The Chinese translation and cross-cultural adaptation of PRISMA-7 questionnaire: an observational study to establish the accuracy, reliability and validity
Bibliographic record
Abstract
BACKGROUND: Frailty is a health condition linked to adverse health outcomes and lower life quality. The PRISMA-7, a 7-item questionnaire from the Program on Research for Integrating Services for the Maintenance of Autonomy (PRISMA), is a validated case-finding tool for frailty with good sensitivity and specificity. This study aimed to translate, culturally adapt, and validate the PRISMA-7 questionnaire for Chinese use. METHODS: A prospective observational study with convenience sampling recruited bilingual adults aged 65 and over living in the community. The Functional Autonomy Measurement System (SMAF) was the gold standard benchmark. The English PRISMA-7 questionnaire was culturally adapted to Chinese using forward and backward translation. Intra- and inter-rater reliability were determined using the intraclass correlation coefficient (ICC). Face, content and criterion validity were determined. The Receiver Operator characteristic (ROC) curve determined the optimal cut-off score. RESULTS: One-hundred-twenty participants (55 females and 65 males) were recruited. The Chinese PRISMA-7 questionnaire had excellent intra-rater and inter-rater reliability (ICC = 1.000). The rigorous forward and backward translation established the face and content validity. The moderately high correlations between the English PRISMA-7 with SMAF (r = - 0.655, p < 0.001) and Chinese PRISMA-7 with SMAF (r = - 0.653, p < 0.001) pairs established the criterion validity. An optimal cut-off score of three "Yes" responses was reported with 100% sensitivity and 85.3% specificity. CONCLUSION: This translation, cross-cultural adaptation, and validation study established the Chinese PRISMA-7 questionnaire. The preliminary results suggest adequate diagnostic test accuracy for frailty screening among the Chinese-literate community.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".