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Record W4295886003 · doi:10.1002/hpja.663

Team characteristics associated with weight loss in a First Nations community intervention: An observational study

2022· article· en· W4295886003 on OpenAlexaboutno aff
Erika Bohn‐Goldbaum, Aaron Cashmore, Adrian Bauman, Anna Sullivan, Lose Fonua, Andrew Milat, Kate Reid, Anne Grunseit

Bibliographic record

VenueHealth Promotion Journal of Australia · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNSW Ministry of HealthUniversity of Sydney
KeywordsWeight lossOverweightMedicineObesityDemographyCommunity healthWeight changeGerontologyEnvironmental healthPublic healthInternal medicineNursing

Abstract

fetched live from OpenAlex

ISSUE ADDRESSED: Group-based weight-loss programs can be effective in addressing high rates of overweight and obesity among Aboriginal and Torres Strait Islander Peoples. The purpose was to determine associations between demographic and baseline weight-related variables and team weight loss in a community-based intervention as no previous studies have analysed this at a team level. METHODS: Binomial models tested associations between team-level age, proportion female and baseline weight and classification as higher weight-loss team (HWT) (>50% persons losing 2.5% of initial weight) vs lower weight-loss team (LWT). Linear regressions compared HWT and LWT on diet and physical activity (PA) outcomes adjusted for age and gender. RESULTS: For each 1 kg increment in mean baseline weight, a team's likelihood of higher weight loss was increased by 4% (APR: 1.04, 95%CI: 1.00, 1.08). HWTs increased vigorous PA by 0.32 sessions more than LWTs (P = .02). Fruit and vegetable intakes were not associated with team weight loss classification. CONCLUSIONS: Only baseline weight and vigorous PA distinguished HWT and LWT. Promoting PA components in team-based weight-loss approaches may be beneficial as these lend themselves to group participation. SO WHAT?: Demographic and baseline weight-related variables are largely not predictive of weight loss success in group programs. Identifying other characteristics shared by HWT may help teams achieve weight loss.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.211
GPT teacher head0.437
Teacher spread0.225 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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