization of participants’ information and audio-recordings were destroyed once analyzed. Sociodemographic and clinical characteristics, medication changes, and answers to questionnaires were securely collected by electronic case report forms (eCRFs) on RedCap®. Interviews were double audio-recorded and field notes were taken during interviews. Recorded interviews were manually transcribed verbatim in MAXQDA® (2018.2) by research assistants and LS and transcripts were validated for accuracy by LS. A random sample of 20% of questionnaires was checked for accuracy for the transcription from the paper questionnaires to the eCRFs. Recorded sequences with no link to the discussed topics were not transcribed and this was noted in the transcripts.

Data analysis

A descriptive statistical analysis of sociodemographic, clinical characteristics and self-reported questionnaire data was carried out. A thematic analysis of transcripts was performed, as described by Braun and Clarke [ 73 ], by following six steps: raw data was read, text segments related to the study objectives were identified, text segments to create new categories were identified, similar or redundant categories were reduced and a model that integrated all significant categories was created. The analysis was conducted in parallel with patient enrolment to ensure data saturation. To ensure the validity of the coding method, transcripts were double coded independently and discussed by the research team until similar themes were obtained. The research group developed and validated an analysis grid, with which LS coded systematically the transcriptions and met regularly with the research team to discuss questions on data analysis and to ensure the quality of coding. The analysis was carried out in French, and the verbatims of interest cited in the manuscript were translated and validated by a native English-speaking researcher to preserve the meaning.

In this analysis, we used the term “healthcare professionals” when more than one profession could be involved in participants’ medication management. Otherwise, when a specific healthcare professional was involved, we used the designated profession (e.g. physicians, pharmacists).

Patient and public involvement

During the development phase of the study, interview guides and questionnaires were reviewed for clarity and validity and adapted by two patient partners, with multiple health conditions and who experienced previously a hospital discharge. They are part of the HUG Patients Partners + 3P platform for research and patient and public involvement.

Interviews and participants’ descriptions

A total of 75 interviews were conducted with 21 participants. In total, 31 patients were contacted, seven refused to participate (four at the project presentation and three at consent), two did not enter the selection criteria at discharge and one was unreachable after discharge. Among the 21 participants, 15 participated in all interviews, four in three interviews, one in two interviews, and one in one interview, due to scheduling constraints. Details regarding interviews and participants characteristics are presented in Tables  1 and 2 .

The median length of time between hospital discharge and interviews 1,2,3 and 4 was 5 (IQR: 4–7), 14 (13-20), 35 (22-38), and 63 days (61-68), respectively. On average, by comparing medications at hospital admission and discharge, a median of 7 medication changes (IQR: 6–9, range:2;17) occurred per participant during hospitalization and a median of 7 changes (5–12) during the two months following discharge. Details regarding participants’ medications are described in Table  3 .

Patient self-reported adherence over the past week for their three most challenging medications are available in Supplementary Material 3 .

Qualitative analysis

We defined care transition as the period from discharge until the first medical appointment post-discharge, and outpatient care as the period starting after the first medical appointment. Data was organized into three key themes (A. Medication management, B. Medication understanding, and C. Medication adherence) divided into subthemes at three time points (1. Hospitalization, 2. Care transition and 3. Outpatient care). Figure  2 summarizes and illustrates the themes and subthemes with their influencing factors as bullet points.

Participants’ medication management, understanding and adherence during hospitalization, care transition and outpatient care

A. Medication management

A.1 medication management during hospitalization: medication management by hospital staff.

Medications during hospitalization were mainly managed by hospital healthcare professionals (i.e. nurses and physicians) with varying degrees of patient involvement: “At the hospital, they prepared the medications for me. […] I didn’t even know what the packages looked like.” Participant 22; interview 1 (P22.1) Some participants reported having therapeutic education sessions with specialized nurses and physicians, such as the explanation and demonstration of insulin injection and glucose monitoring. A patient reported that he was given the choice of several treatments and was involved in shared decision-making. Other participants had an active role in managing and optimizing dosages, such as rapid insulin, due to prior knowledge and use of medications before hospitalization.

A.2 Medication management at transition: obtaining the medication and initiating self-management

Once discharged, some participants had difficulties obtaining their medications at the pharmacy because some medications were not stored and had to be ordered, delaying medication initiation. To counter this problem upstream, a few participants were provided a 24-to-48-hour supply of medications at discharge. It was sometimes requested by the patient or suggested by the healthcare professionals but was not systematic. The transition from medication management by hospital staff to self-management was exhausting for most participants who were faced with a large amount of new information and changes in their medications: “ When I was in the hospital, I didn’t even realize all the changes. When I came back home, I took away the old medication packages and got out the new ones. And then I thought : « my God, all this…I didn’t know I had all these changes » ” P2.1 Written documentation, such as the discharge prescription or dosage labels on medication packages, was helpful in managing their medication at home. Most participants used weekly pill organizers to manage their medications, which were either already used before hospitalization or were introduced post-discharge. The help of a family caregiver in managing and obtaining medications was reported as a facilitator.

A.3 Medication management in outpatient care: daily self-management and medication burden

A couple of days or weeks after discharge, most participants had acquired a routine so that medication management was less demanding, but the medication burden varied depending on the participants. For some, medication management became a simple action well implemented in their routine (“It has become automatic” , P23.4), while for others, the number of medications and the fact that the medications reminded them of the disease was a heavy burden to bear on a daily basis (“ During the first few days after getting out of the hospital, I thought I was going to do everything right. In the end, well [laughs] it’s complicated. I ended up not always taking the medication, not monitoring the blood sugar” P12.2) To support medication self-management, some participants had written documentation such as treatment plans, medication lists, and pictures of their medication packages on their phones. Some participants had difficulties obtaining medications weeks after discharge as discharge prescriptions were not renewable and participants did not see their physician in time. Others had to visit multiple physicians to have their prescriptions updated. A few participants were faced with prescription or dispensing errors, such as prescribing or dispensing the wrong dosage, which affected medication management and decreased trust in healthcare professionals. In most cases, according to participants, the pharmacy staff worked in an interprofessional collaboration with physicians to provide new and updated prescriptions.

B. Medication understanding

B.1 medication understanding during hospitalization: new information and instructions.

The amount of information received during hospitalization varied considerably among participants with some reporting having received too much, while others saying they received too little information regarding medication changes, the reason for changes, or for introducing new medications: “They told me I had to take this medication all my life, but they didn’t tell me what the effects were or why I was taking it.” P5.3

Hospitalization was seen by some participants as a vulnerable and tiring period during which they were less receptive to information. Information and explanations were generally given verbally, making it complicated for most participants to recall it. Some participants reported that hospital staff was attentive to their needs for information and used communication techniques such as teach-back (a way of checking understanding by asking participants to say in their own words what they need to know or do about their health or medications). Some participants were willing to be proactive in the understanding of their medications while others were more passive, had no specific needs for information, and did not see how they could be engaged more.

B.2 Medication understanding at transition: facing medication changes

At hospital discharge, the most challenging difficulty for participants was to understand the changes made regarding their medications. For newly diagnosed participants, the addition of new medications was more difficult to understand, whereas, for experienced participants, changes in known medications such as dosage modification, changes within a therapeutic class, and generic substitutions were the most difficult to understand. Not having been informed about changes caused confusion and misunderstanding. Therefore, medication reconciliation done by the patient was time-consuming, especially for participants with multiple medications: “ They didn’t tell me at all that they had changed my treatment completely. They just told me : « We’ve changed a few things. But it was the whole treatment ». ” P2.3 Written information, such as the discharge prescription, the discharge report (brief letter summarizing information about the hospitalization, given to the patient at discharge), or the label on the medication box (written by the pharmacist with instructions on dosage) helped them find or recall information about their medications and diagnoses. However, technical terms were used in hospital documentations and were not always understandable. For example, this participant said: “ On the prescription of valsartan, they wrote: ‘resume in the morning once profile…’[once hypertension profile allows]… I don’t know what that means.” P8.1 In addition, some documents were incomplete, as mentioned by a patient who did not have the insulin dosage mentioned on the hospital prescription. Some participants sought help from healthcare professionals, such as pharmacists, hospital physicians, or general practitioners a few days after discharge to review medications, answer questions, or obtain additional information.

B.3 Medication understanding in the outpatient care: concerns and knowledge

Weeks after discharge, most participants had concerns about the long-term use of their medications, their usefulness, and the possible risk of interactions or side effects. Some participants also reported having some lack of knowledge regarding indications, names, or how the medication worked: “I don’t even know what Brilique® [ticagrelor, antiplatelet agent] is for. It’s for blood pressure, isn’t it?. I don’t know.” P11.4 According to participants, the main reasons for the lack of understanding were the lack of information at the time of prescribing and the large number of medications, making it difficult to search for information and remember it. Participants sought information from different healthcare professionals or by themselves, on package inserts, through the internet, or from family and friends. Others reported having had all the information needed or were not interested in having more information. In addition, participants with low medication literacy, such as non-native speakers or elderly people, struggled more with medication understanding and sought help from family caregivers or healthcare professionals, even weeks after discharge: “ I don’t understand French very well […] [The doctor] explained it very quickly…[…] I didn’t understand everything he was saying” P16.2

C. Medication adherence

C.2 medication adherence at transition: adopting new behaviors.

Medication adherence was not mentioned as a concern during hospitalization and a few participants reported difficulties in medication initiation once back home: “I have an injection of Lantus® [insulin] in the morning, but obviously, the first day [after discharge], I forgot to do it because I was not used to it.” P23.1 Participants had to quickly adopt new behaviors in the first few days after discharge, especially for participants with few medications pre-hospitalization. The use of weekly pill organizers, alarms and specific storage space were reported as facilitators to support adherence. One patient did not initiate one of his medications because he did not understand the medication indication, and another patient took her old medications because she was used to them. Moreover, most participants experienced their hospitalization as a turning point, a time when they focused on their health, thought about the importance of their medications, and discussed any new lifestyle or dietary measures that might be implemented.

C.3 Medication adherence in outpatient care: ongoing medication adherence

More medication adherence difficulties appeared a few weeks after hospital discharge when most participants reported nonadherence behaviors, such as difficulties implementing the dosage regimen, or intentionally discontinuing the medication and modifying the medication regimen on their initiative. Determinants positively influencing medication adherence were the establishment of a routine; organizing medications in weekly pill-organizers; organizing pocket doses (medications for a short period that participants take with them when away from home); seeking support from family caregivers; using alarm clocks; and using specific storage places. Reasons for nonadherence were changes in daily routine; intake times that were not convenient for the patient; the large number of medications; and poor knowledge of the medication or side effects. Healthcare professionals’ assistance for medication management, such as the help of home nurses or pharmacists for the preparation of weekly pill-organizers, was requested by participants or offered by healthcare professionals to support medication adherence: “ I needed [a home nurse] to put my pills in the pillbox. […] I felt really weak […] and I was making mistakes. So, I’m very happy [the doctor] offered me [home care]. […] I have so many medications.” P22.3 Some participants who experienced prehospitalization non-adherence were more aware of their non-adherence and implemented strategies, such as modifying the timing of intake: “I said to my doctor : « I forget one time out of two […], can I take them in the morning? » We looked it up and yes, I can take it in the morning.” P11.2 In contrast, some participants were still struggling with adherence difficulties that they had before hospitalization. Motivations for taking medications two months after discharge were to improve health, avoid complications, reduce symptoms, reduce the number of medications in the future or out of obligation: “ I force myself to take them because I want to get to the end of my diabetes, I want to reduce the number of pills as much as possible.” P14.2 After a few weeks post-hospitalization, for some participants, health and illness were no longer the priority because of other life imperatives (e.g., family or financial situation).

This longitudinal study provided a multi-faceted representation of how patients manage, understand, and adhere to their medications from hospital discharge to two months after discharge. Our findings highlighted the varying degree of participants’ involvement in managing their medications during their hospitalization, the individualized needs for information during and after hospitalization, the complicated transition from hospital to autonomous medication management, the adaptation of daily routines around medication once back home, and the adherence difficulties that surfaced in the outpatient care, with nonadherence prior to hospitalization being an indicator of the behavior after discharge. Finally, our results confirmed the lack of continuity in care and showed the lack of patient care standardization experienced by the participants during the transition from hospital to outpatient care.

This in-depth analysis of patients’ experiences reinforces common challenges identified in the existing literature such as the lack of personalized information [ 9 , 10 , 11 ], loss of autonomy during hospitalization [ 14 , 74 , 75 ], difficulties in obtaining medication at discharge [ 11 , 45 , 76 ] and challenges in understanding treatment modifications and generics substitution [ 11 , 32 , 77 , 78 ]. Some of these studies were conducted during patients’ hospitalization [ 10 , 75 , 79 ] or up to 12 months after discharge [ 80 , 81 ], but most studies focused on the few days following hospital discharge [ 9 , 11 , 14 , 82 ]. Qualitative studies on medications at transition often focused on a specific topic, such as medication information, or a specific moment in time, and often included healthcare professionals, which muted patients’ voices [ 9 , 10 , 11 , 47 , 49 ]. Our qualitative longitudinal methodology was interested in capturing the temporal dynamics, in-depth narratives, and contextual nuances of patients’ medication experiences during transitions of care [ 59 , 83 ]. This approach provided a comprehensive understanding of how patients’ perspectives and behaviors evolved over time, offering insights into the complex interactions of medication management, understanding and adherence, and turning points within their medication journeys. A qualitative longitudinal design was used by Fylan et al. to underline patients’ resilience in medication management during and after discharge, by Brandberg et al. to show the dynamic process of self-management during the 4 weeks post-discharge and by Lawton et al. to examine how patients with type 2 diabetes perceived their care after discharge over a period of four years [ 49 , 50 , 51 ]. Our study focused on the first two months following hospitalization and future studies should focus on following discharged and at-risk patients over a longer period, as “transitions of care do not comprise linear trajectories of patients’ movements, with a starting and finishing point. Instead, they are endless loops of movements” [ 47 ].

Our results provide a particularly thorough description of how participants move from a state of total dependency during hospitalization regarding their medication management to a sudden and complete autonomy after hospital discharge impacting medication management, understanding, and adherence in the first days after discharge for some participants. Several qualitative studies have described the lack of shared decision-making and the loss of patient autonomy during hospitalization, which had an impact on self-management and created conflicts with healthcare professionals [ 75 , 81 , 84 ]. Our study also highlights nuanced patient experiences, including varying levels of patient needs, involvement, and proactivity during hospitalization and outpatient care, and our results contribute to capturing different perspectives that contrast with some literature that often portrays patients as more passive recipients of care [ 14 , 15 , 74 , 75 ]. Shared decision-making and proactive medication are key elements as they contribute to a smoother transition and better outcomes for patients post-discharge [ 85 , 86 , 87 ].

Consistent with the literature, the study identifies some challenges in medication initiation post-discharge [ 16 , 17 , 88 ] but our results also describe how daily routine rapidly takes over, either solidifying adherence behavior or generating barriers to medication adherence. Participants’ nonadherence prior to hospitalization was a factor influencing participants’ adherence post-hospitalization and this association should be further investigated, as literature showed that hospitalized patients have high scores of non-adherence [ 89 ]. Mortel et al. showed that more than 20% of discharged patients stopped their medications earlier than agreed with the physician and 25% adapted their medication intake [ 90 ]. Furthermore, patients who self-managed their medications had a lower perception of the necessity of their medication than patients who received help, which could negatively impact medication adherence [ 91 ]. Although participants in our study had high BMQ scores for necessity and lower scores for concerns, some participants expressed doubts about the need for their medications and a lack of motivation a few weeks after discharge. Targeted pharmacy interventions for newly prescribed medications have been shown to improve medication adherence, and hospital discharge is an opportune moment to implement this service [ 92 , 93 ].

Many medication changes were made during the transition of care (a median number of 7 changes during hospitalization and 7 changes during the two months after discharge), especially medication additions during hospitalization and interruptions after hospitalization. While medication changes during hospitalization are well described, the many changes following discharge are less discussed [ 7 , 94 ]. A Danish study showed that approximately 65% of changes made during hospitalization were accepted by primary healthcare professionals but only 43% of new medications initiated during hospitalization were continued after discharge [ 95 ]. The numerous changes after discharge may be caused by unnecessary intensification of medications during hospitalization, delayed discharge letters, lack of standardized procedures, miscommunication, patient self-management difficulties, or in response to an acute situation [ 96 , 97 , 98 ]. During the transition of care, in our study, both new and experienced participants were faced with difficulties in managing and understanding medication changes, either for newly prescribed medication or changes in previous medications. Such difficulties corroborate the findings of the literature [ 9 , 10 , 47 ] and our results showed that the lack of understanding during hospitalization led to participants having questions about their medications, even weeks after discharge. Particular attention should be given to patients’ understanding of medication changes jointly by physicians, nurses and pharmacists during the transition of care and in the months that follow as medications are likely to undergo as many changes as during hospitalization.

