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Research Article

A Motivational Technology Perspective on the Use of Smart Wrist-Worn Wearables for Postpartum Exercise and Weight Management

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Published online: 21 Apr 2024
 

ABSTRACT

Exercise and weight management is crucial in preventing postpartum depression and long-term obesity that carries the risk of chronic illness among postpartum women. Although communication devices, such as a smart wrist-worn wearable (SWW), can help users be more physically active, the extent to which postpartum women might benefit from this technology is unknown. We examined how SWWs promoted exercise and helped postpartum women return to pre-pregnancy weight. We tested a model based on the premise that a motivational device that prompts users to engage with it can establish healthy daily routines. An online survey of 309 postpartum women who were living in the United States and were current users of SWWs revealed that the device encouraged them to spend time completing workout goals. Technological affordances (i.e. customization, navigability, and interactivity) and subsequent user engagement with the device positively predicted total workout hours among postpartum women. We present practical implications for postpartum care programs and smart wearable developers.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. A 7-point scale was used unless otherwise specified.

2. Single-item overserved outcome variables in the model (i.e., actual SWW use and weight loss) were also standardized for hypothesis testing in the structural equation model.

3. Power analysis of the structural equation modeling (Preacher & Coffman, Citation2006) indicated that the sample size (N = 309) was sufficient to achieve .99 power with the final model fit (i.e., RMSEA = .06) (MacCallum et al., Citation1996).

4. The behavioral outcome variables (i.e., total hours of exercise per week and weight loss) were the observed variables in the model, while all other variables were latent variables. A mixed modeling method is a common practice in SEM when both observed and unobserved (latent) variables are included in model testing (e.g., Temme et al., Citation2008).

Additional information

Funding

The work was supported by the Towson University.

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