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参与者对使用移动设备进行的个人生成健康数据研究的贡献:范围综述

Participant Contributions to Person-Generated Health Data Research Using Mobile Devices: Scoping Review.

作者信息

Song Shanshan, Ashton Micaela, Yoo Rebecca Hahn, Lkhagvajav Zoljargal, Wright Robert, Mathews Debra J H, Taylor Casey Overby

机构信息

Biomedical Informatics & Data Science Section, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Institute for Computational Medicine, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.

出版信息

J Med Internet Res. 2025 Jan 20;27:e51955. doi: 10.2196/51955.


DOI:10.2196/51955
PMID:39832140
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11791458/
Abstract

BACKGROUND: Mobile devices offer an emerging opportunity for research participants to contribute person-generated health data (PGHD). There is little guidance, however, on how to best report findings from studies leveraging those data. Thus, there is a need to characterize current reporting practices so as to better understand the potential implications for producing reproducible results. OBJECTIVE: The primary objective of this scoping review was to characterize publications' reporting practices for research that collects PGHD using mobile devices. METHODS: We comprehensively searched PubMed and screened the results. Qualifying publications were classified according to 6 dimensions-1 covering key bibliographic details (for all articles) and 5 covering reporting criteria considered necessary for reproducible and responsible research (ie, "participant," "data," "device," "study," and "ethics," for original research). For each of the 5 reporting dimensions, we also assessed reporting completeness. RESULTS: Out of 3602 publications screened, 100 were included in this review. We observed a rapid increase in all publications from 2016 to 2021, with the largest contribution from US authors, with 1 exception, review articles. Few original research publications used crowdsourcing platforms (7%, 3/45). Among the original research publications that reported device ownership, most (75%, 21/28) reported using participant-owned devices for data collection (ie, a Bring-Your-Own-Device [BYOD] strategy). A significant deficiency in reporting completeness was observed for the "data" and "ethics" dimensions (5 reporting factors were missing in over half of the research publications). Reporting completeness for data ownership and participants' access to data after contribution worsened over time. CONCLUSIONS: Our work depicts the reporting practices in publications about research involving PGHD from mobile devices. We found that very few papers reported crowdsourcing platforms for data collection. BYOD strategies are increasingly popular; this creates an opportunity for improved mechanisms to transfer data from device owners to researchers on crowdsourcing platforms. Given substantial reporting deficiencies, we recommend reaching a consensus on best practices for research collecting PGHD from mobile devices. Drawing from the 5 reporting dimensions in this scoping review, we share our recommendations and justifications for 9 items. These items require improved reporting to enhance data representativeness and quality and empower participants.

摘要

背景:移动设备为研究参与者提供了一个新的机会,使其能够贡献个人生成的健康数据(PGHD)。然而,对于如何最好地报告利用这些数据的研究结果,几乎没有相关指导。因此,有必要对当前的报告做法进行描述,以便更好地理解其对产生可重复结果的潜在影响。 目的:本范围综述的主要目的是描述使用移动设备收集PGHD的研究在出版物中的报告做法。 方法:我们全面检索了PubMed并筛选结果。符合条件的出版物根据6个维度进行分类——1个维度涵盖关键书目细节(适用于所有文章),5个维度涵盖可重复和负责任研究所需的报告标准(即针对原创研究的“参与者”“数据”“设备”“研究”和“伦理”)。对于5个报告维度中的每一个,我们还评估了报告的完整性。 结果:在筛选的3602篇出版物中,有100篇纳入了本综述。我们观察到2016年至2021年所有出版物数量迅速增加,美国作者的贡献最大,综述文章除外。很少有原创研究出版物使用众包平台(7%,3/45)。在报告设备所有权的原创研究出版物中,大多数(75%,21/28)报告使用参与者自己的设备进行数据收集(即自带设备[BYOD]策略)。在“数据”和“伦理”维度观察到报告完整性存在重大缺陷(超过一半的研究出版物缺少5个报告因素)。数据所有权和参与者在贡献数据后对数据的访问权限的报告完整性随时间推移而恶化。 结论:我们的工作描述了关于使用移动设备进行PGHD研究的出版物中的报告做法。我们发现很少有论文报告使用众包平台进行数据收集。BYOD策略越来越受欢迎;这为改进将数据从设备所有者转移到众包平台上的研究人员的机制创造了机会。鉴于报告存在大量缺陷,我们建议就从移动设备收集PGHD的研究的最佳实践达成共识。借鉴本范围综述中的5个报告维度,我们分享了9项建议及其理由。这些项目需要改进报告以提高数据的代表性和质量,并增强参与者的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/2a39d3a9c242/jmir_v27i1e51955_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/e6aefa7c0d77/jmir_v27i1e51955_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/42cd02573e45/jmir_v27i1e51955_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/fba0d6e55b4c/jmir_v27i1e51955_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/f554fc0f5b33/jmir_v27i1e51955_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/2a39d3a9c242/jmir_v27i1e51955_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/e6aefa7c0d77/jmir_v27i1e51955_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/42cd02573e45/jmir_v27i1e51955_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/fba0d6e55b4c/jmir_v27i1e51955_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/f554fc0f5b33/jmir_v27i1e51955_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6006/11791458/2a39d3a9c242/jmir_v27i1e51955_fig5.jpg

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