JMIR Publications

ABSTRACT

Background:

Providing financial incentives has gained popularity as a strategy to promote weight loss, but questions remain about how best to utilize them. A promising mHealth strategy provides users with real-time financial incentives based on both the process of weight loss (behavioral modification) and actual weight loss. Leveraging mobile health tools such as smartphone applications, connected body weight scales, and text messaging has the potential to create scalable interventions involving provision of financial incentives in the context of weight loss programs.

Objective:

This article describes the development of and lessons learned from an innovative technology-based solution—Log2Lose—that encouraged individuals to lose weight by providing real-time financial incentives for weight loss and a weight loss behavior, namely dietary self-monitoring.

Methods:

We recruited participants (N=108) with a BMI ≥ 30 kg/m2 for a 24-week weight-loss trial. Participants received a behavioral intervention of biweekly, in-person, group sessions. In addition, in a 2X2 design, participants were randomized to receive financial incentives for: (Group 1) weekly weight loss and dietary self-monitoring, (2) dietary self-monitoring only, (3) weekly weight loss only, or (4) neither. All participants were instructed to log at least 1,000 calories (female) or 1,200 (male) calories per day in MyFitnessPal and to step on the BodyTrace cellular scale at least twice per week. Diet and weight data from the devices were obtained through application programming interfaces (APIs). Each week, we applied algorithms to participants’ data to determine whether they qualified for a monetary incentive (groups 1-3). A text message notified these participants of whether they met weight loss and/or self-monitoring requirements to earn an incentive and the amount earned or would have earned. The money was uploaded to a debit card.

Results:

Our custom-engineering software platform analyzed data from multiple sources, collated and processed data to automatically send appropriate text messages, and informed study staff of the appropriate incentives. We present lessons learned from development of the software system and issues encountered with technology, data transmission, study staff, and participants.

Conclusions:

With consistent and constant validation checks and a robust beta test-run, the process of analyzing data and determining eligibility for weekly incentives was fully automated. Moreover, we were able to accomplish this project within a health system, which required significant security and privacy safeguards. Our success demonstrates how these automated feedback loops can provide health interventions via mobile technology. Clinical Trial: ClinicalTrials.gov: NCT02691260