Development of a scalable weight loss intervention for low-income workers through adaptation of interactive obesity treatment approach (iOTA) - Rachel G. Tabak; Jaime R. Strickland; Richard I. Stein; Hank Dart; Graham A. Colditz; Bridget Kirk; Ann Marie Dale; Bradley A. Evanoff (BMC, 2018)
Abstract Background Describing how and why an evidence-based intervention is adapted for a new population and setting using a formal evaluation and an adaptation framework can inform others seeking to modify evidence-based weight management interventions for different populations or settings. The Working for You intervention was adapted, to fit a workplace environment, from Be Fit Be Well, an evidence-based intervention that targets weight-control and hypertension in patients at an outpatient clinic. Workplace-based efforts that promote diet and activity behavior change among low-income employees have potential to address the obesity epidemic. This paper aims to explicitly describe how Be Fit Be Well was adapted for this new setting and population. Methods To describe and understand the worksite culture, environment, and policies that support or constrain healthy eating and activity in the target population, we used qualitative and quantitative methods including key informant interviews, focus groups, and a worker survey; these data informed intervention adaptation. We organized the adaptations made to Be Fit Be Well using an adaptation framework from implementation science. Results The adapted intervention, Working for You, maintains the theoretical premise and evidence-base underpinning Be Fit Be Well. However, it was modified in terms of the means of delivery (i.e., rather than using interactive voice response, Working for You employs automated SMS text messaging), defined as a modification to context by the adaptation framework. The adaptation framework also includes modifications to content; in this case the behavioral goals were modified for the target population based on updated science related to weight loss and to target a workplace population (e.g., a goal to avoiding free food at work). Conclusions If effective, this scalable and relatively inexpensive intervention can be translated to other work settings to reduce obesity and diabetes risk among low-SES workers, a group with a higher prevalence of these conditions. Using a formal evaluation and framework to guide and organize how and why an evidence-based intervention is adapted for a new population and setting can push the field of intervention research forward. Trial registration ClinicalTrials.gov: NCT02934113; Received: October 12, 2016; Updated: November 7, 2017.