The Effects of Oral Contraceptives on Emotional Reactivity and Cognition
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of oral contraceptives (OCs) on \nemotional reactivity and cognitive ability. Previous research has suggested that OC users \nmay experience blunted positive affect (PA) reactivity and that some women also \nexperience negative mood side effects from OCs. In the present study, 149 participants \n(58 OC users, 46 nonusers, and 38 men) viewed three different emotional videos paired \nwith music intended to evoke either happiness, sadness, or fear. After each emotional \nvideo, participants completed a facial emotions recognition task, and a GoNogo task of \ninhibition. The hypothesis that women taking OCs would have lower PA reactivity \ncompared to nonusers and men was not supported. However, a sex difference in negative \nemotional reactivity (women > men) was found and was strongest in OC users (OC users \n> men) and longer duration OC users. While a small sample size reduces validity of the \nfindings, the hypothesis that OC users with current negative mood side effects would \nhave faster response times than nonusers and men was not supported. However, a sex \ndifference was evident in that men had slower response times to negative faces. Also, \nmen had slower response times than OC users, after sad and fear mood inductions. There \nwas partial support for the third hypothesis that OC users would have more errors of \ncommission than nonusers and men. OC users (and women as a group) made more errors \nof commission during the GoNogo task compared to men, but only after the happy mood \ninduction. Also, OC users with current negative mood side effects had fewer errors of \ncommission after the sad mood induction compared to OC users with no mood side \neffects. Possible mechanisms are discussed for OC-associated impulsivity and for the possible reversal of such an effect in women experiencing OC mood side effects.
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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 | 0.000 | 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) | 0.002 | 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".