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Record W4404025153 · doi:10.22215/cujs.v3i1.4856

Assessing Clinical and Cognitive Outcomes in Depressed Youth Following Chronic Cardiovascular Exercise

2024· article· en· W4404025153 on OpenAlexaff
Katie Bush, Marie Huc, Dana Crack, Corrine Staff, Natalia Jaworska

Bibliographic record

VenueCarleton undergraduate journal of science. · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsCognitionDepression (economics)Clinical psychologyMedicinePhysical therapyPsychologyGerontologyPsychiatry

Abstract

fetched live from OpenAlex

Cardiovascular exercise is an empirically supported treatment for major depressive disorder (MDD); however, its effect on cognitive functioning is understudied. We examined how cardiovascular exercise influenced cognitive functioning in healthy youth and youth with MDD aged 16-24 (N = 51). We also assessed how twelve weeks of aerobic exercise intervention influenced cognitive functioning and depressive symptoms in youth with MDD. The Beck Depression Inventory (BDI) was used to measure depressive symptoms and the NIH Cognition Toolbox was used to calculate fluid and crystallized cognition composite scores. We expected increased cognitive functioning to correlate with larger decreases in MDD symptoms. We found no significant differences in baseline cognition scores between healthy and depressed youth. There were no significant differences between changes in VO2 max (an index of cardiovascular fitness) and depressive symptoms or cognition scores in depressed youth. We found a trend for an improvement in cognition scores after exercise intervention, suggesting that consistent cardiovascular exercise could enhance cognition. This study advances our understanding of aerobic exercise as a treatment modality for youth with MDD and the importance of alternative therapeutic interventions in depression.

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)0.007
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 score0.481
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.406
Teacher spread0.350 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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