Effectiveness of "run-ins" at predicting adherence in a behavioral weight loss efficacy trial.

Tricia M Leahey, Loneke T Blackman Carr, Zeely Denmat, Denise Fernandes, Amy A Gorin

Journal: Contemporary clinical trials 2022;114():106678

PMID: 35007787

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Abstract

There is limited research on whether run-in procedures predict participant adherence during behavioral efficacy trials. This study examined whether information from behavioral run-ins (food diary completion, questionnaire completion, and staff interview) predict intervention adherence, trial retention, and trial outcomes in a behavioral weight loss trial. Using run-in data, trial staff predicted which participants would have high, moderate, or low trial adherence. Participants with predicted high or moderate adherence were randomized. Results showed that predicted high adherers had better intervention adherence (session attendance and completion of self-monitoring records) and superior trial outcomes (i.e. weight loss). Run-in data did not predict trial retention. Results suggest that run-ins may be effective at identifying participants adherent to intervention protocols, thereby enhancing internal validity of behavioral efficacy trials.

Address: University of Connecticut, Department of Allied Health Sciences, Koons Hall, 358 Mansfield Rd., Unit 1101, Storrs, CT 06269-1101, USA. Electronic address: [email protected].; University of Connecticut, Department of Nutritional Sciences, Roy E. Jones Bldg., 27 Mander Rd., Unit 4017, Storrs, CT 06269-1101, USA. Electronic address: [email protected].; University of Connecticut, Institute for Collaboration on Health, Intervention, and Policy, 2006 Hillside Rd., Unit 1248, Storrs, CT 06269-1101, USA. Electronic address: [email protected].; University of Connecticut, Institute for Collaboration on Health, Intervention, and Policy, 2006 Hillside Rd., Unit 1248, Storrs, CT 06269-1101, USA. Electronic address: [email protected].; University of Connecticut, Department of Psychological Sciences, Bousfield Psychology Building, 406 Babbidge Rd, Unit 1020, Storrs, CT 06269-1101, USA. Electronic address: [email protected].

DOI: 10.1016/j.cct.2022.106678

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MeSH Terms: Humans, Weight Loss