Multi-method findings on COVID-19 vaccine acceptability among urban refugee adolescents and youth in Kampala, Uganda
Bibliographic record
Abstract
Scant studies have explored COVID-19 vaccine acceptability among refugees. However, contexts of forced migration may elevate COVID-19 vulnerabilities, and suboptimal refugee immunisation rates are reported for other vaccine-preventable diseases. We conducted a multi-methods study to describe COVID-19 vaccine acceptability among urban refugee youth in Kampala, Uganda. This study uses cross-sectional survey data from a cohort study with refugees aged 16–24 in Kampala to examine socio-demographic factors associated with vaccine acceptability. A purposively sampled cohort subset (n = 24) participated in semi-structured in-depth individual interviews, as did key informants (n = 6), to explore COVID-19 vaccine acceptance. Among 326 survey participants (mean age: 19.9; standard deviation 2.4; 50.0% cisgender women), vaccine acceptance was low (18.1% reported they were very likely to accept an effective COVID-19 vaccine). In multivariable models, vaccine acceptance likelihood was significantly associated with age and country of origin. Qualitative findings highlighted COVID-19 vaccine acceptability barriers and facilitators spanning social-ecological levels, including fear of side effects and mistrust (individual level), misinformed healthcare, community and family attitudes (community level), tailored COVID-19 services for refugees (organisational and practice setting), and political support for vaccines (policy environment). These data signal the urgent need to address social-ecological factors shaping COVID-19 vaccine acceptability among Kampala’s young urban refugees.Trial registration: ClinicalTrials.gov identifier: NCT04631367.
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 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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".