Six‐month prevalence and correlates of generalized anxiety disorder among primary care patients aged 70 years and above: Results from the ESA‐services study
Bibliographic record
Abstract
OBJECTIVES: To estimate the 6-month prevalence of generalized anxiety disorder (GAD) in primary care patients aged 70 years and above and to describe their clinical profile, including types of worries. METHODS/DESIGN: Participants (N = 1193) came from the Étude sur la Santé des Aînés (ESA) services study conducted in Quebec, Canada. An in-person structured interview was used to identify GAD and other anxiety/depressive disorders as well as to identify types of worries. Three groups were created (ie, patients with GAD, patients with another anxiety disorder, and patients without anxiety disorders) and compared on several sociodemographic and clinical characteristics using multinomial logistic regression analyses. RESULTS: The 6-month prevalence of GAD was 2.7%. Findings also indicated that the most common types of worries were about health, being a burden for loved ones, and losing autonomy. Compared with respondents without anxiety disorders, older patients with GAD were more likely to be women, be more educated, suffer from depression, use antidepressants, be unsatisfied with their lives, and use health services. In comparison with respondents with another anxiety disorder, those with GAD were 4.5 times more likely to suffer from minor depression. CONCLUSIONS: GAD has a high prevalence in primary care patients aged 70 years and above. Clinicians working in primary care settings should screen for GAD, since it remains underdiagnosed. In addition, it may be associated with depression and life dissatisfaction. Screening tools for late-life GAD should include worry themes that are specific to aging.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".