Psychometric validation of the COVID-19 vaccine hesitancy scale for primary and booster doses among university students: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Vaccine hesitancy (VH) continues to impede COVID-19 vaccine coverage. Booster dose uptake lags behind primary dose uptake, especially among younger adults. Unlike most studies that focus on initial stages of VH, the aim of this study was to validate the COVID-19 Vaccine Hesitancy Scale (CVHS) for both primary and booster doses among University of Waterloo (UW) students. METHODS: An online survey was conducted among UW students in Ontario, Canada, between March and May 2024. The CVHS items were adapted for primary and booster doses. Exploratory (EFA) and confirmatory factor analyses (CFA) assessed the factor structure and model fit. Reliability was evaluated using Cronbach's alpha and composite reliability (CR). Convergent and discriminant validity were assessed through average variance extracted (AVE). Significant differences between primary and booster dose hesitancy were determined via 95 % Confidence Interval. RESULTS: A total of 4453 students participated. Respondents were predominantly female (57.2 %), aged 18-22 years (84.0 %), and undergraduates (94.8 %). EFA and CFA confirmed a three-factor structure for both primary and booster dose scales. Both scales had high reliability (Cronbach's alpha >0.60, CR >0.7). CFA results indicated a good model fit (Comparative Fit Index = 0.94; Root Mean Square Error of Approximation = 0.07), and demonstrated adequate convergent, discriminant, and criterion validity. Known-group validity was supported by significant differences in VH scores across gender and academic level, with men and undergraduate students reporting higher hesitancy than women and graduate students (p < 0.001). VH was higher for booster doses (33.4 %) than primary doses (19.3 %) with more students delaying (32.1 %) or refusing boosters (29.3 %) than delaying (11.5 %) or refusing (6.2 %) primary doses. CONCLUSION: Our adapted scales performed well psychometrically to measure VH across different COVID-19 vaccine phases. These scales can help in identifying key barriers of VH to understand shifting trajectories over time, thereby informing targeted interventions to promote vaccination uptake among younger adults.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".