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

Publication ,  Journal Article
Hopkins, CM; Miller, HN; Brooks, TL; Mo-Hunter, L; Steinberg, DM; Bennett, GG
Published in: JMIR research protocols
November 2021

Weight bias internalization, also known as weight self-stigma, is a serious health concern for individuals with higher body weight. Weight bias internalization is associated with the greater avoidance of health care and health-promoting activities, disordered eating, 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 for reducing internalized weight bias.Ruby is a 2-arm randomized controlled trial that was designed to test the efficacy of a 4-week digital self-compassion intervention to reduce internalized weight bias compared with a wait-list control.Adults with elevated internalized weight bias and a BMI of >30 kg/m2 (N=80) were recruited. Ruby is a standalone digital trial that will be delivered entirely via a smartphone and will involve web-based data collection and text messages. The 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 throughout time by treatment arm. The analyses will be conducted by using one-way analysis of covariance models and linear mixed models.The 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. Owing 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 that are the 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.ClinicalTrials.gov NCT04678973; https://clinicaltrials.gov/ct2/show/NCT04678973.DERR1-10.2196/31307.

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Published In

JMIR research protocols

DOI

EISSN

1929-0748

ISSN

1929-0748

Publication Date

November 2021

Volume

10

Issue

11

Start / End Page

e31307

Related Subject Headings

  • 4206 Public health
  • 4203 Health services and systems
  • 1117 Public Health and Health Services
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Hopkins, C. M., Miller, H. N., Brooks, T. L., Mo-Hunter, L., Steinberg, D. M., & Bennett, G. G. (2021). Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias. JMIR Research Protocols, 10(11), e31307. https://doi.org/10.2196/31307
Hopkins, Christina M., Hailey N. Miller, Taylor L. Brooks, Lihua Mo-Hunter, Dori M. Steinberg, and Gary G. Bennett. “Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias.JMIR Research Protocols 10, no. 11 (November 2021): e31307. https://doi.org/10.2196/31307.
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 research protocols. 2021 Nov;10(11):e31307.
Hopkins, Christina M., et al. “Designing Ruby: Protocol for a 2-Arm, Brief, Digital Randomized Controlled Trial for Internalized Weight Bias.JMIR Research Protocols, vol. 10, no. 11, Nov. 2021, p. e31307. Epmc, doi:10.2196/31307.
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 research protocols. 2021 Nov;10(11):e31307.

Published In

JMIR research protocols

DOI

EISSN

1929-0748

ISSN

1929-0748

Publication Date

November 2021

Volume

10

Issue

11

Start / End Page

e31307

Related Subject Headings

  • 4206 Public health
  • 4203 Health services and systems
  • 1117 Public Health and Health Services
  • 1103 Clinical Sciences