Efficacy of Emerging Technologies to Manage Childhood Obesity

Mohammad Alotaibi1, Fady Alnajjar2, Massimiliano Cappuccio3

  • 1Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia.

Insights

Technological interventions show promise for childhood obesity prevention and treatment. Future strategies may integrate machine learning and social robots for better management of this public health challenge.

Area of Science:

  • Public Health
  • Pediatrics
  • Medical Technology

Background:

  • Childhood obesity is a significant global health issue with long-term consequences.
  • Obese children face increased risks of adult obesity and related health disorders.
  • Effective prevention and treatment strategies are crucial for public health.

Purpose of the Study:

  • To review technological interventions for childhood obesity prevention and treatment.
  • To assess the role of machine learning and technology in managing childhood obesity.
  • To identify gaps and future directions in technological approaches.

Main Methods:

  • Systematic review of 26 studies on technological interventions for childhood obesity.
  • Analysis of the efficacy of various technological strategies.
  • Examination of machine learning applications in obesity management.

Main Results:

  • Most reviewed studies demonstrated positive outcomes for technological interventions.
  • Limited research was found on the use of robots and artificial intelligence in pediatric obesity.
  • Machine learning was utilized in several studies, indicating its growing relevance.

Conclusions:

  • Technology offers viable options for childhood obesity management.
  • Future research should explore integrating social robots and AI for enhanced treatment efficacy.
  • A combination of machine learning and advanced technologies holds potential for future interventions.

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