在行为减肥计划的维护阶段,参与数字自我监测的模式和预测因素:定量研究
Nicole Crane1, Charlotte Hagerman1, Olivia Horgan1
1Center for Weight, Eating, and Lifestyle Science, Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, United States.
JMIR mHealth and uHealth
|July 18, 2023
概括
许多成年人在减肥维护期间,特别是饮食和体重跟踪时,都在与持续的自我监测 (SM) 斗争. 诸如信息回避和权重偏差内部化等因素影响参与,这表明需要量身定制的干预措施.
科学领域:
- 行为科学是一种行为科学.
- 健康心理学健康心理学
- 数字健康数字健康
背景情况:
- 长期自我监测 (SM) 对于行为减肥 (BWL) 治疗至关重要.
- 在减肥维护 (WLM) 期间持续使用数字SM工具仍然是一个重大挑战.
- 了解影响中小企业参与的因素,可以帮助调整干预措施,以便更好地遵守.
研究的目的:
- 在WLM期间探索数字SM模式.
- 检查退出和重新参与的动态.
- 评估与体重相关的信息回避和体重偏差内部化对中小企业参与的影响.
主要方法:
- 在BWL计划中,72名成年人通过数字追踪体重,饮食和运动.
- 坚持度是通过每月追踪每个行为的几天的百分比来衡量.
- 统计分析包括重复测量ANOVA和多层次建模,以评估坚持趋势和个人层面的因素影响.
主要成果:
- 在WLM期间观察到高坚持 (≥50%天) 运动 (61%),体重 (40%) 和饮食 (21%).
- 对所有目标的坚持随着时间的推移而下降,而运动跟踪比体重或饮食更晚.
- 与体重相关的信息回避预测了更快的饮食SM下降,而高体重偏差内部化与更高体重SM率相关.
结论:
- 在WLM期间遵守每日SM通常很低,特别是在饮食和体重方面.
- 与体重相关的信息回避和体重偏差的内部化是SM参与的潜在指标.
- 干预措施应纳入战略,以支持在WLM期间面临脱风险的参与者.
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