Biopsychosocial predictors of trajectories of postpartum sexual function in first-time mothers.
Bibliographic record
Abstract
OBJECTIVE: The postpartum period is a vulnerable time for sexual health, yet the relationship between biopsychosocial factors and sexual function over time remains unclear. Our aim was to identify trajectories of postpartum sexual function in first-time mothers (N = 646) and examine associations with biopsychosocial factors. METHODS: Biopsychosocial factors were assessed at delivery and 3 months postpartum. Sexual function was assessed during pregnancy, 3, 6, and 12 months postpartum using the Female Sexual Function Index. Latent class growth analysis was conducted to identify distinct sexual function trajectories. Multinomial logistic regressions examined associations between biopsychosocial factors and membership in the trajectories. RESULTS: Three trajectories were identified: 52% of women reported minimal sexual function problems at 3 months postpartum and improved the least over time, 35% of women reported moderate sexual function problems at 3 months and improved the most over time, and 13% of women reported marked sexual function problems at 3 months and improved somewhat over time. Biomedical factors were not significantly related to trajectory membership. Higher sexual distress at 3 months postpartum was associated with increased odds of being in the moderate and marked sexual function problems subgroups, whereas higher sexual function in pregnancy was associated with decreased odds of being in these subgroups. Lower depressive symptoms and higher relationship satisfaction was associated with reduced odds of being in the marked problems subgroup. CONCLUSIONS: Improvement in sexual function postpartum is heterogeneous. Psychosocial, but not biomedical factors were significantly associated with the trajectories. This information may be integrated into psychoeducation, and for informing earlier assessment and intervention practices. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.004 |
| 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".