Wilton, Angelina R.

Introduction Sleep is routinely assessed in the management of mental health conditions. Wearable technologies like smartwatches offer a non-intrusive method to quantitatively measure sleep. However, there are limited empirical benchmarks for sleep duration and sleep quality measured by wearables against user reports. This study aims to evaluate the concordance between user-reported and smartwatch-measured hours of sleep and sleep quality. Methods Participants were recruited from two decentralized digital health well-being studies and completed a 7-day sleep diary while simultaneously wearing their smartwatch to sleep (November 7, 2023 - June 30, 2024). Participants self-reported sleep timestamps and perceived sleep quality using the Sleep Quality Scale. Sleep timestamps and quality were also derived from their smartwatches (Garmin Vívoactive 4 2019, Garmin Venu 2 Plus 2022, and Garmin Venu 3/3S 2023). Statistical analyses included paired t-tests, equipercentile linking, and chi-square tests to assess agreement between smartwatch and self-reported sleep parameters. Exploratory analyses established the difference between reported and recorded sleep duration in healthcare shift workers. Results From 841 sleep instances reported by 130 participants wearing three different generation smartwatches, the mean difference in sleep duration between smartwatch-recorded and participant-reported was 21.22 (Garmin Vívoactive), 11.67 (Garmin Venu 2 Plus), and 6.58 (Garmin Venu 3/3S) minutes, respectively. There were statistically significant between-group differences in mean sleep durations assessed by participant self-report vs. Vívoactive 4 smartwatches, but not self-report vs. Venu 2 Plus or Venu 3/3S smartwatches. Equipercentile linking revealed concordance between smartwatch sleep scores and self-reported sleep quality using the Sleep Quality Scale (SQS) between 4 and 7, with disagreements observed at the SQS ranges from 0–4 and 7-10. Conclusions These results suggest that wearables can reliably measure sleep duration, and future research warrants improvements in algorithms that estimate sleep quality with validations across different wearable vendors.

Importance The potential utility of real-time digital therapeutics that identify impending behavioral outbursts to proactively apply evidence-based interventions for managing children with disruptive behavior disorder has not been tested. Objectives To evaluate feasibility and adherence of a digitally augmented, real-time, proactive behavioral intervention (smartwatch) for children with disruptive behaviors. Design, Setting, and Participants This randomized clinical trial was conducted between March 1, 2022, and December 31, 2023, at Mayo Clinic in Rochester, Minnesota. The study enrolled children aged 3 to 7 years with externalizing behavior problems rated above the clinically significant range (I score ≥120; T score ≥60) on the Eyberg Child Behavior Inventory (ECBI). Interventions Twelve weekly sessions of parent-child interaction therapy (PCIT) (treatment as usual [TAU] arm) vs artificial intelligence (AI)–enhanced PCIT augmented with real-time behavioral outburst alerts (PCIT-AI arm). Main Outcomes and Measures The primary outcome was achieving the a priori feasibility benchmark set at greater than 70% for both completion of PCIT sessions and daily smartwatch wear. Parental reaction time to behavior prompts was measured in seconds. Secondary outcomes were percentage changes in ECBI and Pediatric Sleep Questionnaire scores. Behavioral outburst duration was examined based on parental logs of start and end times of observed tantrums using a smartphone application. Result This study enrolled 50 children (median [IQR] age, 5.0 [4.0-6.0] years; 34 [68%] male and 16 [32%] female; 28 randomized to the PCIT-AI arm and 22 to the PCIT-TAU arm). Of these children, 37 (74%; 21 in the PCIT-AI arm and 16 in the PCIT-TAU arm) completed PCIT, with children wearing the watch a median (IQR) 75.7% (67.8%-82.9%) of the time, thus achieving the feasibility benchmark (primary outcome). Median (IQR) response time to behavior prompts in the PCIT-AI arm was 3.65 (2.07-7.08) seconds. Assessing between-group differences, there was no statistically significantly greater numerical improvement in ECBI-intensity percentage change (13.86%; 95% CI, −1.41% to 29.14%), ECBI-problem percentage change subscale scores (38.59%; 95% CI, −1.22% to 78.40%), or absolute change in Pediatric Sleep Questionnaire scores (−0.16; 95% CI, −1.85 to 1.53) with the PCIT-AI arm than with the PCIT-TAU arm. Children in the PCIT-AI arm had significantly shorter mean (SD) tantrum durations (10.4 [20.8] minutes vs 22.1 [30.0] minutes; P < .001) and lower odds of tantrums lasting for 15 minutes or more (odds ratio, 3.66; 95% CI, 2.72-4.95). Conclusions and Relevance In this randomized clinical trial, both recruitment and technology feasibility benchmarks were achieved. The findings inform the design of fully powered efficacy study of wearable, digitally augmented PCIT for children with disruptive behaviors. Trial Registration ClinicalTrials.gov Identifier: NCT05077722

