Design and face and content validity of a Spanish-language questionnaire on knowledge, perceptions, and practices regarding artificial intelligence among orthodontic students
DOI:
https://doi.org/10.20453/reh.v36i3.7957Keywords:
artificial intelligence, orthodontics, dental students, surveys and questionnaires, validation studyAbstract
Objective: To design and evaluate the face and content validity of a Spanish-language instrument intended to assess knowledge, perceptions, and practices regarding artificial intelligence among orthodontic students. Materials and methods: An exploratory study using quantitative and qualitative methods was conducted in four phases: 1) literature search; 2) design of the initial questionnaire by an expert panel; 3) face and content validity through expert review and calculation of validity indices (Content Validity Index, Content Validity Ratio, and Content Validity Coefficient); and 4) pilot testing in the target population (semantic comprehension, test-retest reliability, and focus group). Results: The literature review allowed the design of an initial questionnaire of 24 items, which was modified to a final version after peer review, being divided into three dimensions: knowledge (n = 7), perceptions (n = 11) and practices (n = 6). The values of the validity indicators exceeded the recommended cut-off values. In the reliability assessment (n = 10), the observed agreement (Po) had a median of 0.70 (IQR = 0.60–0.80), and Gwet's AC1 coefficient had a median of 0.58 (IQR = 0.45–0.65). These results should be considered exploratory because of the small sample size. Conclusions: This study enabled the design and content validation of an instrument to assess knowledge, perceptions, and practices regarding artificial intelligence among orthodontic students. The instrument showed high acceptability among experts and favorable preliminary findings that require confirmation in future studies with larger samples and comprehensive psychometric analyses.
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References
Real Academia Española. Diccionario de la lengua española. 23.ª ed. Madrid: RAE; 2026.
Khalifa M, Albadawy M. Using artificial intelligence in academic writing and research: an essential productivity tool. Comput Methods Programs Biomed Update. 2024;5:100145. doi:10.1016/j.cmpbup.2024.100145
Celik SU. Integrating artificial intelligence into scientific writing: a narrative review for clinical and surgical researchers. Am J Surg. 2025;250:116657. doi:10.1016/j.amjsurg.2025.116657
Organización de Estados Iberoamericanos. Inteligencia artificial en la educación: desarrollo y aplicaciones [Internet]. Madrid; 2024. Disponible en: https://oei.int/wp-content/uploads/2025/04/desarrollo-ia-educacion-7.pdf
Fatima A, Shafi I, Afzal H, et al. Advancements in dentistry with artificial intelligence: current clinical applications and future perspectives. Healthcare. 2022;10(11):2188. doi:10.3390/healthcare10112188
Araidy S, Batshon G, Mirochnik R. Artificial intelligence applications in dentistry: a systematic review. Oral. 2025;5(4):90. doi:10.3390/oral5040090
Saikia A, Kvist T, Fawzy A, et al. Artificial intelligence in dentistry: an overview of systematic reviews and meta-analysis. Evid Based Dent. 2025;26:180. doi:10.1038/s41432-025-01190-z
Oliveira PH, Gonçalves JR, Gandini LG, et al. Clinical decisions in Orthodontics using x-ray-based images and artificial intelligence approaches: a scoping review. Dental Press J Orthod. 2026;30(4):e2524219. doi:10.1590/2177-6709.30.4.e2524219.oar
Nordblom NF, Büttner M, Schwendicke F. Artificial intelligence in orthodontics: critical review. J Dent Res. 2024;103(6):577-84. doi:10.1177/00220345241235606
Dipalma G, Inchingolo AD, Inchingolo AM, et al. Artificial intelligence and its clinical applications in orthodontics: a systematic review. Diagnostics. 2023;13(24):3677. doi:10.3390/diagnostics13243677
Morales-Bravo R, Pisón-Santana L, Hidalgo-Rivas A, et al. Estado del arte de inteligencia artificial en ortodoncia: revisión narrativa. Av Odontoestomatol. 2022;38(4):156-63. doi:10.4321/s0213-12852022000400005
Mörch CM, Atsu S, Cai W, et al. Artificial intelligence and ethics in dentistry: a scoping review. J Dent Res. 2021;100(13):1452-60. doi:10.1177/00220345211013808
Rokhshad R, Ducret M, Chaurasia A, et al. Ethical considerations on artificial intelligence in dentistry: a framework and checklist. J Dent. 2023;135:104593. doi:10.1016/j.jdent.2023.104593
Dashti M, Londono J, Ghasemi S, et al. Attitudes, knowledge, and perceptions of dentists and dental students toward artificial intelligence: a systematic review. J Taibah Univ Med Sci. 2024;19(2):327-37. doi:10.1016/j.jtumed.2023.12.010
Aboalshamat KT. Perception and utilization of artificial intelligence (AI) among dental professionals in Saudi Arabia. Open Dent J. 2022;16(Suppl 4):e187421062208110. doi:10.2174/18742106-v16-e2208110
AlAhmari F. Perspectives of Saudi dental student on the impact of artificial intelligence in dentistry: a cross-sectional study. J Res Med Dent Sci [Internet]. 2022;10(2):33-45. Disponible en: https://www.jrmds.in/articles/perspectives-of-saudi-dental-student-on-the-impact-of-artificial-intelligence-in-dentistry-a-crosssectional-study-89948.html
