Healthcare Provider Narratives of the Impacts of the COVID-19 Pandemic on Pregnant and Parenting Youth in Canada: A Qualitative Study
Bibliographic record
Abstract
The COVID-19 pandemic led to significant challenges for healthcare providers working with pregnant and parenting youth. However, the impacts of the pandemic on this population and healthcare services from the perspective of healthcare providers are not well documented in Canada. We examined the narratives and experiences of healthcare providers regarding these impacts and explored the challenges to service provision. Using a qualitative interpretative description (ID) approach, we recruited 25 health and service providers from Alberta, Ontario, and British Columbia for individual qualitative interviews. Our analysis resulted in three themes: complexities of health service provision during COVID-19, healthcare providers' accounts of impacts on pregnant and parenting youth, and leveraging challenges into opportunities for service provision. Participants described the influence of pandemic policies and distancing measures on accessibility of health services, availability of healthcare resources and personnel, and well-being of their clients. They also reported increased mental health issues, isolation, and exacerbation of inequities within this population. Providers highlighted the role of telemedicine in ensuring some degree of continuity of care. Additionally, they commented on service adaptations to address the evolving needs of their clients. Our findings underline the need for a resilient and adaptable healthcare system that can better support the needs of vulnerable populations during crises.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".