E-Voting Adoption Instrument: Enhancing Validity Through Cognitive Interviews
DOI:
https://doi.org/10.22399/ijcesen.3216Keywords:
E-voting Adoption, Cognitive Interviews, Questionnaire Validity, UTAUT, Developing CountriesAbstract
Digital governance has been transformed with the development of electronic voting (e-voting) which offers prospective advantages to the electoral process, making it more transparent, efficient, and accessible. Although the significance of e-voting has been recognized worldwide, developing countries seem to struggle with its adoption due to numerous factors, primarily the dearth of questionnaire pre-testing methods for ensuring the reliability and validity of the collected data. The current study thus conducts cognitive interviews for the purpose of pre-testing a proposed instrument for measuring the adoption of e-voting amongst prospective voters. The interview participants were selected via purposive sampling which enables the researcher to identify and resolve any vagueness, misinterpretations, and culturally immaterial items in the questionnaire. It was discovered that cognitive interviews are valuable for revealing the participants’ thinking process and enhancing comprehension of the questionnaire items. The instrument’s clarity and relevance were enhanced via adjustments according to the participant feedbacks, hence boosting its construct validity. The practical significance of solid pre-testing methods is underlined in this study, especially in the examination of technology adoption. This study’s refinement of the survey design improves the robustness of e-voting adoption assessment tools, thus aiding policymakers and stakeholders in making informed decisions. These are key towards nurturing voters’ trust and perceived usability of e-voting systems, particularly in the distinct sociocultural setting of developing nations.
References
[1] H. M. Pratama and N. A. Salabi, (2020). Adoption of Voting Technology: A Guide for Electoral Stakeholders in Indonesia. doi: 10.31752/idea.2020.26.
[2] S. Elfattal, M. Awad, and S. Ben Abderrahmen, (2023). E-voting in Literature: Analyzing Nations’ Interest, in Central and Eastern European eDem and eGov Days 2023, New York, NY, USA: ACM, 41–46. doi: 10.1145/3603304.3603340.
[3] H. Salman, D. R. Hasan, and D. E. K. Gbashi, (2022). Development of Electronic Elections Systems: A Review, Webology, vol. 19(1), 1750–1762, doi: 10.14704/web/v19i1/web19117.
[4] G. Ikrissi and T. Mazri, (2024). Electronic Voting: Review and Challenges, in The Proceedings of the International Conference on Smart City Applications, Springer, 110–119.
[5] H. Binte Haq, S. Taha Ali, and R. McDermott, (2022). End-to-end verifiable voting for developing countries--what’s hard in Lausanne is harder still in Lahore, arXiv e-prints, p. arXiv-2210.
[6] L. Lessa and M. Hailu, (2023). Readiness for Implementing an E-Voting System in Ethiopia, in Handbook of Research on Digitalization Solutions for Social and Economic Needs, 243–255. doi: 10.4018/978-1-6684-4102-2.ch011.
[7] R. H. Sahib and E. S. Al-Shamery, (2021). An Online E-voting System based on an Adaptive Ledger with Singular Value Decomposition Technique, Karbala Int. J. Mod. Sci., vol. 7(4). 281–300, 2021, doi: 10.33640/2405-609X.3156.
[8] S. A. Adeshina and A. Ojo, (2020). Factors for e-voting adoption-analysis of general elections in Nigeria, Gov. Inf. Q., vol. 37(3), 101257.
[9] M. K. Alomari and H. U. Khan, (2022). Toward a Significant E-Voting Adoption Model: The Digital Divide, Int. J. Technol. Hum. Interact., vol. 18(1), doi: 10.4018/IJTHI.300283.
[10] J. Sauro and J. Lewis, Seven Reasons People Misinterpret Survey Questions, Measuring U. https://measuringu.com/seven-reasons-for-misinterpretation/
[11] E. M. Ikart, (2019). Survey Questionnaire Survey Pretesting Method: An Evaluation of Survey Questionnaire via Expert Reviews Technique, Asian J. Soc. Sci. Stud., vol. 4(2). doi: 10.20849/ajsss.v4i2.565.
