McCormick KM, Sethi S, Haag D, Macedo DM, Hedges J, Quintero A, Smithers L, Roberts R, Zimet G, Jamieson L, Ribeiro Santiago PH. Development and validation of the COVID-19 Impact Scale in Australia.
Curr Med Res Opin 2023;
39:1341-1354. [PMID:
37656161 DOI:
10.1080/03007995.2023.2247323]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/03/2023] [Accepted: 08/09/2023] [Indexed: 09/02/2023]
Abstract
OBJECTIVE
The COVID-19 pandemic significantly impacted and continues to impact the health and well-being of Australian adults. However, there has been no instrument validated to comprehensively measure how the COVID-19 pandemic impacted adults in Australia across several domains (e.g. fear of COVID-19, attitudes towards vaccination, psychosocial impact of lockdowns).The current study conducted a rigorous psychometric process to develop and validate an instrument to measure the impact of the COVID-19 pandemic in Australia, the COVID-19 Impact Scale (CIS).
METHOD
Data was obtained from the Australian population. Participants (N = 563) aged between 19 and 91 years (M = 54.50, SD = 16.16) provided online responses between June, 2021 and May, 2022. The majority of participants were female (60.9%), employed either full-time (37.7%) or part-time (22.0%), and had completed an undergraduate degree or higher (70.1%). An initial pool of 30 items was developed based on a review of the literature and input from a panel of experts including psychologists, epidemiologists, and public health experts, among others. The study used network psychometrics to examine the psychometric properties of: (1) item score distributions; (2) item redundancy; (3) dimensionality; (4) model fit; (5) measurement invariance; (6) reliability; and (7) criterion validity.
RESULTS
Following an evaluation of items for ceiling/floor effects and redundancy, the final CIS network model included eighteen nodes and displayed a three-dimensional structure. The three communities of "Fear" (consisting of three nodes; ω = 0.82), "Attitudes" (consisting of ten nodes; ω = 0.89), and "Ill-being" (consisting of five nodes; ω = 0.79) displayed adequate reliability. The evaluation of model fit indicated a good fit of the network model (RMSEA = 0.047; CFI =0.98).
CONCLUSION
The instrument is available to be used by Australian researchers and implemented to evaluate public policies, adapted for future pandemics, or used internationally.
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