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Record W2897142691 · doi:10.1016/j.jalz.2018.06.1920

P3‐554: PROFILE OF MILD BEHAVIOURAL IMPAIRMENT IN A POPULATION‐BASED SAMPLE OF ADULTS AGED 50 AND OVER: INITIAL FINDINGS FROM THE PROTECT STUDY

2018· article· en· W2897142691 on OpenAlexaff
Byron Creese, Helen Brooker, Zahinoor Ismail, Dag Aarsland, Anne Corbett, Zunera Khan, María Megalogeni, Clive Ballard, Keith Wesnes

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChecklistDementiaMoodPsychologyClinical psychologyAnxietyCognitive impairmentPsychosisPopulationCognitionPsychiatryMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

Neuropsychiatric symptoms (NPS) are common and historically described in dementia. The co-occurrence of NPS alongside mild cognitive impairment increases progression to dementia, and as such recent years have seen an increasing focus on the manifestations of NPS in preclinical populations. Behavioural deficits may be easier to screen than cognitive changes, and so represent an important potential tool in dementia prediction. The MBI checklist (MBI-C) is a tool explicitly developed for MBI case ascertainment, in accordance with the ISTAART-AA MBI criteria. The purpose of this study is to describe for the first time the frequencies and distribution of these symptoms in the general older adult population. 10,952 people aged 50 or over without a formal diagnosis of dementia completed the Mild Behavioural Impairment Checklist (MBI-C) checklist online. 7,504 also had a project partner who completed the questions with reference to the main participant. Frequencies of responses to each MBI question and domain are presented and comparisons are made between self-reported and informant-reported symptoms. 47.5% of people reported some degree of behavioural disturbance; for 9% of participants this was clinically significant. Frequencies of the interest motivation and drive, mood and anxiety, impulse control/reward, social norms, sensory experience/psychosis domains were 26, 44, 31, 8 and 5% respectively. The frequencies for informant-rated symptoms were similar overall but there were a number of discrepancies between informant-rated and self-rated symptom frequencies. The factor analysis identified 5 independent groupings, with factors 1 and 2 loading exclusively on MBI domains 1 and 2. MBI symptoms and domains are highly prevalent in the general population. Establishing long term outcomes for these individuals, stratified by appropriate measurement cut-points, and incorporating their cognitive and genetic profiles may lead to enhanced dementia prediction and be a useful tool for selection into clinical trials, or for implementation of pharmacological and non-pharmacological prevention interventions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.336
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2018
Admission routes1
Has abstractyes

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