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基于电子邮件的 Health eHeart 研究招募:受邀合格患者的队列分析。

Email-Based Recruitment Into the Health eHeart Study: Cohort Analysis of Invited Eligible Patients.

机构信息

School of Public Health, University of California, Berkeley, CA, United States.

Department of Medicine (Biomedical Informatics), Stanford University, Stanford, CA, United States.

出版信息

J Med Internet Res. 2023 Dec 22;25:e51238. doi: 10.2196/51238.


DOI:10.2196/51238
PMID:38133910
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10770794/
Abstract

BACKGROUND: Web- or app-based digital health studies allow for more efficient collection of health data for research. However, remote recruitment into digital health studies can enroll nonrepresentative study samples, hindering the robustness and generalizability of findings. Through the comprehensive evaluation of an email-based campaign on recruitment into the Health eHeart Study, we aim to uncover key sociodemographic and clinical factors that contribute to enrollment. OBJECTIVE: This study sought to understand the factors related to participation, specifically regarding enrollment, in the Health eHeart Study as a result of a large-scale remote email recruitment campaign. METHODS: We conducted a cohort analysis on all invited University of California, San Francisco (UCSF) patients to identify sociodemographic and clinical predictors of enrollment into the Health eHeart Study. The primary outcome was enrollment, defined by account registration and consent into the Health eHeart Study. The email recruitment campaign was carried out from August 2015 to February 2016, with electronic health record data extracted between September 2019 and December 2019. RESULTS: The email recruitment campaign delivered at least 1 email invitation to 93.5% (193,606/206,983) of all invited patients and yielded a 3.6% (7012/193,606) registration rate among contacted patients and an 84.1% (5899/7012) consent rate among registered patients. Adjusted multivariate logistic regression models analyzed independent sociodemographic and clinical predictors of (1) registration among contacted participants and (2) consent among registered participants. Odds of registration were higher among patients who are older, women, non-Hispanic White, active patients with commercial insurance or Medicare, with a higher comorbidity burden, with congestive heart failure, and randomized to receive up to 2 recruitment emails. The odds of registration were lower among those with medical conditions such as dementia, chronic pulmonary disease, moderate or severe liver disease, paraplegia or hemiplegia, renal disease, or cancer. Odds of subsequent consent after initial registration were different, with an inverse trend of being lower among patients who are older and women. The odds of consent were also lower among those with peripheral vascular disease. However, the odds of consent remained higher among patients who were non-Hispanic White and those with commercial insurance. CONCLUSIONS: This study provides important insights into the potential returns on participant enrollment when digital health study teams invest resources in using email for recruitment. The findings show that participant enrollment was driven more strongly by sociodemographic factors than clinical factors. Overall, email is an extremely efficient means of recruiting participants from a large list into the Health eHeart Study. Despite some improvements in representation, the formulation of truly diverse studies will require additional resources and strategies to overcome persistent participation barriers.

摘要

背景:基于网络或应用程序的数字健康研究可更有效地收集研究用健康数据。然而,远程招募参与数字健康研究可能会招募到非代表性的研究样本,从而阻碍研究结果的稳健性和普遍性。通过对健康电子心脏研究(Health eHeart Study)的电子邮件招募活动进行全面评估,我们旨在揭示导致参与的关键社会人口学和临床因素。

目的:本研究旨在了解通过大规模远程电子邮件招募活动参与 Health eHeart Study 的相关因素,特别是参与注册的因素。

方法:我们对所有受邀的加利福尼亚大学旧金山分校(UCSF)患者进行了队列分析,以确定与 Health eHeart Study 注册相关的社会人口学和临床预测因素。主要结局是注册,定义为 Health eHeart Study 的账户注册和同意。电子邮件招募活动于 2015 年 8 月至 2016 年 2 月进行,电子健康记录数据于 2019 年 9 月至 2019 年 12 月提取。

结果:电子邮件招募活动至少向所有受邀患者中的 93.5%(193606/206983)发送了一封电子邮件邀请,并在联系到的患者中产生了 3.6%(7012/193606)的注册率,在已注册的患者中产生了 84.1%(5899/7012)的同意率。调整后的多变量逻辑回归模型分析了独立的社会人口学和临床预测因素,包括(1)联系到的参与者的注册率和(2)已注册参与者的同意率。在联系到的患者中,年龄较大、女性、非西班牙裔白人、有商业保险或医疗保险的活跃患者、合并症负担较重、充血性心力衰竭患者,以及随机接受 2 封招募电子邮件的患者,其注册的可能性更高。而在有痴呆、慢性肺部疾病、中度或重度肝脏疾病、截瘫或偏瘫、肾脏疾病或癌症等疾病的患者中,注册的可能性较低。在初始注册后同意的可能性也有所不同,年龄较大和女性的患者呈下降趋势。在患有外周血管疾病的患者中,同意的可能性也较低。然而,非西班牙裔白人和有商业保险的患者同意的可能性更高。

结论:本研究为数字健康研究团队投资使用电子邮件招募时的潜在参与者招募回报提供了重要的见解。研究结果表明,参与者的注册更多地受到社会人口学因素的驱动,而不是临床因素。总的来说,电子邮件是从大型名单中招募参与者参加 Health eHeart Study 的一种极其有效的方式。尽管在代表性方面有所改善,但要制定真正多样化的研究,还需要额外的资源和策略来克服持续存在的参与障碍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cad/10770794/8bbbb12c87a4/jmir_v25i1e51238_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cad/10770794/601c2c448b69/jmir_v25i1e51238_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cad/10770794/8bbbb12c87a4/jmir_v25i1e51238_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cad/10770794/601c2c448b69/jmir_v25i1e51238_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cad/10770794/8bbbb12c87a4/jmir_v25i1e51238_fig2.jpg

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[1]
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Digit Health. 2022-9-25

[2]
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Res Nurs Health. 2022-10

[3]
Older adults can use technology: why healthcare professionals must overcome ageism in digital health.

Transl Behav Med. 2022-12-30

[4]
Race/ethnicity reporting and representation in US clinical trials: a cohort study.

Lancet Reg Health Am. 2022-7

[5]
Advancing the inclusion of underrepresented women in clinical research.

Cell Rep Med. 2022-4-19

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J Med Internet Res. 2022-4-26

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