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BACKGROUND: Menstrual cycle tracking apps (MCTAs) have potential in epidemiological studies of women's health, facilitating real-time tracking of bleeding days and menstrual-associated signs and symptoms. However, information regarding the characteristics of MCTA users versus cycle nontrackers is limited, which may inform generalizability. OBJECTIVE: We compared characteristics among individuals using MCTAs (app users), individuals who do not track their cycles (nontrackers), and those who used other forms of menstrual tracking (other trackers). METHODS: The Ovulation and Menstruation Health Pilot Study tested the feasibility of a digitally enabled evaluation of menstrual health. Recruitment occurred between September 2017 and March 2018. Menstrual cycle tracking behavior, demographic, and general and reproductive health history data were collected from eligible individuals (females aged 18-45 years, comfortable communicating in English). Menstrual cycle tracking behavior was categorized in 3 ways: menstrual cycle tracking via app usage, that via other methods, and nontracking. Demographic factors, health conditions, and menstrual cycle characteristics were compared across the menstrual tracking method (app users vs nontrackers, app users vs other trackers, and other trackers vs nontrackers) were assessed using chi-square or Fisher exact tests. RESULTS: In total, 263 participants met the eligibility criteria and completed the digital survey. Most of the cohort (n=191, 72.6%) was 18-29 years old, predominantly White (n=170, 64.6%), had attained 4 years of college education or higher (n= 209, 79.5%), and had a household income below US $50,000 (n=123, 46.8%). Among all participants, 103 (39%) were MCTA users (app users), 97 (37%) did not engage in any tracking (nontrackers), and 63 (24%) used other forms of tracking (other trackers). Across all groups, no meaningful differences existed in race and ethnicity, household income, and education level. The proportion of ever-use of hormonal contraceptives was lower (n=74, 71.8% vs n=87, 90%, P=.001), lifetime smoking status was lower (n=6, 6% vs n=15, 17%, P=.04), and diagnosis rate of gastrointestinal reflux disease (GERD) was higher (n=25, 24.3% vs n=12, 12.4%, P=.04) in app users than in nontrackers. The proportions of hormonal contraceptives ever used and lifetime smoking status were both lower (n=74, 71.8% vs n=56, 88.9%, P=.01; n=6, 6% vs n=11, 17.5%, P=.02) in app users than in other trackers. Other trackers had lower proportions of ever-use of hormonal contraceptives (n=130, 78.3% vs n=87, 89.7%, P=.02) and higher diagnostic rates of heartburn or GERD (n=39, 23.5% vs n=12, 12.4%, P.03) and anxiety or panic disorder (n=64, 38.6% vs n=25, 25.8%, P=.04) than nontrackers. Menstrual cycle characteristics did not differ across all groups. CONCLUSIONS: Our results suggest that app users, other trackers, and nontrackers are largely comparable in demographic and menstrual cycle characteristics. Future studies should determine reasons for tracking and tracking-related behaviors to further understand whether individuals who use MCTAs are comparable to nontrackers.

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OBJECTIVE: Describe the demographic profile of US participants in Amgen clinical trials over a 10-year period and variations across therapeutic areas, indications, and geographies. METHODS: Cross-sectional retrospective study including participants enrolled (2005-2020) in phase 1-3 trials completed between January 1, 2012 and June 30, 2021. RESULTS: Among 31,619 participants enrolled across 258 trials, one-fifth represented racial minority populations (Asian, 3%; Black or African American, 17%; American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, multiracial, each < 1%); fewer than one-fifth (16%) represented an ethnic minority population (Hispanic or Latino). Compared with census data, representation of racial and ethnic groups varied across US states. Across most therapeutic areas (bone, cardiovascular, hematology/oncology, inflammation, metabolic disorders, neuroscience) except nephrology, participants were predominantly White (72-81%). A similar proportion of males and females were enrolled between 2005 and 2016; male representation was disproportionately higher than female between 2016 and 2020. Across most medical indications, the majority of participants were 18-65 years of age. CONCLUSIONS AND RELEVANCE: While the clinical research community is striving to achieve diversity and proportional representation across clinical trials, certain populations remain underrepresented. Our data provide a baseline assessment of the diversity and representation of US participants in Amgen-sponsored clinical trials and add to a growing body of evidence on the importance of diversity in clinical research. These data provide a foundation for strategies aimed at supporting more equitable and representative research, and a baseline from which to assess the impact of future strategies to advance health equity.

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Children experiencing homelessness face particular barriers to accessing early interventions. Our study sought to explore the experiences of families in accessing Early Intervention Program services (EI) while living in a family shelter. Semi-structured in-depth interviews were undertaken with nineteen caregivers who had recently experienced or were contemporaneously experiencing homelessness from three shelter sites in Boston, Massachusetts. Our findings demonstrate the role of the shelter both in inhibiting and promoting access to early intervention. Shelter-related barriers included limited physical space, lack of care continuity amidst frequent relocations, and mistrust due to feelings of stigma. Early interventionists played a crucial role in mitigating challenges but were often unable to fully overcome these and other barriers tied to shelter environments. Effective strategies included flexibility in accommodating shifting schedules, provision of socioemotional support, and proactively linking caregivers to additional upstream resources. Efforts to mitigate shelter-related challenges will require interdisciplinary collaboration at both local and state levels. Further efforts should focus on providing increased continuity of care in a manner that acknowledges the structural barriers of homelessness.

