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减肥效果与参与移动行为改变干预之间的关系:回顾性分析。

The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis.

机构信息

Academic Research, Noom Inc, New York, NY, United States.

Department of Clinical Psychology, Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY, United States.

出版信息

JMIR Mhealth Uhealth. 2021 Nov 8;9(11):e30622. doi: 10.2196/30622.

DOI:10.2196/30622
PMID:34747706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8663454/
Abstract

BACKGROUND

There is large variance in weight loss outcomes of digital behavior change interventions (DBCIs). It has been suggested that different patterns of engagement in the program could be responsible for this variance in outcomes. Previous studies have found that the amount of engagement on DBCIs, such as the number of meals logged or articles read, is positively associated with weight loss.

OBJECTIVE

This retrospective study extends previous research by observing how important weight loss outcomes (high weight loss: 10% or greater body weight loss; moderate weight loss: between 5% to 10%; stable weight: 0 plus or minus 1%) are associated with engagement on a publicly available mobile DBCI (Noom) from 9 to 52 weeks.

METHODS

Engagement and weight data for eligible participants (N=11,252) were extracted from the Noom database. Engagement measures included the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week. Weight was self-reported on the program. Multiple linear regressions examined how weight loss outcome (moderate and high vs stable) was associated with each engagement measure across 3 study time periods: 9-16 weeks, 17-32 weeks, and 33-52 weeks.

RESULTS

At 9-16 weeks, among the 11,252 participants, 2594 (23.05%) had stable weight, 6440 (57.23%) had moderate weight loss, and 2218 (19.71%) had high weight loss. By 33-52 weeks, 525 (18.21%) had stable weight, 1214 (42.11%) had moderate weight loss, and 1144 (39.68%) had high weight loss. Regression results showed that moderate weight loss and high weight loss outcomes were associated with all engagement measures to a significantly greater degree than was stable weight (all P values <.001). These differences held across all time periods with the exception of exercise for the moderate weight loss category at 1 time period of 33-52 weeks. Exercise logging increased from 9 to 52 weeks regardless of the weight loss group.

CONCLUSIONS

Our results suggest that these clinically important weight loss outcomes are related to the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week both in the short-term and long-term (ie, 1 year) on Noom. This provides valuable data on engagement patterns over time on a self-directed mobile DBCI, can help inform how interventions tailor recommendations for engagement depending on how much weight individuals have lost, and raises important questions for future research on engagement in DBCIs.

摘要

背景

数字行为改变干预(DBCI)的减肥效果存在很大差异。有人认为,参与项目的不同模式可能是导致这种结果差异的原因。先前的研究发现,DBCI 的参与度(例如记录的用餐次数或阅读的文章数量)与减肥效果呈正相关。

目的

本回顾性研究通过观察在 Noom 这样一个公开的移动 DBCI 上,从第 9 周到第 52 周,重要的减肥结果(高体重减轻:体重减轻 10%或更多;中度体重减轻:5%至 10%之间;稳定体重:0 加或减 1%)与参与度的关系,扩展了先前的研究。

方法

从 Noom 数据库中提取了符合条件的参与者(N=11252)的参与度和体重数据。参与度衡量指标包括阅读的文章数量、记录的用餐次数、记录的步数、给教练的信息、记录的锻炼情况、称重和每周记录 1 餐的天数。体重是在项目中自我报告的。多项线性回归分析考察了在 3 个研究时间段内(9-16 周、17-32 周和 33-52 周),体重减轻结果(中度和高度与稳定)与每个参与度指标之间的关系。

结果

在第 9-16 周,在 11252 名参与者中,2594 名(23.05%)体重稳定,6440 名(57.23%)体重中度减轻,2218 名(19.71%)体重高度减轻。到第 33-52 周,525 名(18.21%)体重稳定,1214 名(42.11%)体重中度减轻,1144 名(39.68%)体重高度减轻。回归结果表明,中度和高度体重减轻结果与所有参与度衡量指标的相关性显著大于稳定体重(所有 P 值均<.001)。除了在 33-52 周的某个时间段内,中度体重减轻类别中的锻炼情况外,这些差异在所有时间段内均存在。锻炼记录从第 9 周到第 52 周不断增加,无论减肥组如何。

结论

我们的研究结果表明,这些临床重要的减肥结果与在 Noom 上短期和长期(即 1 年)阅读的文章数量、记录的用餐次数、记录的步数、给教练的信息、记录的锻炼情况、称重和每周记录 1 餐的天数有关。这为我们提供了关于自我指导的移动 DBCI 上随时间推移的参与模式的宝贵数据,可以帮助我们了解根据个体减轻的体重如何为参与度调整干预措施,同时也提出了关于 DBCI 参与度的未来研究的重要问题。

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3
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