癌症信息过载和查态度的预测建模:一个横截面研究
1Graduate School of Health Sciences, Department of Nursing (Master's with Thesis), Sakarya University, Sakarya, Türkiye.
Seminars in oncology nursing
|December 13, 2025
概括
过度的癌症信息会对癌症查的态度产生负面影响. 管理信息过载对于改善患者参与查计划至关重要.
科学领域:
- 在瘤学瘤学.
- 健康心理学 心理健康心理学
- 数据科学数据科学数据科学
背景情况:
- 越来越多的癌症信息可能会影响患者的看法.
- 了解影响癌症查态度的因素对于公共卫生至关重要.
研究的目的:
- 研究癌症信息过载和人们对癌症查的态度之间的关系.
- 通过使用统计和机器学习方法,确定选态度的关键预测因素.
主要方法:
- 对410名内科门诊患者的横截面研究.
- 利用癌症信息过载量和癌症查态度量.
- 采用了t测试,ANOVA,回归和7个具有10倍交叉验证的机器学习模型.
主要成果:
- 在癌症信息过载和查态度之间发现了显著的负面关联 (β = -0.321,P < .001).
- 弹性净回归在机器学习模型中表现出优越的预测性能.
- 癌症信息过载成为查态度的最强有力的预测因素.
结论:
- 癌症信息过载的增加与对癌症查的积极态度的减少有关.
- 机器学习模型为预测查态度提供了宝贵的见解.
- 旨在减少信息负担的干预措施可能会提高癌症查参与度.
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