[12] E. D. De Leeuw, (2005). To mix or not to mix data collection modes in surveys., J. Off. Stat., vol. 21(5), 233–255.
[13] C. Buschle, H. Reiter, and A. Bethmann, (2022). The qualitative pretest interview for questionnaire development: Outline of programme and practice, Qual. Quant., vol. 56(2), 823–842.
[14] P. Grimm, (2010). Pretesting a questionnaire, Wiley Int. Encycl. Mark.
[15] A. P. Chokki, A. Simonofski, B. Frénay, and B. Vanderose, (2022). Engaging citizens with open government data: The value of dashboards compared to individual visualizations, Digit. Gov. Res. Pract., vol. 3(3), 1–20.
[16] W. A. Mustafa, P. Subramaniam, S. E. Ghazali, and N. A. Aziz, (2022). Cognitive Intervention and Its Cultural Components for People with Dementia in Asia: A Systematic Review, J. Psikol. MALAYSIA, vol. 35(3).
[17] J. Wright, N. Moghaddam, and D. L. Dawson, (2021). Cognitive interviewing in patient-reported outcome measures: A systematic review of methodological processes., Qual. Psychol., vol. 8(1).
[18] P. Hadler, (2021). Question order effects in cross-cultural web probing: Pretesting behavior and attitude questions, Soc. Sci. Comput. Rev., vol. 39(6), 1292–1312.
[19] R. F. DeVellis and C. T. Thorpe, (2021). Scale development: Theory and applications. Sage publications.
[20] S. Bhalla, N. Bahar, and K. Kanapathy, (2023). Pre-testing semi-structured interview questions using expert review and cognitive interview methods, Int. J. Bus. Manag., vol. 7(5), 11–19.
[21] G. B. Willis, (2004). Cognitive interviewing: A tool for improving questionnaire design. sage publications.
[22] T. R. Meinel et al., (2023). Management of covert brain infarction survey: A call to care for and trial this neglected population, Eur. stroke J., vol. 8(4). 1079–1088.
[23] A. Caporaso and S. Presser, (2024). The Prevalence and Nature of Cognitive Interviewing as a Survey Questionnaire Evaluation Method in the United States, J. Surv. Stat. Methodol., smad047, 2024.
[24] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, (2003). User acceptance of information technology: Toward a unified view, MIS Q. Manag. Inf. Syst., vol. 27(3), 425–478, doi: 10.2307/30036540.
[25] L. Carter and F. Bélanger, (2005). The utilization of e-government services: Citizen trust, innovation and acceptance factors, Inf. Syst. J., vol. 15(1), 5–25, doi: 10.1111/j.1365-2575.2005.00183.x.
[26] S. Risnanto, Y. B. A. Rahim, N. S. Herman, and A. Abdurrohman, (2020). E-voting readiness mapping for general election implementation, J. Theor. Appl. Inf. Technol., vol. 98(20), 3280–3290.
[27] Z. W. Alfain, H. Setiawan, and I. K. S. Buana, (2022). Analysis of Centralized vs Decentralized Electronic Voting, in 2022 IEEE 8th Information Technology International Seminar (ITIS), IEEE, 173–177.
[28] F. D. Davis, (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Q., 319–340.
[29] M. R. Tulkinovna and Z. S. T. Ugli, (2023). E-Voting & Electorate Attitude in 2023 Election in Nigeria, Cent. Asian J. Innov. Tour. Manag. Financ., vol. 04(02), 116–120.
[30] A. Al-Ashoush, K. Altarawneh, and O. Lasaasmeh, (2023). The Feasibility of Adopting a Secure E-voting Based Biometrics Authenticity: The Jordanian Parliamentary Elections, TEM J., vol. 12(1), 59–65, doi: 10.18421/TEM121-08.
