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Stakeholders’ perceptions on potential barriers and facilitators of implementing technology based on Artificial Intelligence for predicting and preventing mental illness among young adults: – a qualitative study applying the NASSS framework
Halmstad University, School of Health and Welfare. (CAISR Center for Applied Intelligent System Research)
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Stakeholders’ perceptions on potential barriers and facilitators of implementing technology based on Artificial Intelligence for predicting and preventing mental illness among young adults : – a qualitative study applying the NASSS framework (English)
Abstract [en]

Mental illness is increasing among young adults, and AI-based technology holds the potential to address this by identifying early signs and predicting individuals at risk. Early prediction enables timely, preventive interventions.The use of AI-based technology offers a new possibility to define health and lifestyle as ongoing processes, supported by predictive tools and preventive interventions. Seeking input from healthcare stakeholders is essential to comprehend AI-based technology´s potential applications and facilitating its effective implementation. The aim of this study was to explore stakeholders’ perceptions of implementing AI-based technology for predicting and preventing mental illness among young adults, focusing on barriers and facilitators based on the NASSS framework.  The study collected data through semi-structured interviews with 13 key stakeholders linked to mental healthcare for young adults. The analysis was made with qualitative content analysis with an abductive approach, , with the NASSS framework as the theoretical basis. The findings identified 17 facilitators and 15 barriers. Barriers included resistance to adoption due to Ai-based technologies' perceived inability to replace human expertise, concerns about data bias, and uncertainty related to laws and regulations. Facilitators included implementing pilot projects within innovative organisations led by strategic leadership and creating digital entry points for AI-based technology-supported preventive interventions.

Abstract [sv]

Psykisk ohälsa ökar bland unga vuxna, och AI-baserad teknik har potential att bemöta denna utveckling genom att identifiera tidiga tecken på psykisk ohälsa och förutsäga vilka individer som är i riskzonen. Tidig prediktion möjliggör tidig preventiv intervention. Forskning indikerar att användning av AI-baserad teknik ger en ny möjlighet att beskriva hälsa och livsstil som pågående processer, stödda av prediktiva verktyg och preventiva åtgärder. För att förstå potentiella tillämpningarna av AI-baserad teknologi och underlätta dess implementering är det viktigt att utforska perspektiven hos intressenter inom hälso- och sjukvården. Syftet med denna studie var att utforska intressenters uppfattningar om att implementera AI-baserad teknik för att förutsäga och förebygga psykisk ohälsa bland unga vuxna, med fokus på barriärer och underlättande faktorer baserat på NASSS-ramverket. Tretton semistrukturerade intervjuer med nyckelintressenter inom hälso- och sjukvården genomfördes.. Analysen genomfördes med abduktiv kvalitativ innehållsanalys, med NASSS-ramverket som teoretisk grund. Resultatet identifierade 15 barriärer och 17 underlättande faktorer för implementeringen. Barriärer var motstånd till tekniken utifrån att den inte kan ersätta mänsklig kompetens, risk för snedvridning av data samt lagar och regelverk skapar osäkerhet. Underlättande faktorer var att genomföra pilotprojekt inom innovativa organisationer med ett strategiskt ledarskap, samt skapa digitala ingångar för preventiva interventioner med AI-baserad teknologi.

Place, publisher, year, edition, pages
2023. , p. 55
Keywords [en]
Artificial Intelligence, Healthcare, Implementation, Mental Illness, Prediction, Prevention, Young Adults
Keywords [sv]
Artificiell Intelligens, Hälso- och sjukvård, Implementering, Psykisk ohälsa, Prediktion, Prevention, Unga vuxna
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
URN: urn:nbn:se:hh:diva-52091OAI: oai:DiVA.org:hh-52091DiVA, id: diva2:1813835
External cooperation
Region Halland
Subject / course
Health and lifestyle
Educational program
Master's Programme in Health and Lifestyle, 120 credits
Supervisors
Examiners
Part of project
Implementing Artificial Intelligence (AI): Exploring how AI changes information and knowledge practices in healthcare, Swedish Research CouncilAvailable from: 2023-12-01 Created: 2023-11-22 Last updated: 2023-12-01Bibliographically approved

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CiteExportLink to record
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