Exploring Patient Engagement: A Service Evaluation on Use of Rehacom in Conjunction with Conventional Cognitive Rehabilitation in Acquired Brain Injury Patients at University Hospitals of Leicester
Bibliographic record
Abstract
Background: Acquired Brain Injuries (ABIs) significantly impact cognitive function, emotional regulation, and daily living activities, posing a substantial burden on individuals and the healthcare system. Cognitive Rehabilitation (CR) aims to address these impairments, with Computer-Assisted Cognitive Rehabilitation (CACR) tools like RehaCom emerging as promising interventions. Objective: This study evaluates adherence to RehaCom in a Neurorehabilitation inpatient setting, exploring patient engagement, barriers to participation, and potential benefits when integrated with conventional CR. Methods: A Service Evaluation was conducted at a UK Neurorehabilitation Unit (NRU) involving 27 patients with ABI, aged 20–80 years, and a Montreal Cognitive Assessment (MoCA) score of <26. Participants completed weekly RehaCom sessions alongside traditional CR over five weeks after completing RehaCom screening. Adherence was assessed through screening completion, session attendance, engagement duration, and patient-reported outcomes. Results: Of the 27 participants, 22.2% were unable to complete the RehaCom screening due to agitation, cognitive deficits leading to non-completion of task or challenges with computer controls. An additional 22.2% engaged in sessions but failed to meet the minimum engagement threshold of 15 minutes. Only 29.6% completed all five weekly sessions, with higher MoCA scores correlating with better adherence. Three main barriers for variable adherence to RehaCom use were cognitive impairment, fatigue and patient preferences for conventional therapy. Conclusion: RehaCom shows promise as a CR tool, but its detailed screening and task complexity may hinder engagement in patients with significant cognitive challenges. Higher MoCA scores predict better adherence, indicating its targeted utility for certain patient subgroups. Future research should explore modifications to enhance usability, integrate education about its benefits, and evaluate longterm outcomes in diverse populations.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".