In the last decade, genomic medicine education initiatives have surfaced across the spectrum of physician training in order to help address a gap in genomic medicine preparedness among physicians. The approaches are diverse and stem from the belief that 21st century physicians must be proficient in genomic medicine applications as they will be leaders in the precision medicine movement. We conducted a review of literature in genomic medicine education and training for medical students, residents, fellows, and practicing physicians with articles published between June 2015 and January 2018 to gain a picture of the current state of genomic medicine education with a focus on the United States. We found evidence of progress in the development of new and innovative educational programs and other resources aimed at increasing physician knowledge and readiness. Three overarching educational approach themes emerged, including immersive and experiential learning; interdisciplinary and interprofessional education; and electronic- and web-based approaches. This review is not exhaustive, nevertheless, it may inform future directions and improvements for genomic medicine education. Important next-steps include: (i) identifying and studying ways to best implement low-cost dissemination of genomic information; (ii) emphasizing genomic medicine education program evaluation and (iii) incorporating interprofessional and interdisciplinary initiatives. Genomic medicine education and training will become more and more relevant in the years to come as physicians increasingly interact with genomic and other precision medicine technologies.

BackgroundResearchers have largely turned to commercial app stores, randomized trials, and systematic reviews to make sense of the mHealth landscape. Few studies have approached understanding by collecting information from target end users. The end user perspective is critical as end user interest in and use of mHealth technologies will ultimately drive the efficacy of these tools.ObjectiveThe purpose of this study was to obtain information from end users of mHealth technologies to better understand the physical and mental health apps people use and for what purposes.MethodsPeople with depressive or anxious symptoms (N=176) seeking entry into a trial of mental health and well-being apps for Android devices completed online questionnaires assessing depression and anxiety (Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7), past and current mental health treatment-seeking behavior, overall mobile device use, and use of mobile health apps. Participants reported the physical health and mental health apps on their devices and their reasons for using them. Data were extracted from the participant self-reports and apps and app purposes were coded in order to categorize them.ResultsParticipants were largely white, middle-aged females from the Midwest region of the United States recruited via a health care organization and Web-based advertising (135 female, 41 male, mean age 38.64 years, age range 19-75 years.) Over three-quarters (137/176, 77.8%) of participants indicated having a health app on their device. The top 3 kinds of apps were exercise, fitness, and pedometers or heart rate monitoring apps (93/176, 52.8%); diet, food, or calorie counting apps (65/177, 36.9%); and mental health/wellness apps (46/177, 26.1%). The mean number of mobile physical and mental health apps on a participant’s phone was 2.15 (SD 3.195). Of 176 participants, 107 (60.8%) specifically reported the top 5 health apps that they used and their purposes. Across the 107 participants, a total of 285 apps were reported, with 139 being unique apps. The majority of these apps were free (129/139, 92.8%). Almost two-thirds of participants (67/107, 62.6%) reported using health apps at least on a daily basis.ConclusionsAmong those seeking support for their well-being via physical and mental health apps, people are using a variety of health apps. These people use health apps on a daily basis, especially free apps. The most common reason for using a health app is to track some health-related data; for mental health apps specifically, training or habit building was the most popular reason. Understanding the end user perspective is important because it allows us to build on the foundation of previously established mHealth research and may help guide future work in mHealth.Trial RegistrationClinicaltrials.gov NCT02176226; https://clinicaltrials.gov/ct2/show/NCT02176226 (Archived by WebCite at http://www.webcitation.org/6rGc1MGyM)

BackgroundThe ability to successfully recruit participants for electronic health (eHealth) clinical trials is largely dependent on the use of efficient and effective recruitment strategies. Determining which types of recruitment strategies to use presents a challenge for many researchers.ObjectiveThe aim of this study was to present an analysis of the time-efficiency and cost-effectiveness of recruitment strategies for eHealth clinical trials, and it describes a framework for cost-effective trial recruitment.MethodsParticipants were recruited for one of 5 eHealth trials of interventions for common mental health conditions. A multipronged recruitment approach was used, including digital (eg, social media and Craigslist), research registry-based, print (eg, flyers and posters on public transportation), clinic-based (eg, a general internal medicine clinic within an academic medical center and a large nonprofit health care organization), a market research recruitment firm, and traditional media strategies (eg, newspaper and television coverage in response to press releases). The time costs and fees for each recruitment method were calculated, and the participant yield on recruitment costs was calculated by dividing the number of enrolled participants by the total cost for each method.ResultsA total of 777 participants were enrolled across all trials. Digital recruitment strategies yielded the largest number of participants across the 5 clinical trials and represented 34.0% (264/777) of the total enrolled participants. Registry-based recruitment strategies were in second place by enrolling 28.0% (217/777) of the total enrolled participants across trials. Research registry-based recruitment had a relatively high conversion rate from potential participants who contacted our center for being screened to be enrolled, and it was also the most cost-effective for enrolling participants in this set of clinical trials with a total cost per person enrolled at US $8.99.ConclusionsOn the basis of these results, a framework is proposed for participant recruitment. To make decisions on initiating and maintaining different types of recruitment strategies, the resources available and requirements of the research study (or studies) need to be carefully examined.

