Optimizing a Digital Mindfulness-Based Intervention to Reduce Risk Factors for Disordered Eating: A...

Area of Science:

• Digital health interventions
• Mindfulness-based interventions (MBIs)
• Eating disorder risk factors

Background:

• Digital MBIs show promise for reducing disordered eating risk factors but have variable effects and suboptimal engagement.
• Intervention length, complexity, and content variation may hinder engagement.
• Optimizing digital interventions requires identifying effective and engaging components.

Purpose of the Study:

• To assess the feasibility of a factorial trial using the Multiphase Optimization Strategy (MOST) to evaluate digital MBI components.
• To determine if adding emotion regulation (ER) and self-compassion (SC) enhances decentred awareness and acceptance (DA+A) in a digital MBI.

Main Methods:

• A 2x2 factorial design tested four conditions: DA+A with or without ER and/or SC.
• 92 participants (M age=21.1 years) were randomized for 3-week access.
• Feasibility (recruitment, retention, engagement, acceptability) and intervention outcomes were assessed.

Main Results:

• Recruitment exceeded targets; retention was acceptable (58-59%).
• All planned analyses were feasible; engagement met criteria (77-85% completion).
• Acceptability was high (M=4.28/5), with participants valuing reminders and offering design suggestions.

Conclusions:

• Findings support progression to a fully powered optimization trial.
• The Multiphase Optimization Strategy (MOST) can be embedded within pilot studies.
• This approach provides a foundation for developing more effective, engaging, and scalable digital interventions.