The Italian McGill Quality of Life Questionnaire-Revised (MQoL-R): Psychometrics in Neurological and Neoplastic Populations
Bibliographic record
Abstract
Background The McGill Quality of Life Questionnaire-Revised (MQoL-R) is the gold standard for assessing QoL in end-of-life, chronic patients; however, an Italian standardization is lacking. Objective This study aimed at assessing the psychometric properties of the Italian MQoL-R in patients with chronic neurological/oncological conditions. Methods 177 inpatients with life-threatening, chronic neurological/oncological conditions were consecutively recruited in 8 clinics in Northern/Southern Italy were administered the MQoL-R and the Karnofsky Performance Status (KPS). Factorial structure (Confirmatory Factor Analysis, CFA), reliability (Cronbach's α) and construct validity against the KPS (Pearson's coefficients) were examined. Results The four-factor model (Physical, Psychological, Existential and Social subscales) was met (comparative fit index = .93; root mean square error of approximation = .07), with all items significantly loading on respective subscales. Internal consistency was good for both the whole scale (Cronbach's α = .83) and subscales ( range = .6-.85). The KPS was unrelated to MQoL-R measures, except for the Physical subscale ( r = .24). Conclusions The Italian MQoL-R is a valid and reliable tool to assess QoL in end-of-life, both neoplastic and neurological, chronic inpatients undergoing palliative care, whose adoption is thus encouraged in both clinical practice and research addressed to such populations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".