ReviewDiabetes, metabolic syndrome and obesity : targets and therapy2022
Efficacy of Emerging Technologies to Manage Childhood Obesity.
Review in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Rising prevalence of stunting and obesity in Iranian schoolchildren: a three-year cohort study.BMC public health · 2026Article
- Integrating digital health into pediatric obesity management: Current practices and future perspectives.Obesity pillars · 2025Review
- Exploring the Use of Digital Technology to Support Health Behavior Change in Young People Under the Care of Complications of Excess Weight (CCEW) Clinics: Qualitative Patient-Centered Design Study.JMIR formative research · 2025Article
- Obesity‑related kidney disease: a review on ultrasound applications.Italian journal of pediatrics · 2025Review
- Article
- Effectiveness of Smartphone App for the Treatment of Pediatric Obesity: A Randomized Controlled Trial.Children (Basel, Switzerland) · 2024Article
- Towards a Deeper Understanding: Utilizing Machine Learning to Investigate the Association between Obesity and Cognitive Decline-A Systematic Review.Journal of clinical medicine · 2024Review
- Applications of artificial intelligence in the management of childhood obesity.Journal of family medicine and primary care · 2023Review
- Artificial intelligence and obesity management: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2023.Obesity pillars · 2023Article
- The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity.Nutrients · 2023Article
- Predicting Childhood Obesity Based on Single and Multiple Well-Child Visit Data Using Machine Learning Classifiers.Sensors (Basel, Switzerland) · 2023Article
- Adolescents with Type 2 Diabetes: Overcoming Barriers to Effective Weight Management.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Review
- Exploring the understanding of how parenting influences the children's nutritional status, physical activity, and BMI.Frontiers in nutrition · 2022Article
- Relevance and Acceptability of a Technology-delivered Childhood Obesity Intervention for Hispanic/Latino Families in Rural Nebraska: A Qualitative Approach.Journal of primary care & community healthArticle
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Childhood obesity is a widespread medical condition and presents a formidable challenge for public health. Long-term treatment strategies and early prevention strategies are required because obese children are more likely to carry this condition into adulthood, increasing their risk of developing other major health disorders. The present review analyses various technological interventions available for childhood obesity prevention and treatment. It also examines whether machine learning and technological interventions can play vital roles in its management. Twenty-six studies were shortlisted for the review using various technological strategies and analysed regarding their efficacy. While most of the selected studies showed positive outcomes, there was a lack of studies using robots and artificial intelligence to manage obesity in children. The use of machine learning was observed in various studies, and the integration of social robots and other efficacious strategies may be effective for treating childhood obesity in the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.