Content validation of a questionnaire on healthcare personnel's perceptions of technologies
DOI:
https://doi.org/10.15649/cuidarte.4145Keywords:
Digital Technology, Health Personnel, Health Knowledge, Attitudes, Practice, Surveys and Questionnaires, Validation StudyAbstract
Highlights
- Various institutions, including the WHO, are driving the adoption of innovative health technologies to improve medical care quality worldwide.
- Effective integration of technologies in healthcare organizations requires acceptance and positive attitudes from healthcare professionals.
- Expert judgment is useful in identifying potential errors, ambiguities, or biases in the instrument that could affect the validity and reliability of the results.
- Aiken's V is one of the main coefficients used in content validation of instruments such as questionnaires.
Introduction: Across the world, multiple institutions in the health sector actively promote the adoption and expansion of health technology innovations, driven by their potential benefits in improving medical care quality. The successful integration of health technologies into healthcare settings brings significant changes to work activities and depends, in part, on their acceptance and appropriation by healthcare personnel. Objective: To determine the content validity of a questionnaire adapted to assess perceptions and attitudes toward health technologies. Materials and Methods: Content validity was assessed through expert judgment using the model proposed by Escobar and Cuervo (2008). A 28-item questionnaire was adapted to assess health personnel's perceptions and attitudes toward technologies, and content validity was determined using Aiken's V coefficient. The Brennan and Prediger coefficient was used to assess agreement among experts. Results: The Aiken V coefficient was 0.98 (95% CI: 0.88 - 1.00) for the entire instrument. The expert agreement was almost perfect. Discussion: Most of the studies evaluating perceptions and attitudes toward technologies do not include validation through expert judgment before conducting statistical validation. Conclusions: According to the criteria of the consulted experts, the questionnaire's content validity is acceptable for assessing perceptions and attitudes toward health technologies.
How to cite this article: Díaz Rincón Maritza, Arango Franco Paula Constanza, Vergel Torrado Jose Alejandro, Lora Díaz Olga Lucia. Content validation of a questionnaire on healthcare personnel's perceptions of technologies. Revista Cuidarte. 2025;16(1):e4145. https://doi.org/10.15649/cuidarte.4145
References
Lizcano-Jaramillo PA, Camacho-Cogollo JE. Evaluación de Tecnologías en Salud: Un Enfoque Hospitalario para la Incorporación de Dispositivos Médicos. Rev Mex Ing Bioméd. 2019;40(3). https://doi.org/10.17488/rmib.40.3.10
Consejo Ejecutivo 118. Tecnologías sanitarias esenciales: informe de la Secretaría. 2006. Consulta: Mayo 24, 2024. Disponible en: https://iris.who.int/handle/10665/24102
Organización Panamericana de la Salud. La eSalud en la Región de las Américas: derribando las barreras a la implementación. Resultados de la Tercera Encuesta Global de eSalud de la Organización Mundial de la Salud. 2016. Consulta: Mayo 24, 2024. Disponible en: https://iris.paho.org/handle/10665.2/31287
OECD/The World Bank. Tecnologías médicas. In: Panorama de la Salud: Latinoamérica y el Caribe. OECD Publishing, Paris; 2020. Disponible en: https://doi.org/10.1787/924f7f5a-es
HolonIQ, Lab IDB. Innovación y tecnología en salud en América Latina y el Caribe. IDB Publ. 2024. Disponible en: http://dx.doi.org/10.18235/0012923
Borges do Nascimento IJB, Abdulazeem HM, Vasanthan LT, Martinez EZ, Zucoloto ML, Østengaard L, et al. The global effect of digital health technologies on health workers’ competencies and health workplace: an umbrella review of systematic reviews and lexical-based and sentence-based meta-analysis. Lancet Digit Health. 2023;5(8):e534–44. https://doi.org/10.1016/S2589-7500(23)00092-4
