Induced abortion and implications for long-term mental health: a cohort study of 1.2 million pregnancies
Bibliographic record
Abstract
BACKGROUND: The relationship between induced abortion and long-term mental health is not clear. We assessed whether having an induced abortion was associated with an increase in the long-term risk of mental health hospitalization. METHODS: We carried out a retrospective cohort study of 28,721 induced abortions and 1,228,807 births in hospitals of Quebec, Canada, between 2006 and 2022. The exposure was induced abortion compared with other pregnancies, and the outcome was hospitalization for a psychiatric disorder, substance use disorder, or suicide attempt over time. We followed patients up to 17 years after the end of pregnancy to identify mental health-related hospitalizations. We calculated hazard ratios (HR) and 95 % confidence intervals (CI) for the association between induced abortion and mental health hospitalization, adjusted for pregnancy characteristics. RESULTS: Rates of mental health-related hospitalization were higher following induced abortions than other pregnancies (104.0 vs. 42.0 per 10,000 person-years). Abortion was associated with hospitalization for psychiatric disorders (HR 1.81, 95 % CI 1.72-1.90), substance use disorders (HR 2.57, 95 % CI 2.41-2.75), and suicide attempts (HR 2.16, 95 % CI 1.91-2.43) compared with other pregnancies. The associations were greater for patients who had preexisting mental illness or were aged less than 25 years at the time of the abortion. Abortion was strongly associated with mental health hospitalization within five years but risks waned over time. CONCLUSION: Induced abortion is associated with an increased risk of mental health-related hospitalization in the long term but the association weakens with time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".