Weight loss intervention adherence and factors promoting adherence: a meta-analysis.

Lemstra, Mark; Bird, Yelena; Nwankwo, Chijioke; Rogers, Marla; Moraros, John

doi:10.2147/PPA.S103649

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Weight loss intervention adherence and factors promoting adherence: a meta-analysis.

Author(s): Mark Lemstra ¹ , Yelena Bird ² , Chijioke Nwankwo ² , Marla Rogers ³ , John Moraros ²

Publication date (Electronic): 2016

Journal: Patient preference and adherence

Publisher: Informa UK Limited

Keywords: community based, obesity, program adherence, social support

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Abstract

Adhering to weight loss interventions is difficult for many people. The majority of those who are overweight or obese and attempt to lose weight are simply not successful. The objectives of this study were 1) to quantify overall adherence rates for various weight loss interventions and 2) to provide pooled estimates for factors associated with improved adherence to weight loss interventions.

Most cited references 44

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Adherence to long-term therapies: evidence for action.

Sabina De Geest, Eduardo Sabate (2004)

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The statistical basis of meta-analysis.

J. L. Fleiss (1993)

Two models for study-to-study variation in a meta-analysis are presented, critiqued and illustrated. One, the fixed effects model, takes the studies being analysed as the universe of interest; the other, the random effects model, takes these studies as representing a sample from a larger population of possible studies. With emphasis on clinical trials, this paper illustrates in some detail the application of both models to three summary measures of the effect of an experimental intervention versus a control: the standardized difference for comparing two means, and the relative risk and odds ratio for comparing two proportions.

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Randomized clinical trials and observational studies: guidelines for assessing respective strengths and limitations.

E Hannan (2008)

The 2 primary types of studies that are used to test new drugs or procedures or compare competing drugs or types of procedures are randomized clinical trials (RCTs) and observational studies (OS). Although it would appear that RCTs always trump OS because they eliminate selection bias, there are many possible limitations to both types of studies, and these limitations must be carefully assessed when comparing the results of RCTs and OS. This state-of-the art review describes these limitations and discusses how to assess the validity of RCTs and OS that yield different conclusions regarding the relative merit of competing treatments/interventions.