Psychometric Validation of the Iowa Infant Feeding Attitude Scale Among Healthcare Students in Vietnam
Bibliographic record
Abstract
Background: The Iowa Infant Feeding Attitude Scale (IIFAS) is widely used to assess breastfeeding attitudes, which are linked to positive breastfeeding practices. However, its psychometric validation in Southeast Asian healthcare students remains limited. Objectives: To investigate the reliability and validity of the IIFAS among Vietnamese healthcare students. Methods: A cross-sectional study was conducted at three medical universities in Vietnam. A total of 542 healthcare students, including medical, nursing, and midwifery students, participated. The students completed the Iowa Infant Feeding Attitude Scale, Breastfeeding Knowledge Scale, and Generalized Anxiety Disorder Scale. The reliability was assessed through the internal consistency and test–retest reliability. The construct validity was tested using exploratory and confirmatory factor analysis. The divergent validity, convergent validity, and known-group comparison were also assessed. Results: The IIFAS showed an excellent internal consistency (Cronbach’s α = 0.94) and test–retest reliability (intraclass correlation = 0.91). A two-factor structure of the Vietnamese IIFAS was identified using exploratory and confirmatory factor analysis with satisfactory fit indices (χ2/df = 1.318, comparative fit index = 0.985, Tucker–Lewis Index = 0.983, and Root Mean Square Error of Approximation = 0.034). Breastfeeding attitudes positively correlated with breastfeeding knowledge (r = 0.74, p < 0.001) and negatively correlated with anxiety symptoms (r = −0.13, p = 0.04). Students who were older, in a higher academic year, and majoring in medicine had significantly higher breastfeeding attitude scores (ps < 0.05). Conclusions: The Vietnamese version of the IIFAS demonstrates excellent reliability and validity, making it a robust tool for assessing breastfeeding attitudes and informing tailored educational programs among healthcare students.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".