Assessment of High School Students’ Understanding of DSM-IV-MR-J Items
Bibliographic record
Abstract
The current study examines the understanding of the DSM-IV-MR-J items to assess pathological gambling among adolescents aged 12 to 15, and explores its accuracy. The DSM-IV-MR-J was first administered in the classroom. Participants were assigned to either an experimental or a control group. Participants in the first group were asked to explain the meaning of each DSM-IV-MR-J item during an individual interview. If the item was not properly understood, the investigator corrected the participant’s understanding of the item. The questionnaire was then administered a second time. The control group was only submitted to a test-retest procedure. The results showed that 22% of the items were misunderstood. Changes in diagnostic categories emerged on the second administration for both groups. A 20% and 29.4% decrease in the number of problem/pathological gamblers was observed in the experimental and control group. The implications of these results are discussed in terms of the reliability of the DSM-IV-MR-J as a measure of problem gambling among adolescents.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".