People differ in whether they understand graphical or numerical representations of statistical information better. However, assessing these skills is often not feasible when deciding which representation to select or use. This study investigates whether people choose the representation they understand better, whether this choice can improve risk comprehension, and whether results are influenced by participants’ skills (graph literacy and numeracy).In an experiment, 160 participants received information about the benefits and side effects of painkillers using either a numerical or a graphical representation. In the “no choice” condition, the representation was randomly assigned to each participant. In the “choice” condition, participants could select the representation they would like to receive. The study assessed gist and verbatim knowledge , accessibility of the information, attractiveness of the representation, as well as graph literacy and numeracy.In the “choice” condition, most (62.5%) chose the graphical format, yet there was no difference in graph literacy or numeracy (nor age or gender) between people who chose the graphical or the numerical format. Whereas choice slightly increased verbatim knowledge, it did not improve gist or overall knowledge compared with random assignment. However, participants who chose a representation rated the representation as more attractive, and those who chose graphs rated them as more accessible than those without a choice.The sample consisted of highly educated undergraduate students with higher graph literacy than the general population. The task was inconsequential for participants in terms of their health.When people can choose between representations, they fail to identify what they comprehend better but largely base that choice on how attractive the representation is for them.People differ systematically in whether they understand graphical or numerical representations of statistical information better. However, assessing these underlying skills to get the right representation to the right people is not feasible in practice. A simple and efficient method to achieve this could be to let people choose among representations themselves.However, our study showed that allowing participants to choose a representation  did not improve overall or gist knowledge compared with determining the representation randomly, even though it did slightly improve verbatim knowledge.Rather, participants largely chose the representation they found more attractive. Most preferred the graphical representation, including those with low graph literacy.It would therefore be important to develop graphical representations that are not only attractive but also comprehensible even for people with low graph literacy. A promising avenue in this regard are graphical representations of statistical information, which can improve understanding of medical risks and promote healthy behaviors.69Making informed health decisions requires understanding of basic statistical information about the benefits and side effects of medical treatments and other health-relevant behaviors. It is well documented, however, that understanding statistical information is quite challenging for most people, including for experts.10 one important caveat is that graphical representations cannot be assumed to be intuitively understandable by everyone. Rather, people differ in how well they understand graphical representations. This competency has been coined as graph literacy1113 and is distinct from the ability to understand numerical information (numeracy5). In fact, research showed that people with low graph literacy may actually be better off with mere numbers.However, while the use of graphical representations is often recommended as an aid for the interpretation of numerical data,The question thus arises how to get the right representation to the right person, that is, a representation  that this person understands well. Assessing patients’ graph literacy and numeracy prior to presenting medical information is time-consuming and potentially awkward, so that it is often not feasible in practice. A much simpler and more feasible method consists in letting people choose which representation they would like to receive themselves, rather than deciding it for them. To improve knowledge, this method would require that people are able to identify the representation that they comprehend better, that is, the representation that fits to their graph literacy and numeracy skills. In this study, we therefore investigate whether allowing people to choose a representation of statistical information does indeed improve knowledge and increases the fit to the underlying skills, compared with a situation in which the representation is randomly assigned. Hawley et al., Tait et al., and Tiede et al.), we assessed 2 different types of knowledge: verbatim knowledge  and gist knowledge . Further, we assessed participants’ ratings of subjective accessibility of the information and the attractiveness of its representation.To investigate this question, we conducted an experiment in which participants received statistical information about the benefits and side effects of a painkiller medication. The central manipulation was that half of the participants could choose whether they wanted a graphical or a numerical representation of that information, whereas the other half of the participants received 1 of the 2 representations at random. At 2 time points of measurement, we assessed how well they comprehended (T1) and recalled (T2) the statistical information that they received. The 2 time points were primarily used to enhance the sensitivity to detect differences by avoiding potential ceiling effects and to check potential effects for robustness. In line with previous research  Which representation will be chosen predominantly, and who chooses the graphical rather than the numerical representation? 2) Does being able to choose between numerical and graphical representations foster knowledge of statistical information in comparison with random allocation to either graphical or numerical representations? 3) Does choice increase ratings of accessibility and/or attractiveness, suggesting that either of those attributes may play a role in choosing?20 and they are rated as more attractive, helpful, or likeable in comparison with numbers,2123 which even holds true for people with low graph literacy.Based on the existing literature, we can expect that most people will choose the graphical rather than the numerical representation: graphs are generally preferred,25 People choosing graphical representations may additionally have lower numeracy on average, because it is particularly those with low numeracy who benefit from graphical representations.27But do people—despite this general preference for graphical representations—choose the representation that fits to their skills such as graph literacy and numeracy, at least to some degree? If this were the case, then people who select graphical rather than numerical representations should have higher graph literacy on average, because research has shown that people with high graph literacy benefit particularly from graphical representations.29 and may thus also prefer numbers over graphs. Furthermore, it has been shown that people with low numeracy focused on graphical information much earlier than people with high numeracy, which makes it plausible to assume that people with low numeracy would also be more likely to choose graphical representations. Finally, people seem to have some insight into their own graph literacy and numeracy skills, given that people’s subjectively rated graph literacy and numeracy correlate well with the actual abilities.29Conversely, people higher in numeracy prefer to receive numerical instead of verbal information3134 others have found that people fare better with formats they preferred.36If people who can choose between representations actually succeeded in choosing the representation that they understand better, they should perform better when confronted with knowledge questions compared with people who randomly received either of the representations, and this should hold true for both individuals who choose graphical and individuals who choose numerical representations. Previous research has studied whether people better understand formats they preferred and found mixed results. While some studies found that preferences were unrelated to knowledge,However, all of these conclusions were based on correlational results. In addition, in most studies, participants provided their preference ratings for all representations, these ratings did not have any consequences, and they were provided only after working with multiple different formats. However, letting people work with all representations before choosing would not be a feasible solution for everyday medical decision making. In sum, to the best of our knowledge, there is no study that has directly tested whether providing the opportunity to choose a representation prior to a knowledge task poses a promising approach to improve knowledge of medical information.). If choice were based on attractiveness, attractiveness ratings should generally be higher when people choose their representation, for both numbers and graphs. If choice were based on what people believe to understand well, then this could be reflected not only in higher actual performance but also in higher perceived accessibility of the information.Subjective ratings of the accessibility of the information as well as of the attractiveness of the representation could yield additional insights into how representations are chosen. As mentioned above, graphical representations have generally been found to be rated as more attractive than numerical ones  in comparison with a placebo. The clinical evidence was taken from 3 Cochrane reviews,ally see .After providing informed consent and stating demographic characteristics, participants were randomly assigned to the “no choice” or “choice” conditions and were provided with information about the medications. Within the “no choice” condition, half of the participants were randomly assigned to receive the numerical representation of the information, while the other half was randomly assigned to receive the graphical representation of the information. Within the “choice” condition, participants saw a brief example of what the numerical and graphical representation would look like and could decide which one they wanted to receive.All participants received an actual printout of the information, either as numerical or graphical representation, and were asked a series of questions about the medication with the printout directly in front of them (T1). These questions concerned comprehension of the information, subjective evaluations of perceived accessibility of the information, and subjective attractiveness ratings of the representation . Next, participants returned the printout with the representation to the experimenter and filled out the graph literacy and numeracy scale. Then, there was a 120 min break. During this break, participants attended to a lecture and a practice exercise about a topic unrelated to the current research . After this break, participants received a task in which they had to recall the same knowledge questions that they had answered previously but without being provided with the information (T2).knowledge if we average across comprehension [T1] and recall [T2]), (perceived) accessibility of the information, and attractiveness of the representation; numeracy was included as a covariate.In sum, the independent variables were condition (“no choice” v. “choice”), whether participants worked with the numerical or the graphical representation of the information, and their graph literacy. The dependent variables were comprehension and recall of both verbatim and gist knowledge .All knowledge questions as well as subjective ratings were previously used by Gaissmaier et al.Supplementary Materials. With both scoring methods, the gist knowledge score is the average proportion of correct answers and was assessed with identical questions at T1 and T2. Missing cells were treated as mistakes.Gist knowledge reflects the essential understanding of the information and was assessed with 5 qualitative questions that were nonnumerical and asked for ordinal comparisons between the painkillers . To answer these questions correctly, participants needed to consider the differences a medication made in comparison with a placebo group; for instance, whether side effects were more frequently observed in the medication compared with the placebo group. This placebo scoring is therefore how we scored the answers to the gist knowledge question for the main text. However, participants may have erroneously looked at only the medication condition, ignoring the placebo condition. Therefore, we also checked the results with an alternative medication-only scoring scheme and will report only its most central findings in the main text, whereas the details are reported in the Verbatim knowledge reflects the precise quantitative understanding and was assessed with 8 quantitative questions that asked for numerical statements and comparisons. To answer those questions, participants needed to read off frequencies from