Service use and needs of people with motor neurone disease and their carers in Scotland
Bibliographic record
Abstract
A national study of patients with motor neurone disease (MND) and their carers was conducted in Scotland in late 1996. A questionnaire covering areas such as: use of medical, social and voluntary services; use of or waiting for specialised equipment; satisfaction with provided services; and standard demographic data was used in face-to-face interviews conducted by the four Scottish Motor Neurone Disease Association care advisers. The care advisers also assessed the respondent's level of impairment, using a standard instrument: the Amyotrophic Lateral Sclerosis Severity Scale (ALSSS). The data was analysed using SPSS-PC. In total 153 people participated (response rate 92%), and as expected with this patient group the study recruited more men (57%) than women. Sixty per cent of the sample was severely disabled as measured on the ALSSS. Health services did not meet the needs of respondents in 19% of the cases and social services failed to do so according to 24% of respondents. Eighty per cent of patients with MND had an identified carer. Nearly four out of 10 of these carers had their sleep disturbed regularly, and nearly a quarter of them would have liked to have more help. In addition, differences were found in service provision between the East and West of Scotland, and consequently differences in respondent's perceptions about the extent to which needs were met. As found in similar studies, the formal health and social care sectors in conjunction with voluntary organisations are only partially managing the trajectory of patients with a rare progressive degenerative disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".