Literature DB >> 25744132

A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace.

María del Mar Seguí1, Julio Cabrero-García2, Ana Crespo3, José Verdú4, Elena Ronda5.   

Abstract

OBJECTIVES: To design and validate a questionnaire to measure visual symptoms related to exposure to computers in the workplace. STUDY DESIGN AND
SETTING: Our computer vision syndrome questionnaire (CVS-Q) was based on a literature review and validated through discussion with experts and performance of a pretest, pilot test, and retest. Content validity was evaluated by occupational health, optometry, and ophthalmology experts. Rasch analysis was used in the psychometric evaluation of the questionnaire. Criterion validity was determined by calculating the sensitivity and specificity, receiver operator characteristic curve, and cutoff point. Test-retest repeatability was tested using the intraclass correlation coefficient (ICC) and concordance by Cohen's kappa (κ).
RESULTS: The CVS-Q was developed with wide consensus among experts and was well accepted by the target group. It assesses the frequency and intensity of 16 symptoms using a single rating scale (symptom severity) that fits the Rasch rating scale model well. The questionnaire has sensitivity and specificity over 70% and achieved good test-retest repeatability both for the scores obtained [ICC = 0.802; 95% confidence interval (CI): 0.673, 0.884] and CVS classification (κ = 0.612; 95% CI: 0.384, 0.839).
CONCLUSION: The CVS-Q has acceptable psychometric properties, making it a valid and reliable tool to control the visual health of computer workers, and can potentially be used in clinical trials and outcome research.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Asthenopia; Computer terminals; Diagnosis; Eye diseases; Occupational exposure; Occupational health

Mesh:

Year:  2015        PMID: 25744132     DOI: 10.1016/j.jclinepi.2015.01.015

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  31 in total

1.  Immediate Ocular Changes After Light-Emitting Diode Displays Exposure-A Preliminary Study.

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Journal:  Front Med (Lausanne)       Date:  2022-04-04

2.  Influence of virtual reality on visual parameters: immersive versus non-immersive mode.

Authors:  Hyeon Jeong Yoon; Jonghwa Kim; Sang Woo Park; Hwan Heo
Journal:  BMC Ophthalmol       Date:  2020-05-24       Impact factor: 2.209

3.  Five levels of performance and two subscales identified in the computer-vision symptom scale (CVSS17) by Rasch, factor, and discriminant analysis.

Authors:  Mariano González-Pérez; Rosario Susi; Ana Barrio; Beatriz Antona
Journal:  PLoS One       Date:  2018-08-28       Impact factor: 3.240

4.  Association between Poor Ergophthalmologic Practices and Computer Vision Syndrome among University Administrative Staff in Ghana.

Authors:  Samuel Bert Boadi-Kusi; Sampson Listowell Abu; George Oppong Acheampong; Peter Osei-Wusu Adueming; Emmanuel Kwasi Abu
Journal:  J Environ Public Health       Date:  2020-04-27

5.  Prevalence of Computer Vision Syndrome and Its Relationship with Ergonomic and Individual Factors in Presbyopic VDT Workers Using Progressive Addition Lenses.

Authors:  Mar Sánchez-Brau; Begoña Domenech-Amigot; Francisco Brocal-Fernández; Jose Antonio Quesada-Rico; Mar Seguí-Crespo
Journal:  Int J Environ Res Public Health       Date:  2020-02-05       Impact factor: 3.390

6.  Computer Vision Syndrome During SARS-CoV-2 Outbreak in University Students: A Comparison Between Online Courses and Classroom Lectures.

Authors:  Lixiang Wang; Xin Wei; Yingping Deng
Journal:  Front Public Health       Date:  2021-07-08

7.  Rasch analysis for development and reduction of Symptom Questionnaire for Visual Dysfunctions (SQVD).

Authors:  Mario Cantó-Cerdán; Pilar Cacho-Martínez; Francisco Lara-Lacárcel; Ángel García-Muñoz
Journal:  Sci Rep       Date:  2021-07-21       Impact factor: 4.379

Review 8.  Optical correction of refractive error for preventing and treating eye symptoms in computer users.

Authors:  Pauline Heus; Jos H Verbeek; Christina Tikka
Journal:  Cochrane Database Syst Rev       Date:  2018-04-10

Review 9.  Digital eye strain: prevalence, measurement and amelioration.

Authors:  Amy L Sheppard; James S Wolffsohn
Journal:  BMJ Open Ophthalmol       Date:  2018-04-16

10.  An investigation of low power convex lenses (adds) for eyestrain in the digital age (CLEDA).

Authors:  Robert Yammouni; Bruce Jw Evans
Journal:  J Optom       Date:  2020-04-22
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