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Record W3205316503 · doi:10.1123/tsp.2021-0045

Exploring Female University Athlete Experiences of Coping With Protracted Concussion Symptoms

2021· article· en· W3205316503 on OpenAlexaff
Rebecca Steins, Gordon A. Bloom, Jeffrey G. Caron

Bibliographic record

VenueThe Sport Psychologist · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationMcGill University
Fundersnot available
KeywordsConcussionCoping (psychology)PsychologyCognitionClinical psychologyAthletesInjury preventionPhysical therapyPoison controlMedicinePsychiatryMedical emergency

Abstract

fetched live from OpenAlex

Concussions result in a multitude of somatic, cognitive, and/or emotional symptoms as well as physical and behavior changes and disturbances in balance, cognition, and sleep. Moreover, some concussed athletes can experience these symptoms, changes, and disturbances for extended periods of time. This qualitative study explored the coping skills used by five female university athletes who suffered persistent concussion symptoms for more than 6 weeks. Our analysis of the interview data indicated that the athletes used emotion-focused coping strategies, such as avoidance and acceptance, throughout their recovery. In addition, the lack of perceived control over their injuries, a lack of a symptom-specific treatment protocol, and the type of social support they received influenced their coping abilities. These results add to the limited, yet growing, body of literature on the psychology of sport-related concussions, particularly with respect to identifying the types of resources that athletes may use to cope and manage concussion symptoms.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.194
GPT teacher head0.354
Teacher spread0.160 · 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 designQualitative
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

Citations5
Published2021
Admission routes1
Has abstractyes

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