PROFESSIONAL ISSUES: ETHICSC-86Neuropsychology Research-Related Activities in the U.S. and Canada: Results from a Professional Survey
Bibliographic record
Abstract
Objective: To describe research-related activities in neuropsychology in a group of professionals in the U.S. and Canada. Method: A total of 452 self-identified neuropsychology professionals (419 from the U.S. and 33 from Canada) completed an online survey (92% completion rate), including questions regarding research-related activities. Among the respondents, 47% (102 males and 112 females, mean age 43.3, SD = 12.1) had conducted research in the area of neuropsychology in the past year. Of those, 71% were employed full-time and most worked in a hospital (49%), medical school (16%), private practice (10%), or college/university (8%) settings. Results: Ninety-three percent reported having received training in neuropsychology research. Regarding research productivity, 92% had one or more peer-reviewed publications (mode = 3); 74% had one or more book chapters; 60% had one or more non-peer-reviewed publications; and 38% had published one or more books. Forty-nine percent reported having received grant funding, while 59% had sufficient resources and materials to conduct research (e.g., personnel, etc.). Seventy-six percent reported conducting their own statistical analyses by using primarily Excel (95%), SPSS (93%), and SAS (50%), with varying degrees of proficiency. Eight percent indicated they do not always seek ethics committee approval prior to starting research projects, while 6% do not obtain informed consent. Conclusion: These findings indicate that the majority of respondents received training in neuropsychology research, with a considerable number receiving grant funding. Results also suggest the need for further training in statistical programs and ethics as well as resources to conduct research. Future studies should focus on determining neuropsychology research practices in these countries.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".