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ABSTRACTBackground Women and underrepresented in medicine and the health sciences (URiM) faculty face inequities in advancement. Career sponsorship may be a remedy. Few studies have described sponsorship in academic medicine and none across an institution.Objective To examine faculty awareness, experiences, and perceptions of sponsorship at a large academic health center.Design Anonymous online survey.Participants Faculty with a ≥50% appointment.Main Measures The survey contained 31 Likert, multiple-choice, yes/no, and open-ended questions about familiarity with the concept of sponsorship; experience of having or being a sponsor; receipt of specific sponsorship activities; sponsorship impact and satisfaction; mentorship and sponsorship co-occurrence; and perception of inequities. Open-ended questions were analyzed using content analysis.Key Results Thirty-one percent of the surveyed faculty (903/2900) responded of whom 53% (477/903) were women and 10% (95/903) were URiM. Familiarity with sponsorship was higher among assistant (91%, 269/894) and associate (182/894; 64%) professors versus full professors (38%, 329/894); women (67%, 319/488) versus men (62%, 169/488); and URiM (77%, 66/517) versus non-URiM faculty (55%, 451/517). A majority had a personal sponsor (528/691; 76%) during their career and were satisfied with their sponsorship (64%, 532/828). However, when responses from faculty of different professorial ranks were stratified by gender and URiM identity, we observed possible cohort effects. Furthermore, 55% (398/718) of respondents perceived that women received less sponsorship than men and 46% (312/672) that URiM faculty received less than their peers. We identified seven qualitative themes: sponsorship importance, growing awareness and change, institutional biases and deficiencies, groups getting less sponsorship, people with sponsorship power, conflation with mentorship, and potential for negative impact.Conclusions A majority of respondents at a large academic health center reported sponsorship familiarity, receipt, and satisfaction. Yet many perceived persistent institutional biases and the need for systematic change to improve sponsorship transparency, equity, and impact.

Objectives: To determine the generalizability of crowdsourced, electronic health data from self-selected individuals using a national survey as a reference., Methods: Using the world's largest crowdsourcing platform in 2015, we collected data on characteristics known to influence cardiovascular disease risk and identified comparable data from the 2013 Behavioral Risk Factor Surveillance System. We used age-stratified logistic regression models to identify differences among groups., Results: Crowdsourced respondents were younger, more likely to be non-Hispanic and White, and had higher educational attainment. Those aged 40 to 59 years were similar to US adults in the rates of smoking, diabetes, hypertension, and hyperlipidemia. Those aged 18 to 39 years were less similar, whereas those aged 60 to 75 years were underrepresented among crowdsourced respondents., Conclusions: Crowdsourced health data might be most generalizable to adults aged 40 to 59 years, but studies of younger or older populations, racial and ethnic minorities, or those with lower educational attainment should approach crowdsourced data with caution. Public Health Implications. Policymakers, the national Precision Medicine Initiative, and others planning to use crowdsourced data should take explicit steps to define and address anticipated underrepresentation by important population subgroups.