Implication for practice and future research

The patients’ perspectives in this study showed, at a system level, that there was a lack of standardization in healthcare professional practices regarding medication dispensing and follow-up. For now, in Switzerland, there are no official guidelines on medication prescription and dispensation during the transition of care although some international guidelines have been developed for outpatient healthcare professionals [ 3 , 99 , 100 , 101 , 102 ]. Here are some suggestions for improvement arising from our results. Patients should be included as partners and healthcare professionals should systematically assess (i) previous medication adherence, (ii) patients’ desired level of involvement and (iii) their needs for information during hospitalization. Hospital discharge processes should be routinely implemented to standardize hospital discharge preparation, medication prescribing, and dispensing. Discharge from the hospital should be planned with community pharmacies to ensure that all medications are available and, if necessary, doses of medications should be supplied by the hospital to bridge the gap. A partnership with outpatient healthcare professionals, such as general practitioners, community pharmacists, and homecare nurses, should be set up for effective asynchronous interprofessional collaboration to consolidate patients’ medication management, knowledge, and adherence, as well as to monitor signs of deterioration or adverse drug events.

Future research should consolidate our first attempt to develop a framework to better characterize medication at the transition of care, using Fig. 2   as a starting point. Contextualized interventions, co-designed by health professionals, patients and stakeholders, should be tested in a hybrid implementation study to test the implementation and effectiveness of the intervention for the health system [ 103 ].

Limitations

This study has some limitations. First, the transcripts were validated for accuracy by the interviewer but not by a third party, which could have increased the robustness of the transcription. Nevertheless, the interviewer followed all methodological recommendations for transcription. Second, patient inclusion took place during the COVID-19 pandemic, which may have had an impact on patient care and the availability of healthcare professionals. Third, we cannot guarantee the accuracy of some participants’ medication history before hospitalization, even though we contacted the participants’ main pharmacy, as participants could have gone to different pharmacies to obtain their medications. Fourth, our findings may not be generalizable to other populations and other healthcare systems because some issues may be specific to multimorbid patients with type 2 diabetes or to the Swiss healthcare setting. Nevertheless, issues encountered by our participants regarding their medications correlate with findings in the literature. Fifth, only 15 out of 21 participants took part in all the interviews, but most participants took part in at least three interviews and data saturation was reached. Lastly, by its qualitative and longitudinal design, it is possible that the discussion during interviews and participants’ reflections between interviews influenced participants’ management, knowledge, and adherence, even though this study was observational, and no advice or recommendations were given by the interviewer during interviews.

Discharged patients are willing to take steps to better manage, understand, and adhere to their medications, yet they are also faced with difficulties in the hospital and outpatient care. Furthermore, extensive changes in medications not only occur during hospitalization but also during the two months following hospital discharge, for which healthcare professionals should give particular attention. The different degrees of patients’ involvement, needs and resources should be carefully considered to enable them to better manage, understand and adhere to their medications. At a system level, patients’ experiences revealed a lack of standardization of medication practices during the transition of care. The healthcare system should provide the ecosystem needed for healthcare professionals responsible for or involved in the management of patients’ medications during the hospital stay, discharge, and outpatient care to standardize their practices while considering the patient as an active partner.

Data availability

The anonymized quantitative survey datasets and the qualitative codes are available in French from the corresponding author on reasonable request.

Abbreviations

adverse drug events

Adherence Visual Analogue Scale

Belief in Medication Questionnaire

Consolidated Criteria for Reporting Qualitative Research

case report form

standard deviation

World Health Organization

American Academy of Family Physician. Continuity of Care, Definition of 2020. Accessed 10 July 2022 https://www.aafp.org/about/policies/all/continuity-of-care-definition.html

Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–41.

Article   CAS   PubMed   Google Scholar  

World Health Organization (WHO). Medication Safety in Transitions of Care. 2019.

Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161–7.

Article   PubMed   Google Scholar  

Krumholz HM. Post-hospital syndrome–an acquired, transient condition of generalized risk. N Engl J Med. 2013;368(2):100–2.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Banholzer S, Dunkelmann L, Haschke M, Derungs A, Exadaktylos A, Krähenbühl S, et al. Retrospective analysis of adverse drug reactions leading to short-term emergency hospital readmission. Swiss Med Wkly. 2021;151:w20400.

Blozik E, Signorell A, Reich O. How does hospitalization affect continuity of drug therapy: an exploratory study. Ther Clin Risk Manag. 2016;12:1277–83.

Article   PubMed   PubMed Central   Google Scholar  

Allen J, Hutchinson AM, Brown R, Livingston PM. User experience and care for older people transitioning from hospital to home: patients’ and carers’ perspectives. Health Expect. 2018;21(2):518–27.

Daliri S, Bekker CL, Buurman BM, Scholte Op Reimer WJM, van den Bemt BJF, Karapinar-Çarkit F. Barriers and facilitators with medication use during the transition from hospital to home: a qualitative study among patients. BMC Health Serv Res. 2019;19(1):204.

Bekker CL, Mohsenian Naghani S, Natsch S, Wartenberg NS, van den Bemt BJF. Information needs and patient perceptions of the quality of medication information available in hospitals: a mixed method study. Int J Clin Pharm. 2020;42(6):1396–404.

Foulon V, Wuyts J, Desplenter F, Spinewine A, Lacour V, Paulus D, et al. Problems in continuity of medication management upon transition between primary and secondary care: patients’ and professionals’ experiences. Acta Clin Belgica: Int J Clin Lab Med. 2019;74(4):263–71.

Article   Google Scholar  

Micheli P, Kossovsky MP, Gerstel E, Louis-Simonet M, Sigaud P, Perneger TV, et al. Patients’ knowledge of drug treatments after hospitalisation: the key role of information. Swiss Med Wkly. 2007;137(43–44):614–20.

PubMed   Google Scholar  

Ziaeian B, Araujo KL, Van Ness PH, Horwitz LI. Medication reconciliation accuracy and patient understanding of intended medication changes on hospital discharge. J Gen Intern Med. 2012;27(11):1513–20.

Allen J, Hutchinson AM, Brown R, Livingston PM. User experience and care integration in Transitional Care for older people from hospital to home: a Meta-synthesis. Qual Health Res. 2016;27(1):24–36.

Mackridge AJ, Rodgers R, Lee D, Morecroft CW, Krska J. Cross-sectional survey of patients’ need for information and support with medicines after discharge from hospital. Int J Pharm Pract. 2018;26(5):433–41.

Mulhem E, Lick D, Varughese J, Barton E, Ripley T, Haveman J. Adherence to medications after hospital discharge in the elderly. Int J Family Med. 2013;2013:901845.

Fallis BA, Dhalla IA, Klemensberg J, Bell CM. Primary medication non-adherence after discharge from a general internal medicine service. PLoS ONE. 2013;8(5):e61735.

Zhou L, Rupa AP. Categorization and association analysis of risk factors for adverse drug events. Eur J Clin Pharmacol. 2018;74(4):389–404.

Moreau-Gruet F. La multimorbidité chez les personnes de 50 ans et plus. Résultats basés sur l’enqête SHARE (Survey of Health, Ageing and Retirement in Europe. Obsan Bulletin 4/2013. 2013(Neuchâtel: OBservatoire suisse de la santé).

Iglay K, Hannachi H, Joseph Howie P, Xu J, Li X, Engel SS, et al. Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus. Curr Med Res Opin. 2016;32(7):1243–52.

Sibounheuang P, Olson PS, Kittiboonyakun P. Patients’ and healthcare providers’ perspectives on diabetes management: a systematic review of qualitative studies. Res Social Adm Pharm. 2020;16(7):854–74.

Müller-Wieland D, Merkel M, Hamann A, Siegel E, Ottillinger B, Woker R, et al. Survey to estimate the prevalence of type 2 diabetes mellitus in hospital patients in Germany by systematic HbA1c measurement upon admission. Int J Clin Pract. 2018;72(12):e13273.

Blanc AL, Fumeaux T, Stirnemann J, Dupuis Lozeron E, Ourhamoune A, Desmeules J, et al. Development of a predictive score for potentially avoidable hospital readmissions for general internal medicine patients. PLoS ONE. 2019;14(7):e0219348.

Hansen LO, Greenwald JL, Budnitz T, Howell E, Halasyamani L, Maynard G, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8):421–7.

Khalid JM, Raluy-Callado M, Curtis BH, Boye KS, Maguire A, Reaney M. Rates and risk of hospitalisation among patients with type 2 diabetes: retrospective cohort study using the UK General Practice Research Database linked to English Hospital Episode statistics. Int J Clin Pract. 2014;68(1):40–8.

Lussier ME, Evans HJ, Wright EA, Gionfriddo MR. The impact of community pharmacist involvement on transitions of care: a systematic review and meta-analysis. J Am Pharm Assoc. 2020;60(1):153–.

van der Heijden A, de Bruijne MC, Nijpels G, Hugtenburg JG. Cost-effectiveness of a clinical medication review in vulnerable older patients at hospital discharge, a randomized controlled trial. Int J Clin Pharm. 2019;41(4):963–71.

Bingham J, Campbell P, Schussel K, Taylor AM, Boesen K, Harrington A, et al. The Discharge Companion Program: an interprofessional collaboration in Transitional Care Model Delivery. Pharm (Basel). 2019;7(2):68.

Google Scholar  

Farris KB, Carter BL, Xu Y, Dawson JD, Shelsky C, Weetman DB, et al. Effect of a care transition intervention by pharmacists: an RCT. BMC Health Serv Res. 2014;14:406.

Meslot C, Gauchet A, Hagger MS, Chatzisarantis N, Lehmann A, Allenet B. A Randomised Controlled Trial to test the effectiveness of planning strategies to improve Medication Adherence in patients with Cardiovascular Disease. Appl Psychol Health Well Being. 2017;9(1):106–29.

Garnier A, Rouiller N, Gachoud D, Nachar C, Voirol P, Griesser AC, et al. Effectiveness of a transition plan at discharge of patients hospitalized with heart failure: a before-and-after study. ESC Heart Fail. 2018;5(4):657–67.

Daliri S, Bekker CL, Buurman BM, Scholte Op Reimer WJM, van den Bemt BJF, Karapinar-Çarkit F. Medication management during transitions from hospital to home: a focus group study with hospital and primary healthcare providers in the Netherlands. Int J Clin Pharm. 2020.

Hansen LO, Young RS, Hinami K, Leung A, Williams MV. Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520–8.

Leppin AL, Gionfriddo MR, Kessler M, Brito JP, Mair FS, Gallacher K, et al. Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials. JAMA Intern Med. 2014;174(7):1095–107.

Donzé J, John G, Genné D, Mancinetti M, Gouveia A, Méan M et al. Effects of a Multimodal Transitional Care Intervention in patients at high risk of readmission: the TARGET-READ Randomized Clinical Trial. JAMA Intern Med. 2023.

Rodrigues CR, Harrington AR, Murdock N, Holmes JT, Borzadek EZ, Calabro K, et al. Effect of pharmacy-supported transition-of-care interventions on 30-Day readmissions: a systematic review and Meta-analysis. Ann Pharmacother. 2017;51(10):866–89.

Lam MYY, Dodds LJ, Corlett SA. Engaging patients to access the community pharmacy medicine review service after discharge from hospital: a cross-sectional study in England. Int J Clin Pharm. 2019;41(4):1110–7.

Hossain LN, Fernandez-Llimos F, Luckett T, Moullin JC, Durks D, Franco-Trigo L, et al. Qualitative meta-synthesis of barriers and facilitators that influence the implementation of community pharmacy services: perspectives of patients, nurses and general medical practitioners. BMJ Open. 2017;7(9):e015471.

En-Nasery-de Heer S, Uitvlugt EB, Bet PM, van den Bemt BJF, Alai A, van den Bemt P et al. Implementation of a pharmacist-led transitional pharmaceutical care programme: process evaluation of medication actions to reduce hospital admissions through a collaboration between Community and Hospital pharmacists (MARCH). J Clin Pharm Ther. 2022.

Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J R Soc Med. 2011;104(12):510–20.

De Geest S, Zúñiga F, Brunkert T, Deschodt M, Zullig LL, Wyss K, et al. Powering Swiss health care for the future: implementation science to bridge the valley of death. Swiss Med Wkly. 2020;150:w20323.

Noonan VK, Lyddiatt A, Ware P, Jaglal SB, Riopelle RJ, Bingham CO 3, et al. Montreal Accord on patient-reported outcomes (PROs) use series - paper 3: patient-reported outcomes can facilitate shared decision-making and guide self-management. J Clin Epidemiol. 2017;89:125–35.

Hesselink G, Schoonhoven L, Barach P, Spijker A, Gademan P, Kalkman C, et al. Improving patient handovers from hospital to primary care: a systematic review. Ann Intern Med. 2012;157(6):417–28.

(OFSP) Interprofessionnalité dans le domaine de la santé Soins ambulatoire. Accessed 4 January 2024. https://www.bag.admin.ch/bag/fr/home/strategie-und-politik/nationale-gesundheitspolitik/foerderprogramme-der-fachkraefteinitiative-plus/foerderprogramme-interprofessionalitaet.html

Mitchell SE, Laurens V, Weigel GM, Hirschman KB, Scott AM, Nguyen HQ, et al. Care transitions from patient and caregiver perspectives. Ann Fam Med. 2018;16(3):225–31.

Davoody N, Koch S, Krakau I, Hägglund M. Post-discharge stroke patients’ information needs as input to proposing patient-centred eHealth services. BMC Med Inf Decis Mak. 2016;16:66.

Ozavci G, Bucknall T, Woodward-Kron R, Hughes C, Jorm C, Joseph K, et al. A systematic review of older patients’ experiences and perceptions of communication about managing medication across transitions of care. Res Social Adm Pharm. 2021;17(2):273–91.

Fylan B, Armitage G, Naylor D, Blenkinsopp A. A qualitative study of patient involvement in medicines management after hospital discharge: an under-recognised source of systems resilience. BMJ Qual Saf. 2018;27(7):539–46.

Fylan B, Marques I, Ismail H, Breen L, Gardner P, Armitage G, et al. Gaps, traps, bridges and props: a mixed-methods study of resilience in the medicines management system for patients with heart failure at hospital discharge. BMJ Open. 2019;9(2):e023440.

Brandberg C, Ekstedt M, Flink M. Self-management challenges following hospital discharge for patients with multimorbidity: a longitudinal qualitative study of a motivational interviewing intervention. BMJ Open. 2021;11(7):e046896.

Lawton J, Rankin D, Peel E, Douglas M. Patients’ perceptions and experiences of transitions in diabetes care: a longitudinal qualitative study. Health Expect. 2009;12(2):138–48.

Mabire C, Bachnick S, Ausserhofer D, Simon M. Patient readiness for hospital discharge and its relationship to discharge preparation and structural factors: a cross-sectional study. Int J Nurs Stud. 2019;90:13–20.

Meyers DC, Durlak JA, Wandersman A. The quality implementation framework: a synthesis of critical steps in the implementation process. Am J Community Psychol. 2012;50(3–4):462–80.

Meyer-Massetti C, Hofstetter V, Hedinger-Grogg B, Meier CR, Guglielmo BJ. Medication-related problems during transfer from hospital to home care: baseline data from Switzerland. Int J Clin Pharm. 2018;40(6):1614–20.

Neeman M, Dobrinas M, Maurer S, Tagan D, Sautebin A, Blanc AL, et al. Transition of care: a set of pharmaceutical interventions improves hospital discharge prescriptions from an internal medicine ward. Eur J Intern Med. 2017;38:30–7.

Geese F, Schmitt KU. Interprofessional Collaboration in Complex Patient Care Transition: a qualitative multi-perspective analysis. Healthc (Basel). 2023;11(3).

Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. Int J Nurs Stud. 2013;50(5):587–92.

Thomson R, Plumridge L, Holland J, Editorial. Int J Soc Res Methodol. 2003;6(3):185–7.

Audulv Å, Hall EOC, Kneck Å, Westergren T, Fegran L, Pedersen MK, et al. Qualitative longitudinal research in health research: a method study. BMC Med Res Methodol. 2022;22(1):255.

Kim H, Sefcik JS, Bradway C. Characteristics of qualitative descriptive studies: a systematic review. Res Nurs Health. 2017;40(1):23–42.

Sandelowski M. Whatever happened to qualitative description? Res Nurs Health. 2000;23(4):334–40.

Bradshaw C, Atkinson S, Doody O. Employing a qualitative description Approach in Health Care Research. Glob Qual Nurs Res. 2017;4:2333393617742282.

PubMed   PubMed Central   Google Scholar  

Bellone JM, Barner JC, Lopez DA. Postdischarge interventions by pharmacists and impact on hospital readmission rates. J Am Pharm Assoc (2003). 2012;52(3):358–62.

