Impact of the COVID-19 pandemic on the sexual and reproductive health of adolescents in Alberta, Canada
Bibliographic record
Abstract
PURPOSE: The COVID-19 pandemic led to major service disruptions in the healthcare sector, especially regarding sexual and reproductive health services. However, the impact of the pandemic on Canadian adolescents is relatively unknown. This study aimed to investigate the impacts of the COVID-19 pandemic and associated public health measures on the sexual and reproductive health (SRH) of adolescents in Alberta, Canada. METHODS: A qualitative study using an interpretive description (ID) approach and community-based participatory research principles was conducted to capture the subjective experience and perceptions of adolescents and service providers. With the collaboration of the Adolescent Advisory Group and community partners, 18 adolescents and 15 service providers were recruited for the study through purposive sampling. Findings from the qualitative interviews were analyzed using thematic analysis. RESULTS: Three major themes emerged from the analysis: (1) COVID-19 SRH experience, (2) barriers to SRH, and (3) adolescent SRH strategies. Our findings highlight numerous barriers and challenges that prevented adolescents from accessing SRH education, products, and services. CONCLUSION: The COVID-19 pandemic had a profound impact on the SRH and the well-being of adolescents. Our study reflects the need for diverse SRH strategies to maintain continued access to SRH resources during disruptive events, such as the pandemic.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".