The nature of anhedonia and avolition in patients with first-episode schizophrenia
Bibliographic record
Abstract
BACKGROUND: Patients with schizophrenia have intact ability to experience emotion, but empirical evidence suggests that they fail to translate emotional salience into effortful behaviour. Previous research in patients with chronic schizophrenia suggests that working memory is important in integrating emotion and behaviour. This study aimed to examine avolition and anhedonia in patients with first-episode schizophrenia and clarify the role of working memory in emotion-behaviour coupling. METHOD: We recruited 72 participants with first-episode schizophrenia and 61 healthy controls, and used a validated emotion-inducing behavioural paradigm to measure participants' affective experiences and how experienced emotion coupled with behaviour. Participants were given the opportunity to expend effort to increase or decrease their exposure to emotion-inducing photographs. Participants with schizophrenia having poor working memory were compared with those with intact working memory in their liking and emotion-behaviour coupling. RESULTS: Patients with first-episode schizophrenia experienced intact 'in-the-moment' emotion, but their emotion was less predictive of the effort expended, compared with controls. The emotion-behaviour coupling was significantly weaker in patients with schizophrenia with poor working memory than in those with intact working memory. However, compared with controls, patients with intact working also showed substantial emotion-behaviour decoupling. CONCLUSIONS: Our findings provide strong evidence for emotion-behaviour decoupling in first-episode schizophrenia. Although working memory deficits contribute to defective translation of liking into effortful behaviour, schizophrenia alone affects emotion-behaviour coupling.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".