Impact of mild behavioral impairment on longitudinal changes in cognitive performance
Bibliographic record
Abstract
Abstract Background Recent research has developed a better appreciation for non‐cognitive factors, such as neuropsychiatric symptoms (NPS), as early indicators for dementia. This has led to the development of criteria for mild behavioral impairment (MBI), or the late‐life onset of NPS. MBI has been associated with a unique cognitive phenotype, but research on longitudinal changes is limited. The goal of this study is to examine if MBI influences changes in cognitive abilities among older adults who are cognitively healthy (CH) or have mild cognitive impairment (MCI). Method Secondary data analysis of participants (n=17,291) from the National Alzheimer’s Coordinating Center who were CH (n=11,771) or diagnosed with MCI (n=5,520). Almost 25% of the sample met the operationalized diagnostic criteria for MBI (n=4,274). Cognitive performance was evaluated using tasks of attention, episodic memory, executive function, language, visuospatial ability, and processing speed. Results Cross‐sectionally, persons with MBI performed worse on tasks of attention, episodic memory, executive function, language, visuospatial ability, and processing speed compared to people without MBI. There were no significant interactions present between MBI and MCI on any of the tasks. Longitudinally up to 14 years, persons with MBI saw a greater decline on tasks of attention, executive function, language, episodic memory, and processing speed compared to individuals without MBI. Further, older adults with MBI performed significantly worse across time on tasks of executive function, language, and processing speed when compared to CH older adults without MBI. Persons with MBI and MCI performed significantly worse across time on tasks of executive function, language, processing speed, and visuospatial ability when compared to those with only MCI. Conclusion Older adults with MBI performed worse on all cognitive domains, compared to those without MBI. Additionally, CH older adults with MBI saw a greater decline across time in the domains of executive function, language, and processing speed. In the MCI group, MBI was associated with a greater decline in all of these domains in addition to visuospatial ability. The results provide support for unique cognitive phenotypes for MBI in CH older adults and MCI, that may be indicative of preclinical and prodromal symptoms of dementia.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".