First Nations parents’ experiences of COVID-19 and associations with symptoms of complex post-traumatic stress disorder
Bibliographic record
Abstract
To examine associations between First Nations parents’ experiences during the COVID-19 pandemic and symptoms of complex post-traumatic stress disorder (C-PTSD). First Nations parents ( n = 110) completed a 90-minute telephone interview between October 2021 and July 2022. Parents self-reported their PTSD or C-PTSD symptoms using the International Trauma Questionnaire (categorised as no/low vs. high levels), COVID-19 events (e.g. testing, diagnosis, isolation) and perceived socioemotional changes in life situation (e.g. quality of relationships) compared with before the pandemic. Logistic regression analysed associations between C/PTSD symptoms (outcome) and demographic factors, COVID-19 events, perceived socioemotional changes since COVID-19 (exposures). More than a quarter (27%) of parents reported high levels of C-PTSD/PTSD symptoms. Most (90%) reported at least one COVID-19 event. Parents who had experienced worsening racism and inequality since the pandemic (OR 0.29, 95% CI 0.11–0.79) or held a Health Care Card (OR 0.27, 95% CI 0.10–0.74) were significantly less likely to report no/low levels of C-PTSD/PTSD symptoms. Financial stress, racism and inequality were associated with increased trauma symptoms, highlighting the importance of implementing trauma-informed public health emergency responses during a pandemic. Those who had fewer disruptions to cultural practices were more likely to be resilient to the stressors of the pandemic, reinforcing the need for a culturally-responsive, trauma-informed public health emergency framework for First Nations communities. Emergency responses that address these factors while optimising safe opportunities to maintain cultural obligations and social connection are essential. • Minimising financial stress, racism and inequality were associated with reduced levels of trauma symptoms, highlighting the importance of implementing trauma-informed public health emergency responses during a pandemic. • Those who had fewer disruptions to cultural practices were more likely to be resilient to the stressors of the pandemic, reinforcing the need for a culturally-responsive, trauma-informed public health emergency framework for First Nations communities. • Emergency responses that address these factors while optimising safe opportunities to maintain cultural obligations and social connection are essential. • This study supports the implementation of a proposed culturally-responsive, trauma-informed public health emergency framework for First Nations communities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.027 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".