Treatment adequacy and remission of depression and anxiety disorders and quality of life in primary care older adults
Bibliographic record
Abstract
Abstract Background Studies on the long-term outcomes of receiving adequate treatment for depression and anxiety disorders are scarce. The aims of this study were to assess the association between adequacy of care and remission of common mental disorders (CMD) and change in quality of life among a population of older adults consulting in primary care. Methods The study was conducted among 225 older adults with a CMD who participated in the longitudinal ESA-Services study. Adequacy of care was assessed using administrative and self-reported data and was based on Canadian guidelines and relevant literature. CMD were measured at baseline and follow-up using self-reported measures (DSM-5 criteria) and physician diagnostic codes (International Classification of Diseases, 9thand 10threvisions) for depression and anxiety disorders. The remission of CMD was defined by the presence of at least one disorder at baseline and absence at follow-up. Quality of life was measured at baseline and follow-up using a visual analog scale and the Satisfaction With Life Scale. To estimate the probability to receive adequate/inadequate care, a propensity score was calculated, and analyses were weighted by the inverse probability. Weighted multivariable analyses were carried out to assess the remission of CMD and change in quality of life as a function of adequacy of care controlling for individual and health system factors. Results Results showed that 40% of older adults received adequate care for CMD and 55% were in remission at follow-up. Adequacy of care was associated with remission of CMD (AOR: 0.66; CI 0.45–0.97; p-value: 0.032). Participants receiving adequate care had an improvement between baseline and follow-up of 0.7 (beta: 0.69, CI 0.18; 1.20,p = 0.008) point on the Satisfaction With Life Scale, while a marginal association was observed with improvement in HRQOL (beta: 2.83, CI 0.12; 5.79,p = 0.060). Conclusion The findings contribute to the rare observational studies on the association between adequacy of care for CMD and long-term treatment effects. Future studies on population effectiveness should focus on patient indicators of quality of care which may better predict long-term outcomes for patients with depression and anxiety.
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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 | 0.002 | 0.008 |
| 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 | 0.001 |
| 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".