Hennink MM, Kaiser BN, Marconi VC. Code saturation versus meaning saturation: how many interviews are Enough? Qual Health Res. 2016;27(4):591–608.

World Health Organization. Adherence to long-term therapies: evidence for action. 2003.

Fisher JD, Fisher WA, Amico KR, Harman JJ. An information-motivation-behavioral skills model of adherence to antiretroviral therapy. Health Psychol. 2006;25(4):462–73.

Bandura A. Health promotion from the perspective of social cognitive theory. Psychol Health. 1998;13(4):623–49.

ShiftEUROQOL Research FOndation EQ 5D Instruments. Accessed 30 July 2022 https://euroqol.org/eq-5d-instruments/sample-demo/

Jeppesen KM, Coyle JD, Miser WF. Screening questions to predict limited health literacy: a cross-sectional study of patients with diabetes mellitus. Ann Fam Med. 2009;7(1):24–31.

Giordano TP, Guzman D, Clark R, Charlebois ED, Bangsberg DR. Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale. HIV Clin Trials. 2004;5(2):74–9.

Horne R, Weinman J, Hankins M. The beliefs about medicines questionnaire: the development and evaluation of a new method for assessing the cognitive representation of medication. Psychol Health. 1999;14(1):1–24.

Horne R, Chapman SC, Parham R, Freemantle N, Forbes A, Cooper V. Understanding patients’ adherence-related beliefs about medicines prescribed for long-term conditions: a meta-analytic review of the necessity-concerns Framework. PLoS ONE. 2013;8(12):e80633.

Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006;3(2):77–101.

Waibel S, Henao D, Aller M-B, Vargas I, Vázquez M-L. What do we know about patients’ perceptions of continuity of care? A meta-synthesis of qualitative studies. Int J Qual Health Care. 2011;24(1):39–48.

Rognan SE, Jørgensen MJ, Mathiesen L, Druedahl LC, Lie HB, Bengtsson K, et al. The way you talk, do I have a choice?’ Patient narratives of medication decision-making during hospitalization. Int J Qualitative Stud Health Well-being. 2023;18(1):2250084.

Michel B, Hemery M, Rybarczyk-Vigouret MC, Wehrle P, Beck M. Drug-dispensing problems community pharmacists face when patients are discharged from hospitals: a study about 537 prescriptions in Alsace. Int J Qual Health Care. 2016;28(6):779–84.

Bruhwiler LD, Hersberger KE, Lutters M. Hospital discharge: what are the problems, information needs and objectives of community pharmacists? A mixed method approach. Pharm Pract (Granada). 2017;15(3):1046.

Knight DA, Thompson D, Mathie E, Dickinson A. Seamless care? Just a list would have helped!’ Older people and their carer’s experiences of support with medication on discharge home from hospital. Health Expect. 2013;16(3):277–91.

Gualandi R, Masella C, Viglione D, Tartaglini D. Exploring the hospital patient journey: what does the patient experience? PLoS ONE. 2019;14(12):e0224899.

Norberg H, Håkansson Lindqvist M, Gustafsson M. Older individuals’ experiences of Medication Management and Care after Discharge from Hospital: an interview study. Patient Prefer Adherence. 2023;17:781–92.

Jones KC, Austad K, Silver S, Cordova-Ramos EG, Fantasia KL, Perez DC, et al. Patient perspectives of the hospital discharge process: a qualitative study. J Patient Exp. 2023;10:23743735231171564.

Hesselink G, Flink M, Olsson M, Barach P, Dudzik-Urbaniak E, Orrego C, et al. Are patients discharged with care? A qualitative study of perceptions and experiences of patients, family members and care providers. BMJ Qual Saf. 2012;21(Suppl 1):i39–49.

Murray SA, Kendall M, Carduff E, Worth A, Harris FM, Lloyd A, et al. Use of serial qualitative interviews to understand patients’ evolving experiences and needs. BMJ. 2009;339:b3702.

Berger ZD, Boss EF, Beach MC. Communication behaviors and patient autonomy in hospital care: a qualitative study. Patient Educ Couns. 2017;100(8):1473–81.

Davis RE, Jacklin R, Sevdalis N, Vincent CA. Patient involvement in patient safety: what factors influence patient participation and engagement? Health Expect. 2007;10(3):259–67.

Greene J, Hibbard JH. Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes. J Gen Intern Med. 2012;27(5):520–6.

Mitchell SE, Gardiner PM, Sadikova E, Martin JM, Jack BW, Hibbard JH, et al. Patient activation and 30-day post-discharge hospital utilization. J Gen Intern Med. 2014;29(2):349–55.

Weir DL, Motulsky A, Abrahamowicz M, Lee TC, Morgan S, Buckeridge DL, et al. Failure to follow medication changes made at hospital discharge is associated with adverse events in 30 days. Health Serv Res. 2020;55(4):512–23.

Kripalani S, Goggins K, Nwosu S, Schildcrout J, Mixon AS, McNaughton C, et al. Medication nonadherence before hospitalization for Acute Cardiac events. J Health Commun. 2015;20(Suppl 2):34–42.

Mortelmans L, De Baetselier E, Goossens E, Dilles T. What happens after Hospital Discharge? Deficiencies in Medication Management encountered by geriatric patients with polypharmacy. Int J Environ Res Public Health. 2021;18(13).

Mortelmans L, Goossens E, Dilles T. Beliefs about medication after hospital discharge in geriatric patients with polypharmacy. Geriatr Nurs. 2022;43:280–7.

Bandiera C, Ribaut J, Dima AL, Allemann SS, Molesworth K, Kalumiya K et al. Swiss Priority setting on implementing Medication Adherence interventions as Part of the European ENABLE COST action. Int J Public Health. 2022;67.

Elliott R, Boyd M, Nde S. at e. Supporting adherence for people starting a new medication for a long-term condition through community pharmacies: a pragmaticrandomised controlled trial of the New Medicine Service. 2015.

Grimmsmann T, Schwabe U, Himmel W. The influence of hospitalisation on drug prescription in primary care–a large-scale follow-up study. Eur J Clin Pharmacol. 2007;63(8):783–90.

Larsen MD, Rosholm JU, Hallas J. The influence of comprehensive geriatric assessment on drug therapy in elderly patients. Eur J Clin Pharmacol. 2014;70(2):233–9.

Viktil KK, Blix HS, Eek AK, Davies MN, Moger TA, Reikvam A. How are drug regimen changes during hospitalisation handled after discharge: a cohort study. BMJ Open. 2012;2(6):e001461.

Strehlau AG, Larsen MD, Søndergaard J, Almarsdóttir AB, Rosholm J-U. General practitioners’ continuation and acceptance of medication changes at sectorial transitions of geriatric patients - a qualitative interview study. BMC Fam Pract. 2018;19(1):168.

Anderson TS, Lee S, Jing B, Fung K, Ngo S, Silvestrini M, et al. Prevalence of diabetes medication intensifications in older adults discharged from US Veterans Health Administration Hospitals. JAMA Netw Open. 2020;3(3):e201511.

Royal Pharmaceutical Society. Keeping patients safewhen they transfer between care providers– getting the medicines right June 2012. Accessed 27 October 2023 https://www.rpharms.com/Portals/0/RPS%20document%20library/Open%20access/Publications/Keeping%20patients%20safe%20transfer%20of%20care%20report.pdf

International Pharmaceutical Federation (FIP). Medicines reconciliation: A toolkit for pharmacists. Accessed 23 September 2023 https://www.fip.org/file/4949

Californian Pharmacist Assiociation Transitions of Care Resource Guide. https://cdn.ymaws.com/www.cshp.org/resource/resmgr/Files/Practice-Policy/For_Pharmacists/transitions_of_care_final_10.pdf

Royal Collegue of Physicians. Medication safety at hospital discharge: Improvement guide and resource. Accessed 18 September 2023 https://www.rcplondon.ac.uk/file/33421/download

Douglas N, Campbell W, Hinckley J. Implementation science: buzzword or game changer. J Speech Lang Hear Res. 2015;58.

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Acknowledgements

The authors would like to thank all the patients who took part in this study. We would also like to thank the Geneva University Hospitals Patients Partners + 3P platform as well as Mrs. Tourane Corbière and Mr. Joël Mermoud, patient partners, who reviewed interview guides for clarity and significance. We would like to thank Samuel Fabbi, Vitcoryavarman Koh, and Pierre Repiton for the transcriptions of the audio recordings.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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LS, GG, and MS conceptualized and designed the study. LS and GG screened and recruited participants. LS conducted the interviews. LS, GG, and MS performed data analysis and interpretation. LS drafted the manuscript and LS and MS worked on the different versions. MS and GG approved the final manuscript.

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Solh Dost, L., Gastaldi, G. & Schneider, M. Patient medication management, understanding and adherence during the transition from hospital to outpatient care - a qualitative longitudinal study in polymorbid patients with type 2 diabetes. BMC Health Serv Res 24 , 620 (2024). https://doi.org/10.1186/s12913-024-10784-9

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Facilitators and barriers of HPV vaccination: a qualitative study in rural Georgia

• Courtney N. Petagna 1 ,
• Stephen Perez 1 ,
• Erica Hsu 1 ,
• Brenda M. Greene 2 ,
• Ionie Banner 1 ,
• Robert A. Bednarczyk 3 &
• Cam Escoffery 1  

BMC Cancer volume  24 , Article number:  592 ( 2024 ) Cite this article

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Introduction

Human papillomavirus (HPV) vaccination protects against HPV-associated cancers and genital warts. Healthy People 2030 goal for HPV vaccine uptake is 80%, but as of 2021, only 58.5% of adolescents are up to date in Georgia. The purpose of the study is to assess the attitudes, vaccine practices, facilitators, and barriers to receiving the HPV vaccine in southwest Georgia.

We conducted 40 semi-structured interviews in the United States from May 2020-Feburary 2022 with three different audiences (young adults, parents, and providers and public health professionals) guided by the P3 (patient-, provider-, practice-levels) Model. The audiences were recruited by multiple methods including fliers, a community advisory board, Facebook ads, phone calls or emails to schools and health systems, and snowball sampling. Young adults and parents were interviewed to assess their perceived benefits, barriers, and susceptibility of the HPV vaccine. Providers and public health professionals were interviewed about facilitators and barriers of patients receiving the HPV vaccine in their communities. We used deductive coding approach using a structured codebook, two coders, analyses in MAXQDA, and matrices.

Out of the 40 interviews: 10 young adults, 20 parents, and 10 providers and public health professionals were interviewed. Emerging facilitator themes to increase the uptake of the HPV vaccine included existing knowledge (patient level) and community outreach, providers’ approach to the HPV vaccine recommendations and use of educational materials in addition to counseling parents or young adults (provider level) and immunization reminders (practice level). Barrier themes were lack of knowledge around HPV and the HPV vaccine (patient level), need for strong provider recommendation and discussing the vaccine with patients (provider level), and limited patient reminders and health education information around HPV vaccination (practice level). Related to socio-ecology, the lack of transportation and culture of limited discussion about vaccination in rural communities and the lack of policies facilitating the uptake of the HPV vaccine (e.g., school mandates) were described as challenges.

These interviews revealed key themes around education, knowledge, importance of immunization reminders, and approaches to increasing the HPV vaccination in rural Georgia. This data can inform future interventions across all levels (patient, provider, practice, policy, etc.) to increase HPV vaccination rates in rural communities.

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Human papillomavirus (HPV) is a common sexually transmitted infection (STI) in the United States (US) with an estimated prevalence of 42.5 million people and an incidence of 13 million people per year [ 1 ]. HPV-associated cancers, including vulvar, vaginal, cervical, penile, anal, and oropharyngeal cancers, can develop years or decades following persistent HPV infection [ 2 , 3 ]. Between 2015 and 2019, it was estimated HPV caused 47,199 new cancer cases each year [ 2 ]. Georgia has an incidence rate of 12.9 per 100,000 persons of all HPV associated cancers compared to the United States at 11.8 per 100,000 persons [ 4 ]. Additionally, Georgia is ranked in the top 15 nationally for having high cervical cancer incidence rates (7.4 per 100,000 persons) and the national incident rate is 6.5 per 100,000 persons [ 4 ]. Due to the high incidence rates of HPV associated cancers, the Georgia Cancer Plan: 2019–2024 made targeting HPV associated cancers a priority in an effort to support cancer prevention efforts [ 5 ]. The objective related to this priority is (Objective 1): “To increase the number of females and males who complete the HPV vaccine series in accordance with the Advisory Committee on Immunization Practices (ACIP) and recommendations” [ 5 ].

HPV vaccine was developed to prevent HPV associated cancers and genital warts; [ 6 ] currently HPV vaccine is one of two cancer prevention vaccines available globally [ 7 ]. Previous research determined each HPV vaccine is safe and has at least 96% efficacy for preventing HPV-associated cancers [ 8 ]. HPV vaccination was recommended in the US for adolescent females in 2006, and for adolescent males in 2011 [ 9 ]. The Advisory Committee on Immunization Practices (ACIP) recommends vaccination from as young as 9 years old to age 26, with the possibility of receiving the vaccine up to the age of 45 through a shared decision making process between the provider and the patient [ 10 ]. The earlier a person receives the HPV vaccine before engaging in sexual activity, the better protected they will be from HPV-associated cancers and genital warts [ 11 ]. If the vaccine is initiated prior to the 15th birthday, vaccine recipients need to complete a two-dose vaccine series; if the first dose is given after the 15th birthday, vaccine recipients need to complete a three-dose series [ 12 ]. Healthy People 2030 offers standardized 10-year measurable health objectives for the United States. Among their target goals is to have 80% of adolescents aged 13 to 15 receive all recommended doses of the HPV vaccine. As of 2021, the current national rate is suboptimal at 58.5% [ 13 ].

According to the National Immunization Survey-Teen (NIS-Teen) data from 2022, 76.0% of adolescents aged 13–17 have received at least one HPV vaccine dose with 62.6% having completed the series [ 14 ]. Comparatively, other adolescent vaccines such as Tdap and meningococcal are closer to 90% for receiving one dose. [ 14 ] Compared to the national percentage from the NIS-Teen 2022, Georgia’s HPV vaccine initiation and up-to-date rates among adolescents aged 13–17 are 70.8% and 61.5%, respectively [ 15 ]. Adolescents residing in rural areas compared to urban areas have lower initiation (68% versus 77.8%) and up-to-date (49.2% versus 60.4%) HPV vaccination rates from NIS-Teen 2020 [ 16 ]. Similarly, in the District of Albany (rural GA), only 47.9% adolescents aged 13–17 were up-to-date on their HPV vaccinations, which is 13% lower than the rest of the state, provided by Georgia Registry of Immunization Transactions and Services (GRITS) [ 17 ]. Therefore, this shows a gap in HPV vaccine uptake in rural communities and understanding the reasons behind low vaccine rates is crucial to increasing vaccination efforts.

Research has examined facilitators and barriers at the patient- (adolescent & parent), provider-, and practice-levels. The facilitators at both the patient- and provider-levels are patient’s trust in the provider, knowledge of the vaccine, and self-efficacy in one’s own ability to discuss the vaccine [ 18 , 19 ]. For practice-level, the facilitators are the availability of the vaccine, scheduling future vaccine appointments, and prioritizing the vaccine [ 18 ]. The barriers at the patient- and provider-levels are the lack of knowledge and self-efficacy discussing the vaccine, concerns about safety and adverse effects, and not receiving provider recommendation for HPV vaccine [ 18 , 20 ]. The barriers for practice-level are lack of access to vaccine provider, clinic logistics, and reminder system. [ 19 ] Few studies have explored facilitators and barriers of receiving the HPV vaccine intersecting at multiple levels of the socio-ecological model (SEM), and even fewer have been conducted in rural southwest Georgia [ 18 , 21 , 22 , 23 , 24 ].

This qualitative study aimed to identify socio-ecological determinants influencing HPV vaccination uptake among parents, young adults, and public health professionals and providers in rural Georgia. We applied the P3 (patient-, provider-, practice-levels) Model to examine all three levels at the same time and how they impact each other, specifically around HPV vaccination [ 25 ]. At the patient level we assessed parents and young adults perceived susceptibility and severity. To assess all three levels we asked parents, young adults, providers and public health professionals about the facilitators and barriers of receiving the HPV vaccine series.

We conducted a cross-sectional qualitative study to assess attitudes, knowledge, perceived severity and susceptibility, and reasons for HPV vaccination uptake (or lack of) among parents and young adults. In addition, interviews with healthcare providers and public health professionals were conducted to assess their knowledge, attitudes, practices, and the facilitators and barriers to HPV vaccination in rural communities. Between September 2020 to March 2022, a series of 40 interviews were virtually conducted with participants from southwest Georgia. At the beginning of the interview, the participant was told about the study, their role, risks and benefits of the study, and consented to participate. After consent was given, the interview was recorded on Zoom or an audio recorder. Emory staff (coordinators and students) were trained on the study, interview guide and conducted the interviews. The interviews were between 30–45 min and participants were compensated with a $25 electronic gift card. The study was deemed exempt by the Institutional Review Board at Emory University.

