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. 2023 Nov;18(11):e13071.
doi: 10.1111/ijpo.13071. Epub 2023 Sep 7.

Attrition rate and predictors of a monitoring mHealth application in adolescents with obesity

Maurane Desmet  1 , Alicia Fillon  2   3 , David Thivel  2   3 , Ann Tanghe  4 , Caroline Braet  1
Affiliations

Attrition rate and predictors of a monitoring mHealth application in adolescents with obesity

Maurane Desmet et al. Pediatr Obes. 2023 Nov.

Abstract

Background: Integrating mobile health (mHealth) into paediatric obesity treatment can provide opportunities for more personalized and lifetime treatment. However, high attrition rates pose a significant challenge. The current study attempts to better understand attrition by exploring (1) attrition rates of a monitoring mHealth application for usage over 14 days and (2) testing predictors of attrition in adolescents with obesity.

Methods: Participants were 69 adolescents between 12 and 16 years old who engaged in a multidisciplinary obesity treatment centre (either outpatient or inpatient) in two countries (Belgium and France). To assess the attrition rates, frequency distributions were used. To test the predictors of attrition, zero-inflated negative binomial regression was performed.

Results: Attrition rates were high, in the outpatient group, more than half of the participants (53.3%) used the app for only 0-7 days. In the inpatient group, this percentage was 24.1%. Only deficits in initiating (a component of executive functions) were a negative predictor of attrition, indicating that deficits in initiating lead to lower attrition rates.

Conclusions: This study provides evidence for high attrition rates in mHealth interventions for adolescents with obesity and was the first to investigate psychological predictors of attrition to an mHealth monitoring tool in adolescents with obesity in treatment. Findings regarding predictors of attrition should be approached with caution due to the small sample size.

Keywords: adolescents; attrition; eHealth; obesity; predictors.

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References

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