Generalized anxiety disorder and health care use
Bibliographic record
Abstract
OBJECTIVE To examine self-reported health care use and health care–seeking behaviour of patients meeting DSM-IV’s diagnostic criteria for generalized anxiety disorder (GAD). DESIGN Survey of outpatients recruited at three diff erent times of the day using questionnaires on worry and anxiety (a six-item screening questionnaire based on DSM-IV criteria for GAD), on perceived health problems, and on health care use and health care–seeking behaviour. The assessment package also included well validated assessment instruments for insomnia and depression symptoms. All patients seeking health care were invited to participate. Participants completed the survey as they waited in the reception area. SETTING Four randomly selected community-based medical clinics of Quebec city’s metropolitan area. PARTICIPANTS A fi nal sample of 1110 patients among 1878 outpatients invited to participate included 219 (19.7%) who tested positive for GAD. MAIN OUTCOME MEASURES Self-reported worry and anxiety (based on DSM-IV criteria for GAD), self-perceived health problems, health care use and health care–seeking behaviour, insomnia, and symptoms of depression. RESULTS Participants who tested positive on a screening test for GAD reported more annual medical visits (5.3 versus 3.4) than other patients. Those who reported at least fi ve annual medical visits were nearly four times more likely to
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".