Estimating prevalence of anxiety and mood disorder in survey data using the GHQ12: Exploration of threshold values
Bibliographic record
Abstract
Background and Objectives: Our study explored the validity of different \nthreshold values on the 12-item version of the General Health Questionnaire (GHQ12) for \nestimating the prevalence of anxiety and mood disorders (AMD) in Ontario population \nsurvey data. Methods: Data were drawn from the 2003, 2004 and 2006 cycles of the CAMH Monitor (N = 7,126), an ongoing general population survey of Ontario adults aged 18 and older, \nwhich includes the GHQ12. The concordance of different threshold values on the GHQ12 \nfor determination of AMD with a criterion based on individuals who were prescribed either \nanti-anxiety or anti-depressant drugs in the past 12 months and who reported 14 or \nmore mentally unhealthy days in the past 30 days was examined using receiver operator \ncharacteristic (ROC) analysis. \nResults: Concordance between the GHQ12 determination of AMD and the criterion \nmeasure reached “moderate” levels. ROC analysis revealed an area under the curve (AUC) \nof 0.89. At a GHQ12 threshold value of 4, the specificity and sensitivity values obtained \nwere 0.92 and 0.71, respectively. Also at that value, the estimated prevalence of AMD was \nnearly identical to that seen in recent Canadian studies using the CIDI. \nConclusions: These analyses suggest that the GHQ12 may be suitable for providing a \nproxy measure of AMD for epidemiological and surveillance purposes. A threshold score \nof 4 seems to be most suitable for these purposes when using Canadian data.
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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 | 0.000 | 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) | 0.001 | 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".