School of Social Work, The University of Texas at Arlington, Arlington, TX, United States.
Department of Sociology, University of North Carolina, Chapel Hill, NC, United States.
J Med Internet Res. 2024 Aug 14;26:e54745. doi: 10.2196/54745.
Despite the potential benefits of using eHealth, sociodemographic disparities exist in eHealth use, which threatens to further widen health equity gaps. The literature has consistently shown age and education to be associated with eHealth use, while the findings for racial and ethnic disparities are mixed. However, previous disparities may have narrowed as health care interactions shifted to web-based modalities for everyone because of the COVID-19 pandemic.
This study aims to provide an updated examination of sociodemographic disparities that contribute to the health equity gap related to using eHealth for information seeking using 3 time points.
Data for this study came from the nationally representative 2018 (n=3504), 2020 (n=3865), and 2022 (n=6252) time points of the Health Information National Trends Survey. Logistic regression was used to regress the use of eHealth for information seeking on race and ethnicity, sex, age, education, income, health status, and year of survey. Given the consistent association of age with the dependent variable, analyses were stratified by age cohort (millennials, Generation X, baby boomers, and silent generation) to compare individuals of similar age.
For millennials, being female, attaining some college or a college degree, and reporting an annual income of US $50,000-$74,999 or >US $75,000 were associated with the use of eHealth for information seeking. For Generation X, being female, having attained some college or a college degree, reporting an annual income of US $50,000-$74,999 or >US $75,000, better self-reported health, and completing the survey in 2022 (vs 2018; odds ratio [OR] 1.80, 95% CI 1.11-2.91) were associated with the use of eHealth for information seeking. For baby boomers, being female, being older, attaining a high school degree, attaining some college or a college degree, reporting an annual income of US $50,000-$74,999 or >US $75,000, and completing the survey in 2020 (OR 1.56, 95% CI 1.15-2.12) and 2022 (OR 4.04, 95% CI 2.77-5.87) were associated with the use of eHealth for information seeking. Among the silent generation, being older, attaining some college or a college degree, reporting an annual income of US $50,000-$74,999 or >US $75,000, and completing the survey in 2022 (OR 5.76, 95% CI 3.05-10.89) were associated with the use of eHealth for information seeking.
Baby boomers may have made the most gains in using eHealth for information seeking over time. The race and ethnicity findings, or lack thereof, may indicate a reduction in racial and ethnic disparities. Disparities based on sex, education, and income remained consistent across all age groups. This aligns with health disparities literature focused on individuals with lower socioeconomic status, and more recently on men who are less likely to seek health care compared to women.
尽管电子健康具有潜在益处,但在电子健康的使用方面存在社会人口统计学方面的差异,这有可能进一步扩大健康公平差距。文献一致表明年龄和教育与电子健康的使用有关,而种族和民族差异的研究结果则存在差异。然而,由于 COVID-19 大流行,医疗保健互动转向基于网络的模式,以前的差异可能已经缩小。
本研究旨在通过 3 个时间点提供对导致使用电子健康进行信息搜索的健康公平差距的社会人口统计学差异的最新研究,以更新相关研究。
本研究的数据来自于全国代表性的 2018 年(n=3504)、2020 年(n=3865)和 2022 年(n=6252)的健康信息国家趋势调查时间点。使用逻辑回归分析种族和民族、性别、年龄、教育、收入、健康状况和调查年份对电子健康用于信息搜索的使用情况的影响。鉴于年龄与因变量的一致关联,分析按年龄队列(千禧一代、X 世代、婴儿潮一代和沉默一代)分层,以比较年龄相似的个体。
对于千禧一代,女性、获得一些大学或大学学位、以及报告年收入为 US $50,000-$74,999 或>US $75,000 与使用电子健康进行信息搜索有关。对于 X 世代,女性、获得一些大学或大学学位、报告年收入为 US $50,000-$74,999 或>US $75,000、自我报告健康状况较好以及在 2022 年(与 2018 年相比;优势比 [OR] 1.80,95%CI 1.11-2.91)完成调查与使用电子健康进行信息搜索有关。对于婴儿潮一代,女性、年龄较大、获得高中文凭、获得一些大学或大学学位、报告年收入为 US $50,000-$74,999 或>US $75,000 以及在 2020 年(OR 1.56,95%CI 1.15-2.12)和 2022 年(OR 4.04,95%CI 2.77-5.87)完成调查与使用电子健康进行信息搜索有关。在沉默一代中,年龄较大、获得一些大学或大学学位、报告年收入为 US $50,000-$74,999 或>US $75,000 以及在 2022 年(OR 5.76,95%CI 3.05-10.89)完成调查与使用电子健康进行信息搜索有关。
婴儿潮一代可能随着时间的推移在使用电子健康进行信息搜索方面取得了最大的进展。种族和民族的发现或缺乏发现可能表明种族和民族差异有所缩小。基于性别、教育和收入的差异在所有年龄组中仍然存在。这与关注社会经济地位较低的个体的健康差异文献以及最近关注与女性相比男性不太可能寻求医疗保健的男性健康差异文献一致。