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使用自我监测应用程序进行防晒的偏好:一项离散选择实验研究的方案

Preferences for Sun Protection With a Self-Monitoring App: Protocol of a Discrete Choice Experiment Study.

作者信息

Nittas Vasileios, Mütsch Margot, Puhan Milo Alan

机构信息

Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.

出版信息

JMIR Res Protoc. 2020 Feb 8;9(2):e16087. doi: 10.2196/16087.


DOI:10.2196/16087
PMID:32130187
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7055859/
Abstract

BACKGROUND: The incidence of sun-exposure-related skin conditions, such as melanoma, is a gradually increasing and largely preventable public health problem. Simultaneously, the availability of mobile apps that enable the self-monitoring of health behavior and outcomes is ever increasing. Inevitably, recent years have seen an emerging volume of electronic patient-generated health data (PGHD), as well as their targeted application across primary prevention areas, including sun protection and skin health. Despite their preventive potential, the actual impact of these apps relies on the engagement of health care consumers, who are primarily responsible for recording, sharing, and using their PGHD. Exploring preferences is a key step toward facilitating consumer engagement and ultimately realizing their potential. OBJECTIVE: This paper describes an ongoing research project that aims to elicit the preferences of health care consumers for sun protection via app-based self-monitoring. METHODS: A discrete choice experiment (DCE) will be conducted to explore how healthy consumers choose between two alternative preventive self-monitoring apps. DCE development and attribute selection were built on extensive qualitative work, consisting of the secondary use of a previously conducted scoping review, a rapid review of reviews, 13 expert interviews, and 12 health care consumer interviews, the results of which are reported in this paper. Following D-optimality criteria, a fractional factorial survey design was generated. The final DCE will be administered in the waiting room of a travel clinic, targeting a sample of 200 participants. Choice data will be analyzed with conditional logit and multinomial logit models, accounting for individual participant characteristics. RESULTS: An ethics approval was waived by the Ethics Committee Zurich. The study started in September 2019 and estimated data collection and completion is set for January 2020. Five two-level attributes have been selected for inclusion in the DCE, addressing (1) data generation methods, (2) privacy control, (3) data sharing with general practitioner, (4) reminder timing, and (5) costs. Data synthesis, analysis, and reporting are planned for January and February 2020. Results are expected to be submitted for publication by February 2020. CONCLUSIONS: Our results will target technology developers, health care providers, and policy makers, potentially offering some guidance on how to design or use sun-protection-focused self-monitoring apps in ways that are responsive to consumer preferences. Preferences are ultimately linked to engagement and motivation, which are key elements for the uptake and success of digital health. Our findings will inform the design of person-centered apps, while also inspiring future preference-eliciting research in the field of emerging and complex eHealth services. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/16087.

摘要

背景:与阳光暴露相关的皮肤疾病,如黑色素瘤的发病率呈逐渐上升趋势,且在很大程度上是可预防的公共卫生问题。与此同时,能够实现健康行为和结果自我监测的移动应用程序越来越多。不可避免地,近年来出现了大量电子患者生成的健康数据(PGHD),以及它们在包括防晒和皮肤健康在内的初级预防领域的针对性应用。尽管这些应用程序具有预防潜力,但其实际影响取决于医疗保健消费者的参与,他们主要负责记录、分享和使用自己的PGHD。探索偏好是促进消费者参与并最终实现其潜力的关键一步。 目的:本文描述了一个正在进行的研究项目,旨在通过基于应用程序的自我监测来了解医疗保健消费者对防晒的偏好。 方法:将进行一项离散选择实验(DCE),以探索健康消费者如何在两款替代性预防自我监测应用程序之间进行选择。DCE的开发和属性选择基于广泛的定性研究工作,包括对先前进行的范围审查的二次利用、对综述的快速审查、13次专家访谈和12次医疗保健消费者访谈,本文报告了这些研究结果。根据D最优标准,生成了分数析因调查设计。最终的DCE将在一家旅行诊所的候诊室进行,目标样本为200名参与者。选择数据将使用条件逻辑回归和多项逻辑回归模型进行分析,并考虑个体参与者特征。 结果:苏黎世伦理委员会豁免了伦理批准。该研究于2019年9月开始,预计数据收集和完成时间为2020年1月。已选择五个二级属性纳入DCE,涉及(1)数据生成方法,(2)隐私控制,(3)与全科医生的数据共享,(4)提醒时间,以及(5)成本。计划于2020年1月和2月进行数据综合、分析和报告。预计结果将于2020年2月提交发表。 结论:我们的结果将针对技术开发者、医疗保健提供者和政策制定者,可能为如何以响应消费者偏好的方式设计或使用以防晒为重点的自我监测应用程序提供一些指导。偏好最终与参与度和动机相关联,而参与度和动机是数字健康应用采用和成功的关键要素。我们的研究结果将为以用户为中心的应用程序设计提供参考,同时也将激发未来在新兴和复杂的电子健康服务领域进行偏好诱导研究。 国际注册报告识别码(IRRID):PRR1-10.2196/

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0609/7055859/a1aea2eace31/resprot_v9i2e16087_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0609/7055859/87eb5e1af487/resprot_v9i2e16087_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0609/7055859/a1aea2eace31/resprot_v9i2e16087_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0609/7055859/87eb5e1af487/resprot_v9i2e16087_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0609/7055859/a1aea2eace31/resprot_v9i2e16087_fig2.jpg

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[2]
Decision Trade-Offs in Ecological Momentary Assessments and Digital Wearables Uptake: Protocol for a Discrete Choice Experiment.

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[3]
Self-Monitoring App Preferences for Sun Protection: Discrete Choice Experiment Survey Analysis.

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[4]
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本文引用的文献

[1]
Electronic Patient-Generated Health Data to Facilitate Disease Prevention and Health Promotion: Scoping Review.

J Med Internet Res. 2019-10-14

[2]
Text Messaging Interventions for Improvement in Physical Activity and Sedentary Behavior in Youth: Systematic Review.

JMIR Mhealth Uhealth. 2018-9-17

[3]
Electronic patient-generated health data to facilitate prevention and health promotion: a scoping review protocol.

BMJ Open. 2018-8-10

[4]
Patient preferences for massively parallel sequencing genetic testing of colorectal cancer risk: a discrete choice experiment.

Eur J Hum Genet. 2018-5-25

[5]
Conducting a Discrete-Choice Experiment Study Following Recommendations for Good Research Practices: An Application for Eliciting Patient Preferences for Diabetes Treatments.

Value Health. 2018-1

[6]
Key Components in eHealth Interventions Combining Self-Tracking and Persuasive eCoaching to Promote a Healthier Lifestyle: A Scoping Review.

J Med Internet Res. 2017-8-1

[7]
Systematic and Iterative Development of a Smartphone App to Promote Sun-Protection Among Holidaymakers: Design of a Prototype and Results of Usability and Acceptability Testing.

JMIR Res Protoc. 2017-6-12

[8]
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PM R. 2017-5

[9]
The efficacy of wearable activity tracking technology as part of a weight loss program: a systematic review.

J Sports Med Phys Fitness. 2018-4

[10]
Who Uses Mobile Phone Health Apps and Does Use Matter? A Secondary Data Analytics Approach.

J Med Internet Res. 2017-4-19

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