Home⇛Asia Pacific Journal of Allied Health Sciences⇛vol. 6 no. 1 (2023)

Development of Knowledge, Attitude, and Practices Questionnaire for Computer Workstation Ergonomic Behaviors among Senior High School and College Teachers in a Private University in the Philippines

Kaycee E. Franco | Jamile Lorenza R. Magnaye | Evan Dave G. Gajiran | Ma. Pauline E. Eje | Juan Miguel H. Llanto | Raymond M. Tosoc

Discipline: Education

 

Abstract:

The shift to a work-from-home set-up placed professionals, particularly those in the education sector, at risk for developing musculoskeletal disorders (MSKD). Targeting teachers' knowledge, attitude, and practices (KAP) concerning computer workstation ergonomic behaviors (CWEB) is a way to reduce the risk. Still, there is currently a shortage of information about this strategy. The researchers conducted a pilot study to develop a KAP questionnaire to provide information about the risk factors for developing MSKD and KAP related to CWEB. The first draft was generated via literature review and was revised by six (6) experts through content validation. Thirty (30) teachers from the senior high school department and colleges of Lyceum of the Philippines University – Batangas answered the revised questionnaire. Five teachers and five experts performed face validation. Discriminant validity was analyzed using Pearson correlation. Internal consistency was analyzed using Cronbach's alpha for attitude and Kuder-Richardson 20 formula (KR20) for knowledge and practices. Test-retest reliability was assessed using the intraclass correlation coefficient. Results from the validation process demonstrated adequate content, face, and construct validity. KR-20 values of knowledge (0.70) and practices (0.72), as well as Cronbach's alpha coefficient of attitude (0.94) section, indicated acceptable tool reliability. The second draft of the questionnaire showed adequate psychometric properties in assessing KAP related to CWEB when used as a self-report tool. The questionnaire was further revised based on the appreciation of the results for improvement. Overall, this pilot study produced a valid and reliable tool with the potential for large-scale testing and implementation. This tool can facilitate future research exploring the risk factors and ergonomic behaviors of teachers, which can then be used as a guide in planning and designing interventions to lessen the risk of developing MSKD.



References:

