Quality of life in ALS depends on factors other than strength and physical function
Bibliographic record
Abstract
OBJECTIVES: To study patients with ALS to determine the following: 1) the relationship between physical function and quality of life (QOL); 2) the instruments that best reflect patients' own ratings of QOL; and 3) whether spiritual/religious factors play a role in determining QOL. METHODS: The authors prospectively studied 96 patients with ALS using several instruments, including the McGill Quality of Life (MQOL) instrument, the Idler Index of Religiosity, the Sickness Impact Profile (SIP)/ALS-19, and several measures of strength and physical function. RESULTS: QOL as assessed by patients (MQOL single item score) did not correlate with measures of physical function and strength, but correlated with the total MQOL score (p < 0.0005), the psychological and existential subscores of MQOL (p < 0. 0005), the support subscore of MQOL (p = 0.001), and the total Idler score (p = 0.001). In contrast, correlations between SIP/ALS-19 and these measures were not significant, although SIP/ALS-19 correlated with measures of physical function and strength. CONCLUSIONS: QOL, as assessed by the patient with ALS, does not correlate with measures of strength and physical function, but appears to depend on psychological and existential factors, and thus may be measured well by the MQOL scale. Spiritual factors and support systems appear to play roles as well. SIP/ALS-19 is a good measure of physical function, but not of overall QOL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".