Comparisons between the South Oaks Gambling Screen and a DSM-IV—Based Interview in a Community Survey of Problem Gambling
Bibliographic record
Abstract
OBJECTIVE: To directly compare 2 forms of assessment for determining gambling problems in a community survey, and to examine the characteristics of respondents who endorsed DSM-IV symptoms but who scored below the formal DSM-IV diagnostic cut-off for pathological gambling. METHOD: We interviewed 1489 Winnipeg adults by phone (response rate 70.5%) using th South Oaks Gambling Screen (SOGS), a DSM-IV-based instrument, and several gambling-related variables. RESULTS: The lifetime prevalence of "probable pathological gambling" (according to the SOGS, having a score of > or = 5) was 2.6%. The SOGS items and DSM-IV symptoms were highly correlated (r = 0.80), but a score of 5 or more symptoms for a DSM-IV diagnosis produced lower prevalence figures. Comparisons between recreational gamblers (those with no DSM-IV symptoms), subthreshold pathological gamblers (those with 1 to 4 DSM-IV symptoms), and pathological gamblers (those with > or = 5 DSM-IV symptoms) on series of gambling-related variables (for example, high use of video lottery terminals) revealed that subthreshold individuals significantly differed from recreational gamblers and more closely approximated the characteristics displayed by pathological gamblers. CONCLUSIONS: SOGS items show a high degree of association with the DSM-IV clinical symptoms of pathological gambling, but the DSM-IV cut-off of 5 symptoms is more conservative in defining gambling problems. Results support a continuum view of gambling problems in the community. DSM-IV scores of 3 or 4 represent the higher end of the group officially considered diagnostically "subthreshold" and may be important from both a clinical and public health perspective.
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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 | 0.004 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".