The Breastfeeding Self-Efficacy Scale–Short Form (BSES-SF): German Translation and Psychometric Assessment
Bibliographic record
Abstract
BACKGROUND: German-speaking mothers have breastfeeding rates below the international breastfeeding recommendations. Previous research has found that breastfeeding self-efficacy is an important and modifiable predictor of breastfeeding outcomes, thus improving breastfeeding rates. The Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF) is used in many countries to assess maternal breastfeeding self-efficacy. This instrument has not been available in German. RESEARCH AIMS: To translate the BSES-SF into German and assess its psychometric properties among breastfeeding mothers up to 12 weeks postpartum. METHODS: This cross-sectional study was conducted online with 355 breastfeeding mothers recruited from breastfeeding groups through Facebook. The BSES-SF was translated into German using forward and back-translation. To test reliability, item-total characteristics, including Cronbach's alpha, were examined. We used principal component analysis, as well as known-groups comparisons for evaluating construct validity, and examined the relationship between breastfeeding self-efficacy and demographic variables. RESULTS: = 4.32). The Cronbach's alpha coefficient was .88 and corrected item-total correlations ranged between .37 and .73. Principal components analysis yielded one component with factor loadings >.40 and an eigenvalue of 5.62, which explained 40% of the total variance. In addition, known group comparisons provided further evidence for construct validity. There was no significant difference in BSES-SF scores in terms of demographic and obstetrics characteristics. CONCLUSION: Our results provide evidence that the German version of the BSES-SF is a reliable and valid tool for measuring breastfeeding self-efficacy among mothers in German-speaking countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".