iKNOWgynetics - A web-based learning concept to empower primary care gynecologists to participate in the care of patients with a family history of breast and ovarian cancer.

Familial cancer burden and genetics play an increasingly important role in the early detection and prevention of gynecological cancers. However, people with hereditary cancer risks are often identified late when they already have cancer. We aimed at developing and evaluating a training concept for primary care gynecologists-iKNOWgynetics-to improve their knowledge and awareness of genetic cancer syndromes and their ability to identify patients with increased familial cancer risks based on up-to-date evidence and current guidelines (in Germany, primary care includes all doctors treating patients on an outpatient basis without a clear separation of the expertise of the doctor or of their specialty). Starting off with a needs assessment among primary care gynecologists, we developed and evaluated an online training concept-using a web-based learning platform in combination with a live virtual seminar-to convey practice-relevant knowledge about familial cancer. After registration, participants get access to the web-based learning platform (www.iknowgynetics.de) to prepare for the virtual seminars and to use it as online reference to re-access the contents after the training. Evaluation included multiple-choice (MC) questions on knowledge and participants' self-efficacy to implement the acquired knowledge, which were administered in a pre-post design. Of 109 participants, 103 (94.5%) filled out pre- and post-questionnaires. Eighty-five participants were gynecologists in primary care from Berlin (81.2%) and Brandenburg (18.8%) and had an average of 24.1 years (SD = 8.5 years) of professional experience. After the training, participants answered significantly more knowledge questions correctly (M = 15.2 of 17, SD = 1.3) than before (M = 13.8 of 17, SD = 1.7) (p < 0.01) and felt more confident to be able to apply referral criteria for specialized counseling in practice (p < 0.001). The online-based training iKNOWgynetics considers the busy schedule of primary care gynecologists and supports them in acquiring practice-relevant information on familial cancer risks and on how to identify healthy persons at risk, which may ultimately help to improve the prevention of gynecological cancers. In future studies, the reported concept could be transferred to other entities.

Characteristics of Users and Nonusers of Symptom Checkers in Germany: Cross-Sectional Survey Study.

BACKGROUND: Previous studies have revealed that users of symptom checkers (SCs, apps that support self-diagnosis and self-triage) are predominantly female, are younger than average, and have higher levels of formal education. Little data are available for Germany, and no study has so far compared usage patterns with people's awareness of SCs and the perception of usefulness. OBJECTIVE: We explored the sociodemographic and individual characteristics that are associated with the awareness, usage, and perceived usefulness of SCs in the German population. METHODS: We conducted a cross-sectional online survey among 1084 German residents in July 2022 regarding personal characteristics and people's awareness and usage of SCs. Using random sampling from a commercial panel, we collected participant responses stratified by gender, state of residence, income, and age to reflect the German population. We analyzed the collected data exploratively. RESULTS: Of all respondents, 16.3% (177/1084) were aware of SCs and 6.5% (71/1084) had used them before. Those aware of SCs were younger (mean 38.8, SD 14.6 years, vs mean 48.3, SD 15.7 years), were more often female (107/177, 60.5%, vs 453/907, 49.9%), and had higher formal education levels (eg, 72/177, 40.7%, vs 238/907, 26.2%, with a university/college degree) than those unaware. The same observation applied to users compared to nonusers. It disappeared, however, when comparing users to nonusers who were aware of SCs. Among users, 40.8% (29/71) considered these tools useful. Those considering them useful reported higher self-efficacy (mean 4.21, SD 0.66, vs mean 3.63, SD 0.81, on a scale of 1-5) and a higher net household income (mean EUR 2591.63, SD EUR 1103.96 [mean US $2798.96, SD US $1192.28], vs mean EUR 1626.60, SD EUR 649.05 [mean US $1756.73, SD US $700.97]) than those who considered them not useful. More women considered SCs unhelpful (13/44, 29.5%) compared to men (4/26, 15.4%). CONCLUSIONS: Concurring with studies from other countries, our findings show associations between sociodemographic characteristics and SC usage in a German sample: users were on average younger, of higher socioeconomic status, and more commonly female compared to nonusers. However, usage cannot be explained by sociodemographic differences alone. It rather seems that sociodemographics explain who is or is not aware of the technology, but those who are aware of SCs are equally likely to use them, independently of sociodemographic differences. Although in some groups (eg, people with anxiety disorder), more participants reported to know and use SCs, they tended to perceive them as less useful. In other groups (eg, male participants), fewer respondents were aware of SCs, but those who used them perceived them to be more useful. Thus, SCs should be designed to fit specific user needs, and strategies should be developed to help reach individuals who could benefit but are not aware of SCs yet.

