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Methodological quality of behavioural weight loss studies: a systematic review
S C Lemon1, M L Wang2, C F Haughton1
1UMass Worcester Prevention Research Center, Division of Preventive and Behavioral Medicine, University of Massachusetts Medical School, Worcester, MA, USA.
This review found behavioral weight loss studies to be high quality in design and measurement. However, improving statistical analysis for loss to follow-up and reporting intervention fidelity are recommended for future research.
Area of Science:
- Behavioral Science
- Obesity Research
- Clinical Trials Methodology
Background:
- Methodological rigor is crucial for evaluating the effectiveness of behavioral weight loss interventions.
- Assessing the quality of published studies informs future research and clinical practice.
Purpose of the Study:
- To systematically review the methodological quality of behavioral weight loss intervention studies in adults.
- To examine the association between study quality and statistically significant weight loss outcomes, intervention effectiveness, and sample size.
Main Methods:
- Searched PUBMED, MEDLINE, and PSYCINFO for trials published between January 2009 and December 2014, identifying 90 studies.
- Assessed methodological quality using indicators such as study design, anthropometric measurements, intent-to-treat (ITT) analysis, and loss to follow-up strategies.
- Analyzed associations between quality indicators and study outcomes, effect size, and sample size.
Main Results:
- Most studies employed randomized designs (100%), objective anthropometrics (96.7%), and ITT analysis (86.7%).
- High follow-up rates (>75%) and reporting of loss to follow-up strategies were common (62.2% and 69.9%, respectively).
- Intervention fidelity reporting (34.4%) and sampling from known populations (41.1%) were less common. Methodological quality was not associated with significant results, effect size, or sample size.
Conclusions:
- Published behavioral weight loss trials demonstrate high quality in specific areas like study design and measurement.
- Areas for improvement include more rigorous statistical approaches for handling loss to follow-up and enhanced reporting of intervention fidelity.
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