Artificial Intelligence in Mental Health Care: A Study of Students’ Perspectives at Helsinki's 3AMK Universities
Parashuram, Manasa (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024120633526
https://urn.fi/URN:NBN:fi:amk-2024120633526
Tiivistelmä
This thesis explores the potential of Artificial Intelligence (AI) to improve mental health support for bachelor students in the Helsinki Metropolitan Area, focusing on the 3AMK universities: Haaga-Helia, Laurea, and Metropolia. With rising mental health issues like anxiety and depression, traditional support services often struggle with accessibility. AI tools such as chatbots and mobile apps offer an immediate, personalized solution. This research examines students' perceptions of AI-based mental health tools, focusing on their effectiveness, usability, and factors influencing adoption.
The study has two main objectives: to assess how students perceive the practicality and effectiveness of AI tools, and to identify barriers and enablers, such as privacy concerns and ease of use. The research is limited to bachelor students from the 3AMK universities of Helsinki and focuses on AI tools specifically Chatbots and Mobile Applications for managing anxiety and depression.
The theoretical framework of the study is grounded in the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and privacy and trust theories, which help explain the factors affecting students' adoption of AI tools. These frameworks examine the role of perceived usefulness, ease of use, social influence, and trust in shaping students' attitudes toward AI applications in mental health care.
A qualitative research approach was employed, using semi-structured interviews with 15 bachelor students. This method provided in-depth insights into students’ experiences and concerns regarding AI-based mental health tools. The data were analyzed using thematic and narrative analysis to identify key themes related to trust, privacy, usability, and perceived effectiveness. The findings reveal a mixed response: students appreciate AI's accessibility and personalization but express concerns about privacy and the lack of human empathy. The study highlights the importance of designing AI tools that are effective, trustworthy, and user-friendly to enhance student engagement.
This research contributes to the growing field of AI in mental health by providing valuable insights into how university students perceive and interact with AI tools. It offers practical recommendations for the development of AI-driven mental health solutions that are tailored to student needs, ensuring that these tools are accessible, ethical, and effective in supporting students' mental well-being.
The study has two main objectives: to assess how students perceive the practicality and effectiveness of AI tools, and to identify barriers and enablers, such as privacy concerns and ease of use. The research is limited to bachelor students from the 3AMK universities of Helsinki and focuses on AI tools specifically Chatbots and Mobile Applications for managing anxiety and depression.
The theoretical framework of the study is grounded in the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and privacy and trust theories, which help explain the factors affecting students' adoption of AI tools. These frameworks examine the role of perceived usefulness, ease of use, social influence, and trust in shaping students' attitudes toward AI applications in mental health care.
A qualitative research approach was employed, using semi-structured interviews with 15 bachelor students. This method provided in-depth insights into students’ experiences and concerns regarding AI-based mental health tools. The data were analyzed using thematic and narrative analysis to identify key themes related to trust, privacy, usability, and perceived effectiveness. The findings reveal a mixed response: students appreciate AI's accessibility and personalization but express concerns about privacy and the lack of human empathy. The study highlights the importance of designing AI tools that are effective, trustworthy, and user-friendly to enhance student engagement.
This research contributes to the growing field of AI in mental health by providing valuable insights into how university students perceive and interact with AI tools. It offers practical recommendations for the development of AI-driven mental health solutions that are tailored to student needs, ensuring that these tools are accessible, ethical, and effective in supporting students' mental well-being.