Surviving the 2021 heat dome with schizophrenia: A qualitative, interview-based unpacking of risks and vulnerabilities
Bibliographic record
Abstract
This study explores the multifaceted challenges experienced by individuals with schizophrenia during extreme heat, highlighting the interplay between individual factors, social dynamics, and environmental influences. Despite making up only 1% of the Canadian population, individuals diagnosed with schizophrenia comprised 16% ( n = 97) of the deaths during the 2021 heat dome in Western Canada. However, to date, there exists scant qualitative research that explore the direct experiences and the intricacies of intersecting factors faced by individuals with schizophrenia during extreme heat events. This study aims to explore experiences of heat by those living with schizophrenia, including social, behavioural and physiological vulnerability factors that may exacerbate heat-related risks. Between October 2023 and February 2024, semi-structured interviews were conducted with 35 people with a clinical diagnosis of schizophrenia from in-patient and community settings. Participants had experienced the 2021 Heat Dome, or other extreme heat events, in a community setting within British Columbia, Canada. A descriptive form of thematic analysis that prioritizes participants’ experiences was used to identify and explore patterns in the interview transcripts. Participants' narratives underscore how some symptoms of schizophrenia – such as paranoia and delusional thinking – may hinder participants' ability to seek relief from the heat and interpret bodily sensations accurately. Social isolation, compounded by societal stigma, acts as a significant barrier to accessing support networks and public resources for coping with extreme temperatures. Additionally, participants described feeling deterred from seeking medical care or public resources due to past negative experiences and social stigma. Findings illustrate various factors that contribute to the disproportionate impact of extreme heat on individuals diagnosed with schizophrenia, encapsulating both schizophrenia-specific biomedical factors as well as social vulnerability associated with their diagnosis. These findings can inform the development of a multidimensional approach that transcends individual responsibility and addresses the systemic and structural determinants of health. • Heat vulnerability in people living with schizophrenia is influenced by complex social, environmental, and biomedical factors. • Symptoms like delusions and cognitive deficits impair heat awareness and support access. • Substance use, poor quality and/or insecure housing exacerbate heat-related risks for individuals with schizophrenia. • Balancing independence with adequate public resources poses challenges in supporting this population. • Future research should focus on the impacts of medication and substance use on heat-health risks, as well as geographical and cultural influences.
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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".