  1. Pal, M., Berhanu, G., Desalegn, C., & Kandi, V. (Institute for Health Metrics and Evaluation. (2019). Philippines: Both sexes, All ages, 2019, DALYs attributable to Occupational ergonomic factors. In GBD Compare: Viz Hub. Retrieved August 2022, from https://vizhub.healthdata.org/gbd-compare/  
  2. World Health Organization and International Labour Organization. (2021). WHO/ILO joint estimates of the work-related burden of disease and injury, 2000-2016: global monitoring report. https://www.ilo.org/wcmsp5/groups/public/@ed_dialogue/@lab_admin/documents/publication/wcms_819788.pdf
  3. Centers for Disease Control and Prevention. (2020, February 12). Work-related Musculoskeletal Disorders & Ergonomics. Retrieved April 2021, from https://www.cdc.gov/workplacehealthpromotion/health-strategies/musculoskeletal-disorders/index.html  
  4. United Nations Development Programme. (2022). Decent work and economic growth. Sustainable Development Goals. Retrieved August 2022, from https://www.undp.org/sustainable-development-goals  
  5. United Nations Development Programme. (2022). Good health and well-being. Sustainable Development Goals. Retrieved August 2022, from  https://www.undp.org/sustainable-development-goals
  6. National Economic and Development Authority. (2022, May 9). Goal 3 – Good health and well-being - SDGs - Philippines. Retrieved August 2022, from https://sdg.neda.gov.ph/goal-3/  
  7. National Economic and Development Authority. (2022, May 9). Goal 8 – Decent work and economic growth - SDGs - Philippines. Retrieved August 2022, from https://sdg.neda.gov.ph/goal-8/
  8. Jessiman-Perreault, G., Alberga, A., Jorge, F., Makwarimba, E., & Allen Scott, L. (2020). Size Matters: A Latent Class Analysis of Workplace Health Promotion Knowledge, Attitudes, Practices and Likelihood of Action in Small Workplaces. International Journal of Environmental Research and Public Health, 17(4), 1251. https://doi:10.3390/ijerph17041251
  9. Andrade, C., Menon, V., Ameen, S., & Kumar Praharaj, S. (2020). Designing and conducting knowledge, attitude, and practice surveys in psychiatry: practical guidance. Indian Journal of Psychological Medicine, 42(5), 478–481. https://doi:10.1177/0253717620946111
  10. United States Department of Labor - Occupational Safety and Health Administration. (n.d.). Ergonomics. Retrieved May 2021, from https://www.osha.gov/ergonomics
  11. Canadian Centre for Occupational Health and Safety. (2022). Ergonomics. OSH Answers Fact Sheets. Retrieved April 2022, from  https://www.ccohs.ca/oshanswers/ergonomics
  12. Kim, J., Yang, K., Min, J., & White, B. (2022). Hope, fear, and consumer behavioral change amid COVID‐19: Application of protection motivation theory. International Journal of Consumer Studies, 46(2), 558-574. https://doi.org/10.1111/ijcs.12700
  13. Floyd, D. L., Prentice‐Dunn, S., & Rogers, R. W. (2000). A meta‐analysis of research on protection motivation theory. Journal of applied social psychology, 30(2), 407-429. https://doi.org/10.1111/j.1559-1816.2000.tb02323.x
  14. Philippine Statistics Authority. (2019). Table 11.8 Employed Persons by Major Industry Group and Major Occupation Group, Philippines: 2015-2017. (p 326) 2019 Philippine Statistical Yearbook. https://psa.gov.ph/products-and-services/publications/philippine-statistical-yearbook
  15. Department of Education. (2020). Revised Guidelines on Alternative Work Arrangements in the Department of Education During the Period of State of National Emergency Due to COVID-19 Pandemic. Retrieved April 2021, from: https://www.deped.gov.ph/2020/06/15/do-011-s-2020/
  16. Commission on Higher Education. (2020). CMO No. 4, Series of 2020 – Guidelines on the Implementation of Flexible Learning. Retrieved April 2021, from https://ched.gov.ph/wp-content/uploads/CMO-No.-4-s.-2020-Guidelines-on-the-Implementation-of-Flexible-Learning.pdf
  17. Dayagbil, F. T., Palompon, D. R., Garcia, L. L., & Olvido, M. M. J. (2021). Teaching and learning continuity amid and beyond the pandemic. In Frontiers in Education (p. 269). Frontiers. https://doi.org/10.3389/feduc.2021.678692
