Eze Chinwe E, Dorsch Michael P, Coe Antoinette B, Lester Corey A, Buis Lorraine R, Farris Karen B
College of Pharmacy-Clinical Pharmacy Department, University of Michigan-Ann Arbor, 428 Church Street, Ann Arbor, MI, 48109, United States, 1 7346806587.
Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA.
J Med Internet Res. 2025 Jul 31;27:e71926. doi: 10.2196/71926.
BACKGROUND: The ability to participate in digital health services such as remote blood pressure monitoring needs digital skills and knowledge known as eHealth literacy (e-HL). However, e-HL is rarely studied among those participating in remote blood pressure monitoring (RBPM). OBJECTIVE: This study assessed e-HL levels among participants with hypertension and determined the e-HL domains that predict participation in RBPM. This study provides important focus areas to increase RBPM participation. METHODS: This study was a quantitative, cross-sectional survey of people with hypertension in the United States. The survey included demographics, RBPM participation questions, and the e-HL questionnaire (eHLQ) for assessment of e-HL. The eHLQ is a 35-item, 7-domain validated questionnaire including the (1) ability to process information, (2) engagement in own health, (3) ability to actively engage with digital services, (4) feel safe and in control, (5) motivated to engage with digital services, (6) access to digital services that work, and (7) digital services that suit individual needs. The eHLQ item scores range from 1 to 4, and the higher the score, the higher the e-HL status. Descriptive statistics were used to describe the participants' demographics and e-HL status. χ2 tests were used to compare participants' characteristics between RBPM and nonRBPM groups. The Mann-Whitney U test compared the e-HL domain scores in RBPM and nonRBPM groups. Firth logistic regression was used to predict participation in RBPM. The dependent variable was participation in RBPM. The independent variables were demographics and e-HL domains. RESULTS: A total of 507 people with hypertension participated in the survey. Sixty participants were currently participating in RBPM, giving a prevalence of 11.8% (60/507). The mean age of RBPM participants was 46.2 (SD 14.7) years and nonRBPM was 62 (SD 13.7) years (P<.001). The e-HL scores in all 7 domains were significantly higher for the RBPM group than the nonRBPM group. Among the e-HL domains, higher scores in digital services that suit individual needs (domain 7) were the only predictor of RBPM participation (adjusted odds ratio 2.84, 95% CI 1.002-8.84) adjusted for age, sex, and race. CONCLUSIONS: Digital services that are tailored to individual patients' needs are more likely to result in participation in RBPM.
背景：参与远程血压监测等数字健康服务的能力需要数字技能和知识，即电子健康素养（e-HL）。然而，在参与远程血压监测（RBPM）的人群中，对电子健康素养的研究很少。 目的：本研究评估了高血压患者的电子健康素养水平，并确定了预测参与RBPM的电子健康素养领域。本研究为提高RBPM的参与度提供了重要的重点领域。 方法：本研究是对美国高血压患者进行的一项定量横断面调查。该调查包括人口统计学信息、RBPM参与问题以及用于评估电子健康素养的电子健康素养问卷（eHLQ）。eHLQ是一份包含35个项目、7个领域的有效问卷，包括（1）信息处理能力，（2）自身健康参与度，（3）积极参与数字服务的能力，（4）感到安全并能掌控，（5）参与数字服务的积极性，（6）获得有效的数字服务，以及（7）符合个人需求的数字服务。eHLQ项目得分范围为1至4分，得分越高，电子健康素养水平越高。描述性统计用于描述参与者的人口统计学信息和电子健康素养状况。χ2检验用于比较RBPM组和非RBPM组参与者的特征。Mann-Whitney U检验比较RBPM组和非RBPM组的电子健康素养领域得分。Firth逻辑回归用于预测参与RBPM的情况。因变量是参与RBPM。自变量是人口统计学信息和电子健康素养领域。 结果：共有507名高血压患者参与了调查。60名参与者目前正在参与RBPM，患病率为11.8%（60/507）。RBPM参与者的平均年龄为46.2（标准差14.7）岁，非RBPM参与者的平均年龄为62（标准差13.7）岁（P<0.001）。RBPM组在所有7个领域的电子健康素养得分均显著高于非RBPM组。在电子健康素养领域中，在符合个人需求的数字服务（领域7）中得分较高是调整年龄、性别和种族后参与RBPM的唯一预测因素（调整后的优势比为2.84，95%置信区间为1.002-8.84）。 结论：根据个体患者需求定制的数字服务更有可能促使患者参与RBPM。
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