Characterization of depression subtypes and depression chronicity in middle aged and older adults: An Analysis of the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
The heterogenous clinical presentations of depression are not sufficiently reflected by current diagnostic criteria.Associations between adverse childhood experiences (ACEs), allostatic load (AL), and depression subtypes have not been extensively studied.This study aimed to characterize depression subtypes based on their clinical presentations, and to elucidate the relationships between depression subtypes, AL biomarkers, and ACEs in a sample of middleaged and older adults.Participants from the Canadian Longitudinal Study on Aging Comprehensive cohort with a score of 10 or more on the Center for Epidemiologic Studies Depression-10 item scale were included (n=3966).Latent profile analyses were used to determine depression subtypes and AL and ACE profiles.Multinomial logistic regression was used to determine associations between depression subtypes, stressor profiles and other covariates.Four distinct depression subtypes were identified, including positive affect (63.5%), melancholic (10.5%), typical (14.4%), and atypical (11.6%).Distinct associations between depression subtypes, ACE and AL profiles, and covariates of interest were observed.In particular, the atypical depression had the largest significant associations with stressors compared to the positive affect subtype; it was associated with an higher relative risk of lowcardiovascular AL profile (RRR 1.31, 95%CI: 1.02-1.68)and a lower risk of highcardiovascular AL profile (RRR 0.64, 95% CI: 0.49, 0.85) and a lower relative risk of physical abuse ACE (RRR 0.73, 95% CI: 0.57,0.93).The melancholic subtype had an increased risk of low cardiovascular AL (RRR 0.72, 95%CI: 0.53-0.99),and the typical subtype had a lower risk of high-cardiovascular AL (RRR 0.63, 95% CI: 0.43, 0.92).Other significant covariates differentiating the subtypes included age, sex, smoking status, chronic condition score, marital status, and physical activity.The present study describes distinct associations between depression subtypes and objective and self-reported measures of stress, as well as related factors that differentiate subtypes.The findings may inform more targeted and integrated clinical management strategies for depression in individuals exposed to multiple stressors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".