Assessment and Management of Cognitive and Psychosocial Difficulties for People with Multiple Sclerosis in Ireland: A National Survey of Clinical Practice
Bibliographic record
Abstract
Background . A recent survey of 109 healthcare professionals explored how UK healthcare professionals typically assess and treat multiple sclerosis (MS)‐related cognitive impairment. Little is currently known about what constitutes usual care for cognitive impairment and psychosocial care for people with MS in Ireland. Aim . The aim of the current research was to survey healthcare professionals (HCPs) who work with people with MS, to understand current assessment and management of cognition and psychosocial care in people with MS in the Republic of Ireland. Methods . A cross‐sectional survey design was used. Data were collected online through Microsoft forms and through postal responses. The original UK questionnaire was adapted, piloted, and distributed to Irish HCPs. Participants were qualified HCPs who work clinically with people with MS in the Republic of Ireland. Results . Ninety‐eight HCPs completed the survey. Only 34% of those surveyed reported routine screening of cognition for people with MS within their services; approximately, 36% HCPs reported that they did not provide information or services in relation to cognition to people with MS and 39% reported not referring elsewhere when cognitive difficulties were suspected. Out of the 98 HCPs, 47% reported assessing mood difficulties as part of their services, with 14% unsure. In total, 70% of participants reported onward referral took place if mood difficulties were identified. The Montreal Cognitive Assessment was the most commonly administrated cognitive assessment. Cognitive intervention choices were found to be guided by clinical judgement in 75.5% of cases. Discussion . Despite the high importance placed on cognitive and psychosocial care, there is very little consistency in treatment and assessment across services for people with MS in Ireland.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".