Translation and Cultural Adaptation of the Ages and Stages Questionnaires (ASQ) Worldwide: A Scoping Review
Bibliographic record
Abstract
OBJECTIVE: This scoping review aims to provide a data mapping and narrative synthesis of the available peer-reviewed scientific literature on the translation and cultural adaptation processes relative to the Ages and Stages Questionnaires (ASQ) as reported by the authors. It also seeks to paint an overall portrait of the implementation of the translated and culturally adapted ASQ worldwide. METHODS: Articles published between 1995 and May 11, 2018, were identified via systematic searches of peer-reviewed literature carried out using CINAHL, Scopus, MEDLINE, Education Source, PsycINFO, and ERIC. The articles included in the qualitative synthesis were coded based on an extraction form developed for the study. RESULTS: In the 46 articles surveyed, 37 different cultural adaptations were identified in 29 languages and 27 countries. Translations were included in 33 cultural adaptations, and language modifications were reported in 18 adaptations. The forward-backward translation method was reported in 25 cases. The authors declared having made cultural content, language, visual, and/or conceptual modifications in 26 adaptations. Cultural content modifications were reported in 24 adaptations. At least one method (pilot study, individual interview, survey or focus group with respondents) was reported in 24 adaptations. CONCLUSION: Cultural modifications were relatively minor and were, in general, made to establish equivalence with the source version. As well, the processes used to translate and culturally adapt the ASQ varied widely based on the types of methods. Additional work should be conducted to document the process of this crucial phase.
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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 | 0.147 | 0.395 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.028 | 0.029 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".