Cross-cultural adaptation of the Schizophrenia Caregiver Questionnaire (SCQ) and the Caregiver Global Impression (CaGI) Scales in 11 languages
Bibliographic record
Abstract
BACKGROUND: The Schizophrenia Caregiver Questionnaire (SCQ) was developed to provide a comprehensive view of caregivers' subjective experiences of the impacts of caring for someone with schizophrenia. The Caregiver Global Impression (CaGI) scales were designed to assess their perception of the severity of the schizophrenia symptoms, of change in schizophrenia symptoms and in the experience of caring since the beginning of the study. The objectives of the study were to translate the SCQ and CaGI scales in 11 languages [French (Canada, France), English (Canada, UK, Australia), German (Germany), Italian (Italy), Spanish (Spain), Dutch (the Netherlands), Finnish (Finland), and Swedish (Sweden)], to present evidence that the translations capture the concepts of the original questionnaires and are well understood by caregivers of patients with schizophrenia in each target country. METHODS: The different language versions were developed using a standard or adjusted linguistic validation process fully complying with the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) recommended procedures. RESULTS: Interviews were conducted with 55 caregivers of patients with schizophrenia from 10 countries representing the 11 different languages. Participants ranged in age from 28 to 84 years and had 5 to 16 years of education. Women represented 69.1 % (38/55) of the sample. Fourteen out of the 32 items of the SCQ generated difficulties which were mostly of semantic origin (13 items). The translation of the CaGI scales did not raise any major difficulty. Only five out of the 55 caregivers had difficulty understanding the meaning of the translations of "degree" in the expressions "degree of change in experience of caring" and "degree of change in symptoms". CONCLUSIONS: Translations of the SCQ and CaGI scales into 11 languages adequately captured the concepts in the original English versions of the questionnaires, thereby demonstrating the conceptual, semantic, and cultural equivalence of each translation.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".