[31] F. Yousef and A. Albattat, (2023). The use of UTAUT to investigate the Intention to use E-Voting System in Jordan mediated by Perceived Value.
[32] S. Agbesi, (2020). Institutional Drivers of Internet Voting Adoption in Ghana: A Qualitative Exploratory Studies, Nord. Balt. J. Inf. Commun. Technol., vol. 1, 53–76, doi: 10.13052/nbjict1902-097x.2020.003.
[33] C. E. Hilton, The importance of pretesting questionnaires : a field research example of cognitive pretesting the Exercise referral Quality of Life Scale (ER-QLS) The importance of pretesting questionnaires : a field research example of cognitive pretesting the Exerci, doi: 10.1080/13645579.2015.1091640.
[34] J. Dent, N. Smeeton, L. Whiting, and T. Watson, (2023). Exploring midwives’ emotional wellbeing: evaluation of a survey using cognitive interviews, Br. J. Midwifery, vol. 31(5), 252–259.
[35] V. Zamanzadeh, A. Ghahramanian, and L. Valizadeh, (2022). Improving the face validity of self-report scales through cognitive interviews based on Tourangeau question and answer framework: A practical work on the nursing talent Identification scale.
[36] A. MacFadyen and W. Amanda, (2023). Cognitive Interview Evaluation of Questions on Caregiving,https://wwwn.cdc.gov/qbank/report/MacFadyen_2024_NCHS_Caregiving.pdf
[37] G. Brancato et al., (2006). Handbook of Recommended Practices for Questionnarie Development and Testing in European Statistical Systems European Commission Grant Agreement, Eur. Comm. Grat Agreem. http://epp.eurostat.ec.europaipv6.eu/portal/page/portal/research_methodology/documents/Handbook_questionnaire_development_2006.pdf
[38] E. Sandri et al., (2024). Development and psychometric testing of the nutritional and social health habits scale (NutSo-HH): A methodological review of existing tools, MethodsX, p. 102768.
[39] J. W. Creswell and J. D. Creswell, (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
[40] G. B. Willis and R. A. Anthony, (2013). What Do Our Respondents Think We’re Asking? Using Cognitive Interviewing to Improve Medical Education Surveys, J. Grad. Med. Educ., vol. 5(3), 353–356, doi: 10.4300/jgme-d-13-00154.1.
[41] D. Kwak, K.-S. C. Blair, and D. Russo, (2024). Development of the Values-Centered Assessment Tool (VCAT) to inform culturally responsive behavioral services, Behav. Anal. Pract., 1–19.
[42] G. B. Willis, (2005). Cognitive interviewing: A tool for improving questionnaire design. sage publications.
[43] B. Mathews et al., (2023). Adaptation and validation of the Juvenile Victimization Questionnaire-R2 for a national study of child maltreatment in Australia, Child Abuse Negl., vol. 139, 106093.
[44] G. B. Willis, (1994). Cognitive interviewing and questionnaire design: A training manual. US Department of Health and Human Services, Centers for Disease Control and ….
[45] M. P. Jolles et al., (2024). Development and validation of a pragmatic measure of cocreation in research engagement: a study protocol, BMJ Open, vol. 14(12), p. e091966.
[46] J. A. Garner, G. V Proaño, K. Kelley, J. C. Banna, N. J. Emenaker, and K. Sauer, (2021). Revising the Academy’s Research Priorities: Methods of the Research Priorities and Strategies Development Task Force, 2017-2019, J. Acad. Nutr. Diet., vol. 121(11), 2275–2286.
[47] P. Haggar, E. Ampatzi, D. Potoglou, and M. Schweiker, (2022). Information sharing preferences within buildings: Benefits of cognitive interviewing for enhancing a discrete choice experiment, Energy Build., vol. 258, 111786.
