The utility of behavioral biometrics in user authentication and demographic characteristic detection: a scoping review.

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 ).

Early-stage studies to larger-scale trials: investigators' perspectives on scaling-up childhood obesity interventions.

BACKGROUND: Pilot/feasibility studies play an important role in the development and refinement of behavioral interventions by providing information about feasibility, acceptability, and potential efficacy. Despite their importance and wide-spread use, the approaches taken by behavioral scientists to scale-up early-stage studies to larger-scale trials has received little attention. The aim of our study was to understand the role that pilot studies play in the development and execution of larger-scale trials. METHODS: We conducted interviews with childhood obesity researchers who had published pilot behavioral interventions and larger-scale trials of the same or similar interventions. Questions were asked about the role of pilot studies in developing larger-scale trials and the challenges encountered when scaling-up an intervention based upon pilot findings. Data were coded and analyzed using an inductive analytic approach to identify themes. RESULTS: Twenty-four interventionists (54% women, 37-70 years old, mean 20 years since terminal degree) completed a total of 148 pilot studies across their careers (mean 6.4, range 1-20), of which 59% were scaled-up. Scaling was described as resource intensive and pilot work was considered essential to successfully competing for funding by 63% of the sample (n = 15). When asked to define a high-quality pilot study, interventionists described studies that allowed them to evaluate two independent factors: components of their intervention (e.g., acceptability, feasibility) and study parameters (e.g., sample size, measures). Interventionists expressed that more process implementation measures, different study designs, and additional iterations could improve decisions to scale-up. Most agreed that pilot studies were likely to produce inflated estimates of potential efficacy though only nine interventionists provided potential solutions for decreasing inflated measures of efficacy. Suggested major causes of inflated effects included high levels of oversight in pilot studies (e.g., researcher support), reliance on subjective measures, and utilizing convenience or highly motivated samples. Potential solutions included designing pilots for real-world implementation, only conducting randomized controlled pilot studies, and pre-registering pilot studies. CONCLUSIONS: Pilot studies purposes are multifaceted and deemed essential to obtaining funding for larger-scale trials. Clarifying the form and function of preliminary, early-stage research may enhance the productive utilization of early-stage studies and reduced drops in efficacy when transitioning to larger scale studies.