Artificial Intelligence in Mental Health Practice: Literacy, Perceived Barriers, Benefits, and Adoption Intentions

Artificial Intelligence has revolutionized mental health services through its advantages yet it creates obstacles for delivering mental health care. While AI has potential of transforming the clinical practices, but it’s very important to know how it used both responsibly and ethically in clinical settings. For this, clinical psychologists need to be familiar with the AI tools and have knowledge of how to use AI tools in their clinical practices. The present study aimed to explore the relationship between AI literacy, perceived benefits and barriers and the intention to adopt AI in clinical practices. A cross–sectional research design is used to collect data from a purposive sample of 147 clinical psychologists aged (M = 27.68, SD = 5.15) years working in various mental health settings in Islamabad and Rawalpindi. The study employed standardized questionnaires to measure AI literacy through the MAIL Scale and to assess perceived benefits using the TAM Scale and perceived barriers using the BAAI Scale and to evaluate the intention to adopt AI through the Trust in Automation Scale. The results showed that AI literacy and perceived benefits significantly positively predicted intentions to adopt AI in clinical settings. The research demonstrates why AI literacy stands as a critical factor while showing the necessity to enhance AI knowledge and reduce obstacles which will help professionals use AI tools properly. These components need to be addressed to establish a link between mental health technology and its real-world application in healthcare systems.

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Publication Details

Journal
˜The œcritical review of social sciences studies
Published
2025-10-01
DOI
https://doi.org/10.59075/q3rsjf20
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in Mental Health Practice: Literacy, Perceived Barriers, Benefits, and Adoption Intentions

Marwa Javaid, Muhammad Faran, Hamna Ashraf
˜The œcritical review of social sciences studies
Digital Mental Health Interventions
article

Artificial Intelligence in Mental Health Practice: Literacy, Perceived Barriers, Benefits, and Adoption Intentions

Marwa Javaid, Muhammad Faran, Hamna Ashraf
article en

Abstract

Artificial Intelligence has revolutionized mental health services through its advantages yet it creates obstacles for delivering mental health care. While AI has potential of transforming the clinical practices, but it’s very important to know how it used both responsibly and ethically in clinical settings. For this, clinical psychologists need to be familiar with the AI tools and have knowledge of how to use AI tools in their clinical practices. The present study aimed to explore the relationship between AI literacy, perceived benefits and barriers and the intention to adopt AI in clinical practices. A cross–sectional research design is used to collect data from a purposive sample of 147 clinical psychologists aged (M = 27.68, SD = 5.15) years working in various mental health settings in Islamabad and Rawalpindi. The study employed standardized questionnaires to measure AI literacy through the MAIL Scale and to assess perceived benefits using the TAM Scale and perceived barriers using the BAAI Scale and to evaluate the intention to adopt AI through the Trust in Automation Scale. The results showed that AI literacy and perceived benefits significantly positively predicted intentions to adopt AI in clinical settings. The research demonstrates why AI literacy stands as a critical factor while showing the necessity to enhance AI knowledge and reduce obstacles which will help professionals use AI tools properly. These components need to be addressed to establish a link between mental health technology and its real-world application in healthcare systems.

˜The œcritical review of social sciences studiesVol. 3(4)
Bahria University (PK)
Openalex Percentile: Top 69%
Digital Mental Health Interventions
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