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Background: Objective measures of screen time are necessary to better understand the complex relationship between screen time and health outcomes. However, current objective measures of screen time (e.g., passive sensing applications) are limited in identifying the user of the mobile device, a critical limitation in children's screen time research where devices are often shared across a family. Behavioral biometrics, a technology that uses embedded sensors on modern mobile devices to continuously authenticate users, could be used to address this limitation. Objective: The purpose of this scoping review was to summarize the current state of behavioral biometric authentication and synthesize these findings within the scope of applying behavioral biometric technology to screen time measurement. Methods: We systematically searched five databases (Web of Science Core Collection, Inspec in Engineering Village, Applied Science & Technology Source, IEEE Xplore, PubMed), with the last search in September of 2022. Eligible studies were on the authentication of the user or the detection of demographic characteristics (age, gender) using built-in sensors on mobile devices (e.g., smartphone, tablet). Studies were required to use the following methods for authentication: motion behavior, touch, keystroke dynamics, and/or behavior profiling. We extracted study characteristics (sample size, age, gender), data collection methods, data stream, model evaluation metrics, and performance of models, and additionally performed a study quality assessment. Summary characteristics were tabulated and compiled in Excel. We synthesized the extracted information using a narrative approach. Results: Of the 14,179 articles screened, 122 were included in this scoping review. Of the 122 included studies, the most highly used biometric methods were touch gestures (n = 76) and movement (n = 63), with 30 studies using keystroke dynamics and 6 studies using behavior profiling. Of the studies that reported age (47), most were performed exclusively in adult populations (n = 34). The overall study quality was low, with an average score of 5.5/14. Conclusion: The field of behavioral biometrics is limited by the low overall quality of studies. Behavioral biometric technology has the potential to be used in a public health context to address the limitations of current measures of screen time; however, more rigorous research must be performed in child populations first. Systematic review registration: The protocol has been pre-registered in the Open Science Framework database (https://doi.org/10.17605/OSF.IO/92YCT). [ABSTRACT FROM AUTHOR]

Background: Children from low-income families experience accelerated BMI gain and learning loss during summer. Healthy Summer Learners (HSL) addresses accelerated BMI gain and academic learning loss during summer by providing academic- and health-focused programming. This manuscript reports the effects of HSL on underlying obesogenic behaviors (i.e., physical activity, screen time, sleep, diet) that lead to accelerated summer BMI gain, a necessary first step to informing a future randomized controlled trial of HSL. Methods: In the summer of 2018 and 2019 using a quasi-experimental study design, 180 children (90 per summer, 7.9 years [SD = 1.0], 94% non-Hispanic Black, 40% male) at two schools (i.e., one per summer) who were struggling academically (25–75% on a standardized reading test) were provided a free, school-based 6-week health- and academic-focused summer program (i.e., HSL, n = 60), a 4- to 6-week academic-focused summer program (i.e., 21st Century Summer Learning program (21C), n = 60), or no summer program (n = 60). Children wore the Fitbit Charge 2™ over a 10-week period during the summers (June–Aug) of 2018–2019. Differences within (within child days attend vs. not attend) and between (differences between groups attend vs. not attend) were evaluated using mixed effects linear regression. Results: Regression estimates indicated that, on days attending, HSL children experienced a greater reduction in sedentary minutes (− 58.6 [95% CI = − 92.7, − 24.4]) and a greater increase in moderate-to-vigorous physical activity (MVPA) (36.2 [95% CI = 25.1, 47.3]) and steps (2799.2 [95% CI = 2114.2, 3484.2]) compared to 21C children. However, both HSL and 21C children were more active (i.e., greater MVPA, total steps) and less sedentary (i.e., less sedentary minutes and total screen time) and displayed better sleeping patterns (i.e., earlier and less variability in sleep onset and offset) on days they attended than children in the control. Conclusions: HSL produced greater changes in physical activity than 21C. However, attendance at either HSL or 21C leads to more healthy obesogenic behaviors. Based on the behavioral data in this pilot study, a larger trial may be warranted. These results must be considered along with the pending primary outcomes (i.e., academics and BMI z-score) of the HSL pilot to determine if a full-scale trial is warranted. Trial registration: NIH-NCT03321071. Registered 25 October 2017 [ABSTRACT FROM AUTHOR]