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Mapping the Process of Engagement With Digital Health Interventions: A Cross-Case Synthesis.

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Summary

This study maps engagement components in digital health interventions. Findings reveal interactions between affective, cognitive, and behavioral elements, offering a framework to enhance intervention design and impact.

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Area of Science:

  • Digital health interventions
  • Human-computer interaction
  • Behavioral science

Background:

  • Engagement is crucial for digital health intervention success.
  • Understanding affective, cognitive, and behavioral engagement components is key.
  • Existing models may not fully capture engagement dynamics.

Purpose of the Study:

  • To map associations between affective, cognitive, and behavioral engagement components.
  • To develop a framework for improving digital health intervention design and impact.
  • To compare empirical findings with a hypothesized engagement model.

Main Methods:

  • Exploratory multiple case study design.
  • Examined three digital health interventions: childhood obesity app, mental health chatbot, and post-surgical assessment tool.
  • Qualitative data from semi-structured interviews analyzed using codebook thematic analysis.

Main Results:

  • Close associations observed between affective, cognitive, and behavioral engagement components.
  • Empirical engagement patterns emerged but differed from the hypothesized model.
  • The order of influence between cognitive and affective engagement varied from literature.

Conclusions:

  • Understanding engagement component interactions is vital for intervention optimization.
  • The proposed framework offers guidance for supporting engagement.
  • Further research is needed on component order and feature influence for enhanced clinical impact.