Pre‐partum distress in women with intellectual disabilities
Bibliographic record
Abstract
BACKGROUND: This study investigates depression, anxiety and stress in pregnant women with intellectual disabilities and/or self-reported learning difficulties, and examines the association between these negative emotional states and perceived support and conflict in the women's interpersonal relationships. METHOD: Eight-hundred-and-seventy-eight women attending their first antenatal visit in a socioeconomically disadvantaged area of Sydney, Australia during a 5-month period in 2002 completed a brief questionnaire to identify those with intellectual disabilities (ID) and/or self-reported learning difficulties. These 57 women were then invited to participate in a series of three interviews (two pre- and one post-partum). The second interview, which was conducted with 31 women in their third trimester, incorporated standard measures of depression, anxiety and stress, and support and conflict in interpersonal relationships, and is the subject of the research reported here. RESULTS: More than one-third of the women interviewed reported moderate to severe depression, anxiety and stress. A significant association was found between depression and both perceived support and conflict in interpersonal relationships. Stress was associated with conflict but not with either perceived support. Anxiety was not significantly associated with either perceived support or conflict. CONCLUSIONS: Negative emotional states in this population of women may be confounded with their cognitive deficits. Routine antenatal screening for negative emotional states is therefore recommended to ensure that the mental health care needs of women with ID and/or self-reported learning difficulties are not overlooked.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".