Dysmenorrhea and psychological wellbeing among females with attention deficit hyperactivity disorder
Bibliographic record
Abstract
Although rarely examined together, ADHD, emotional regulation (ER), and dysmenorrhea may be associated, which could create additive burdens on psychological well-being (PWB). Clinicians working with ADHD populations may need to take these challenges into consideration to maximize treatment outcomes. This study investigated the relationships among ADHD, dysmenorrhea, ER, and PWB within a sample of 266 adult females with a self-reported ADHD diagnosis. ADHD symptom severity was positively correlated with dysmenorrhea severity, but ER skills were not a significant moderator of this relationship. ADHD symptom severity was negatively correlated with PWB; however, this relationship was not moderated by dysmenorrhea severity nor ER ability. Overall, a positive association between ADHD symptom severity and dysmenorrhea severity was found in our sample. Further research is needed to understand the nature of this association, as well as factors that may contribute to PWB among individuals with these comorbid conditions.
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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".