PD68 A Cross-Cultural Validation Study Of The German And English Versions Of The ICEpop CAPability measure for Adults (ICECAP-A)
Bibliographic record
Abstract
Introduction Proponents of the capability approach argue that the effect of health technologies should be measured in terms of capabilities, that is, the freedom to live as desired. The ICECAP-A, initially developed in the UK, has been used internationally to measure capability wellbeing. This study examined whether participants from Australia, Canada, Germany, the UK, and the USA similarly interpret and respond to the ICECAP-A. Methods A multigroup confirmatory factor analysis was conducted. Four types of measurement invariance were tested: configural invariance, metric invariance, scalar invariance, and residual invariance. Measurement invariance was assessed by studying the comparative fit index (CFI) and the root mean square error of approximation (RMSEA) and standardized root mean squared residual (SRMR) fit indices. For this study, data from the multi-instrument comparison database were used to compare response patterns of participants from Australia (n=1,430), Canada (n=1,330), Germany (n=1,269), the UK (n=1,356), and the USA (n=1,460). Results The configural invariant model showed adequate fit (CFI 0.992, RMSEA 0.076, SRMR 0.016), and metric invariance was established (change in variables: CFI -0.002, RMSEA -0.014, SRMR 0.015). Scalar invariance (and consequently residual invariance) was not established (change in variables: CFI -0.036, RMSEA 0.046, SRMR 0.018). Post-hoc analysis indicated that full measurement invariance could be established by excluding the German sample, with improved fit index values for configural invariance (CFI 0.994, RMSEA 0.069, SRMR 0.015), metric invariance (change in variables: CFI-0.000, RMSEA -0.020, SRMR 0.006), scalar invariance (change in variables: CFI -0.007, RMSEA 0.011, SRMR 0.006), and residual invariance (change in variables: CFI -0.002, RMSEA 0.009, RMR 0.006). Conclusions Response patterns to the German and English versions of the ICECAP-A differed. Caution should be exercised when using these two versions in the same study. Further research is required to determine whether these differences are due to linguistic variations from translation, or whether they indicate fundamental differences in participant understanding and responses to the different versions of the ICECAP-A.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".