Psychometric analysis of Iowa infant feeding attitude scale to improve clinical use and efficacy among prenatal women in Canada
Bibliographic record
Abstract
Breastfeeding is the optimal source of nutrition for newborns, and yet the rates of breastfeeding initiation and continuation in Canada, and specifically Newfoundland and Labrador (NL) are low. Maternal attitudes toward breastfeeding is the best predictor of breastfeeding behaviour, and can be assessed using the validated 17-item Iowa Infant Feeding Attitude Scale (IIFAS). This thesis aimed to 1) reduce the IIFAS to a more manageable length while maintaining its validity and reliability and 2) determine optimal cut-off scores for both the original and reduced IIFAS with the objective being to increase its clinical usefulness in various settings. A 13-item psychometrically and conceptually sound IIFAS is proposed. Cut-off scores of 60 on the original scale and 45 on the reduced item IIFAS scale are the optimal cut-off scores to identify intention to breastfeed and infant feeding outcomes at one month postpartum in mothers in their 3rd trimester of pregnancy.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".