Stay in treatment: Predicting dropout from pediatric weight management study protocol

Diane C Berry1, Erinn T Rhodes2, Sarah Hampl3

  • 1The University of North Carolina, School of Nursing, Chapel Hill, NC, USA.

Insights

This study refines the Outcomes Forecasting System (OFS) to predict and reduce dropout in pediatric weight management programs. The improved OFS will enhance patient retention and program effectiveness.

Area of Science:

  • Pediatrics
  • Public Health
  • Data Science

Background:

  • Childhood obesity presents a significant public health challenge.
  • Multidisciplinary pediatric weight management programs are effective but hampered by high attrition rates.
  • Attrition limits health benefits and resource efficiency in these programs.

Purpose of the Study:

  • To refine the Outcomes Forecasting System (OFS) for precise prediction of participant dropout in pediatric weight management.
  • To validate and establish the external validity of the OFS across multiple weight management sites.
  • To pilot an intervention utilizing the OFS to reduce attrition and improve outcomes.

Main Methods:

  • Developing and validating the OFS by acquiring patient, family, and treatment data from multiple sites.
  • Testing the OFS's external validity at a fourth pediatric weight management program.
  • Conducting a pilot clinical trial to implement an OFS-based intervention to reduce attrition.

Main Results:

  • The study aims to significantly increase the power and precision of the OFS model.
  • External validity will be established by applying the OFS to diverse program settings.
  • The refined OFS is expected to accurately forecast participant dropout.

Conclusions:

  • Understanding patient, family, and disease factors predicting dropout is key to prevention.
  • The refined OFS will serve as a valuable, efficient tool for diverse weight management programs.
  • This tool will decrease costs, improve patient retention, adherence, and overall outcomes.
Abstract

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