ImportanceBurnout remains prevalent among physicians and can negatively affect quality, safety, and cost of patient care. Few randomized studies on interventions to address burnout have been conducted to date.ObjectiveTo determine whether wearing a smartwatch and having access to its physiological data (eg, sleep, step count, and heart rate) improves physician well-being (and if so, which dimensions of well-being).Design, Setting, and ParticipantsThis randomized clinical trial included physicians at 2 US medical centers (Mayo Clinic and the University of Colorado School of Medicine) who volunteered to wear a provided smartwatch beginning June 7, 2023. The study concluded on June 27, 2024.InterventionSix months of wearing a smartwatch.Main Outcomes and MeasuresBurnout, resilience, quality of life, depressive symptoms, stress, and sleepiness were measured using validated scales. Participants completed electronic surveys at baseline and 3, 6, 9, and 12 months. An intention-to-treat analysis was conducted.ResultsThis study included 184 physicians (mean [SD] age, 37.5 [9.3] years; 107 females [58.8%]). A total of 83 of 183 physicians (45.4%) were residents or fellows, 103 of 184 (56.0%) lived in Colorado, and 99 of 182 (54.4%) worked in non–primary care settings. Baseline levels of well-being across the measured dimensions were similar for the 2 study arms. At 6 months, 35 of 85 physicians (41.2%) in the intervention arm had burnout compared with 46 of 91 (50.5%) in the control arm (P = .21). Mean (SD) resilience scores at 6 months were 31.9 (5.0) and 29.5 (6.2) among physicians in the intervention and control arms, respectively (P = .01). In multivariable analysis adjusting for baseline score, demographics, specialty, and work hours, the prevalence of burnout was lower (odds ratio, 0.46 [95% CI, 0.21-0.99]; P = .046) and mean resilience score was higher (parameter estimate [scale, 0-40], 1.20 points [95% CI, 0.11-2.28 points]; P = .03; Cohen d = 0.17) among physicians in the intervention arm vs the control arm after 6 months.Conclusions and RelevanceIn this randomized clinical trial to evaluate the effect of wearing a smartwatch and having access to its physiological data on physician well-being, physicians who wore a smartwatch experienced improvements in burnout and resilience. Future research should explore whether engagement with smartwatch data leads to actual behavior change (eg, adaptive coping or reflective habits) that reduces burnout risk and enhances resilience.Trial RegistrationClinicalTrials.gov Identifier: NCT05463250

ABSTRACT Adherence in digital health studies with extended observation periods (≥ 12 months) is limited, and participant retention considerably reduces with time. The US Food and Drug Administration has issued guidelines for improving participant engagement, adherence, and diversity in digital health studies combined with decentralized procedures. A decentralized digital health study on well‐being was designed with protocolized procedures to study the feasibility of participant engagement and technology support to facilitate adherence (wearing the smartwatch ≥ 70% of time) sustained over a 12‐month period. At the end of the study, participants were asked about their ease of participation and free‐response questions about how wearing the smartwatches impacted their physical wellness. An inductive thematic analysis (ITA) was performed to assess themes of those responses and association with adherence. A total of 298 participants were recruited between 2022 and 2023 ( n = 129 in Cohort A in October 22, n = 169 in Cohort B in April 23), with 23% non‐white participants accrued. Among the 298 participants accrued, 273 (92% of accrued participants) completed the 12‐month study with an average overall adherence of 77.4% (SD = 32.64) wear‐time across 12 months. Median adherence of participants whose responses exemplified an ITA theme encompassing perceived behavior changes in sleep and physical activity was higher than those who did not have a response exemplifying that theme. Conversely, those expressing perceived discomfort or intrusiveness of the smartwatch had a statistically lower adherence. These results highlight the crucial roles of technology support and robust engagement efforts to enable sustained adherence over extended follow‐up periods in decentralized digital health studies.