Self‐regulatory control processes in youths: A temporal network analysis approach

Abstract Objective This study aimed to better understand the temporal interrelationships among self‐control, response inhibition, and anger (i.e., momentary state and rumination) on both the within‐ and between‐person levels in male adolescents. Method We applied temporal network analyses among 62 male adolescents with a wide range of behavioral difficulties. Self‐control, momentary anger, and anger rumination were mapped by self‐report measures, whereas we measured response inhibition through an ambulatory Go/No‐go task (two measures a day—morning and afternoon—over a 9‐day period). Results Temporal network analysis, at the within‐person level, revealed that morning measures of response inhibition, anger rumination, and self‐control were related to the corresponding measure in the afternoon. More efficient response inhibition in the morning was associated with higher self‐control in the afternoon. Higher anger rumination in the morning led to higher momentary anger in the afternoon. In a concurrent within‐person network, higher momentary anger was reciprocally associated with lower self‐control. At the between‐person level, higher momentary anger was correlated to higher anger rumination, lower response inhibition, and lower self‐control. Discussion This study provides insight into the dynamic interactions among self‐control, response inhibition, and anger (momentary state and rumination) in male adolescents, advancing the understanding of self‐regulatory control functioning

A Template and Tutorial for Preregistering Studies Using Passive Smartphone Measures

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures

A Template and Tutorial for Preregistering Studies Using Passive Smartphone Measures

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers are faced with multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Here we propose a preregistration template that is easy to use and understandable for researchers