Psychometric properties of the motors of COVID-19 vaccination acceptance scale in New Zealand: Insights from confirmatory factor analysis
| dc.contributor.author | Adu, Peter | |
| dc.contributor.author | Popoola, Tosin | |
| dc.contributor.author | Collings, Sunny | |
| dc.contributor.author | Aspin, Clive | |
| dc.contributor.author | Medvedev, Oleg N. | |
| dc.contributor.author | Simpson, Colin R. | |
| dc.date.accessioned | 2024-06-25T01:47:12Z | |
| dc.date.available | 2024-06-25T01:47:12Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | 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 < 0.08. The full scales of the MoVac-COVID19S demonstrated excellent reliability for both the 12-item (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. | |
| dc.identifier.citation | Adu, P., Popoola, T., Collings, S., Aspin, C., Medvedev, O. N., & Simpson, C. R. (2024). Psychometric properties of the motors of COVID-19 vaccination acceptance scale in New Zealand: Insights from confirmatory factor analysis. Current Psychology. https://doi.org/10.1007/s12144-024-05877-x | |
| dc.identifier.doi | 10.1007/s12144-024-05877-x | |
| dc.identifier.eissn | 1936-4733 | |
| dc.identifier.issn | 1046-1310 | |
| dc.identifier.uri | https://hdl.handle.net/10289/16648 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | Springer | |
| dc.relation.isPartOf | Current Psychology | |
| dc.rights | Attribution 4.0 International Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | reliability | |
| dc.subject | validity | |
| dc.subject | COVID-19 | |
| dc.subject | psychometric | |
| dc.subject | validation | |
| dc.subject | vaccine | |
| dc.subject | acceptance | |
| dc.subject | New Zealand | |
| dc.subject.anzsrc2020 | 52 Psychology | |
| dc.subject.anzsrc2020 | 5201 Applied and Developmental Psychology | |
| dc.subject.anzsrc2020 | 52 Psychology | |
| dc.subject.sdg | 3 Good Health and Well Being | |
| dc.title | Psychometric properties of the motors of COVID-19 vaccination acceptance scale in New Zealand: Insights from confirmatory factor analysis | |
| dc.type | Journal Article | |
| dspace.entity.type | Publication |
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