The Value of Patient-administered Depression Rating Scale in Detecting Cognitive Deficits in Depressed Patients
Bibliographic record
Abstract
BACKGROUND: The aims of this study was to clarify how accurate the depressed patients perceive their cognitive symptoms, and verify the appropriateness of the depressive rating scales in evaluating cognitive deficits in major depressive disorder (MDD) patients. METHODS: The subjects consisted of 19 well-characterized medication-free patients with MDD and 19 healthy volunteers. The clinical and neuropsychological assessments, including Hamilton Rating Scale for Depression (HAM-D), Taiwanese Depression Questionnaire (TDQ), Finger Tapping Test, Wechsler Memory Scale-Revised, Stroop Color-Word Test, and Continuous Performance Test, were administered at the time of recruitment and repeated six months after treatment. RESULTS: Depressed patients exhibited significant impairment in several neurocognitive domains. Neurocognitive impairment was correlated with both the affective and somatic factors, but not with the cognitive factors of TDQ. The similar results were shown after 6-month treatment. CONCLUSIONS: Our results suggest that the MDD patients do not perceive their cognitive dysfunction correctly. The depression rating scales, especially the patient-administered scale, need to be validated for measuring neurocognitive deficits of MDD patients in the future, if cognitive component is suspected as one of the major domains of self-rating scale. KEYWORDS: Major depressive disorder; Cognitive deficits; Depression rating scale.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".