Boosting for insight and/or boosting for agency? How to maximize accurate test interpretation with natural frequencies.

BACKGROUND: Many physicians do not know how to accurately interpret test results using Bayes' rule. As a remedy, two kinds of interventions have been shown effective: boosting insight and boosting agency with natural frequencies. To boost insight, test statistics are provided in natural frequencies (rather than conditional probabilities), without instructions on how to use them. To boost agency, a training is provided on how to translate probabilities into natural frequencies and apply them in Bayes' rule. What has not been shown is whether boosting agency is sufficient or if representing test statistics in natural frequencies may additionally boost insight to maximize accurate test interpretation. METHODS: We used a pre/posttest design to assess test interpretation accuracy of 577 medical students before and after a training on two Bayesian reasoning tasks, one providing conditional probabilities, the other natural frequencies. The pretest assessed baseline abilities versus the effect of natural frequencies to boost insight. After participants received a training on how to translate conditional probabilities into natural frequencies and how to apply them in Bayes' rule, test interpretation skills were assessed using the same tasks again, comparing the effects of training-induced agency with versus without additionally boosting insight (i.e., test statistics in natural frequencies versus conditional probabilities). RESULTS: Compared to the test question formatted in conditional probabilities (34% correct answers), natural frequencies facilitated Bayesian reasoning without training (68%), that is, they increased insight. The training on how to use natural frequencies improved performance for tasks formatted in conditional probabilities (64%). Performance was maximal after training and with test statistics formatted in natural frequencies, that is, with a combination of boosting insight and agency (89%). CONCLUSIONS: Natural frequencies should be used to boost insight and agency to maximize effective use of teaching resources. Thus, mandating that test statistics are provided in natural frequencies and adopting short trainings on how to translate conditional probabilities into natural frequencies and how to apply them in Bayes' rule will help to maximize accurate test interpretation. TRIAL REGISTRATION: The study was a registered with the German Clinical Trial Registry ( DRKS00008723 ; 06/03/2015).

Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation.

BACKGROUND: Symptom checkers are digital tools assisting laypersons in self-assessing the urgency and potential causes of their medical complaints. They are widely used but face concerns from both patients and health care professionals, especially regarding their accuracy. A 2015 landmark study substantiated these concerns using case vignettes to demonstrate that symptom checkers commonly err in their triage assessment. OBJECTIVE: This study aims to revisit the landmark index study to investigate whether and how symptom checkers' capabilities have evolved since 2015 and how they currently compare with laypersons' stand-alone triage appraisal. METHODS: In early 2020, we searched for smartphone and web-based applications providing triage advice. We evaluated these apps on the same 45 case vignettes as the index study. Using descriptive statistics, we compared our findings with those of the index study and with publicly available data on laypersons' triage capability. RESULTS: We retrieved 22 symptom checkers providing triage advice. The median triage accuracy in 2020 (55.8%, IQR 15.1%) was close to that in 2015 (59.1%, IQR 15.5%). The apps in 2020 were less risk averse (odds 1.11:1, the ratio of overtriage errors to undertriage errors) than those in 2015 (odds 2.82:1), missing >40% of emergencies. Few apps outperformed laypersons in either deciding whether emergency care was required or whether self-care was sufficient. No apps outperformed the laypersons on both decisions. CONCLUSIONS: Triage performance of symptom checkers has, on average, not improved over the course of 5 years. It decreased in 2 use cases (advice on when emergency care is required and when no health care is needed for the moment). However, triage capability varies widely within the sample of symptom checkers. Whether it is beneficial to seek advice from symptom checkers depends on the app chosen and on the specific question to be answered. Future research should develop resources (eg, case vignette repositories) to audit the capabilities of symptom checkers continuously and independently and provide guidance on when and to whom they should be recommended.

