Translation and validation of Computer Vision Syndrome Scale 17 (CVSS 17) – the Malay version
List of Authors
  • Din NSS , Mazapuspavina MY

Keyword
  • CVSS17, “Computer vision syndrome” (CVS), “Computer-related vision and ocular symptoms” (CRVOS), validation, translation

Abstract
  • INTRODUCTION: Computer Vision Syndrome Scale 17 (CVSS17) is a questionnaire to measure computer-related visual and ocular symptoms among video display terminal workers. This study aimed to translate CVSS17 into Malay language and determine its psychometric properties among video display terminal workers. MATERIALS AND METHODS: This was a cross-sectional validation study involving 206 workers in Universiti Teknologi MARA UiTM Selayang and Sungai Buloh Campus. The English version of the CVSS17 questionnaire is a 17-item scale measuring two key factors, which are internal symptom factors (11 items) and external symptom factors (6 items). The CVSS17 underwent forward-backward translation, face validation, and field testing to produce the Malay version. Validity of the items assessing psychometric properties was performed using exploratory factor analysis. The reliability testing was performed using internal consistency and test-retest reliability. RESULTS: The validated CVSS17-Malay version retained all 17 items with acceptable factor loadings. There were 13 items in the external, and 4 items in the internal symptom factors domain. In comparison to the original version, 4 items (A2, A22, A28, A30) were swapped from internal to external symptom factors and 2 items (C16 and C23) swapped from external to internal symptom factors. The changes of these items into different domains were discussed. The overall Cronbach’s α was 0.867 and the intraclass correlation coefficient was 0.866. The Kaiser-Meyer-Olkin was 0.928, and Bartlett’s test of sphericity was p-value <0.001. CONCLUSION: The CVSS17 Malay version is valid, reliable, and stable over time, to be used in measuring computer vision syndrome among Malay-speaking workers.

Reference
  • 1.Parihar JKS, Jain VK, Chaturvedi P, et al. Computer and visual display terminals (VDT) vision syndrome (CVDTS). Med J Armed Forces India 2016; 72(3):270-6.
    2.Coles-Brennan C, Sulley A, Young G. Management of digital eye strain. Clinical and ExperimentalOptometry 2019; 102(1):18-29.
    3.Blehm C, Vishnu S, Khattak A, et al. Computer Vision Syndrome: A Review. Survey of Ophthalmology 2005; 50(3):253-62.
    4.Sheedy JE, Hayes JN, Engle J. Is all asthenopia the same? Optom Vis Sci 2003; 80(11):732-9.
    5.M Logaraj VM, SK Hegde. Computer Vision Syndrome and Associated Factors Among Medical and Engineering Students in Chennai. Annal Medical Health & Science Research 2014; 4(2):179-85.
    6.Assefa NL, Zenebe D, Weldemichael, et al. Prevalence and associated factors of computer vision syndrome among bank workers in Gondar City, northwest Ethiopia, 2015. Clinical Optometry 2017; 9:67-76.
    7.P. Ranasinghe WSW, Y. S. Perera, D. A. Lamabadusuriya, et al. Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors. BMC research notes 2016; 9(150).
    8.Zairina A. Rahman SS. Computer User: Demographic and Computer Related Factors that Predispose User to Get Computer Vision Syndrome. International Journal of Business, Humanities and Technology 2011; Vol. 1(No 2).
    9.Reddy SC, Low CK, Lim YP, et al. Computer vision syndrome: a study of knowledge and practices in university students. Nepal J Ophthalmol 2013; 5(2):161-8.
    10.Masakazu Yamada YM, Chika Shigeyasu. Impact of dry eye on work productivity. ClinicoEconomics and Outcomes Research 2012; 2012(4):307-12.
    11.Hayes JR, Sheedy, James E., et al. Computer use, symptoms, and quality of life Optom Vis Sci 2007; 84(8):738-44.
    12.Sheppard AL, Wolffsohn JS. Digital eye strain: prevalence, measurement and amelioration. BMJ Open Ophthalmology 2018; 3(1):e000146.
    13.Maeda E, Yoshikawa T, Hayashi N, et al. Radiology reading-caused fatigue and measurement of eye strain with critical flicker fusion frequency. Japanese journal of radiology 2011; 29(7):483-7.
    14.Freudenthaler N, Neuf H, Kadner G, Schlote T. Characteristics of spontaneous eyeblink activity during video display terminal use in healthy volunteers. Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie 2003; 241(11):914-20.
    15.Himebaugh NL, Begley CG, Bradley A, et al. Blinking and tear break-up during four visual tasks. Optom Vis Sci 2009; 86(2):E106-14.
    16.Chi CF, Lin FT. A comparison of seven visual fatigue assessment techniques in three dataacquisition VDT tasks. Human factors 1998; 40(4):577-90.
    17.Mocci F, Serra A, Corrias GA. Psychological factors and visual fatigue in working with video display terminals. Occupational and Environmental Medicine 2001; 58(4):267.
    18.Woods V. Musculoskeletal disorders and visual strain in intensive data processing workers. Occupational medicine (Oxford, England) 2005; 55(2):121-7.
    19.Ye Z, Honda S, Abe Y, et al. Influence of work duration or physical symptoms on mental health among Japanese visual display terminal users. Industrial health 2007; 45(2):328-33.
    20.Sen A RS. A study of computer-related upper limb discomfort and computer vision syndrome. Journal of human ergology (Tokyo) 2007; 36(2):45-50.
    21.Rajabi-Vardanjani H, Habibi E, Pourabdian S, et al. Designing and validation a visual fatigue questionnaire for video display terminals operators. Int J Prev Med 2014; 5(7):841-8.
    22.Segui Mdel M, Cabrero-Garcia J, Crespo A, et al. A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace. J Clin Epidemiol 2015; 68(6):662-73.
    23.González-Pérez M, Susi R, Antona B, et al. The Computer-Vision Symptom Scale (CVSS17): Development and Initial ValidationDevelopment and Initial Validation of the CVSS17. Investigative Ophthalmology & Visual Science 2014; 55(7):4504-11.
    24.González-Pérez M, Susi R, Barrio A, et al. Five levels of performance and two subscales identified in the computer-vision symptom scale (CVSS17) by Rasch, factor, and discriminant analysis. PLOS ONE 2018; 13(8):e0202173.
    25.Wild D, Grove A, Martin M, et al. Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes (PRO) Measures: report of the ISPOR Task Force for Translation and Cultural Adaptation. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research 2005; 8(2):94-104.