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Adolescent Engagement With a Multicomponent mHealth Tool: Identifying Usage Patterns, Determinants, and Health

Carmen Peuters1,2,3, Ann DeSmet4,5, Laura Maenhout2

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Summary

Adolescents showed varied engagement styles with the mobile health (mHealth) intervention #LIFEGOALS, but no single style significantly improved health behaviors. Tailoring interventions to individual characteristics is recommended for better adolescent engagement.

Keywords:
activity trackeradolescentsbehavior changebehavioral engagementcluster analysisengagementexperiential engagementgamificationlaw of attritionlogistic regressionmobile healthmobile phonemulticomponent interventionssleep qualitysupport chatbotsystem log datatailoring digital health interventionsteensunstructured appsyouth

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Area of Science:

  • Adolescent Health
  • Digital Health Interventions
  • Behavioral Science

Background:

  • Limited research exists on adolescent engagement with mobile health (mHealth) interventions.
  • Adolescent engagement is widely assumed to influence the effectiveness of mHealth interventions.

Purpose of the Study:

  • To investigate adolescent engagement patterns with the #LIFEGOALS mHealth intervention.
  • To identify distinct adolescent engagement styles and their correlation with personal characteristics.
  • To determine if specific engagement styles predict changes in health behaviors.

Main Methods:

  • 159 adolescents participated in a 12-week mHealth intervention (#LIFEGOALS) promoting healthy behaviors and mental health.
  • Usage data and self-reports were collected to analyze behavioral and experiential engagement.
  • Exploratory cluster analysis identified engagement styles, and regression models assessed their impact on behavior change.

Main Results:

  • Adolescent engagement with the mHealth intervention decreased significantly after the first week.
  • Four distinct engagement styles were identified: narrative, app, activity tracker (Fitbit), and no usage.
  • Engagement styles did not significantly predict changes in health behavior outcomes.

Conclusions:

  • Adolescent engagement with mHealth interventions varies, with distinct styles identified.
  • Tailoring mHealth interventions to individual, interpersonal, and contextual factors is crucial.
  • Low overall engagement may have limited the detection of significant health effects across different engagement styles.