Turner-McGrievy Gabrielle, Tate Deborah
Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States.
J Med Internet Res. 2011 Dec 20;13(4):e120. doi: 10.2196/jmir.1841.
Previous interventions have shown promising results using theory-based podcasts to deliver a behavioral weight-loss intervention.
The objective of our study was to examine whether a combination of podcasting, mobile support communication, and mobile diet monitoring can assist people in weight loss.
In this 6-month, minimal contact intervention, overweight (n = 96, body mass index 32.6 kg/m(2)) adults were recruited through television advertisements and email listservs and randomly assigned to Podcast-only or Podcast+Mobile groups. Both groups received 2 podcasts per week for 3 months and 2 minipodcasts per week for months 3-6. In addition to the podcasts, the Podcast+Mobile group was also instructed to use a diet and physical activity monitoring application (app) on their mobile device and to interact with study counselors and other participants on Twitter.
Weight loss did not differ by group at 6 months: mean -2.7% (SD 5.6%) Podcast+Mobile, n = 47; mean -2.7% (SD 5.1%) Podcast, n = 49; P = .98. Days/week of reported diet monitoring did not differ between Podcast+Mobile (mean 2.3, SD 1.9 days/week) and Podcast groups (mean 1.9, SD 1.7 days/week; P = .28) but method of monitoring did differ. Podcast+Mobile participants were 3.5 times more likely than the Podcast group to use an app to monitor diet (P = .01), whereas the majority of Podcast participants reported using the Web (14/41, 34%) or paper (12/41, 29%). There were more downloads per episode in the Podcast+Mobile group (1.4/person) than in the Podcast group (1.1/person; P < .001). The number of podcasts participants reported downloading over the 6-month period was significantly moderately correlated with weight loss in both the Podcast+Mobile (r = -.46, P = .001) and the Podcast (r = -.53, P < .001) groups. Podcast+Mobile participants felt more user control at 3 months (P = .02), but not at 6 months, and there was a trend (P = .06) toward greater elaboration among Podcast+Mobile participants. There were significant differences in reported source of social support between groups. More Podcast participants relied on friends (11/40, 28% vs 4/40, 10%; P = .045) whereas Podcast+Mobile participants relied on online sources (10/40, 25% vs 0/40; P = .001).
Results confirm and extend previous findings showing a minimally intensive weight-loss intervention can be delivered via podcast, but prompting and mobile communication via Twitter and monitoring app without feedback did not enhance weight loss.
Clinicaltrials.gov NCT01139255; http://clinicaltrials.gov/ct2/show/NCT01139255 (Archived by WebCite at http://www.webcitation.org/625OjhiDy).
以往的干预措施显示,使用基于理论的播客进行行为减肥干预取得了有前景的成果。
我们研究的目的是检验播客、移动支持通信和移动饮食监测相结合是否能帮助人们减肥。
在这项为期6个月的低接触干预中,通过电视广告和电子邮件列表招募超重(n = 96,体重指数32.6 kg/m²)成年人,并随机分配到仅播客组或播客+移动组。两组均每周接收2个播客,共3个月,第3至6个月每周接收2个迷你播客。除了播客,播客+移动组还被指示在其移动设备上使用饮食和身体活动监测应用程序(应用),并在推特上与研究顾问和其他参与者互动。
6个月时两组体重减轻情况无差异:播客+移动组平均减轻2.7%(标准差5.6%),n = 47;播客组平均减轻2.7%(标准差5.1%),n = 49;P = 0.98。播客+移动组(平均每周2.3天,标准差1.9天/周)和播客组(平均每周1.9天,标准差1.7天/周;P = 0.28)报告的每周饮食监测天数无差异,但监测方法不同。播客+移动组参与者使用应用程序监测饮食的可能性是播客组的3.5倍(P = 0.01),而大多数播客组参与者报告使用网络(14/41,34%)或纸质记录(12/41,29%)。播客+移动组每集的下载量(1.4/人)高于播客组(1.1/人;P < 0.001)。在6个月期间,参与者报告下载的播客数量与播客+移动组(r = -0.46,P = 0.001)和播客组(r = -0.53,P < 0.001)的体重减轻均显著中度相关。播客+移动组参与者在3个月时感觉用户控制感更强(P = 0.02),但6个月时没有,并且播客+移动组参与者有更深入思考的趋势(P = 0.06)。两组报告的社会支持来源存在显著差异。更多播客组参与者依赖朋友(11/40,28%对4/40,10%;P = 0.045),而播客+移动组参与者依赖在线来源(10/40,25%对0/40;P = 0.001)。
结果证实并扩展了先前的研究结果,表明可以通过播客进行低强度的减肥干预,但通过推特进行的提示和移动通信以及无反馈的监测应用程序并没有增强减肥效果。
Clinicaltrials.gov NCT01139255;http://clinicaltrials.gov/ct2/show/NCT01139255(由WebCite存档于http://www.webcitation.org/625OjhiDy)