Adapting to reality: Effect of Online Assessments as Compared to In‐Person Assessments
Bibliographic record
Abstract
Abstract Background Neuropsychological evaluations are normally assessed in‐person by a trained psychometrician using a variety of tests representing several domains. The COVID‐19 pandemic has obliged medicine and research to switch to online assessment. However, minimal research has tested the reliability of conducting cognitive evaluations online versus in‐person. This study aims to explore the clinical utility of virtually assisted neuropsychological evaluations in a comparative analysis following the effects of the COVID‐19 pandemic. Method 62 cognitively unimpaired (CU) individuals from the TRIAD cohort underwent baseline and follow‐up neuropsychological assessments which included the Boston Naming Test (Short Form), BORB‐Object Recognition Task, WASI‐II Matrix Reasoning, WAIS‐III Digit Span, D‐KEFS Category Fluency Tests, Rey Auditory Verbal Learning Test (RAVLT), and Free & Cued Selective Reminding Test (FCSRT). Participants were considered CU when they obtained a CDR score of 0, MMSE ≥ 26, with negative amyloid‐β and tau statuses (global amyloid‐β [18F]AZD4694 <1.55 SUVR and temporal meta‐ROI [18F]MK6240 <1.24 SUVR). Participants were divided into two equally represented groups, both of which completed an in‐person baseline evaluation. 30 participants completed their follow‐up evaluation in‐person and 32 completed their evaluation virtually. A mixed linear regression model was used to assess the difference in the rate of change in scores between cohorts using age, sex, and years of education as covariates. Result Follow‐up at‐home neuropsychological test results did not significantly differ from in‐person scores across all domains. Participant demographics are shown in table 1. The Boston Naming Test (Short Form), BORB‐Object Recognition Task, WASI‐II Matrix Reasoning, WAIS‐III Digit Span, D‐KEFS Category Fluency Tests, Rey Auditory Verbal Learning Test (RAVLT), and Free & Cued Selective Reminding Test (FCSRT) yielded p values of 0.47, 0.74, 0.17, 0.28, 0.13, 0.53, and 0.77, respectively. Conclusion Scores from our battery were selected to represent the different cognitive domains. Based on our findings, there was no difference when individuals conducted in‐person versus online assessments. These results will allow for the geriatric community to receive the medical assistance they require without having to impose any inconveniences or unnecessary health risks. Additionally, virtual assessments will assist to increase contact for prospective participants which would otherwise not be possible in‐person.
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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 | 0.011 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".