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Record W4412114234 · doi:10.1177/15588661251356444

Physical Activity and Wellness Series: Examining an Integrated Physical and Mental Wellness Program for International Students

2025· article· en· W4412114234 on OpenAlexaffabout
Kimberley D. Curtin, Farshid Mirzaalian, Tanya R. Berry

Bibliographic record

VenueRecreational Sports Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsWomen's Health Research InstituteUniversity of Alberta
FundersNIRSA Foundation
KeywordsMental healthSeries (stratigraphy)PsychologyPhysical activityApplied psychologyMedical educationMedicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

International students may experience many stressors when adjusting to their new environment. The Physical Activity and Wellness Series was an integrated wellness and physical activity program aimed at improving international students’ physical activity participation, self-efficacy, coping and social belonging, and reducing stress. Four sessions of the 8–10 week program were evaluated with N = 45 international students. Participants completed surveys at the beginning and end of the program, and a focus group following each session. Measures included self-efficacy for physical activity, social self-efficacy, coping self-efficacy, stress, social belonging, and physical activity. Focus groups assessed participant experiences including expectations, barriers, and facilitators. Most of the mean values trended in the expected direction (higher self-efficacy and physical activity, lower stress and social isolation) and focus group themes included mental and physical health, social connections, and Canadian culture. Combining mental wellness and physical activity in a weekly program resulted in positive social wellness outcomes for international students.

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)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.028
GPT teacher head0.387
Teacher spread0.359 · 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
Published2025
Admission routes2
Has abstractyes

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