Construction and Psychometric Testing of the Quality of Developmental Care Scale
Bibliographic record
Abstract
Background: The incidence of poor neurodevelopmental outcomes is rising in children with congenital heart disease as a result of higher risk infants surviving cardiac surgery.Little is known about the reason for variations in neurodevelopment.Notably, there is a gap in the literature addressing the impact of nurse caregiving on the neurodevelopmental outcomes of neonates with congenital heart disease in the cardiac intensive care unit.Research from neonatal intensive care units indicate developmental care is a widely used nursing care intervention that has exhibited a strong relationship with improved neurodevelopment.Although several developmental care measures exist, none of them are specific to nurses caring for neonates in the cardiac intensive care unit and none of the existing self-assessment measurements have been psychometrically tested.Purpose: The purposes of this dissertation study were to develop and psychometrically test the Quality of Developmental Care Scale, which measures the performance of developmental care delivered to neonates with CHD from the perspective of the individual nurse, and to identify variables associated with developmental care performance based on a conceptual model derived from the Theory of Planned Behavior.Methods: Initially, a systematic review was conducted to examine the effects of developmental care interventions on neurodevelopment.Key elements of developmental care programs were identified, as were major study limitations.Based on recommendations from the first study, the second manuscript discussed the results of item pool development and content validity of the iii Quality of Developmental Care Scale.Results indicated evidence of content validity for use with bedside nurses caring for neonates with congenital heart disease.In the third study, the Quality of Developmental Care Scale was psychometrically tested with 121 cardiac intensive care unit nurses using a cross-sectional, descriptive design.Results: Evidence of internal consistency reliability (𝛼 = .89)was established.Multidimensionality was supported by factor analysis, with loadings ranging from .42 to .82 with 51.7% of the variance explained by the first four factors.Model testing through a hierarchical multiple regression equation guided by a conceptual model provided further evidence of construct validity.This dissertation provided a better understanding of the literature regarding developmental care interventions appropriate and feasible for neonates in the cardiac intensive care unit.It also led to the development of a psychometrically sound instrument specific to bedside nurses in the cardiac intensive care unit with great potential for future research.iv
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".