Engaging adults with obesity in organic online communities to support weight loss: a mixed methods pilot study

Abstract

Objectives

Organic online communities have shown potential for aiding weight loss, but few adults use them. We sought to test strategies to encourage adults to select and engage in online communities for weight loss.

Design

4-week single-arm, mixed-methods pilot.

Main Outcome Measures

Quantitative and qualitative data on selection of online community, engagement with community, and engagement and satisfaction with tasks.

Results

On average, participants (n = 25) were female (80.0%) and white (68.0%), 45.2 ± 18.1 years old, with a BMI of 36.2 ± 6.5 kg/m². Selection of online community varied across participants (13 MyFitnessPal, 5 Facebook, 5 Reddit). In qualitative analyses, reasons for selection included experience with community, privacy considerations, and seeking people similar to them. Most tasks were fully or partially completed by a majority of participants (>80.0%). For most tasks, ∼50% of participants felt the task helped them with weight loss support. Variability in response was observed, especially between tasks that requested reading compared to posting/commenting in the community. Frequent reading of community content throughout the study was reported by >70.0% of participants, though posting/commenting was less frequent. Barriers to further engagement included concerns about privacy, judgement, and misinformation.

Conclusions

This study provides insights about strategies for engaging individuals in online health communities.

Keywords:

• Social media
• online community
• weight loss
• obesity
• social support

Acknowledgements

We thank the research participants for their invaluable contributions.

Disclosure statement

The authors declare that they have no conflicts of interest.

Data availability statement

While our consent form language was not written to allow full sharing of de-identified data, individuals who email us requesting access to the data sets can complete a data sharing agreement and receive a de-identified data set.

Additional information

Funding

This work was supported by the University of Florida College of Health and Human Performance.