Self-regulation mechanisms in health behavior change: a systematic meta-review of meta-analyses, 2006–2017

ABSTRACT

Self-regulation is one primary mechanism in interventions for health behavior change and has been examined in numerous recent meta-analyses. This pre-registered meta-review (PROSPERO CRD42017074018) examined Mmeta-analyses of any intervention and health behavior/outcome were eligible if they quantitatively assessed self-regulation and appeared between January 2006 and August 2017. In total, 66 meta-analyses were ultimately eligible; 27% reported a protocol, 11% used GRADE; 58% focused on RCTs. Reviews satisfied only a moderate number of items on the AMSTAR 2 (M = 45.45%, SD = 29.57%). Only 6% of meta-analyses directly examined whether changes in self-regulation predicted the behavior change (i.e., self-efficacy and physical activity, l = 2; frequency of self-monitoring and goal attainment, l = 1; cognitive bias modification and addiction, l = 1). Meta-analyses more routinely assessed self-regulation by comparing the efficacy of intervention components (97%), such as those from behavior change taxonomies. Meta-analyses that focused on intervention components identified several as successful, including personalized feedback, goal setting, and self-monitoring; however, none were consistently successful in that each worked only for some health behaviors and with particular populations. Some components had inconclusive evidence, given that they were only examined in low- quality reviews. Future reviewers should utilize advanced methods to assess mechanisms, and study authors should report hypothesized mechanisms to facilitate synthesis.

KEYWORDS:

• Behavior change techniques
• health
• intervention
• meta-review
• self-regulation

Acknowledgements

This work was supported by the National Institutes of Health (NIH) Science of Behavior Change Common Fund Program through an award administered by the National Institute on Aging (U.S. PHS grant 5U24AG052175). The views presented here are solely the responsibility of the authors, and do not necessarily represent the official views of the NIH. We thank our literature screeners and coders: Emily Betterton, Meiko Howell, Sahar Iqbal, Kiana McDavid, and Lindsay Roethke. We also thank reference librarians for help with creating electronic searches: Louise Falzon and Valerie Banfi. We thank Cleo Protogerou for her thoughtful comments on our manuscript. Finally, we are thankful for the constructive commentary of the editors and the anonymous reviewers.

Disclosure statement

The authors declare that they have no potential conflict of interest.

ORCID

Emily A. Hennessy http://orcid.org/0000-0002-5146-5823

Notes

1 Based on our extraction of the stated aim of each of the reviews (see Table A1), other reviews may have had similar population criteria in place but did not specify these as study inclusion/exclusion criteria.

Additional information

Funding

This work was supported by the National Institutes of Health (NIH) Science of Behavior Change Common Fund Program through an award administered by the National Institute on Aging (U.S. PHS grant 5U24AG052175). The views presented here are solely the responsibility of the authors, and do not necessarily represent the official views of the NIH.