Influences on help-seeking decisions for behavioral child sleep problems: Why parents do and do not seek help
Bibliographic record
Abstract
OBJECTIVES: Behavioral sleep problems affect 25% of children and impact functioning, but little is known about help-seeking for these problems. We identified (1) predictors for sleep problem perception and help-seeking, using nested-logit regression and (2) reasons why parents did not seek professional help for sleep problems, using chi-square. METHODS: = 407) of children (2-10-years-old) completed the study online. Parents indicated whether their child had no sleep problem, a mild problem, or a moderate-to-severe problem and completed additional questionnaires on parent/child functioning. RESULTS: Overall, 5.4% ± 2.2% of parents sought professional help for a child sleep problem. Greater child sleep problem severity and greater child socioemotional problems were significant predictors of parents perceiving a sleep problem. Among parents who perceived a sleep problem, greater parental socioemotional problems significantly predicted professional help-seeking. Parents who perceived no problem or a mild sleep problem reported not needing professional help as the main reason for not seeking help; parents who perceived a moderate-to-severe problem reported logistic barriers most often (e.g. treatment unavailability, cost). CONCLUSIONS: Problem perception and help-seeking predictors resemble the children's mental health literature. Differences in barriers, based on problem severity, suggest differential help-seeking interventions are needed (e.g. education vs access).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".