Feasibility Study of the Boston Naming Test for the Arab Population
Bibliographic record
Abstract
Introduction The Boston Naming Test (BNT) is a widely used US neuropsychological evaluation of confrontation naming for the examination of adults and children with learning disabilities and diagnosis of communication disorders, aphasia, dementia, and acquired brain injury or dysfunction. The purpose of the present study is to evaluate the practicality of the original English version of the 60-item BNT (BNT-60) on an Arab population and the need for a new adaptive Arabic version sensitive to cultural biases and to offer normative data that can serve as a reference for researchers and clinicians in the Gulf region, especially the Kingdom of Saudi Arabia (KSA). Data relating to the familiarity degree of the BNT-60 were also collected. Methods This research involved 105 randomly selected and cognitively healthy college students who were native Arabic speakers recruited in Jeddah. The Montreal Cognitive Assessment (MOCA) was administered with a cutoff score of 26. The participants were examined for naming accuracy, naming agreement, and familiarity in using the BNT-60. The data were then analyzed and compared with the findings from studies conducted in the United States. Results The BNT-60 was administered to 105 university students from the KSA, and the results were compared with the BNT-60 booklet norms (second edition). Their average performance was noticeably below the norms established by the original test standards. Compared with the participants in the US studies, the participants made approximately 65% more errors on the items including pretzel, wreath, beaver, harmonica, acorn, stilts, harp, hammock, knocker, pelican, muzzle, unicorn, funnel, accordion, asparagus, tripod, yoke, and trellis and 25% more errors on the items including seahorse, dart, igloo, sphinx, palette, and abacus. The item "boomerang" was not compared with the US sample because of differences in the version of the BNT, but the errors in naming this item were as frequent as those in naming the other misrecognized items. The internal consistency among the items' degrees of familiarity was also very high (α = 0.966), and a significant connection (r = 0.837, P < 0.001) was observed between object familiarity and naming accuracy. The Arabic-speaking population in the KSA and English-speaking population in the United States showed very different levels of familiarity with numerous items. Conclusion The participants' familiarity with the BNT objects varied depending on their culture and impacted their naming accuracy and overall scores on the test. Accordingly, the possibility of cultural biases should be considered when administering the BNT to the population of the KSA and the possibility of making changes so that the test better reflects the Arab culture as suggested.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".