Validity of a novel computerized screening test system for mild cognitive impairment
Bibliographic record
Abstract
ABSTRACTBackground:The mobile screening test system for screening mild cognitive impairment (mSTS-MCI) was developed for clinical use. However, the clinical usefulness of mSTS-MCI to detect elderly with MCI from those who are cognitively healthy has yet to be validated. Moreover, the comparability between this system and traditional screening tests for MCI has not been evaluated. OBJECTIVE: The purpose of this study was to examine the validity and reliability of the mSTS-MCI and confirm the cut-off scores to detect MCI. METHOD: The data were collected from 107 healthy elderly people and 74 elderly people with MCI. Concurrent validity was examined using the Korean version of Montreal Cognitive Assessment (MoCA-K) as a gold standard test, and test-retest reliability was investigated using 30 of the study participants at four-week intervals. The sensitivity, specificity, positive predictive value, and negative predictive value (NPV) were confirmed through Receiver Operating Characteristic (ROC) analysis, and the cut-off scores for elderly people with MCI were identified. RESULTS: Concurrent validity showed statistically significant correlations between the mSTS-MCI and MoCA-K and test-rests reliability indicated high correlation. As a result of screening predictability, the mSTS-MCI had a higher NPV than the MoCA-K. CONCLUSIONS: The mSTS-MCI was identified as a system with a high degree of validity and reliability. In addition, the mSTS-MCI showed high screening predictability, indicating it can be used in the clinical field as a screening test system for mild cognitive impairment.
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 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 | 0.000 |
| 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".