Screening Scales in Neuropsychological Rehabilitation: Opportunities, Requirements and Limitations
Bibliographic record
Abstract
Popularity of screening scales in the assessment of cognitive functions in neuropsychological rehabilitation often involves their direct adoption in Russia without appropriate approbation and improper conclusions. In the article based on the examples of Montreal Cognitive Assessment and the Mini-Mental State Examination we consider the requirements, limitations and conditions for the use of standardized instruments in cognitive neuropsychology in Russia. We consider four groups of requirements: (1) taking into account the theoretical basis of the methodic, (2) keeping the scope, conditions and samples described for the instrument, (3) adaptation and validation in Russia, (4) the choice of psychometric indicators that take into inter-disciplinary demands and goals for rehabilitation. Since the process, the principles and the results of neuropsychological diagnostics, as well as setting goals and selection methods for rehabilitation depend on the neuropsychological approach that the specialist uses, comparison of neurocognitive approach with the system-dynamic approach to localization of higher mental functions is necessary. The results of neuropsychological testing, based on one theoretical approach can be understood, qualified and substantiated within the framework of a different approach, but not directly transferred. Screening tools have a limited task of identifying high-risk groups for subsequent more detailed examination and if dynamics of the large groups is assessed, but they cannot substitute neuropsychological examination. In accordance with the principles of neurocognitive approach on which screening tools are based, their use requires to proove not only linguistic, but also the construct, measurement and metric equivalence to the original version of the test. Choice of psychometric properties that are important to justify the applicability of the instrument for concrete rehabilitation tasks is ambiguous and depends on the objectives (diagnostics, rehabilitation, expertise, etc.), target groups and interdisciplinary requirements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.118 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".