FROM BRAZIL TO CANADA: TRANSLATION AND CROSS-CULTURAL ADAPTATION OF AN APP FOR BREASTFEEDING PREMATURE BABIES
Bibliographic record
Abstract
ABSTRACT Objective: Translating and culturally adapting the AmamentaCoach app, originally developed in Brazil, for use by mothers of premature babies in Canada, through international research collaboration. Method: This is applied research in the form of technological development, in which the World Health Organization's recommendations for the translation and cultural adaptation of instruments were taken into account. Five Canadian researchers who are experts in breastfeeding promotion evaluated the appearance, language, and content of the new version of the app. An 18-item instrument was used with Likert scale response options indicating the degree of agreement for each statement, where 1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, and 5=Strongly Agree. Results: In the first round of evaluation, the total Content Validity Index (CVI-T) was 0.72, and 6 of the 18 items did not reach CVI-I ≥0.8. A total of 59 screens (74%) of the app were modified, especially in terms of language and the quality of the translation of the texts, reaching CVI-T=0.87 in the second round. Conclusion: The Breastfeeding Coach app showed expressions adjusted to Canadian reality, meaningful images, and new auxiliary resources specific to Canada. Changes in content and attenuations in the rhetorical textual pattern, prompted by cultural differences in the nurse-client relationship and the woman's role in these two different societies, sought consistency with the reality of breastfeeding practices in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".