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Record W2096001846 · doi:10.1037/0894-4105.17.3.410

Cognitive complaints, depression, medical symptoms, and their association with neuropsychological functioning in HIV infection: A structural equation model analysis.

2003· article· en· W2096001846 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuropsychology · 2003
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of WindsorSt. Michael's Hospital
Fundersnot available
KeywordsNeuropsychologyPsychologyStructural equation modelingMoodNeuropsychological testCognitionClinical psychologyPsychomotor learningCognitive skillVerbal fluency testPsychiatryDepression (economics)Neuropsychological assessment

Abstract

fetched live from OpenAlex

The main objective of this study was to use structural equation modeling (SEM) to clarify the relationship between subjective cognitive complaints and neuropsychological functioning in 160 adults with HIV infection. Participants completed questionnaires assessing cognitive complaints, symptoms of depression, and HIV-related medical symptoms. Neuropsychological tests included measures of attention, verbal fluency, psychomotor skills, learning, memory, and executive skills. SEM was used to test models of the relationships among cognitive complaints, mood, and medical symptoms with neuropsychological functioning. The model indicated that although depressed mood (beta = 0.32, p < .01) and medical symptoms (beta = 0.31, p < .01) influenced cognitive complaints, cognitive complaints were independently associated with poorer neuropsychological performance (beta = 0.39, p < .01). Mood and medical symptoms were significantly correlated but were not significantly associated with neuropsychological skills.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.294
Teacher spread0.273 · 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