Reinwand Dominique A, Schulz Daniela N, Crutzen Rik, Kremers Stef Pj, de Vries Hein
CAPHRI School for Public Health and Primary Care, Department of Health Promotion, Maastricht University, Maastricht, Netherlands.
J Med Internet Res. 2015 May 11;17(5):e115. doi: 10.2196/jmir.3932.
Computer-tailored eHealth interventions to improve health behavior have been demonstrated to be effective and cost-effective if they are used as recommended. However, different subgroups may use the Internet differently, which might also affect intervention use and effectiveness. To date, there is little research available depicting whether adherence to intervention recommendations differs according to personal characteristics.
The aim was to assess which personal characteristics are associated with using an eHealth intervention as recommended.
A randomized controlled trial was conducted among a sample of the adult Dutch population (N=1638) testing an intervention aimed at improving 5 healthy lifestyle behaviors: increasing fruit and vegetable consumption, increasing physical activity, reducing alcohol intake, and promoting smoking cessation. Participants were asked to participate in those specific online modules for which they did not meet the national guideline(s) for the respective behavior(s). Participants who started with fewer than the recommended number of modules of the intervention were defined as users who did not follow the intervention recommendation.
The fewer modules recommended to participants, the better participants adhered to the intervention modules. Following the intervention recommendation increased when participants were older (χ(2)1=39.8, P<.001), female (χ(2)1=15.8, P<.001), unemployed (χ(2)1=7.9, P=.003), ill (χ(2)1=4.5, P=.02), or in a relationship (χ(2)1=7.8, P=.003). No significant relevant differences were found between groups with different levels of education, incomes, or quality of life.
Our findings indicate that eHealth interventions were used differently by subgroups. The more frequent as-recommended intervention use by unemployed, older, and ill participants may be an indication that these eHealth interventions are attractive to people with a greater need for health care information. Further research is necessary to make intervention use more attractive for people with unhealthy lifestyle patterns.
计算机定制的电子健康干预措施若按推荐使用,已被证明能有效改善健康行为且具有成本效益。然而,不同亚组使用互联网的方式可能不同,这也可能影响干预措施的使用和效果。迄今为止,几乎没有研究描述根据个人特征,对干预建议的依从性是否存在差异。
评估哪些个人特征与按推荐使用电子健康干预措施相关。
在荷兰成年人群样本(N = 1638)中进行了一项随机对照试验,测试一项旨在改善5种健康生活方式行为的干预措施:增加水果和蔬菜摄入量、增加身体活动、减少酒精摄入以及促进戒烟。要求参与者参与那些他们未达到相应行为国家指南的特定在线模块。开始时使用少于推荐数量干预模块的参与者被定义为未遵循干预建议的使用者。
推荐给参与者的模块越少,参与者对干预模块的依从性越好。当参与者年龄较大(χ(2)1 = 39.8,P <.001)、女性(χ(2)1 = 15.8,P <.001)、失业(χ(2)1 = 7.9,P =.003)、生病(χ(2)1 = 4.5,P =.02)或处于恋爱关系中(χ(2)1 = 7.8,P =.003)时,遵循干预建议的情况会增加。在不同教育水平、收入或生活质量的组之间未发现显著的相关差异。
我们的研究结果表明,不同亚组使用电子健康干预措施的方式不同。失业、年龄较大和生病的参与者更频繁地按推荐使用干预措施,这可能表明这些电子健康干预措施对更需要医疗保健信息的人具有吸引力。有必要进行进一步研究,以使干预措施对有不健康生活方式模式的人更具吸引力。