Assessment practices of clinical neuropsychologists in the United States and Canada: A survey of INS, NAN, and APA Division 40 members
Bibliographic record
Abstract
The present study surveyed assessment practices and test usage patterns among clinical neuropsychologists. Respondents were 747 North American, doctorate-level psychologists (40% usable response rate) affiliated with Division 40 of the American Psychological Association (APA), the National Academy of Neuropsychology (NAN), or the International Neuropsychological Society (INS). Respondents first provided basic demographic and practice-related information and reported their most frequently utilized instruments. Overall, the Wechsler Adult Intelligence Scales and Wechsler Memory Scales were most frequently used, followed by the Trail Making Test, California Verbal Learning Test, and Wechsler Intelligence Scale for Children. Respondents also reviewed a vignette about a traumatic brain injury patient, and then reported the instruments they would use to assess this patient's specific cognitive symptomatology, general cognitive ability, and capacity to return to work. Particular attention was paid to the areas of memory, attention, and executive functioning. The current study represents the largest and most comprehensive test usage survey conducted to date within the field of clinical neuropsychology. Survey results update and greatly expand knowledge about neuropsychologists' assessment practices. Following a review of findings, results are compared to those obtained in prior surveys and implications for the field of neuropsychology are discussed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".