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Record W4411984523 · doi:10.1123/jsep.2024-0294

Socially Supportive and Unsupportive Behaviors in Group Exercise for People Living With Cancer

2025· article· en· W4411984523 on OpenAlexaff
Bobbie-Ann P. Craig, Meghan H. McDonough, S. Nicole Culos‐Reed, William Bridel

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFocus groupCoping (psychology)PsychologyDistressThematic analysisSocial supportPerceptionQualitative researchClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Socially supportive relationships in physical activity (PA) can assist in coping with cancer-related distress and contribute to PA. While perceptions that social support (SS) is available are associated with well-being and PA, less is known about what behaviors contribute to perceptions of being supported, which is important for developing strategies to facilitate SS. We examined participants' experiences with SS behaviors in group exercise oncology programs. Twelve interviews and three focus groups were conducted with 24 people living with cancer to explore experiences with SS related to PA programs. Using reflexive thematic analysis, SS behaviors were identified in five themes: developing caring relationships; a safe haven of care, connection, and understanding; nurturing a desire for seizing opportunities; facilitating preparation for engagement in opportunities; and helping to fully engage in opportunities. SS helped participants cope with cancer, learn new skills and improve their exercise abilities, and form supportive connections with others.

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)0.005
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.325
Teacher spread0.315 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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