AUTHOR=Ji Nan , Wu Mao , Liu Yong 

TITLE=Impact of smart healthcare-based behaviors of elderly patients with chronic diseases on physicians’ behavioral adaptations

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1595637

DOI=10.3389/fmed.2025.1595637

ISSN=2296-858X

ABSTRACT=BackgroundThis study aimed to investigate how the smart healthcare-based behaviors of elderly patients with chronic diseases influence physicians’ behavioral adaptations.MethodsPhysicians providing healthcare services to elderly patients with chronic diseases between July 1, 2024, and July 31, 2024, were recruited. A total of 100 physicians and 100 of their patients were enrolled. Data were collected using a general information questionnaire, the Chinese version of the Self-Efficacy in Patient-Centeredness Questionnaire (SEPCQ), the Chinese version of the Wake Forest Physician Trust Scale (WFPTS-C-10), the Health Information Seeking Behavior (HISB) scale, and the Cloud Follow-up Service Experience Scale for Patients with Chronic Diseases.ResultsThe mean scores were as follows: SEPCQ (50.54 ± 6.16), WFPTS-C-10 (107.82 ± 5.16), HISB (31.96 ± 4.94), and the Cloud Follow-up Service Experience Scale for Chronic Disease Patients (26.11 ± 3.16). No statistically significant differences were observed (p > 0.05). There were statistically significant differences in SEPCQ scores among physicians of different ages, frequencies of individual communication with patients per week and years of working experience (p < 0.05). Correlation analysis revealed that SEPCQ scores were positively correlated with the scores of WFPTS-C-10, HISB, age, number of individual communications with patients per week, and working years (r = 0.264, 0.289, 0.311, 0.276, 0.333, p < 0.001), and negatively correlated with the scores of Cloud Follow-up Service Experience Scale for Patients with Chronic Diseases (r = −0.879, p < 0.001). Multiple linear regression analysis showed that age, the number of separate communications with patients per week, working years, WFPTS-C-10, HISB and the scores of Cloud Follow-up Service Experience Scale for Patients with Chronic Diseases were significant predictors of SEPCQ scores (p < 0.05), accounting for 38.7% of the variance.ConclusionIn the current healthcare context, behaviors of elderly patients with chronic diseases significantly influence physicians’ behavioral adaptations.