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Record W2043218432 · doi:10.1080/13825585.2014.993584

Evidence of cognitive decline in older adults after remote traumatic brain injury: an exploratory study

2014· article· en· W2043218432 on OpenAlexafffund
Lana J. Ozen, Myra A. Fernandes, Amanda J. Clark, Éric Roy

Bibliographic record

VenueAging Neuropsychology and Cognition · 2014
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTraumatic brain injuryStroop effectNeuropsychologyCognitionCognitive declinePsychologyExecutive functionsTrail Making TestExecutive dysfunctionNeuropsychological assessmentNeuropsychological testHead injuryClinical psychologyMedicinePsychiatryDementiaInternal medicine

Abstract

fetched live from OpenAlex

Separate bodies of literature indicate that a history of a traumatic brain injury (TBI) and natural aging may result in overlapping cognitive profiles, yet little is known about their combined effect. We predicted that a remote TBI would compound normal age-related cognitive decline, particularly affecting executive function. Neuropsychological task performance was compared between a group of older adults who sustained a TBI in their distant past (N = 9) and a group of older adults with no history of head injury (N = 15). While all participants scored in the normal range on the Mini-Mental State Examination, the TBI group scored lower than the non-TBI group. Also, in line with predictions, the TBI group made more errors on measures of executive functioning compared to the non-TBI group (the Trail Making B test and the incongruent condition of the Stroop Test), but performed similarly on all tasks with little executive requirements. Findings from this exploratory study indicate that a past TBI may put older adults at a higher risk for exacerbated age-related cognitive decline compared to older adults with no history of TBI.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.082
GPT teacher head0.397
Teacher spread0.315 · 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 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

Citations13
Published2014
Admission routes2
Has abstractyes

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