The effect of study partner characteristics on the reporting of neuropsychiatric symptoms across the neurocognitive spectrum
Bibliographic record
Abstract
OBJECTIVES: We explored the influence of study partner (SP) characteristics on SP-reported neuropsychiatric symptoms (NPS) presence across the neurocognitive spectrum and on the prognostic utility of mild behavioral impairment (MBI). DESIGN, SETTING, AND PARTICIPANTS: We performed cross-sectional (n = 26,748) and longitudinal (n = 12,794) analyses using participant-SP dyad data from the National Alzheimer's Coordinating Center. Participants were cognitively normal (CN; n = 11,951) or had mild cognitive impairment (MCI; n = 5686) or dementia (n = 9111). MEASUREMENTS: SPs rated NPS using the Neuropsychiatric Inventory Questionnaire. We used multivariable logistic regression to model the association between SP characteristics (age, sex, and relationship to participant [spouse, child, and other]) and NPS status (outcome). Cox regressions assessed SP characteristics as moderators of MBI associations with incident dementia or as predictors of incident dementia in MBI + participants only. RESULTS: Among CN persons, younger, female, and spouse SPs reported NPS more frequently. In MCI, younger SPs and those who were spouses or children of participants reported higher NPS odds. For dementia participants, NPS odds were higher in female and spouse SPs. MBI associations with incident dementia were slightly weaker when SPs were older but did not depend on SP sex or relationship to participant. Among MBI + participants with spouse or child SPs, hazard for dementia was higher when compared to MBI + participants with other SPs. CONCLUSIONS: SP age, sex, and relationship to participant influence NPS reporting across the neurocognitive spectrum, with potential implications for MBI prognosis. Considering SP characteristics may enhance the accuracy of NPS assessments, which may facilitate therapy planning and prognosis.
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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 | 0.005 | 0.018 |
| 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) | 0.002 | 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".