Polysensoriality and Aesthetics: The Lived Sensory Experiences of Adults with Mental Illness
Bibliographic record
Abstract
Background. Research in neuroscience shows that adults with schizophrenia or related psychotic disorders experience atypical sensory processing (e.g., deficits in sensory gating and mismatch negativity). Despite significant evidence proving these biomarkers are common among adults with serious mental illness, it is unclear how their sensory experiences impact their occupations in daily life (i.e., real-world implications of atypical sensory processing). Purpose. To explore how the lived sensory experiences of adults with psychotic disorders affect their occupations. Method. We used Walking with Video, photo-elicitation, and semi-structured interviews to study how the lived sensory experiences of adults with psychotic disorders ( N = 6) relate to their occupations. Informed by a phenomenological perspective, we analysed data from semistructured interviews, and undertook analyses through iterative rounds of coding to develop themes and two cycles of group reflective practices to identify researcher biases and assumptions. Findings. Analyses revealed the following themes: polysensoriality, embodied aesthetics of everyday life, habits of sensing and sensory anchors, and active sensory beings. Implications. In clinical contexts, occupational therapists should carefully consider the situatedness of sensory experiences while avoiding assumptions that sensory preferences and aversions mechanistically generalize across contexts and occupations.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".