The development of a measure of maternal cognitive sensitivity appropriate for use in primary care health settings
Bibliographic record
Abstract
BACKGROUND: Parental responsivity is important to children's cognitive and socioemotional development, yet is under-represented in primary healthcare, because the measurement is specialized and time-consuming. METHODS: The current study developed a measure of maternal cognitive sensitivity (CS), which uses impressionistic ratings based on brief observations of parent-child interaction when children are 3 years old. RESULTS: Using data from a longitudinal cohort (Time 1, N = 501), the CS measure had good psychometric properties, was significantly related to a gold-standard maternal responsivity measure, and was predicted by the same socio-demographic factors predictive of other measures of parental responsivity. Finally, a well-established pathway from socioeconomic risk (child age 2 months) to compromised parenting (child age 3 years) to negative child outcome (child age 4.5 years) was demonstrated with CS as the mediator. CONCLUSION: The maternal CS measure is brief, can be easily trained, and takes 8 min to administer and code, making it potentially useful in primary healthcare settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".