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Record W2766007293 · doi:10.1016/j.jalz.2017.06.927

[P2–274]: MILD BEHAVIORAL IMPAIRMENT: WHAT ARE THE RISK FACTORS?

2017· article· en· W2766007293 on OpenAlexaff
Moyra E. Mortby, Ranmalee Eramudugolla, Richard Burns, Zahinoor Ismail, Kaarin J. Anstey

Bibliographic record

VenueAlzheimer s & Dementia · 2017
Typearticle
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiopsychosocial modelMedicineDepression (economics)Social supportInternal medicineCognitive impairmentDiseaseMultivariate analysisPsychologyPsychiatryClinical psychology

Abstract

fetched live from OpenAlex

Little is known about the genesis and predictors of Mild Behavioural Impairment (MBI), a construct describing the emergence of sustained and impactful neuropsychiatric symptoms in advance of or in combination with Mild Cognitive Impairment (MCI) (Ismail et al., 2016). This is the first epidemiological study to examine the role of biopsychosocial factors as risk factors for MBI 12 years later. 1377 older adults (age range 72–79 years; 52% male) with normal and preclinical cognition at wave 4 of the PATH Through Life Project (MCI=133; ‘cognitively normal, but-at-risk’ = 397; cognitively healthy = 847). Baseline depressive symptoms (PHQ-9), self-reported cardio-metabolic conditions (e.g., diabetes, heart disease), number of medications, neurological events (e.g., stroke, TIA, head injury, infection), physical activity, social engagement, negative social support and behavioural activation (BISBAS) were examined as risk factors for MBI 12 years later. MBI was assessed in accordance with the ISTAART-AA diagnostic criteria for MBI using the Neuropsychiatric Inventory. Univariate associations were found between cardio-metabolic conditions (OR=3.98, 95% CI: 1.80–8.78), number of medications (OR=3.44, 95% CI: 1.84–6.43), negative social support (OR=1.18, 95% CI: 1.10–1.26), depression (OR=1.15, 95% CI: 1.11–1.19), female gender (OR=0.78, 95% CI: 0.62–0.97), social engagement (OR=0.47, 95% CI: 0.27–0.83) and a higher risk of MBI 12 years later. Multivariate analyses showed an increased risk of MBI for number of medications (OR=2.22, 95% CI: 1.11–4.44), negative social support (OR=1.12, 95% CI: 1.04–1.25), depression (OR=1.12, 95% CI: 1.07–1.17) and female gender (OR=0.74, 95% CI: 0.58–0.94) when all variables were adjusted for. Gender interactions were not significant. In a subclinical population-based sample, biopsychosocial factors of depression, negative social support, number of medications and female gender were associated with a higher risk of MBI 12 years later. Our findings are the first to investigate modifiable risk factors for MBI and highlight the need to consider the interplay between biological, psychological and social factors in the context of MBI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.092
GPT teacher head0.373
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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