Psychometric Properties of the Korean Version of THINC-integrated Tool (THINC-it-K): A Tool for Screening Assessment of Cognitive Function in Patients with Major Depressive Disorder
Bibliographic record
Abstract
Objective: The present study was performed to investigate the validity and reliability of the Korean version of the THINC-it tool (THINC-it-K) in adult patients with major depressive disorder (MDD).Methods: Subjects aged 19-65 years with recurrent MDD experiencing moderate to severe major depressive episode (n = 44) were evaluated and compared to age and sex matched healthy controls (n = 44).Subjects completed the THINC-it-K which includes variants of the Identification Task (IDN) using Choice Reaction Time, One-Back Test, Digit Symbol Substitution Test, Trail Making Test-Part B, and the Perceived Deficits Questionnaire for Depression-5-item (PDQ-5-D).Results: A total of 75.0% of patients with MDD exhibited cognitive performance 1 standard deviation or below.The differences in Spotter (p = 0.001), Codebreaker (p = 0.001), PDQ-5-D (p 0.001) and objective THINC-it-K composite score (p = 0.002) were significant between the two groups.Concurrent validity of the THINC-it-K based on a calculated composite score was good (r = 0.856, p 0.001), and ranges for each component tests were from 0.076 (IDN) to 0.928 (PDQ-5-D).Conclusion: The THINC-it-K exhibits good reliability and validity in adults with MDD.It could be a useful tool for the measurement of cognitive deficits in persons with MDD and should be implemented in clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".