ORIGINAL RESEARCH article
Front. Med.
Sec. Family Medicine and Primary Care
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1595637
Impact of Smart Healthcare-Based Behaviors of Elderly Patients with Chronic Diseases on Physicians' Behavioral Adaptations
Provisionally accepted
- 1School of Design, Jiangnan University, Wuxi, Jiangsu Province, China
- 2Wuxi Traditional Chinese Medicine Hospital, Wuxi, China
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Background: This study aimed to investigate how the smart healthcare-based behaviors of elderly patients with chronic diseases influence physicians' behavioral adaptations. Methods: Physicians 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. Results: The 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. Conclusion: In the current healthcare context, behaviors of elderly patients with chronic diseases significantly influence physicians' behavioral adaptations.
Keywords: Smart healthcare, Elderly, chronic diseases, Behavior, Influencing factors
Received: 28 Mar 2025; Accepted: 29 Jul 2025.
Copyright: © 2025 Ji, Wu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yong Liu, Wuxi Traditional Chinese Medicine Hospital, Wuxi, China
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