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Record W3034068202 · doi:10.1002/alz.12116

Repetitive negative thinking is associated with amyloid, tau, and cognitive decline

2020· article· en· W3034068202 on OpenAlexafffund
Natalie L. Marchant, Lise R. Lovland, Rebecca Jones, Alexa Pichet Binette, Julie Gonneaud, Eider M. Arenaza‐Urquijo, Gaël Chételat, Sylvia Villeneuve

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health ResearchAlzheimer SocietyGovernment of CanadaAlzheimer's SocietyPfizerFondation Brain CanadaMcGill UniversityPfizer CanadaAlzheimer's Association
KeywordsCognitive declineCognitionAnxietyDepression (economics)CohortConfoundingNeuroimagingAmyloid (mycology)PsychologyDiseaseMedicineClinical psychologyEffects of sleep deprivation on cognitive performanceOncologyInternal medicineDementiaPsychiatryPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: The Cognitive Debt hypothesis proposes that repetitive negative thinking (RNT), a modifiable process common to many psychological risk factors for Alzheimer's disease (AD) may itself increase risk. We sought to empirically examine relationships between RNT and markers of AD, compared with anxiety and depression symptoms. METHODS: Two hundred and ninety-two older adults with longitudinal cognitive assessments, including 113 with amyloid-positron emission tomography (PET) and tau-PET scans, from the PREVENT-AD cohort and 68 adults with amyloid-PET scans from the IMAP+ cohort were included. All participants completed RNT, anxiety, and depression questionnaires. RESULTS: RNT was associated with decline in global cognition (P = .02); immediate (P = .03) and delayed memory (P = .04); and global amyloid (PREVENT-AD: P = .01; IMAP+: P = .03) and entorhinal tau (P = .02) deposition. Relationships remained after adjusting for potential confounders. DISCUSSION: RNT was associated with decline in cognitive domains affected early in AD and with neuroimaging AD biomarkers. Future research could investigate whether modifying RNT reduces AD risk.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.076
GPT teacher head0.294
Teacher spread0.219 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations113
Published2020
Admission routes2
Has abstractyes

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