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Record W4412773332 · doi:10.1080/02699052.2025.2531984

Patient voices to enhance concussion research participation: an exploratory qualitative study

2025· article· en· W4412773332 on OpenAlexafffund
Cindy Hunt, Maryam Fereig, Sarah Diaz, Shannon Kenrick-Rochon, Andrew Baker

Bibliographic record

VenueBrain Injury · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsSt. Michael's HospitalNOSM UniversityOntario Stroke NetworkSunnybrook Health Science CentreUniversity of TorontoHealth Sciences NorthHealth Sciences Centre
FundersOntario Brain Institute
KeywordsConcussionExploratory researchQualitative researchPsychologyPoison controlInjury preventionHuman factors and ergonomicsMedicineClinical psychologyPhysical medicine and rehabilitationMedical emergencySociology

Abstract

fetched live from OpenAlex

PURPOSE: There are unique characteristics of vulnerability among adult patients who experience a concussion and have persistent symptoms suggesting the need to tailor recruitment and retention strategies for this population. We aimed to obtain perspectives from post-concussion patients regarding factors they value to encourage recruitment and support retention, thereby assisting research teams conducting studies on concussion. METHODS: The authors used purposive, nonrandom sampling to identify potential research participants for this exploratory qualitative sub-study. Interview questions were designed using Appreciative Inquiry to gain patient-centered approaches to support recruitment and retention. Transcripts from telephone interviews were analyzed using reflexive thematic analysis. RESULTS: We identified two main themes: 1) positive change and 2) participant-centered study design. Each main theme had three sub-themes to support recruitment and/or retention. Positive changes included a) meaningful study impact, b) personal contribution counts, and c) gain information, and reassurance. Participant-centered study design included a) convenience, b) accommodation, and c) feeling valued. CONCLUSIONS: Focused efforts in planning to recruit and retain vulnerable populations for research are paramount. Based on our exploratory findings from a limited sample, we offer patient-reported insights to reflect upon the ongoing learning process to optimize recruitment and retention in the field of concussion research.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.165
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.187
GPT teacher head0.552
Teacher spread0.365 · 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.

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

Citations0
Published2025
Admission routes2
Has abstractyes

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