Information processing and cognitive organization in unipolar depression: Specificity and comorbidity issues.
Bibliographic record
Abstract
This study investigated information processing and cognitive organization in clinical depression. The specificity of various cognitive mechanisms to depression was also examined. Twenty-six depressed/anxious individuals, 24 pure depressives, 25 never-depressed anxious controls, and 25 nonpsychiatric controls completed a modified Stroop task, the Self-Referent Encoding Task, and two tasks designed to assess cognitive structure. Comorbid depressed/anxious, depressed, and anxious groups performed similarly to one another but differed significantly from nonpsychiatric controls, on the processing and organization of negative content. Specificity to depression was also obtained, as both depressed groups endorsed and recalled less positive information and organized positive self-relevant information with less interconnectedness than anxious individuals and nonpsychiatric controls. These results suggest that depressed individuals have an interconnected negative self-representational system and lack a well-organized positive template of self. These findings are discussed in terms of cognitive models of depression and the tripartite model of depression and anxiety.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".