the information chart  and compute absolute differences between 2 frequencies from the information chart . The verbatim knowledge score is the average proportion of correct answers and was assessed with identical questions at T1 and T2. Missing cells were treated as mistakes.not at all) to 5 (very much). They covered the following aspects: comprehensibility, usefulness, seriousness, intuitive accessibility, and difficulty of answering the questions. Answers were averaged to generate 1 accessibility score for each participant, excluding missing items. The internal consistency of this scale was acceptable (Cronbach’s α = 0.66).Subjective accessibility of the information was assessed with 5 questions, each of which could be answered on a 5-point scale ranging from 1  to 5 (very attractive). They covered the following aspects of the representation: overall impression, attractiveness of colors, imagery, technical implementation, size, font size, font, and composition. Answers were averaged to receive 1 attractiveness score for each participant, excluding missing items. The internal consistency of this scale was good (Cronbach’s α = 0.87).Subjective attractiveness of the representation was assessed with 8 questions, each of which could be answered on a 5-point scale ranging from 1 . The graph literacy score corresponds to the proportion of questions answered correctly.We assessed graph literacy using the Spanish translation of the Graph Literacy Scale. The scale assesses an individual’s knowledge of health-related information based on graphical representations with 13 items on 3 levels of difficulty: reading the data , reading between the data , and reading beyond the data . The English and German versions of this scale were validated on nationally representative samples in Germany and the United States and showed good psychometric properties.r[154] = 0.25, P = 0.002). Numeracy was assessed using a 9-item questionnaire that consisted of 3 items by Schwartz et al. and 6 items by Lipkus et al. The scale assesses an individual’s ability to use and process probabilistic and numerical concepts. For example, one item was, “If the chance of getting a disease is 10%, how many people would be expected to get the disease out of 1,000?” This scale has been validated on nationally representative samples. The numeracy score corresponds to the proportion of questions answered correctly.We assessed numeracy as a control variable, because it is correlated with graph literacy (in our sample: M = 24.0 y old (s = 4.1 y). Mean graph literacy was 0.81 (s = 0.11) and mean numeracy was 0.83 (s = 0.18).One hundred sixty participants (80 in each of the conditions “choice” and “no choice”) were included in the study that comprised working with the materials (T1) and the recall test (T2). All participants were students at the University of Granada, Spain, and they received course credit for participation. The sample included 78 females and was https://osf.io/c94hj/?view_only=38e293b9ff9c47a7af624361898cda7a.The data and analysis script for this study are openly available at As presented in P = 0.033.We first checked whether participants in the “choice” condition were more likely to choose one of the representations by comparing the actual choice proportions with a 50/50 split, using a binomial test. Participants were generally more likely to choose the graphical representation than the numerical one. Of the 80 participants in this condition, there were 50 participants (62.5%) who chose the graphical representation but only 30 (37.5%) who chose the numerical representation, which we compared to 50% each expected by chance with a binomial test, t tests. As presented in tWelch(43.49) = 0.820, P = 0.42, numeracy, t(76) = 0.420, P = 0.68, age, t(78) = 0.528, P = 0.60, and gender, χ2 = 0.013, P = 0.91, respectively.Within the “choice” condition, we then tested whether participants who chose the graphical condition had higher graph literacy and lower numeracy scores than those who chose the numerical representation, using  based on which we expected an important interaction of graph literacy with representation, whereas for numeracy, we merely expected a general effect on knowledge, but no interactions. Controlling for numeracy is still important, because it is correlated with graph literacy, and this procedure allowed us to assess effects of graph literacy that go above and beyond numeracy.To analyze whether knowledge differed between the “no choice” and the “choice” condition, we ran a linear mixed-effects model with random intercepts for participants. The outcome variable was knowledge and the predictors were time  and knowledge type , the between-subjects factors condition , representation , graph literacy (centered), and all possible interactions. Numeracy (centered) was included as a covariate. Note that including graph literacy as a predictor variable, yet numeracy only as a covariate, was done in line with a related study,Supplementary Materials, Table S4). In that model, the results were similar if not explicitly mentioned. Four participants did not fill out the numeracy questionnaire, and due to row-wise deletion of missing data in the mixed-effects models, they were not included in the analysis that included numeracy as a predictor or covariate. We also tested whether our results were robust to including these 4 participants but excluding numeracy as a covariate and found results similar to those reported below.As a robustness check, we nevertheless also ran the same model with numeracy as a predictor  and to include a continuous predictor , as suggested by Magezi.s = 13.4 v. low: s = 14.6; bGraphLiteracy = 0.35, SE = 0.10, P < 0.001). People higher in numeracy, however, had slightly lower overall knowledge .People higher in graph literacy had overall higher knowledge . Importantly, simple effects analyses revealed that choice improved knowledge neither for people who saw graphs  nor for people who saw numbers .In contrast to our expectations, choice did not generally improve knowledge , which was not the case for gist knowledge . Note, however, that the interaction disappeared in the model with numeracy as predictor rather than a covariate ; thus, it should be interpreted with caution.Choice did, however, specifically increase verbatim knowledge , but there was no interaction between condition and knowledge type . Simple effects analyses revealed that this overall effect of choice was again exclusively driven by the same specific effect of choice on verbatim knowledge , in the absence of an effect on gist knowledge . In the end, we thus consider the results of medication-only scoring to be similar to placebo scoring.Interestingly, in contrast to (our default) placebo scoring, if we scored gist knowledge with medication-only scoring, choice increased overall knowledge . As illustrated in  the effect of representation was different for people with low versus high graph literacy . Simple effects analyses revealed that specifically people with low graph literacy performed better with numbers than with graphs , whereas those with high graph literacy did not reliably perform better with graphs than with numbers .Participants who worked with numbers were overall better than those who worked with graphs , representation , and graph literacy (centered) and their interactions. Numeracy (centered) was included as a covariate but did not yield any effect on accessibility and attractiveness  and is thus not further discussed in detail here. For both models, the results were similar when running a model with numeracy as predictor and when excluding numeracy as a covariate or predictor. The results are illustrated in s = 0.70 v. graphs: s = 0.67; bRepresentation = 0.08, SE = 0.11, P = 0.46) and did not depend on graph literacy . Choice did not generally result in enhanced accessibility . Choice did, however, lead to enhanced accessibility of the graphical representation in comparison to no choice , which was not the case for the numerical representation .Participants’ ratings of accessibility did not differ between graphs and numbers , but attractiveness ratings did not depend on graph literacy . Choice generally resulted in enhanced attractiveness, . This effect did not seem to differ between the numerical and graphical representation . However, when analyzing the effect of choice separately for numerical and graphical representation, the effect of choice was significant only for the numerical representation  but not for the graphical representation .Participants generally rated graphs as more attractive than numbers . Thus, the question emerged of how it could alternatively be decided who receives which kind of representation. A simple and potentially effective way would be to allow people to choose themselves which kind of representation they prefer.Not everyone benefits from graphical representations of statistical information, and for some people, numerical representations are actually better suited to foster knowledge.). However, this choice was clearly not based on individual skills such as graph literacy or numeracy: participants who chose the graphical representation did not differ with regard to graph literacy or numeracy from those who chose the numerical representation, and they also did not differ in terms of age and gender. Thus, even though it has been documented that people have a sense for their skills (by moderate correlations between objective and subjective measures of graph literacy and numeracy19), that does not seem to determine their choice for a representation. This finding is in line with a study that asked participants who worked with different representations to rank order their preferences for a numerical and 2 graphical representations and found no differences in graph literacy for rank-ordered preferences.We were first asking which representation gets chosen more often and whether people chose representations in line with underlying skills, particularly graph literacy, but also numeracy. In line with previous research, most participants chose the graphical over the numerical representation  percentage points in the knowledge score with 80% (90%) power. Thus, our study had been able to detect a substantial effect of choice on overall knowledge but not effects smaller than that. It is debatable whether effects smaller than about 6 percentage points would be clinically relevant in the first place, given baseline knowledge scores of about 70% (across types of knowledge and measurement times).Our second question was whether allowing people to choose the representation would yield better objective comprehension and recall of the information, which could be the case if choice fosters the match between people’s abilities and chosen representations. Our results, however, show that choosing does not increase comprehension and recall overall. To test whether this null effect could be attributed to limited power to detect a significant effect, we ran a simulation-based sensitivity analysis following DeBruine and Barr44 Finally, the effect of choice on verbatim knowledge was not perfectly robust to the exact specifications of the model, as it largely disappeared when including numeracy as predictor rather than as a covariate . On the other hand, with medication-only scoring of gist knowledge, there was a reliable effect of choice on overall knowledge, even though the difference was only 3.1 percentage points. As this effect was again solely driven by the specific effect of choice on verbatim knowledge, similar to (our default) placebo scoring, this does not change our overall conclusion: there is a specific and small effect of choice on verbatim knowledge and recall. Yet more substantial, and more general, knowledge improvements would have been possible had participants based their choice more strongly on their skills, as predictable differences in performance we found illustrate: replicating the findings of Gaissmaier et al. and Garcia-Retamero and Galesic, performance with the different representations (numbers versus graphs) depended on graph literacy, such that particularly participants with low graph literacy achieved better gist and verbatim knowledge with the numerical than the graphical representation.With regard to different types of knowledge, choice did not affect gist knowledge and recall at all, yet it slightly increased verbatim knowledge compared with the “no choice” condition. However, although this increase in verbatim knowledge was statistically significant, it is unclear whether this increase of about 5 percentage points on 1 knowledge dimension is clinically relevant given a baseline performance of about 70% (across both points in time). Furthermore, whereas having precise verbatim knowledge about clinical options is clearly important, gist knowledge may in fact matter more for making medical decisions. As the association between choice and attractiveness is merely a correlation in these data, we cannot be certain about the direction of the effect. However, it speaks against mere postdecision effects that accessibility ratings were not also generally increased, but future research would be needed to tell more precisely.The third and final question was whether subjective ratings of accessibility and/or attractiveness would be increased in the “choice” condition, revealing