Conceptual framework

This study was informed by the P3 Model and the SEM [ 25 , 26 ]. The P3 Model is a unique approach since it encompasses not one but all three levels (patient, provider, and practice) of the clinic approach and integrates key components of health promotion and behavioral theoretical models (e.g., Health Belief Model, Theory of Planned Behavior, and ecological models (SEM) to impact health outcomes (Fig. 1 ) [ 25 ]. Since the P3 Model integrates multiple theories into the model, we utilized the model to guide our study and focused on targeting each of the levels in the model. The SEM describes the interplay of different levels of health factors that may influence the uptake of health behaviors at the individual, interpersonal, organizational (i.e., health systems), community, and policy levels [ 26 ]. From the SEM, we included questions beyond the P3 Model including community and policy-level factors that facilitate or hinder vaccine uptake. The frameworks applied to this study address limitations in existing rural health literature on HPV vaccination by considering healthcare system components beyond patient-level factors influencing parents’ and young adults’ vaccination decisions [ 25 , 27 ].

The HPV vaccine applied to the P3 (practice, provider, and patient level) model

Eligibility

This study included diverse participant categories from parents, young adults, providers and public health professionals. The parent of a child category was split into two groups: 1) vaccinated and 2) unvaccinated. The eligibility criteria for parents with a vaccinated child is a parent whose child received at least one dose of the HPV vaccine series and the child were between the ages 9–17. The eligibility for parents with an unvaccinated child is a parent whose child did not receive any doses of the HPV vaccine series and were between the ages 9–17. To be eligible for the young adult category, the person had to be between the ages of 18–34. Providers and public health professionals had to be a person who worked in a clinical setting or public health department or public health organization. The eligibility criteria of the interview sample are in Table  1 .

Recruitment

We used snowball and convenience sampling methods for participant recruitment and recruited only from southwest Georgia, which consists of 33 counties. Participants (e.g., parents and young adults) were recruited from the Emory Prevention Research Center (EPRC) Community Advisory Board (CAB), Facebook advertisements, and emails. The CAB is comprised of community members and leaders, health providers or staff from health systems, the public health district, businesses, and non-profits in southwest Georgia. This CAB has been in existence for over 20 years and members typically commit for two–three years. The Facebook advertisements were posted on the EPRC Facebook page targeting parents and young adults who live in southwest Georgia. Some parents, young adults, and providers were recruited from elementary schools and universities by receiving cold emails from the study team. In the email, eligibility and demographic questions were asked such as the age of the child/young adult, has the child/young adult received the HPV vaccine series, and if not, whether there are any plans for them to receive the HPV vaccine series in the future. The last two questions were about county of residence and race. These two questions were asked to make sure the study team captured a diverse sample. Public health professionals were recruited from non-profits and health agencies through word of mouth, fliers, and emails. To ensure saturation was met we had at least 10 participants for each category.

Interview guide development

The qualitative study had three interview guides for different audiences (parents, young adults, and providers/public health professionals). The interview guides were informed by the P3 Model and the socio-ecological model [ 25 , 26 ]. The questions revolved around six topical categories, including: 1) knowledge, 2) facilitators to receipt of HPV vaccine, 3) barriers to receipt of HPV vaccine, 4) healthcare delivery factors, 5) community and resources, and 6) demographics. In addition, in the parent and young adult interview guides we asked about preventive care and interaction with providers around HPV vaccination. For providers, we also asked about promotional methods for the vaccine, the use of the Vaccine for Children’s program, staffing and supply issues, and if they have strategies or received training on how to talk to patients and parents about the vaccine (Table 2 ). Across all categories, we assessed participant demographics by asking demographic questions at the end of the interview before concluding the recording. The demographic questions included age, gender, race, and ethnicity (whether they are of Hispanic/Spanish descent). In addition, for providers and public health professionals, we inquired about their title and discipline, the organization they work for, and how long they have worked there. The interview guides and methods were reviewed by the study team and a working subgroup consisting of researchers from the EPRC and the EPRC CAB. The CAB members who participated are a healthcare provider, an infectious disease epidemiologist, and a health district deputy director. These CAB members, EPRC researchers, and our Emory team met three times before the data collection to guide the instrument development, recruitment methods, and data analysis plans. The results also were shared with them through several CAB meetings.

All the interviews except for two were recorded on Zoom. The two interviews not recorded on Zoom were recorded on an audio recorder since the interviews were conducted over the phone. The interviews were then transcribed by a professional transcription service. We applied a systematic method for thematic data analysis including iterative codebook development with deductive codes from the interview guide, first-round coding, secondary coding, refinement of the codebook, consensus, final analysis, and matrices of themes [ 28 ]. A codebook with definitions was developed using a deductive coding approach from the three interview guides (parent, young adult, and providers/public health professionals) and the P3 Model and inductive codes. All transcripts were uploaded to MAXQDA for analysis [ 29 ]. Two trained researchers coded each transcript with the secondary coder reviewing coding from the primary coder. If there were discrepancies, then the coders would meet to discuss and come to an agreement and add new codes to the codebook when needed [ 28 ]. Emerging themes were identified for barriers and facilitators across each of the levels and finalized until saturation was reached [ 30 ]. Themes were sorted by facilitators and barriers and then broken down further by each of the levels in the P3 Model and socio-ecological levels (community and policy) in matrices with stronger themes ranked first.

We had 10 young adults, 20 parents, and 10 providers and public health professionals (health system participants) participating in the qualitative study. The young adults were 80% female and 20% male, 60% Black, and 40% White, 90% non-Hispanic and 10% Hispanic. The parents were 95% female and 5% male, 60% Black, 35% White, and 5% did not specify their race. Adolescents of the parents were 53% female and 47% male, 42% were ages 9–12, 48% were ages 13–17 and 10% were 18 and over. Health system participants were 90% female, 10% male, 60% Black and 30% White and 10% not specified. More than half of all participants and providers identified as African American (60%), about a third identified as White (35%), and 5% of participants did not specify their race. Additional demographics of the sample are displayed in Tables  3. and  4 . The 40 participants reside in 11 out of the 33 counties in southwest Georgia and the top three counties are: Dougherty (52.5%), Lee (15%), and Colquitt (10%) seen in Supplemental Table 1.

Facilitators

There were facilitators for receiving the HPV vaccine identified at each of the three levels in the P3 Model. Facilitators at the patient level were having existing knowledge of HPV and the HPV vaccine, knowing the vaccine is safe, having knowledge on who can receive the vaccine and when, and having trusted individuals provide information about the HPV vaccine to their community. At the provider level, they were having efficacy of the vaccine, framing of the HPV vaccine to patients, and revisiting the HPV vaccination with hesitant parents. Facilitators at the practice level were immunization reminders, patient registries, the use of social media (e.g., educational videos), and other health clinics who support the vaccine. Immunization reminders was the most mentioned strategy mentioned across participants, both for the patients and providers to remind patients about the vaccine. See Table  5 for more facilitator quotes for each level.

Patient level

At the patient level, participants (primarily parents of vaccinated children and young adults both vaccinated and unvaccinated) consistently referenced having existing knowledge of HPV as a facilitator to increase uptake in administering the HPV vaccine. In describing the vaccine, participants referenced a basic understanding of which cancers it can prevent, and ages at which adolescents can receive the vaccine. Parents and young adults understood the safety of the vaccine, which assisted in having positive attitudes towards the vaccine. One parent described: "I’m going to say it’s [HPV vaccine] some insurance for your child’s behaviors and actions later on in life, you know? Lots of insurance." (Participant 7, parent of vaccinated child). For young adults, they learned about the vaccine on social media, and through school. Enlisting trustworthy individuals to connect community members with information within the community serves as another facilitator for increasing HPV vaccine uptake. A director of a non-profit alluded to this: "I think once they are educated, you know, by a trusted voice, you know, whether that’s their physician or, you know, pastor or somebody, whoever that trusted voice is for them, I think they’re more likely to be acceptable to that ." (Participant 39, health systems).

Provider level

At the provider level, parents of vaccinated children highlighted the approach their children’s providers took when discussing the HPV vaccine with them. The providers framed the vaccine as a preventative measure against other diseases. Providers often spoke of the efficacy the vaccine has against contracting and spreading sexually transmitted infections (STIs), and how those STIs may have more serious ramifications later in life. A parent described this perspective: "Just putting it out and putting the information out and let them stress that it is an STD just like any other STD. Of course, with repercussions in the future, and if you can prevent it, why not." (Participant 6, parent of vaccinated child) .

In addition to framing the discussion, several education and messaging strategies were viewed as successful facilitators; these included patient visits at clinics, health departments, and utilizing community events to educate local community members. Some health system participants offered effective strategies such as revisiting the topic with hesitant parents and using information sheets to allow the parents to learn about the vaccine and its importance. One provider described their approach: "And I try to re-educate if they didn’t, just because a lot of it is that they kind of don’t know what HPV is. They’ve heard of the vaccine. They understand that it’s a vaccine, but I don’t think they really know what HPV is and why they should be concerned about it." (Participant 40, health systems). Parents of vaccinated children emphasized the use of brochures and pamphlets offered by providers as effective learning strategies. Some reflected on how this allowed for parents to take their time learning about the vaccine, and its benefits. Others viewed the brochure as a first step towards having a deeper conversation with the provider. Ultimately, parents thought brochures may bridge the gap for parents who do not know enough about the vaccine but want to learn more about it.

Practice level

At the practice level, immunization reminders sent to parents and young adults were seen as effective strategies by parents whose children were vaccinated and vaccinated young adults for patients to receive their HPV vaccine doses. Reminders included different formats depending on the health system, including phone calls and reminder cards. Health system participants also recognized different strategies to ensure patients returned for subsequent doses. These included the use of patient registries and highlighting those due for immunizations, as well as through the standardized Georgia Registry of Immunization Transactions and Services (GRITS), the statewide immunization information system. As one provider described their practice’s strategy:

"We have what’s called precall-recall, and so once a month we print out a list of our patients here that either they’re coming due for a set of immunizations they’ll be turning 11 in the next month. We’ll send out a letter that says your child will be due for immunizations on this day. We won't specifically say what immunization, but we’ll say they’re due for immunizations…" (Participant 9, health systems) .

Community and policy levels

At the community and policy levels, parents with vaccinated children and health system participants discussed techniques of using central and familiar locations like schools to engage in community outreach. Another one was to have champions within the community. One provider described: “I’d say insight into the community, definitely, to get the word out. Because if you don’t have somebody from the community that also buys in, then they’re not going to participate, not going to show up” (Participant 25, health system nurse). For policy, health system participants mentioned vaccine programs, explaining : “I think we have a free program with HPV…We get them (adult patients) to sign something and then we can get it for free for people who are uninsured” (Participant 23, health system provider).

The barriers for receiving the HPV vaccine at each of the three levels in the P3 Model were the lack of information and dialogue around the HPV vaccine. At the patient level, the main barriers were a dearth of education on HPV and the HPV vaccine, misinformation, and stigma as is relates to STIs and sexual intercourse. At the provider level, a deficiency exists in direct provider-patient communication, including instances where providers fail to inform and recommend the HPV vaccine to their patients. At the practice level, there are a lack of systematic reminders for patient immunizations reminders, limited information, time, staff, and resources committed to the HPV vaccine (Table  6 ).

At the patient level, a persistent theme among parents of both vaccinated and unvaccinated children in our study focused on a dearth of knowledge among parents and their communities about the importance of vaccinating their children against HPV. They highlighted how it is not a common topic to be discussed among parents with their children. One young adult described their experience as a child, “They’re (doctor) like, oh yeah, we now offer the HPV vaccine. Is it something you want to get? And my mom was like, eh, no, she doesn’t need that right now. And I was like, okay. I don’t really want a shot either, so it’s fine with me.” (Participant 17, unvaccinated young adult). Not only is it not being discussed, but parents described not knowing where to go to find more information about the vaccine. Health system participants also discussed how parents often did not have the necessary knowledge about the vaccine to effectively make decisions on behalf of their children. Stemming from this lack of education is the impact that misinformation has surrounding the efficacy, safety, and utility of the HPV vaccine. Two non-vaccinated young adults address misinformation, one stated, “… they’re [young adults] very hesitant about getting like even the COVID vaccine, just because, you know, they heard rumors, oh, it has this in it, it has that in it… ” another stated, “They [young adults] look at social media and certain people may say this is what they do, this is what they don’t do, this is that. So, I think actually with social media and peer pressure that conveys a lot of the youth.”

A director of a non-profit described, “I think all of the conspiracy theories that are out there now, and it’s even worse since COVID, nobody trusts, or a lot of people don’t trust public health messages anymore.” (Participant 12, health systems). In this context, the participant emphasizes the challenge of discussing the vaccine with parents and how a lack of trust in public health complicates messaging strategies.

Coupled with this misinformation was the resulting stigma of discussing HPV due to it being a STI. Vaccinated and unvaccinated young adults, both parents of vaccinated and unvaccinated children, and health system participants described how some parents may be reluctant to vaccinate their child, because they perceive it to indicate their child could be engaging in sex, or receiving the vaccine encourages the child to be sexually active. As one parent described, “Well, I think part of it is that since it is sexually transmitted, I think that a lot of parents don’t want to really delve into that thought that their kids are being sexually active or may be sexually active soon” (Participant 1, parent of vaccinated child). Particularly in southwest Georgia, sexual intercourse is stigmatized. As one provider described,

“ I think the – I think stigma, because it is associated with sexual – a sexual nature. So, they kind of clam up like here in southwest Georgia, Bible belt, like it’s just kind of a – you know, you don’t speak of those things. Those are kind of taboo. Like everybody knows it’s occurring, but you don’t really want to I guess see your child doing – you know, doing things like that. So, I think it’s just the culture here” (Participant 15, health system nurse).

By attempting to discuss a vaccine to prevent STIs, health system participants believed this may contradict many who view teenage sexual health education as only relevant through abstinence.

At the provider level, parents of unvaccinated children and young adults (both vaccinated and unvaccinated) alluded to the dearth of direct communication with providers about the vaccine and revisiting the topic with their patients. Specifically, some parents described how their child’s doctor did not educate them on the reasons for getting the vaccine. As one parent described their experience with a doctor as:

"…they presented it, and asked did I want him to receive the vaccine, but at that time, I just had not had enough information on it personally, and with that, they did not give me any more information. And so, with that being said, you know, if my – if the doctor is not willing to provide more and give me more insight into it, any side effects, you know, statistics, and things of the sort, then you know, (laughs) yeah." (Participant 2, parent of unvaccinated child).

This parent highlighted how they may have been convinced had the doctor provided more details about the reason for vaccinating their child. Another parent with an unvaccinated child described providers not revisiting the HPV vaccine with them at later visits if the parent initially said “no.” Aligned with the lack of direct communication, providers were not informing and recommending the HPV vaccine to patients. As a director of a non-profit stated, “ I think maybe lack of consistent recommendations. You know, they may get tied up in, you know, other bunch of check list of things that they’ve got to do and then may – it just may not be consistent throughout the flow…” (Participant 39, health systems). A parent also felt the providers need to be speaking more about the HPV vaccine in the exam room. One parent described, “I feel they should be more open and mention it in an exam. I do. I feel like they should. Not just have the poster up, like in the hallway. They still should mention it. The same way that they’re stressing the COVID vaccine, they should stress that vaccine in the same manner, I think.” (Participant 35, parent of unvaccinated child) . Here, the parent wished the approach to HPV and the HPV vaccine was similar to the COVID-19 vaccine in order for them to understand its importance during their child’s visits.

At the practice level, participants described lack of systematic reminders for patient immunizations, limited time, resources, and staff allocated per patient, and lack of education in the clinic or medical offices. A parent of each a vaccinated and unvaccinated child referenced not receiving vaccine reminders. One of the parents stated: "Yeah. I think that like, for example, in my case, if there were an actual mailing that came to our house-…I would have seen it. I would have at least begun a conversation with my husband about it, and he was the one responsible for taking him to the pediatrician and getting it handled." (Participant 1, parent of vaccinated child) . Although their child was vaccinated, the need for a mailed reminder would have facilitated discussions between the parents about vaccinating their child. Similarly, a young adult who received their first shot did not return for their second shot since they did not know when to return to the doctor’s office. Other barriers at the practice level include limited information, time, staff, and resources dedicated to the HPV vaccine. Both parents and health system participants mentioned time being a factor. One provider stated,

“ Time would be one I would see, because with a lot of the things that we’re having to do now, you don’t’ have as much time to do the education as you would like to, and sometimes when you’re talking about sex and HPV, if it’s on a one to one basis, it’s hard to establish a rapport in five, ten minutes and get all the information that you need to get to them and then allow them to ask questions” (Participant 25, health system nurse).

