Virtual Cognitive Testing‐ Neuropsychology, MyCogHealth and Cogniciti
Bibliographic record
Abstract
Abstract Background It is increasingly possible to mobilize technology to more readily evaluate effects of lifestyle interventions. Past research has found virtual administration of neuropsychological testing yields comparable results to in‐person assessments. Self‐administered paradigms using app‐and web‐based assessments have likewise shown promise for measuring cognition longitudinally. The Brain Health Support Program (BHSP) investigates three highly scalable cognitive assessment approaches for use in dementia prevention trials. Method The BHSP includes 60‐minute traditional neuropsychological assessments administered remotely via videoconferencing by a study coordinator (baseline & 12‐mos.), 20‐minute self‐administered web‐based cognitive screening assessments with Cogniciti (baseline, 6, and 12‐mos.), and self‐administered ecological momentary assessments using the MyCogHealth app. An intensive measurement protocol is implemented with MyCogHealth whereby participants completed five assessment “bursts” in three‐month intervals. Each “burst” involved five‐minute cognitive testing sessions completed twice daily across seven days. Remote neuropsychological assessments and Cogniciti were completed at home on personal devices. Study phones were provided to those without a smartphone capable of operating MyCogHealth. A three‐month feasibility pilot was completed in early 2022. Result The BHSP Pilot found 100% compliance with remote neuropsychological assessments. Participants averaged 85% compliance with the MyCogHealth burst testing schedule. Self‐reported satisfaction with MyCogHealth ranged from 85% (comfort using the app) to 95% (satisfaction with burst testing schedule). During the BHSP Baseline, all participants successfully completed the remote neuropsychological assessment, Cogniciti, and MyCogHealth. 82% had a personal mobile device for operating MyCogHealth and the remainder were provided study phones. Mixed linear regression analyses modeling cognitive trajectories over the first six months of the BHSP in relation to modifiable dementia risk factors and change in health behaviours will be presented. Marginal and conditional R‐Squared values will characterize the relative sensitivity of the three virtual testing paradigms for measuring change. Conclusion All three approaches to virtual cognitive testing were feasible for use with the BHSP cohort. Longitudinal results provide an evidence base to inform future applications of virtual testing in dementia prevention trials. Virtual cognitive testing could be stage‐setting by saving clinic visits and lowering trial costs that would in turn expand geographic diversity of participants and enable more interventions to be evaluated.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".