Department of Movement and Sports Sciences, Faculty of Medicine and Health, Ghent University, Ghent, Belgium.
Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium.
JMIR Mhealth Uhealth. 2022 Jan 31;10(1):e30583. doi: 10.2196/30583.
Digital health interventions have gained momentum to change health behaviors such as physical activity (PA) and sedentary behavior (SB). Although these interventions show promising results in terms of behavior change, they still suffer from high attrition rates, resulting in a lower potential and accessibility. To reduce attrition rates in the future, there is a need to investigate the reasons why individuals stop using the interventions. Certain demographic variables have already been related to attrition; however, the role of psychological determinants of behavior change as predictors of attrition has not yet been fully explored.
The aim of this study was to examine when, which, and why users stopped using a digital health intervention. In particular, we aimed to investigate whether psychological determinants of behavior change were predictors for attrition.
The sample consisted of 473 healthy adults who participated in the intervention MyPlan 2.0 to promote PA or reduce SB. The intervention was developed using the health action process approach (HAPA) model, which describes psychological determinants that guide individuals in changing their behavior. If participants stopped with the intervention, a questionnaire with 8 question concerning attrition was sent by email. To analyze when users stopped using the intervention, descriptive statistics were used per part of the intervention (including pre- and posttest measurements and the 5 website sessions). To analyze which users stopped using the intervention, demographic variables, behavioral status, and HAPA-based psychological determinants at pretest measurement were investigated as potential predictors of attrition using logistic regression models. To analyze why users stopped using the intervention, descriptive statistics of scores to the attrition-related questionnaire were used.
The study demonstrated that 47.9% (227/473) of participants stopped using the intervention, and drop out occurred mainly in the beginning of the intervention. The results seem to indicate that gender and participant scores on the psychological determinants action planning, coping planning, and self-monitoring were predictors of first session, third session, or whole intervention completion. The most endorsed reasons to stop using the intervention were the time-consuming nature of questionnaires (55%), not having time (50%), dissatisfaction with the content of the intervention (41%), technical problems (39%), already meeting the guidelines for PA/SB (31%), and, to a lesser extent, the experience of medical/emotional problems (16%).
This study provides some directions for future studies. To decrease attrition, it will be important to personalize interventions on different levels, questionnaires (either for research purposes or tailoring) should be kept to a minimum especially in the beginning of interventions by, for example, using objective monitoring devices, and technical aspects of digital health interventions should be thoroughly tested in advance.
ClinicalTrials.gov NCT03274271; https://clinicaltrials.gov/ct2/show/NCT03274271.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-019-3456-7.
数字健康干预措施已逐渐兴起,以改变身体活动(PA)和久坐行为(SB)等健康行为。尽管这些干预措施在行为改变方面显示出了有希望的结果,但它们仍然存在高流失率的问题,从而降低了潜在的和可及性。为了减少未来的流失率,有必要调查个人停止使用干预措施的原因。某些人口统计学变量已经与流失有关;然而,行为改变的心理决定因素作为流失的预测因素的作用尚未得到充分探讨。
本研究旨在探讨用户何时、为何停止使用数字健康干预措施。特别是,我们旨在调查行为改变的心理决定因素是否是流失的预测因素。
该样本由 473 名参加 MyPlan 2.0 促进 PA 或减少 SB 的健康成年人组成。该干预措施是使用健康行动过程方法(HAPA)模型开发的,该模型描述了指导个人改变行为的心理决定因素。如果参与者停止使用干预措施,将通过电子邮件发送一份包含 8 个关于流失问题的问卷。为了分析用户何时停止使用干预措施,按干预措施的各个部分(包括预测试和后测试测量以及 5 个网站会话)使用描述性统计进行分析。为了分析哪些用户停止使用干预措施,使用逻辑回归模型调查了前测测量时的人口统计学变量、行为状态和基于 HAPA 的心理决定因素,以确定流失的潜在预测因素。为了分析用户停止使用干预措施的原因,使用与流失相关的问卷的分数的描述性统计进行分析。
该研究表明,47.9%(227/473)的参与者停止使用干预措施,流失主要发生在干预措施的开始阶段。结果似乎表明,性别和参与者在心理决定因素行动计划、应对计划和自我监测方面的得分是第一次会话、第三次会话或整个干预完成的预测因素。停止使用干预措施的最主要原因是问卷耗时(55%)、没有时间(50%)、对干预内容不满意(41%)、技术问题(39%)、已经达到 PA/SB 指南(31%),以及在较小程度上,经历医疗/情绪问题(16%)。
本研究为未来的研究提供了一些方向。为了减少流失,个性化干预措施在不同层面上非常重要,尤其是在干预措施的开始阶段,应尽量减少问卷(无论是用于研究目的还是定制目的),例如使用客观监测设备,并且应提前彻底测试数字健康干预措施的技术方面。
ClinicalTrials.gov NCT03274271; https://clinicaltrials.gov/ct2/show/NCT03274271.
国际注册报告标识符(IRRID):RR2-10.1186/s13063-019-3456-7.