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Record W4368339234

The Healthy Weights Initiative: a community-based obesity reduction program with positive impact on depressed mood scores

2016· article· en· W4368339234 on OpenAlexaboutno aff
Mark Lemstra, Marla Rogers

Bibliographic record

VenueDove Medical Press (Taylor and Francis Group) · 2016
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsMoodReduction (mathematics)ObesityPsychologyClinical psychologyGerontologyMedicinePhysical therapyInternal medicineMathematics
DOInot available

Abstract

fetched live from OpenAlex

Mark Edgar Lemstra,1 Marla Rochelle Rogers2 1Department of Psychiatry, 2Department of Physical Medicine and Rehabilitation, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada Objectives: The risk for many chronic diseases increases with obesity. In addition to these, the risk for depression also increases. Exercise interventions for weight loss among those who are not overweight or obese have shown a moderate effect on depression, but few studies have looked at those with obesity. The objectives of this study were to determine 1) the prevalence of depressed mood in obese participants as determined by the Beck Depression Inventory II at baseline and follow-up; 2) the change in depressed mood between those who completed the program and those who did not; and 3) the differences between those whose depressed mood was alleviated after the program and those who continued to have depressed mood. Methods: Depressed mood scores were calculated at baseline and follow-up for those who completed the program and for those who quit. Among those who completed the program, chi-squares were used to determine the differences between those who no longer had depressed mood and those who still had depressed mood at the end of the program, and regression analysis was used to determine the independent risk factors for still having depressed mood at program completion. Results: Depressed mood prevalence decreased from 45.7% to 11.7% (P<0.000) from baseline to follow-up among those who completed the program and increased from 44.8% to 55.6% (P<0.000) among those who quit. After logistic regression, a score of <40 in general health increased the risk of still having depressed mood upon program completion (odds ratio [OR] 3.39; 95% CI 1.18–9.72; P=0.023). Conclusion: Treating depressed mood among obese adults through a community-based, weight-loss program based on evidence may be an adjunct to medical treatment. More research is needed. Keywords: obesity, adult, evidence-based practice, depression, Canada

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.304
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2016
Admission routes1
Has abstractyes

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