Depression and the existential domain in the assessment of quality of life in HIV outpatients with the McGill questionnaire.
Bibliographic record
Abstract
AIM: The aim of the present study was to further test criterion validity and factorial validity of the McGIll Quality Of Life (MQOL) questionnaire, and to assess its reliability and sensitivity to clinical change in outpatients with HIV infection. METHODS: The authors present a longitudinal study on a consecutive sample of 216 adults treated with HAART at the outpatient facility of an hospital-based tertiary care center in Italy. Patients completed the MQOL and the Beck Depression Inventory (BDI) both at baseline and follow-up assessments. Patients were classified into subgroups (improved, unchanged, worsened) based on change in BDI scores or CD4 count over time. RESULTS: The pattern of correlation between MQOL subscales and the BDI was as hypothesised. A fairly simple factor structure emerged, with a striking resemblance between the factors and the MQOL subscales. The internal consistency of the MQOL and its subscales was high. The test-retest reliability in clinically unchanged patients was satisfactory. Sensitivity to change, as measured by Guyatt responsiveness statistic, was also satisfactory. CONCLUSIONS: This study contributed to building evidence of reliability and validity for the MQOL questionnaire, which may be particularly useful to assess the so-called "existential" aspects of QOL that are particularly relevant for patients infected with HIV.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".