As for the lack of resources, parents with a vaccinated child mentioned they have seen posters about measles, mumps, and rubella but not on the HPV vaccine and clinics not having enough of vaccines to distribute. A barrier widely mentioned across participants (parents, young adults unvaccinated, and health systems) were the differences between private practices and public health departments in rural communities. The differences between the two discussed were the patient-provider relationship and patient privacy differences. A parent explained:

“If you’re more familiar with the doctor you have more trust, and you’re more likely to take their advice. When you go to one of the local clinics, the convenient care clinics, it’s not a guarantee you’re going to get the same doctor. So, you may not be as comfortable having a certain conversation with one doctor as you would with a doctor that you’re used to seeing on a regular basis” (Participant 13, parent with a vaccinated child).

Another parent stated, “Private, is not private, and a lot of people may avoid going to the health department and would rather go to an outside pediatrician but don’t have the transportation to get there (Participant 6, parent with a vaccinated child). This parent explained health department layouts are openly structured and patients get called to a window to discuss their health information and people in the waiting room can hear those discussions, causing a lack of privacy for the patient, Similarly, a young adult unvaccinated also mentioned how privacy and courtesy of health professionals at certain clinics can be a barrier for patients. A lack of privacy is a concern at a patient level, while limited resources for transportation infrastructure affect the community at large.

Several barriers at the community and policy level were mentioned by participants. At the community level the barriers include inadequate transportation, and lack of information within the community about HPV and the HPV vaccine and resources. A parent alluded to how important having a car is: “If I didn’t have a car, I probably wouldn’t even – I would barely go to the doctor if I had to use public transportation” (Participant 27, parent with an unvaccinated child). There is public transportation, but it takes more time and some unvaccinated young adults also stated how rural communities are spread out, which makes it challenging to travel to clinics that are out of their town and far away. A young adult described the lack of discussion around the vaccine in rural Georgia communities: “No, just that there is really not a lot of talks about it. I definitely think there needs to be more communication about it for sure” (Participant 17, unvaccinated young adult). At the policy level, the two main barriers participants mentioned were the financial barriers and lack of policies facilitating the uptake of the HPV vaccine. A provider described not being able to provide the vaccine to a minor without parental consent, “…hey, we can’t give them to you, because you’re not 18. We can give you, you know, reproductive care, but we cannot give you any vaccine without your parents’ permission” (Participant 15, health system nurse).

Our study used the P3 Model framework and found common facilitators and barriers to receipt of the HPV vaccine in rural communities. Some of the facilitators we found were trusted individuals in the community, existing knowledge, and providers stating the vaccine is a cancer prevention tool. Parent participants from a study in Alabama reported that guidance from pediatricians or family physicians influenced their decision to vaccinate their children against HPV [ 31 ]. Another study in Montana noted parents may be more receptive to the HPV vaccine when it is discussed as a cancer prevention tool rather than an STI prevention tool [ 32 ]. A pivotal facilitator at the provider level in our study involved how providers phrase and frame the HPV vaccine to patients. Medical providers and public health stakeholders from a prior study in Montana identified a presumptive style of recommending the HPV vaccine. An announcement and conversation training HPV intervention for providers led to an increase in HPV vaccinations for adolescents ages 11–18 over those in a control group in North Carolina [ 33 , 34 ]. This style included offering the HPV vaccine with other immunizations such as meningococcal, HPV, and Tdap together, which was successful [ 32 , 34 ].

Additionally, our research revealed that immunization reminders were a key facilitator in improving HPV vaccination rates. A study in rural Alabama similarly reported that receiving appointment reminders via card, call, or text helped ensure all doses were received [ 35 ]. Similarly, healthcare provider participants from a study in Georgia highlighted the importance of scheduling subsequent HPV vaccine appointments before patients leave their first vaccination appointment and the use of reminder systems [ 18 ]. In addition to immunization reminders, health education material such as educational videos, and incorporating the use of social media were mentioned as strategies to engage people on the HPV vaccine by our participants. Our participants suggested that employing simplified strategies will better attract and engage the general population, especially those with lower health literacy. Previous research found that rural communities need increased access to education on HPV, the HPV vaccine, and sexual health [ 36 ].

In addition to examining facilitators within the P3 Model, we also examined community and policy-level factors. From our study, the community facilitators were trusted community key stakeholders and how they were instrumental in the development of interventions, [ 37 ] community and school education programs, [ 38 ] and county-wide social marketing campaigns [ 39 ]. Our participants mentioned having webinars and the use of school events and outreach is beneficial for increasing the uptake of the HPV vaccine. Future research could investigate interventions like technological reminders and capacity-building for rural healthcare systems to boost HPV vaccination rates. Additionally, future HPV vaccine promotion efforts could focus on community education and participation in campaigns such as the American Cancer Society’s Mission HPV Cancer Free [ 40 ]. At the policy level, some existing facilitators were the Vaccines for Children (VFC) program and private clinics instituting standing orders within their practice for the HPV vaccine [ 41 ]. The VFC was designed so children can receive vaccines regardless if the parent or guardian can afford the vaccines. Similarly, our study participants mentioned how beneficial vaccine programs are not only for children but for adults too.

Data from the 2010–2020 National Immunization Survey-Teen identified the following barriers to receiving the HPV vaccine: lack of knowledge, abstinence, safety concerns, and viewing the vaccine as unnecessary [ 42 ]. A lack of knowledge on HPV was reported as a prominent barrier among our rural participants, which has been observed across multiple rural-based studies [ 18 , 19 , 31 , 35 , 43 ]. Studies in rural Alabama found a lack of parental understanding about the HPV vaccine was a key barrier as reported by parents, pediatricians, and nurse participants [ 19 , 35 ]. Provider participants from a quantitative study reported vaccinating adolescent females (13–17 years old) at higher rates compared to pre-adolescent females (9–12 years old) [ 44 ]. Barriers such as parental discomfort and potential adverse side effects in vaccinating their pre-adolescent child against HPV, especially if the child has underlying health conditions can influence the age group disparity in vaccine uptake [ 44 , 45 ].

Another frequently discussed barrier in our study was stigma surrounding HPV as an STI and challenges in discussing sexual health, particularly given the conservative nature of southwest Georgia, located in the “Bible Belt” region. Previous research in the south (Georgia, Alabama, Kentucky, and North and South Carolina) found that parental perception of the HPV vaccination encouraging or permitting sexual activity discourages parents from having their child vaccinated against HPV [ 18 , 31 , 36 , 43 ]. Prior research with healthcare providers from Georgia noted providers avoid discussing sex at all when recommending the HPV vaccine due to STI stigma [ 18 ].

Similarly, a lack of provider recommendations or discussion about HPV was a prominent barrier among our participants, consistent with previous literature [ 18 , 35 , 42 ]. According to providers in Georgia, low provider confidence in the HPV vaccine can pose a barrier to giving patients strong recommendations for the vaccine [ 18 ]. A national survey examining the quality of physician recommendation for HPV vaccination revealed that physicians in the sample often lacked consistency, urgency, and timeliness in their recommendation of the HPV vaccine [ 46 ]. Strategies such as education from other lay health professionals such as community health workers or navigators, training or mentoring of providers through technology, or partnering with other health organizations may be possible intervention strategies to explore [ 47 ]. Provider training on strong recommendations and presumptive communication has been effective in approaching this discussion about the HPV vaccine with parents and/or adolescents and effective in promoting vaccination [ 33 , 48 ]. This type of training should be delivered to rural public health and healthcare providers to address these barriers [ 49 ].

Additionally, we found that a lack of patient reminders can hinder increases in HPV vaccination rates, which has been observed in prior studies. Reminder cards can easily be lost, so technology-based options, particularly email or text should be utilized based on individual patient preferences [ 43 ]. However, not all rural areas have the capacity to utilize text messaging based on limited cellar service [ 50 ]. Future efforts to increase HPV vaccination need to include relevant reminders for patients and/or caregivers. In addition to a lack of patient reminders, there is a lack of privacy within healthcare for patients. As shown in our study, patients commented on the lack of privacy in health departments and previous research highlights healthcare does not have appropriate privacy protections for patients [ 51 ]. Moreover, our participants noted that in rural areas, inadequate staffing and resources were also barriers to HPV vaccine uptake. A study in rural North and South Carolina also found that provider shortages in rural areas result in fewer opportunities for parents and adolescents to learn about the HPV vaccine [ 36 ].

From previous research, barriers at the community level consist of a lack of transportation and how it negatively affects people getting to their appointments to receive medical care [ 52 , 53 ]. Participants in our study mentioned how a lack of transportation is a challenge, especially when one does not own a car or is unable to drive. Future research can explore methods to increase vaccinations outside of clinical settings including community settings or in pharmacies, as recommended by the President’s Cancer Panel report [ 54 ].

Similarly, a lack of policies can impact the uptake of the HPV vaccine. For example, the HPV vaccine is not routinely mandated for school entry at the state level, unlike other vaccines such as Tdap. While all states and the District of Columbia have middle school entry requirements for Tdap vaccination, only four U.S. jurisdictions (Rhode Island, Virginia, Puerto Rico, and the District of Columbia) currently have HPV vaccination requirements [ 41 , 55 ]. Georgia did propose a bill in 2019 to allow adolescents younger than 16 to consent to vaccinations without parental consent, however, the bill did not pass [ 56 , 57 ]. Due to this, minors will need parental approval to receive the vaccine and our participants explained the difficulty of this. Other policy barriers are financial vaccine burdens on health systems that administer the vaccines and lack of reimbursement from insurance companies [ 58 ]. Future implementation and evaluation of HPV policies (e.g., school or policy requirements) could assess policy solutions and impacts on HPV vaccine uptake.

Strengthens and limitations

The strengths of this study include interviewing three categories of community stakeholders and receiving their insights on the facilitators and barriers of the HPV vaccine in rural Georgia. In addition, for parents and young adults, we received perspectives from those who received and did not receive the HPV vaccine. Using the P3 Model in our study and the subsequent findings, allowed for consideration of multi-level interventions for increasing HPV vaccination. Research has shown numerous programs that promote HPV vaccination operate at a single level [ 59 ]. Mostly focusing on either the patient or provider levels and a lack of focus on including facilitators and barriers at the practice level [ 60 , 61 , 62 ]. Public health professionals and providers can learn from these facilitators and barriers to test strategies at different levels to increase rural HPV vaccination rates. However, our study has some limitations. The study findings may not be generalizable outside of rural southwest Georgia to other states or regions. There were also delays in recruitment because of participants’ limited time due to the impact of the COVID-19 pandemic. We had to pause recruiting providers because the community asked us to due to the demands of the pandemic and we focused our efforts on recruiting parents and young adults for the study. Participants may have offered socially desirable responses during the interview regarding the HPV vaccine. Finally, although we used several methods to increase the reliability of the qualitative data analyses such as using verbatim transcripts, a structured, iterative codebook and training of coders, and two research team members coding each interview, there may be research biases in the analyses and interpretation of our data.

Identifying multi-level facilitators and barriers influencing HPV vaccination is necessary for increasing vaccine uptake, particularly in rural areas where vaccine coverage is disproportionately low. We found some key barriers at all three levels of the P3 model including misinformation, lack of knowledge, provider-patient communication, provider recommendation, lack of systematic reminders, and limited time and resources. These barriers highlight the need for future research to explore the effectiveness of the following strategies in rural communities: HPV vaccine education in rural communities through public health providers, provider training on strong recommendations, and technological health systems activities such as patient reminders.

Availability of data and materials

The data supports the findings of this study are available in tables and supplementary materials of this article. We can share general data matrices or summaries of the qualitative data if there are requested. Since this is a qualitative data and there is sensitive information about the vaccine and perhaps health systems, we will not share the actual transcripts. Contact Cam Escoffery at [email protected] about data availability.

Abbreviations

Community advisory board

Human papillomavirus

Patient-provider-practice-level Model

Socio-ecological Model

Sexually transmitted infections

CDC. Sexually transmitted infections prevalence, incidence, and cost estimates in the United States. 2021.  https://www.cdc.gov/std/statistics/prevalence-2020-at-a-glance.htm . Accessed Jan 2023.

CDC. Cancers associtated with human papillmavirus, United States, 2015–2019. https://www.cdc.gov/cancer/uscs/about/data-briefs/no31-hpv-assoc-cancers-UnitedStates-2015-2019.htm .

CDC. Cancers caused by HPV. 2021. https://www.cdc.gov/hpv/parents/cancer.html .

Google Scholar  

State profile: Georgia. St. Jude Research Hospital. 2023.  https://www.stjude.org/research/comprehensive-cancer-center/hpv-cancer-prevention-program/resources.html . Accessed Sept 2023.

Consortium GCC. Georgia Cancer Control Consortium comprehensive cancer control plan 2019–2024. Georgia Department of Public Health; 2019. https://dph.georgia.gov/chronic-disease-prevention/cancer-prevention-and-control .

Bauer HM, Wright G, Chow J. Evidence of human papillomavirus vaccine effectiveness in reducing genital warts: an analysis of California public family planning administrative claims data, 2007–2010. Am J Public Health. 2012;102(5):833–5. https://doi.org/10.2105/ajph.2011.300465 . (In eng).

Article   PubMed   PubMed Central   Google Scholar  

CDC. Vaccines (shots). 2023. https://www.cdc.gov/cancer/dcpc/prevention/vaccination.htm .

Seyferth ER, Bratic JS, Bocchini JA Jr. Human papillomavirus epidemiology and vaccine recommendations: selected review of the recent literature. Curr Opin Pediatr. 2016;28(3):400–6. https://doi.org/10.1097/mop.0000000000000354 . (In eng).

Article   CAS   PubMed   Google Scholar  

Rosenblum HG, Lewis RM, Gargano JW, Querec TD, Unger ER, Markowitz LE. Human papillomavirus vaccine impact and effectiveness through 12 years after vaccine introduction in the United States, 2003 to 2018. Ann Intern Med. 2022;175(7):918–26. https://doi.org/10.7326/m21-3798 . (In eng).

Article   PubMed   Google Scholar  

Meites E, Szilagyi PG, Chesson HW, Unger ER, Romero JR, Markowitz LE. Human papillomavirus vaccination for adults: updated recommendations of the advisory committee on immunization practices. MMWR Morb Mortal Wkly Rep. 2019;68(32):698–702. https://doi.org/10.15585/mmwr.mm6832a3 . (In eng).

CDC. HPV vaccine. 2023.  https://www.cdc.gov/hpv/parents/vaccine-for-hpv.html .  Accessed July 2023.

Petrosky E, Bocchini JA Jr, Hariri S, et al. Use of 9-valent human papillomavirus (HPV) vaccine: updated HPV vaccination recommendations of the advisory committee on immunization practices. MMWR Morb Mortal Wkly Rep. 2015;64(11):300–4 (In eng).

PubMed   PubMed Central   Google Scholar  

Healthy People 2030. U.S. Department of health and human services. 2021.  https://health.gov/healthypeople/objectives-and-data/browse-objectives/vaccination/increase-proportion-adolescents-who-get-recommended-doses-hpv-vaccine-iid-08 . Accessed July 2023.

Pingali CYD, Elam-Evans LD, Markowitz LE, Valier MR, Benjamin Fredua B, Crowe SJ, DeSisto CL, Stokley S, Singleton JA. Vaccination coverage among adolescents aged 13–17 years — national immunization survey-teen, United States, 2022. MMWR Morb Mortal Wkly Rep. 2023. https://doi.org/10.15585/mmwr.mm7234a3 .

CDC. TeenVaxView interactive! 2021. 2021. https://www.cdc.gov/vaccines/imz-managers/coverage/teenvaxview/data-reports/index.html .

Pingali C, Yankey D, Elam-Evans LD, et al. National, regional, state, and selected local area vaccination coverage among adolescents aged 13–17 years - United States, 2020. MMWR Morb Mortal Wkly Rep. 2021;70(35):1183–90. https://doi.org/10.15585/mmwr.mm7035a1 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

GDPH. Adolescent report 2020. https://dph.georgia.gov/immunization-study-reports .

Vu M, King AR, Jang HM, Bednarczyk RA. Practice-, provider- and patient-level facilitators of and barriers to HPV vaccine promotion and uptake in Georgia: a qualitative study of healthcare providers’ perspectives. Health Educ Res. 2020;35(6):512–23. https://doi.org/10.1093/her/cyaa026 . (In eng).

Dilley SE, Peral S, Straughn JM Jr, Scarinci IC. The challenge of HPV vaccination uptake and opportunities for solutions: lessons learned from Alabama. Prev Med. 2018;113:124–31. https://doi.org/10.1016/j.ypmed.2018.05.021 . (In eng).

