Assessing the Effectiveness of ChatGPT in Delivering Mental Health Support: A Qualitative Study
Open accessAbstract
Background: Artificial Intelligence (AI) applications are widely researched for their potential in effectively improving the healthcare operations and disease management. However, the research trend shows that these applications also have significant negative implications on the service delivery. Purpose: To assess the use of ChatGPT for mental health support. Methods: Due to the novelty and unfamiliarity of the ChatGPT technology, a quasi-experimental design was chosen for this study. Outpatients from a public hospital were included in the sample. A two-week experiment followed by semi-structured interviews was conducted in which participants used ChatGPT for mental health support. Semi-structured interviews were conducted with 24 individuals with mental health conditions. Results: Eight positive factors (psychoeducation, emotional support, goal setting and motivation, referral and resource information, self-assessment and monitoring, cognitive behavioral therapy, crisis interventions, and psychotherapeutic exercises) and four negative factors (ethical and legal considerations, accuracy and reliability, limited assessment capabilities, and cultural and linguistic considerations) were associated with the use of ChatGPT for mental health support. Conclusion: It is important to carefully consider the ethical, reliability, accuracy, and legal challenges and develop appropriate strategies to mitigate them in order to ensure safe and effective use of AI-based applications like ChatGPT in mental health support.
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LLM-CBs' constant availability, non-judgmental attitudes, knowledge of psychotherapeutic concepts, and perceived empathy make them appear attractive as mental health support tools, especially in societies with logistical and resource-based limitations in mental health treatment.
“LLM-CBs’ constant availability, non-judgmental attitudes, knowledge of psychotherapeutic concepts, and perceived empathy make them appear as attractive mental health support tools149,150, especially in societies marked by logistical and resource-based limitations in mental health treatment151.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [150]
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Experimental — accuracy not yet measuredQualitative studies published so far include thematic analyses of user forum comments on both generative AI and rule-based DMHIs, student survey responses on companion-focused generative AI chatbots, and semi-structured interviews with hospital outpatients who were asked to try ChatGPT for mental health support.
“Qualitative studies published so far include thematic analyses of user forum comments on both generative AI and rule-based DMHIs23, student survey responses on companion-focused generative AI chatbots48, and semi-structured interviews with hospital outpatients who were asked to try ChatGPT for mental health support49.”
From “It happened to be the perfect thing”: experiences of generative AI chatbots for mental health (2024) · cites this paper as [49]
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- Authors
- Alanezi, F.
- Affiliations
- Imam Abdulrahman Bin Faisal University (SA)
- Corresponding author
- Alanezi, Fahad
- ORCID
- Alanezi, Fahad
- Venue
- Journal of Multidisciplinary Healthcare
- Publisher
- Informa UK Limited
- Published
- 2024-01
- Volume
- Volume 17
- Pages
- 461-471
- ISSN
- 1178-2390 (ISSN-L)
- PMC
- PMC10838501
- OpenAlex
- W4391405701
- Cited by
- 139
- References
- 45
- Citations by year
- 2026: 55 · 2025: 63 · 2024: 21
- FWCI
- 54.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Multidisciplinary Healthcare (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Dove Medical Press (Taylor and Francis Group) (submittedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- ChatGPT, mental health support, artificial intelligence in healthcare, AI chatbots, psychoeducation, emotional support, cognitive behavioral therapy, crisis intervention, legal and ethical considerations, language and cultural barriers, outpatients
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