A-169 Remote Cognitive Screening: A Preliminary Study of Location Administration of the Boston Cognitive Assessment (BoCA)
Bibliographic record
Abstract
Abstract Objective Digital, remote, cognitive assessment has become crucial for efficient screening of patients cognitive concerns. The Boston Cognitive Assessment (BoCA) is a brief, digital, global screening instrument that can be administered both in-office on a laptop, or remotely from patients’ homes. Potential differences in performance from completing the BoCA in-office versus completing it at home remain uninvestigated. As such, this study aimed to compared performances across these settings among demographically and cognitively matched patient samples. Method Data from 35 cognitively healthy participants who completed the BoCA (18 administered in-office; 17 remotely administered) were retroactively collected; groups were matched by age, education, gender, ethnicity, and global cognitive functioning based on their scores on a separate screening instrument. Overall BoCA scores (total = 30) as well as performance on the eight BoCA subscales (Immediate Recall, Delayed Recall, Verbal Reasoning, Visuospatial Reasoning, Executive Functions, Attention, Mental Math, and Orientation) were compared using nonparametric testing. Results A Contingency analysis and an independent samples Mann–Whitney U test confirmed the demographic and cognitive similarities between the two groups. Comparisons of BoCA scores revealed no differences in total scores or any of the BoCA subscales between those who completed the BoCA in-office and those who completed it remotely. Conclusion Results from the present study suggest that performance on the BoCA is not influenced by one’s environment at the time of administration. This further adds to the utility of the BoCA as a remote, self-administered, global screening instrument, and may support its adoption in settings where serial screening is indicated.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".