Utility of temporal self-regulation theory in health and social behaviours: A meta-analysis

PurposeTemporal self-regulation theory was developed to address an observed intention-behaviour gap across behaviours. However, a synthesis of studies has not yet been conducted to investigate the theory's utility to explain behaviour and bridge the intention-behaviour gap. This review aimed to evaluate the predictive ability of temporal self-regulation theory to understanding behaviour and pre-registered at PROSPERO (ID: CRD42021253174). MethodForward citation searches on the original theory publication through Google Scholar until May 2021 identified 37 eligible articles, including, 12,555 participants assessing at least two of the three theory constructs. Random-effects meta-analyses assessed the strength of associations between theory constructs on behaviour and random effects meta-regressions assessed moderators of behaviour. ResultsFindings provide support for temporal self-regulation theory to explain behaviour with very weak (self-regulatory capacity r = .039, CI = .00, -.07) to moderate (intention r = .331, CI = .26, .40; behavioural pre-potency r = .379, CI = .32, .44) effect sizes. Further, the strength of associations varied across behaviour types and contexts. However, there was high heterogeneity across studies and some moderating effects could not be assessed due to insufficient numbers of studies assessing interactions. ConclusionsWe urge researchers to assess and report interactions for better understanding of the drivers of behaviour to develop effective interventions for positive behaviour change.

Automated summary

This review aimed to evaluate the predictive ability of temporal self-regulation theory to understand behavior. The findings suggest that the theory can explain behavior, although the effect sizes vary from weak to moderate. The strength of associations also varies across different behavior types and contexts. The study highlights the importance of assessing and reporting interactions to better understand the drivers of behavior and develop effective interventions.