potential motifs of choosing a particular representation. In line with the general preference for the graphical representation, attractiveness ratings of the graphical representation were higher than those of the numerical representation. Importantly, choice consistently increased ratings of attractiveness in comparison with the randomly allocated representations, for both numbers and graphs. This suggests that perceptions of how attractive particular representations are for individual participants played an important role when they chose between representations. Of course, there could additionally be an effect in the other direction, that is, from choice to attractiveness. It is very well documented that people judge options to be more desirable after they have chosen them, even if desirability was identical before making the choice.r = −0.19, P = 0.017).Whereas choice did not generally increase rated accessibility, it specifically increased ratings of accessibility for the graphical representation. Yet this increased accessibility did not translate into increased overall knowledge scores, as summarized above. In fact, when looking at bivariate correlations between ratings of accessibility and the various knowledge scores , it turns out that they are, by and large, uncorrelated with one another; in one case, there is even one small negative correlation, indicating lower gist knowledge at T1 with higher ratings of accessibility  revealed a general preference for the graphical representation, and this preference was not related to abilities ; 2) did not yield better comprehension and recall overall; and 3) was correlated with increased attractiveness ratings for chosen representations compared with their randomly allocated counterparts and for graphs additionally with increased perceived accessibility (without translating into increased knowledge). Taken together, letting patients choose the representation is not an efficient way to ensure they receive a representation that they understand or recall well. Although choice improved verbatim knowledge, this limited benefit is not enough to recommend giving patients the opportunity to choose a representation as an approach to improve knowledge of medical information. Rather, these results suggest that people choose the representation they thought of as more attractive and, at least for graphs, the one they believe to more accessible, rather than choosing the one that they objectively comprehend better.). On one hand, this prohibits generalization to the overall public. On the other hand, it is actually striking that even within such a limited range of graph literacy, substantial differences in understanding the graphical representation of the statistical information can be observed, and we could replicate the findings of Gaissmaier et al., which had a more diverse sample. It seems plausible to assume that those differences would be larger in the general population, but this is, of course, an empirical question.Several limitations of the study need to be taken into consideration when interpreting the results. First, the sample consisted of a diverse yet highly educated group of students who are not representative of the general population in Spain. Consequently, they have higher graph literacy scores than an average person randomly drawn from the population  incentives make a difference for behavior are mixed,9 but also in light of its correlation with graph literacy in this data (r = 0.25), which is somewhat lower than what has been observed elsewhere14 but not zero and/or completely out of range. With a very high average proportion correct on the numeracy scale (0.83), a potential ceiling effect could be an explanation, even though this did not occur for graph literacy with a similarly high average proportion correct (0.81). However, numeracy was much more skewed than graph literacy, with the most frequently observed score being a perfect numeracy score . This may, at least in part, explain why we did not find the expected effect of numeracy.Furthermore, there are some peculiarities in the data that we would like to discuss transparently. The first peculiarity is that numeracy was not at all related to comprehension, recall, or accessibility ratings . This is surprising in light of the vast literature showing the impact of numeracy on understanding health-related statistical information79 other research challenges the assumption that graphical representations would be helpful for everyone but stresses the importance of graph literacy as a prerequisite in this regard.24 Also here, it was particularly those with low graph literacy for whom numbers turned out to be substantially better than graphs. This replication of this very specific interaction between graph literacy and the kind of representation (numbers v. graphs) generally underpins the quality and reliability of the data at hand. Yet it does not rule out that the specific graphical representation we used was less understandable than others and that also the results could thus be different for other graphical representations. In any case, the results highlight the need for designing more easily understandable graphical representations, which we will further discuss in the Conclusion.The second peculiarity is that comprehension and recall were, on average, better with the numerical than with the graphical representation. Whereas a substantial amount of literature suggests that graphical representations are helpful to understand statistical information,48 as well as to improve knowledge of less graph-literate individuals.People differ in which kind of representation of statistical information they understand best: Some people understand graphical representations better, others are better off with mere numbers. Yet assessing their abilities to understand graphical and numerical information is infeasible in practice. Giving patients the opportunity to decide which representation to receive could have been a very efficient way to provide those information representations to patients that fit their abilities and thus improve comprehension and recall. However, despite some very minor benefits for verbatim knowledge, overall this approach is not sufficient to improve comprehension and recall of medical information. Instead, people seem to choose the representation they perceive as more attractive. Thus, improving knowledge by getting the right representation to the right people would require other methods of tailoring rather than choice, yet those would need to be feasible in practice. As graphical representations were rated as being more attractive and are preferred by a majority, there is another solution to improve knowledge that requires further work, however: to develop better graphical representations that are so clearly designed that they are understandable for broader audiences—including for those with low graph literacy. Important steps in that direction include adding numerical and textual information to graphs that simply describes what can be seen, which has been shown to improve performance and reduce the impact of numeracy,Click here for additional data file.Supplemental material, sj-docx-1-mdm-10.1177_0272989X231201579 for The Lure of Beauty: People Select Representations of Statistical Information Largely Based on Attractiveness, Not Comprehensibility by Wolfgang Gaissmaier, Kevin E. Tiede and Rocio Garcia-Retamero in Medical Decision Making


Female representation at scientific conferences is crucial for encouraging women pursuing an academic career. Nevertheless, gender inequity at urological conferences is common place and women are often stereotyped choosing functional urology. However, there is no evidence whether female representation is higher in functional urology. This investigations aims to analyze gender representation at functional urology sessions.National and international urological congresses between 2019 and 2021 with a focus on functional urology and female urology sessions were evaluated. Congresses were categorized as national or international. Session type, topic, gender of chairs and speakers of the identified sessions were recorded. In addition, affiliation and medical specialty were collected for chairs.p = 0.076). When considering gender distribution of chairs, the gap was more pronounced by 35.5%. Furthermore, men were more likely to be invited to be a speaker in plenary and podiums sessions.A total of 29 congresses were evaluated. Out of a total of 2893 chairs and speakers, 1034 (35.7%) were women and 1839 (63.6%) were men. This represents an overall gender gap of 27.9% for functional urology sessions. No significant differences in gender representation between national and international congresses could be identified (Gender inequality is present in functional urology sessions. There is a need for greater efforts to achieve gender equality. An important step to remedy the situation is the inclusion of women in scientific program committees. Furthermore, support by the leadership of urological societies and academic departments is essential to herald a lasting change in gender inequality. Involvement in academic conferences is an important gateway to an academic career and continues to be routine part of an academic career path . The preThe degree of female representation and how welcoming such meetings are to women is also dependent on the disciplines addressed and content of conferences . In thisThe current study is at assessing contemporary gender representation in functional urology and female urology sessions through an analysis of various national and international congresses and scientific meetings.p value < 0.05 was considered significant. Statistical analysis was performed using SPSS 27 .National and international urological congresses between 2019 and 2021 with focus on the topics of functional urology and female urology were evaluated. No ethical vote was required because no human being or animal was involved in this study. Selected were national and international urological and/or urogynaecological and/or neurourological congresses. Only sessions targeting functional urology and female urology were included. If international congresses were evaluated, the host country was recorded. Congresses in Belgium, France, Germany, Italy, Portugal, Turkey, Spain, United Kingdom, Sweden, Switzerland, Australia and United States were evaluated. Congresses were categorized in national and international types. Session type, topic and gender of chairs and speakers of the identified sessions were recorded. In addition, affiliation and medical specialty (urology vs. other) were collected for chairs. Descriptive analysis was applied. Univariate analysis to identify correlations between gender and the collected variables was performed. The Cochrane–Mantel–Haenszel test was used to assess independence of categorical predictors associated with congress type. A p = 0.076).A total of 29 national and international congresses in 12 different European countries, and two congresses in the United States and Australia, were evaluated. A total of 2893 chairs and speakers were available for analysis. Of these, 1034 (35.7%) were women and 1839 (63.6%) were men, whereas 20 (0.7%) gender were not identifiable. This represents an overall gender gap of 27.9%. No significant differences in gender representation between national and international congresses could be identified (p = 0.465). This indicates a pooled gender gap for chairs in functional urology of 35.5%.A total of 758 chairs were identified in functional and female urology topics, distributed by 357 (47.1%), 131 (17.3%) and 270 (35.6%) for the years of 2019, 2020 and 2021, respectively. 