Krasonikolakis I, Tsarbopoulos M, Eng TY. Are incumbent banks bygones in the face of digital transformation? J Gen Manag. 2020;46(1):60–9. https://doi.org/10.1177/0306307020937883
Borges do Nascimento IJ, Abdulazeem H, Vasanthan LT, Martinez EZ, Zucoloto ML, Østengaard L, et al. Barriers and facilitators to utilizing digital health technologies by healthcare professionals. NPJ Digit Med. 2023;6(1):161. https://doi.org/10.1038/s41746-023-00899-4
Chang H, Choi JY, Shim J, Kim M, Choi M. Benefits of Information Technology in Healthcare: Artificial Intelligence, Internet of Things, and Personal Health Records. Healthc Inform Res. 2023;29(4):323–333. https://doi.org/10.4258/hir.2023.29.4.323
Valdiviezo GT, Alegre LR, Ayala DM, Padilla R del PL. Transformación digital en América Latina: una revisión sistemática. Rev Venez Gerenc. 2022 Sep 23;27(100):1519–36. https://doi.org/10.52080/rvgluz.27.100.15
Schoville RR, Titler MG. Guiding healthcare technology implementation: a new integrated technology implementation model. Comput Inform Nurs CIN. 2015;33(3):99–107. https://doi.org/10.1097/cin.0000000000000130
Hilty DM, Chan S, Hwang T, Wong A, Bauer AM. Advances in mobile mental health: opportunities and implications for the spectrum of e-mental health services. mHealth. 2017;3:34. https://doi.org/10.21037/mhealth.2017.06.02
Safi S, Thiessen T, Schmailzl KJ. Acceptance and Resistance of New Digital Technologies in Medicine: Qualitative Study. JMIR Res Protoc. 2018;7(12):e11072. https://doi.org/10.2196/11072
Escobar-Pérez J, Cuervo-Martínez Á. Validez de contenido y juicio de expertos: Una aproximación a su utilización. Av En Medición. 2008;6:27–36. https://go.revistacomunicar.com/xjGfFy
Akudjedu TN, Torre S, Khine R, Katsifarakis D, Newman D, Malamateniou C. Knowledge, perceptions, and expectations of Artificial intelligence in radiography practice: A global radiography workforce survey. J Med Imaging Radiat Sci. 2023;54(1):104–16. https://doi.org/10.1016/j.jmir.2022.11.016
Bimerew M, Chipps J. Perceived technology use, attitudes, and barriers among primary care nurses. Health SA SA Gesondheid. 2022;27:1-7. https://doi.org/10.4102/hsag.v27i0.2056
De Leeuw JA, Woltjer H, Kool RB. Identification of Factors Influencing the Adoption of Health Information Technology by Nurses Who Are Digitally Lagging: In-Depth Interview Study. J Med Internet Res. 2020;22(8):e15630. https://doi.org/10.2196/15630
Flores-Mir C, Palmer NG, Northcott HC, Khurshed F, Major PW. Perceptions and Attitudes of Canadian Dentists toward Digital and Electronic Technologies. J Can Dent Assoc. 2006;72(3):243–243. https://www.cda-adc.ca/jcda/vol-72/issue-3/243.pdf
Jarva E, Oikarinen A, Andersson J, Tuomikoski A, Kääriäinen M, Meriläinen M, et al. Healthcare professionals’ perceptions of digital health competence: A qualitative descriptive study. Nurs Open. 2022;9(2):1379–93. https://doi.org/10.1002/nop2.1184
Knop M, Mueller M, Niehaves B. Investigating the Use of Telemedicine for Digitally Mediated Delegation in Team-Based Primary Care: Mixed Methods Study. J Med Internet Res. 2021;23(8):e28151. https://doi.org/10.2196/28151
Ncube B, Mars M, Scott RE. Perceptions and attitudes of patients and healthcare workers towards the use of telemedicine in Botswana: An exploratory study. PLoS ONE. 2023;18(2):e0281754. https://doi.org/10.1371/journal.pone.0281754
Park S, Woo K. Military Doctors’ and Nurses’ Perceptions of Telemedicine and the Factors Affecting Use Intention. Telemed E-Health. 2023;29(9):1412–20. https://pubmed.ncbi.nlm.nih.gov/36695673/
World Health Organization & Stop TB Partnership. Advocacy, communication and social mobilization for TB control: a guide to developing knowledge, attitude and practice surveys. World Health Organization; [Internet] 2008. [Cited: 2024 May 24] Available from: https://iris.who.int/handle/10665/43790
Aiken LR. Three coefficients for analyzing the reliability and validity of ratings. Educ Psychol Meas. 1985;45(1):131–42. https://doi.org/10.1177/0013164485451012
