Hormonal contraceptive use and type matter: Distinct cortisol patterns and cortisol-mood relations
Bibliographic record
Abstract
Abstract Hormonal contraceptives (HCs) are used by millions of people globally; however, the implications of HC use on mood and neuroendocrine processes are not fully understood. Thus, the main goal of the current investigation was to assess stress, mood, quality of life, and cortisol patterns in individuals who were naturally cycling or using HC. Another goal was to differentiate HC type, assessing relations in combined oral contraceptive (COC) versus progestin-only HC users. Young females (N = 191) in first- and second-year university (Mage = 19.02, SD = 1.04) completed online self-report stress and mood questionnaires and provided samples for diurnal cortisol determination. When comparing HC users to naturally cycling females, no differences were found for stress, mood or diurnal cortisol patterns. However, distinct correlations were found between cortisol profiles and mood outcomes. This may indicate that the linkages between elevated mood symptoms and cortisol are dysregulated among HC users. When considering HC type, quality of life was higher in COC users compared to naturally cycling females; however, this was not found in progestin-only users. Progestin-only users were more likely to self-report a mental health diagnosis, an effect also significant in an independent replication sample of young females (N = 411; Mage = 19.34, SD = 2.15). Moreover, in the replication sample, plasma cortisol levels were lower among progestin-only users compared to COC users. This study contributes to a growing body of evidence that highlights complex relationships between HC use, mood outcomes, and neuroendocrine functioning, and emphasizes that type of HC matters.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".