Learning with psychosis: A narrative inquiry exploring the lived experiences of secondary students living with early psychosis
Bibliographic record
Abstract
Those who experience psychosis struggle to find inclusion within educational institutions (Goulding, Chien, & Compton, 2010; Laurence, Rosseau, Foriter, & Mottard, 2016; Morgan et al., 2012) despite a growing recognition of the need to create an equitable environment for students with mental health difficulties. This research explores the complexities of the experiences of students with psychosis in the secondary school environment with a view to improving support for these individuals. The research focused on each student’s unique experiences by using an empowerment and narrative inquiry design. I recruited a small sample of three primary participants from an early psychosis intervention program located in an Ontario community. Data were collected through in-depth semi-structured one-on-one interviews and analyzed with narrative processes. My findings are presented through retelling the story of each participant’s high school experiences, and highlighting their perceptions of inclusion and support. Key findings in Mary, Angel, and Isaac’s stories describe: (a) typical high school experiences, external challenges, academic challenges, and social challenges; (b) sense of belonging, community participation, social inclusion at school, and the challenges that impacted how participants were included at school; and (c) feelings of support, environmental supports, supportive people, supportive actions, and the challenges that impacted support at school. Reading the stories of these students will provide teachers, administrators and policy makers with insight into the unique experiences of students who live with early psychosis. My aim is that this insight will contribute to a more inclusive discussion about mental health in education, informed by the voices of students who have experienced psychosis.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".