College Students’ Attitudes About Mental Health-Related Content in Mobile Apps

Palmer, Kathleen; Henderson, Samantha

doi:10.1007/s41347-019-00102-0

Cited by 8 publications

(3 citation statements)

References 24 publications

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“…In addition, most young adults are likely students and fresh workers who may not be able to afford high cost of subscription. This aligns with evidence that most students download free mental health apps [61]. Furthermore, people in low-income countries will have difficulty subscribing due to financial constraints.…”

Section: ) App Developers Should Offer Low-cost Subscription Plans Asupporting

confidence: 76%

“…Research has shown that most people download and use free mental health apps [61]. In addition, commercial developers of mental health apps offering direct-to-consumer services have difficulty acquiring enough users and sustaining their business in both short and long-term [62], [63].…”

Section: ) Billing Issuesmentioning

confidence: 99%

“…iv. Free content: Most people install mental health apps because they offer free content [61]. Also, most users want to engage with the content first before making a decision to purchase or not, hence the term "free always wins" [66].…”

Section: ) Content Of Apps Should Be Of High Quality Complete Accementioning

confidence: 99%

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Using Machine Learning and Thematic Analysis Methods to Evaluate Mental Health Apps Based on User Reviews

2020

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The proliferation of smartphones has led to an increase in mobile health (mHealth) apps over the years. Thus, it is imperative to evaluate these apps by identifying shortcomings or barriers hampering effective delivery of intended services. In this paper, we evaluate 104 mental health apps on Google Play and App Store by performing sentiment analysis of 88125 user reviews using machine learning (ML), and then conducting thematic analysis on the reviews. We implement and compare the performance of five classifiers using supervised ML algorithms that are widely used for solving classification problems. The best performing classifier, with F1-score of 89.42%, was then used in predicting the sentiment polarity of reviews. Next, we conduct a thematic analysis of positive and negative reviews to identify themes representing various factors affecting the effectiveness of mental health apps positively and negatively. Our results uncover 21 negative themes and 29 positive themes. The negative themes fall under the following categories: usability issues, content issues, ethical issues, customer support issues, and billing issues. Some of the positive themes include aesthetically pleasing interface, app stability, customizability, high-quality content, content variation/diversity, personalized content, privacy and security, and low-subscription cost. Finally, we offer design recommendations on how the identified negative factors can be tackled to improve the effectiveness of mental health apps.

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Section: ) App Developers Should Offer Low-cost Subscription Plans Asupporting

confidence: 76%

Section: ) Billing Issuesmentioning

confidence: 99%