Evaluating functional abilities within the context of memory assessment: A practice survey of neuropsychologists
Bibliographic record
Abstract
Objective: Functioning in daily life is an important consideration when differentiating between individuals with normal cognition, mild neurocognitive disorder, and major neurocognitive disorder. Despite this, there is no gold standard measurement approach for assessing functional abilities and few guidelines on how to do so. The objective of this study was to examine neuropsychologists’ practices regarding the assessment of functional abilities across the spectrum of memory ability. Method: A total of 278 psychologists who routinely conduct neuropsychological assessments completed an online survey (estimated 15% response rate) querying their practices and perspectives with respect to the assessment of functional abilities. Results: Respondents identified that changes to several components of daily functioning, including activities of daily living, were important when evaluating functional abilities. Respondents reported utilizing a variety of instruments to assess functioning, with an overwhelming majority indicating the use of semi-structured interviews. Although most respondents are satisfied with existing tools, a quarter of respondents felt strongly that there was a need for more instruments of everyday functioning. Respondents further indicated that their recommendations to patients, particularly regarding compensatory strategies and follow-up with other professionals, were informed by results of their functional assessment. Conclusions: Overall, our survey results indicate that neuropsychologists perceive multiple factors of daily life to be important considerations when evaluating functioning, use a variety of techniques to assess functioning, and perceive a need for more measures of functional abilities.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".