An Assessment of the Psychometric Properties of Italian Version of CPGI
Bibliographic record
Abstract
The aim of this study was to adapt to the Italian context a very commonly used international instrument to detect problem gambling, the canadian problem gambling index (CPGI), and assess its psychometric properties. Cross-cultural adaptation of CPGI was performed in several steps and the questionnaire was administered as a survey among Italian general population (n = 5,292). Cronbach's alpha reliability coefficient was 0.87 and can be considered to be highly reliable. Construct validity was assessed first by means of a principal component analysis and then by means of confirmatory factor analysis, showing that only one factor, problem gambling, was extracted from the CPGI questionnaire (an eigenvalues of 4,684 with percentage of variance 52 %). As far as convergent validity is concerned, CPGI was compared with Lie/Bet questionnaire, a two-item screening tool for detecting problem gamblers, and with both depression and stress scales. A short form DSM-IV CIDI questionnaire was used for depression and VRS scale, a rating scale, was used for rapid stress evaluation. A strong convergent validity with these instruments was found and these findings are consistent with past research on problem gambling, where another way to confirm the validity is to determine the extent to which it correlates with other qualities or measures known to be directly related to problem gambling. In sum, despite the lack of a direct comparison with a classic gold-standard such as DSM-IV, the Italian version of CPGI exhibits good psychometric properties and can be used among the Italian general population to identify at-risk problem gamblers.
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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 | 0.000 |
| 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) | 0.000 | 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".