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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Apr 16, 2021
Date Accepted: Jun 11, 2021

The final, peer-reviewed published version of this preprint can be found here:

Popular Evidence-Based Commercial Mental Health Apps: Analysis of Engagement, Functionality, Aesthetics, and Information Quality

Lau N, O'Daffer A, Yi-Frazier JP, Rosenberg AR

Popular Evidence-Based Commercial Mental Health Apps: Analysis of Engagement, Functionality, Aesthetics, and Information Quality

JMIR Mhealth Uhealth 2021;9(7):e29689

DOI: 10.2196/29689

PMID: 34259639

PMCID: 8319777

Popular Evidence-Based Commercial Mental Health Apps: An Analysis of Engagement, Functionality, Aesthetics, and Information Quality

  • Nancy Lau; 
  • Alison O'Daffer; 
  • Joyce P Yi-Frazier; 
  • Abby R Rosenberg

ABSTRACT

Background:

The mHealth for mental health consumer market is oversaturated and under-regulated, and consumers endorse interest in evidence-based apps.

Objective:

The aim of this study was to evaluate the quality of apps that are successful across both research and consumer sectors. We conducted a user-centered design analysis of popular consumer apps with scientific backing utilizing the well-validated Mobile Application Ratings Scale (MARS).

Methods:

Included apps were popular consumer apps with research support identified via a systematic search of the App Store iOS (Apple Inc) and Google Play (Google LLC) and literature review. We evaluated the quality metrics of 19 mental health apps along four MARS subscales: engagement, functionality, aesthetics, and information quality. MARS total and subscale scores range from 1 to 5, with higher scores representing better quality. We calculated Pearson correlation coefficients to identify associations between MARS scores, App Store iOS/Google Play consumer ratings, and number of evidence-based treatment components.

Results:

The mean MARS score was M = 3.52 (SD = 0.71), consumer rating was M = 4.22 (SD = 0.54), and number of evidence-based treatment components was M = 2.32 (SD = 1.42). Consumer ratings were significantly correlated with the MARS functionality subscale (r = 0.74, p < .001), aesthetics subscale (r = 0.70, p <.01), and total score (r = 0.58, p = .01). Number of evidence-based intervention components was not associated with MARS scores (r = 0.085, p = .73) or consumer ratings (r = -.329, p = .169).

Conclusions:

In our analysis of popular research-supported consumer apps, objective app quality and subjective consumer ratings were generally high. App functionality and aesthetics were highly consistent with consumer appeal; evidence-based components were not. In addition to designing treatments that work, we recommend that researchers prioritize aspects of app design (e.g., ease of use, navigation, visual appeal) that impact the user experience for engagement and sustainability. This will help translate evidence-based interventions to the competitive consumer app market, thus bridging the gap between research development and real-world implementation.


 Citation

Please cite as:

Lau N, O'Daffer A, Yi-Frazier JP, Rosenberg AR

Popular Evidence-Based Commercial Mental Health Apps: Analysis of Engagement, Functionality, Aesthetics, and Information Quality

JMIR Mhealth Uhealth 2021;9(7):e29689

DOI: 10.2196/29689

PMID: 34259639

PMCID: 8319777

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