BMC Public Health (Jul 2021)

Reach, engagement and effectiveness of in-person and online lifestyle change programs to prevent diabetes

  • Ilya Golovaty,
  • Sandeep Wadhwa,
  • Lois Fisher,
  • Iryna Lobach,
  • Byron Crowe,
  • Ronli Levi,
  • Hilary Seligman

DOI
https://doi.org/10.1186/s12889-021-11378-4
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 11

Abstract

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Abstract Background COVID-19 has accelerated interest in and need for online delivery of healthcare. We examined the reach, engagement and effectiveness of online delivery of lifestyle change programs (LCP) modelled after the Diabetes Prevention Program (DPP) in a multistate, real-world setting. Methods Longitudinal, non-randomized study comparing online and in-person LCP in a large multistate sample delivered over 1 year. Sample included at-risk adults (n = 26,743) referred to online (n = 9) and in-person (n = 11) CDC-recognized LCP from a multi-state registry (California, Florida and Colorado) between 2015 and 2018. The main outcome was effectiveness (proportion achieving > 5% weight loss) at one-year. Our secondary outcomes included reach (proportion enrolled among referred) and engagement (proportion ≥ 9 sessions by week 26). We used logistic regression modelling to assess the association between participant- and setting -level characteristics with meaningful weight loss. Results Online LCP effectiveness was lower, with 23% of online participants achieving > 5% weight loss, compared with 35% of in-person participants (p < 0.001). More adults referred to online programs enrolled (56% vs 51%, p < 0.001), but fewer engaged at 6-months (attendance at ≥9 sessions 46% vs 66%, p < 0.001) compared to in-person participants. Conclusions Compared to adults referred to in-person LCP, those referred to online LCP were more likely to enroll and less likely to engage. Online participants achieved modest meaningful weight loss. Online delivery of LCP is an attractive strategy to deliver and scale DPP, particularly with social distancing measures currently in place. However, it is unclear how to optimize delivery models for maximal impact given trade-offs in reach and effectiveness.

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