Validation and Psychometric Evaluation of the Italian Version of the Fear of COVID-19 Scale

Abstract

Background: The advent of COVID-19 worldwide has led to consequences for people's health, both physical and psychological, such as fear and anxiety. This is the case in Italy, one of the countries most affected by the pandemic. Given the heightened fear concerning COVID-19 in Italy., the present study analyzed the psychometric properties of the Italian version of the Fear of COVID-19 Scale (FCV-19S). Methods: The sample comprised 250 Italian participants who were administered Italian versions of the FCV-19S, the Hospital Anxiety and Depression Scale (HADS), and the Severity Measure for Specific Phobia-Adult (SMSP-A). Several psychometric tests were performed to investigate the validity and reliability of the test including confirmatory factor analysis. Results: Analysis of the data showed satisfactory psychometric characteristics and confirmed the scale's unidimensional properties. The seven FCV-19S items had acceptable correlations with the test total (from .443 to .784). Furthermore, the loadings on the factor were significant and strong (from .684 to .897). The internal consistency was very good (α = .871). Construct validity for the FCV-19S was supported by significant and positive correlations with the HADS (r=.649) and SMSP-A (r=.703). Conclusions: The Italian version of the Fear of COVID-19 Scale is valid and reliable in assessing fear of COVID-19 among the general Italian population.

Shown for reading. Its publisher allows quoting it, not republishing it.

References 52

1. 1.
   The Fear of COVID-19 Scale: Development and Initial Validation · 2020

   No notice
2. 2.

   American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 2013.

   Not in our library

3. 3.

   Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000). Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 25(24), 3186–3191. 10.1097/00007632-200012150-00014.

   Not in our library10.1097/00007632-200012150-00014

4. 4.
   Infectious Disease Threats in the Twenty-First Century: Strengthening the Global Response · 2019

   No notice
5. 5.

   Bollen, K. A., & Long, J. S. (1993). Testing structural equation models. London: Sage

   Not in our library

6. 6.

   Boomsma, A. (2000). Reporting analyses of covariance structures. Structural Equation Modeling, 7(3), 461–483. 10.1207/S15328007SEM0703_6.

   Not in our library

7. 7.

   Brannon N, Schuyler D. Comorbid generalized anxiety disorder, phobia, and panic disorder. Primary Care Companion to the Journal of Clinical Psychiatry. 2000;2(4):141-142.

   Not in our library10.4088/pcc.v02n0411

8. 8.

   Browne MW, Cudeck R. Single sample cross-validation indices for covariance structure. British Journal of Mathematical and Statistical Psychology. 1993;37:62-83.

   Not in our library10.1111/j.2044-8317.1984.tb00789.x

9. 9.

   Centers for Disease Control and Prevention. (2020a). Coronavirus Disease 2019 (COVID-19): Manage anxiety & stress. Retrieved from: https://www.cdc.gov/coronavirus/2019-ncov/prepare/managing-stress-anxiety.html. Accessed 15 Apr 15 2020.

   Not in our library

10. 10.

    Centers for Disease Control and Prevention. (2020b). Coronavirus disease 2019 (COVID-19): reducing stigma. Retrieved from: https://www.cdc.gov/coronavirus/2019-ncov/about/related-stigma.html. Accessed 15 Apr 2020.

    Not in our library

11. 11.

    Centers for Disease Control and Prevention. (2020c). Coronavirus disease 2019 (COVID-19): stress and coping. Retrieved from: https://www.cdc.gov/coronavirus/2019-ncov/daily-life-coping/managing-stress-anxiety.html. Accessed 15 Apr 2020.

    Not in our library

12. 12.

    Cerny CA, Kaiser HF. A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivariate Behavioral Research. 1977;12(1):43-47.

    Not in our library10.1207/s15327906mbr1201_3

13. 13.

    Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han Y., Qiu Y., Wang J., Liu Y., Wei Y., Xia J., Yu T., Zhang X. Zhang, L. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. The Lancet, 395(10223), 507–513.

    Not in our library10.1016/s0140-6736(20)30211-7

14. 14.

    Costantini, M., Musso, M., Viterbori, P., Bonci, F., Del Mastro, L., Garrone, O., Venturini, M., & Morasso, G. (1999). Detecting psychological distress in cancer patients: Validity of the Italian version of the Hospital Anxiety and Depression Scale. Supportive Care in Cancer, 7(3), 121–127.

    Not in our library10.1007/s005200050241

15. 15.

    Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302. 10.1037/h0040957.

    Not in our library10.1037/h0040957

16. 16.

