Relationships between parental sleep quality, fatigue, cognitions about infant sleep, and parental depression pre and post-intervention for infant behavioral sleep problems
Bibliographic record
Abstract
BACKGROUND: Maternal and paternal depression has been associated with infants' behavioral sleep problems. Behavioral sleep interventions, which alter parental cognitions about infant sleep, have improved infant sleep problems. This study reports relationships between parental depression, fatigue, sleep quality, and cognitions about infant sleep pre and post-intervention for a behavioral sleep problem. METHODS: This secondary analysis of data from Canadian parents (n = 455), with healthy infants aged 6-to-8-months exposed to a behavioral sleep intervention, examined baseline data and follow-up data from 18 or 24 weeks post intervention (group teaching or printed material) exposure. Parents reported on sleep quality, fatigue, depression, and cognitions about infant sleep. Data were analyzed using Pearson's r and stepwise regression analysis. RESULTS: Parents' fatigue, sleep quality, sleep cognitions, and depression scores were correlated at baseline and follow-up. At baseline, sleep quality (b = .52, 95% CI .19-.85), fatigue (b = .48, 95% CI .33-.63), doubt about managing infant sleep (b = .44, 95% CI .19-.69), and anger about infant sleep (b = .69, 95% CI .44-.94) were associated with mothers' depression. At baseline, fathers' depression related to sleep quality (b = .42, 95% CI .01-.83), fatigue (b = .47, 95% CI .32-.63), and doubt about managing infant sleep (b = .50, 95% CI .24-.76). At follow-up, mothers' depression was associated with sleep quality (b = .76, 95% CI .41-1.12), fatigue (b = .25, 95% CI .14-.37), doubt about managing infant sleep (b = .44, 95% CI .16-.73), sleep anger (b = .31, 95% CI .02-.59), and setting sleep limits (b = -.22, 95% CI -.41-[-.03]). At follow-up, fathers' depression related to sleep quality (b = .84, 95% CI .46-1.22), fatigue (b = .31, 95% CI .17-.45), sleep doubt (b = .34, 95% CI .05-.62), and setting sleep limits (b = .25, 95% CI .01-.49). CONCLUSIONS: Mothers' and fathers' cognitions about infant sleep demonstrate complex relationships with their depression scores. While mothers' setting sleep limit scores are associated with decreased depression scores, fathers' setting limits scores are associated with increased depression scores. Parental doubts about managing infant sleep and difficulties with setting sleep limits require attention in interventions.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".