Patient Trust in AI-generated Medication Information and the Role of Clinical Pharmacists in Preventing Medication-related Safety Risks: A Cross-sectional Survey

BACKGROUND: To assess patient trust in AI-generated medication information, examine associated behavioral safety risks, and evaluate patient expectations regarding the role of clinical pharmacists in preventing medication-related harm. METHODS: A cross-sectional survey was conducted among adult patients attending outpatient clinics and community pharmacies in Abha, Saudi Arabia. Data were collected across 3 sites (King Khalid University Hospital outpatient department and 2 affiliated community pharmacies) over a 10-week period (December 2025-January 2026), after ethical approval (KKU-147-2025-31). A structured questionnaire assessed demographic characteristics, AI use patterns, trust in AI-generated medication information, verification behaviors, and perceptions of pharmacist involvement. Psychometric evaluation demonstrated good internal consistency of the trust in AI scale. Data were analyzed using descriptive statistics, nonparametric tests, exploratory factor analysis, and ordinal logistic regression. RESULTS: Among 167 participants, trust in AI-generated medication information varied significantly across demographic groups and AI platforms, with higher trust reported for large language model-based tools. Participants without health care backgrounds demonstrated higher trust than health care professionals. Increasing trust was associated with higher behavioral risk, including acting on AI-generated medication advice without verification (P=0.002). Factor analysis identified distinct cognitive trust and behavioral engagement dimensions. Strong support was observed for pharmacist involvement in verifying AI-generated medication information. CONCLUSIONS: Patient trust in AI-generated medication information is closely linked to behaviors that may increase medication-related safety risks. Clinical pharmacists play a critical role as a safety barrier, underscoring the need to integrate pharmacist-led verification into AI-informed medication counseling to enhance patient safety.

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Publication Details

Journal
Journal of Patient Safety
Published
2026-06-19
DOI
https://doi.org/10.1097/pts.0000000000001546
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00
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article

Patient Trust in AI-generated Medication Information and the Role of Clinical Pharmacists in Preventing Medication-related Safety Risks: A Cross-sectional Survey

Geetha Kandasamy, Praveen Devanandan, Rajalakshimi Vasudevan, Lama Faisal Alasmari et al.
Journal of Patient Safety
Artificial Intelligence in Healthcare and Education
article

Patient Trust in AI-generated Medication Information and the Role of Clinical Pharmacists in Preventing Medication-related Safety Risks: A Cross-sectional Survey

Geetha Kandasamy, Praveen Devanandan, Rajalakshimi Vasudevan, Lama Faisal Alasmari, Salwa Mohammed Al Malh, Krishnaraju Venkatesan
article en

Abstract

BACKGROUND: To assess patient trust in AI-generated medication information, examine associated behavioral safety risks, and evaluate patient expectations regarding the role of clinical pharmacists in preventing medication-related harm. METHODS: A cross-sectional survey was conducted among adult patients attending outpatient clinics and community pharmacies in Abha, Saudi Arabia. Data were collected across 3 sites (King Khalid University Hospital outpatient department and 2 affiliated community pharmacies) over a 10-week period (December 2025-January 2026), after ethical approval (KKU-147-2025-31). A structured questionnaire assessed demographic characteristics, AI use patterns, trust in AI-generated medication information, verification behaviors, and perceptions of pharmacist involvement. Psychometric evaluation demonstrated good internal consistency of the trust in AI scale. Data were analyzed using descriptive statistics, nonparametric tests, exploratory factor analysis, and ordinal logistic regression. RESULTS: Among 167 participants, trust in AI-generated medication information varied significantly across demographic groups and AI platforms, with higher trust reported for large language model-based tools. Participants without health care backgrounds demonstrated higher trust than health care professionals. Increasing trust was associated with higher behavioral risk, including acting on AI-generated medication advice without verification (P=0.002). Factor analysis identified distinct cognitive trust and behavioral engagement dimensions. Strong support was observed for pharmacist involvement in verifying AI-generated medication information. CONCLUSIONS: Patient trust in AI-generated medication information is closely linked to behaviors that may increase medication-related safety risks. Clinical pharmacists play a critical role as a safety barrier, underscoring the need to integrate pharmacist-led verification into AI-informed medication counseling to enhance patient safety.

Journal of Patient Safety
St. Peter's Institute of Higher Education and Research (IN), King Khalid University (SA)
Good health and well-being
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
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