Factors associated with delayed diagnosis of mood and/or anxiety disorders
Bibliographic record
Abstract
INTRODUCTION: This study examined the association between time to diagnosis and sociodemographic and clinical characteristics as well as time to diagnosis and physical and mental health status, among Canadian adults with a self-reported mood and/or anxiety disorder diagnosis. METHODS: We used data from the 2014 Survey on Living with Chronic Diseases in Canada-Mood and Anxiety Disorders Component. The study sample (n=3212) was divided into three time to diagnosis subgroups: long (> 5 years), moderate (1-5 years) and short (< 1 year). We performed descriptive and multinomial multivariate logistic regression analyses. Estimates were weighted to represent the Canadian adult household population living in the 10 provinces with diagnosed mood and/or anxiety disorders. RESULTS: The majority (61.6%) of Canadians with a mood and/or anxiety disorder diagnosis reported having received their diagnosis more than one year after symptom onset (30.0% reported a moderate delay and 31.6% a long delay). Upon controlling for individual characteristics, we found significant associations between a moderate delay and having no or few physical comorbidities; a long delay and older age; and both moderate and long delays and early age of symptom onset. In addition, a long delay was significantly associated with "poor" or "fair" perceived mental health and the greatest number of activity limitations. CONCLUSION: These findings affirm that a long delay in diagnosis is associated with negative health outcomes among Canadian adults with mood and/or anxiety disorders. Time to diagnosis is particularly suboptimal among older adults and people with early symptom onset. Tailored strategies to facilitate an early diagnosis for those at greatest risk of a delayed diagnosis, especially for those with early symptom onset, are needed.
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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".