Factor Structure and Reliability of New COVID-19 Anxiety Scale

Abstract

Introduction: Covid-19 pandemic poses a challenge to our mental health.  Anxiety and depression cases are increased dramatically due to economic, psychological, and social changes in this time. The present study aimed to develop a covid-19 anxiety scale on the Indian sample. Methods: The first pool of items has been written after the interview of 5 participants who had identified as more fearful with covid-19 in observation. Thereafter, a questionnaire of 9-items with a 5-point rating scale was distributed to 300 participants, of which 253 filled questionnaires were collected. Data were analyzed with the help of Excel and SPSS version 23. Item-discrimination, principal component analysis for factor structure, and reliability analysis were done to evaluate the psychometric properties of the scale. In addition to this, correlation of anxiety and depression was analyzed with a covid-19 anxiety scale. Results: Item discrimination analysis revealed that items are discriminating from high anxiety to low anxiety groups. The principal component analysis gives a two-factor structure solution, and the alpha coefficient has been found 0.80 which is a good reliability coefficient for a scale. Results of correlation and regression analysis showed that covide-19 anxiety significant predicted the anxiety and depression. Conclusion: Results of study suggest that the in initial test of present covid-19 anxiety scale found reliable. It can be used to screen out the individuals with covid-19 anxiety. However, further and more studies will be required to validate this scale with multiple approach and across the population. This newly developed scale would be helpful in the diagnosis and treatment of people suffering from covid-19 anxiety.