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Record W2037371730 · doi:10.1080/13854040701290062

Comparability of Neuropsychological Test Profiles in Patients with Chronic Substance Abuse and Mild Traumatic Brain Injury

2008· article· en· W2037371730 on OpenAlexaff
Rael T. Lange, Grant L. Iverson, Michael D. Franzen

Bibliographic record

VenueThe Clinical Neuropsychologist · 2008
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of British ColumbiaRiverview Hospital
Fundersnot available
KeywordsNeuropsychologyTraumatic brain injuryCognitionClinical psychologySubstance abusePsychiatryPsychologyNeuropsychological testNeuropsychological assessmentMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to compare 104 patients with acute uncomplicated mild traumatic brain injury (MTBI) to a sample of 104 patients from an inpatient substance abuse program to determine whether these patients could be differentiated by their pattern of relative cognitive strengths and weaknesses. Patients were matched on age, education, and gender. Eight cognitive measures were used that included tests of attention, memory, and processing speed. There were no statistically significant differences between the two groups on any of the cognitive measures. Using a two-step cluster analysis procedure (i.e., hierarchical and k-means analyses), seven common profiles were identified. There was no significant difference in the proportions of patients from the MTBI or substance abuse group in each of the seven profiles. These results show that patients with uncomplicated MTBIs could not be reliably differentiated from patients with substance abuse problems on these cognitive measures. This is of particular concern for clinicians evaluating the neuropsychological effects of MTBI in individuals with a comorbid history of substance abuse.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
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 head0.219
GPT teacher head0.433
Teacher spread0.214 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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