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Related Experiment Videos

Proportionate methods for evaluating a simple digital mental health tool.

E Bethan Davies1,2,3, Michael P Craven1,3,4, Jennifer L Martin1,2,3

  • 1NIHR MindTech Healthcare Technology Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.

Evidence-Based Mental Health
|October 11, 2017
PubMed
Summary
This summary is machine-generated.

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Evaluating mobile health (mHealth) tools requires new methods. Combining app analytics and user feedback offers a practical way to assess the impact of mental well-being apps on users.

Area of Science:

  • Digital health evaluation methodologies
  • Mobile health (mHealth) technology assessment
  • Mental well-being digital interventions

Background:

  • Traditional evaluation methods struggle to keep pace with rapid advancements in mobile health (mHealth).
  • There is a need for flexible methodologies to evaluate mHealth technologies, especially simple, self-help tools.
  • Combining diverse methods and data provides a comprehensive understanding of technology use and user impact.

Purpose of the Study:

  • To demonstrate a triangulated approach using analytical data and user feedback for evaluating a mental well-being smartphone app.
  • To showcase a proportionate and practical evaluation strategy for mHealth tools.
  • To assess the effectiveness and user perception of the 'In Hand' mental well-being app.

Main Methods:

Keywords:
mental health

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  • A three-part data collection process was employed: app analytics, an online user survey, and user interviews.
  • App analytics tracked user engagement metrics.
  • User surveys and interviews gathered qualitative and quantitative feedback on perceived helpfulness and impact.

Main Results:

  • Over 50% of user sessions were classified as 'meaningful engagement' based on analytics.
  • A user survey (n=108) indicated that the 'In Hand' app was perceived as beneficial for various aspects of mental well-being.
  • Interviews (n=8) provided nuanced insights into users' understanding of the app's positive effects.

Conclusions:

  • Combining multiple evaluation methods provides a realistic assessment of self-help digital tools.
  • Triangulation of data offers insights into app usage patterns and their impact on user well-being.
  • This evaluation approach is valuable for healthcare professionals and commissioners recommending digital well-being tools.