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Record W2909973432 · doi:10.5014/ajot.2019.027995

Feasibility and Effects of the CO–OP Approach™ in Postconcussion Rehabilitation

2019· article· en· W2909973432 on OpenAlexaff
Anne Hunt, Melissa Paniccia, Katie Mah, Deirdre Dawson, Nick Reed

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsBaycrest HospitalHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsMoodRehabilitationPhysical therapyIntervention (counseling)PsychologyMedicineActivities of daily livingConcussionClinical psychologyPhysical medicine and rehabilitationInjury preventionPoison controlPsychiatryMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: on activity performance and satisfaction, symptoms, and mood of adolescents with persistent postconcussion symptoms. METHOD: In a prospective case series, 3 participants with persistent symptoms 3 mo after concussion and difficulties resuming activities were taught to use a metacognitive strategy (Goal-Plan-Do-Check) to work toward occupation-based goals in a 7-wk intervention (10 sessions, 30-60 min each). Participants were assessed pre- and postintervention and at 3-mo follow-up. Feasibility was determined by positive changes on study measures, ease of administration, and acceptability to participants. RESULTS: Clinically significant, positive changes were found in participants' activity performance and satisfaction. All participants had decreases in symptoms and improved mood scores at posttest. CONCLUSION: The CO-OP Approach to rehabilitation for youth postconcussion is feasible and may make a positive contribution to recovery.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.057
GPT teacher head0.395
Teacher spread0.338 · 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 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

Citations12
Published2019
Admission routes1
Has abstractyes

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