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Optimizing Self-Monitoring in a Digital Weight Loss Intervention (Spark): Protocol for a Factorial Randomized Trial.

Michele L Patel¹, Abby C King^1,2, Lisa G Rosas^2,3

¹Department of Medicine, Stanford Prevention Research Center, School of Medicine, Stanford University, Palo Alto, CA, United States.

JMIR Research Protocols

|September 23, 2025

Summary

This summary is machine-generated.

This study identifies effective self-monitoring strategies for digital weight loss interventions. Findings will optimize patient effort and maximize weight loss outcomes by pinpointing key components.

Keywords:

RCT behavior change behavioral obesity treatment digital health intervention multiphase optimization strategy obesity randomized controlled trial self-monitoring tracking weight loss

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Area of Science:

Behavioral Science
Digital Health
Obesity Treatment

Background:

Self-monitoring is crucial for obesity treatment, involving tracking diet, activity, and weight.
The optimal combination of self-monitoring strategies for maximizing weight loss remains undetermined.
The multiphase optimization strategy framework identifies effective intervention components and minimizes patient burden.

Purpose of the Study:

To examine the unique and combined effects of tracking dietary intake, steps, and body weight on weight loss.
To identify the most effective self-monitoring strategies within a digital weight loss intervention.

Main Methods:

An optimization-randomized clinical trial (Spark) with a 2x2x2 full factorial design involving 176 US adults with overweight or obesity.
Participants received 0-3 self-monitoring strategies (diet, steps, weight) in a 6-month digital intervention using commercial tools.
Primary outcome: weight change from baseline to 6 months; secondary outcomes include BMI, caloric intake, diet quality, physical activity, and quality of life.

Main Results:

Recruitment occurred from September 2023 to November 2024; data collection concluded in June 2025.
Data analysis is currently ongoing.
Results will elucidate the impact of individual and combined self-monitoring strategies on weight loss.

Conclusions:

This trial will identify the "active ingredients" of self-monitoring in digital weight loss interventions.
Findings will inform optimized interventions, maximizing weight loss and minimizing patient burden.
Exploration of subgroup benefits from specific strategies will personalize treatment approaches.