Preventing the obesity epidemic by second generation tailored health communication: an interdisciplinary review.
Preventing the obesity epidemic by second generation tailored health communication: an interdisciplinary review.
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DOI：
10.2196/jmir.1409
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发表时间：
2010-06-28
影响因子：
7.4
通讯作者：
Huotari ML
中科院分区：
文献类型：
--
作者：
Enwald HP;Huotari ML
预防肥胖和与肥胖相关的健康问题是世界范围内的主要挑战。在个人层面上使用电子保健通信和通过互联网提供的信息的定制可能会提高干预措施的有效性。掌握与营养、体育活动和体重管理相关的行为是预防肥胖的主要问题，显然需要这一领域的跨学科知识。其目的是审查文献量身定制的健康沟通，并提出了一个跨学科的分析研究“第二”代量身定制的干预措施，旨在改变行为的营养，体力活动，或体重管理。对健康传播的主要电子信息源进行了文献检索。确定了选择标准，并选择了23项干预研究。内容分析集中在以下方面：研究设计，行为改变的目标，目标群体，样本量，研究长度，流失率，应用的理论，干预设计，使用的基于计算机的渠道，从剪裁的角度来看，统计上显著的结果，以及研究可能存在的偏差。然而，这不是一个结构化的荟萃分析，不能复制。在这23项研究中，21项是随机对照试验，所有研究都集中在行为改变方面：10项研究集中在营养方面的行为改变，7项集中在体力活动方面，2项集中在营养和体力活动方面，4项集中在体重管理方面。目标群体和参与者数量各不相同：8项研究包含超过500名参与者，6项研究包含少于100名参与者。大多数研究都很短; 20项研究的持续时间为6个月或更短。23项研究中有14项应用了跨理论模型，15项研究除了互联网网站（或程序）外还使用了反馈作为剪裁机制，11项研究除了电子邮件外还使用了反馈。15项研究采用自我报告，14项研究没有无信息对照组。裁缝是更有效的营养干预比身体活动和体重管理干预。在4项身体活动干预研究和3项体重管理研究中，结果是混合或负面的。使用无信息对照组似乎与测量体力活动的统计学显著组间效应有关。这种与干预设计相关的偏倚效应可以解释体力活动研究结果的差异。剪裁被证明是营养干预的有效方法，但体力活动的结果好坏参半，这与以前的研究一致。然而，不应低估可能存在的偏差的影响，例如仅依赖自我报告和没有无信息对照组的干预设计。因此，在规划干预措施和未来的荟萃分析中，偏见问题值得更多的关注。
The prevention of obesity and health concerns related to obesity are major challenges worldwide. The use of eHealth communication and the tailoring of information delivered via the Internet at the individual level may increase the effectiveness of interventions. Mastering behaviors related to nutrition, physical activity, and weight management are the main issues in preventing obesity, and the need for interdisciplinary knowledge within this area is obvious. The objectives were to review the literature on tailored health communication and to present an interdisciplinary analysis of studies on “second” generation tailored interventions aimed at behavior change in nutrition, physical activity, or weight management. A literature search was conducted of the main electronic information sources on health communication. Selection criteria were defined, and 23 intervention studies were selected. The content analysis focused on the following: study designs, objectives of behavior change, target groups, sample sizes, study lengths, attrition rates, theories applied, intervention designs, computer-based channels used, statistically significant outcomes from the perspective of tailoring, and possible biases of the studies. However, this was not a structured meta-analysis and cannot be replicated as such. Of the 23 studies, 21 were randomized controlled trials, and all focused on behavior change: 10 studies focused on behavior change in nutrition, 7 on physical activity, 2 on nutrition and physical activity, and 4 on weight management. The target groups and the number of participants varied: 8 studies included more than 500 participants, and 6 studies included less than 100. Most studies were short; the duration of 20 studies was 6 months or less. The Transtheoretical Model was applied in 14 of the 23 studies, and feedback as a tailoring mechanism was used in addition to an Internet site (or program) in 15 studies and in addition to email in 11 studies. Self-reporting was used in 15 studies, and 14 studies did not have a no-information control group. Tailoring was more effective in nutrition interventions than in physical activity and weight management interventions. The outcomes were mixed or negative in 4 studies of physical activity interventions and in 3 studies of weight management. The use of a no-information control group seemed to have been linked to statistically significant between-group effects in measuring physical activity. This bias effect related to intervention design may explain the differences in the outcomes of the physical activity studies. Tailoring was shown to have been an effective method in nutrition interventions, but the results for physical activity were mixed, which is in line with previous studies. Nevertheless, the effect of possible biases, such as relying solely on self-reports and on intervention design without a no-information control group, should not be underestimated. Thus, the issue of bias merits more attention in planning interventions and in future meta-analyses.