Monitoring Adverse Psychosocial Outcomes One and Two Years After the Lac-Mégantic Train Derailment Tragedy (Eastern Townships, Quebec, Canada)
Bibliographic record
Abstract
INTRODUCTION: In July 2013, a train carrying 72 cars of crude oil derailed in the town of Lac-Mégantic (Eastern Townships, Quebec, Canada). This disaster provoked a major conflagration, explosions, 47 deaths, the destruction of 44 buildings, the evacuation of one-third of the local population, and an unparalleled oil spill. Notwithstanding the environmental impact, many citizens of this town and in surrounding areas have suffered and continue to suffer substantial losses as a direct consequence of this catastrophe. PROBLEM: To tailor public health interventions and to meet the psychosocial needs of the community, the Public Health Department of Eastern Townships has undertaken repeated surveys to monitor health and well-being over time. This study focuses on negative psychosocial outcomes one and two years after the tragedy. METHODS: Two cross-sectional surveys (2014 and 2015) were conducted among large random samples of adults in Lac-Mégantic and surrounding areas (2014: n = 811; 2015: n = 800), and elsewhere in the region (2014: n = 7,926; 2015: n = 800). A wide range of psychosocial outcomes was assessed (ie, daily stress, main source of stress, sense of insecurity, psychological distress, excessive drinking, anxiety or mood disorders, psychosocial services use, anxiolytic drug use, gambling habits, and posttraumatic stress symptoms [PSS]). Exposure to the tragedy was assessed using residential location (ie, six-digit postal code) and intensity of exposure (ie, intense, moderate, or low exposure; from nine items capturing human, material, or subjective losses). Relationships between such exposures and adverse psychosocial outcomes were examined using chi-squares and t-tests. Distribution of outcomes was also examined over time. RESULTS: One year after the disaster, an important proportion of participants reported human, material, and subjective losses (64%, 23%, and 54%, respectively), whereas 17% of people experienced intense exposure. Participants from Lac-Mégantic, particularly those intensely exposed, were much more likely to report psychological distress, depressive episode, anxiety disorders, and anxiolytic drug use, relative to less-exposed ones. In 2015, 67% of the Lac-Mégantic participants (76% of intensely exposed) reported moderate to severe PSS. Surprisingly, the use of psychosocial services in Lac-Mégantic declined by 41% from 2014 to 2015. CONCLUSION: The psychosocial burden in the aftermath of the Lac-Mégantic tragedy is substantial and persistent. Public health organizations responding to large-scaling disasters should monitor long-term psychosocial consequences and advocate for community-based psychosocial support in order to help citizens in their recovery process.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".