Workarounds in the Shadow System: An Ethnographic Study of Requirements for Documentation and Cooperation in a Clinical Advisory Center.

OBJECTIVE: Hospital information systems (HIS) are meant to manage complex work processes across healthcare organizations. We describe limitations of HIS to address local information requirements and how they are circumvented at different organizational levels. Results can be used to better support collaboration in socio-technical systems. BACKGROUND: Workarounds describe a mismatch between a technology's purpose and its actual use, whereas shadow systems are unofficial IT systems circumventing limitations of official systems to support workflows. Boundary infrastructures are conceptualized as the entirety of all (in)formal digital and analog systems connecting different communities of practice in a socio-technical system. METHODS: An ethnographic study with observations and semi-structured interviews was conducted and analyzed through categorization and iterative coding. RESULTS: Several digital-analog workarounds are employed for documentation and a shared server functions as a shadow system to support workflows in ways the HIS cannot. For collaborative documentation, all (official and informal) information sources were used simultaneously as part of an interconnected boundary infrastructure. CONCLUSION: Formal and informal IT systems are interconnected across different organizational levels and provide insights into unmet information requirements, effective and problematic work practices, and how to address them to improve system functioning. An integrated perspective on boundary infrastructures, workarounds, and shadow systems may advance system analysis, providing a more comprehensive picture of IT requirements than any concept alone. APPLICATION: Workarounds and shadow systems highlight that HIS should support systemic and local needs. Customized interfaces in HIS to support search, access, and exchange of relevant data might help to mitigate current shortcomings.

Correction: Benchmarking Triage Capability of Symptom Checkers Against That of Medical Laypersons: Survey Study.

[This corrects the article DOI: 10.2196/24475.].

Benchmarking Triage Capability of Symptom Checkers Against That of Medical Laypersons: Survey Study.

BACKGROUND: Symptom checkers (SCs) are tools developed to provide clinical decision support to laypersons. Apart from suggesting probable diagnoses, they commonly advise when users should seek care (triage advice). SCs have become increasingly popular despite prior studies rating their performance as mediocre. To date, it is unclear whether SCs can triage better than those who might choose to use them. OBJECTIVE: This study aims to compare triage accuracy between SCs and their potential users (ie, laypersons). METHODS: On Amazon Mechanical Turk, we recruited 91 adults from the United States who had no professional medical background. In a web-based survey, the participants evaluated 45 fictitious clinical case vignettes. Data for 15 SCs that had processed the same vignettes were obtained from a previous study. As main outcome measures, we assessed the accuracy of the triage assessments made by participants and SCs for each of the three triage levels (ie, emergency care, nonemergency care, self-care) and overall, the proportion of participants outperforming each SC in terms of accuracy, and the risk aversion of participants and SCs by comparing the proportion of cases that were overtriaged. RESULTS: The mean overall triage accuracy was similar for participants (60.9%, SD 6.8%; 95% CI 59.5%-62.3%) and SCs (58%, SD 12.8%). Most participants outperformed all but 5 SCs. On average, SCs more reliably detected emergencies (80.6%, SD 17.9%) than laypersons did (67.5%, SD 16.4%; 95% CI 64.1%-70.8%). Although both SCs and participants struggled with cases requiring self-care (the least urgent triage category), SCs more often wrongly classified these cases as emergencies (43/174, 24.7%) compared with laypersons (56/1365, 4.10%). CONCLUSIONS: Most SCs had no greater triage capability than an average layperson, although the triage accuracy of the five best SCs was superior to the accuracy of most participants. SCs might improve early detection of emergencies but might also needlessly increase resource utilization in health care. Laypersons sometimes require support in deciding when to rely on self-care but it is in that very situation where SCs perform the worst. Further research is needed to determine how to best combine the strengths of humans and SCs.

