Relationships of the psychological influence of food and barriers to lifestyle change to weight and utilization of online weight loss tools.

The open medical informatics journal Pub Date : 2012-01-01 Epub Date: 2012-04-19 DOI:10.2174/1874431101206010009
Martin Binks, Trevor van Mierlo, Christopher L Edwards
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Abstract

Introduction: The psychological influence of food (PFS) and perceived barriers to lifestyle change (PBLC) were considered as predictors of body mass index and website tool utilization (TU) in an online weight loss program.

Materials and methodology: An archival analysis of all (N = 1361) overweight/obese (BMI M = 31.6 + 6.24 kg/m2), adult (M = 42.0 + 10.72 years) users (82.4% female) of an evidence-based, multidisciplinary Internet weight loss program was performed. Predictor variables included: PFS and PBLC, age, and longest maintained weight loss in relation to 1) BMI 2) TU.

Results: Both PBLC and PFS were correlated with baseline BMI and TU. Regression analyses indicated that only PFS independently predicted BMI (p = .0001) and TU (p = .001) when the model included all predictor variables. One-way ANOVA indicated gender differences on both PBLC and PFS scores (p = .001). Subsequent regression analyses separated by gender showed that in females PFS predicted BMI (p = .0001) and TU (p = .005). For males no variable significantly predicted BMI (p's > .05) however PBLC did predict TU (p = .008).

Conclusions: Our findings suggest that when developing online weight loss programs clinical characteristics of the user could inform website algorithms to maximize website utilization. Gender differences indicated that for women it may be important to understand how factors related to the psychological influence of food impact utilization of online weight loss programs, however, for men broader barriers to lifestyle change is an important consideration.

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食物的心理影响和改变生活方式的障碍与体重和使用在线减肥工具的关系。
介绍:在一项在线减肥计划中,食物的心理影响(PFS)和生活方式改变的感知障碍(PBLC)被认为是体重指数和网站工具利用率(TU)的预测因素:对基于证据的多学科互联网减肥计划的所有(N = 1361)超重/肥胖(体重指数 M = 31.6 + 6.24 kg/m2)成人(M = 42.0 + 10.72 岁)用户(82.4% 为女性)进行了档案分析。预测变量包括预测变量包括:PFS 和 PBLC、年龄以及与 1) BMI 2) TU 相关的最长维持减重时间:结果:PBLC 和 PFS 均与基线体重指数和 TU 相关。回归分析表明,当模型包括所有预测变量时,只有 PFS 可独立预测 BMI(p = .0001)和 TU(p = .001)。单向方差分析表明,PBLC 和 PFS 分数存在性别差异(p = .001)。随后按性别进行的回归分析表明,女性的 PFS 预测了 BMI(p = .0001)和 TU(p = .005)。对于男性来说,没有任何变量能明显预测体重指数(p>.05),但 PBLC 确实能预测 TU(p = .008):我们的研究结果表明,在开发在线减肥项目时,用户的临床特征可以为网站算法提供参考,从而最大限度地提高网站的利用率。性别差异表明,对于女性来说,了解与食物的心理影响有关的因素如何影响在线减肥计划的利用率可能很重要,然而,对于男性来说,改变生活方式的更广泛障碍是一个重要的考虑因素。
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