‘Life became harder with COVID-19’: Impacts of COVID-19 on youth living in eThekwini district, South Africa, a qualitative analysis of responses to an online survey
Bibliographic record
Abstract
Abstract Background In South Africa, pervasive age and gender inequities have been exacerbated by the COVID-19 pandemic and public health response. We aimed to explore the impacts of the COVID-19 pandemic on youth in eThekwini, South Africa. Methods Between December 2021-May 2022 we explored the impacts of the COVID-19 pandemic on youth aged 16–24 residing in eThekwini, South Africa using open-ended responses to an online survey focused on understanding multi-levelled health and social impacts of the pandemic. Inductive coding summarized open-ended responses to the question “Has the COVID-19 pandemic affected you in any other way you want to tell us about?” overall and by gender. Results Of 2,068 respondents, 256 (12.4%, median age = 22, 62.1% women or non-binary) completed the open-ended survey question (11% in isiZulu). Results were organized into three main themes encompassing 1) COVID-19-related overwhelming loss, fear, grief, and exacerbated mental and physical health concerns; 2) COVID-19-related intensified hardships, which contributed to financial, employment, food, educational, and relationship insecurities for individuals and households; and 3) positive impacts of the pandemic response, including the benefits of government policies and silver linings to government restrictions. South African youth experienced significant grief and multiple losses (e.g., death, income, job, and educational) during the COVID-19 pandemic. Conclusions We found that South African youth experienced significant grief and multiple losses (e.g., death, income, job, and educational) during the COVID-19 pandemic. Trauma-aware interventions that provide economic and educational opportunities must be included in post-COVID recovery efforts.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".