在线健康信息搜索对使用阿司匹林预防心血管疾病的不同影响

IF 3.4 3区 医学 Q1 HEALTH POLICY & SERVICES Health Policy and Technology Pub Date : 2024-06-01 DOI:10.1016/j.hlpt.2024.100842
Jingrong Zhu , Yunfeng Shi , Yi Cui , Wei Yan
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引用次数: 0

摘要

背景互联网已成为大众获取健康信息的重要来源。以往的研究表明,在线健康信息搜索与坚持用药有关。然而,这种关系的方向仍存在争议。目标研究 2016 年至 2018 年美国适用成年人群中,在线健康信息寻求对使用阿司匹林预防心血管疾病的异质性影响以及可能的调节因素。方法根据阿司匹林使用指南,从 2016 年至 2018 年全国健康访谈调查中抽取 40 岁或以上的受访者。采用线性概率模型在四个独立的亚人群中检验了患者阿司匹林使用行为与相关变量之间的关联。结果阿司匹林用于预防心血管疾病与在线健康信息搜索之间存在不同的关联。当患者接受医生建议使用阿司匹林时,在线信息搜索对阿司匹林的使用有负面影响,这取决于个人是否有心血管疾病风险因素。然而,对于没有医疗服务提供者建议的患者来说,在线信息搜索对自行使用阿司匹林的影响取决于不同的预防类型(即一级预防与二级预防)和心血管疾病风险因素:结论:在线健康信息可能会导致阿司匹林在心血管疾病预防中的过度使用或使用不足。在线信息搜索与影响消费者决策的其他信息来源相互作用。消费者的主要特征和风险因素也可能会缓和这种关系。
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The Heterogeneous Influences of Online Health Information Seeking on Aspirin Use for Cardiovascular Disease Prevention

Background

The internet has become an important source of health information for the general population. Previous research has shown that online health information seeking is associated with medication adherence. However, the direction of this relationship is still a matter of dispute. Even less is known about the factors that moderate such a relationship.

Objective

To investigate the heterogeneous influences of online health information seeking on the use of aspirin in CVD prevention and the possible moderating factors among the applicable adult population in the U.S from 2016 to 2018.

Methods

Respondents aged 40 or older, based on guidelines for aspirin use, were sampled from the 2016 to 2018 National Health Interview Survey. Linear probability models were used to test the association between patients’ aspirin use behaviors and the variables of interest in four separate sub-populations.

Results

Aspirin use for CVD prevention was associated with online health information seeking in different ways. When patients received doctors’ advice to use aspirin, online information seeking has a negative influence on aspirin use, depending on whether the individual has CVD risk factors. However, for patients without recommendations from providers, the effects of online information seeking on self-initiated aspirin use depend on the different types of prevention (i.e., primary vs. secondary) and CVD risk factors.

Conclusions

Online health information might lead to both overuse and underuse of aspirin in CVD prevention. Online information seeking interacts with other information sources affecting consumers' decision making. Key consumer characteristics and risk factors may also moderate such a relationship.

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来源期刊
Health Policy and Technology
Health Policy and Technology Medicine-Health Policy
CiteScore
9.20
自引率
3.30%
发文量
78
审稿时长
88 days
期刊介绍: Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics
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