Neuropsychological dysfunction in chronic fatigue syndrome and the relation between objective and subjective findings.
Bibliographic record
Abstract
OBJECTIVE: This study aimed to explore the relationship between self-reported cognitive difficulties, objective neuropsychological test performances, and subjective health complaints in chronic fatigue syndrome (CFS) and to examine the degree of impaired cognitive functions. METHOD: A total of 236 consecutively recruited outpatients, 18-62 years of age, completed the tests. Self-administered questionnaires were used for assessing fatigue, pain, depression, anxiety and subjective cognitive complaints (Everyday Memory Questionnaire [EMQ]). Also, neuropsychological tests, that is, Stroop I-IV, California Verbal Learning Test-Second Edition (CVLT-II) learning and delay, Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) Letter Number (L-N) Sequencing, and the Paced Auditory Serial Addition Task were performed to examine whether these objective measures correlated with subjective complaints and were compared with normative data. RESULTS: < .001). Between 21% and 38% of the patients performed below the 1.5-SD cutoff for clinically significant impairment on the Stroop tests. CONCLUSION: The self-reported cognitive performance was not strongly associated with the objective cognitive performances on any domains in patients with CFS. Patients with higher fatigue, pain, and depression levels reported greater subjective cognitive difficulties, as well as higher pain related to lower objective working memory function. The CFS patients had problems mainly in the domains of psychomotor speed and attention measured by the objective neuropsychological tests. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".