Background: Due to the COVID-19 pandemic, most faculty in science, technology, engineering, mathematics, and medicine (STEMM) began working from home, including many who were simultaneously caring for children. The objective was to assess associations of gender and parental status with self-reported academic productivity before ( i.e. , mid-January to mid-March 2020) and during the pandemic ( i.e. , mid-March to mid-May 2020). Materials and Methods: STEMM faculty in the United States ( N = 284, 67.6% women, 57.0% with children younger than the age of 18 years living at home) completed a survey about the number of hours worked and the frequency of academic productivity activities. Results: There was no significant difference in the hours worked per week by gender (men, M [standard deviation, SD] = 45.8 [16.7], women = 43.1 [16.3]). Faculty with 0–5-year-old children reported significantly fewer work hours (33.7 [13.9]) compared to all other groups (No children = 49.2 [14.9], 6–11 years old = 48.3 [13.9], and 12–17 years old = 49.5 [13.9], p < 0.0001). Women's self-reported first/corresponding author's and coauthor's article submissions decreased significantly between the two time periods; men's productivity metrics did not change. Faculty with 0–5-year-old children completed significantly fewer peer review assignments, attended fewer funding panel meetings, and submitted fewer first authors' articles during the pandemic compared to the previous period. Those with children aged 6 years or older at home or without children at home reported significant increases or stable productivity. Conclusions: Overall, significant disparities were observed in academic productivity by gender and child age during the pandemic and if confirmed by further research, should be considered by academic institutions and funding agencies when making decisions regarding funding and hiring as well as promotion and tenure.

Digital interventions offer many possibilities for improving health, as remote interventions can enhance reach and access to underserved groups of society. However, research evaluating digital health interventions demonstrates that such technologies do not equally benefit all and that some in fact seem to reinforce a “digital health divide.” By better understanding these potential pitfalls, we may contribute to narrowing the digital divide in health promotion. The aim of this article is to highlight and reflect upon study design decisions that might unintentionally enhance inequities across key research stages—recruitment, enrollment, engagement, efficacy/effectiveness, and retention. To address the concerns highlighted, we propose strategies including (1) the standard definition of “effectiveness” should be revised to include a measure of inclusivity; (2) studies should report a broad range of potential inequity indicators of participants recruited, randomized, and retained and should conduct sensitivity analyses examining potential sociodemographic differences for both the effect and engagement of the digital interventions; (3) participants from historically marginalized groups should be involved in the design of study procedures, including those related to recruitment, consent, intervention implementation and engagement, assessment, and retention; (4) eligibility criteria should be minimized and carefully selected and the screening process should be streamlined; (5) preregistration of trials should include recruitment benchmarks for sample diversity and comprehensive lists of sociodemographic characteristics assessed; and (6) studies within trials should be embedded to systematically test recruitment and retention strategies to improve inclusivity. The implementation of these strategies would enhance the ability of digital health trials to recruit, randomize, engage, and retain a broader and more representative population in trials, ultimately minimizing the digital divide and broadly improving population health.

With the COVID‐19 pandemic, clinicians and researchers have been suddenly confronted with the difficulty of treatment provision and continuation of clinical trials without face‐to‐face contact. This predicament has resulted in the rapid adoption of telehealth methodologies.¹ Clinicians and researchers focused on obesity management have an additional need‐‐ a remote way to measure weight. In this piece, we will describe electronic scales (e‐scales) and provide guidance on how clinicians/researchers might best implement e‐scales in their clinical practice or research studies to remotely measure weight.

An accurate estimate of preconception weight is necessary for providing a gestational weight gain range based on the Institute of Medicine’s guidelines; however, an accurate and proximal preconception weight is not available for most women. We examined the validity of first trimester weights for estimating preconception body mass index category. Under identical measurement conditions, preconception weight and two first trimester weights (i.e., 4–10 and 12 weeks gestation) were obtained (n = 43). The 4–10 week and the 12 week weight correctly classified 95 and 91% women, respectively. Mean weight changes were relatively small overall (M = 0.74 ± 1.99 kg at 4–10 weeks and M = 1.02 ± 2.46 at 12 weeks). There was a significant difference in mean weight gain by body mass index category at 4–10 weeks (−0.09 ± 1.86 kg for normal weight participants vs. 1.61 + 1.76 kg for overweight/obese participants, p = 0.01), but not at 12 weeks (0.53 ± 2.29 kg for normal weight participants vs. 1.54 ± 2.58 kg for overweight/obese participants). Assigning gestational weight gain guidelines based on an early first trimester weight resulted in 5–9% of women being misclassified depending on the gestational week the weight was obtained. Thus, most women are correctly classified based on a first trimester weight, particularly an early first trimester weight, although it is possible that modeling strategies could be developed to further improve estimates of preconception body mass index category. Clinicaltrials.gov # NCT01131117 , registered May 25, 2010.

Patient-provider communication is a critical component of healthcare and is associated with treatment quality and outcomes for women with breast cancer. This qualitative study examines similarities and differences in patient perspectives of communication needs between Black and White breast cancer survivors. We conducted four focus groups (N = 28) involving women with early-stage breast cancer on adjuvant endocrine therapy (AET), stratified by race and length of time on AET (< 6 months and >6 months). Each group was moderated by a race-concordant moderator and analyzed by emergent themes. Participants expressed common patient-provider communication needs, namely increased sensitivity from oncologists during the initial cancer diagnosis, personalized information to facilitate treatment decisions, emotional support during the transition from active treatment to maintenance, and rapid provider responses to mobile app-based queries. Communication differences by race also emerged. Black women were less likely than White women to describe having their informational needs met. White women praised longstanding relationships with providers, while Black women shared personal stories of disempowered interactions and noted the importance of patient advocates. White women more often reported privacy concerns about technology use. Unlike White women, Black women reported willingness to discuss sensitive topics, both online and offline, but believed those discussions made their providers feel uncomfortable. Early-stage breast cancer patients on AET, regardless of race, have similar needs for patient-centered communication with their oncologists. However, Black women were more likely to report experiencing poorer communication with providers than White women, which may be improved by technology and advocates.