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Layperson-Led vs Professional-Led Behavioral Interventions for Weight Loss in Pediatric Obesity

2020· review· en· W3041634197 on OpenAlexafffund
Jonathan McGavock, Bhupendrasinh F Chauhan, Rasheda Rabbani, Sofia Dias, Nika Klaprat, Sara Boissoneault, Justin Lys, Aleksandra Wierzbowski, Mohammad Nazmus Sakib, Ryan Zarychanski, Ahmed M Abou-Setta

Bibliographic record

VenueJAMA Network Open · 2020
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of WaterlooSt. Boniface HospitalGeorge & Fay Yee Centre for Healthcare InnovationUniversity of ManitobaCancerCare ManitobaChildren's Hospital Research Institute of Manitoba
FundersMedical Research CouncilCanadian Institutes of Health Research
KeywordsLaypersonPsychological interventionMedicineWeight lossObesityPsychologyPsychiatryInternal medicinePolitical science

Abstract

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Importance: The appropriate approach for weight loss among children and adolescents with overweight and obesity remains unclear. Objective: To evaluate the difference in the treatment outcomes associated with behavioral weight loss interventions led by laypersons and professionals in comparison with unsupervised control arms among children and adolescents with overweight and obesity. Data Sources: For this systematic review and meta-analysis, the Medical Literature Analysis and Retrieval System Online (MEDLINE), Embase, the Cochrane Library, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) databases were searched from January 1, 1996, to June 1, 2019. Study Selection: Included in this study were randomized clinical trials (RCTs) of behavioral interventions lasting at least 12 weeks for children and adolescents (aged 5-18 years) with overweight and obesity. Exclusion criteria included non-RCT studies, interventions lasting less than 12 weeks, adult enrollment, participants with other medical diagnoses, pharmacological treatment use, and articles not written in English. Two of 6 reviewers independently screened all citations. Of 25 586 citations, after duplicate removal, 78 RCTs (5780 participants) met eligibility criteria. Data Extraction and Synthesis: A bayesian framework and Markov chain Monte Carlo simulation methods were used to combine direct and indirect associations. Random-effects and fixed-effect network meta-analysis models were used with the preferred model chosen by comparing the deviance information criteria. This study was registered with the International Prospective Register of Systematic Reviews (PROSPERO) and followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Main Outcomes and Measures: The immediate and sustained changes in weight and body mass index (BMI) standardized mean difference (SMD) were primary outcomes planned before data collection began, whereas waist circumference and percent body fat were secondary outcomes. The hypothesis being tested was formulated before the data collection. Results: Of 25 586 citations retrieved, we included 78 RCTs (5780 participants), with a follow-up of 12 to 104 weeks. Compared with the control condition, random-effects models revealed that professional-led weight loss interventions were associated with reductions in weight (mean difference [MD], -1.60 kg [95% CI, -2.30 to -0.99 kg]; 68 trials; P < .001) and BMI (SMD, -0.30 [95% CI, -0.39 to -0.20]; 59 trials; P < .001) that were not sustained long term (weight MD, -1.02 kg [95% CI, -2.20 to 0.34 kg]; 21 trials; P = .06; BMI SMD, -0.12 [95% CI, -0.46 to 0.21]; 20 trials; P < .001). There was no association between layperson-led interventions and weight loss in the short-term (MD, -1.40 kg [95% CI, -3.00 to 0.26 kg]; 5 trials; P = .05) or long-term (MD, -0.98 kg [95% CI, -3.60 to 1.80 kg]; 1 trial; P = .23) compared with standard care. No difference was found in head-to-head trials (professional vs layperson MD, -0.25 kg [95% CI -1.90 to 1.30 kg]; 5 trials; P = .38). Conclusions and Relevance: This systematic review and meta-analysis found that professional-led weight loss interventions were associated with short-term but not sustained weight reduction among children and adolescents with overweight or obesity, and the evidence for layperson-led approaches was insufficient to draw firm conclusions.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.404
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2020
Admission routes2
Has abstractyes

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