Development and validation of a questionnaire to assess patient satisfaction with digital consultations among individuals with type 2 diabetes
Main Article Content
Keywords
Type 2 Diabetes, Telehealth, Patient Satisfaction, Surveys and Questionnaires
Abstract
Introduction: Digital Consultation was implemented at the Mexican Social Security Institute (IMSS) as a strategy to improve remote medical care. This service has been extended to the care of patients with diabetes. It is characterized by interviewing the patient remotely without the possibility of performing a physical examination, which could impact their satisfaction with the medical care received. However, there is no validated instrument to assess satisfaction with this modality.
Objective: To develop and validate a questionnaire to assess the satisfaction of patients with type 2 diabetes with the Digital Consultation program.
Materials and Methods: A validation study was conducted. One hundred participants diagnosed with type 2 diabetes who received care through the Digital Consultation at Family Medicine Unit No. 30 of IMSS were recruited. An initial 20-item questionnaire with Likert-type responses was designed. Reliability was assessed using Cronbach's alpha coefficient, and structural validity through exploratory and confirmatory factor analysis.
Results: The questionnaire proved to be reliable (Cronbach's alpha = 0.95). Exploratory factor analysis identified a unidimensional structure. Confirmatory validation supported the proposed theoretical model.
Conclusions: The questionnaire is valid and reliable for assessing patient satisfaction with digital consultation for diabetes care at IMSS. Its application may contribute to improving the quality of the service.
References
1. Koonin LM, Hoots B, Tsang CA, et al. Trends in the Use of Telehealth During the Emergence of the COVID-19 Pandemic - United States, January-March 2020. MMWR Morb Mortal Wkly Rep. 2020;69(43):1595-9. Disponible en: https://www.doi.org/10.15585/mmwr.mm6943a3
2. Mohammadzadeh N, Rezayi S, Saeedi S. Telemedicine for Patient Management in Remote Areas and Underserved Populations. Disaster Med Public Health Prep. 2022;17:e167. Disponible en: https://www.doi.org/10.1017/dmp.2022.76
3. Wootton R. Telemedicine: a cautious welcome. BMJ. 1996;313(7069):1375-7. Disponible en: https://www.doi.org/10.1136/bmj.313.7069.1375
4. Greiwe J. Telemedicine Lessons Learned During the COVID-19 Pandemic. Curr Allergy Asthma Rep. 2022;22(1):1-5. Disponible en: https://www.doi.org/10.1007/s11882-022-01026-1
5. De La Torre A, Diaz P, Perdomo R. Analysis of the virtual healthcare model in Latin America: a systematic review of current challenges and barriers. Mhealth. 2024;10:20. Disponible en: https://www.doi.org/10.21037/mhealth-23-47
6. Valencia-Rivero K, Muñoz-Pinzón D, Caviativa-Castro Y, et al. Barriers for successful implementation of telemedicine in developing countries: the Colombian case. European Journal of Public Health. 2023;33(Supplement_2):ckad160.1219. Disponible en: https://doi.org/10.1093/eurpub/ckad160.1219
7. Dos Santos AF, Pacheco-López A, Hidalgo ACC, et al. Telehealth Actions to Address COVID-19 in Latin American Countries. Telemed J E Health. 2023;29(11):1650-8. Disponible en: https://www.doi.org/10.1089/tmj.2022.0432
8. Instituto Mexicano del Seguro Social. Informe de labores y programa de actividades 2021-2022. México: IMSS; 2022. Disponible en: https://www.imss.gob.mx/sites/all/statics/pdf/informes/2022/ILPA-21-22.pdf.
9. Instituto Mexicano del Seguro Social. IMSS ha otorgado más de 815 mil consultas digitales para pacientes con COVID-19, enfermedades crónicas y en especialidades. México: IMSS; 2022 Disponible en: http://www.imss.gob.mx/prensa/archivo/202207/352.
10. Instituto Mexicano del Seguro Social. Trabaja IMSS en dos proyectos piloto para mejorar la atención en la consulta de Medicina Familiar. México: IMSS; 2022. Disponible en: https://www.imss.gob.mx/prensa/archivo/202203/133.
11. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021. Diabetes Care. 2021;44(Suppl 1):S15-s33. Disponible en: https://www.doi.org/10.2337/dc21-S002
12. World Health Organiztion. Diabetes. WHO; 2024. Disponible en: https://www.who.int/news-room/fact-sheets/detail/diabetes.
13. International Diabetes Fedration. IDF Diabetes Atlas, 11th Edition. IDF; 2025.
14. Gobierno de México. México construye un sistema de salud universal, gratuito, equitativo y enfocado en la atención primaria. México: Gobierno de México; 2025.
15. Protocolo Nacional de Atención Médica (PRONAM) Diabetes y síndrome metabólico. México: Secretaría de Salud; 2025.
16. Alqahtani M, Alanazi M, Alsuwaidan S. Patient satisfaction with primary health care services in Riyadh city, Saudi Arabia. International Journal of Clinical Medicine. 2023;14(8):366-76.
17. Sebera E, Hagenimana C, Twagirumukiza E. Patient satisfaction survey in a public hospital: Remera Rukoma District Hospital, Rwanda, 2023. BMC Health Serv Res. 2024;24(1):1478. Disponible en: https://www.doi.org/10.1186/s12913-024-11996-9
18. Setia MS. Methodology Series Module 8: Designing Questionnaires and Clinical Record Forms. Indian J Dermatol. 2017;62(2):130-4 https://www.doi.org/10.4103/ijd.IJD_76_17
19. Kyriazos TA. Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology. 2018;9(08):2207 https://www.doi.org/10.4236/psych.2018.98126
20. Güvendir MA, Özkan YÖ. Item removal strategies conducted in exploratory factor analysis: A comparative study. International Journal of Assessment Tools in Education. 2022;9(1):165-80
21. Du Y, Gu Y. The development of evaluation scale of the patient satisfaction with telemedicine: a systematic review. BMC Med Inform Decis Mak. 2024;24(1):31. Disponible en: https://www.doi.org/10.1186/s12911-024-02436-z
22. Cronbach LJ. Coefficient alpha and the internal structure of tests. psychometrika. 1951;16(3):297-334
23. Boyle GJ. Does item homogeneity indicate internal consistency or item redundancy in psychometric scales? Personality and Individual Differences. 1991;12(3):291-4. Disponible en: https://doi.org/10.1016/0191-8869(91)90115-R
24. Cao C, Kim ES, Chen YH, etal. Examining the Impact of and Sensitivity of Fit Indices to Omitting Covariates Interaction Effect in Multilevel Multiple-Indicator Multiple-Cause Models. Educ Psychol Meas. 2021;81(5):817-46. Disponible en: https://www.doi.org/10.1177/0013164421992407
25. Gaudine A, Parsons K, Smith-Young J. Older Adults’ Experiences with Remote Care for Specialized Health Service During the COVID-19 Pandemic: A Descriptive Qualitative Study. Canadian Journal on Aging / La Revue canadienne du vieillissement. 2024;43(2):257-65. Disponible en: https://www.doi.org/10.1017/S0714980823000636
26. Bertolazzi A, Quaglia V, Bongelli R. Barriers and facilitators to health technology adoption by older adults with chronic diseases: an integrative systematic review. BMC public health. 2024;24(1):506.
27. Andrade C. The Inconvenient Truth About Convenience and Purposive Samples. Indian J Psychol Med. 2021;43(1):86-8.
28. Streiner DL, Norman GR, Cairney J. Health measurement scales: a practical guide to their development and use: Oxford University Press; 2024.