    Dong L, Hu S, Gao J. Discovering drugs to treat coronavirus disease 2019 (COVID-19). Drug Discoveries & Therapeutics. 2020;14(1):58-60.

    Not in our library10.5582/ddt.2020.01012

17. 17.

    Duncan, L. A., Schaller, M., & Park, J. H. (2009). Perceived vulnerability to disease: Development and validation of a 15-item self-report instrument. Personality and Individual Differences, 47(6), 541–546.

    Not in our library

18. 18.

    Falagas, M. E., & Kiriaze, I. J. (2006). Reaction to the threat of influenza pandemic: The mass media and the public. Critical Care, 10(2), 408.

    Not in our library10.1186/cc4910

19. 19.

    Ferguson, E. A., & Cox, T. (1993). Exploratory factor analysis: A users’ guide. International Journal of Selection and Assessment, 1, 84–94.

    Not in our library

20. 20.

    Ferrando, P., & Lorenzo-Seva, U. (2017). Program FACTOR at 10: Origins, development and future directions. Psicothema, 29, 236–240. 10.7334/psicothema2016.304.

    Not in our library10.7334/psicothema2016.304

21. 21.

    Ford BN, Yolken RH, Dickerson FB, Teague TK, Irwin MR, Paulus MP, Savitz J. Reduced immunity to measles in adults with major depressive disorder. Psychological Medicine. 2018;49(2):243-249.

    Not in our library10.1017/s0033291718000661

22. 22.

    Fornell C, Larcker D. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 1981;18(1):39-50.

    Not in our library10.1177/002224378101800104

23. 23.

    Fossati, A., Borroni, S., & Del Corno, F. (2015). Scala di valutazione della gravità della fobia specifica – Adulto - Raffaello Cortina Editore - Ebook Raffaello Cortina Editore. Retrieved from: http://www.raffaellocortina.it/scheda-ebook/american-psychiatric-association/scale-divalutazione-adulti-9788860307668-2150.html. Accessed 15 Apr 2020.

    Not in our library

24. 24.

    Gorsuch, R. L. (1983). Factor analysis (2nd Edition). Hillsdale, NJ: Erlbaum.

    Not in our library

25. 25.

    Greenson RR. Phobia, anxiety, and depression. Journal of the American Psychoanalytic Association. 1959;7(4):663-674.

    Not in our library10.1177/000306515900700404

26. 26.

    Guan, W., Ni, Z., Hu, Y., Liang, W., Ou, C.,... & Zhong, N. (2020). Clinical characteristics of coronavirus disease 2019 in China. New England Journal of Medicine. Epub ahead of print. 10.1056/nejmoa2002032.

    Not in our library10.1056/nejmoa2002032

27. 27.

    Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.

    Not in our library

28. 28.

    Huang, Y., & Zhao, N. (2020). Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 epidemic in China: A web-based cross-sectional survey. medRxiv. 10.1101/2020.02.19.20025395.

    Not in our library10.1016/j.psychres.2020.112954

29. 29.

    IBM Corp. (2017). IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.

    Not in our library

30. 30.

    Johns Hopkins Center for Systems Science and Engineering. (2020). Coronavirus COVID-19 global cases. retrieved April 2, from: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6.

    Not in our library

31. 31.

    Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. 10.1007/BF02291575.

    Not in our library

32. 32.

    Kline RB. Methodology in the social sciences. Principles and practice of structural equation modeling. 2011.

    Not in our library

33. 33.

    Kline, R. B. (2016). Methodology in the social sciences. Principles and practice of structural equation modeling (4th ed.). Guilford Press.

    Not in our library

34. 34.

    Knappe, S., Klotsche, J., Strobel, A., LeBeau, R., Craske, M., Wittchen, H., & Beesdo-Baum, K. (2013). Dimensional anxiety scales for DSM-5: Sensitivity to clinical severity. European Psychiatry, 28(7), 448–456.

    Not in our library10.1016/j.eurpsy.2013.02.001

35. 35.

    Lin C-Y. Social reaction toward the 2019 novel coronavirus (COVID-19). Social Health and Behavior. 2020;3(1):1-2.

    Not in our library10.4103/shb.shb_11_20

36. 36.

    Matthews, T., Danese, A., Caspi, A., Fisher, H. L., Goldman-Mellor, S., Kepa, A., Moffitt, T. E., Odgers, C. L., & Arseneault, L. (2019). Lonely young adults in modern Britain: Findings from an epidemiological cohort study. Psychological Medicine, 49(2), 268–277.

    Not in our library10.1017/s0033291718000788

37. 37.

