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Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

Sheik Mohammad Roushdat Ally Elaheebocus1,2, Mark Weal1, Leanne Morrison3

  • 1School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom.

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|February 24, 2018
PubMed
Summary

Social media features in digital behavior change interventions (DBCIs) show promise, but clear design principles are lacking. This review presents a taxonomy to guide the development and evaluation of social media in DBCIs.

Keywords:
behavior controlbehavioral medicineeHealthhealth behaviorsocial mediasystematic review

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Area of Science:

  • Digital Health
  • Behavioral Science
  • Public Health Interventions

Background:

  • Social media features are increasingly integrated into digital behavior change interventions (DBCIs).
  • A significant gap exists in clear design principles for utilizing these features effectively in behavioral interventions.
  • This limitation hinders cross-study comparisons and understanding of their impact.

Purpose of the Study:

  • To systematically review DBCIs incorporating social media features targeting modifiable behavioral risk factors.
  • To present a novel taxonomy of social media features for use in behavioral interventions.
  • To inform the development, description, and evaluation of DBCIs.

Main Methods:

  • A systematic literature search was conducted across 8 databases.
  • Studies targeting tobacco smoking, diet, physical activity, or alcohol consumption were identified.
  • Screening and review were performed by two independent researchers.

Main Results:

  • 134 studies were included in the review, with 70% reporting positive outcomes.
  • A taxonomy of 36 social media features, organized into 7 categories, was developed.
  • Few studies reported on the direct association between social media features and intervention effectiveness.

Conclusions:

  • Social media features are common in DBCIs, yet their specific impact on outcomes remains under-researched.
  • A lack of guidance exists for selecting appropriate social media features for different behavioral targets.
  • The proposed taxonomy and recommendations aim to support future research, improve reporting, and facilitate cross-study evaluations.