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Exploring the Role of Mobile Apps for Insomnia in Depression: Systematic Review
Yi-Hang Chiu1,2, Yen-Fen Lee3, Huang-Li Lin4,5
1Department of Psychiatry, Wan Fang Hospital, Taipei Medical University, Taipei City, Taiwan.
Journal of Medical Internet Research
|October 18, 2024
Summary
Mobile apps using artificial intelligence (AI), especially chatbots, show promise in treating depression and insomnia. These AI-driven tools offer accessible, cost-effective mental health support, improving sleep and mood.
Area of Science:
- Mental Health Technology
- Digital Therapeutics
- Artificial Intelligence in Healthcare
Background:
- The COVID-19 pandemic exacerbated mental health issues, increasing depression and insomnia rates.
- Mobile applications, enhanced by AI, offer novel solutions for mental health support.
- Existing reviews often address depression and insomnia separately, necessitating a combined evaluation.
Purpose of the Study:
- To systematically review and evaluate mobile applications for depression and insomnia.
- To identify features, effectiveness, and research gaps in current digital mental health tools.
- To highlight the role of AI and deep learning in mobile health interventions.
Main Methods:
- Systematic literature search of PubMed, Scopus, and Web of Science (2017-2023).
- Inclusion criteria: mobile apps for depression and insomnia, adult/young participants, efficacy data.
- Duplicate screening and data extraction with risk of bias assessment.
Main Results:
- 18 full-text articles were analyzed from an initial 383 studies.
- Mobile apps were used for early detection, assessment, screening, counseling, and Cognitive Behavioral Therapy (CBT).
- Chatbots showed significant efficacy in improving depression symptoms and were explored as alternative interventions for depression and sleep.
Conclusions:
- AI and deep learning, particularly in chatbots, offer personalized and effective mental health support.
- Mobile apps provide accessible, cost-effective alternatives to traditional therapies for depression and insomnia.
- Features like NLP, machine learning, and generative dialogue enhance user interaction and therapeutic outcomes.
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