Patient Monitoring Alarms in an Intensive Care Unit: Observational Study With Do-It-Yourself Instructions.

BACKGROUND: As one of the most essential technical components of the intensive care unit (ICU), continuous monitoring of patients' vital parameters has significantly improved patient safety by alerting staff through an alarm when a parameter deviates from the normal range. However, the vast number of alarms regularly overwhelms staff and may induce alarm fatigue, a condition recently exacerbated by COVID-19 and potentially endangering patients. OBJECTIVE: This study focused on providing a complete and repeatable analysis of the alarm data of an ICU's patient monitoring system. We aimed to develop do-it-yourself (DIY) instructions for technically versed ICU staff to analyze their monitoring data themselves, which is an essential element for developing efficient and effective alarm optimization strategies. METHODS: This observational study was conducted using alarm log data extracted from the patient monitoring system of a 21-bed surgical ICU in 2019. DIY instructions were iteratively developed in informal interdisciplinary team meetings. The data analysis was grounded in a framework consisting of 5 dimensions, each with specific metrics: alarm load (eg, alarms per bed per day, alarm flood conditions, alarm per device and per criticality), avoidable alarms, (eg, the number of technical alarms), responsiveness and alarm handling (eg alarm duration), sensing (eg, usage of the alarm pause function), and exposure (eg, alarms per room type). Results were visualized using the R package ggplot2 to provide detailed insights into the ICU's alarm situation. RESULTS: We developed 6 DIY instructions that should be followed iteratively step by step. Alarm load metrics should be (re)defined before alarm log data are collected and analyzed. Intuitive visualizations of the alarm metrics should be created next and presented to staff in order to help identify patterns in the alarm data for designing and implementing effective alarm management interventions. We provide the script we used for the data preparation and an R-Markdown file to create comprehensive alarm reports. The alarm load in the respective ICU was quantified by 152.5 (SD 42.2) alarms per bed per day on average and alarm flood conditions with, on average, 69.55 (SD 31.12) per day that both occurred mostly in the morning shifts. Most alarms were issued by the ventilator, invasive blood pressure device, and electrocardiogram (ie, high and low blood pressure, high respiratory rate, low heart rate). The exposure to alarms per bed per day was higher in single rooms (26%, mean 172.9/137.2 alarms per day per bed). CONCLUSIONS: Analyzing ICU alarm log data provides valuable insights into the current alarm situation. Our results call for alarm management interventions that effectively reduce the number of alarms in order to ensure patient safety and ICU staff's work satisfaction. We hope our DIY instructions encourage others to follow suit in analyzing and publishing their ICU alarm data.

Heuristics for designing user-centric drug products: Lessons learned from Human Factors and Ergonomics.

Even the most effective drug product may be used improperly and thus ultimately prove ineffective if it does not meet the perceptual, motor and cognitive capacities of its target users. Currently, no comprehensive guideline for systematically designing user-centric drug products that would help prevent such limitations exists. We have compiled a list of approximate but nonetheless useful strategies-heuristics-for implementing a user-centric design of drug products and drug product portfolios. First, we present a general heuristic for user-centric design based on the framework of Human Factors and Ergonomics (HF/E). Then we demonstrate how to implement this general heuristic for older drug users (i.e., patients and caregivers aged 65 years and older) and with respect to three specific challenges (use-cases) of medication management: (A) knowing what drug product to take/administer, (B) knowing how and when to take/administer it, and (C) actually taking/administering it. The presented heuristics can be applied prospectively to include existing knowledge about user-centric design at every step during drug discovery, pharmaceutical drug development, and pre-clinical and clinical trials. After a product has been released to the market, the heuristics may guide a retrospective analysis of medication errors and barriers to product usage as a basis for iteratively optimizing both the drug product and its portfolio over their life cycle.

