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Record W2108465631 · doi:10.1123/jsep.26.1.3

Exercise and Depression: Considering Variability and Contextuality

2004· article· en· W2108465631 on OpenAlexaff
Guy Faulkner, Stuart Biddle

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2004
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyKochen–Specker theoremContext (archaeology)Depression (economics)Qualitative researchPopulationAssociation (psychology)Clinical psychologyPsychotherapistSocial psychologyApplied psychologyMedicineSocial science

Abstract

fetched live from OpenAlex

Research continues to support the consideration of exercise as an adjunctive treatment for depression. Adopting a qualitative approach, the aim of this study was to extend our understanding of the motives and barriers to exercise faced by this clinical population, and to explore the role of physical activity in promoting psychological well-being, in a way that encompasses the variability and contextuality of the lives of individuals. Marking a departure from standard content analyses reported in the literature, instrumental case studies are developed that offer a different format for representing qualitative data. Given its longitudinal nature, this study demonstrates the fundamental importance of considering the wider context of participants’ lives in order to understand the relationship between physical activity and psychological well-being. This association is likely to be complex and highly idiosyncratic. Such an understanding may inform a more critical insight into the potential of exercise as an antidepressant in terms of process and effectiveness.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.155
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.039
GPT teacher head0.353
Teacher spread0.313 · 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

Citations69
Published2004
Admission routes1
Has abstractyes

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