Phenomenology and Subjective Experience of Catatonia: Clinical Cases
Bibliographic record
Abstract
This chapter illustrates different psychopathological presentations, highlights key aspects crucial for catatonia management, explores the subjective experiences of catatonia patients, and proposes novel approaches to address various symptoms while deriving therapeutic options. We present five catatonia patients, four of them were treated at the Central Institute of Mental Health (CIMH) in Mannheim, Germany, by Dr. Hirjak, one patient was treated by Dr. Northoff at the Department of Psychiatry in Magdeburg, Germany. This chapter focuses on their catatonic and other psychopathological symptoms, subjective experiences, treatment outcomes, and follow-up assessments in the outpatient departments of CIMH and Magdeburg. The patient case examples are structured as follows: (1) introduction and background on the significance and relevance of the case, (2) case presentation, (3) treatment, (4) follow-up and outcomes, and (5) discussion. Patient examples, including statements from a first-person perspective, will be provided, and new clinical rating scales on the subjective experience of catatonia patients will be discussed.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".