Pakistan journal of medical sciences · 2026
Artificial Intelligence perception and its influence on the Psychological Distress of Healthcare Professional.
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Alnasser Badr, Kumar Rakesh
Аннотация
OBJECTIVES: Th research examines how AI perception (AIP) affect psychological distress of healthcare professional in Kingdom of Saudi Arabia (KSA). The study also investigates the moderating role of technology readiness (TRD).
METHODOLOGY: This research adopts cross-sectional design. A self-administrative, close ended, survey was used to collect primary data. Total 411 healthcare professionals voluntarily participated from public hospitals of the Hail Health Cluster, in KSA. The survey was carried out through convenience sampling method. Data was processed through SPSS 27 version. Analysis consisted of demographic summary, descriptive analysis and regression analysis through Hayes process.
RESULTS: A total of 411 healthcare professionals participated, with the majority being male (60.8%) and aged 36-45 (41.4%). Additionally, the descriptive statistics revealed adequate reliability for all variables including AIP, DASS-21 and TRD. Moreover, the regression analysis showed that AIP significantly influenced DASS-21 (β = -0.2194, p = 0.0099). Finally, the TRD strengthen the negative impact of AIP on DASS-21 (β = 0.1547, p = 0.0000). The model's R-Square values indicated a strong fit, with significant improvements in prediction.
CONCLUSION: The study highlights that AI perception significantly impacts psychological distress, particularly Depression and Anxiety, among healthcare professionals. While technology readiness significantly strengthens this relationship. Future research should explore other potential moderating factors, such as organizational support, to further understand the impact of AI perception in healthcare settings.
METHODOLOGY: This research adopts cross-sectional design. A self-administrative, close ended, survey was used to collect primary data. Total 411 healthcare professionals voluntarily participated from public hospitals of the Hail Health Cluster, in KSA. The survey was carried out through convenience sampling method. Data was processed through SPSS 27 version. Analysis consisted of demographic summary, descriptive analysis and regression analysis through Hayes process.
RESULTS: A total of 411 healthcare professionals participated, with the majority being male (60.8%) and aged 36-45 (41.4%). Additionally, the descriptive statistics revealed adequate reliability for all variables including AIP, DASS-21 and TRD. Moreover, the regression analysis showed that AIP significantly influenced DASS-21 (β = -0.2194, p = 0.0099). Finally, the TRD strengthen the negative impact of AIP on DASS-21 (β = 0.1547, p = 0.0000). The model's R-Square values indicated a strong fit, with significant improvements in prediction.
CONCLUSION: The study highlights that AI perception significantly impacts psychological distress, particularly Depression and Anxiety, among healthcare professionals. While technology readiness significantly strengthens this relationship. Future research should explore other potential moderating factors, such as organizational support, to further understand the impact of AI perception in healthcare settings.