Development and Psychometric Properties of the Sleep Parenting Scale for Infants
Bibliographic record
Abstract
Although infants’ sleep behaviors are shaped by their interactions with parents at bedtime, few tools exist to capture parents’ sleep parenting practices. This study developed a Sleep Parenting Scale for Infants (SPS-I) and aimed to (1) explore and validate its factorial structure, (2) examine its measurement invariance across mothers and fathers, and (3) investigate its reliability and concurrent and convergent validity. SPS-I was developed via a combination of items modified from existing scales and the development of novel items. Participants included 188 mothers and 152 mother–father dyads resulting in 340 mothers and 152 fathers; about half were non-Hispanic white. Mothers and fathers completed a 14-item SPS-I for their 12-month-old infant. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to explore and validate SPS-I’s underlying structure. Multigroup CFA was used to examine measurement invariance across mothers and fathers. Reliability was examined using Cronbach’s alpha. Concurrent validity was assessed using linear regressions examining associations between SPS-I factors and parent-reported infants nighttime sleep duration. Convergent validity was assessed using paired-sample t-tests to test whether the SPS-I subscale scores were similar between mothers and fathers in the same household. EFA and CFA confirmed a 3-factor, 12-item model: sleep routines, sleep autonomy, and screen media in the sleep environment. SPS-I was invariant across mothers and fathers and was reliable. Concurrent and convergent validity were established. SPS-I has good psychometric properties, supporting its use for characterizing sleep routines, sleep autonomy, and screen media in the sleep environment by mothers and fathers.Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.2002799 .
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".