Mild Behavioral Impairment in Psychogeriatric Patients: Clinical Features and Psychopathology Severity
Bibliographic record
Abstract
The Mild Behavioral Impairment (MBI) concept was developed to determine whether late-onset persistent neuropsychiatric symptoms (NPSs) may be early manifestations of cognitive decline. Our study aims to investigate the prevalence and differentiating features of MBI with respect to major neurocognitive disorders (MNDs) and primary psychiatric disorders (PPDs). A total of 144 elderly patients who were referred to our psychogeriatric outpatient service were recruited. The severity of mental illness was evaluated by means of the Clinical Global Impression Severity scale, the severity of psychopathology was evaluated by means of the Brief Psychiatric Rating Scale (BPRS), and overall functioning was evaluated by means of the Global Assessment of Functioning scale. The sample included 73 (50.6%) patients with PPDs, 40 (27.8%) patients with MBI, and 31 (21.5%) patients with MNDs. Patients with MNDs reported the greatest severity of mental illness, the highest BPRS Total, Psychosis, Activation, and Negative Symptom scores, and the lowest functioning. Patients with MBI and PPDs had comparable levels of severity of mental illness and overall functioning, but MBI patients reported higher BPRS Total and Negative Symptom scores than PPD patients. Patients with MBI frequently reported specific clinical features, including a higher severity of apathy and motor retardation. These features merit further investigation since they may help the differential diagnosis between MBI and PPDs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".