| 摘要: |
| ［摘要］ 目的 探讨基于人工智能辅助的多维自我效能促进护理对肺癌化疗后骨髓抑制患者应对方式、自我效能感及治疗依从性的影响。方法 招募2022年4月至2023年4月于中国医学科学院肿瘤医院深圳医院收治的肺癌化疗后出现骨髓抑制的患者68例，采用随机数字表法将其分为观察组和对照组，各34例。对照组实施骨髓抑制相关常规护理，观察组在常规护理基础上实施人工智能辅助多维自我效能促进护理。人工智能工具主要用于患者风险分层与护理决策支持。干预前后采用简易应对方式问卷（SCSQ）和一般自我效能感量表（GSES）评估患者应对方式和自我效能水平，并比较两组患者治疗依从性情况。结果 干预后，观察组SCSQ-积极应对评分、GSES评分高于对照组，SCSQ-消极应对评分低于对照组，差异有统计学意义（P<0.05）。观察组治疗完全依从率高于对照组，差异有统计学意义（P<0.05）。结论 基于人工智能辅助的多维自我效能促进护理有助于改善肺癌化疗后骨髓抑制患者的应对方式和自我效能水平，并提高患者治疗依从性。 |
| 关键词: 人工智能 肺癌 骨髓抑制 自我效能 护理干预 人工智能辅助护理 化疗 |
| DOI：10.3969/j.issn.1674-3806.2026.01.03 |
| 分类号:R 734.2；TP 18 |
| 基金项目:中国医学科学院肿瘤医院深圳医院科研课题（编号：E010424010） |
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| AI-driven multidimensional self-efficacy nursing care: a clinical study on improving the coping styles and treatment adherence in lung cancer patients with chemotherapy-induced myelosuppression |
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FU Jianghong1, LI Siqin1, WANG Yu1, NIU Niu1, NING Yanting2
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1.Department of Medical Oncology, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen, National Cancer Center, National Clinical Research Center for Cancer, Shenzhen 518116, China; 2.Department of Nursing, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen, National Cancer Center, National Clinical Research Center for Cancer, Shenzhen 518116, China
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| Abstract: |
| ［Abstract］ Objective To investigate the effects of artificial intelligence(AI)-assisted multidimensional self-efficacy improving nursing care on coping styles, self-efficacy, and treatment adherence in lung cancer patients with chemotherapy-induced myelosuppression. Methods A total of 68 lung cancer patients with chemotherapy-induced myelosuppression who were admitted to Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen were recruited and divided into observation group and control group by using random number table method, with 34 patients in each group. The control group received routine nursing care related to myelosuppression, while the observation group received the same routine nursing care as the control group plus AI-assisted multidimensional self-efficacy improving nursing care. The AI tools were mainly used for the patients′ risk stratification and nursing decision support. Before and after the intervention, the Simple Coping Style Questionnaire(SCSQ) and the General Self-Efficacy Scale(GSES) were used to evaluate the coping styles and self-efficacy levels of the patients, and the treatment adherence was compared between the patients in the two groups. Results After the intervention, the SCSQ-positive coping style scores and GSES scores in the observation group were higher than those in the control group, while the SCSQ-negative coping style scores in the observation group were lower than those in the control group, with statistically significant differences between the two groups(P<0.05). The complete adherence rate of the treatment in the observation group was higher than that in the control group, with statistically significant difference between the two groups(P<0.05). Conclusion AI-assisted multidimensional self-efficacy improving nursing care is conducive to improving the coping styles and self-efficacy levels in lung cancer patients with chemotherapy-induced myelosuppression, and enhances the patients′ treatment adherence. |
| Key words: Artificial intelligence(AI) Lung cancer Myelosuppression Self-efficacy Nursing intervention Artificial intelligence-assisted nursing care Chemotherapy |