  18. Daquioag, J. L. A. (2021, August 10). Ph teachers use personal money to buy devices, services, NRCP Study shows. NRCP. Retrieved April 2022, from https://nrcp.dost.gov.ph/feature-articles/769-ph-teachers-use-personal-money-to-buy-devices-services-nrcp-study-shows  
  19. Netemeyer, R.G., Bearden, W.O., & Sharma, S. (2003). Scaling procedures: Issues and applications. Thousand Oaks, CA: Sage.
  20. Browne R. H. (1975). On the use of a pilot sample for sample size determination. Statistics in medicine, 14(17), 1933–1940. https://doi.org/10.1002/sim.4780141709
  21. Schultz, K.S., & Whitney, D.J. (2005). Measurement theory in action. Thousand Oaks, CA: Sage.
  22. Park, D. (2021). Development and Validation of a Knowledge, Attitudes and Practices Questionnaire on COVID-19 (KAP COVID-19). International Journal Of Environmental Research And Public Health, 18(14), 7493. https://doi.org/10.3390/ijerph18147493
  23. Saefi, M.,  Fauzi, A., Kristiana, E., Adi, W., Muchson, M., & Setiawan, M. et al. (2020). Validating of Knowledge, Attitudes, and Practices Questionnaire for Prevention of COVID-19 infections among Undergraduate Students: A RASCH and Factor Analysis. Eurasia Journal Of Mathematics, Science And Technology Education, 16(12), em1926. https://doi.org/10.29333/ejmste/9352
  24. Hatfield, M., Parsons, R., & Ciccarelli, M. (2016). The development and validation of the Healthy Computing Questionnaire for Children (HCQC). Work, 54(2), 389-399. https://doi.org/10.3233/WOR-162324
  25. Oza-Frank, R., Ali, M. K., Vaccarino, V., & Narayan, K. V. (2009). Asian Americans: diabetes prevalence across US and World Health Organization weight classifications. Diabetes care, 32(9), 1644-1646. https://doi.org/10.2337/dc09-0573
  26. World Health Organization expert consultation. (2004). Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet (London, England), 363(9403), 157-163. https://doi.org/10.1016/S0140-6736(03)15268-3
  27. Lynn, M.R. (1986). Determination and quantification of content validity. Nursing Research, 35, 382–385
  28. DeVon, H. A., Block, M. E., Moyle-Wright, P., Ernst, D. M., Hayden, S. J., Lazzara, D. J., Kostas-Polston, E. (2007). A Psychometric Toolbox for Testing Validity and Reliability. Journal of Nursing Scholarship, 39(2), 155–164. https://doi.org/10.1111/j.1547-5069.2007.00161.x
  29. Panjaitan, R. L., Irawati, R., Sujana, A., Hanifah, N., & Djuanda, D. (2018). Item validity vs. item discrimination index: a redundancy?.Journal of Physics: Conference Series (Vol. 983, No. 1, p. 012101). IOP Publishing. https://doi.org/10.1088/1742-6596/983/1/012101
  30. Earnest, B.S.P., Bhargava, P., Das, A.K., Azhar, D.M.T.M., Ibrahim, N.M., Sirisinghe, R.G. (2018). Transforming Teaching-Learning Culture by Appropriate Use of Discrimination Index in Item Analysis. In: Tang, S., Cheah, S. (eds) Redesigning Learning for Greater Social Impact. Springer, Singapore. https://doi.org/10.1007/978-981-10-4223-2_14
  31. Rush, B. R., Rankin, D. C., & White, B. J. (2016). The impact of item-writing flaws and item complexity on examination item difficulty and discrimination value. BMC medical education, 16(1), 1-10. https://doi.org/10.1186/s12909-016-0773-3
  32. Taib, F., & Yusoff, M. S. B. (2014). Difficulty index, discrimination index, sensitivity and specificity of long case and multiple choice questions to predict medical students’ examination performance. Journal of Taibah University Medical Sciences, 9(2), 110-114. http://dx.doi.org/10.1016/j.jtumed.2013.12.002
  33. Sim, S. M., & Rasiah, R. I. (2006). Relationship Between Item Difficulty and Discrimination Indices in True/False-Type Multiple Choice Questions of a Para-clinical Multidisciplinary Paper. Ann Acad Med Singapore, 35, 67-71. Retrieved August 8, 2022 from https://annals.edu.sg/pdf/35VolNo2200603/V35N2p67.pdf
  34. Backhoff, E., Larrazolo, N., & Rosas, M. (2000). The level of difficulty and discrimination power of the Basic Knowledge and Skills Examination (EXHCOBA). Revista Electrónica de Investigación Educativa, 2(1).  Retrieved August 8, 2022 from: https://redie.uabc.mx/vol2no1/contents-backhoff.htm
  35. Toma, R. B., & Meneses Villagrá, J. Á. (2019). Validation of the single-items Spanish-School Science Attitude Survey (S-SSAS) for elementary education. PloS one, 14(1), e0209027. https://doi.org/10.1371/journal.pone.0209027