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Background In comparison with the general population, physicians, and physicians‐in‐training are at greater risk for suicide. Although key gender differences in suicide risk factors and behaviors have been identified in the general population, the extent to which these differences apply to physicians and physicians‐in‐training is unclear. Here, we aimed to identify gender differences in risk factors, clinical presentation, and help‐seeking behaviors of medical students, house staff, and physician faculty at high risk for suicide. Methods We explored gender differences among 450 physicians and trainees meeting criteria for high suicide risk on anonymous online questionnaires completed between 2009 and 2017. Results High‐risk female trainees and physicians had higher mean Patient Health Questionnaire‐9 (PHQ‐9) scores compared with the males (11.1, standard deviation [SD] 5.1 vs. 9.8, SD 4.7) and were more likely to endorse feeling worried (73.8% vs. 61.2%), irritable (60.4% vs. 49.4%), and stressed (79.6% vs. 70%). High‐risk male trainees and physicians were more likely than females to endorse suicidal thoughts (31.2% vs. 22.1%), intense anger (24.3% vs. 16.1%), drinking too much (31.2% vs. 22.3%), and recreational drug or prescription medication use without clinically appropriate follow‐up (9.4% vs. 4.3%). There were no gender differences in help‐seeking behaviors. Conclusions This is the first study to report gender differences among risk factors, presentation, and help‐seeking behaviors of physicians, and trainees at high risk for suicide. Our findings are mostly consistent with those of the general population and show that only a minority of at‐risk men and women in healthcare sought treatment, highlighting the importance of intervention and suicide prevention in this population.

The authors thank Erin Smith, Ph.D. and Vikas Bansal, Ph.D. for their contributions to the development of the DNA ancestry testing pipeline, Debra L. Boeldt, Ph.D. for her contributions to an earlier draft of the manuscript, and Lisette Diaz for her assistance conducting literature searches.

Objective We sought to present a model of privacy disposition and its development based on qualitative research on privacy considerations in the context of emerging health technologies. Materials and Methods We spoke to 108 participants across 44 interviews and 9 focus groups to understand the range of ways in which individuals value (or do not value) control over their health information. Transcripts of interviews and focus groups were systematically coded and analyzed in ATLAS.ti for privacy considerations expressed by respondents. Results Three key findings from the qualitative data suggest a model of privacy disposition. First, participants described privacy related behavior as both contextual and habitual. Second, there are motivations for and deterrents to sharing personal information that do not fit into the analytical categories of risks and benefits. Third, philosophies of privacy, often described as attitudes toward privacy, should be classified as a subtype of motivation or deterrent. Discussion This qualitative analysis suggests a simple but potentially powerful conceptual model of privacy disposition, or what makes a person more or less private. Components of privacy disposition are identifiable and measurable through self-report and therefore amenable to operationalization and further quantitative inquiry. Conclusions We propose this model as the basis for a psychometric instrument that can be used to identify types of privacy dispositions, with potential applications in research, clinical practice, system design, and policy.

Objective: This exploratory study examines privacy perceptions and preferences among adolescent and young adult (AYA) and adult individuals with an emphasis on health-related information. Method: Participants (N ϭ 112) completed surveys including measures of privacy concern, consumer control of information, online privacy concern and behavior, and sensitivity of personal information. Results: AYAs (n ϭ 36) and adults (n ϭ 76) showed similar levels of general privacy concern; specifically, their ratings of the sensitivity of non-health-related personal data did not differ. AYAs' ratings of various health information sensitivities were lower than adults' ratings, and AYAs reported less concern on subscales addressing online and consumer data collection. Conclusion: Discrepancies between AYA and adult responses to different privacy scales suggest contextual integrity at work. That is, AYAs' and adults' privacy perceptions differ based on the type of information being shared, and they draw on different norms to govern information flow. AYAs are more likely to feel they have control over their personal information and feel comfortable employing privacy protecting strategies. AYAs are less likely to see online information collection as a violation of an implied social contract. This study highlights differences in AYA and adult attitudes toward privacy and suggests that AYAs care about privacy but perceive certain types of information collection as less threatening than adults. Implications for Impact StatementAdolescents and young adults (AYAs) and adults follow different norms with regards to appropriate information flow. Policymakers, parents, educators, and others who are charged with protecting young people should be aware that AYAs may be more open to information flows that they perceive as appropriate, including health information flows. Healthcare providers who encourage AYAs to use mobile health apps and devices should be mindful of privacy concerns as they work to serve their patients' best interests.