482 (63.3%) chairs were represented in national and 276 (36.4%) in international congresses. Gender distribution was 513 (67.7%) and 244 (32.2%) for male and female chairs, respectively. One (0.1%) gender reference was missing. No significant difference of gender distribution between the years could be identified (p = 0.130). Considering gender distribution by medical specialty, significant more women were invited outside of the urology community. Female urologist chairs were only represented by 24.1% in the congresses compared to balanced gender distribution (49% vs. 51%) if chairs were invited outside of the urology field ] and Belgium . Countries with less than 60% male chair representation were Sweden [n = 36 (59.0%)], United Kingdom [n = 9 (45%)] and the United States [n = 10 (43.5%)].Countries with more than 80% male chair representation were Turkey  and Portugal [n = 46 (85.2%)], whereas countries with less of 60% male speaker representation were Sweden [n = 155 (59.4%)], the United Kingdom [n = 33 (58.9%)] and Italy [n = 121 (47.3%)].Countries with more than 80% of male speaker representation were Turkey [The current investigation aimed to evaluate the gender representation at functional urology and female urology sessions in international and national urologic academic meetings. On assessment of chair and speaker representation, we identified an overall gender gap of 28%. This gap was more pronounced in gender representation of chairs of sessions with a gap of 35.5%. Interestingly, considering only chairs who were invited originated from outwith the urology field, a balanced gender representation was achieved. By contrast, female chairs invited from the urology field were underrepresented by 24%. Furthermore, in terms of the gender gap for speakers was 25%. Plenary/Podiums sessions were uniformly dominated by male in both, chair and speaker categories, compared to other session types. No differences of gender representation of chairs and speakers between national and international congresses could be identified in functional urology. Interestingly, less than 60% male representation for chairs and speakers were consistently identified in Sweden and United Kingdom.This study confirmed the existing gender gap for functional urology sessions. A comparable analysis of the North American Neuromodulation Society meeting identified similar results, although a steadily increase of female speaker representation over the last 5 years was observed . NeverthWomen are often choose to go into functional urology based on stereoptypical pereception based on gender , 13. ThiFurthermore, male speakers and chairs were preferably invited for plenary and podiums sessions. This finding is consistent with the literature and is a recognised problem in academia in general , 7. A coIt has been demonstrated, that female scientists with identical qualifications and experience are judged to be less competent than their male counterparts, receive less mentoring offers and have lower starting salaries . Male prThe increase of female representation depends on the individual societies efforts to aim diversity. Whereas some did not demonstrate any change of female representation over a 5 year period, others included, amongst others implementations, women in the program committees and achieved higher female representation . In thisThe inclusion of women into the program committees has been identified as crucial factor for increasing female representation at conferences , 16–18. On the other hand, women also have an important part to play. When women are invited for academic conferences, they should accept . Women hWe acknowledge some limitations of the current study. Chairs and speakers varied between the included countries limiting the comparative analyses. Furthermore, gender could not be or not clearly identified in some cases, although this number was low. Comparative analysis between countries was limited due to imbalanced number conferences included per country.Furthermore, this study addressed only one of the factors potentially involved in discrimination, which is gender. Other possible sources of discrimination exist including identity, sexual orientation, cultural practices, ethnicity and race , 19. TraAcademic conferences are a crucial gateway to an academic career . The numGender equality is our collective responsibility . Female


The aim of our study is to evaluate the usability of the Free Gingival Graft (FGG) procedure, which is included in YouTube videos, in both patient information and student education. A search was performed on YouTube on December 1, in 2022, using the search term ‘‘Free Gingival Graft’’. First 150 videos were pre-evaluated, and 67 videos were included in the study. The length of the videos, the number of views, the number of likes, the presence of animation and the number of months after uploading were evaluated. The quality of the videos was evaluated and analyzed with The Global Quality Score (GQS), Usefulness Score (US) and The Journal of American Medical Association (JAMA) scores.p<0.001). A positive correlation was found between viewer interaction, video duration and quality scores. The median values of the quality scores were 2 for the GQS, 2 for the JAMA score and 1 for the Usefulness score. The level of quality scores was found to be insufficient . There is a high level, positive and statistically significant correlation between the GQS and the Usefulness score (r=0.858 and  YouTube videos containing the FGG procedure were found to be insufficient for both student education and patient information purposes. Key words:Medical education, free gingival graft, patient information, social media, youtube. Apical displacement of the gingival soft tissue margin from the enamel-cementum junction is defined as gingival recession and isa common clinical feature in the general population ,2. PerioThe main indications for root coverage procedures are aesthetic demands, treatment of tooth sensitivity, and enhancement of keratinized tissue to reduce the risk of defect progression ,7. GingiAlthough there are many soft tissue augmentation procedures to increase the width of keratinized tissue, FGG is the one of the most preferred procedures . Free giYouTube is a very popular website that people easily access, thousands of new videos are uploaded every day and millions of videos are watched daily ,17. VisuIn a study in the literature, 76.8% of individuals/patients declared that they use the internet for health purposes . AlthougThis study does not contain any human or animal resources, ethical approval was not needed for this study. Patient information was not used in the study. Therefore, the patient consent document was not obtained.- YouTube Search and exclude criteriaIn this study, a search was performed on YouTube on December 1, 2022, using the search term ‘‘Free Gingival Graft’’. Based on the relevance to this keyword, the first 150 videos were recorded for assessment. Videos not related to the title, repetitive videos containing different procedures, and videos that do not contain all of the FGG procedures were not included in the study. The videos were watched by a single physician and their stated features were analyzed. Video length in seconds, view counts, number of likes, number of dislikes, video category (animation or not), video content, days since upload, and source of upload (uploader) were recorded. The usability of the videos in patient education was evaluated using the Global Quality Score (GQS) . The qua- Quality ScoresJAMA scoring system : The JAMCriteria Description:Authorship; Author and contributor credentials and their affiliations should be provided.Attribution; Clearly lists all copyright information and states references and sources for content.Currency; Initial date of posted content and subsequent updates to content should be provided.Disclosure; Conflicts of interest, funding, sponsorship, advertising, support, and video ownership should be fully disclosed.Global quality score criteria : Non-speScore Description of quality:Score 1. Poor quality; is unlikely of be to use for patient education.Score 2. Poor quality; is of limited use to patients because only some information is presentScore 3. Suboptimal quality and flow; is somewhat useful to patients; important topics are missing, some information is present.Score 4. Good quality and flow; useful to patients because most important topics are covered.Sroce 5. Excellent quality and flow; is highly useful to patients.The Usefullness Score for Students : Eight tA score of 0 to 2 showed the content of poor [1] video that composed misleading information and was not all useful information about eight domains evaluated;A score of 3 to 5 showed the content of moderate [2] video that gave a positive message related to FGG but poorly discussed some domains;A score of 6 to 8 showed the content of excellent [3] video that gave detailed, valid and correct information for students recorded a usefulness score.The usefulness score was determined based on quality and flow of the content;poor [1]: poor quality, poor flow, missing and inadequate information.moderate [2]: moderate quality, suboptimal flow, adequate information about content.excellent [3]: excellent quality and flow, comprehensive and very useful information.All data from 67 videos were statistically analyzed.- Statistical analysisp<0.05.Data analysis was performed with IBM SPSS Statistics Version 26 package program. The conformity of the data to the normal distribution was tested with the Kolmogorov Smirnov test of normality. Descriptive statistics of information about videos and scores are given as number (n), percentage (%), minimum value, maximum value and median (Q1-Q3). Spearman correlation test was used to determine the relationship between non-normally distributed video feature measurements and scores. The Kruskal Wallis test was used to compare the GQS and JAMA score medians according to the Usefullness classification, which has three categories. The Mann Whitneu U test was used to compare the medians of the score and video characteristics according to their genre, anime or not, doctor or not. All the results obtained were considered statistically significant at 67 videos were included in the study. 49 of these videos were uploaded by a doctor. While 9 of the videos are animated, 58 of them are not animated, and SDG surgery is shown on patients. Descriptive statistics of video-related features and quality scores are given in p<0.001). Similarly, there is a high, positive and statistically significant correlation between the number of video views and the rate of viewing (r=0.879 and p<0.001). Considering the number of video views and the viewer interaction, there is a low, negative and statistically significant correlation (r=-0.376 and p=0.002). There is a high, positive and statistically significant correlation between the number of likes and the view rate (r=0.896 and p<0.001). There is a weak, positive and statistically significant correlation between the number of likes and the duration of the video (r=0.274 and p=0.005).Correlations between video features and Quality scores are given in p<0.001). There is also a weak, positive and statistically significant correlation between viewer interaction and GQS (r=0.365 and p=0.002). In addition, there is a weak, positive and statistically significant correlation between viewer interaction and Usefulness score (r=0.301 and p=0.013).There is a weak, positive and statistically significant correlation between viewer interaction and video duration (r=0.457 and p<0.001). There was a weak, positive and statistically significant correlation between video duration and JAMA score (r=0.431 and p<0.001). There is a moderate, positive and statistically significant correlation between video duration and usefulness score (r=0.509 and p<0.001).There was a moderate, positive and statistically significant correlation between video duration and GQS (r=0.528 and p=0.001). There is a high level, positive and statistically significant correlation between the GQS and the usefulness score (r=0.858 and p<0.001). There is a weak, positive and statistically significant correlation between JAMA score and usefulness score (r=0.391 and p=0.001).Correlations between Quality Scores are given in p<0.001).There is a statistically significant difference in terms of GQS medians and JAMA score medians between the poor, moderate, and excellent classes of Usefulness (While there was a statistically significant difference between the animated and non-animated videos in terms of the number of views, medians of viewing rates and JAMA score medians, there was no statistical difference in other features and quality scores .While a statistically significant difference was found between the medians of the number of views and the medians of the JAMA score between the video source and non-doctor, there was no significant difference between the other features .et al. compared the information about cardiovascular mechanism in textbook and YouTube videos and showed that using YouTube can be ideal as a textbook (The internet is an easily accessible resource for health services and a comprehensive source of information ,18. In ttextbook . In our In the current study, in terms of content, 60% of YouTube videos were found insufficient for patient education, 70% for student education, and the quality of videos on YouTube was found to be insufficient for use for these purposes. When the literature is examined; Similar to our study, in an article investigating the quality of dental implants as content on YouTube, it was determined that YouTube has very limited quality . YouTubeIn our study, it was observed that the scores measuring the video quality increased significantly as the duration of the videos increased. In a previous study, it was seen that the video length was effective in the decision to watch or not watch the video . For thiIn our study, it was observed that there was a positive and significant relationship between the video duration of the viewer interaction, GQS and US scores. In other words, the level of likes of the watched video was determined to be related to the quality of the video . The posIt is important to indicate for that there are some limitations in our study. As one of them, YouTube is a dynamic platform and the results have the potential to change depending on the upload of new videos in different time zones. Another limitation is that the videos that will be met by individuals when they search YouTube using other expressions other than the word "free gingival graft" may be different.Students and patients frequently use technological opportunities today, but technology offers many advantages when it is used correctly. Although the use of YouTube videos has advantages such as being cheap and easy, its use in student education and patient information is not sufficient for FGG, which is a periodontal surgery option.


