Disease Influenced Vaccine Acceptance Scale-Six (DIVAS-6)

Abstract

The Disease Influenced Vaccine Acceptance Scale-Six (DIVAS-6), developed by Grech et al. in 2023, is a concise, six-item psychometric instrument designed to quantify specific disease-related attitudes and concerns that contribute to vaccine hesitancy, particularly in the context of COVID-19. The scale fills a critical gap by focusing on hesitancy factors directly tied to a patient’s existing disease status or ongoing treatment regimens.

The development process involved a panel of specialist clinician-researchers and patient representatives who created the items based on an extensive literature review. The DIVAS-6 was subsequently administered electronically to adults in Australia who had been diagnosed with severe and/or chronic illnesses, such as cancer, diabetes, and multiple sclerosis (MS). Psychometric validation confirmed a robust two-factor structure through Exploratory Factor Analysis (EFA) and Exploratory Structural Equation Modeling (ESEM). The study provided detailed reports on the scale’s reliability, validity, and measurement invariance across different patient groups.

Keywords

COVID-19 Vaccine Hesitancy, Disease Influence, Chronic Illness, COVID-19 Vaccination, COVID-19 Vaccine Attitudes, Disease Complacency, Treatment-Related Hesitancy, Vaccine Acceptance, Vaccine Effect on Disease Progression, Vaccine Interaction with Treatment, Vaccine Vulnerability

Authors

Grech, Lisa, Loe, Bao Sheng, Day, Daphne, Freeman, Daniel, Kwok, Alastair, Nguyen, Mike, Bain, Nathan, Segelov, Eva

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Purpose

The primary purpose of the DIVAS-6 is to provide researchers and clinicians with a specialized tool to evaluate attitudes and concerns related to COVID-19 vaccination among medically vulnerable populations. It specifically targets two distinct dimensions of disease-influenced hesitancy.

These dimensions include “disease complacency,” which addresses concerns regarding potential complications of SARS-CoV-2 infection due to an underlying disease, and “vaccine vulnerability,” which measures the perceived negative impact of the vaccination itself on disease progression or ongoing medical treatment.

Construct

The DIVAS-6 measures disease-influenced vaccine attitudes structured around two independent psychological constructs, as confirmed by factor analysis:

• Disease Complacency: This factor captures the perception of risk associated with the underlying disease and the importance of vaccination in mitigating that risk. Items in this subscale often reflect the patient’s concern about infection severity given their chronic condition.

• Vaccine Vulnerability: This factor captures the patient’s concerns regarding the vaccine’s interaction with their existing health status or therapeutic regimen. This includes worries about vaccine efficacy (how well it will work) and safety (how it might affect their disease or treatment).

Validity

The validation study provided evidence for both convergent validity and acceptable discriminative ability of the DIVAS-6.

Convergent/Concurrent Validity: Both identified factors within the DIVAS-6 demonstrated significant correlations with scores derived from two established COVID-19 vaccine scales. This finding confirms that the DIVAS-6 measures constructs conceptually aligned with general vaccine hesitancy and associated attitudes, establishing strong convergent validity.

Discriminative Ability: The total summary score of the DIVAS-6 showed an acceptable capacity to distinguish between vaccinated and unvaccinated individuals across various chronic disease groups. For the overall sample, the scale exhibited good-to-excellent discriminative ability. Specific cutoff scores were identified for classification: a cutoff of ≥ 13 yielded high sensitivity (0.90) for classifying vaccinated participants (though with low specificity, 0.43). Conversely, increasing the cutoff score to ≥ 18 resulted in reduced sensitivity (0.45) but significantly increased specificity (0.90) for correctly classifying unvaccinated individuals.

Reliability

The DIVAS-6 demonstrated strong internal consistency across its two components, suggesting that the items within each factor reliably measure the intended underlying construct.

Internal Consistency: The two factors comprising the DIVAS-6 achieved high internal consistency scores, with Cronbach’s alpha values reported at 0.73 and 0.85, respectively. These values meet or exceed standard thresholds for psychometric reliability in psychological inventories.

Factor Analysis

The structural integrity of the DIVAS-6 was rigorously tested using advanced statistical modeling techniques, confirming a two-factor model that effectively accounts for the variance in disease-influenced vaccine attitudes.

Exploratory Factor Analysis (EFA): Parallel analysis indicated that a two-factor solution was optimal. These factors were extracted and subjected to oblique rotation. Collectively, the two factors explained a substantial proportion of the variance in the data, accounting for over 58.0% of the total variance. The correlation between the two factors was found to be minimal (r = -0.10), suggesting that while related, they represent relatively distinct constructs.