Holman DM, Benard V, Roland KB, Watson M, Liddon N, Stokley S. Barriers to human papillomavirus vaccination among US adolescents: a systematic review of the literature. JAMA Pediatr. 2014;168(1):76–82. https://doi.org/10.1001/jamapediatrics.2013.2752 . (In eng).

Paskett ED, Krok-Schoen JL, Pennell ML, et al. Results of a multilevel intervention trial to increase human papillomavirus (HPV) vaccine uptake among adolescent girls. Cancer Epidemiol Biomarkers Prev. 2016;25(4):593–602. https://doi.org/10.1158/1055-9965.Epi-15-1243 . (In eng).

Ruffin MTT, Hade EM, Gorsline MR, et al. Human papillomavirus vaccine knowledge and hypothetical acceptance among women in Appalachia Ohio. Vaccine. 2012;30(36):5349–57. https://doi.org/10.1016/j.vaccine.2012.06.034 . (In eng).

Ryan C, Duvall KL, Weyant EC, Johnson KR, Wood D. Human papillomavirus vaccine uptake, knowledge, and acceptance for youth: a systematic review of Appalachia. J Community Health. 2018;43(3):616–24. https://doi.org/10.1007/s10900-018-0500-6 . (In eng).

Thomas TL, Strickland O, Diclemente R, Higgins M. An opportunity for cancer prevention during preadolescence and adolescence: stopping human papillomavirus (HPV)-related cancer through HPV vaccination. J Adolesc Health. 2013;52(5 Suppl):S60-68. https://doi.org/10.1016/j.jadohealth.2012.08.011 . (In eng).

Bednarczyk RA, Chamberlain A, Mathewson K, Salmon DA, Practice- OSB. Provider-, and patient-level interventions to improve preventive care: development of the P3 model. Prev Med Rep. 2018;11:131–8. https://doi.org/10.1016/j.pmedr.2018.06.009 . (In eng).

Stokols D. Translating social ecological theory into guidelines for community health promotion. Am J Health Promot. 1996;10(4):282–98. https://doi.org/10.4278/0890-1171-10.4.282 . (In eng).

Dennison C, King AR, Rutledge H, Bednarczyk RA. HPV vaccine-related research, promotion and coordination in the State of Georgia: a systematic review. J Community Health. 2019;44(2):313–21. https://doi.org/10.1007/s10900-018-0589-7 . (In eng).

Hennink M, Hutter I, Bailey A. Qualitative research methods. Thousand Oaks CA: Sage Publication; 2020.

VERBI. MAXQDA 2022. Software. 2021. https://www.maxqda.com .

Miles H, Huberman AM, Saldana J. Qualitative data analysis: a methods sourcebook. 4th. Thousand Oaks, CA: Sage Publication; 2019.

Westrick SC, Hohmann LA, McFarland SJ, Teeter BS, White KK, Hastings TJ. Parental acceptance of human papillomavirus vaccinations and community pharmacies as vaccination settings: a qualitative study in Alabama. Papillomavirus Res. 2017;3:24–9. https://doi.org/10.1016/j.pvr.2016.12.003 .

Newcomer SR, Caringi J, Jones B, Coyle E, Schehl T, Daley MF. A mixed-methods analysis of barriers to and facilitators of human papillomavirus vaccination among adolescents in Montana. Public Health Rep. 2020;135(6):842–50. https://doi.org/10.1177/0033354920954512 .

Brewer NT, Hall ME, Malo TL, Gilkey MB, Quinn B, Lathren C. Announcements versus conversations to improve HPV vaccination coverage: a randomized trial. Pediatrics. 2017;139(1):e20161764. https://doi.org/10.1542/peds.2016-1764 .

Moss JL, Reiter PL, Rimer BK, Brewer NT. Collaborative patient-provider communication and uptake of adolescent vaccines. Soc Sci Med. 2016;159:100–7. https://doi.org/10.1016/j.socscimed.2016.04.030 . (In eng).

Boyd ED, Phillips JM, Schoenberger YM, Simpson T. Barriers and facilitators to HPV vaccination among rural Alabama adolescents and their caregivers. Vaccine. 2018;36(28):4126–33. https://doi.org/10.1016/j.vaccine.2018.04.085 .

Fish LJ, Harrison SE, McDonald JA, et al. Key stakeholder perspectives on challenges and opportunities for rural HPV vaccination in North and South Carolina. Hum Vaccin Immunother. 2022;18(5):2058264. https://doi.org/10.1080/21645515.2022.2058264 .

Crosby LE, Real FJ, Cunnigham J, Mitchell M. Overcoming vaccine hesitancy using community-based efforts. Pediatr Clin North Am. 2023;70(2):359–70. https://doi.org/10.1016/j.pcl.2022.11.012 . (In eng).

Niccolai LM, Hansen CE. Practice- and community-based interventions to increase human papillomavirus vaccine coverage: a systematic review. JAMA Pediatr. 2015;169(7):686–92. https://doi.org/10.1001/jamapediatrics.2015.0310 .

Peterson CE, Silva A, Holt HK, Balanean A, Goben AH, Dykens JA. Barriers and facilitators to HPV vaccine uptake among US rural populations: a scoping review. Cancer Causes Control. 2020;31(9):801–14. https://doi.org/10.1007/s10552-020-01323-y .

Our HPV vaccination initiatives. American Cancer Society. 2023.  https://www.cancer.org/health-care-professionals/hpv-vaccination-information-for-health-professionals/our-hpv-vaccination-initatives.html . Accessed Aug 2023.

Vanderpool RC, Stradtman LR, Brandt HM. Policy opportunities to increase HPV vaccination in rural communities. Hum Vaccin Immunother. 2019;15(7–8):1527–32. https://doi.org/10.1080/21645515.2018.1553475 .

Adjei Boakye E, Nair M, Abouelella DK, et al. Trends in reasons for human papillomavirus vaccine hesitancy: 2010–2020. Pediatrics. 2023;151(6):e2022060410. https://doi.org/10.1542/peds.2022-060410 .

Head KJ, Vanderpool RC, Mills LA. Health care providers’ perspectives on low HPV vaccine uptake and adherence in Appalachian Kentucky. Public Health Nurs. 2013;30(4):351–60. https://doi.org/10.1111/phn.12044 .

McCave EL. Influential factors in HPV vaccination uptake among providers in four states. J Community Health. 2010;35(6):645–52. https://doi.org/10.1007/s10900-010-9255-4 .

Bairu W, King AR, Bednarczyk RA. Caregivers of adolescents’ motivators and barriers to vaccinating children against human papillomavirus. J Prev. 2022;43(3):407–20. https://doi.org/10.1007/s10935-022-00674-3 . (In eng).

Article   Google Scholar  

Gilkey MB, Malo TL, Shah PD, Hall ME, Brewer NT. Quality of physician communication about human papillomavirus vaccine: findings from a national survey. Cancer Epidemiol Biomarkers Prev. 2015;24(11):1673–9. https://doi.org/10.1158/1055-9965.EPI-15-0326 .

Levit LA, Byatt L, Lyss AP, et al. Closing the rural cancer care gap: three institutional approaches. JCO Oncol Pract. 2020;16(7):422–30. https://doi.org/10.1200/OP.20.00174 .

Constable C, Ferguson K, Nicholson J, Quinn GP. Clinician communication strategies associated with increased uptake of the human papillomavirus (HPV) vaccine: a systematic review. CA Cancer J Clin. 2022;72(6):561–9. https://doi.org/10.3322/caac.21753 .

Brewer NT, Mitchell CG, Alton Dailey S, et al. HPV vaccine communication training in healthcare systems: evaluating a train-the-trainer model. Vaccine. 2021;39(28):3731–6. https://doi.org/10.1016/j.vaccine.2021.05.038 .

Cherryhomes E, Guillot-Wright S. Dissemination and implementation of a text messaging campaign to improve health disparities among Im/Migrant workers. Int J Environ Res Public Health. 2023;20(7). https://doi.org/10.3390/ijerph20075311 . (In eng).

Bednarczyk RA, Nadeau JA, Davis CF, et al. Privacy in the pharmacy environment: analysis of observations from inside the pharmacy. J Am Pharm Assoc (2003). 2010;50(3):362–7. https://doi.org/10.1331/JAPhA.2010.09001 . (In eng).

White AA, Neelon B, Martin RH, et al. Predicting HPV vaccination among Tdap vaccinated adolescents in Georgia at the county level ☆ . Ann Epidemiol. 2022;70:74–8. https://doi.org/10.1016/j.annepidem.2022.03.008 .

Wercholuk A, Parikh A, Snyder R. The road less traveled: transportation barriers to cancer care delivery in the rural patient population. JCO Oncol Pract. 2022;18(9):652–62. https://doi.org/10.1200/OP.22.00122 .

Accelerating HPV Vaccine Uptake: Urgency for Action to Prevent Cancer. A Report to the President of the United States from the President’s Cancer Panel. National Cancer Institute, 2014.  https://deainfo.nci.nih.gov/advisory/pcp/annualreports/hpv/Part3Goal3.htm .  Accessed Jan 2024.

Roundtable H. School entry requirements for HPV vaccine. 2019. http://hpvroundtable.org/wp-content/uploads/2019/09/05_School_Entry_Requirements_for_HPV_Vaccination_WEB_updated.pdf .

Zimet GD, Silverman RD, Bednarczyk RA, English A. Adolescent consent for human papillomavirus vaccine: ethical, legal, and practical considerations. J Pediatr. 2021;231:24–30. https://doi.org/10.1016/j.jpeds.2021.01.026 . (In eng).

Georgia HB615: 2019-2020: regular session. https://legiscan.com/GA/bill/HB615/2019 .

Ellingson MK, Bednarczyk RA, O’Leary ST, Schwartz JL, Shapiro ED, Niccolai LM. Understanding the factors influencing health care provider recommendations about adolescent vaccines: a proposed framework. J Behav Med. 2023;46(1–2):356–65. https://doi.org/10.1007/s10865-022-00296-4 . (In eng).

Escoffery C, Petagna C, Agnone C, et al. A systematic review of interventions to promote HPV vaccination globally. BMC Public Health. 2023;23(1):1262. https://doi.org/10.1186/s12889-023-15876-5 .

Lake PW, Kasting ML, Christy SM, Vadaparampil ST. Provider perspectives on multilevel barriers to HPV vaccination. Hum Vaccin Immunother. 2019;15(7–8):1784–93. https://doi.org/10.1080/21645515.2019.1581554 . (In eng).

Bednarczyk RA, Brewer NT, Gilkey MB, et al. Human papillomavirus vaccination at the first opportunity: an overview. Hum Vaccin Immunother. 2023;19(1):2213603. https://doi.org/10.1080/21645515.2023.2213603 . (In eng).

Bednarczyk RA, Brandt HM. Descriptive epidemiology of age at HPV vaccination: analysis using the 2020 NIS-Teen. Hum Vaccin Immunother. 2023;19(1):2204784. https://doi.org/10.1080/21645515.2023.2204784 . (In eng).

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Acknowledgements

The authors would like to acknowledge the Emory Prevention Research Center Community Advisory Board members who assisted with recruiting participants and all the participants who provided their time and insight for this study.

This study was supported by Centers for Disease Control and Prevention, SIP 19–005 Cancer Prevention and Control Research Network, U48 DP006377 and Winship Cancer Institute, P30CA138292. The funders had no role in the study design, data collection, analysis, and interpretation of data and in writing the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the CDC. The authors thank the members of the Emory Prevention Research Center’s Community Advisory Board for their many contributions to this project. They thank the organizations and participants that participated in this qualitative study.

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Courtney N. Petagna, Stephen Perez, Erica Hsu, Ionie Banner & Cam Escoffery

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Contributions

C.E. and C.N.P. are responsible for the study design and oversight of the study. B.M.G. contributed to recruiting participants and to the conception of the study. C.N.P. and S.P. interviewed participants, and C.N.P., S.P., and I.B. coded transcripts. S.P., C.N.P., and C.E. contributed to the data analysis and the results. C.N.P., E.H., and C.E. contributed to the discussion. E.H. and C.N.P. prepared Fig.  1 and Table  2 . C.N.P. and I.B. prepared Tables 3. and 4 . S.P. prepared Tables 5 and 6 . C.N.P. prepared Table  1 and the Supplemental Table 1. R.A.B. contributed his model, expertise, and design of the study. All authors read, edited, and approved the final manuscript.

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Correspondence to Courtney N. Petagna .

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Petagna, C.N., Perez, S., Hsu, E. et al. Facilitators and barriers of HPV vaccination: a qualitative study in rural Georgia. BMC Cancer 24 , 592 (2024). https://doi.org/10.1186/s12885-024-12351-1

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A qualitative study to explore the burden of disease in activated phosphoinositide 3-kinase delta syndrome (APDS)

• Ian Hitchcock 1 ,
• Hanna Skrobanski 2 ,
• Elina Matter 2 ,
• Ewen Munro 1 ,
• John Whalen 1 ,
• Joanne Tutein Nolthenius 1 ,
• Alex Crocker-Buque 1 ,
• Amanda Harrington 3 ,
• Delphine Vandenberghe 1 ,
• Sarah Acaster 2 &
• Kate Williams   ORCID: orcid.org/0000-0003-4874-0334 2  

Orphanet Journal of Rare Diseases volume  19 , Article number:  203 ( 2024 ) Cite this article

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Activated phosphoinositide 3-kinase delta syndrome (APDS) is an ultra-rare primary immunodeficiency, with only 256 cases reported globally. This study aimed to explore the disease burden of APDS from the perspective of individuals with APDS and their caregivers.

Qualitative interviews were conducted with healthcare providers (HCPs), individuals with APDS and caregivers, to explore the symptoms and health-related quality of life (HRQoL) impact of APDS. Some individuals and caregivers also completed a narrative account exercise. All interviews were audio recorded and transcribed. Data were analysed using thematic analysis and saturation was recorded.

Semi-structured qualitative interviews were conducted with healthcare providers (HCPs), individuals with APDS and caregivers. Individuals and caregivers had the option of completing a narrative account exercise. Six HCPs participated in an interview. Seven participants completed the narrative account exercise ( N  = 5 caregivers and N  = 2 individuals with APDS) and 12 took part in an interview ( N  = 4 caregivers and N  = 8 individuals with APDS). Themes identified from HCPs interviews included symptoms, clinical manifestations, HRQoL impacts and treatments/management of APDS. The narrative account exercise identified similar themes, but with the addition to the journey to diagnosis. These themes were explored during the individual/caregiver interviews. Reported clinical manifestations and symptoms of APDS included susceptibility to infections, lymphoproliferation, gastrointestinal (GI) disorders, fatigue, bodily pain, and breathing difficulties. HRQoL impacts of living with APDS included negative impacts to daily activities, including work, education and social and leisure activities, physical functioning, as well as emotional well-being, such as concern for the future, and interpersonal relationships. Impacts to caregiver HRQoL included negative impacts to physical health, work, emotional well-being, interpersonal relationships and family life and holidays. The management of APDS included the use of healthcare services and medications including immunoglobulin replacement therapy (IRT), rapamycin, prophylactic antibiotics, leniolisib, as well as medical procedures due to complications.

Conclusions

APDS has a high disease burden and there is an unmet need for licensed, more targeted treatments which modify disease progression. This study was the first to describe the day-to-day experience and HRQoL impact of APDS from the perspective of individuals living with the condition, caregivers and treating physicians.

Activated phosphoinositide 3-kinase delta syndrome (APDS) is an ultra-rare primary immunodeficiency (PID) first characterised in 2013, with only 256 cases reported globally [ 1 , 2 , 3 , 4 , 5 ]. The disease is categorised into two types depending on the causal mutation, with APDS1 associated with the PIK3CD mutation, and APDS2 with the PIK3R1 mutation [ 2 , 6 ]. Conventional medical interventions for APDS include preventative antibiotics, immunoglobin replacement therapy (IRT), immunosuppressive therapies and haematopoietic stem cell transplant (HSCT) [ 1 , 3 , 4 , 6 ]. However, most of these interventions are not disease modifying agents and are primarily focused on managing and treating the symptoms of APDS. HSCT is potentially curative but is accompanied by the risk of complications (such as Graft-versus-Host Disease) and associated mortality [ 7 ]. Additionally, despite the historically available treatments, individuals with APDS experience the risk of a reduced lifespan with the most common causes of death being lymphoma and complications resulting from HSCT [ 8 ]. Most recently, leniolisib (CDZ173), an oral inhibitor of the p110δ subunit of PI3Kδ, was approved by the United States (US) Food and Drug Administration (FDA) in March 2023, and is the first approved medication for the treatment of APDS [ 6 , 9 ].

