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. 2022 Apr 27:13:857304.
doi: 10.3389/fpsyt.2022.857304. eCollection 2022.

mHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis

Erin Lucy Funnell  1 , Benedetta Spadaro  1 , Nayra Martin-Key  1 , Tim Metcalfe  2 , Sabine Bahn  1
Affiliations

mHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis

Erin Lucy Funnell et al. Front Psychiatry. .

Abstract

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

Keywords: app reviews; app users; digital health; mHealth; mental health; sentiment analysis; thematic analysis.

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Conflict of interest statement

SB is a director of Psynova Neurotech Ltd and Psyomics Ltd. SB has financial interests in Psyomics Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
PRISMA flow chart of included apps and reviews. Key. MIND, Mobile Health Index and Navigation Database.
Figure 2
Figure 2
Number of apps excluded within a given exclusion category (n = 1,286). Key. CBT, cognitive behavioral therapy.
Figure 3
Figure 3
Apps by number of conditions assessed (N = 92).
Figure 4
Figure 4
Frequencies of different sentiments of the reviews included in the sentiment analysis dataset (n = 676).
Figure 5
Figure 5
Frequencies of different themes identified in the thematic analysis (n = 558).
See this image and copyright information in PMC

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