Medical education should teach heuristics rather than train them away.

CONTEXT: Ample research suggests that most decisions are based on heuristics-simple rules of thumb-that violate prescriptions of logic and probability theory and should therefore be avoided. Yet findings on decision making in everyday work contexts support the idea that heuristics are in fact the very basis of good decision making if adapted to the challenges and performance criteria of the specific work domain. Because traditional pedagogies aim at circumventing heuristics in (clinical) decision making, ways in which to improve the use of heuristics via (medical) education have rarely been explored. OBJECTIVE: To describe the rationale for teaching and learning proper use of heuristics, rather than stigmatising them, and to identify principles and potential implications for the design and improvement of pedagogies for training in clinical decision making. RESULTS: Based on theory and evidence concerning heuristic decision making in everyday work domains, we suggest that heuristics should not be avoided as irrational or a mere source of errors, in particular in domains where errors are unavoidable. Instead, we should teach and learn how to use heuristics to make fewer and 'smarter' mistakes rather than 'dumb' ones. Based on concepts borrowed from signal detection and control theory, we demonstrate that, to improve heuristic decision making, teaching should focus on differential diagnoses and learning from feedback and mistakes, in teams and in contextually rich settings where the frequencies, costs and trade-offs between different types of errors (misses versus false alarms) can be experienced. We discuss three possible teaching formats and how to best implement them based on our findings. CONCLUSIONS: The most promising way to train (future) physicians and other health professionals in clinical decision making is not to circumvent heuristics or correct deviations from logic and probability theory but to enhance the use of heuristics by improving perspicacity, that is, by tuning the (recognition) processes that underlie the domain-specific adaptive selection of heuristics and management of ensuing errors.

How to Uncover Sources of Unwarranted Practice Variation: A Case Study in Emergency Medicine.

Forty years of statistical database analyses have demonstrated the existence of unwarranted practice variation in care delivery, that is, variations independent of medical need, evidence, or patient preference. Alas, little is known about the underlying mechanisms and thus finding interventions to reduce unwarranted variations remains difficult, hampering quality, equity, and efficiency of care. Whereas statistical analyses describe deviations from ideal patterns, ethnographically inspired analyses aim at understanding when, how, and why variations occur in practice. Based on case studies derived from shadowing emergency physicians, I demonstrate that analyzing practice variation in practice helps to (a) advance the understanding of mechanisms and (b) evaluate/expand the existing repertoire of interventions. Results revealed unmet expectations and new sources of known variations as well as interventions complementing systemic changes with those that empower individuals to better cope with the existing system. These findings highlight the benefits of mixed-methods for understanding and tackling practice variation.

Does size matter? Spacious car cockpits may increase the probability of parking violations.

Cockpit design is a core area of human factors and ergonomics (HF/E). Ideally, good design compensates for human capacity limitations by distributing task requirements over human and interface to improve safety and performance. Recent empirical findings suggest that the mere spatial layout of car cockpits may influence driver behaviour, expanding current views on HF/E in cockpit design. To assess the reliability of findings showing that an expansive driver seat space predicts parking violations, we replicated an original field study in a geographically and socio-culturally different location and included an additional covariate. After controlling for car length, brand status, and car price, driver seat space remained a positive predictor of illegal parking. This suggests that the spatial design of vehicle cockpits may indeed have an influence on driver behaviour and may therefore be a relevant dimension to be included in research and applications of HF/E in cockpit design. Practitioner summary: In car cockpit design, ergonomists typically focus on optimising human-machine interfaces to improve traffic safety. We replicate evidence showing that increasing physical space surrounding the driver relates to an increased probability of parking violations. This suggests that spatial design should be added to the ergonomist's toolbox for reducing traffic violations.

