Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom.
Centre for Health Informatics, Manchester Academic Health Science Centre, Manchester, United Kingdom.
J Med Internet Res. 2023 Feb 7;25:e42449. doi: 10.2196/42449.
The use of data from smartphones and wearable devices has huge potential for population health research, given the high level of device ownership; the range of novel health-relevant data types available from consumer devices; and the frequency and duration with which data are, or could be, collected. Yet, the uptake and success of large-scale mobile health research in the last decade have not met this intensely promoted opportunity. We make the argument that digital person-generated health data are required and necessary to answer many top priority research questions, using illustrative examples taken from the James Lind Alliance Priority Setting Partnerships. We then summarize the findings from 2 UK initiatives that considered the challenges and possible solutions for what needs to be done and how such solutions can be implemented to realize the future opportunities of digital person-generated health data for clinically important population health research. Examples of important areas that must be addressed to advance the field include digital inequality and possible selection bias; easy access for researchers to the appropriate data collection tools, including how best to harmonize data items; analysis methodologies for time series data; patient and public involvement and engagement methods for optimizing recruitment, retention, and public trust; and methods for providing research participants with greater control over their data. There is also a major opportunity, provided through the linkage of digital person-generated health data to routinely collected data, to support novel population health research, bringing together clinician-reported and patient-reported measures. We recognize that well-conducted studies need a wide range of diverse challenges to be skillfully addressed in unison (eg, challenges regarding epidemiology, data science and biostatistics, psychometrics, behavioral and social science, software engineering, user interface design, information governance, data management, and patient and public involvement and engagement). Consequently, progress would be accelerated by the establishment of a new interdisciplinary community where all relevant and necessary skills are brought together to allow for excellence throughout the life cycle of a research study. This will require a partnership of diverse people, methods, and technologies. If done right, the synergy of such a partnership has the potential to transform many millions of people's lives for the better.
使用智能手机和可穿戴设备的数据在人群健康研究方面具有巨大潜力,因为设备拥有率很高;消费者设备可以提供各种新颖的健康相关数据类型;并且可以以或高或低的频率和时长收集数据。然而,在过去十年中,大规模移动健康研究的采用和成功并未达到这一强烈推动的机会水平。我们认为,数字个人生成的健康数据是回答许多首要研究问题所必需的,并用詹姆斯·林德联盟优先设置伙伴关系中的说明性示例对此进行了论证。然后,我们总结了英国的两个举措的调查结果,这些举措考虑了为实现数字个人生成的健康数据在重要的人群健康研究中的未来机会而需要做什么以及如何实施这些解决方案所面临的挑战和可能的解决方案。为了推进该领域,必须解决的重要领域包括数字不平等和可能的选择偏差;研究人员方便地获得适当的数据收集工具,包括如何最好地协调数据项;时间序列数据的分析方法;患者和公众参与和参与方法,以优化招募、保留和公众信任;以及为研究参与者提供更多控制其数据的方法。通过将数字个人生成的健康数据与常规收集的数据联系起来,还有一个主要机会可以支持新颖的人群健康研究,将临床医生报告的和患者报告的措施结合起来。我们认识到,精心进行的研究需要协同解决广泛的各种挑战(例如,流行病学、数据科学和生物统计学、心理测量学、行为和社会科学、软件工程、用户界面设计、信息治理、数据管理以及患者和公众参与和参与方面的挑战)。因此,通过建立一个新的跨学科社区,汇集所有相关和必要的技能,可以在研究的整个生命周期中实现卓越,从而加速进展。这将需要多样化的人员、方法和技术的合作。如果做得好,这种合作的协同作用有可能改善数百万人的生活。