The relationship between major depression and marital disruption is bidirectional
Bibliographic record
Abstract
BACKGROUND: Marital status is important to the epidemiology of psychiatric disorders. In particular, the high prevalence of major depression in individuals with separated, divorced, or widowed status has been well documented. However, the literature is divided as to whether marital disruption results in major depression and/or vise versa. We examined whether major depression influences changes of marital status, and, conversely, whether marital status influences the incidence of this disorder. METHODS: We employed data from the longitudinal Canadian National Population Health Survey (1994-2004), and proportional hazards models with time-varying covariates. RESULTS: Major depression had no effect on the proportion of individuals who changed from single to common-law, single to married, or common-law to married status. In contrast, exposure to depression doubled the proportion of transitions from common-law or married to separated or divorced status (HR=2.0; 95% CI 1.4-2.9 P<0.001). Conversely an increased proportion of nondepressed individuals with separated or divorced status subsequently experienced major depression (hazard ratio, HR=1.3; 95% CI 1.0-1.5 P=0.04). CONCLUSION: The high prevalence of major depression in separated or divorced individuals is due to both an increased risk of marital disruption in those with major depression, and also to the higher risk of this disorder in those with divorced or separated marital status. Thus a clinically significant interplay exists between major depression and marital status. Clinicians should be aware of the deleterious impact of major depression on marital relationships. Proactive management of marital problems in clinical settings may help minimize the psycho-social "scar" that is sometimes associated with this disorder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".