eHealth Research Institute, School of Management, Harbin Institute of Technology, Harbin, China.
Center for Health Information & Decision Systems, Department of Decision, Operations, and Information Technologies, Robert H Smith School of Business, University of Maryland, College Park, MD, United States.
JMIR Mhealth Uhealth. 2020 Aug 10;8(8):e17709. doi: 10.2196/17709.
Mobile technology for health (mHealth) interventions are increasingly being used to help improve self-management among patients with diabetes; however, these interventions have not been adopted by a large number of patients and often have high dropout rates. Patient personality characteristics may play a critical role in app adoption and active utilization, but few studies have focused on addressing this question.
This study aims to address a gap in understanding of the relationship between personality traits and mHealth treatment for patients with diabetes. We tested the role of the five-factor model of personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) in mHealth adoption preference and active utilization.
We developed an mHealth app (DiaSocial) aimed to encourage diabetes self-management. We recruited 98 patients with diabetes-each patient freely chose whether to receive the standard care or the mHealth app intervention. Patient demographic information and patient personality characteristics were assessed at baseline. App usage data were collected to measure user utilization of the app. Patient health outcomes were assessed with lab measures of glycated hemoglobin (HbA level). Logistic regression models and linear regression were employed to explore factors predicting the relationship between mHealth use (adoption and active utilization) and changes in health outcome.
Of 98 study participants, 46 (47%) downloaded and used the app. Relatively younger patients with diabetes were 9% more likely to try and use the app (P=.02, odds ratio [OR] 0.91, 95% CI 0.85-0.98) than older patients with diabetes were. Extraversion was negatively associated with adoption of the mHealth app (P=.04, OR 0.71, 95% CI 0.51-0.98), and openness to experience was positively associated with adoption of the app (P=.03, OR 1.73, 95% CI 1.07-2.80). Gender (P=.43, OR 0.66, 95% CI 0.23-1.88), education (senior: P=.99, OR 1.00, 95% CI 0.32-3.11; higher: P=.21, OR 2.51, 95% CI 0.59-10.66), and baseline HbA level (P=.36, OR 0.79, 95% CI 0.47-1.31) were not associated with app adoption. Among those who adopted the app, a low education level (senior versus primary P=.003; higher versus primary P=.03) and a high level of openness to experience (P=.048, OR 2.01, 95% CI 1.01-4.00) were associated with active app utilization. Active users showed a significantly greater decrease in HbA level than other users (ΔHbA=-0.64, P=.05).
This is one of the first studies to investigate how different personality traits influence the adoption and active utilization of an mHealth app among patients with diabetes. The research findings suggest that personality is a factor that should be considered when trying to identify patients who would benefit the most from apps for diabetes management.
移动医疗技术（mHealth）干预措施正越来越多地被用于帮助改善糖尿病患者的自我管理；然而，这些干预措施并没有被大量患者采用，并且经常出现高退出率。患者的个性特征可能在应用程序的采用和积极利用中起着至关重要的作用，但很少有研究关注这个问题。
本研究旨在填补理解个性特征与糖尿病患者的 mHealth 治疗之间关系的空白。我们测试了五因素人格模型（开放性、尽责性、外向性、宜人性和神经质）在 mHealth 采用偏好和积极利用中的作用。
我们开发了一个 mHealth 应用程序（DiaSocial），旨在鼓励糖尿病自我管理。我们招募了 98 名糖尿病患者-每个患者都可以自由选择接受标准护理或 mHealth 应用程序干预。在基线时评估了患者的人口统计学信息和患者的个性特征。收集应用程序使用数据来衡量用户对应用程序的使用情况。使用实验室测量的糖化血红蛋白（HbA 水平）来评估患者的健康结果。采用逻辑回归模型和线性回归来探讨预测 mHealth 使用（采用和积极利用）与健康结果变化之间关系的因素。
在 98 名研究参与者中，有 46 名（47%）下载并使用了该应用程序。相对较年轻的糖尿病患者尝试和使用该应用程序的可能性比年长的糖尿病患者高 9%（P=.02，优势比[OR]0.91，95%置信区间[CI]0.85-0.98）。外向性与 mHealth 应用程序的采用呈负相关（P=.04，OR 0.71，95%CI 0.51-0.98），开放性与应用程序的采用呈正相关（P=.03，OR 1.73，95%CI 1.07-2.80）。性别（P=.43，OR 0.66，95%CI 0.23-1.88）、教育（高中：P=.99，OR 1.00，95%CI 0.32-3.11；更高：P=.21，OR 2.51，95%CI 0.59-10.66）和基线 HbA 水平（P=.36，OR 0.79，95%CI 0.47-1.31）与应用程序的采用无关。在那些采用该应用程序的患者中，低教育水平（高中与初级 P=.003；更高与初级 P=.03）和高开放性（P=.048，OR 2.01，95%CI 1.01-4.00）与积极使用应用程序有关。积极用户的 HbA 水平下降幅度明显大于其他用户（ΔHbA=-0.64，P=.05）。
这是首批研究个性特征如何影响糖尿病患者对 mHealth 应用程序的采用和积极利用的研究之一。研究结果表明，在试图确定最能从糖尿病管理应用程序中受益的患者时，个性是一个需要考虑的因素。