[48] K. Barale, M. C. Aragón, K. Yerxa, G. Auld, and A. Hess, (2022). Development of Reliable and Valid Questions to Assess Food Resource Management Behaviors in Adults With Limited Income, J. Nutr. Educ. Behav., vol. 54(4), 346–358.
[49] M. M. Khan, (2024). Optimizing Web Surveys in Research: Methodological Considerations and Validity Aspects, Int. J. Res. Sci. Innov., vol. 11(4), 75–105.
[50] W. C. John, (2017). All Are Equal , But Some Are More Equal Than Others, J. Futur. Stud., vol. 23 1–9, doi: 10.6531/JFS.201812.
[51] M. Saunders, P. Lewis, and A. Thornhill, Research Methods for Business Students. Pearson Education, https://books.google.iq/books?id=zoy1EAAAQBAJ
[52] V. Weerakkody, R. El-Haddadeh, F. Al-Sobhi, M. A. Shareef, and Y. K. Dwivedi, (2013). Examining the influence of intermediaries in facilitating e-government adoption: An empirical investigation, Int. J. Inf. Manage., vol. 33(5), 716–725.
[53] Jim E. Helm, (2015). Internet e-Voting : How Technology Acceptance and the Digital Divide Influence Senior Citizen Intention to Use a New Voting Technology.
[54] I. K. Mensah, (2019). Factors Influencing the Intention of University Students to Adopt and Use E-Government Services: An Empirical Evidence in China, SAGE Open, vol. 9(2), doi: 10.1177/2158244019855823.
[55] I. K. Mensah and S. Adams, (2019). A Comparative Analysis of the Impact of Political Trust on the Adoption of E-Government Services, Int. J. Public Adm., vol. 43(08), 682–696, doi: 10.1080/01900692.2019.1645687.
[56] Y. K. Dwivedi, N. P. Rana, A. Jeyaraj, M. Clement, and M. D. Williams, (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model, Inf. Syst. Front., vol. 21(3). 719–734, doi: 10.1007/s10796-017-9774-y.
[57] A. A. Rabaa’i, (2018). The use of UTAUT to investigate the adoption of E-government in Jordan: A cultural perspective, Int. J. Bus. Inf. Syst., vol. 24(3), 285–305, doi: 10.1504/IJBIS.2017.10002806.
[58] M. A. Shareef, V. Kumar, U. Kumar, and Y. K. Dwivedi, (2011). E-Government Adoption Model (GAM): Differing service maturity levels, Gov. Inf. Q., vol. 28(1), 17–35, doi: 10.1016/j.giq.2010.05.006.
[59] S. Chauhan, M. Jaiswal, and A. K. Kar, (2018). The acceptance of electronic voting machines in India: A UTAUT approach, Electron. Gov., vol. 14(3), 255–275, doi: 10.1504/EG.2018.093427.
[60] K. P. Gupta, S. Singh, and P. Bhaskar, (2016). Citizen adoption of e-government : a literature review and conceptual framework, Electron. Gov. An Int. J., vol. 12(2), 160–185.
[61] A. Miller and O. Listhaug, (1999). Political Performance and Institutional Trust, Critical Citizens: Global Support for Democratic Government. Oxford University Press, doi: 10.1093/0198295685.003.0010.
[62] E. Ouattara, E. Steenvoorden, and T. van der Meer, (2023). Political Trust as an Evaluation against Normative Benchmarks? A Two-wave Survey Experiment on the Role of Normative Benchmarks in the Evaluative Model of Political Trust, Int. J. Public Opin. Res., vol. 35(2), 1–13, doi: 10.1093/ijpor/edad015.
[63] L. Lambert and D. Newman, (2023). Construct development and validation in three practical steps: Recommendations for reviewers, editors, and authors, Organ. Res. Methods, vol. 26(4), 574–607.
[64] A. Spoto, M. Nucci, E. Prunetti, and M. Vicovaro, (2023). Improving content validity evaluation of assessment instruments through formal content validity analysis., Psychol. Methods.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 International Journal of Computational and Experimental Science and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.
