Identifying psychiatric comorbidities that occur following the introduction of hormonal contraception: A Scoping review
Bibliographic record
Abstract
Introduction: Hormonal contraceptives are widely used by women of reproductive age, yet concerns persist regarding their potential effects on mental health. Although mood-related side effects are frequently reported, their prevalence, clinical significance, and variation across formulations remain unclear. This scoping review examined associations between hormonal contraception and psychiatric outcomes, focusing on depressive symptoms, anxiety, and other mental health disorders. Methods: A comprehensive search of four major databases identified peer-reviewed studies published between 2014 and 2024. Forty-six studies met inclusion criteria, encompassing observational cohorts, cross-sectional surveys, and clinical trials. Study quality was assessed using the Joanna Briggs Institute checklist. Random-effects meta-analysis and subgroup analyses were conducted by hormonal class and psychiatric outcome. Results: Pooled analyses indicated a small but statistically significant association between hormonal contraceptive use (particularly progestin-only methods) and increased depressive symptoms (RR = 1.24, 95% CI 1.08-1.42; I² = 97.7%). For suicidality, cohort studies reported estimates ranging from HR = 1.97 in younger users to OR = 1.57 with long-term progestin-only use, although the pooled estimate across four studies was imprecise (RR = 1.20, 95% CI 0.65-2.21; I² = 98%). Evidence for anxiety and other psychiatric outcomes was inconsistent; four anxiety-focused studies yielded a non-significant pooled effect (RR = 1.08, 95% CI 0.83-1.40; τ² = 0.13). Methodological heterogeneity, particularly in outcome measurement and control for confounding, was a frequent limitation. Discussion: These findings suggest that hormonal contraception may contribute to adverse psychiatric outcomes in a subset of users. Integrating mental health screening into contraceptive counseling and conducting well-designed prospective studies with standardized psychiatric measures are essential for guiding safer, more tailored contraceptive prescribing practices.
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 | 0.007 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".