Malnutrition is associated with a high risk of mortality in adults with ischemic stroke (IS). This study aimed to investigate the relationship between malnutrition and the risk of stroke-associated pneumonia (SAP) as only a few studies examined the relationship between malnutrition and the risk of SAP in IS.Patients were included from emergency departments of five tertiary hospitals in the REtrospective Multicenter study for Ischemic Stroke Evaluation (REMISE) study from January 2020 to December 2020. Malnutrition was defined according to the Controlling Nutritional Status (CONUT), Geriatric Nutritional Risk Index (GNRI), and Prognostic Nutritional Index (PNI) systems. Multivariable logistic regression analysis was used to explore the association between malnutrition and risk of SAP.P < 0.001), CONUT , and GNRI  scores. Furthermore, adding malnutrition assessment indices to the A2DS2 score significantly improved the ability to predict SAP by analysis of receiver operating characteristic curves and net reclassification improvement.We enrolled 915 patients with IS, 193 (14.75%), 495 (54.1%), and 148 (16.2%) of whom were malnourished according to the PNI, CONUT, and GNRI scores, respectively. SAP occurred in 294 (32.1%) patients. After adjusting for confounding influencing factors in the logistic regression analysis, malnutrition  was independently associated with an increased risk of SAP based on the PNI (odds ratio [OR], 5.038; 95% confidence interval [CI] 2.435–10.421, Malnutrition was notably prevalent in patients with IS and independently associated with an increased risk of SAP. Further studies are required to identify the effect of interventions on malnutrition to reduce the risk of SAP.The online version contains supplementary material available at 10.1186/s12883-023-03340-1. Stroke is a main cause of death and long-term disability globally, and stroke-associated pneumonia (SAP) is a common and serious consequence of ischemic stroke (IS), affecting 7% to 38% IS patients –3. Previ2DS2 Score, Kwon Pneumonia Score, PASS Pneumonia Rule, and ISAN Score, have been derived to predict SAP events using some routinely available clinical risk variables [Attempts have been made to determine the risk of SAP in IS patients using various risk variables and predictive scores. Some studies indicated that age, dysphagia, atrial fibrillation, severity of the stroke, and stroke-induced immunodepression syndrome were linked to the risk of SAP, and certain inflammatory indicators, including neutrophil to lymphocyte ratio (NLR), C-reactive protein, and procalcitonin, had predictive value for SAP in IS patients; however, no single marker or pattern has exhibited sufficient accuracy and reliability , 5, 9–13. Therefore, the purpose of this research was to investigate whether IS patients with worse malnutrition, assessed by GNRI, PNI, and CONUT, had a higher risk of SAP, and whether these tools provided an additional value beyond traditional tools for predicting the incidence of SAP.Malnutrition, as screening by the Geriatric Nutrition Risk Index (GNRI), Controlling Nutritional Status (CONUT), and Prognostic Nutritional Index (PNI) scores at admission, is prevalent in adults with IS and is linked to an increased risk of all-cause mortality and ineffective functional consequences. Moreover, Patients with IS are especially vulnerable to malnutrition due to age, dysphagia, immunodepression, cognitive deficits, and even limited mobility . It suggThe REtrospective Multicenter study for Ischemic Stroke Evaluation (REMISE) study was a multicenter retrospective cohort study, registered at Chinese Clinical Trial Registry (Identifier: ChiCTR2100052025). Patients with IS were recruited from emergency departments of five tertiary hospitals in Sichuan, China from January 2020 to December 2020. Regarding the COVID-19 pandemics, patients without negative nucleic acid test for SARS-CoV-2 within 24 h are temporarily placed in isolation wards. There are only a small number of COVID-19 confirmed patients in Sichuan Province, and none of the IS patients during this study periods were infected. This study adhered to the Declaration of Helsinki and was approved by the ethics committee of West China Hospital of Sichuan University. Retrospective chart review without need of informed consent form (Approved No. of ethic committee: 2021–1175).We investigated the association between malnutrition and the risk of SAP in individuals with IS. Patients were included if they were first diagnosed with IS according to the 2019 American Heart Association Stroke guidelines and did not receive mechanical ventilation within 7 days of stroke onset . We exclSample Size Calculation: assuming that the AUROC of three malnutrition assessment tools for predicting SAP is greater than 0.75. And the smallest ratio of sample sizes in non-malnutrition to malnutrition groups is 6. To satisfy that Type I error  and Type II error  should be less than 0.01, the smallest sample size was 252.Information was gathered from the REMISE database. Using standard case report forms, trained physicians collected baseline data, including demographic and characteristic information, vital signs, medical histories, laboratory examinations, imaging examinations, inpatient complications, adverse outcomes, and treatment therapies in the hospital and at discharge, from the electronic health records. All laboratory testing and imaging examinations were carried out in line with Sichuan University West China Hospital's standard operating procedures..2DS2 score (score ranging from 0 to 10) was calculated according to age, dysphagia, male sex, atrial fibrillation, and stroke severity [2DS2 score can easily be completed on admission, and it is a widely validated screening tool for SAP in China, Denmark, the United Kingdom, Spain, and France.The National Institutes of Health Stroke Scale (NIHSS) was used at admission and discharge to evaluate stroke-related neurological deficits. The range of NIHSS scores is 0 to 42, with higher scores indicating more severe neurological impairment . Furtherseverity . A2DS2 sNutritional risk screening was performed by professionally trained researchers using GNRI, CONUT, and PNI. The GNRI, CONUT, and PNI scores were measured within 4 h after admission to collect blood samples for analysis.The GNRI score was computed using the following formula:  1.48 × sThe nutritional status of the patients was evaluated using CONUT  based on3). A score of > 45 indicated the absence of malnutrition, while scores of 40–45 and < 40 indicated moderate and severe malnutrition, respectively [The PNI score was computed as 10 × serum albumin (g/dL) + 0.005 × lymphocyte count  were imputed by multiple imputation analysis. Normally distributed continuous variables were represented by means ± standard deviations, while non-normally distributed continuous variables were represented by medians with interquartile ranges. Categorical variables are represented as frequencies and percentages. The Kruskal–Wallis H test was used to compare normally distributed variables, whereas one-way analysis was used to evaluate non-normally distributed patient characteristics. For the purpose of comparing categorical variables, either Fisher's exact test or the chi-square test was used.The restricted cubic linear splines of the PNI, CONUT, and GNRI scores with three evenly spaced knots were utilized in order to investigate the associations between malnutrition scoring systems and adjusted odds ratios (ORs) for SAP outcomes. These restricted cubic linear splines were determined using the Harrell et al. method.. An inve9/L vs. > 7 × 109/L), and NIHSS score (≤ 7 vs. > 7). The interaction effects of these variables with the three malnutrition indices and SAP were calculated. The area under the receiver operating characteristic (AUROC) curves and continuous net reclassification improvement (NRI) were constructed to assess the predictive ability of the GNRI, CONUT, and PNI scores for SAP and to determine the additional prognostic value of the three malnutrition indices beyond A2DS2 via DeLong test [In the risk factor-adjusted logistic regression model, subgroup analyses were stratified by age (< 65 vs. ≥ 65 years), sex , atrial fibrillation (yes vs. no), smoking (yes vs. no), WBC count  and R version 3.5.0. .All A total of 915 participants with IS were enrolled, with an average age of 64.65 ± 14.06 years. Of these participants, 576 (63.0%) were men. Additionally, 294 (32.1%) patients developed SAP. The baseline characteristics of individuals with SAP and those without SAP are compared in Table According to the PNI, CONUT, and GNRI scores, 193 (21.1%), 495 (54.1%), and 148 (16.1%) malnourished patients were screened, respectively. Of these patients, 140 (15.3%), 449 (49.1%), and 57 (6.2%) patients, respectively, were classified into mild malnutrition; moreover, 53 (5.7%), 46 (5.0%), and 91 (10.0%) patients, respectively, classified into moderate or severe malnutrition.P < 0.001; CONUT, 76.1% vs. 37.6% vs. 21.4%, P < 0.001; GNRI, 61.4% vs. 51.6% vs. 27.6%, P < 0.001; Supplementary Fig. P < 0.001), CONUT , and GNRI  had a significantly higher SAP risk than patients with normal nutrition (Table Patients (moderate and severe vs. mild vs. absent) with worse malnutrition risk had a higher incidence of SAP , 0.643 , and 0.646 , respectively. The three malnutrition indices were inferior to A2DS2 . However, A2DS2 combined with PNI, CONUT, and GNRI achieved higher AUROCs  than those achieved by A2DS2 alone (P < 0.05). The three malnutrition indexes achieved additional predictive values for SAP beyond the A2DS2 according to the NRI analysis  , and the pneumonia severity index. The detailed results are shown in Supplementary Fig. Spearman correlation analysis showed that the scoring systems such PNI, CONUT or GNRI, were associated with age, systemic inflammatory markers , severity of IS  predicted SAP events in IS patients, and there was a strong association between NLR and pneumonia severity , 10–12. n = 82) to calculate PNI, CONUT, or GNRI scores were excluded, that may cause bias. Fourth, although patients were enrolled within 12 h of IS onset in this trial, blood sample collection was completed within 1 h of entry. This could still have introduced biases based on patient differences. Fifth, considering that it is a retrospective study, there may be potential confounding factors that have not been fully adjusted. Sixth, although we evaluated the predictive efficacy of the three nutrition screening measures, we did not