  36. Brown Timothy, A. (2006). Confirmatory factor analysis for applied research. New York, NY: Guilford Press
  37. Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Economics and Finance, 20, 679-686. https://doi.org/10.1016/S2212-5671(15)00123-9
  38. Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53. https://doi.org/10.5116/ijme.4dfb.8dfd
  39. Beaton, D. E., Wright, J. G., Katz, J. N., & Upper Extremity Collaborative Group. (2005). Development of the QuickDASH: comparison of three item-reduction approaches. JBJS, 87(5), 1038-1046. https://doi.org/10.2106/JBJS.D.02060
  40. Bland, J. M., & Altman, D. G. (1997). Statistics notes: Cronbach’s alpha. BMJ, 314(7080), 572. https://doi.org/10.1136/bmj.314.7080.572
  41. Kumar, D., Jaipurkar, R., Shekhar, A., Sikri, G., & Srinivas, V. (2021). Item analysis of multiple-choice questions: A quality assurance test for an assessment tool. Medical Journal Armed Forces India, 77, S85-S89. https://doi.org/10.1016/j.mjafi.2020.11.007
  42. Koo, T. K., & Li, M. Y. (2016). A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. Journal of chiropractic medicine, 15(2), 155–163. https://doi.org/10.1016/j.jcm.2016.02.012
  43. Woo, E. H. C., White, P., & Lai, C. W. K. (2015). Ergonomics standards and guidelines for computer workstation design and the impact on users’ health – a review. Ergonomics, 59(3), 464–475. https://doi.org/10.1080/00140139.2015.1076528
  44. Algarni, F. S., Kachanathu, S. J., & AlAbdulwahab, S. S. (2020). A cross-sectional study on the association of patterns and physical risk factors with musculoskeletal disorders among academicians in saudi arabia. BioMed Research International, 2020, 1–7. https://doi.org/10.1155/2020/8930968
  45. Ardahan, M., & Simsek, H. (2016). Analyzing musculoskeletal system discomforts and risk factors in computer-using office workers. Pakistan Journal of Medical Sciences, 32(6). https://doi.org/10.12669/pjms.326.11436
  46. Aytutuldu, G. K., Birinci, T., & Tarakcı, E. (2020). Musculoskeletal pain and its relation to individual and work-related factors: A cross-sectional study among Turkish office workers who work using computers. International Journal of Occupational Safety and Ergonomics, 1–21. https://doi.org/10.1080/10803548.2020.1827528
  47. Bento, T. P. F., Genebra, C. V. dos S., Maciel, N. M., Cornélio, G. P., Simeão, S. F. A. P., & Vitta, A. de. (2019). Low back pain and some associated factors: is there any difference between genders? Brazilian Journal of Physical Therapy. https://doi.org/10.1016/j.bjpt.2019.01.012
  48. Celik, K., Celik, K., Dirimese, E., Tasdemir, N., Arik, T., Buyukkara., I. (2018). Determination of pain in musculoskeletal system reported by office workers and the pain risk factors. International Journal  of Occupational Medicine and Environmental Health. https://doi.org/10.13075/ijomeh.1896.00901
  49. Elshaer, N., (2018). Prevalence and associated factors related to arm, neck, and shoulder complaints in a selected sample of computer office workers. Journal of the Egyptian Public Health Association, (92)4. https://doi.org/10.21608/EPX.2018.22041
  50. Feng, B., Chen, K., Zhu, X., Ip, W.-Y., Andersen, L. L., Page, P., & Wang, Y. (2021). Prevalence and risk factors of self-reported wrist and hand symptoms and clinically confirmed carpal tunnel syndrome among office workers in China: a cross-sectional study. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-020-10137-1
  51. James, C., James, D., Nie, V., Schumacher, T., Guest, M., Tessier, J., Bohatko-Naismith, J., Snodgrass, S. (2018). Musculoskeletal discomfort and use of computers in the university environment. Applied Ergonomics, 69, 128–135. https://doi.org/10.1016/j.apergo.2018.01.   
  52. Janwantanakul, P., Sitthipornvorakul, E., & Paksaichol, A. (2012). Risk factors for the onset of nonspecific low back pain in office workers: a systematic review of prospective cohort studies. Journal of Manipulative and Physiological Therapeutics, 35(7), 568–577 https://doi.org/10.1016/j.jmpt.2012.07.008
