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Record W2602783962

Effects of physical activity on depression in adult females

2016· article· en· W2602783962 on OpenAlexaff
Michelle Fortier, Taylor McFadden, Isabelle Soucy, Martin D. Provencher

Bibliographic record

VenueJournal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository) · 2016
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsDepression (economics)Physical activityIntervention (counseling)PsychologyDepressive symptomsClinical psychologyRandomized controlled trialAnalysis of varianceMedicinePhysical therapyPsychiatryInternal medicineCognition
DOInot available

Abstract

fetched live from OpenAlex

A number of reviews/meta-analyses have shown the positive effects of physical activity on depression (Schuch et al., 2016). Females report twice the rates of depression than males (Pearson, Janz, & Ali, 2013). The purpose of this presentation is to report the results of 2 experimental studies examining the effects of PA on depression in female adults. The first was an RCT comparing a physical activity intervention, a behavioural activation intervention and a control condition. The second was a multiple single subject study using a physical activity counsellor to help depressed female undergraduate students increase their physical activity. For study 1, a mixed ANOVA was conducted to assess the impact of the 3 conditions on depressive symptoms. The physical activity intervention showed a significant reduction in depressive symptoms, F(2, 54.74) = 3.49, p

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)0.003
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.281
Teacher spread0.264 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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