Cross-cultural adaptation and validation of the German version of the Birth Satisfaction Scale-Revised (BSS-R)
Bibliographic record
Abstract
BACKGROUND: Up to one third of women are dissatisfied with their birth experience. A negative birth experience can have detrimental outcomes, making an early detection of dissatisfaction with the birth experience very important. The Birth Satisfaction Scale-Revised (BSS-R) is a multi-dimensional measure of birth satisfaction, which has been translated into several languages. The current study aimed to translate and validate a German version of the BSS-R (DE-BSS-R). METHODS: A total of 3747 German women, who were participating in the cross-sectional study INVITE, completed the DE-BSS-R 3–4 months postpartum. The factor structure of the DE-BSS-R was tested using confirmatory factor analysis. Moreover, internal consistency as well as known-groups discriminant, divergent, convergent, and predictive validity were evaluated. RESULTS: Both the tri-dimensional and the bi-factor measurement model of the original BSS-R showed excellent fit to the data. Internal consistency was acceptable for the total score and the subscale Women’s personal attributes, but just below the recommended cut-off for the subscales Stress experienced during labour and Quality of care. However, Cronbach’s alpha did not differ significantly from the acceptable alpha values of the original BSS-R. Women with a non-instrumental vaginal birth had significantly higher birth satisfaction than women with an instrumental birth (instrumental vaginal, caesarean section). The DE-BSS-R showed good divergent, convergent, and predictive validity. CONCLUSIONS: Overall, the German cross-cultural adaptation of the BSS-R showed excellent psychometric properties. Both the total score and the three subscale scores are valid to quickly measure German women’s satisfaction with birth in research and clinical practice.
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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 | 0.007 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".