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Record W4391170838 · doi:10.1111/josh.13434

Describing High School Stakeholders' Preferences for a Return‐to‐School Framework Following Concussion

2024· article· en· W4391170838 on OpenAlexafffundabout
Heather A. Shepherd, Emily E Heming, Nick Reed, Jeffrey G. Caron, Keith Owen Yeates, Carolyn A. Emery

Bibliographic record

VenueJournal of School Health · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationHotchkiss Brain InstituteAlberta Children's HospitalToronto Rehabilitation InstituteUniversity of TorontoUniversity of Calgary
FundersQueen's UniversityAlberta Children's Hospital FoundationAlberta Children's Hospital Research InstituteChildren's Hospital Foundation
KeywordsConcussionPsychologySchool healthInjury preventionMedical educationApplied psychologyPoison controlMedicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Return to school supports are recommended to facilitate adolescents' re-entry to school following a concussion. However, little is known as to what school stakeholders prefer for a return-to-school process. This study sought to describe the preferences of high school students, parents, and educators for a Return-to-School Framework for adolescents following a concussion. METHODS: We conducted qualitative semi-structured, 1-on-1 or group interviews with high school students (n = 6), parents (n = 5), and educators (n = 15) from Calgary, Canada. Interviews aimed to describe participants' preferences for a Return-to-School Framework for students following a concussion. Interviews were analyzed using conventional content analysis. RESULTS: We organized the data into 4 main themes: (1) purpose of the Return-to-School Framework; (2) format and operation of the Return-to-School Framework; (3) communication about a student's concussion; and (4) necessity of concussion education for students and educators. IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: A Return-to-School Framework following concussion should be developed in consultation with families, educators, and students and supports should be tailored to each student. CONCLUSIONS: Participants preferred a standardized and consistent Return-to-School Framework including ongoing communication between stakeholders as well as feasible and individualized school supports.

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)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.288
GPT teacher head0.432
Teacher spread0.144 · 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.

Study designNot applicable
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

Citations2
Published2024
Admission routes3
Has abstractyes

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