Relevance of Autonomic Arousal in the Stress Response in Psychopathology
Bibliographic record
Abstract
The principal goal of this study is to describe the relevance of typical autonomic patterns of response in accordance to a number of psychopathological syndromes for an accurate multi-dimensional assessment.A sample of 89 subjects was subdivided in five pathological groups in accordance with the clinical diagnosis following the diagnostic criteria of DSM V [1]: Generalized Anxiety Disorder (GAD), Panic Attack Disorders (PAD), Major Depressive Episodes (MDE), Obsessive Compulsive Disorders (OCD), Anorexia Nervosa (AN) and a Healthy control group. Obtained data were compared in regard to each physiological parameters by using the mean value of the last minute of the registration at rest, and two activation indexes: “stress response” and “recovery after stress”.Furthermore, for each of the physiological parameters (EMG, SCL/SCR, PT and HR), and diagnostic group, mean values in the three different phases (last minute of rest, first minute of stress, last minute of recovery) were compared to evaluate the four physiological parameters trends.In GAD and PAD patients, the obtained Conductance Response mean values are much higher than MDE and OCD.Furthermore, the HR response is also higher in GAD than in the other three groups. So, OCD and MDE patients seem to be characterized by a flat profile in all the parameters.We confirmed that a condition of autonomic hyper activation is typically connected to a high level of tension and anxiety; vice versa, a low level of autonomic activation and the impossibility to react to the stimuli is typically connected to MDE, OCD and AN.Obtained data suggest that there might be a new tool for differential diagnosis in psychopathology, represented by specific and typical pattern in autonomic response.
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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".