Characteristics Associated with Fear of COVID-19 among Syrian Refugee Parents in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: The aim was to assess the prevalence and factors associated with fear of COVID-19 among Syrian refugee parents in Ontario, Canada. Methods: A sample of 540 Syrian refugee parents who resettled in Ontario were interviewed between March 2021, and March 2022. The level of fear was measured using the Fear of COVID-19 scale. Multiple linear regression analysis was performed to assess the relationships between socio-demographic, migration, and health-related factors and fear of COVID-19. Results: The mean (SD) score for the Fear of COVID-19 scale was 15.6 (6.02), and 15.4% of the participants were categorized as having high levels of Fear of COVID-19. Results of the multiple linear regression analysis showed that low self-rated English/French language ability was significantly associated with increased fear of COVID-19 (Adjβ=0.65, p=0.047). When compared to participants who do not need an interpreter, those who needed an interpreter, and were always provided with one, were at reduced fear of COVID-19 (Adjβ=-1.56, p=0.061). In addition, findings indicated that low self-perceived socioeconomic status, more years spent in Canada, living in a refugee camp, and poor self-rated mental health contributed significantly to elevated levels of fear of COVID-19. Discussion: Targeted intervention and prevention strategies for reducing the fear of COVID-19 should be considered for the Syrian refugee population in Canada. Language ability is one of the factors related to increased fear of COVID-19, thus, providing information and interventions in different languages is essential for this population.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it