How a year of pandemic and related public health measures impacted youth and young adults and the foundations they build upon: Qualitative interviews in Ontario Canada
Bibliographic record
Abstract
Abstract Introduction During youth and young adult (YYA) years education, employment, relationships with family and friends, and important rituals representing transition to new phases of life are foundations on which personal identity and future well-being are established. These were shaken by the COVID-19 pandemic. We explore how Ontario YYAs and the foundations they build upon (education, employment, relationships, transitional events) were impacted by over a year of pandemic and public health responses to prevent spread. Methods In-depth semi-structured interviews with 19 Ontario YYAs age 16-21 were conducted during April - June 2021. Reflexive thematic analysis aided by MAXQDA software was used to iteratively engage with data to search for patterns and shared meaning. Results Thirteen themes were identified, organized into four meta-themes: impacts on self, impacts on foundations (educational, employment, transitional events/rituals), impacts on relationships, and coping responses. Many, especially those living with loved ones believed to risk a fatal outcome from COVID-19, felt the weight of needing to avoid the virus to protect loved ones. YYAs who were in their last year of secondary school in spring 2020 or 2021 missed important transitional endings, e.g., graduation. Those graduating in 2020 and going on to post-secondary school also missed transitional beginnings, e.g., experiencing in-person on-campus higher education classrooms, living in residence, and meeting new friends. Perceived negative impacts on education quality and professional development were common. Virtual learning models and changes to in-person schooling, hastily introduced and evolving over the next year, did not measure up to traditional learning models. Conclusions All of these impacts took a toll. Respondents routinely volunteered concerns about stress, loneliness, and their mental health. There is need for further research to assess long-term impacts of these experiences, especially among YYAs who had family members at severe risk, and those finishing secondary school in spring of 2020.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.025 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".