MBI‐C structure in MBI participants from the CompAS and Pisa cohort studies: A Multidimensional Scaling Approach
Bibliographic record
Abstract
BACKGROUND: The Mild Behavioral Impairment Checklist (MBI-C) is a 34-question tool that assess neuropsychiatric symptoms (NPS) in individuals at risk of dementia. However, its foundational structure is still not well understood. Multidimensional Scaling (MDS) has some advantages that make it appropriate to analyze MBI-C's structure:(1) provides orthogonal, normalized dimensions to explain items relationships; (2) is iterative, not analytic, requiring no prior assumptions about the data; (3) offers simpler solutions with fewer dimensions for a good fit. Thus, we aimed to analyze the underlying structure of the MBI-C at baseline by using MDS in a sample of MBI participants from the CompAS and the Pisa cohort studies. METHOD: Participants from the CompAS and Pisa studies were recruited, respectively, at primary care health centers and psychogeriatric outpatient service. Pre-dementia participants from the Pisa and the CompAS studies completed the MBI-C and only those with met the MBI diagnosis criteria were considered (Pisa=55; CompAS=24). Regarding the MDS analyses, a two-step bidimensional weighted dichotomous MDS was performed. RESULTS: Study comparisons showed only significant age differences, being the participants from the Pisa study older than those from the CompAS. No significant differences were found in the other variables (see Table 1). The MDS analyses showed optimal fit indices (stress-II = .25; D.A.F. = .98). Figure 1 shows the coordinates for the MBI-C items in the bidimensional solution. Dimension I (horizontal) differentiate between internalizing vs externalizing symptoms. Dimension II (vertical) distinguishes between behavioral-goal directed dyscontrol vs emotional dysregulation. Thus, these quadrants indicate symptoms of Covert-Goal directed dysregulation (I, top left); Overt-Goal directed dyscontrol (II, top right); Overt-emotional dyscontrol (III, bottom right); and Covert-emotional dysregulation (IV, bottom left). CONCLUSION: Results suggest two main criteria underline NPS included in the original scale: internalizing vs externalizing symptoms and behavioral-goal directed dyscontrol vs emotional dysregulation. These two criteria seem to differentiate between four NPS states (Covert-Goal directed dysregulation, Overt-Goal directed dyscontrol, Overt-emotional dyscontrol, and Covert-emotional dysregulation), which could be useful in the determination of risk factors for predementia participants.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".