Supplementary Material for: Psychometric Performance of the Memory Complain Scale among Colombian Individuals of 60 Years and Older
Bibliographic record
Abstract
Introduction: The Memory Complaint Scale (MCS-15) is a 15-item instrument to explore frequent forgetfulness in daily life in people with possible cognitive impairment. However, knowledge about its psychometric performance is limited. Objective: The objective of this study was to know the dimensionality and internal consistency of the MCS-15 in Colombian older adults. Methods: A probabilistic sample of 1,957 older adults from the general Colombian population was taken, aged between 60 and 98 years (mean = 71.0 ± 7.9), and 62.2% were women. Internal consistency (Cronbach’s alpha and McDonald’s omega) and dimensionality (exploratory and confirmatory factor analysis) were calculated for the original and ten-item versions. Results: The 15-item version showed Cronbach’s alpha and McDonald’s omega of 0.91, and one dimension accounted for 45.3% of the variance. A version of ten items showed Cronbach’s alpha and McDonald’s omega of 0.89 and a single factor that explained 50.9% of the variance with better indicators in the confirmatory factor analysis. Convergence with the shortened Mini-Mental State Examination was rs = 0.43 (p < 0.001), and the Montreal Cognitive Assessment test was rs = 0.38 (p < 0.001). The nomological validity with the geriatric depression scale was rs = 0.44 (p < 0.001), and women scored higher than men (p < 0.001). Conclusions: The MCS-15 shows high internal consistency with poor dimensionality. However, a ten-item version shows high internal consistency and a clear one-dimensional structure. More research is needed: testing the performance against a structured interview for major cognitive impairment.
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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 | 0.002 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.722 | 0.162 |
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".