Structural Equation Modeling (SEM) & Confirmatory Factor Analysis (CFA): The final model was refined using Exploratory Structural Equation Modeling (ESEM). The ESEM model demonstrated an excellent fit to the data (χ2 = 21.67, df = 4, p < 0.0002; CFI = 0.995; TLI = 0.98; RMSEA = 0.042; SRMR = 0.009). In contrast, the traditional Confirmatory Factor Analysis (CFA) model failed to achieve a satisfactory model fit. Comparative analysis using a chi-square difference test showed a significant difference favoring the ESEM model (△χ2 = 438.13, df = 4, p = <0.0001). Further supporting its superiority, the ESEM model exhibited lower AIC and BIC values. Importantly, measurement invariance analysis confirmed that the two factors maintain psychometric equivalence when applied across different groups of patients with varying chronic conditions.

Instrument

Test Type: Original Inventory/Questionnaire

Format: The DIVAS-6 utilizes a 5-point Likert scale for responses, ranging from “strongly agree,” “somewhat agree,” “neither disagree nor agree,” “somewhat disagree,” to “strongly disagree.” A crucial “don’t know” option is also provided to accommodate respondents who may be uncertain about the complex medical interactions described. The standard administration method is electronic.

Language Available: English

Population Group: Human (Male, Female, and individuals with Non-Binary/Other gender identities).

Age Group: Adulthood (18 years and older), including Young Adulthood (18-29 years), Thirties (30-39 years), Middle Age (40-64 years), and Aged (65 years and older).

Population Details: The scale was validated on patients specifically diagnosed with chronic illnesses, including cancer, diabetes, and multiple sclerosis (MS), residing in Australia.

Test Methodology: The psychometric development involved Test Validity (including Concurrent Validity, Convergent Validity, and Discriminant Validity), Test Reliability (including Internal Consistency), Factor Analysis (including Confirmatory Factor Analysis, Exploratory Factor Analysis, and Structural Equation Modeling), Test Sensitivity, and Test Specificity.

Keywords

Treatment-Related Hesitancy, Disease Complacency, Vaccine Vulnerability, Psychometric properties, Factor Structure, COVID-19 Attitudes, Multiple Sclerosis, Cancer, Diabetes

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Authors

Author ORCID Identifier:

• Grech, Lisa: http://orcid.org/0000-0003-0914-8573

• Freeman, Daniel: http://orcid.org/0000-0002-2541-2197

• Kwok, Alastair: http://orcid.org/0000-0002-8064-867X

• Nguyen, Mike: http://orcid.org/0000-0003-3044-1707

• Segelov, Eva: http://orcid.org/0000-0002-4410-6144

Affiliation Email addresses:

• Grech, Lisa: Department of Medicine, School of Clinical Sciences Monash University. Email: [email protected]

• Loe, Bao Sheng: Psychometrics Centre, University of Cambridge. No data is Available

• Day, Daphne: Department of Medicine, School of Clinical Sciences Monash University. No data is Available

• Freeman, Daniel: Department of Psychiatry, University of Oxford. No data is Available

• Kwok, Alastair: Department of Oncology, Monash Health. No data is Available

• Nguyen, Mike: Department of Medicine, School of Clinical Sciences Monash University. No data is Available

• Bain, Nathan: Department of Oncology, Monash Health. No data is Available

• Segelov, Eva: Department of Medicine, School of Clinical Sciences Monash University. No data is Available

Correspondence Address:

Grech, Lisa: Monash University, Department of Medicine, 246 Clayton Road, Melbourne, Victoria, Australia, 3168, [email protected]

Permissions & Fee and Test Year

Permissions: Contact Publisher

Fee: No

Commercial: No

Test Year: 2023

Reference’s

Grech, L., Loe, B. S., Day, D., Freeman, D., Kwok, A., Nguyen, M., Bain, N., & Segelov, E. (2023). The Disease Influenced Vaccine Acceptance Scale-Six (DIVAS-6): Validation of a measure to assess disease-related COVID-19 vaccine attitudes and concerns. Behavioral Medicine, 49(4), 402–411. https://doi.org/10.1080/08964289.2022.2082358

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Items of the Disease Influenced Vaccine Acceptance Scale-Six (DIVAS-6)

IMPORTANT: The following scale items must be preserved in their original language and must not be changed in any way.

The DIVAS-6 consists of 6 items. The specific content of the items is available in the source reference: 2022-74553-001, Table 2, Page 406.

Factors and Subscales:

• Disease complacency

• Vaccine vulnerability

This instrument is comprised of two subscales: Disease Complacency and Vaccine Vulnerability.

Note. Responses are made on a 5-point Likert scale with an additional “don’t know” option (“strongly agree,” “somewhat agree,” “neither disagree nor agree,” “some what disagree,” “strongly disagree”).