Jethlia A, Lunkad H, Muaini SA, et al. Knowledge, attitudes and perceptions of intern and dental practioners in Saudi Arabia towards artificial intelligence. J Pharm Negat Results. 2022;13:1161-7. Disponible en: doi:10.47750/pnr.2022.13.S09.137
Khanagar S, Alkathiri M, Alhamlan R, et al. Knowledge, attitudes, and perceptions of dental students towards artificial intelligence in Riyadh, Saudi Arabia. Med Sci [Internet]. 2021;25(114):1857-67. Disponible en: https://www.discoveryjournals.org/medicalscience/current_issue/v25/n114/A8.htm
Asmatahasin M, Pratap K, Padma TM, et al. Attitude and perception of dental students towards artificial intelligence. Indian J Basic Appl Med Res. 2021;10(3):305-14. doi:10.36848/IJBAMR/2020/29215.557818
Seram T, Batra M, Gijwani D, et al. Attitude and perception of dental students towards artificial intelligence. Univ J Dent Sci. 2021;7(3):77-81. doi:10.21276/ujds.2021.7.3.13
Sur J, Bose S, Khan F, et al. Knowledge, attitudes, and perceptions regarding the future of artificial intelligence in oral radiology in India: a survey. Imaging Sci Dent. 2020;50(3):193-8. doi:10.5624/isd.2020.50.3.193
Thulasi MS, Sowjanya B, Sreenivasulu K, et al. Knowledge attitude and practices of dental students and dental practitioners towards artificial intelligence. Int J Intell Syst Appl Eng [Internet]. 2022;10(1s):248-53. Disponible en: https://ijisae.org/index.php/IJISAE/article/view/2288
Vamshi V, Sadeep H. Assessment of knowledge and awareness of artificial intelligence and its uses in dentistry among dental students. J Pharm Negat Results. 2022;13(special issue 4):1304-9. doi:10.47750/pnr.2022.13.S04.155
Keser G, Pekiner FM. Attitudes, perceptions and knowledge regarding the future of artificial intelligence in oral radiology among a group of dental students in Turkey: a survey. Clin Exp Health Sci. 2021;11(4):637-41. doi:10.33808/clinexphealthsci.928246
Yüzbaşıoğlu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ. 2021;85(1):60-8. doi:10.1002/jdd.12385
Akhtar H, Faheem S, Qasim R, et al. Assessment of knowledge and perceptions of artificial intelligence among dental students of Karachi, Pakistan: a multi-center survey. Pakistan Oral Dental J [Internet]. 2022;42(4):193-9. Disponible en: https://www.podj.com.pk/index.php/podj/article/view/711
Karan-Romero M, Salazar-Gamarra RE, Leon-Rios XA. Evaluation of attitudes and perceptions in students about the use of artificial intelligence in dentistry. Dent J. 2023;11(5):125. doi:10.3390/dj11050125
Elchaghaby M, Wahby R. Knowledge, attitudes, and perceptions of a group of Egyptian dental students toward artificial intelligence: a cross-sectional study. BMC Oral Health. 2025;25:11. doi:10.1186/s12903-024-05282-7
Ozbey F, Yasa Y. The relationships of personality traits on perceptions and attitudes of dentistry students towards AI. BMC Med Educ. 2025;25:26. doi:10.1186/s12909-024-06630-5
Mengi A, Singh RP, Mengi N, et al. A questionnaire study regarding knowledge, attitude and usage of artificial intelligence and machine learning by the orthodontic fraternity of Northern India. J Oral Biol Craniofac Res. 2024;14(5):500-6. doi:10.1016/j.jobcr.2024.06.004
Gupta S, Verma S, Chauhan AK, et al. Knowledge, attitude, and perception of orthodontic students, and orthodontists regarding role of artificial intelligence in field of orthodontics-An online cross-sectional survey. J World Fed Orthod. 2025;14(1):3-11. doi:10.1016/j.ejwf.2024.08.002
Arias-Mendoza MJ, Agudelo-Suárez AA, Ochoa-Acosta EM, et al. Development and validation of a Spanish-language questionnaire to assess mothers’ knowledge and practices regarding their children’s oral health. Rev Cient Odontol. 2026;14(3):e299. doi:10.21142/2523-2754-1403-2026-299
Artino AR Jr., La Rochelle JS, Dezee KJ, et al. Developing questionnaires for educational research: AMEE Guide No. 87. Med Teach. 2014;36(6):463-74. doi:10.3109/0142159X.2014.889814
Rojas Z, Torres G, Garavito EL. Construcción y validación de instrumentos de medición en el ámbito de la salud: revisión de literatura. Odontol Pediat. 2022;21(1):46-52. doi:10.33738/spo.v21i1.206
Kalaimani G, Sivapathasundharam B, Chockalingam RM, et al. Evaluation of knowledge, attitude, and practice (kap) of artificial intelligence among dentists and dental students: a cross-sectional online survey. Cureus. 2023;15(9):e44656. doi:10.7759/cureus.44656
BIREME. Descriptores en Ciencias de la Salud (DeCS) [Internet]. BIREME. Disponible en: https://decs.bvsalud.org/es/
Lynn MR. Determination and quantification of content validity. Nurs Res. 1986;35(6):382-5. doi:10.1097/00006199-198611000-00017
Polit DF, Beck CT. The content validity index: Are you sure you know what's being reported? Critique and recommendations. Res Nurs Health. 2006;29(5):489-97. doi:10.1002/nur.20147
Lawshe CH. A quantitative approach to content validity. Pers Psychol. 1975;28(4):563-75. doi:10.1111/j.1744-6570.1975.tb01393.x
Wilson FR, Pan W, Schumsky DA. Recalculation of the critical values for lawshe’s content validity ratio. Meas Evaluation Couns Dev. 2012;45(3):197-210. doi:10.1177/0748175612440286
Hernández-Nieto RA. Contribuciones al análisis estadístico. Mérida: Universidad de Los Andes-Instituto de Estudios en Informática; 2002.
