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Record W2765915572 · doi:10.4103/ijpvm.ijpvm_306_16

Indicator for Success of Obesity Reduction Programs in Adolescents: Body Composition or Body Mass Index? Evaluating a School-based Health Promotion Project after 12 Weeks of Intervention

2017· article· en· W2765915572 on OpenAlexaboutno aff
Naser Kalantari, Shahram Rafieifar, Hassan Eini‐Zinab, Atefeh Aminifard, Hanieh Malmir, Narjes Ashoori, Sheyda Abdi, Maryam Gholamalizadeh, Saeid Doaei

Bibliographic record

VenueInternational Journal of Preventive Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsBody mass indexObesityMedicineAnthropometryIntervention (counseling)Physical therapyHealth promotionBody fat percentagePublic healthInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Obesity in adolescence is the strongest risk factor for obesity in adulthood. This study aimed to evaluate the effects of a comprehensive lifestyle intervention on different anthropometric indices in 12-16-year-old boy adolescents after 12 Weeks of Intervention. METHODS: A total of 96 male adolescents from two schools participated in this study. The schools were randomly assigned to intervention (53 students) and control school (43 students). Height and weight of students were measured and their body mass index (BMI) was calculated. Body fat percent (BF) and body muscle percent (BM) was assessed using a bioimpedance analyzer considering the age, gender, and height of students at baseline and after intervention. The obesity reduction intervention was implemented in the intervention school based on the Ottawa charter for health promotion. RESULTS: < 0.01). However, weight, BMI, and BM did not change significantly. CONCLUSIONS: The result of this study showed that a comprehensive lifestyle intervention decreased the body fat percent in obese adolescents, although these changes was not reflected in the BMI. It is possible that BMI is not a good indicator in assessment of the success of obesity management intervention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.063
GPT teacher head0.420
Teacher spread0.357 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations44
Published2017
Admission routes1
Has abstractyes

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