compare them to other nutrition screening tools with more thorough nutrition assessments. Finally, we could not collect data on dietary components to examine the relationship between dietary constituents and nutritional status.The present study had a few limitations. First, it was a multicenter retrospective cohort research done at stroke sites in the emergency departments of tertiary hospitals in China. Although the sample size was quite large, bias may have occurred in patient selection, and caution is required when evaluating the results of clinical nutritional assessments from different institutions. Second, we collected clinical data only at admission and discharge. The initial malnutrition indices of patients at admission were collected and could not be estimated at different time points. The dynamic fluctuation in nutritional scores assessed at different time points during hospitalization may be a better predictor of SAP. In addition, other risk factors and scoring systems related to SAP could not be continuously and dynamically evaluated. Third, patients with missing data  PNI, (B) CONUT, and (C) GNRI. CONUT, controlling nutritional status score, GNRI, geriatric nutritional risk index, PNI, prognostic nutritional index SAP, stroke-associated pneumonia. Supplementary Fig. 2. The incidence of all-cause mortality according to different nutritional risk groups of three malnutrition indexes (A) PNI, (B) CONUT, and (C) GNRI. Abbreviation: CONUT, controlling nutritional status score, GNRI, geriatric nutritional risk index, PNI, prognostic nutritional index. Supplementary Fig. 3. The length of stay according to different nutritional risk groups of three malnutrition indexes (A) PNI, (B) CONUT, and (C) GNRI. Abbreviation: CONUT, controlling nutritional status score, GNRI, geriatric nutritional risk index, PNI, prognostic nutritional index. Supplementary Fig. 4. Spearman correlation anaysis analyse the correlation of three malnutrition scoring systems and age, systemic inflammatory markers, the severity of IS, and the severity index of pneumonia. Abbreviation: SII, systemic inflammatory index, WBC, white blood cell count, NLR, neutrophil to lymphocyte ratio, PSI, pneumonia severity index.


The guttural pouch of the horse is an extension of the auditory tube connecting the throat to the ear. As equine veterinarians, we are actually very fortunate because the guttural pouch provides us with a unique window into numerous important and complex anatomic structures. A thorough knowledge of the underlying structures visible during guttural pouch endoscopy is essential, not only for an accurate diagnosis but also for the treatment of problems in this area. The objectives of this anatomic observational study were to: (1) identify each structure visible on endoscopic examination of the guttural pouch; (2) create a map of the region; and (3) describe a systematic guttural pouch endoscopic examination. Conventional dissections of the guttural pouches of six equine cadavers were first performed, and each adjacent structure was identified. Then, a guttural pouch endoscopic exam of the dissected heads was performed in order to correctly map each visible underlying anatomic structure identified from the previous dissection. Our investigation provides new practical information on guttural pouch endoscopic anatomy and has allowed us to identify structures that were not previously described. We believe that this information may help with an accurate diagnosis in some cases and also potentially reduce iatrogenic trauma to important structures.Guttural pouch endoscopy allows for both the visualization and treatment of many clinical problems in the equine retropharyngeal region. This area is extremely complex, and its description remains a real challenge for veterinary anatomists and practitioners. Six clinically normal equine cadavers were employed. Conventional dissections of guttural pouches without penetrating the guttural pouch membrane were first performed, and each adjacent structure was identified. Then, a guttural pouch endoscopic exam of the dissected heads was performed in order to correctly map each visible underlying anatomic structure identified in the previous dissection. This allowed us to: 1—identify each structure visible on endoscopic examination of the guttural pouch; 2—create a representative map of all the structures accurately identified via endoscopy; and 3—describe a systematic guttural pouch endoscopic examination with practical keys to help identification of the underlying vital structures. Our investigation provides new practical information on guttural pouch endoscopic anatomy and has allowed us to identify structures that were not previously described. We believe that this information may help with an accurate diagnosis in some cases and also potentially reduce iatrogenic trauma to important structures. The guttural pouch (Diverticulum tubae auditivae) of a horse is a paired extension of the Eustachian tube (Tuba auditiva),, connecting the nasopharynx to the middle ear .As equine veterinarians, we are actually very fortunate because the guttural pouch (GP) provides us with a unique window into numerous important and complex anatomic structures  that areThis area is extremely complex, and its description remains a real challenge for veterinary anatomists . More imA thorough knowledge of the underlying structures visible during GP endoscopy is essential, not only for an accurate diagnosis but also for the treatment of problems in this area and the limitation of the risk of life-threatening complications .The objectives of this anatomic observational study were to: 1—Identify each structure visible on an endoscopic exam of the guttural pouch;2—Create an exact map of the region;3—Describe a systematic GP endoscopic examination with practical keys to help identify the underlying vital structures.For this purpose, we performed a study in two arms: First, we studied the classic anatomy of the GP from the outside in. We performed conventional dissections of guttural pouches on 6 clinically normal horses postmortem. The head was disarticulated at the level of the atlanto-axial joint, and the guttural pouches were exposed via a lateral and caudal approach. The guttural pouch membrane was not penetrated. The identity of all the important structures adjacent to each guttural pouch was confirmed by an experienced veterinary anatomist, Pr. Barone.Then, we studied the endoscopic anatomy from the inside out. We performed a guttural pouch endoscopic exam of the dissected head to correctly map each visible underlying anatomic structure identified in the previous dissection. Each structure was visualized and identified from the inside of the pouch via endoscopy, and then its identity was confirmed from the exterior of the pouch by palpation of the different dissected organs. This allowed us to create a representative map of all the structures accurately identified via endoscopy.Each GP pouch observed endoscopically was different; the thickness of the membrane and the presence of underlying fat made each pouch unique. None of them could show all the underlying anatomic structures.Thus, we had to pool the different information from each GP observation into a complete representative map that highlights all the identified visible structures . We will define below the position and aspect of each underlying anatomic structure by proposing and describing a complete systematic GP endoscopic examination:A right guttural pouch will be used for the description .We suggest first examining the medial compartment and performing a stepwise inspection of four areas: first, the ceiling of the pouch; then, the caudal wall; next the medial wall; and finally, continuing down to investigate the floor of the pouch. We also suggest leaving the nerve assessment until the end, as the anatomy is more complex and variable. And, finally, we will look at the lateral compartment.Roof of the medial compartment .−The most clinically relevant structure in this area is the temporohyoid joint, which is a symphysis and links the stylohyoid bone and the styloid process of the temporal bone.−Just close to them lies the petrous part of the temporal bone, which we can see as a large white relief medially to the joint.−Just above the joint, the tensor veli palatini muscle is visible and runs toward the rostral part of the roof of the guttural pouch. −Medially, the internal carotid artery is visible. It forms a sigmoid inflexion before leaving contact with the pouch to join the Circle of Willis.Caudal wall of the medial compartment .−The occipito-hyoïdeus muscle links the jugular process of the occipital bone to the stylohyoïd bone.−The caudal part of the Digastricus muscle is also inserted into the jugular process but runs ventrally and quickly loses contact with the pouch.−Finally, the stylohyoideus muscle is sometimes visible and runs along the caudal aspect of the stylohyoid bone.−The atlanto-occipital joint lies close to this mass of muscles. It looks like a large circular white surface, more or less concave. Its location is important, as fungal arthritis of this joint has been reported following guttural pouch mycosis .Numerous muscles are visible through the transparent membrane:Medial wall of the medial compartment .−The median septum, created by the apposition of the mucous membranes of the two pouches:−The longus capitis muscle caudally, which is a large fleshy muscular body covered by a white and shiny vertical band;−The dorsal pharyngeal recess rostro-ventrally, which is not easily visible from the pouch, but it is important to know its position, especially when performing laser surgery.It consists of three structures:Then, we go down to the floor of the pouch.Floor of the medial compartment −The floor lies on the Carotid trifurcation, but this major branching is never clearly visible.−Laterally, we can see the origin of the external carotid artery, which runs under the stylohyoid bone and then goes into the lateral compartment.−Occasionally, it is also possible to visualize the origin of the linguofacial trunk, running cranially, and of the occipital artery, running proximally, between the two carotids.−The stylopharyngeus muscle is particularly evident on the medial and distal aspects of the stylohyoid bone .−The medial retropharyngeal lymph nodes, which can cause GP empyema, lie ventrally, under the floor of the guttural pouch.