Regular cognitive self-monitoring in community-dwelling older adults using an internet-based tool
Bibliographic record
Abstract
INTRODUCTION: Monitoring for various health conditions (e.g., breast cancer, hypertension) has become common practice. However, there is still no established tool for regular monitoring of cognition. In this pilot longitudinal study, we examined the utility and feasibility of internet-based cognitive self-monitoring using data from the first 12 months of this ongoing study. METHOD: Cognitively healthy community-dwelling older adults (Montreal Cognitive Assessment ≥ 26) were enrolled on a rolling basis and were trained in self-administration of the internet-based version of the CogState Brief Battery. The battery uses playing cards and includes Detection, Identification, One Back, and One Card Learning subtasks. RESULTS: Of the 118 participants enrolled, 26 dropped out, mostly around first in-home session. Common reasons for participant attrition were internet browser problems, health problems, and computer problems. Common reasons for delayed session completion were being busy, being out of town, and health problems. Participants needed about one reminder phone call per four completed sessions or one reminder email per five completed sessions. Performance across the monthly sessions showed slight (but significant) improvement on three of the four tasks. Change in performance was unaffected by individual characteristics with the exception of previous computer use, with less frequent users showing greater improvement on One Card Learning. We also found low intraindividual variability in monthly test scores beyond the first self-administered testing session. CONCLUSIONS: Internet-based self-monitoring offers a potentially feasible and effective method of continuous cognitive monitoring among older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".