A Novel Landscape for Understanding Physical and Mental Health: Body Mapping Research with Youth Experiencing Psychosis
Bibliographic record
Abstract
Estimates indicate the lifespan of individuals with psychotic illness is reduced by approximately 15-20 years. Consequently there is a need to address the physical health of those who live with a mental illness, like psychosis. The Bondi Centre provides an integrated model of care to young people with a first episode of psychosis. The Keeping the Body In Mind program focuses on prevention and early intervention of physical health issues and is offered alongside treatment for mental health and social issues as part of routine care. We used body mapping, an arts-based research method, to explore the complexity of this physical health intervention. Our aim was to develop an in-depth understanding of experiences of young clients of the early intervention centre, with a particular focus on the embodied relationship between physical and mental health. Six young people engaged in creating life-sized body maps depicting their experience of the physical intervention program over four 3-hour sessions, followed by an in-depth interview. Analysis of our body maps drew on thematic analysis and narrative inquiry. The narrative trope was one of recovery, highlighting the importance of the link between body and mind, individual and community, and the balance between light and darkness. There was an emphasis on developing feelings of connectedness (to self and others), hope and optimism for the future, a sense of having an identity, and a sense of meaning and empowerment. Recovery was conceptualised as an ongoing process rather than an end product or fixed state. Involvement in the body mapping process was consistently identified as therapeutic, offering an opportunity for reflection on the journey to recovery with a focus on past, present and imagined storylines of the future.
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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 | 0.017 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| 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".