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Published on: May 31, 2021
Evaluation of Five Novel Intervention Components in Online Obesity Treatment: Outcomes of a Randomized Factorial
J Graham Thomas1,2, Carly M Goldstein1,2, Dale S Bond3
1Weight Control and Diabetes Research Center, The Miriam Hospital, Providence, Rhode Island, USA.
Objective:
This study aimed to optimize weight loss outcomes in an online behavioral obesity treatment program by evaluating the effects of five novel intervention components using a factorial experiment informed by the multiphase optimization strategy framework.
Methods:
A randomized factorial experiment tested 12-month weight loss resulting from an established online obesity treatment program with randomization to zero to five novel intervention components (interactive video feedback, tailored intervention to promote physical activity, skills for dysregulated eating, virtual reality skills training, and social support with friendly competition).
Results:
Adults (N = 384; 83% female, 12% male, 5% another sex/gender or did not disclose; 23% racial and/or ethnic minority) with (mean ± SD) age of 53.5 ± 11.7 years and BMI of 35.0 ± 6.1 kg/m2 were randomized. No intervention component independently improved weight loss (p values > 0.199). Interaction terms (p values < 0.01) suggest the combination of interactive video feedback, skills for dysregulated eating, and social support with friendly competition improved weight loss. Mediation analysis indicated that social support and dysregulated eating interventions influenced weight loss outcomes through improvements in social support for physical activity and dietary quality.
Conclusions:
This study identified a combination of intervention components that may improve weight loss outcomes compared to the established online treatment program.
Trial Registration:
ClinicalTrials.gov identifier NCT04520256.
Insights
A combination of interactive video feedback, dysregulated eating skills, and social support significantly improved weight loss in an online obesity program. This finding offers a new approach to optimizing digital health interventions for weight management.
Area of Science:
- Behavioral science
- Digital health
- Obesity treatment
Background:
- Obesity is a complex health issue requiring effective, scalable treatment solutions.
- Online behavioral programs offer accessibility but require optimization for better outcomes.
- The multiphase optimization strategy (MOST) framework guides efficient intervention development.
Purpose of the Study:
- To optimize weight loss in an online behavioral obesity treatment program.
- To evaluate the impact of five novel intervention components.
- To identify effective combinations of interventions using a factorial experiment.
Main Methods:
- A randomized factorial experiment tested 12-month weight loss.
- Participants were randomized to zero to five novel components.
- Components included interactive video feedback, physical activity tailoring, dysregulated eating skills, virtual reality training, and social support.
Main Results:
- No single component independently improved weight loss.
- A combination of interactive video feedback, dysregulated eating skills, and social support significantly improved weight loss (p < 0.01).
- Interventions influenced weight loss through improved social support for physical activity and dietary quality.
Conclusions:
- A specific combination of intervention components can enhance weight loss outcomes.
- This optimized approach may offer a more effective online obesity treatment.
- Findings support the use of MOST for developing targeted digital health interventions.
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