Early infant crying and sleeping problems: A pilot study of impact on parental well‐being and parent‐endorsed strategies for management
Bibliographic record
Abstract
AIMS: Infant sleeping and crying problems are common and impact adversely on maternal mental health but their impact on paternal mental health is unknown. A consistent approach to managing such problems has not been identified. Parents may be able to identify useful management strategies, which could then inform the content of a prevention/early intervention approach to such problems. We aimed to determine the impact of infant behaviour problems on maternal and paternal mental health and management strategies that parents find useful. DESIGN: Pre-post intervention pilot. SETTING: Paediatric outpatient clinic at the Royal Children's Hospital, Melbourne. PARTICIPANTS: 71 mothers and 60 fathers of infants aged 2 weeks to 7 months recruited from July 2004 to April 2005. MAIN OUTCOME MEASURES: Pre and post questionnaires measuring maternal and paternal well-being (Edinburgh Postnatal Depression Scale (EPDS)), parent report of infant behaviour problems, usefulness of consultation strategies. RESULTS: Three weeks post consultation, fewer parents reported that their infant's behaviour was still a problem (64% of mothers and 55% of fathers). Thirty per cent fewer mothers reported an EPDS score>12 (45% pre vs. 15% post clinic) while 11% fewer fathers reported an EPDS score>9 (30% pre vs. 19% post clinic). Most parents (80% or more) rated exclusion of medical causes and information about normal sleeping/crying as useful. CONCLUSIONS: Problem infant behaviours are associated with poor parental mental health. An intervention/prevention approach to infant behaviour problems should include fathers and contain information about normal infant sleeping and crying patterns and exclusion of medical causes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".