SEM model analysis of diabetic patients' acceptance of artificial intelligence for diabetic retinopathy.

ABSTRACT:

Aims

This study aimed to investigate diabetic patients' acceptance of artificial intelligence (AI) devices for diabetic retinopathy screening and the related influencing factors.

Methods

An integrated model was proposed, and structural equation modeling was used to evaluate items and construct reliability and validity via confirmatory factor analysis. The model's path effects, significance, goodness of fit, and mediation and moderation effects were analyzed.

Results

Intention to Use (IU) is significantly affected by Subjective Norms (SN), Resistance Bias (RB), and Uniqueness Neglect (UN). Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) were significant mediators between IU and other variables. The moderating effect of trust (TR) is non-significant on the pa

SUBMITTER: Jin L 

PROVIDER: S-EPMC12023383 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature