Dataset Information

Challenges of conducting a remote behavioral weight loss study: Lessons learned and a practical guide.

ABSTRACT:

Objectives

To describe challenges and lessons learned in conducting a remote behavioral weight loss trial.

Methods

The Personal Diet Study is an ongoing randomized clinical trial which aims to compare two mobile health (mHealth) weight loss approaches, standardized diet vs. personalized feedback, on glycemic response. Over a six-month period, participants attended dietitian-led group meetings via remote videoconferencing and were encouraged to self-monitor dietary intake using a smartphone app. Descriptive statistics were used to report adherence to counseling sessions and self-monitoring. Challenges were tracked during weekly project meetings.

Results

Challenges in connecting to and engaging in the videoconferencing sessions were noted. To address these issues, we provided a step-by-step user manual and video tutorials regarding use of WebEx, encouraged alternative means to join sessions, and sent reminder emails/texts about the WebEx sessions and asking participants to join sessions early. Self-monitoring app-related issue included inability to find specific foods in the app database. To overcome this, the study team incorporated commonly consumed foods as "favorites" in the app database, provided a manual and video tutorials regarding use of the app and checked the self-monitoring app dashboard weekly to identify nonadherent participants and intervened as appropriate. Among 135 participants included in the analysis, the median attendance rate for the 14 remote sessions was 85.7% (IQR: 64.3%-92.9%).

Conclusions

Experience and lessons shared in this report may provide critical and timely guidance to other behavioral researchers and interventionists seeking to adapt behavioral counseling programs for remote delivery in the age of COVID-19.

SUBMITTER: Hu L

PROVIDER: S-EPMC8491412 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Publications

Challenges of conducting a remote behavioral weight loss study: Lessons learned and a practical guide.

Hu Lu L Illiano Paige P Pompeii Mary Lou ML Popp Collin J CJ Kharmats Anna Y AY Curran Margaret M Perdomo Katherine K Chen Shirley S Bergman Michael M Segal Eran E Sevick Mary Ann MA

Contemporary clinical trials 20210802

<h4>Objectives</h4>To describe challenges and lessons learned in conducting a remote behavioral weight loss trial.<h4>Methods</h4>The Personal Diet Study is an ongoing randomized clinical trial which aims to compare two mobile health (mHealth) weight loss approaches, standardized diet vs. personalized feedback, on glycemic response. Over a six-month period, participants attended dietitian-led group meetings via remote videoconferencing and were encouraged to self-monitor dietary intake using a s ...[more]

PMID: 34352387

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Project description:BackgroundProviding financial incentives has gained popularity as a strategy to promote weight loss, but questions remain about how best to utilize them. A promising mobile health strategy provides users with near-real-time financial incentives based on both the process of weight loss (behavioral modification) and actual weight loss. To maximize the impact of this strategy, a methodology is needed to close the gap between the desired behavior and the financial incentive. Leveraging mobile health tools-such as mobile phone apps, cellular body weight scales that transmit data to physicians and researchers, and text messaging for instructions and encouragement-has the potential to close this gap.ObjectiveThis study aimed to describe the development of an innovative technology-based solution and lessons learned from a feasibility trial-Log2Lose-that encouraged individuals to lose weight by providing near-real-time financial incentives for weight loss and/or dietary self-monitoring.MethodsWe recruited participants (N=96) with a body mass index greater than or equal to 30 kg/m2 for a 24-week weight loss trial. Participants received a behavioral intervention of biweekly, in-person group sessions and were instructed to log a minimum number of daily calories in MyFitnessPal and to step on the BodyTrace cellular scale at least twice per week. In a 2×2 design, participants were randomized into 4 groups to receive financial incentives for the following: (group 1) weekly weight loss and dietary self-monitoring, (group 2) dietary self-monitoring only, (group 3) weekly weight loss only, or (group 4) no financial incentives. Diet and weight data from the devices were obtained through application programming interfaces. 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 they earned or would have earned. The money was uploaded to a debit card.ResultsOur custom-engineered software platform analyzed data from multiple sources, collated and processed the data to send appropriate text messages automatically, and informed study staff of the appropriate incentives. We present lessons learned from the development of the software system and challenges encountered with technology, data transmission, and participants (eg, lost connections or delayed communication).ConclusionsWith consistent and constant validation checks and a robust beta test run, the process of analyzing data and determining eligibility for weekly incentives can be mostly automated. We were able to accomplish this project within an academic health system, which required significant security and privacy safeguards. Our success demonstrates how this methodology of automated feedback loops can provide health interventions via mobile technology.Trial registrationClinicalTrials.gov NCT02691260; https://clinicaltrials.gov/ct2/show/NCT02691260.

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Dataset Information

Challenges of conducting a remote behavioral weight loss study: Lessons learned and a practical guide.

Objectives

Methods

Results

Conclusions

Publications

Challenges of conducting a remote behavioral weight loss study: Lessons learned and a practical guide.

Similar Datasets

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