Embodied Self and Metaphor Comprehension Predict Comprehension of Boundary Concept in Patients with Schizophrenia
Bibliographic record
Abstract
Background. The embodied self refers to the sense of self intertwined with our physical body and its experiences, which is impaired in schizophrenia. Metaphors, which are cognitive tools that help to comprehend abstract ideas, are also impaired in patients with schizophrenia. Conceptual Metaphor Theory (CMT) links embodied experiences and metaphors to boundaries, indicating that these disruptions may lead to difficulties in understanding boundaries in schizophrenia.Aims. This study explores the role of embodied self and metaphor comprehension, in predicting boundary concept comprehension in patients with schizophrenia. Method. The current study recruited 85 Persian speaking Male patients who were diagnosed with schizophrenia (mean age = 47.84 years, SD = 7.58). All participants completed the Embodied Sense of Self scale, the Montreal evaluation of communication_ Metaphor subtest, and a researcher-developed questionnaire on comprehension of the boundary concept. Multiple linear regression analyses were applied to assess the associations between the embodied self, metaphor comprehension, and understanding of the boundary concept.Results. The suggested Model predicts 50% of the total variance (P<0.01,R2=0.50). Metaphor comprehension predicts boundary concept understanding (β=0.67, p≤0.01,R2=0.50), while the embodied self (β=-0.13, p=0.1, R2=0.50) does not. Conclusion. Our findings indicate that impairments in metaphor comprehension are significantly associated to the understanding of boundary concepts in schizophrenia, while no such relationship was observed with the embodied self. These results highlight the role of metaphorical cognitions in boundary perception, potentially extending to issues with the self-other boundary and representing relations of self-other boundary disturbances and Metaphorical cognition.
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 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".