An experimental paradigm for triggering a depressive syndrome.
Bibliographic record
Abstract
Research investigating whether depression is an adaptation or a disorder has been hindered by the lack of an experimental paradigm that can test causal relationships. Moreover, studies attempting to induce the syndrome often fail to capture the suite of feelings, thoughts, and behaviors that characterize depression. An experimental paradigm for triggering depressive symptoms can improve our etiological understanding of the syndrome. The present study attempts to induce core symptoms of depression, particularly those related to rumination, in a healthy, nonclinical sample through a controlled social experiment. These symptoms are sad or depressed mood, anhedonia, feelings of worthlessness or guilt, and difficulty concentrating. One hundred and thirty-four undergraduate students were randomly assigned to either an exclusion (E) or control (C) group. Participants in the exclusion group were exposed to a modified Cyberball paradigm, designed to make them feel socially excluded, followed by a dual-interference task to assess whether their exclusion interfered with their working memory. Excluded participants: (a) self-reported a significant increase in sadness and decrease in happiness, but not anxiety or calmness; (b) scored significantly higher in four of five variables related to depressive rumination; and (c) performed significantly worse on a dual-interference task, suggesting an impaired ability to concentrate. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".