Pain and major depressive disorder: Associations with cognitive impairment as measured by the THINC-integrated tool (THINC-it)
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.
Bibliographic record
Abstract
OBJECTIVES: To examine the role of pain on cognitive function in adults with major depressive disorder (MDD). METHODS: =100) for comparison. Cognitive function was assessed using the recently validated THINC-integrated tool (THINC-it), which comprises variants of the choice reaction time (i.e., THINC-it: Spotter), One-Back (i.e., THINC-it: Symbol Check), Digit Symbol Substitution Test (i.e., THINC-it: Codebreaker), Trail Making Test - Part B (i.e., THINC-it: Trails), as well as the Perceived Deficits Questionnaire for Depression - 5-item (i.e., THINC-it: PDQ-5-D). A global index of objective cognitive function was computed using objective measures from the THINC-it, while self-rated cognitive deficits were measured using the PDQ-5-D. Pain was measured using a Visual Analogue Scale (VAS). Regression analyses evaluated the role of pain in predicting objective and subjective cognitive function. RESULTS: A significant between-group differences on the VAS was observed (p<0.001), with individuals with MDD reporting higher pain severity as evidenced by higher scores on the VAS than HC. Significant interaction effects were observed between self -rated cognitive deficits and pain ratings (p<0.001) on objective cognitive performance (after adjusting for MADRS total score), suggesting that pain moderates the association between self-rated and objective cognitive function. CONCLUSIONS: Results indicated that pain is associated with increased self-rated and objective cognitive deficits in adults with MDD. IMPLICATIONS: The study herein provides preliminary evidence demonstrating that adults with MDD reporting pain symptomatology and poorer subjective cognitive function is predictive of poorer objective cognitive performance. THINC-it is capable of detecting cognitive dysfunction amongst adults with MDD and pain.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it