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Determinants of completion and early dropout in an adult weight management service: a prospective observational study
Jordan D Everitt1, Enzo M Battista-Dowds2, Daniel Heggs3
1Evidence Service, Public Health Wales, Cardiff, Wales, UK.
Background:
High attrition rates in weight management interventions (WMIs) undermine their effectiveness but are poorly understood. This study aimed to identify determinants of completion and early dropout in National Health Service (NHS) WMIs.
Methods:
In this prospective observational study, 329 patients recruited at initial consultation appointments satisfied the eligibility criteria: age ≥18 years and body mass index (BMI) ≥30 kg/m2 . Multivariate logistic regression analyses were performed to identify the odds ratios (OR, given with 95% confidence interval) of completion and early dropout.
Results:
Intervention completion rate was 39.8% (131 of 329). Variables that increased the likelihood of completion included engagement in support sessions, OR10.6 (4.7-23.6, p < 0.001); male sex, OR2.5 (1.4-4.5, p = 0.002); osteoarthritis, OR1.9 (1.1-3.3, p = 0.014); and one or more missed intervention appointments marked as 'could not attend' (notified nonattendance), OR1.8 (1.1-2.9, p = 0.032). Odds of early dropout were higher for participants with anxiety and depression OR2.0 (1.0-4.0, p = 0.039). Dietetic 1:1 participants were less likely to drop out early compared with group programme participants, OR0.3 (0.2-0.7, p = 0.002), but were less likely to complete the full intervention, OR0.5 (0.3-0.9, p = 0.02). Age, BMI, social deprivation and travel distance were among the variables not associated with completion or early dropout.
Conclusions:
This study provides further evidence of the importance of support for participants of WMIs and the need for services to consider how support networks can be incorporated. Patients with poorer mental health may be more likely to drop out early and consequently benefit less from WMIs. Future research should qualitatively explore why these factors contribute to attrition to improve WMI effectiveness.
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