Psychometric properties of the motors of Covid-19 vaccination acceptance scale in New Zealand
Insights from confirmatory factor analysis
Bibliographic Data
| ID | 21628949 |
|---|---|
| Authors | Peter Adu (0000-0002-1931-147X, Victoria University of Wellington, corresponding author), Tosin Popoola (0000-0003-2761-7783, University of Newcastle Australia), Sunny Colling (0000-0002-5486-1194, Victoria University of Wellington), Sunny Collings, Clive Aspin (0000-0001-5688-777X, Victoria University of Wellington), Oleg N Medvedev (0000-0002-2167-5002, University of Waikato), Colin R Simpson (0000-0002-5194-8083, Victoria University of Wellington) |
| Year | 2024 |
| Volume | 43 |
| Issue | 32 |
| Pages | 26628-26638 |
| Publication date | 2024-08-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Current Psychology (JOURNAL) |
| Journal identifiers | ISSN: 1046-1310 • E-ISSN: 1936-4733 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s12144-024-05877-x |
| OpenAlex | W4394854581 |
| Language | EN |
| Citations received | 2 |
| References cited | 32 |
High vaccination coverage plays an essential role in curbing epidemics and pandemics, making it important to have a country-specific valid and standardised instruments for assessing vaccination attitudes. This study aimed to assess the psychometric properties of the Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S) in New Zealand. A total of 413 participants completed an online survey in June and July 2022, which included the MoVac-COVID19S questions, demographic factors, and a single-item measure of COVID-19 vaccination willingness. Confirmatory Factor Analysis (CFA) was used to examine the factor structures of the scale. Results indicated that the one-factor structure of the 9-item version best fitted the data compared to the one and four factor structures of the 12-item version, which showed acceptable fit indices after model modifications. All estimated fit indices were acceptable: CFI, GFI, and TLI > 0.95, RMSEA and SRMR α = 0.91; ω = 0.91) and the 9-item ( α = 0.94; ω = 0.95) versions. The bifactor model indicated a strong general factor, explaining 60–90% of the Explained Common Variance (ECV) for most items, surpassing specific factors. The MoVac-COVID19S is a reliable and valid scale to measure COVID-19 vaccination attitudes. The 9-item version appeared as the best choice for a unidimensional assessment. Future vaccination programmes can benefit from an adapted version of the MoVac-COVID19S to assess public attitudes towards new vaccines. Further psychometric assessment, including Rasch analysis, is recommended to strengthen the reliability and validity of the MoVac-COVID19S
Cartography · Confirmatory factor analysis · Explained variation · Geography · Psychometrics · Statistics · Structural equation modeling · Vaccination · Clinical Psychology · COVID-19 and Mental Health · COVID-19 Pandemic Impacts · Mathematics · Medicine · Psychology · Vaccine Coverage and Hesitancy · Virology
Interaction Effects in Multiple Regression
A caveat on using single‐item versus multiple‐item scales
Scoring and Modeling Psychological Measures in the Presence of Multidimensionality
Cognitive Elements of Empowerment
Data quality in online human-subjects research
Best Alternatives to Cronbach's Alpha Reliability in Realistic Conditions
Considerations in determining sample size for pilot studies
Bifactor Models and Rotations
Cross-cultural adaptation of research instruments
Understanding Power and Rules of Thumb for Determining Sample Sizes
Applied Psychometrics
Social Desirability Bias
Cutoff criteria for fit indexes in covariance structure analysis
A Test of Missing Completely at Random for Multivariate Data with Missing Values
| Citations per year | 2 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |