The THINC-it Tool for Cognitive Assessment and Measurement in Major Depressive Disorder: Sensitivity to Change
Bibliographic record
Abstract
BACKGROUND: Herein, we sought to determine the sensitivity to change in cognitive function, as measured by the THINC-it tool, in a sample of adults with major depressive disorder (MDD) receiving standardized antidepressant therapy. METHODS: , Montgomery Åsberg Depression Rating Scale (MADRS) total score ≥ 20] were treated with open-label vortioxetine (10-20 mg/day, flexibly-dosed) for 8 weeks. The previously validated THINC-it tool was the primary dependent measure. The THINC-it tool was validated against the paper and pencil version of the Digit Symbol Substitution Test (DSST) and the Trails Making Test B (TMTB). RESULTS: , symbol check; SC) exhibited significant improvement at Weeks 2 and 8 in latency (p = 0.032), SC accuracy (p = 0.046), and objective z-score (p = 0.001) independent of depressive symptoms. A linear regression analysis determined that the THINC-it tool measures of processing speed, as well as executive function were significantly associated with changes observed on the pencil and paper version the Digit Symbol Substitution Test (DSST) (p = 0.002) and in Trails Making Test B (TMTB) (p = 0.003), respectively. CONCLUSION: The THINC-it tool demonstrates sensitivity to change in adults with MDD and is highly correlated with improvements on pencil and paper versions of DSST and TMTB. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier NCT03053362.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".