A meta-analysis of self-regulation and digital recreation from birth to adolescence

There is good reason to implicate self-regulation in our digital recreation duration, choices, and behaviours. However, the direction, degree, and diversity of their association is unclear. To offer more robust and nuanced evidence to this issue of acute public concern, the current study presents a comprehensive meta-analysis of the associations between self-regulation and digital recreation from birth to adolescence – consolidating 183 studies reporting 232 associations from 234,476 children and adolescents. Across these studies, digital recreation clustered into investigations of screen time, features of problematic digital engagement, exposure to violent content, communicating with strangers online, sexting, and media multitasking. Although a pattern of negative bivariate associations was observed between self-regulation and aspects of digital recreation, the strength of association for screen time was weak ( r = −.04 for computer use to r = −.15 for social media use). Once control variables were considered, relationships with exposure to violent digital content were rendered similarly trivial, suggesting other variables likely account for these correlations. This reduces our confidence in these associations. In contrast, lower self-regulation was more highly associated with problematic engagement ( r = −.28 for problematic gaming to r = −.41 for problematic mobile phone use), communicating with strangers online ( r = −.18), and sexting ( r = −.20). This pattern of results points to a relationship that is variable by type of digital activity, which in our meta-analyses ranged from null to strong and negative. Where a relationship exists, it may be bi-directional given associations remained for longitudinal studies that positioned either self-regulation or digital recreation as predictor. Most moderators of these associations were non-significant, although the negative association of self-regulation with time spent gaming was increasingly strong with increasing participant age. This study instigates a disentangling of the nature of the relationship between self-regulation and digital choices and behaviours across the early stages of life. • We identified 183 eligible studies to meta-analyse associations of self-regulation with digital recreation. • Self-regulation was most studied in relation to digital recreation time and features of problematic digital engagement. • Associations of self-regulation with digital recreation time were small, implying low explanatory utility. • Self-regulation was more highly associated with problematic digital recreation. • Associations were mostly unmoderated by age, design, risk of bias, or measurement method.

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Publication Details

Journal
Computers in Human Behavior
Published
2024-10-20
DOI
https://doi.org/10.1016/j.chb.2024.108472
Citations
9
Primary Topic
Impact of Technology on Adolescents
Type
article
Field-Weighted Citation Impact
10.19
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article

A meta-analysis of self-regulation and digital recreation from birth to adolescence

Sumudu Mallawaarachchi, Daniel Johnson, Steven James Howard, Laura Bentley et al.
9 citations
Computers in Human Behavior
Impact of Technology on Adolescents
10.19
article

A meta-analysis of self-regulation and digital recreation from birth to adolescence

Sumudu Mallawaarachchi, Daniel Johnson, Steven James Howard, Laura Bentley, Nicole Hayes, Sonia White, Janelle Mackenzie, Cathrine Neilsen‐Hewett
article en
9 citations

Abstract

There is good reason to implicate self-regulation in our digital recreation duration, choices, and behaviours. However, the direction, degree, and diversity of their association is unclear. To offer more robust and nuanced evidence to this issue of acute public concern, the current study presents a comprehensive meta-analysis of the associations between self-regulation and digital recreation from birth to adolescence – consolidating 183 studies reporting 232 associations from 234,476 children and adolescents. Across these studies, digital recreation clustered into investigations of screen time, features of problematic digital engagement, exposure to violent content, communicating with strangers online, sexting, and media multitasking. Although a pattern of negative bivariate associations was observed between self-regulation and aspects of digital recreation, the strength of association for screen time was weak ( r = −.04 for computer use to r = −.15 for social media use). Once control variables were considered, relationships with exposure to violent digital content were rendered similarly trivial, suggesting other variables likely account for these correlations. This reduces our confidence in these associations. In contrast, lower self-regulation was more highly associated with problematic engagement ( r = −.28 for problematic gaming to r = −.41 for problematic mobile phone use), communicating with strangers online ( r = −.18), and sexting ( r = −.20). This pattern of results points to a relationship that is variable by type of digital activity, which in our meta-analyses ranged from null to strong and negative. Where a relationship exists, it may be bi-directional given associations remained for longitudinal studies that positioned either self-regulation or digital recreation as predictor. Most moderators of these associations were non-significant, although the negative association of self-regulation with time spent gaming was increasingly strong with increasing participant age. This study instigates a disentangling of the nature of the relationship between self-regulation and digital choices and behaviours across the early stages of life. • We identified 183 eligible studies to meta-analyse associations of self-regulation with digital recreation. • Self-regulation was most studied in relation to digital recreation time and features of problematic digital engagement. • Associations of self-regulation with digital recreation time were small, implying low explanatory utility. • Self-regulation was more highly associated with problematic digital recreation. • Associations were mostly unmoderated by age, design, risk of bias, or measurement method.

Computers in Human BehaviorVol. 163
Australian Research Council (AU), Queensland University of Technology (AU), The University of Queensland (AU), University of Wollongong (AU)
Openalex Percentile: Top 2%
Impact of Technology on Adolescents
10.19
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