How an Online Intervention to Prevent Excessive Gestational Weight Gain Is Used and by Whom: A Randomized Controlled Process Evaluation
How an Online Intervention to Prevent Excessive Gestational Weight Gain Is Used and by Whom: A Randomized Controlled Process Evaluation
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DOI：
10.2196/jmir.3483
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发表时间：
2014-08-01
影响因子：
7.4
通讯作者：
Olson, Christine Marie
中科院分区：
文献类型：
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作者：
Demment, Margaret Mochon;Graham, Meredith Leigh;Olson, Christine Marie
背景：在线干预已成为促进健康行为的流行策略。目前，关于如何获取在线干预参与的协议很少。也不确定哪些人参与了与体重相关的在线干预，以及参与程度如何因人口统计学和体重特征而异。目的：本研究的目的是（1）描述孕妇如何参与在线干预以防止妊娠期体重过度增加，（2）确定样本中妇女的人口统计学和体重状态亚组，和（3）检查在使用干预功能的人口统计学和体重状态subgroup.Methods的差异：一个样本的种族和社会经济上不同的孕妇从美国东北部城市被分配到干预组的随机对照试验，以防止过度妊娠体重增加（n=1014）。干预网站包括以下功能：体重增加跟踪器，健康相关文章，博客，体育活动和饮食目标设定工具，以及本地资源。创建参与变量以使用潜在类分析捕获整个妊娠期间特征使用的量、一致性和模式。还使用潜在类别分析创建了人口统计学/体重状态亚组。使用卡方分析检查了人口统计学/体重状况亚组之间的参与差异。（13.02%，132/1014），“中等用户”（14.00%，142/1014），“持续使用体重追踪器”（14.99%，152/1014）;“几乎一致的体重追踪器用户”（21.99%，223/1014）、“不一致的体重追踪器使用者”（15.98%，162/1014）和“非使用者”（20.02%，203/1014）。出现了四个人口统计学/体重状况亚组：三个少数民族和一个白色。有不同的人口统计学/体重状况亚组的参与模式。超级使用者更可能属于白色亚组，而非使用者更可能属于少数亚组。然而，在少数群体中，约有三分之一的女性一直或几乎一直使用体重追踪器。（黑人，年轻女性，32.2%，67/208;黑人，较重女性，37.9%，50/132;西班牙裔女性，27.4%，32/117）。虽然白色和高收入妇女的参与程度一般较高，但根据衡量标准，少数民族和低收入妇女的参与程度仍然很高。
Background: Online interventions have emerged as a popular strategy to promote healthy behaviors. Currently, there is little agreement about how to capture online intervention engagement. It is also uncertain who engages with weight-related online interventions and how engagement differs by demographic and weight characteristics.Objective: The objectives of this study were to (1) characterize how pregnant women engaged with features of an online intervention to prevent excessive gestational weight gain, (2) identify demographic and weight status subgroups of women within the sample, and (3) examine differences in use of intervention features across the demographic and weight status subgroups.Methods: A sample of racially and socioeconomically diverse pregnant women from a northeastern US city was assigned to the intervention group in a randomized controlled trial to prevent excessive gestational weight gain (n=1014). The intervention website included these features: weight-gain tracker, health-related articles, blogs, physical activity and diet goal-setting tools, and local resources. Engagement variables were created to capture the amount, consistency, and patterns of feature use across pregnancy using latent class analysis. Demographic/weight status subgroups were also created using latent class analysis. Differences in engagement across the demographic/weight status subgroups were examined using chi-square analysis.Results: Six engagement patterns emerged: "super-users" (13.02%, 132/1014), "medium-users" (14.00%, 142/1014), "consistent weight-tracker users" (14.99%, 152/1014); "almost consistent weight-tracker users" (21.99%, 223/1014), "inconsistent weight-tracker users" (15.98%, 162/1014), and "non-users" (20.02%, 203/1014). Four demographic/weight status subgroups emerged: three minority and one white. There were different engagement patterns by demographic/weight status subgroups. Super-users were more likely to be in the white subgroup, while non-users were more likely to be in the minority subgroups. However, around a third of women in minority subgroups were consistently or almost consistently engaging with the weight-tracker (black, young women, 32.2%, 67/208; black, heavier women, 37.9%, 50/132; Hispanic women, 27.4%, 32/117).Conclusions: While white and higher income women had higher engagement in general, depending on the measure, there was still considerable engagement by the minority and low-income women.