Mild behavioral impairment in people with mild cognitive impairment: Are the two conditions related?
Bibliographic record
Abstract
Background Mild cognitive impairment (MCI) and mild behavioral impairment (MBI) are both considered potential prodromal stages of dementia, especially Alzheimer's disease. Previous literature has lacked specific information about MBI in individuals with MCI and associations of several aspects of both, MBI and MCI. Objective Our aim was to investigate whether associations exist between aspects of MBI and aspects of cognitive performance in certain dimensions of the Montreal Cognitive Assessment (MoCA). Methods We used baseline data from the double-blind randomized controlled intervention MCI-CCT-study. Current cognitive performance of individuals with MCI was measured with the MoCA. MBI was assessed with the MBI Shortscale (MBI short), which was administered through a self-report interview. Associations were assessed with Pearson correlations. Sensitivity analyses were conducted for gender and cognition. Group differences were examined with independent samples t-tests or Welch test. Significant correlations were considered in binary logistic regressions under control of covariates. Results There was no significant correlation between the current MoCA and MBI short scores in the total sample or in the gender-related analysis. Using dichotomized cognitive performance, significant correlations between MCI and MBI were revealed for individuals with lower MoCA scores. On the task level, several significant associations were identified between MoCA dimensions and MBI dimensions in the total sample and in the sensitivity analyses, also under control of covariates. Conclusions Our findings support the hypothesis that with increasing cognitive decline, the association between MCI and MBI becomes stronger. Furthermore, a certain cut-off on the MoCA must be reached to identify a correlation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".