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Record W4321372507 · doi:10.1080/87568225.2023.2181255

CBT + Exercise vs Treatment as Usual in Treating Anxiety and Depression in University Students: A Pilot Study

2023· article· en· W4321372507 on OpenAlexaff
Breagh C. Newcombe, Janine V. Olthuis, Matthew MacLean, Ryan Hamilton, Taylor McAulay

Bibliographic record

VenueJournal of College Student Mental Health · 2023
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAnxietyClinical psychologyDepression (economics)MoodIntervention (counseling)Session (web analytics)Physical therapyPsychologyCognitive behavioral therapyCognitionPsychotherapistMedicinePsychiatry

Abstract

fetched live from OpenAlex

The current pilot study tested the feasibility and preliminary efficacy of a combined group cognitive behavioral therapy and exercise intervention (CBT+E), as compared to treatment as usual (TAU) for managing anxiety and mood symptoms in university students. Participants were 16 undergraduate students with at least mild anxiety, depression, or stress symptoms. Participants were randomly assigned to group CBT+E or TAU. CBT+E ran for seven weeks with group sessions held twice weekly. The first weekly session consisted of group CBT followed by 30 minutes of running and the second weekly session consisted of only group running. Findings suggest that the group CBT+E intervention is feasible in terms of retention and participation, but that recruitment strategies need to be improved. Suggestions to improve recruitment in future research are provided. Preliminary efficacy data show positive trends suggesting further pursuit of this type of intervention is important.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.053
GPT teacher head0.440
Teacher spread0.387 · 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 designNon-randomized trial
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

Citations3
Published2023
Admission routes1
Has abstractyes

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