  53. Kaliniene, G., Ustinaviciene, R., Skemiene, L., Vaiciulis, V., & Vasilavicius, P. (2016). Associations between musculoskeletal pain and work-related factors among public service sector computer workers in kaunas county, lithuania. BMC Musculoskeletal Disorders, 17(1). https://doi.org/10.1186/s12891-016-1281-7
  54. Kraemer, K., Moreira, M. F., & Guimarães, B. (2021). Musculoskeletal pain and ergonomic risks in teachers of a federal institution. Revista Brasileira De Medicina Do Trabalho: Publicacao Oficial Da Associacao Nacional De Medicina Do Trabalho-ANAMT, 18(3), 343–351. https://doi.org/10.47626/1679-4435-2020-608
  55. Mohan, V., Justine, M., Jagannathan, M., Aminudin, S. B., & Johari, S. H. B. (2015). Preliminary study of the patterns and physical risk factors of work-related musculoskeletal disorders among academicians in a higher learning institute. Journal of Orthopaedic Science, 20(2), 410–417. https://doi.org/10.1007/s00776-014-0682-4
  56. Oha, K., Animägi, L., Pääsuke, M., Coggon, D., & Merisalu, E. (2014). Individual and work-related risk factors for musculoskeletal pain: a cross-sectional study among Estonian computer users. BMC Musculoskeletal Disorders, 15(1). https://doi.org/10.1186/1471-2474-15-181
  57. Okezue, O. C., Anamezie, T. H., John, J. N., & John, D. O. (2020). Work-related musculoskeletal disorders among office workers in higher education institutions: A Cross-Sectional Study. Ethiopian Journal of Health Sciences, 30(5):715. https://dx.doi.org/10.4314/ejhs.v30i5.10
  58. Ranasinghe, P., Perera, Y. S., Lamabadusuriya, D. A., Kulatunga, S., Jayawardana, N., Rajapakse, S., & Katulanda, P. (2011). Work related complaints of neck, shoulder and arm among computer office workers: a cross-sectional evaluation of prevalence and risk factors in a developing country. Environmental Health, 10(1). https://doi.org/10.1186/1476-069x-10-70
  59. Rodríguez-Nogueira, Ó., Leirós-Rodríguez, R., Benítez-Andrades, J. A., Álvarez-Álvarez, M. J., Marqués-Sánchez, P., & Pinto-Carral, A. (2020). Musculoskeletal pain and teleworking in times of the covid-19: analysis of the impact on the workers at two Spanish universities. International Journal of Environmental Research and Public Health, 18(1), 31. https://doi.org/10.3390/ijerph18010031
  60. Muehlhausen, W., Doll, H., Quadri, N., Fordham, B., O’Donohoe, P., Dogar, N., & Wild, D. J. (2015). Equivalence of electronic and paper administration of patient-reported outcome measures: a systematic review and meta-analysis of studies conducted between 2007 and 2013. Health and quality of life outcomes, 13(1), 1-20. https://doi.org/10.1186/s12955-015-0362-x
  61. Campbell, N., Ali, F., Finlay, A. Y., & Salek, S. S. (2015). Equivalence of electronic and paper-based patient-reported outcome measures. Quality of Life Research, 24(8), 1949-1961. https://doi.org/10.1007/s11136-015-0937-3
  62. Brenner, P. S., DeLamater, J. (2016). Lies, Damned Lies, and Survey Self Reports? Identity as a Cause of Measurement Bias. Social Psychology Quarterly, 79(4), 333–354.
  63. Tourangeau, Roger, and Ting Yan. 2007. ‘‘Sensitive Questions in Surveys.’’ Psychological Bulletin 133:859–83.
  64. Buckle, P., & Buckle, J. (2011). Obesity, ergonomics and public health. Perspectives in Public Health, 131(4), 170-176. https://doi.org/10.1177/1757913911407267
  65. Food and Nutrition Research Institute of the Department of Science and Technology. (2013). 8th National nutrition survey. https://www.fnri.dost.gov.ph/images/sources/anthrop_adults-revised.pdf
  66. Akyol, P., Key, J., & Krishna, K. (2016, August 24). Precision versus bias in multiple choice exams. Centre for Economic Policy Research (CEPR). Retrieved September 14, 2022, from https://cepr.org/voxeu/columns/precision-versus-bias-multiple-choice-exams
  67. Prochaska, J. O. (2008). Decision making in the transtheoretical model of behavior change. Medical decision making, 28(6), 845-849. https://doi.org/10.1177/0272989X08327068.
  68. Prochaska, J. O., and Velicer, W. F. (1997). The transtheoretical model of health behavior. American Journal of Health Promotion. 12(1)

Tools


Copyright © 2025  KITE Digital Educational Solutions |  Exclusively distributed by CE-Logic