Navigating the Decision Space: Shared Medical Decision Making as Distributed Cognition.

Despite increasing prominence, little is known about the cognitive processes underlying shared decision making. To investigate these processes, we conceptualize shared decision making as a form of distributed cognition. We introduce a Decision Space Model to identify physical and social influences on decision making. Using field observations and interviews, we demonstrate that patients and physicians in both acute and chronic care consider these influences when identifying the need for a decision, searching for decision parameters, making actionable decisions Based on the distribution of access to information and actions, we then identify four related patterns: physician dominated; physician-defined, patient-made; patient-defined, physician-made; and patient-dominated decisions. Results suggests that (a) decision making is necessarily distributed between physicians and patients, (b) differential access to information and action over time requires participants to transform a distributed task into a shared decision, and (c) adverse outcomes may result from failures to integrate physician and patient reasoning. Our analysis unifies disparate findings in the medical decision-making literature and has implications for improving care and medical training.

What makes a doctor a scholar: a systematic review and content analysis of outcome frameworks.

BACKGROUND: Many national outcome frameworks (OF) call for a sound scholarship education and scholarly behaviour of physicians. Educators however are known to interpret the scholar role in markedly different ways and at least one major initiative to unify several national outcome frameworks failed to agree on a common definition of the scholar role. Both circumstances currently limit the development of educational and assessment strategies specific for the scholar role. Given increasing physician mobility together with the global perspective inherent in a doctor's role as a scholar, we were interested in what different OFs define as the scholar role and attempted to identify communalities and differences between them. METHODS: We conducted a systematic review for OF in medical education in PubMed and google. After in- and exclusion processes, we extracted all content listed under the scholar role (if present) and categorized it based on Boyer's established model of scholarship. Next, we extracted all content related to scholarship from OFs not explicitly defining a scholar role and used it to validate the categories resulting from step one. RESULTS: From 1816 search results, we identified 13 eligible OFs, seven of which explicitly specified a scholar role. The outcomes only partly map onto Boyer's definition of scholarship: Discovery, Integration, Application, and Teaching. We adapted and validated a model extending this definition to contain Common Basics (partly overlapping with Integration and Teaching), Clinical Application (specifying Application), Research (Discovery and partly Integration), Teaching and Education (partly overlapping with Teaching) and Lifelong Learning (no equivalent in Boyer's model). Whereas almost all OFs cover Common Basics, Clinical Application, and Lifelong Learning, fewer and less specific outcomes relate to Research or Teaching. CONCLUSIONS: The need to adapt existing models of scholarship may result from the changing demands directed at medical scholars. The considerable differences identified between OFs may explain why educators have difficulties defining the scholar role and why the role is rarely assessed. We may have missed OFs due to our in- and exclusion criteria but the results provide a solid basis on which to build a common understanding of what makes a doctor a scholar.

Comparability of outcome frameworks in medical education: Implications for framework development.

BACKGROUND: Given the increasing mobility of medical students and practitioners, there is a growing need for harmonization of medical education and qualifications. Although several initiatives have sought to compare national outcome frameworks, this task has proven a challenge. Drawing on an analysis of existing outcome frameworks, we identify factors that hinder comparability and suggest ways of facilitating comparability during framework development and revisions. METHODS: We searched MedLine, EmBase and the Internet for outcome frameworks in medical education published by national or governmental organizations. We analyzed these frameworks for differences and similarities that influence comparability. RESULTS: Of 1816 search results, 13 outcome frameworks met our inclusion criteria. These frameworks differ in five core features: history and origins, formal structure, medical education system, target audience and key terms. Many frameworks reference other frameworks without acknowledging these differences. Importantly, the level of detail of the outcomes specified differs both within and between frameworks. CONCLUSION: The differences identified explain some of the challenges involved in comparing outcome frameworks and medical qualifications. We propose a two-level model distinguishing between "core" competencies and culture-specific "secondary" competencies. This approach could strike a balance between local specifics and cross-national comparability of outcome frameworks and medical education.

