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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Jun 16, 2021
Date Accepted: Aug 28, 2021
Date Submitted to PubMed: Nov 29, 2021

The final, peer-reviewed published version of this preprint can be found here:

Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias

Hopkins CM, Miller HN, Brooks TL, Mo-Hunter L, Steinberg DM, Bennett GG

Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias

JMIR Res Protoc 2021;10(11):e31307

DOI: 10.2196/31307

PMID: 34842549

PMCID: 8663559

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Designing Ruby: a brief digital randomized controlled trial for internalized weight bias

  • Christina Maria Hopkins; 
  • Hailey N. Miller; 
  • Taylor L. Brooks; 
  • Lihua Mo-Hunter; 
  • Dori M. Steinberg; 
  • Gary G. Bennett

ABSTRACT

Weight bias internalization – also known as weight self-stigma - is a serious health concern for individuals at higher body weights. Weight bias internalization is associated with more avoidance of healthcare and health-promoting activities, more disordered eating, more social isolation, and weight gain. Elevated weight bias internalization has been associated with low self-compassion, yet few investigations have explored self-compassion as a potential mechanism in reduction of internalized weight bias. Ruby is a two-arm randomized controlled trial designed to test the efficacy of a 4-week digital self-compassion intervention to reduce internalized weight bias, compared to wait list control. Adults with elevated internalized weight bias and a body mass index over 30 kg/m2 (n=80) will be recruited. Ruby is a standalone digital trial and will be delivered entirely via smartphone using web-based data collection and text messages. Intervention content will include psychoeducation and daily mindfulness practices with a focus on self-compassion and body concerns. We will use intent-to-treat analyses to examine changes in weight bias internalization over time by treatment arm using one-way analysis of covariance (ANCOVA) models and linear mixed models. The present protocol was designed in May 2020 and approved in December 2020. Data collection is currently underway. Ruby will be the first digital standalone self-compassion based intervention designed to reduce internalized weight bias. Due to its standalone digital delivery, Ruby may be a highly-scalable treatment for internalized weight bias that can be delivered on its own or combined with other treatments. We expect Ruby to be accessible to many, as participants can access the digital intervention at times of the day most convenient in their schedule and are not burdened by in-person time commitments, which can be a barrier for participants with competing demands on their time and resources. If efficacious, Ruby will be poised to expand a burgeoning body of literature related to psychological intervention in this area of need.


 Citation

Please cite as:

Hopkins CM, Miller HN, Brooks TL, Mo-Hunter L, Steinberg DM, Bennett GG

Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias

JMIR Res Protoc 2021;10(11):e31307

DOI: 10.2196/31307

PMID: 34842549

PMCID: 8663559

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