−Sometimes as in , it is aWe will now move on to the identification of the different cranial nerves in the medial compartment.Cranial nerve assessment in the medial compartment .Their pathways are variable, which can sometimes make their recognition difficult. That is why some points of reference can be useful:The cranial nerves IX, X, XI, and XII emerge from the cranium behind the ICA and are divided into two pairs of nerves: nerves IX and XII cross the caudal wall obliquely toward the stylohyoid bone, while nerves X and XI course along the ICA.−The glossopharyngeal nerve is the most dorsal and lateral and is often thinner than its neighbor, number XII. It goes halfway through a ramification that goes down toward the carotid trifurcation: the Hering nerve, or branch of glossopharyngeal nerve, to the carotid sinus, which plays a role in the regulation of blood pressure.We found that the pharyngeal branch of the glossopharyngeal nerve emerges more distally, under the floor of the pouch, and so is not in contact with the pouch and not endoscopically visible.−The hypoglossal nerve also runs obliquely, either alone under the glossopharyngeal nerve or joined onto it , in the −The vagus and accessory nerves are difficult to distinguish as both of them run along or behind the internal carotid artery. A simple way to identify the vagus nerve is to identify its pharyngeal branch, which is easily visible, and go back up to its origin. This branch is the little nerve that we always see running ventrally across the longus capitis muscle, with a rostral direction toward the pharyngeal plexus. Generally, the vagus nerve is lateral to the ICA, and the accessory nerve is medial. It is important to know that the vagus nerve also has another branch, the laryngeal branch, which is rarely visible, emerges higher than the pharyngeal branch, and runs distally toward the carotid trifurcation. The last part of the examination is the assessment of structures in the lateral compartment.Lateral compartment of guttural pouch .−The external carotid artery (ECA) emerges from behind the stylohyoid bone and gives rise to the others.−The first branch is the caudal auricular artery, which runs up along the stylohyoid bone.−The next branch is the superficial temporal artery.−Following this, the ECA becomes the maxillary artery, which curves and loses contact with the pouch by entering the alar foramen.−The spider web that is visible on the inflection of the maxillary artery is the carotid plexus, which innervates the external carotid and maxillary artery.−Rostrally and ventrally, the maxillary vein runs along the internal pterygoideus muscle.−Then, in the back of the compartment, it is easy to see the styloid process of the auricular cartilage. It looks like a matchstick and moves with the ear.−The facial nerve lies ventrally to this cartilage. It consists of a large horizontal white band that crosses the compartment between the two arteries. It is the largest nerve visible in the guttural pouch. −Just in the triangle formed by the facial nerve and the two arteries, we observe some pink globular structures, which are part of the parotid gland.−Very rarely, it is possible to see the chorda tympani and the maxillary nerve, as in The vessels are the largest structures here:As reviewed by Freeman , complicOur investigation provided new practical information on guttural pouch endoscopic anatomy and allowed us to identify structures that were not previously described via endoscopy: the facial nerve, Hering nerve, chorda tympani, mandibular nerve, atlanto-occipital joint, jugular process of the occipital bone, auricular cartilage, and lateral retropharyngeal lymph nodes.We also tried to describe a practical way to localize and recognize the complex nervous and arterial networks underlying the GP in order to help each veterinarian or surgeon during his/her daily work.However, there are several limitations to our study. First, the dissections were performed on only six normal cadavers. Therefore, this study is only observational, and no statistics on the anatomic variability of the GP were produced. This could be the subject of a further prospective in vivo study. Second, the assessment was performed on normal, healthy heads; inflammation and different pathologies could interfere with or modify our normal findings. Finally, the dissection and identification of each underlying anatomic structure were performed by an anatomist and are dependent on subjectivity and human error. However, we significantly reduced this risk by having one of the most renowned and experienced anatomists in the world perform the dissections: Pr. Robert Barone.To conclude, we believe that this information may help with an accurate diagnosis with a complete lesional assessment in some cases. It can also potentially reduce iatrogenic trauma to important structures during surgeries, whether through transendoscopic techniques ,10,12,13


Vaccine hesitancy has hampered the control of COVID-19 and other vaccine-preventable diseases.We conducted a national internet-based, quasi-experimental study to evaluate COVID-19 vaccine informational videos. Participants received an informational animated video paired with the randomized assignment of (1) a credible source (differing race/ethnicity) and (2) sequencing of a personal narrative before or after the video addressing their primary vaccine concern. We examined viewing time and asked video evaluation questions to those who viewed the full video.p < 0.01). Respondent–provider race/ethnicity congruence was associated with increased odds of viewing the full video . Most viewers rated the informational video(s) to be helpful, easy to understand, trustworthy, and likely to impact others' vaccine decisions, with differences by demographics and also vaccine intentions and concerns.Among 14,235 participants, 2,422 (17.0%) viewed the full video. Those who viewed a personal story first (concern video second) were 10 times more likely to view the full video (Using peer-delivered, personal narrative, and/or racially congruent credible sources to introduce and deliver vaccine safety information may improve the openness of vaccine message recipients to messages and engagement. Vaccine hesitancy and its role in vaccine uptake and also the subsequent control of vaccine-preventable diseases have become a major focus of research and practice . Since tThe acceptance or refusal of COVID-19 vaccination—despite the widespread availability of vaccines—has been hampered by beliefs that COVID-19 does not present a serious health risk and a variety of concerns related to vaccine effectiveness and safety , 11. AloExperts agree that addressing vaccine hesitancy is context-specific, requiring tailored interventions that include a range of vaccine communication strategies . PatientOur study was conducted as a part of the CDC-funded COVID-19 Vaccines Information Equity and Demand Creation (COVIED) program –22, a boUsing real-time interactive worldwide intelligence's (RIWI) patented Random Domain Intercept Technology (RDIT) –22, we iWe developed content tailored to each of the following relevant sub-populations of COVID-19 vaccine decision-makers: primary caregivers of children  who have concerns about COVID-19 vaccines for their children, primary caregivers who do not have concerns about COVID-19 vaccines, non-caregivers who have concerns about COVID-19 vaccines for themselves, and non-caregivers who do not have concerns about COVID-19 vaccines. Formative research for our study was conducted using analyses of RIWI RDIT-derived data from two other national-level rapid response surveys designed to ascertain the public's COVID-19 vaccination attitudes and beliefs , 22, rapAll videos included an introduction and concluding message by a clinical provider as well as an animated informational video. Introduction and concluding recordings were performed by three clinicians representing different racial and ethnic backgrounds . The use of a personal story to introduce (or conclude) eight informational videos on COVID-19 vaccine concerns was developed based on the theory of change  that by We implemented the quasi-experiment from 06 December 2021 to 01 January 2022. We collected participant sociodemographic characteristics and determined video intervention eligibility based on answers to five questions regarding (1) caregiver status, (2) COVID-19 vaccination status, (3) race and ethnicity, (4) presence of COVID-19 vaccination concerns, and (5) intention to get the COVID-19 vaccine among the unvaccinated respondents. Based on answers to these questions, participants were assigned to appropriate message pathways . SupplemChild caregivers were stratified by those with any COVID-19 vaccine concern and those without a concern. All caregivers without any concern were assigned to view a video discussing benefits for the child (Child Benefit video). Caregivers who had a concern about the COVID-19 vaccine and infertility were randomly (3:1) assigned to view a concern video addressing their concern about infertility or the child benefit video. The remaining concerned caregivers were assigned to the child benefit video.Among non-caregivers, any unvaccinated participant without COVID-19 vaccine concerns was assigned to a video discussing benefits for adults (adult benefit video). Vaccinated non-caregivers with a previous COVID-19 vaccine concern as well as any unvaccinated non-caregivers with a COVID-19 vaccine concern were asked a multiple-choice question—“what are/were your main concerns about the COVID-19 vaccine?”—and could select all that applied. Based on anticipated sample size limits, any participant indicating concern about vaccine ingredients  was automatically assigned to the concern video addressing this specific concern. Participants selecting only one concern were assigned to the associated concerned video. Participants who selected more than one concern  were randomly assigned to a concern video addressing one of the selected concerns. Participants who selected “other” concerns were assigned to view the adult benefit video. In order to test our theory of change using personal narrative to introduce vaccine risk and safety messages, one out of every eight participants assigned to view a concern video was randomly selected to view a personal story video before viewing the concern video .Unvaccinated non-caregivers without concern about the COVID-19 vaccine were assigned to view the adult benefit video. Clinical provider race/ethnicity was randomly assigned  for all videos. Vaccinated non-caregivers without previous COVID-19 vaccine concerns were asked to participate in a brief survey about COVID-19 vaccine boosters.We used a continuous measure of the length of time (in seconds) each respondent spent viewing their assigned video and a standardized measure of the proportion of the video viewed based on the total length of each video. The total length included the introduction, informational animation, and concluding message. We then created a dichotomous outcome variable identifying those who fully viewed their assigned video and those who did not. For respondents viewing a concern video, the total length of viewing time included both the concern video and the personal story video.Participants who completed viewing their assigned video were asked to provide their level of agreement or disagreement using a five-point Likert scale  with three statements to evaluate their assigned video:(1) The video was helpful in making a vaccine decision.