Influence of Disease-Related Stigma on Patients' Decisions to Upload Medical Reports to the German Electronic Health Record: Randomized Controlled Trial.

BACKGROUND: The rollout of the electronic health record (EHR) represents a central component of the digital transformation of the German health care system. Although the EHR promises more effective, safer, and faster treatment of patients from a systems perspective, the successful implementation of the EHR largely depends on the patient. In a recent survey, 3 out of 4 Germans stated that they intend to use the EHR, whereas other studies show that the intention to use a technology is not a reliable and sufficient predictor of actual use. OBJECTIVE: Controlling for patients' intention to use the EHR, we investigated whether disease-specific risk perceptions related to the time course of the disease and disease-related stigma explain the additional variance in patients' decisions to upload medical reports to the EHR. METHODS: In an online user study, 241 German participants were asked to interact with a randomly assigned medical report that varied systematically in terms of disease-related stigma (high vs low) and disease time course (acute vs chronic) and to decide whether to upload it to the EHR. RESULTS: Disease-related stigma (odds ratio 0.154, P<.001) offset the generally positive relationship between intention to use and the upload decision (odds ratio 2.628, P<.001), whereas the disease time course showed no effect. CONCLUSIONS: Even if patients generally intend to use the EHR, risk perceptions such as those related to diseases associated with social stigma may deter people from uploading related medical reports to the EHR. To ensure the reliable use of this key technology in a digitalized health care system, transparent and easy-to-comprehend information about the safety standards of the EHR are warranted across the board, even for populations that are generally in favor of using the EHR.

Talking about Familial Breast and Ovarian Cancer Risk-Evaluation of a Psychosocial Training Module for Gynecologists in Germany.

Primary care gynecologists are increasingly integrated into the care of patients with hereditary breast and ovarian cancer (HBOC) risks. These physicians should not only have basic genetic knowledge; they should also feel able to sensitively address an increased HBOC risk and deal with emotional, stressful situations in this context. Our project aimed at developing a training module, 'iKNOWgynetics', addressing psychosocial challenges in the context of HBOC care for primary care gynecologists. We developed the psychosocial training module in three phases: first, we conducted an online survey with n = 35 women with a family history of breast or ovarian cancer to assess patients' experiences and needs. Second, based on the results of the needs assessment, we developed the training module. Third, we evaluated the training by assessing physicians' (n = 109) self-efficacy with regard to communication skills in the context of HBOC before and after the training. In the needs assessment, seven psychosocial themes emerged. These themes, complementing a review of the literature, informed the training curriculum. The training was divided into two parts: (1) communicating with women before genetic testing and (2) care co-management for women with HBOC after genetic testing. After the training, participants reported a significant increase in self-efficacy in three domains: communicating empathetically, educating patients in a comprehensible way and dealing with emotionally challenging situations. Our results highlight the relevance of psychosocial issues for patients with HBOC. A genetic literacy training module that integrates aspects of psychosocial care increases physicians' confidence in dealing with emotionally challenging situations before and after their patients' genetic testing. Thus, such trainings may improve the care of women with hereditary cancer risks.

Teaching prudent antibiotic use on the go: a descriptive report on development, utilization and listener satisfaction of an educational podcast format for medical students and young professionals.

