Oral contraceptive formulation and socio-cognitive performance: a short communication
Bibliographic record
Abstract
Background: Oral contraceptives (OC) offer a range of ethinyl estradiol (EE) doses and progestin types, with evidence indicating marked differences in cognitive and emotional abilities in OC users. However, it remains unclear whether dose variations in EE (low vs high) and progestin androgenicity (androgenic vs anti-androgenic) are associated with variations in cognitive and emotional abilities. Objectives: Our study aimed to investigate the cognitive and emotional effects of various OC formulations. Design: Online between-subjects experimental design. Methods: = 25). The Repeatable Battery for the Assessment of Neuropsychological Status, emotion recognition task, and the Positive and Negative Affect Schedule were administered. Visual analogue scales were also administered to assess rejection sensitivity before and after a social exclusion task (Cyberball task). Analysis of variance (2 × 2) models were used to compare cognitive and socio-emotional abilities between groups. Results: Anti-androgenic users demonstrated higher intensity ratings for emotional faces, and heightened feelings of insecurity after a social stressor. Overall positive and negative affect, as well as performance on objective cognitive tests, were similar across OC formulations. Conclusion: In OC users, OC formulations containing an anti-androgenic progestin were associated with greater perceived intensity of emotional faces as well as heightened rejection sensitivity. However, these subtle differences in task performance did not translate to differences in overall affect or cognitive performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 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".