Continued study of the psychometric properties of the McGill quality of life questionnaire
Bibliographic record
Abstract
The McGill Quality of Life Questionnaire (MQOL) is a widely used tool that has been specifically developed to measure the quality of life of patients facing a life-threatening illness. Preferably, a self-report instrument has an equal number of items worded positively and negatively. However, all the psychological scales of the MQOL are worded so that a high score is negative, whereas the existential scales are worded so that a high score is positive. The goal of this study was to investigate the influence of MQOL item formatting on patient responses. In order to do so, a modified version of the questionnaire was distributed to and completed by 205 patients in two oncology clinics. The modified version had an equal amount of items worded in a positive direction and negative direction in each of the domains. Results of this study were found to be different from those of other studies: the loading of the items was partly based on scale direction. These changes support the idea that the MQOL formatting has some impact on patient responses. However, factors were also determined by content. Given that MQOL has been widely used and the original formatting provides conceptually clearer subscales, we suggest maintaining the original format, keeping in mind the effect of formatting when interpreting scores.
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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 | 0.064 | 0.165 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".