如何防止辍学:理解为什么成年人参与总结性电子健康评估。

IF 5.9 Q1 Computer Science
Marian Z M Hurmuz, Stephanie M Jansen-Kosterink, Lex van Velsen
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引用次数: 0

摘要

本研究的目的是调查为什么成年人参与总结性电子健康评估,以及他们参与的原因是否会影响他们(不)使用电子健康。在参加总结性电子健康评估的成年人(年龄≥18岁)中分发一份问卷。该问卷主要关注参与者报名的原因,他们的期望,以及研究是否符合他们的期望。开放式问题的答案由两名研究人员独立编码。使用广义估计方程方法,我们测试了使用电子健康服务的原因类型之间是否存在差异。131名成年人参与其中(64.9%为女性;平均年龄62.5岁(SD = 10.5))。他们参加的原因主要是与健康有关(例如,更积极)。在两种动机之间,使用电子健康服务的情况有所不同:与利他动机的参与者相比,智力动机的参与者更有可能退出。在参加总结性电子健康评估时,最普遍的期望是与健康相关的(比如期望改善自己的健康)。38.6%的参与者表示他们的期望通过研究得到了满足。总之,我们鼓励电子健康评估人员了解成年人参与总结性评估的动机,因为这种动机很可能影响他们的结果。包括利他动机的参与者,他们倾向于继续参与一项研究,从而使结果产生偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

How to Prevent the Drop-Out: Understanding Why Adults Participate in Summative eHealth Evaluations.

How to Prevent the Drop-Out: Understanding Why Adults Participate in Summative eHealth Evaluations.

How to Prevent the Drop-Out: Understanding Why Adults Participate in Summative eHealth Evaluations.

How to Prevent the Drop-Out: Understanding Why Adults Participate in Summative eHealth Evaluations.

The aim of this study was to investigate why adults participate in summative eHealth evaluations, and whether their reasons for participating affect their (non-)use of eHealth. A questionnaire was distributed among adults (aged ≥ 18 years) who participated in a summative eHealth evaluation. This questionnaire focused on participants' reason to enroll, their expectations, and on whether the study met their expectations. Answers to open-ended questions were coded by two researchers independently. With the generalized estimating equations method we tested whether there is a difference between the type of reasons in use of the eHealth service. One hundred and thirty-one adults participated (64.9% female; mean age 62.5 years (SD = 10.5)). Their reasons for participating were mainly health-related (e.g., being more active). Between two types of motivations there was a difference in the use of the eHealth service: Participants with an intellectual motivation were more likely to drop out, compared to participants with an altruistic motivation. The most prevalent expectations when joining a summative eHealth evaluation were health-related (like expecting to improve one's health). 38.6% of the participants said their expectation was fulfilled by the study. In conclusion, We encourage eHealth evaluators to learn about adults' motivation to participate in their summative evaluation, as this motivation is very likely to affect their results. Including altruistically motivated participants biases the results by their tendency to continue participating in a study.

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来源期刊
Journal of Healthcare Informatics Research
Journal of Healthcare Informatics Research Computer Science-Computer Science Applications
CiteScore
13.60
自引率
1.70%
发文量
12
期刊介绍: Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics.  The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications.   Topics include but are not limited to: ·         healthcare software architecture, framework, design, and engineering;·         electronic health records·         medical data mining·         predictive modeling·         medical information retrieval·         medical natural language processing·         healthcare information systems·         smart health and connected health·         social media analytics·         mobile healthcare·         medical signal processing·         human factors in healthcare·         usability studies in healthcare·         user-interface design for medical devices and healthcare software·         health service delivery·         health games·         security and privacy in healthcare·         medical recommender system·         healthcare workflow management·         disease profiling and personalized treatment·         visualization of medical data·         intelligent medical devices and sensors·         RFID solutions for healthcare·         healthcare decision analytics and support systems·         epidemiological surveillance systems and intervention modeling·         consumer and clinician health information needs, seeking, sharing, and use·         semantic Web, linked data, and ontology·         collaboration technologies for healthcare·         assistive and adaptive ubiquitous computing technologies·         statistics and quality of medical data·         healthcare delivery in developing countries·         health systems modeling and simulation·         computer-aided diagnosis
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