Commonly cited manifestations of APDS include, but are not limited to, recurrent respiratory tract infections [ 2 , 3 , 6 , 10 , 11 , 12 ], chronic lung diseases such as bronchiectasis and asthma [ 13 , 14 ], herpes virus infections, gastrointestinal (GI) disorders, and autoimmune and autoinflammatory disorders, as well as chronic non-malignant lymphoproliferation including generalised lymphadenopathy and hepatosplenomegaly [ 2 , 3 , 4 , 6 , 10 ]. Additionally, individuals with APDS are at greater risk of developing haematologic malignancies such as diffuse Large B cell lymphoma [ 4 ] and may have growth and neurodevelopmental abnormalities [ 3 , 10 , 15 ]. However, to date, no studies have explored the HRQoL impacts of these symptoms and manifestations on individuals or caregivers.

Qualitative research enables an in-depth exploration of a disease's impact, allowing participants to share their experiences beyond the constraints of closed-question surveys or questionnaires. This is particularly valuable in rare diseases, such as APDS, as it can highlight previously unknown symptoms and impacts. No qualitative studies have previously been conducted with individuals with APDS or their caregivers. Therefore, the primary aim of this study was to qualitatively explore the symptoms, impacts and challenges experienced by individuals with APDS, as well as experience with treatment for APDS. The secondary aim was to explore the experience of caring for and treating an individual with APDS.

Design and participants

The main component of this study included qualitative interviews of individuals with APDS and caregivers. These were informed by healthcare provider (HCP) interviews and a narrative account exercise, completed by a selection of individuals with APDS/caregivers prior to their interview. To take part in the study, individuals had to have a confirmed diagnosis with APDS and be aged 12 years or older. Caregivers were eligible to participate if they were a parent or other caregiver providing ≥ 50% care to an individual with a confirmed diagnosis of APDS and were willing and able to consent to take part. The only exclusion criterion for caregivers was paid caregivers. HCPs were eligible if they were currently a registered nursing professional or licensed physician, with experience working with at least one individual with APDS.

Study materials

Three semi-structured interview guides were developed for the individual/caregiver interviews, which were tailored to either 1) adults with APDS, 2) adolescents with APDS or 3) caregivers. The guides were developed based on findings from a targeted literature search, the HCP interviews, and the individual/caregiver narrative accounts. The guides included open-ended questions on symptoms, treatments and impacts of living with APDS or caring for someone with APDS, including perceptions of meaningful change in symptoms and impacts.

An HCP interview guide, background questionnaires for HCPs, individuals and caregivers, and instructions for the narrative account exercise with individuals and caregivers, were also developed.

Ethical approval

The study was reviewed and approved by Western Institutional Review Board (WIRB-Copernicus Group Independent Review Board (IRB tracking number: 20226879).

Recruitment and data collection

Recruitment took place through a specialist recruitment agency between January and June 2023. HCPs were sought from Canada, France, Germany, Italy, Spain, and the United Kingdom (UK). Individuals APDS and caregivers were sought from Australia, Canada, France, Germany, Italy, Spain, the Czech Republic, the Netherlands, the Republic of Ireland, the UK, and the United States (US). HCPs were invited to participate in the study by the recruitment agency via email. Individuals with APDS and caregivers were either invited by email (if they were part of a patient database) or direct social media message, or responded to a recruitment advertisement. Potential patients were asked to contact the recruitment agency using the contact details provided. Adult individuals/caregivers and parents/legal guardians of adolescent individuals gave written informed consent to participate or their child to participate in the study, while adolescent individuals gave written assent. Most caregiver participants included in the study were not attached to study participants who had APDS. However, three caregivers took part alongside their child in the interviews, and another caregiver took part in the narrative account while their child subsequently took part in the interview alone. It was not known whether HCPs were attached to an individual with APDS in the study as this information was not collected, and HCPs and individuals with APDS were recruited independently.

All participants received an information sheet about the study alongside a background questionnaire to complete and return by email. A selection of individuals and caregivers were invited to participate in the narrative account exercise prior to an interview. This involved asking participants to write or record a voice note with an unstructured detailed account of their experience of APDS and return via email.

HCPs interviews were conducted in February 2023, and individual/caregiver interviews were conducted between February and June 2023. Individuals and caregivers re-confirmed their consent/assent verbally at the start of each interview. All interviews were conducted over teleconference, lasted approximately 60 min, and were audio-recorded. All HCP interviews, and the English language individual/caregiver interviews were conducted in English by two study authors (HS and EM), both with an MSc or PhD in Psychology and more than 13 years combined qualitative research experience. The non-English individual/caregiver interviews were conducted by trained interviewers in each study country in the local language. Some parents/legal guardians of adolescent individuals were present during interviews when requested by the care recipient. None of the participants were known to the interviewers.

Recordings were transcribed verbatim, and non-English transcripts and written accounts were translated into English. All transcripts and written accounts were de-identified and assigned participant identification numbers.

Quantitative data collected from the background questionnaires were summarised using descriptive statistics in Excel [ 16 ]. Qualitative data collected from the narrative accounts and interviews with individuals with APDS, caregivers and HCPs were analysed separately using thematic analysis in MAXQDA [ 17 ].

Two researchers (HS and EM) independently developed and tested an initial coding framework on the same section of a transcript or narrative account. For each dataset, the coding was compared and an inter-coder agreement on the final frameworks were reached before the entire narrative accounts or transcripts were coded. A senior researcher, (KW) also reviewed the initial and revised coding frameworks to enhance the quality of the analysis. Concepts were identified from the coded segments from each dataset and grouped into themes. Data saturation for the individual /caregiver interviews was monitored using a saturation grid, with concepts in columns and interview participants as rows.

A conceptual model was developed using the concepts identified from the individual/caregiver interviews to provide a visual representation of the burden of living with APDS and the relationships between concepts.

Sample characteristics

Six HCPs with experience treating individuals with APDS participated in an interview. All were licensed physicians, with clinical specialties in immunology ( n  = 3; [50.0%]), haematology ( n  = 2; [33.3%]) and internal medicine ( n  = 1; [16.6%]). Physicians’ years of experience in the role ranged from 19–32 years, and years of experience specifically treating individuals with APDS ranged from 3–15 years. Four HCPs had experience with treating five or more individuals with APDS.

Seven participants completed the narrative account exercise ( N  = 5 caregivers and N  = 2 individuals with APDS), at which point enough information was collected to inform the development of the interview guides. Twelve participants took part in an interview ( N  = 4 caregivers and N  = 8 individuals with APDS). Tables 1 and 2 provide more detail on the demographic and clinical characteristics of individuals with APDS.

Healthcare professional (HCP) interview findings

HCPs reported a range of symptoms and clinical manifestations associated with APDS, including susceptibility to infections ( n  = 6), lymphoproliferation ( n  = 6), GI issues ( n  = 5), autoimmune and autoinflammatory disorders ( n  = 5), neuropsychiatric disorders ( n  = 5) and fatigue ( n  = 2). Variations in symptoms and clinical manifestations based on clinical status (e.g. more active lymphoproliferation in more advanced individuals with APDS) ( n  = 4), and disease progression (e.g. malignancies) ( n  = 3), were also discussed. HCPs also noted variations with age ( n  = 3), with a higher prevalence of recurrent respiratory infections in paediatric individuals with APDS. In contrast, adults with APDS were reported to have more frequent or severe clinical manifestations (e.g. more gastrointestinal issues) ( n  = 3). HCPs reported perceived impacts on individuals with APDS, including work and school ( n  = 3), daily and social activities ( n  = 5) and emotional well-being ( n  = 3). Three HCPs perceived the HRQoL of their individuals with APDS as low ( n  = 2) or moderate ( n  = 1).

All six HCPs discussed immunoglobulin replacement therapy (IRT) as a treatment for APDS, including intravenous immunoglobulin (IVIG) and subcutaneous immunoglobulin (SCIG) therapies. Reported benefits of IRT included its affordability and accessibility ( n  = 1), and its perceived impact on improving quality of life and reducing bacterial infections. One HCP reported that they avoid prescribing it due to the risk of adverse drug reactions which could be fatal. Reported side effects of IRT included headaches ( N  = 1), body aches ( N  = 1), chills ( N  = 1), fever ( N  = 1), malaise ( N  = 1), local pain at the injection site ( N  = 1) and fatigue ( N  = 1).

Four HCPs reported on their experience treating patients with leniolisib. Potential benefits of leniolisib included its perceived impact on reducing infection frequency ( N  = 1), diminishing lymphoproliferation ( n  = 3), improving fatigue ( N  = 1) and improving clinical biomarkers ( N  = 3), such as immunoglobulin levels. However, one HCP also expressed concerns about the lack of long-term safety data for leniolisib, and another reported that one of their patients had experienced a temporary elevation in hepatic enzymes, aspartate transaminase (AST) and alanine transaminase (ALT).

Perceived attributes of a successful treatment in general included stopping disease progression ( n  = 2), improvements in clinical biomarkers ( n  = 2), a reduction in infection frequency and associated symptoms ( n  = 2), and improvements in lymphoproliferation ( n  = 1). All HCPs ( n  = 6) discussed the need for targeted treatments for APDS. One HCP discussed that a key attribute of a successful treatment is for the patient to regain their quality of life.

“…the main goal for anyone I’m treating with APDS is to return, to retain and [be] able to gain back their quality of life that they’ve been missing on because of the impact of this illness on their life.” - HCP 201, Haematologist, UK

Additional example quotes describing the key insights from the HCP interviews are provided in Additional Material 1.

Individual with APDS and caregiver narrative account exercise findings

All participants ( N  = 7) provided a written account, ranging between 1–4 pages in length. The main themes raised were: (1) Journey to diagnosis; (2) Clinical manifestations and symptoms of APDS; (3) Impacts on APDS patient’s HRQoL; (4) Caregiver HRQoL impacts and family HRQoL impacts; and (5) APDS management. Example quotes from the narrative account exercise describing the perspective of individuals with APDS and their caregivers are provided in Additional Material 2.

Individual with APDS and caregiver interview findings

The main themes identified from the interviews included clinical manifestations, symptoms, functional issues, HRQoL impacts and APDS management. The relationships between these themes are shown in a conceptual model (Fig.  1 ). Data saturation was reached for the broad overarching themes, with 78.1% of the individual with APDS concepts and 57.1% of the caregiver concepts reported in the first five interviews (Table  3 ).

Conceptual model of the experience of APDS. The top line of the conceptual model underneath the ‘living with APDS’ box, shows the clinical manifestations of APDS and associated complications. The second line shows the symptoms associated with APDS which were described to be caused by different clinical manifestations or to be general symptoms of the condition and the third row shows functional issues that were described to be caused by the symptoms of APDS rather than to be a direct consequence of APDS or associated clinical manifestations. The final row shows the HRQoL impacts reported to be associated with clinical manifestations, symptoms, and functional issues as well as management of APDS. Arrows show reported relationships between concepts

Clinical manifestations and associated symptoms of APDS

All participants ( n  = 12) reported susceptibility to infections as a clinical manifestation of APDS. Types of infections included ear infections ( n  = 10), sinus infections ( n  = 8), eye infections ( n  = 7), fungal infection ( n  = 1), and respiratory infections and associated complications such as pneumonia ( n  = 7), colds ( n  = 3), flu ( n  = 3), bronchitis ( n  = 2) and bronchiectasis ( n  = 3). Participants described various forms of lymphoproliferation, including enlarged nymph nodes ( n  = 8), spleen ( n  = 5), tonsils ( n  = 4), adenoids ( n  = 3) and liver ( n  = 1) as well as nodular lymphoid hyperplasia ( n  = 3). Other disorders associated with APDS reported by participants were autoimmune or autoinflammatory disorders ( n  = 8), physical developmental disorders ( n  = 6), blood coagulation disorders ( n  = 3), anaemia ( n  = 2), kidney and liver disease ( n  = 1) and thrombocytopenia ( n  = 1). Participants reported the various impacts of these additional disorders, including difficulty in movement ( n  = 2) due to their legs being different lengths ( n  = 1) or low muscle mass ( n  = 1) and concerns around future family planning because of delayed puberty ( n  = 2).

APDS and its clinical manifestations were reported to be associated with a range of symptoms, including bodily pain ( n  = 12), fatigue ( n  = 11), GI symptoms ( n  = 10) such as diarrhoea ( n  = 7) and constipation ( n  = 6), and breathing difficulties ( n  = 9). Other symptoms reported by more than one participant included skin rashes ( n  = 4) and mouth sores ( n  = 4).

Impact of clinical manifestations and symptoms on daily life and HRQoL

Participants reported that bodily pain ( n  = 7), fatigue ( n  = 6) and breathing difficulties ( n  = 3) all impaired their physical functioning, including their ability to stand, walk and climb stairs without assistance:

“There was a point where I had to be in a wheelchair and on oxygen because my lungs weren’t able to work by themselves.” - Participant 203, 16-year-old individual with APDS, US

Further, participants reported that fatigue ( n  = 8), breathing difficulties ( n  = 5), GI disorders ( n  = 3) impacted their daily activities, including their ability to work, and partake in housework and social and leisure activities, and their sleep. For example, one individual with APDS stated that their GI disorders would require them always to be near a toilet:

“I felt like I couldn’t even go do anything because I had to always be around the toilet, like I couldn’t get in the car because I was too scared I would have to go to the bathroom.”- Participant 204, 28-year-old individual with APDS, US

Some participants reported lymphoproliferation impacted their sleep ( n  = 3) and their ability to eat ( n  = 1) due to associated breathing and swallowing difficulties.

“She would end up choking and gagging on stuff because she couldn’t swallow very well because of the tonsils” - Participant 201, caregiver of 3-year-old individual with APDS, US

Several participants described how infections, or the risk of infections, impacted their / their care recipients’ lives such as restrictions to their social and leisure activities due to the need to shield. Six participants reported regular absences from work or school due to illness resulting in gaps in learning or career development.

“I had gaps in learning because I was off ill. I think science and maths said to mum one parents’ evening that, ‘She’ll be here one lesson, she’ll then be off one or two lessons and then she’ll be back but she misses that link between the two lessons, so she’ll get one lesson and get the other one but she’ll miss the middle lesson link’ so I didn’t do very well in certain subjects because I didn’t have the links” - Participant 101, 24-year-old patient, UK.

Seven participants reported emotional impacts, such as the fear of socialising, and loneliness due to having to shield themselves from potential infections.

“I fear going to prom, I fear going to graduation, I fear going to a lot of big events because I worry about what I might catch and if I’ll come back from it” - Participant 202, 17-year-old individual with APDS, US

Other emotional impacts included concerns for the future ( n  = 6) including worry about disease progression ( n  = 3), loneliness ( n  = 4), anxiety ( n  = 3), depression ( n  = 3), frustration ( n  = 2) and feeling downhearted ( n  = 1).

“I worry about lymphoma, especially since I’m predisposed to the lymphoma cancer, and for me it can at times become very overwhelming” - Participant 208, 56-year-old patient, US

Likewise, four participants reported impacts to their interpersonal relationships because of APDS, which mostly derived from a lack of understanding of APDS by their peers ( n  = 3).

“When everybody found out that we had an immunodeficiency, APDS, they thought that it was contagious. We were barred from ever being friends with anybody” - Participant 202, 17-year-old individual with APDS, US.

Perceived impact of improved symptoms on HRQoL

Participants described how an improvement in symptoms, such as, GI disorders ( n  = 5 out of 6 asked), fatigue ( n  = 11 out of 12 asked), bodily pain ( n  = 7 out of 7 asked) and breathing difficulties ( n  = 1 out of 1 asked) would have a meaningful impact on their lives.

“It would be nice for her to enjoy a family vacation. We’re taking her to Disney, and that was where we went last time, and she didn’t really get to enjoy it much. She slept through half of the princesses that she wanted to see.” – Participant 201, caregiver of 3-year-old individual with APDS, US

Six of nine participants asked, reported that an improvement in susceptibility to infections would have a meaningful impact on individuals’ lives, attributed to improvements in their ability to carry out daily activities such as school, work, and social and leisure activities, as well as recovery from infections and frequency of medical appointments.

“It would be more meaningful if I could spend more time with my friends without having to worry about getting as sick” - Participant 204, 28-year-old individual with APDS, US

Two individuals ( n = 10 not asked) stated an improvement to lymphoproliferation would be meaningful to their HRQoL due to reduced pain and worry about developing cancer.

“It would be very meaningful, not having to worry about the lumps, not having to worry about those lumps turning into lymphoma, the pain, obviously.” - Participant 401, 38-year-old individual with APDS, Australia

Management of APDS

Participants described their prolonged journey to diagnosis ( n  = 7), taking three to 22 years duration from when they first developed symptoms to receiving an official diagnosis of ADPS. Two caregivers expressed the negative emotional impact of having to wait for their care recipient’s illness to be diagnosed. Participants also reported negative experiences of using healthcare services for APDS, such as HCPs dismissing their concerns ( N  = 1) and HCP’s lack of understanding about APDS restricting their ability treat the condition ( N  = 3).