    Mindrila, D. (2010). Maximum likelihood (ML) and diagonally weighted least squares (DWLS) estimation procedures: A comparison of estimation bias with ordinal and multivariate non-normal data. International Journal of Digital Society, 1, 60–66.

    Not in our library

38. 38.

    Morey JN, Boggero IA, Scott AB, Segerstrom SC. Current directions in stress and human immune function. Current Opinion in Psychology. 2015;5:13-17.

    Not in our library10.1016/j.copsyc.2015.03.007

39. 39.

    Muthén B, Kaplan D. A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology. 1985;38(2):171-189.

    Not in our library10.1111/j.2044-8317.1985.tb00832.x

40. 40.

    Muthén LK, Muthén BO. Mplus user’s guide. 1998.

    Not in our library

41. 41.

    Netemeyer RG, Bearden WO, Sharma S. Scaling procedures. Issues and applications. 2003.

    Not in our library

42. 42.

    Pappas G, Kiriaze IJ, Giannakis P, Falagas ME. Psychosocial consequences of infectious diseases. Clinical Microbiology and Infection. 2009;15(8):743-747.

    Not in our library10.1111/j.1469-0691.2009.02947.x

43. 43.

    R Core Team. (2014). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.

    Not in our library

44. 44.

    Raykov T. Estimation of composite reliability for congeneric measures. Applied Psychological Measurement. 1997;21(2):173-184.

    Not in our library10.1177/01466216970212006

45. 45.

    Ropeik D. The consequences of fear. EMBO Reports. 2004;5(Suppl 1):S56-S60.

    Not in our library10.1038/sj.embor.7400228

46. 46.

    Rosseel, Y. (2011). lavaan: An R Package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. 10.18637/jss.v048.i02.

    Not in our library

47. 47.

    Santini, Z. I., Jose, P. E., Cornwell, E. Y., Koyanagi, A., Nielsen, L., Hinrichsen, C., et al. (2020). Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): A longitudinal mediation analysis. The Lancet Public Health, 5(1), e62–e70.

    Not in our library10.1016/s2468-2667(19)30230-0

48. 48.

    Tabachnick BG, Fidell LS. Using multivariate statistics. 2007.

    Not in our library

49. 49.

    Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X.,... & Peng, Z. (2020). Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA, 323, 1061.

    Not in our library10.1001/jama.2020.1585

50. 50.

    Whittaker, T. A. (2012). Using the modification index and standardized expected parameter change for model modification. Journal of Experimental Education, 80(1), 26–44.

    Not in our library

51. 51.

    World Health Organization (2020). Coronavirus disease (COVID-2019): situation report-54. Retrieved from: https://www.who.int/docs/defaultsource/coronaviruse/situation-reports/20200314-sitrep-54-covid19.pdf?sfvrsn=dcd46351_2. Accessed 15 Apr 2020.

    Not in our library

52. 52.

    Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67(6), 361–370.

    Not in our library10.1111/j.1600-0447.1983.tb09716.x

Cited by papers we hold 12

• Parallel exploratory and confirmatory factor analysis of the Hungarian Fear of COVID-19 Scale in a large general population sample: a psychometric and dimensionality evaluation · 2022
  Not checked
• The effect of vaccination beliefs regarding vaccination benefits and COVID-19 fear on the number of vaccination injections · 2022
  Not checked
• Sleep quality and mental health during the COVID-19 pandemic in patients with severe obstructive sleep apnea · 2022
  Not checked
• Fear of COVID-19 and its association with mental health-related factors: systematic review and meta-analysis · 2022
  No notice
• Socio-Demographic Variables, Fear of COVID-19, Anxiety, and Depression: Prevalence, Relationships and Explanatory Model in the General Population of Seven Latin American Countries · 2021
  Not checked
• Systematic Review and Meta-Analysis of Fear of COVID-19 · 2021
  No notice
• Does COVID-19 Impact Less on Post-stroke Aphasia? This Is Not the Case · 2020
  Not checked
• On the Nature of Fear and Anxiety Triggered by COVID-19 · 2020
  No notice
• Depression and Anxiety in Hong Kong during COVID-19 · 2020
  No notice
• Fear of COVID-19, Stress, and Anxiety in University Undergraduate Students: A Predictive Model for Depression · 2020
  No notice
• Meaning in Life and Self-Control Buffer Stress in Times of COVID-19: Moderating and Mediating Effects With Regard to Mental Distress · 2020
  No notice
• Psychometric Validation of the Bangla Fear of COVID-19 Scale: Confirmatory Factor Analysis and Rasch Analysis · 2020
  No notice

Reads

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.