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INTRODUCTION: People experiencing homelessness (PEH) make up a disproportionate share of opioid overdose fatalities. We set out to identify the facilitators and barriers that shape whether PEH initiate medications for opioid use disorder (MOUDs), both generally and after an overdose. METHODS: We conducted semi-structured interviews with 29 PEH in Boston who had self-reported history of opioid overdose. Seventeen participants had taken prescribed MOUD, and 12 had not. Using NVivo software we then coded transcripts applying the Borkan Immersion Crystallization method to identify individual, social, and structural factors influencing MOUD initiation. RESULTS: Individual factors: Within the "timing" theme, non-fatal overdoses often led participants to feel sick with naloxone-induced withdrawal, decreasing treatment-seeking. By contrast, chronic opioid use consequences, like daily stress with finding drugs and shelter, increased interest in MOUD. Within the "medication benefits" and "medication concerns" themes, interest in MOUD initiation hinged on whether participants believed in or doubted MOUDs' effectiveness for reducing drug use. In a related theme, participants perceived that individuals must be "ready" in order for MOUDs to be effective. Social factors: Within the "peer influence" theme, peers who use opioids were prominent sources of encouragement or deterrence for starting MOUD. "Family influence" emerged as a theme for participants with MOUD history. Structural factors: Within the "health systems" theme, participants described that experiencing stigma from care providers toward people who use drugs was a barrier to MOUD. Within the "treatment systems" theme, regulations made methadone particularly difficult to access, even though nearly all participants had Medicaid coverage to pay for treatment. Within the "criminal justice systems" theme, participants reported frequent criminal justice involvement, with jails facilitating or preventing MOUD access. CONCLUSIONS: Future interventions should (a) increase MOUD interest by messaging-ideally via peers-that MOUDs are effective for PEH and (b) increase MOUD access by making MOUDs available across health, treatment, and carceral systems. Mobile outreach and MOUD treatment would help reach PEH when they are facing daily opioid use disorder stressors and are more open to MOUD initiation. Future research should explore how racial, ethnic, and linguistic identities affect MOUD engagement among PEH.

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PURPOSE OF REVIEW: The goal of this review was to evaluate whether the fields available in iOS mobile phone apps for recording menstrual cycle symptoms are able to be harmonized across platforms for potential use in research, such as aggregated data analysis. RECENT FINDINGS: Symptom tracking capabilities are a common feature among menstrual health apps but have been the subject of limited investigations. Apps differ with respect to which symptoms are included and the rationale for these differences is unclear. Epidemiologic studies are poised to incorporate these data; however, a thorough exploration of symptom tracking functionality across apps is required. SUMMARY: Our review finds that the language used to describe symptoms and the specificity with which symptoms are collected varies greatly across the most used iOS tracking apps. Although some apps allow numerical and qualitative description of symptoms, such as sleep and mood, most simply record the presence or absence of a symptom. Collaborative efforts between clinicians and researchers to guide what and how data is collected may allow tracking apps to realize their potential diagnostic applicability. Regardless, with the increasing use of menstrual health tracking apps, it is imperative that data retrieved from such apps can realize its potential in the research and clinical ecosystems.

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This review updates and consolidates evidence on the safety of transcranial Direct Current Stimulation (tDCS). Safety is here operationally defined by, and limited to, the absence of evidence for a Serious Adverse Effect, the criteria for which are rigorously defined. This review adopts an evidence-based approach, based on an aggregation of experience from human trials, taking care not to confuse speculation on potential hazards or lack of data to refute such speculation with evidence for risk. Safety data from animal tests for tissue damage are reviewed with systematic consideration of translation to humans. Arbitrary safety considerations are avoided. Computational models are used to relate dose to brain exposure in humans and animals. We review relevant dose-response curves and dose metrics (e.g. current, duration, current density, charge, charge density) for meaningful safety standards. Special consideration is given to theoretically vulnerable populations including children and the elderly, subjects with mood disorders, epilepsy, stroke, implants, and home users. Evidence from relevant animal models indicates that brain injury by Direct Current Stimulation (DCS) occurs at predicted brain current densities (6.3-13 A/m(2)) that are over an order of magnitude above those produced by conventional tDCS. To date, the use of conventional tDCS protocols in human trials (≤40 min, ≤4 milliamperes, ≤7.2 Coulombs) has not produced any reports of a Serious Adverse Effect or irreversible injury across over 33,200 sessions and 1000 subjects with repeated sessions. This includes a wide variety of subjects, including persons from potentially vulnerable populations.

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