“I think sometimes [HCPs] get to a point where they don’t know what else to do to help [daughter] and so then we get pushed down on the totem pole as far as people to call back or respond to or follow up with because they kind of hit a road block and don’t know how else to help” - Participant 201, caregiver of 3-year-old individual with APDS, US

Participants discussed the frequency of medical appointments as every six months ( n  = 4), once a month ( n  = 2) or a couple times a week ( n  = 1). Likewise, the reported time taken for medical appointments ranged from two to three hours ( n  = 4) to a couple of days ( n  = 1). Further, most participants ( n  = 10) reported that they (or their care recipient) had experienced emergency hospital admission relating to APDS, for reasons such as having pneumonia ( n  = 1) and experiencing fever ( n  = 1) and shingles ( n  = 1). Participants also mentioned the use of prophylactic antibiotics to prevent infections ( n  = 7) and other types of antibiotics in response to developing infections ( n  = 5).

For participants with experiences with IRT ( n  = 11), ten reported that IRT had a positive effect on reducing APDS symptoms. However, eight of these participants also reported side effects, including headaches ( n  = 3), pain at infusion site ( n  = 3), fatigue ( n  = 2), itch ( n  = 1), nausea ( n  = 1), kidney pain ( n  = 1) and kidney issues ( n  = 1).

Participants reported various impacts of APDS management, including frequent or prolonged time off work or school ( n  = 8), the need to plan medical care before leaving home ( n  = 5) and concern for the future due to the impact of frequent IRT administration ( n  = 1).

“The intravenous immunoglobulin [intravenous IRT] has brought my look on life a little to the breaking point because I struggle with, “Well who’s going to cover this if I get a job? What am I going to do when I do have to go off to college? Where am I going to see my nurse?” - Participant 202, 17-year-old individual with APDS, US

Two participants had experience with leniolisib ( n  = 2). One individual with APDS, who had received leniolisib for over four years, reported improvements such as their tonsils not growing back again after a tonsillectomy, stabilising lung capacity and breathing, fewer periods of hospitalisation and illness. They also reported gaining weight but viewed this as a disadvantage. The other participant, a caregiver, reported no changes in their 12-year-old adolescent care recipient’s symptoms or impacts since they started leniolisib four months previously; however, they questioned their care recipient’s dosage strength. The caregiver also reported that their care recipient (not a participant) experienced bouts of extreme tiredness in the initial stages of treatment.

Participants reported the characteristics of a successful treatment, including improved symptoms ( n  = 6) and clinical outcomes ( n  = 2), living a normal life ( n  = 2) as well as no need ( n  = 1) or a reduced dosage ( n  = 1) for medication.

Caregiver HRQoL impacts

Four caregivers described the HRQoL impacts of caring for someone with APDS. Three reported spending a substantial time providing care, which included managing referrals and medical appointments ( n  = 4), administering medication ( n  = 3), complicated medical procedures ( n  = 2), ordering medical supplies ( n  = 2), research on APDS ( n  = 1) and managing insurance ( n  = 1).

“It’s really hard sometimes. Learning how to do quite a complicated medical procedure that has to be done in a sterile way. There’s specialist skills that you have to develop in terms of needles and all that kind of thing” - Participant 102, caregiver of 11-year-old individual with APDS, UK

Three caregivers reported impacts to their physical health, including physical tension ( n  = 1), fatigue ( n  = 1), and sleep difficulties ( n  = 1) due to the stress of caring for a child with APDS.

“I was just in such worry for the child that I’d sometimes get up in the night just to make sure she was okay or worrying when I’d go to work. My physical health I’d say was just more sleep deprived” - Participant 205, caregiver of 10-month-old individual with APDS, US

All caregivers ( n  = 4) reported impacted daily activities which mostly pertained to work, including reduced working hours ( n  = 2) or quitting their job completely ( n  = 1) to cope with caring responsibilities. One caregiver reported missing out on employment advancement opportunities and conflict with their co-workers.

“I’ve possibly missed some employment advancement opportunities because of my absence and it also can cause a bit of strife with co-workers who happen to pick up my end of the workload while, in my absence.” - Participant 205, caregiver of 10-month-old individual with APDS, US

Moreover, all caregivers reported an impact to their emotional well-being, including reports of loneliness and isolation ( n  = 2), anxiety ( n  = 2), depression ( n  = 1), low moods ( n  = 1) and feelings of stress ( n  = 1), irritability ( n  = 1) and hopelessness ( n  = 1).

Finally, three caregivers reported an impact to their family life, which included restrictions to family holidays due to risk of infection ( n  = 1) or logistical concerns around treatment schedule ( n  = 1) or medical equipment ( n  = 1). Two caregivers reported avoiding leisure activities to shield due to the patient’s risk of infections.

“We don’t get together with people like we used to, just because either A, it’s not exposing her to other stuff, or we’re too tired to or she just is not feeling up to it, and so then we cut that out.” - Participant 201, caregiver of a 3-year-old individual with APDS, US

This was the first qualitative study exploring the impact of APDS from the perspective of individuals with APDS and caregivers. It provides several insights into the humanistic burden of the disease. While clinical studies have previously reported symptoms, functions, and clinical manifestation of APDS, this study augments this by highlighting the specific impacts that these have on the daily life and HRQoL of individuals living with the condition [ 9 , 18 , 19 ]. Living with APDS was reported to substantially impact the HRQoL of individuals, including work and education, social and leisure activities, household chores, physical functioning, relationships, and emotional well-being, such as concern for the future. Participants also highlighted the burden experienced by individuals with APDS associated with attending frequent medical appointments, having numerous periods of hospitalisation, and organising and planning around their medical care (e.g., IRT administration). Participants additionally described how the prolonged journey to APDS diagnosis, and their perceptions that HCPs lack of knowledge about this ultra-rare condition, added to their emotional burden.

The conceptual model expands these findings by illustrating the relationship between the clinical manifestations, symptoms, functional issues, and impacts. The interconnectivity of these factors highlights how an improvement or worsening in one area has a knock-on effect on other symptoms and areas of life. For instance, based on the model, an improvement in lymphoproliferation has the potential to lead to improvements in symptoms and functional issues, such as pain, breathing difficulties, and physical function, which may in turn lead to improvements in HRQoL impacts, such as worry about developing lymphoma and ability to take part in leisure and social activities.

The study also highlighted caregiver burden in APDS. Identified caregiver impacts included impacts on daily activities (particularly involving work), emotional well-being, interpersonal relationships, and physical health. Family impacts were also reported, such as restricted ability to partake in social and leisure activities as a family or going on family holidays due to life evolving around the individual with APDS’s needs.

Although this was the first qualitative study exploring the HRQoL of individuals with APDS, its findings are consistent with studies investigating the HRQoL of individuals with other PIDs. Compared to healthy individuals, people with PIDs experience significantly lower HRQoL [ 20 ]. Studies have shown that HRQoL in children with primary antibody deficiencies similar to APDS are often worse than the HRQoL of children with other chronic conditions [ 21 , 22 ].

Some limitations were present within this study. Firstly, although participants were sought from across Australia, Canada, the US and Europe, the majority were recruited from the US, potentially impacting the transferability of the results to other individuals with APDS and caregiver populations. However, there is no published evidence to suggest that individuals with APDS and their caregivers within these countries would experience HRQoL vastly differently from those within the US and further research is needed to confirm the transferability of these results across study populations. Additionally, some volunteer and non-response bias may be present within the study sample, as recruitment was determined by participants’ volition. Individuals who volunteer for a study may possess distinct characteristics compared to those that do not. However, qualitative research is not designed to be representative, and, as APDS is an ultra-rare disease, recruitment relied on a limited pool of individuals agreeing to participate. The data saturation matrix for the individual/caregiver interviews indicated that saturation had been reached, with most concepts first being mentioned spontaneously within the first five interviews. However, given the heterogeneity in the reported clinical manifestations, symptoms and functional issues, additional interviews may have identified new concepts. It is also worth noting that the insights gathered from the caregivers interviewed on behalf of individuals with APDS relied purely on observation and may not have directly reflected their care recipient's experience.

This is the first study to describe the day-to-day experience and HRQoL impact of this ultra-rare condition, APDS, from the perspective of individuals, and their caregivers, as well as the perspective of treating physicians. The findings highlight a high disease burden and the substantial unmet need in this population for more licensed and targeted effective treatments which modify disease progression, and that are less burdensome than conventional treatments (e.g., oral medication). Moreover, the findings emphasise the need for better awareness and understanding of the symptoms and manifestations of APDS, including any differences between paediatric and adult patients, to limit the risk of misdiagnosis and shorten the time to referral to an immunologist to obtain a diagnosis and initiate effective treatment options.

Availability of data and materials

Raw data (interview transcripts) are not publicly available to protect participant privacy, as APDS is a rare disease and there are few participants in each country.

Moriya K, Mitsui-Sekinaka K, Sekinaka Y, Endo A, Kanegane H, Morio T, et al. Clinical practice guideline for activated phosphatidyl inositol 3-kinase-delta syndrome in Japan. Immunol Med. 2023;13:1–5.

Google Scholar  

Ewertowska M, Grześk E, Urbańczyk A, Dąbrowska A, Bąbol-Pokora K, Łęcka M, et al. Activated phosphoinositide 3-kinase delta syndrome 1 and 2 (APDS 1 and APDS 2): similarities and differences based on clinical presentation in two boys. Allergy Asthma Clin Immunol. 2020;16(1):22.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Michalovich D, Nejentsev S. Activated PI3 Kinase Delta Syndrome: From Genetics to Therapy. Front Immunol. 2018;27:9.

Jamee M, Moniri S, Zaki-Dizaji M, Olbrich P, Yazdani R, Jadidi-Niaragh F, et al. Clinical, Immunological, and Genetic Features in Patients with Activated PI3Kδ Syndrome (APDS): a Systematic Review. Clin Rev Allergy Immunol. 2020;59(3):323–33.

Article   CAS   PubMed   Google Scholar  

Hanson J, Bonnen PE. Systematic review of mortality and survival rates for APDS. Clin Exp Med. 2024;24(1):17.

Coulter TI, Cant AJ. The Treatment of Activated PI3Kδ Syndrome. Front Immunol. 2018;7:9.

Justiz Vaillant AA. Modi P. Graft-Versus-Host Disease: Mohammadi O; 2024.

Hanson J, Bonnen PE. Real-world evidence of mortality and survival rates in 256 individuals with APDS. Available from: https://doi.org/10.1101/2022.12.05.22283110

Hoegenauer K, Soldermann N, Zécri F, Strang RS, Graveleau N, Wolf RM, et al. Discovery of CDZ173 (Leniolisib), Representing a Structurally Novel Class of PI3K Delta-Selective Inhibitors. ACS Med Chem Lett. 2017;8(9):975–80.

Singh A, Joshi V, Jindal AK, Mathew B, Rawat A. An updated review on activated PI3 kinase delta syndrome (APDS). Genes Dis. 2020;7(1):67–74.

Elkaim E, Neven B, Bruneau J, Mitsui-Sekinaka K, Stanislas A, Heurtier L, et al. Clinical and immunologic phenotype associated with activated phosphoinositide 3-kinase δ syndrome 2: A cohort study. Journal of Allergy and Clinical Immunology. 2016;138(1):210-218.e9.

Lucas CL, Zhang Y, Venida A, Wang Y, Hughes J, McElwee J, et al. Heterozygous splice mutation in PIK3R1 causes human immunodeficiency with lymphoproliferation due to dominant activation of PI3K. J Exp Med. 2014;211(13):2537–47.

Condliffe AM, Chandra A. Respiratory Manifestations of the Activated Phosphoinositide 3-Kinase Delta Syndrome. Front Immunol. 2018;5:9.

Coulter TI, Chandra A, Bacon CM, Babar J, Curtis J, Screaton N, et al. Clinical spectrum and features of activated phosphoinositide 3-kinase δ syndrome: A large patient cohort study. Journal of Allergy and Clinical Immunology. 2017;139(2):597-606.e4.

Conti F, Catelli A, Cifaldi C, Leonardi L, Mulè R, Fusconi M, et al. Case Report: Hodgkin Lymphoma and Refractory Systemic Lupus Erythematosus Unveil Activated Phosphoinositide 3-Kinase-δ Syndrome 2 in an Adult Patient. Front Pediatr. 2021;8:9.

Microsoft Corporation. Microsoft Excel. Microsoft Corporation. 2023.

VERBI Software. MAXQDA 2022 [Internet]. Berlin, Germany: VERBI Software; 2021 [cited 2023 Aug 10]. Available from: https://www.maxqda.com

Rao VK, Webster S, Šedivá A, Plebani A, Schuetz C, Shcherbina A, et al. A randomized, placebo-controlled phase 3 trial of the PI3Kδ inhibitor leniolisib for activated PI3Kδ syndrome. Blood. 2023;141(9):971–83.

Rao VK, Webster S, Dalm VASH, Šedivá A, van Hagen PM, Holland S, et al. Effective “activated PI3Kδ syndrome”–targeted therapy with the PI3Kδ inhibitor leniolisib. Blood. 2017;130(21):2307–16.

Anderson JT, Cowan J, Condino-Neto A, Levy D, Prusty S. Health-related quality of life in primary immunodeficiencies: Impact of delayed diagnosis and treatment burden. Clin Immunol. 2022;236:108931.

Peshko D, Kulbachinskaya E, Korsunskiy I, Kondrikova E, Pulvirenti F, Quinti I, et al. Health-Related Quality of Life in Children and Adults with Primary Immunodeficiencies: A Systematic Review and Meta-Analysis. J Allergy Clin Immunol Pract. 2019;7(6):1929-1957.e5.

Article   PubMed   Google Scholar  

Titman P, Allwood Z, Gilmour C, Malcolmson C, Duran-Persson C, Cale C, et al. Quality of Life in Children with Primary Antibody Deficiency. J Clin Immunol. 2014;34(7):844–52.

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Acknowledgements

Editorial support was provided by Sebastian Snow of Acaster Lloyd Consulting.

The study was funded by Pharming Group N.V.

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Ian Hitchcock (IH), Hanna Skrobanski (HS), Elina Matter (EMa), Ewen Munro (EMu), John Whalen (JW), Joanne Tutein Nolthenius (JTN), Alex Crocker-Buque (ACB), Amanda Harrington (AH), Delphine Vandenberghe (DV), Sarah Acaster (SA) and Kate Williams (KW) were the authors of the study. The study was conceived by IH, KW and SA. All authors (IH, HS, EMa, EMu, JW, JTN, ACB, AH, DV, SA and KW) made a substantial contribution to the design of the study. The study materials were developed by HS, EMa and KW and all other authors (IH, EMu, JW, JTN, ACB, AH, DV, and SA) provided feedback. The English language interviews were conducted by HS and EMa. The analysis was conducted by HS and EMa, with review by KW. The manuscript was drafted by HS, EMa, and KW, with medical writer support and all other authors (IH, EMu, JW, JTN, ACB, AH, DV, and SA) provided feedback on the draft manuscript. All authors (IH, HS, EMa, EMu, JW, JTN, ACB, AH, DV, SA and KW) approved the final submitted version.

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Correspondence to Kate Williams .

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The study was reviewed and approved by Western Institutional Review Board (WIRB-Copernicus Group Independent Review Board (IRB tracking number:20226879).

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Ewen Munro (EMu), John Whalen, Joanne Tutein Nolthenius, Alex Crocker-Buque and Delphine Vandenberghe are all employees of Pharming Group N.V and may hold stock or stock option in the company. Amanda Harrington is an employee of Pharming Healthcare, Inc. and may hold stock or stock option in the company. Ian Hitchcock was an employee of Pharming Group N.V. and may hold stock or stock option in the company. Hanna Skrobanski, Elina Matter (EMa) and Kate Williams are employees of Acaster Lloyd Consulting and may hold stock or stock options in the company. Sarah Acaster is a company director of Acaster Lloyd Consulting.

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Supplementary Information

13023_2024_3215_moesm1_esm.docx.

Additional file 1: Additional Material 1. HCP Interview findings. Exemplary quotes from HCPS describing their experiences with APDS.

13023_2024_3215_MOESM2_ESM.docx

Additional file 2: Additional Material 2. Patient/Caregiver narrative account findings. Exemplary quotes from patients and caregivers describing their experiences with APDS.

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Hitchcock, I., Skrobanski, H., Matter, E. et al. A qualitative study to explore the burden of disease in activated phosphoinositide 3-kinase delta syndrome (APDS). Orphanet J Rare Dis 19 , 203 (2024). https://doi.org/10.1186/s13023-024-03215-9

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Received : 22 November 2023

Accepted : 10 May 2024

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DOI : https://doi.org/10.1186/s13023-024-03215-9

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