Escurra LME. Cuantificación de la validez de contenido por criterio de jueces. Rev Psicol. 1988;6(1–2):103–11. https://doi.org/10.18800/psico.198801-02.008
Penfield RD, Giacobbi PR. Applying a Score Confidence Interval to Aiken’s Item Content-Relevance Index. Meas Phys Educ Exerc Sci. 2004;8(4):213–25. https://doi.org/10.1207/s15327841mpee0804_3
Soto CM, Segovia JL. Intervalos de confianza asimétricos para el índice la validez de contenido: un programa visual basic para la V de Aiken. An Psicol Ann Psychol. 2009;25(1):169–71. https://revistas.um.es/analesps/article/view/71631
Charter RA. A breakdown of reliability coefficients by test type and reliability method, and the clinical implications of low reliability. J Gen Psychol. 2003;130(3):290–304. https://doi.org/10.1080/00221300309601160
Torres-Malca JR, Vera-Ponce VJ, Zuzunaga-Montoya FE, Talavera JE, Cruz-Vargas JADL. Validez de contenido por juicio de expertos de un instrumento para medir conocimientos, actitudes y prácticas sobre el consumo de sal en la población peruana. Rev Fac Med Humana. 2022;22(2):273–9. http://dx.doi.org/10.25176/rfmh.v22i2.4768
Díaz-Rincón M, Arango-Franco P, Vergel-Torrado J, Lora-Díaz O. Validación de contenido. Harvard Dataverse; 2024. Available from: https://doi.org/10.7910/DVN/RTAN64.
Gwet KL. Testing the Difference of Correlated Agreement Coefficients for Statistical Significance. Educ Psychol Meas. 2016;76(4):609–37. https://doi.org/10.1177/0013164415596420
García MA, Benavente A, López JJ. Análisis comparativo de tres enfoques para evaluar el acuerdo entre observadores. Psicothema Oviedo. 2006;18(3):638–45. https://www.redalyc.org/pdf/727/72718346.pdf
Ministerio de Salud y Protección Social. Resolución 8430 de 1993. Colombia; 1993. Consulta: mayo 24 2024. Disponible en: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/DIJ/RESOLUCION-8430-DE-1993.PDF
Mendoza NIC, de León Castañeda CD, Álvarez CV, León PP, Trejo M del CG, Alba GG, et al. Validez de contenido del cuestionario de Aceptación Tecnológica en Sistemas de Salud en dos países latinoamericanos. Rev Salud Pública. 2023;29(1). https://doi.org/10.31052/1853.1180.v29.n1.38884
Rodríguez S, María A. Diseño y validación de instrumentos de medición. 2014;8(14):19-40. https://www.revistas.udb.edu.sv/ojs/index.php/dl/article/view/166
Beer P, Mulder RH. The Effects of Technological Developments on Work and Their Implications for Continuous Vocational Education and Training: A Systematic Review. Front Psychol. 2020;11:918. https://doi.org/10.3389/fpsyg.2020.00918
Golz C, Peter KA, Müller TJ, Mutschler J, Zwakhalen SMG, Hahn S. Technostress and Digital Competence Among Health Professionals in Swiss Psychiatric Hospitals: Cross-sectional Study. JMIR Ment Health. 2021;8(11):e31408. https://doi.org/10.2196/31408
Holland Brown TM, Bewick M. Digital health education: the need for a digitally ready workforce. Arch Dis Child Educ Pract Ed. 2023 Jun;108(3):214–217. https://doi.org/10.1136/archdischild-2021-322022
Downloads
Published
How to Cite
Issue
Section
Categories
Funding data
Altmetrics
Downloads
License
Copyright (c) 2024 Revista Cuidarte
This work is licensed under a Creative Commons Attribution 4.0 International License.
Journal Cuidarte, scientific publication of open access, is licensed under a Creative Commons Attribution (CC BY-NC), which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Any other form of use such as reproduction, transformation, public communication or distribution, for profit, requires the prior authorization of the University of Santander UDES.
The names and e-mail addresses entered in the Journal Cuidarte will be used exclusively for the purposes stated by this magazine and will not be available for any other purpose or other person.
The articles published in the Journal Cuidarte represent the criteria of their authors and do not necessarily constitute the official opinion of the University of Santander UDES.