Associations between trauma and substance use among healthcare workers and public safety personnel during the SARS-CoV-2 (COVID-19) pandemic: the mediating roles of dissociation and emotion dysregulation
Bibliographic record
Abstract
Background: Given the highly stressful environment surrounding the SARS-CoV-2 pandemic, healthcare workers (HCW) and public safety personnel (PSP) are at an elevated risk for adverse psychological outcomes, including posttraumatic stress disorder (PTSD) and alcohol/substance use problems. As such, the study aimed to identify associations between PTSD severity, related dissociation and emotion dysregulation symptoms, and alcohol/substance use problems among HCWs and PSP.Methods: A subset of data (N = 498; HCWs = 299; PSP = 199) was extracted from a larger study examining psychological variables among Canadian HCWs and PSP during the pandemic. Structural equation modelling assessed associations between PTSD symptoms and alcohol/substance use-related problems with dissociation and emotion dysregulation as mediators.Results: Among HCWs, dissociation fully mediated the relation between PTSD and alcohol-related problems (indirect effect β = .133, p = .03) and emotion dysregulation partially mediated the relation between PTSD and substance-related problems (indirect effect β = .151, p = .046). In PSP, emotion dysregulation fully mediated the relation between PTSD and alcohol-related problems (indirect effects β = .184, p = .005). For substance-related problems among PSP, neither emotion dysregulation nor dissociation (ps >.05) had any effects.Conclusion: To our knowledge, this is the first study examining associations between PTSD severity and alcohol/substance use-related problems via mediating impacts of emotion dysregulation and dissociation among HCWs and PSP during the SARS-CoV-2 pandemic. These findings highlight dissociation and emotion dysregulation as important therapeutic targets for structured interventions aimed at reducing the burden of PTSD and/or SUD among Canadian HCWs or PSP suffering from the adverse mental health impacts of the SARS-CoV-2 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".