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慢性病老年患者基于智能医疗的行为对医生行为适应的影响

Impact of smart healthcare-based behaviors of elderly patients with chronic diseases on physicians' behavioral adaptations.

作者信息

Ji Nan, Wu Mao, Liu Yong

机构信息

School of Design, Jiangnan University, Wuxi, China.

Department of Orthopaedics, Wuxi Hospital of Traditional Chinese Medicine, Wuxi, China.

出版信息

Front Med (Lausanne). 2025 Aug 13;12:1595637. doi: 10.3389/fmed.2025.1595637. eCollection 2025.

Abstract

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 ( > 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 ( < 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 ( = 0.264, 0.289, 0.311, 0.276, 0.333,  < 0.001), and negatively correlated with the scores of Cloud Follow-up Service Experience Scale for Patients with Chronic Diseases ( = -0.879,  < 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 ( < 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.

摘要

背景

本研究旨在调查慢性病老年患者基于智能医疗的行为如何影响医生的行为适应。

方法

招募在2024年7月1日至2024年7月31日期间为慢性病老年患者提供医疗服务的医生。共招募了100名医生及其100名患者。使用一般信息问卷、中文版以患者为中心的自我效能量表(SEPCQ)、中文版维克森林医生信任量表(WFPTS-C-10)、健康信息寻求行为(HISB)量表以及慢性病患者云随访服务体验量表收集数据。

结果

平均得分如下:SEPCQ(50.54±6.16)、WFPTS-C-10(107.82±5.16)、HISB(31.96±4.94)以及慢性病患者云随访服务体验量表(26.11±3.16)。未观察到统计学显著差异(>0.05)。不同年龄、每周与患者单独沟通的频率以及工作年限的医生在SEPCQ得分上存在统计学显著差异(<0.05)。相关分析显示,SEPCQ得分与WFPTS-C-10、HISB、年龄、每周与患者单独沟通的次数以及工作年限的得分呈正相关(=0.264、0.289、0.311、0.276、0.333,<0.001),与慢性病患者云随访服务体验量表的得分呈负相关(= -0.879,<0.001)。多元线性回归分析表明,年龄、每周与患者单独沟通的次数、工作年限、WFPTS-C-10、HISB以及慢性病患者云随访服务体验量表的得分是SEPCQ得分的显著预测因素(<0.05),解释了38.7%的方差。

结论

在当前医疗背景下,慢性病老年患者的行为显著影响医生的行为适应。

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