Negative Symptoms and Avoidance of Social Interaction: A Study of Non-Verbal Behaviour
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
BACKGROUND: Non-verbal behaviour is fundamental to social interaction. Patients with schizophrenia display an expressivity deficit of non-verbal behaviour, exhibiting behaviour that differs from both healthy subjects and patients with different psychiatric diagnoses. The present study aimed to explore the association between non-verbal behaviour and symptom domains, overcoming methodological shortcomings of previous studies. SAMPLING AND METHODS: Standardised interviews with 63 outpatients diagnosed with schizophrenia were videotaped. Symptoms were assessed using the Clinical Assessment Interview for Negative Symptoms (CAINS), the Positive and Negative Syndrome Scale (PANSS) and the Calgary Depression Scale. Independent raters later analysed the videos for non-verbal behaviour, using a modified version of the Ethological Coding System for Interviews (ECSI). RESULTS: Patients with a higher level of negative symptoms displayed significantly fewer prosocial (e.g., nodding and smiling), gesture, and displacement behaviours (e.g., fumbling), but significantly more flight behaviours (e.g., looking away, freezing). No gender differences were found, and these associations held true when adjusted for antipsychotic medication dosage. CONCLUSIONS: Negative symptoms are associated with both a lower level of actively engaging non-verbal behaviour and an increased active avoidance of social contact. Future research should aim to identify the mechanisms behind flight behaviour, with implications for the development of treatments to improve social functioning.
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 | 0.000 | 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 it