Maldonado-Suárez N, Santoyo-Telles F. Validez de contenido por juicio de expertos: Integración cuantitativa y cualitativa en la construcción de instrumentos de medición. REIRE. 2024;17(2). doi:10.1344/reire.46238
Gwet KL. Computing inter-rater reliability and its variance in the presence of high agreement. Br J Math Stat Psychol. 2008;61(1):29-48. doi:10.1348/000711006X126600
Prinsen CA, Mokkink LB, Bouter LM, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1147-57. doi:10.1007/s11136-018-1798-3
Mokkink LB, de Vet H, Diemeer S, et al. Sample size recommendations for studies on reliability and measurement error: an online application based on simulation studies. Health Serv Outcomes Res Method. 2023;23(3):241-65. doi:10.1007/s10742-022-00293-9
World Medical Association. World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191-4. doi:10.1001/jama.2013.281053
Council for International Organizations of Medical Sciences. International Ethical Guidelines for Health-related Research Involving Humans. Ginebra, Switzerland: CIOMS; WHO; 2016. doi:10.56759/rgxl7405
Resolución n.° 8430 de 1993 (4 de octubre), por la cual se establecen las normas científicas, técnicas y administrativas para la investigación en salud [Internet]. Bogotá (Colombia): Ministerio de Salud y Protección Social; 1993. Disponible en: https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/de/dij/resolucion-8430-DE-1993.PDF
Andrade C, Menon V, Ameen S, et al. Designing and conducting knowledge, attitude, and practice surveys in psychiatry: practical guidance. Indian J Psychol Med. 2020;42(5):478-81. doi:10.1177/0253717620946111
Bisdas S, Topriceanu CC, Zakrzewska Z, et al. Artificial intelligence in medicine: a multinational multi-center survey on the medical and dental students' perception. Front Public Health. 2021;9:795284. doi:10.3389/fpubh.2021.795284
Rajeh MT, Sembawa SN, Nassar AA, et al. Social media as a learning tool: dental students' perspectives. J Dent Educ. 2021;85(4):513-20. doi:10.1002/jdd.12478
Uma E, Nieminen P, Mani SA, et al. Social media usage among dental undergraduate students-a comparative study. Healthcare. 2021;9(11):1408. doi:10.3390/healthcare9111408
Abdullah S, Hasan SR, Asim MA, et al. Exploring dental faculty awareness, knowledge, and attitudes toward AI integration in education and practice: a mixed-method study. BMC Med Educ. 2025;25(1):691. doi:10.1186/s12909-025-07259-8
Priyadarshini S, Sharma S, Arish, et al. Determining the factors associated with knowledge and practice regarding artificial intelligence in dentistry among the dental professionals of North India. Asian J Converg Technol. 2022;8(1):41-6. doi:10.33130/AJCT.2022v08i01.007
Alam ST, Bhanotia D, Trehan M, et al. Assessing the AI acumen: a study on the knowledge, attitude and behaviour of dental students towards artificial intelligence. J Contemp Orthod. 2024;8(3):290-3. doi:10.18231/j.jco.2024.043
Baseer S, Jamil B, Khan SA, et al. Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey. BMC Med Educ. 2025;25(1):632. doi:10.1186/s12909-025-06911-7
Boateng GO, Neilands TB, Frongillo EA, et al. Best Practices for developing and validating scales for health, social, and behavioral research: a primer. Front Public Health. 2018;6:149. doi:10.3389/fpubh.2018.00149
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Copyright (c) 2026 Jimena Castrillón-Arbeláez, Ricardo Lopera-Naranjo, Diana M. Barbosa-Liz, Ligia I. Ramírez-Restrepo, Oscar Zapata-Noreña, Andrés A. Agudelo-Suárez
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