An Interdisciplinary Study on Generative AI: Exploring Its Efficacy in Mental Health Interventions within the Gaming Ecosystem
DOI:
https://doi.org/10.14738/bjhmr.104.15114Keywords:
Generative artificial intelligence, Gaming, Serious Games, e-health, eHealth, Healthtech, Mental health, OpenAI, ChatGPT, Google Brain, IBM Watson, Google Bard, Deepmind, Health Informatics, digital therapeuticsAbstract
The integration of generative artificial intelligence with game mechanics in e-health innovations holds promise for addressing mental health challenges. However, the extent to which this inter-section can provide effective, applicable, and safe interventions remains unclear. In this regard, this paper evaluates the effectiveness, usability, and benefits of integrating generative AI and gaming in e-health innovations for mental well-being. (1) Background: Through a multidisciplinary approach and the utilisation of secondary sources drawn from various disciplines like healthcare, psychology, and computer science, the study seeks a comprehensive understanding of the study topic. Findings show that the integration of generative AI with game mechanics in mental health interventions offers effective and engaging interventions, fostering emotional connection, therapeutic outcomes, and usability. However, ethical considerations, content filtering, and data privacy issues should be addressed for safe implementation. (2) Methods: Through a multidisciplinary approach with regard to theory triangulation, investigator triangulation, and utilisation of secondary sources drawn from various disciplines like healthcare, psychology, computer science, and databases such as PubMed, Science Direct, and BMC Public Health, the study seeks a comprehensive understanding of the study topic. Numerous quantified sources published on or after 2020 were investigated for design triangulation in terms of determinants, indicators, and deductive rigour in the formation of search terms. (3) Results: The thematic analysis shows that the integration of generative AI with game mechanics in mental health interventions offers effective and engaging interventions, fostering emotional connection, therapeutic outcomes, and usability. However, ethical considerations, content filtering, and data privacy issues should be addressed for safe implementation. (4) Conclusions: Generative AI-driven game mechanics interventions have illustrated significant increases in emotional connection, engagement, and therapeutic outcomes in mental health interventions. Particularly, the increased emotional connection, engagement, and positive therapeutic outcomes associated with generative AI-powered game mechanics enhance the quality of service delivery to people with mental health as the enjoyment and motivation of playing games increase the effectiveness and acceptance of AI in the healthcare environment.
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