Severe postpartum distress in Icelandic mothers with difficult infants: a follow‐up study on their health care
Bibliographic record
Abstract
This article describes help seeking and health care of mothers with a difficult infant who suffered long-term depressive symptoms and a high degree of parenting stress. A subsample of severely distressed mothers (n = 37) was recruited from a cross-sectional national survey and followed up 2 months later by a semi-structured telephone interview. The survey included all Icelandic women who gave birth during a quarter of a year and had a live baby 2 months later (n = 1053). All distressed mothers with a difficult infant were selected from sample respondents on preset scores of two self-report distress measures. The study sample emerged during the selection process for an intervention study from which it was excluded on grounds of very high distress scores. Results showed that 5% of the surveyed population were postpartum severely distressed. Findings from this follow-up study revealed that only one woman of four received health care for severe distress by various professionals. One woman of six received help from others. Very few women utilized the services available at Health Care Centers. About half of the women held attitudes that hindered them in seeking help and health care. It is concluded that postpartum severely distressed women receive little primary health care for mental health problems and the majority of them show little initiative to seek out for help. More active outreach by health professionals is recommended.
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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 | 0.001 |
| 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) | 0.001 | 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".