C - 62Contributing Towards a Cultural Neuropsychology Assessment Decision-Making Framework: Comparison of WAIS-IV Norms from Colombia, Chile, Mexico, Spain, United States, and Canada
Bibliographic record
Abstract
Objective: Test and normative data selection in cross-cultural neuropsychology remain a complex issue. Despite growing awareness, more studies and instruments are needed for assessments to adequately address the impact of cultural factors, such as quantity and quality of education. In this study, we examine the interpretive effects of applying six different relevant WAIS-IV norms to a Colombian sample. Method: A sample of 305 highly educated Colombian corporate executives completed the WAIS-IV. Data were scored using norms from Colombia, Chile, Mexico, Spain, United States, and Canada and scores were compared using ANOVA. Additionally, a comparative sociodemographic framework was established to contextualize our sample to the standardization samples and populations of the six countries. Results: Colombian and Chilean norms yielded systematically similar FSIQ/Index scores (mean range = 117–121), while incrementally lower scores were found with norms from Mexico (−3–9 points), Spain (−3–11 points), USA (−8–13 points), and Canada (−11–18 points). The Verbal Comprehension Index (VCI) was the only with a different pattern: highest scores were obtained with Mexican and Spanish norms, followed by Colombian, Chilean, American, and Canadian norms. Conclusions: Although the Chilean norms are more frequently used in Colombia, the recently developed Colombian norms appear optimal for our sample; the scores do not have meaningful differences with those obtained with Chilean norms and offer fidelity to local population representation. Mexican, Spanish, American, and Canadian norms all underestimate WAIS-IV scores and distort the sample’s score distribution. Finally, notably different VCI score patterns suggest the verbal comprehension WAIS-IV construct may have some cultural nuances likely associated with education system differences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".