head JofIMAB
Journal of IMAB - Annual Proceeding (Scientific Papers)
Publisher: Peytchinski Publishing Ltd.
ISSN: 1312-773X (Online)
Issue: 2020, vol. 26, issue1
Subject Area: Dental Medicine
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DOI: 10.5272/jimab.2020261.2970
Published online: 13 March 2020

Original article

J of IMAB. 2020 Jan-Mar;26(1):2970-2974
COMPARISON BETWEEN WEB-BASED AND PAPER QUESTIONNAIRES FOR THE ASSESSMENT OF BURNOUT SYNDROME USING BOYKO’S METHODOLOGY
Rumyana Stoyanova1ORCID logo Corresponding Autoremail, Stanislava Harizanova2ORCID logo,
1) Department of Health Management and Health Economics, Faculty of Public Health, Medical University of Plovdiv, Bulgaria.
2) Department of Hygiene and Ecomedicine, Faculty of Public Health, Medical University of Plovdiv, Bulgaria.

ABSTRACT:
Introduction: Questionnaires are often used to quantify the subjective aspects of burnout syndrome. Data collection using web-based questionnaires generally improves data quality, because data are entered electronically and may automatically be transformed into an analyzable format, and errors in the process of data entry and coding are avoided as well.
Purpose: The aim of the study is to compare the completeness of data and consuming time of web-based and paper questionnaires for burnout syndrome based on Boyko’s inventory
Material and methods: In study took part 30 patients from one ambulatory practice, who completed the two versions of the questionnaire and their physician. Data completeness was assessed by comparing the number of missing values between the two methods. Consuming time was assessed by comparing the duration of completing and analyzed the data from the web-based and paper questionnaires.
Results: Paper questionnaires generally had more missing values (P<.05). Web-based questionnaires were completely filled out due to pop-up notifications that appeared directly onto questions with missing values. Duration of completing and processing a returned paper questionnaire was 3.5 times that of a returned web-based questionnaire.
Conclusion: The web-based system can be less time-consuming and a source of fewer errors than paper questionnaires and permits review of the data and compliance during the study.

Keywords: burnout, Boyko’s inventory, web-based questionnaire, eHealth,

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Please cite this article as: Stoyanova R, Harizanova S. Comparison between web-based and paper questionnaires for the assessment of burnout syndrome using Boyko’s methodology. J of IMAB. 2020 Jan-Mar;26(1):2970-2974. DOI: 10.5272/jimab.2020261.2970

Corresponding AutorCorrespondence to: Rumyana Stoyanova, Department of Health Management and Health Economics, Faculty of Public Health, Medical University of Plovdiv; 15A, Vasil Aprilov blvd., Plovdiv 4002, Bulgaria; E-mail: rumi_stoqnova@abv.bg

REFERENCES:
1. Dimova R, Mateva N, Bakova D, Tilov B. Burnout in Healthcare Employees Working in Surgical Departments, Anesthesiology and Intensive Care. In: New Model of Burn Out Syndrome: Towards early diagnosis and prevention. Stoyanov D, ed. River Publishers. January 2014. Chapter 5. p.59-70.
2. Harizanova S, Stoyanova R. Burnout among nurses and correctional officers. Work. 2020; 65(1):71-77. [PubMed] [Crossref]
3. Stoyanova R. Relationship Between Working Environment Factors, Burnout Syndrome and Turnover Intentions Among Nurses – A Cross-Sectional Study in Bulgaria. In: Bagnara S, Tartaglia R, Albolino S, Alexander T, Fujita Y. (eds). Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 818. Springer, Cham. 2019. pp.35-43. [Crossref]
4. Tsenova, B. Personality correlates of burnout syndrome. In: Dimitrov et all. Eds. Publishing House: Sofia-R. 2005;360-367. [in Bulgarian]
5. Ahola K, Väänänen A, Koskinen A, Kouvonen A, Shirom A. Burnout as a predictor of all-cause mortality among industrial employees: A 10-year prospective register-linkage study. J Psychosom Res.2010 July;69(1):51-57. [PubMed] [Crossref]
6. Kant IJ, Bültmann U, Schröer K, Beurskens A, Van Amelsvoort L, Swaen G. An epidemiological approach to study fatigue in the working population: The Maastricht Cohort Study. Occup Environ Med. 2003 June;60(Suppl. 1):i32-i39. [PubMed] [Crossref]
7. Langelaan S, Bakker AB, Schaufeli WB, van Rhenen W, van Doornen L. Do burned-out and work-engaged employees differ in the functioning of the hypothalamic-pituitary-adrenal axis? Scand J Work Environ Health. 2006 Oct;32(5):339-348. [PubMed] [Crossref]
8. von Känel R, van Nuffel M, Fuchs WJ. Risk assessment for job burnout with a mobile health web application using questionnaire data: a proof of concept study. Biopsychosoc Med. 2016 Nov 2;10(1):31. [PubMed] [Crossref]
9. King JD, Buolamwini J, Cromwell EA, Panfel A, Teferi T, Zerihun M, at al. A novel electronic data collection system for large-scale surveys of neglected tropical diseases. PLoS One. 2013 Sep 16;8(9):e74570. [PubMed] [Crossref]
10. Weber BA, Yarandi H, Rowe MA, Weber JP. A comparison study: paper-based versus web-based data collection and management. Appl Nurs Res.2005Aug;18(3):182-185. [PubMed] [Crossref]
11. Van Gelder MM, Bretveld RW, Roeleveld N. Web-based questionnaires: the future in epidemiology? Am J Epidemiol. 2010Sep;172(11):1292-1298. [PubMed] [Crossref]
12. mHealth App Developper Economics 2015. The current status and trends ofthe mHealth app market. 5th annual study on mHealth app publishing based on 5000 plus respondents. research2guidance. November 2015. [Internet]
13. Martínez-Pérez B, de la Torre-Díez I, López-Coronado M. Mobile health applications for the most prevalent conditions by the World Health Organization: review and analysis. J Med Internet Res. 2013 Jun 14;15(6):e120.  [PubMed] [Crossref].

Received: 05 September 2019
Published online: 13 March 2020

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