BACKGROUND: An important component in fostering the responsible use of antibiotics is training of new and future prescribers in this interdisciplinary topic. Because podcasts are playing an increasing role in medical education, we aimed to develop and evaluate a podcast format with practice and guideline-oriented learning content on antibiotic therapy for medical students and young medical professionals. METHODS: We developed the concept for the podcast with the direct involvement of medical students and medical experts with teaching experience. We used video conferencing when recording the episodes in order to have quick, easy, and nationwide access to the experts involved. We released an episode every 2 to 4 weeks on the popular podcast platforms. The podcast was promoted through mailing lists, social and print media, and at conferences. The evaluation of episodes was based on user data provided by the platforms and an anonymous feedback questionnaire linked to each episode in the podcast notes. RESULTS: Between December 2021 and December 2022 19 episodes of InfectEd: der Antibiotika-Podcast were released. The mean duration of an episode was 91 min. By March 9, 2023, a total of 38,829 downloads and streams had been recorded. The majority of users listened to the podcast on a mobile device. The average playing time per episode was 65%. The feedback questionnaire was completed 135 times. 60.7% of respondents were female, 38.5% male. The majority of respondents were in their twenties and thirties (66.7%). 31.1% were medical students, 25.9% were residents, and 25.2% were specialists. Listeners were asked to rate episodes on a scale from 1 to 6, where 1 was "very good" and 6 was "insufficient." Ratings did not differ significantly between female and male respondents or between medical students and others. 118 respondents (87.4%) reported an increase in knowledge. Free-text feedback frequently emphasized clinical and also exam relevance. CONCLUSION: Our podcast format, developed with a user-centered approach, was broadly distributed and has been well accepted by both medical students and physicians alike. It provides a large number of learners with low-threshold access to current, guideline-orientated content and could be a useful supplement to conventional teaching formats.

Extending the Privacy Calculus to the mHealth Domain: Survey Study on the Intention to Use mHealth Apps in Germany.

BACKGROUND: With the increasing digitalization of the health sector, more and more mobile health (mHealth) apps are coming to the market to continuously collect and process sensitive health data for the benefit of patients and providers. These technologies open up new opportunities to make the health care system more efficient and save costs but also pose potential threats such as loss of data or finances. OBJECTIVE: This study aims to present an empirical review and adaptation of the extended privacy calculus model to the mHealth domain and to understand what factors influence the intended usage of mHealth technologies. METHODS: A survey study was conducted to empirically validate our model, using a case vignette as cover story. Data were collected from 250 German participants and analyzed using a covariance-based structural equation model. RESULTS: The model explains R2=79.3% of the variance in intention to use. The 3 main factors (social norms, attitude to privacy, and perceived control over personal data) influenced the intention to use mHealth apps, albeit partially indirectly. The intention to use mHealth apps is driven by the perceived benefits of the technology, trust in the provider, and social norms. Privacy concerns have no bearing on the intention to use. The attitude to privacy has a large inhibiting effect on perceived benefits, as well as on trust in the provider. Perceived control over personal data clearly dispels privacy concerns and supports the relationship of trust between the user and the provider. CONCLUSIONS: Based on the privacy calculus, our domain-specific model explains the intention to use mHealth apps better than previous, more general models. The findings allow health care providers to improve their products and to increase usage by targeting specific user groups.

[Virtual hallway chats and status updates: collaboration in avatar-based work environments]. / Virtuelle Flurgespräche und Status-Updates: Zusammenarbeit in avatar-basierten Arbeitsumgebungen.

This article focuses on the collaboration of hybrid teams in avatar-based virtual office environments. Based on the three dimensions of virtuality, we pursue the following research questions: (1) How is everyday work and collaboration coordinated in these environments? and (2) Which advantages and challenges do users perceive in relation to this form of work? Based on a multi-method study consisting of qualitative interviews with experienced users and a participatory focus group discussion with new users, we illustrate that collaboration in avatar-based work environments is marked by a diverse array of work practices-ranging from co-present to mobile work-and that promising implementation methods exist to coordinate these practices. However, our results also suggest that to exploit this potential, not only the virtual environments but also teams' work practices and digital infrastructure must be further developed.Practical relevance: The study discusses virtuality based on a currently used avatar-based work environment and illustrates the perspectives of experienced and new users on collaboration in these socio-technical work systems. Specifically, we present concrete implementations and challenges of collaborative work practices in these virtual environments, which offer orientation for practitioners interested in applying these solutions to their own work contexts.