(2) I trusted the information in the video.(3) The video was easy to understand.Viewers were asked to answer a fourth evaluation question (“how would this video influence others to get vaccinated?”) using a five-point Likert scale . We opted for a neutral phrasing of the question to avoid any appearance of favor toward or against vaccination. Likert scales were dichotomized for analysis by combining “strongly agree” and “agree” or “much more likely” and “somewhat more likely” to form agree vs. disagree and likely vs. unlikely categories, respectively.The main exposure of interest was a categorical variable classifying respondents according to their assigned video type. For those assigned to any of the concern videos, separate categories were used to indicate whether the personal story video or concern video was viewed first. Sociodemographic characteristics of respondent age, sex, race and ethnicity, and COVID-19 vaccination status (vaccinated vs. unvaccinated), as well as provider's race and ethnicity, were measured. We created a dichotomous variable to indicate racial/ethnic congruence between the provider and the respondent. Respondent location was categorized according to nine regions using Centers for Disease Control and Prevention (CDC) definitions .t-test for normally distributed data. No covariates had missingness of data exceeding 5%. Analyses were performed using the two-sided significance level (0.05). All analyses were conducted using Stata 16.1 .For descriptive analyses, we compared distributions using chi-square and Fisher's exact tests for proportions, Wilcoxon rank-sum for non-parametric data, and Student's We used multivariable logistic regression to model the log odds of each of our dichotomous outcomes of interest: (1) viewing the assigned video in its entirety vs. not, and the respondent agreed (or disagreed) the following of the video; (2) is easy to understand; (3) is helpful for making vaccination decisions; (4) information is trustworthy; and (5) will influence others to get vaccinated. Among 117,750 individuals who initially reached for participating, 75,616 (64.2%) completed the first five qualifying questions required for video assignment and 14,235 (18.8%) started to view the assigned video, allowing us to evaluate the length of time spent viewing the assigned video . Among those who started, 2,422 (17.0%) completed viewing the full video and answered at least one video and content quality or potential video utility evaluation question.p-values < 0.01). Specifically, we observed higher proportions of video completion compared to demographic counterparts among respondents aged 46–55 and 56–64 years of age , women (15.8%), self-reporting race and ethnicity as Hispanic/Latinx or Multiple (15–21%), those who were COVID-19 unvaccinated (19%), those who were COVID-19 vaccinated who are planning to get a COVID-19 booster (14%), and those who were COVID-19 unvaccinated and hesitant (delaying or refusing vaccination) (22%).Among respondents assigned to view a concern and personal story video , distributions of age, sex, race and ethnicity, COVID-19 vaccination status, COVID-19 booster status among the vaccinated, and intention to get the COVID-19 vaccine among the unvaccinated differed significantly by video viewing completion status . Mainly, those who were 36–74 years of age (~17%), self-identified race and ethnicity as Multiple (18%), Black (17%), and White or Hispanic/Latinx (15%) and were vaccinated but had not yet received the first COVID-19 booster but planned to (19%) had higher proportions of viewing compared to their younger (12–13%), Asian (9%), Alaskan Native (12%), American Indian (12%), and COVID-19 vaccinated (and have received a booster) (12%) counterparts , we observed statistically significant differences in the distributions of age, race and ethnicity, and COVID-19 booster status among the vaccinated by video viewing completion status , mostly 5–11-year-old children (36%) completed viewing than those aged 0–4 (23%) or 12–17 (18%) years (p = 0.02). No other significantly different distributions were found by video viewing completion status. Distributions of age (p < 0.01), sex (p = 0.01), and race and ethnicity (p < 0.01) differed significantly by child benefit video viewing completion status among 5,752 respondents where greater proportions of 36–64-year-olds (~9%), female (8%), and White (9%), Black (7%), Multiple (7%), Hispanic (7%), or American Indian (7%) completed viewing the video compared to those younger and older than the middle aged (~5%), male (7%), and Asian, Alaskan Native, or American Indian  more likely to watch the complete informational animation. Viewers of the personal story first (concern video second) were also ~4.5 times (p < 0.01) more likely to watch the complete informational animation compared to viewers of the infertility concern video, as well as 20 times (p < 0.01) and nine times (p < 0.01) more likely to watch than the viewers of the child benefit and adult benefit videos, respectively. Unadjusted estimates of viewing time measures are provided in In p < 0.01; 82%, p < 0.01) than those viewing videos presented by the White physician (p < 0.01) compared to their White counterparts as did Asian viewers . Those reporting a multi-racial and/or ethnic identity had greater odds of completely viewing the assigned video  though the relationship had borderline statistical significance (p = 0.06). Women aged 36–74 years and unvaccinated viewers had increased odds of fully viewing the assigned video compared to their men aged 18–35 years and vaccinated counterparts .Those viewing introduction/concluding material presented by the Black or Hispanic physician had lower odds of fully viewing the assigned video . Racial congruence was associated with increased odds of fully viewing a video .When adjusting for racial congruence between the provider and the viewer/respondent , the oddp < 0.01; p < 0.01) of evaluating the videos positively [and American Indian or Alaskan Native (AI/AN)] or others have a lower odds (≤46% lower odds where p < 0.01) than their White counterparts (p = 0.03). When adjusting for racial congruence, female viewers had greater odds  of positively evaluating their assigned videos whereas older adults  and the unvaccinated ones had lower odds  were greater among those who viewed the personal story first (concern video second) though the adjusted odds ratio was statistically significant only when asking about the video's influence on others to get vaccinated . Moreover, we found no evidence that provider race (or respondent race) acts as an effect modifier on the relationship between provider–respondent racial congruence and our outcomes of interest .There was no evidence of a confounding effect of survey time on the primary relationship of interest  and tailoring messages. Race and ethnicity have been identified as factors associated with COVID-19 (and other) vaccine uptake and vaccine hesitancy , 34–36. We found that while unvaccinated respondents were more likely to fully view their assigned video compared to vaccinated respondents, they were also less likely to give positive feedback on video content and usefulness. The majority of unvaccinated respondents (62%) agreed or strongly agreed that the video content was easy to understand, but greater proportions of unvaccinated respondents disagreed or strongly disagreed that the videos were helpful for making vaccine decisions or influencing others to get vaccinated or that the information was trusted than agreed or strongly agreed . Even before the COVID-19 pandemic, vaccine hesitancy and refusal were identified as public health concerns , 39. Regp < 0.01) and have fewer reported COVID-19 vaccine concerns than those described in our study sample . This may strengthen our findings that suggest the usefulness of our vaccine communication videos among specific sub-populations of the American public, noting that the distribution of intentions to complete the COVID-19 vaccine series or booster were similar between those lost to follow-up and those in our study (Selection bias may have been introduced due to the opt-in, unincentivized design of the study. We explored the distribution of sociodemographic characteristics  among thur study . We noteOur study findings further support the importance of tailoring vaccine communication strategies to sub-population vaccine attitudes by delivering vaccine messages through trusted, race/ethnicity-congruent providers or other trusted health authorities. Introducing vaccine safety information with peer-delivered, personal narratives may improve the openness of vaccine message recipients to vaccine messages and engagement. Further research is needed to evaluate the effect of vaccine safety informational video packages on vaccine uptake. Additionally, further formative work is needed to explore message engagement among sub-populations that maintain fewer positive views of vaccine safety information.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This study was reviewed by the Institutional Review Board at John Hopkins Bloomberg School of Public Health. Written informed consent and approval was not required as the study was determined to not be human subject research.HS, RR, RB, PO, MD, L-SK, RS, SL, LW, JL, WO, JB, AJ, JS, RJ, DG, and DS contributed to the conception and/or the design of the work represented in this paper. RS and SL were a part of the acquisition of data. HS, RB, MD, RS, LW, WO, and DS contributed to the analysis and interpretation of data. HS and DS drafted the work. All authors revised the work critically and gave final approval of the version to be published.