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.

Obesity (Silver Spring, Md.)
|September 19, 2025
PubMed
Abstract

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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