93 Combined cognitive-strategy and task-specific training as an occupational therapy intervention in an acute neurosciences setting
Bibliographic record
Abstract
Aims Use the Cognitive Orientation to daily Occupational Performance (CO-OP) approach as part of a patients’ Occupational Therapy (OT) in an acute-neuroscience setting. Gain patient and parent perspectives of engaging in CO-OP and clinician reflections. Background The CO-OP approach is a patient-centred OT intervention combining cognitive-strategy and task-specific training. The CO-OP framework guides the patient through activity analysis and problem-solving strategies relating to patient-set goals, with the patient identifying strengths and weaknesses and solutions to their difficulties. This results in a sense of achievement and empowerment along with skills to address other goals they have. CO-OP has shown to provide improvements in performance and satisfaction and enhance goal attainment in adults with neurological conditions (Polatajko et al 2012, McEwen et al 2014, Borujeni et al 2019 and Hunt et al 2021). Feasibility of CO-OP is established in cerebral palsy (CP) and non-acute ABI populations (Gimeno et al 2021). CO-OP interventions have not been studied in acute paediatric neurosciences care. Method Case study presentation of a 14-year-old in acute stage recovery following craniotomy for excision of intra cranial arteriovenous malformation. Presented with dense left sided weakness, use of right hand only in unimanual activities, carer completing all bimanual daily activities for him. Previously left hand dominant. Outcome measures Canadian Occupational Performance Model (COPM)- patient rated performance and satisfaction scale. Patient Quality Rating Scale (PQRS)- observational measure of performance quality. Informal opinion-based feedback obtained throughout from patient, carer and therapists. Conclusion From feedback, qualitative themes emerged; client centred practise, transferrable skills, enhanced motivation and patient and carer perception of empowerment. Additionally therapist feedback suggested use of technology and resources to enhance CO-OP in this setting. Quantitively this patient made progress; Goal 1. COPM performance (+2), COPM satisfaction (+3.5), PRQS (+5). Goal 2. COPM performance (+7), COPM satisfaction (+5), PQRS (+8).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".