Resumen
Objetivo: Este estudio desarrolló y evaluó la aplicación JOIA®, analizando su impacto en la autoconciencia y prevención en salud, así como su usabilidad, seguridad y privacidad en el sistema de salud pública. Métodos: El estudio se llevó a cabo en dos etapas: 1) desarrollo de JOIA® (para Android e iOS); 2) estudio de intervención antes y después, realizado en un hospital universitario público en el sur de Brasil, con 100 pacientes mayores de 50 años. Se evaluaron la usabilidad (System Usability Scale - SUS) y la conformidad con la Ley General de Protección de Datos (LGPD). Resultados: El 90% de los pacientes descargaron y utilizaron la aplicación, el 95% la consideró útil y el 93% mostró interés en seguir usándola. La autoconciencia aumentó cinco veces, la satisfacción con la salud 32 veces, y el reconocimiento de la prevención 3,6 veces. Conclusión: La aplicación JOIA® facilitó la comunicación entre pacientes y profesionales de la salud, garantizando seguridad conforme a la LGPD. El 68% calificó la usabilidad de intermedia a excelente, señalando áreas de mejora en la interfaz y en el soporte al usuario. La aplicación demostró ser eficaz para la participación y prevención en salud, con potencial para optimizar el sistema público y reducir costos.
Referencias
AANDERSON K, et al. Mobile Health Apps to Facilitate Self-Care: A Qualitative Study of User Experiences. PLoS One. 2016; 11(5): 156164.
ABRAHAM C, et al. The Need for a Personalized. Core digital resource to facilitate health self-management. Prev Med. 2023; 173: 107569.
AGHER D, et al. Encouraging Behavior Changes and Preventing Cardiovascular Diseases Using the Prevent Connect Mobile Health App: Conception and Evaluation of App Quality. J Med Internet Res. 2022; 24(1): 25384.
ARGAWAL S, et al. WHO mHealth Technical Evidence Review Group. Guidelines for reporting of health interventions using mobile phones: mobile health (mHealth) evidence reporting and assessment (mERA) checklist. BMJ. 2016; 352: 1174.
BJARNADÓTTIR MV, et al. Health Care Usage During the COVID-19 Pandemic and the Adoption of Telemedicine: Retrospective Study of Chronic Disease Cohorts. J Med Internet Res. 2024; 26: 54991.
BORRELL-CARRIÓ F e EPSTEIN RM. Preventing Errors in Clinical Practice: A Call for Self-Awareness. Ann Fam Med. 2004; 2(4): 310-6.
BRASIL. Lei n° 13.709, de 14 de agosto de 2018. Presidência da República. Disponível em: https ://www.planalto.gov.br/ccivil_03/_ato2015-2018/2018/lei/l13709.htm. Acessado em: 22 de nove mbro de 2024.
BROOK J. SUS - A quick and dirty usability scale. In: Jordan PW, Thomas B, Weerdmeester BA, McClelland IL, editors. Usability Evaluation in Industry. London: Taylor & Francis; 1996; 189-94.
CUNHA AS, et al. Facilitators of and Barriers to Accessing Hospital Medical Specialty Telemedicine Consultations During the COVID-19 Pandemic: Systematic Review. J Med Internet Res. 2023; 25: 44188.
DENIZ-GARCIA A, et al. Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges. J Med Internet Res. 2023; 25: 44030.
HALL PA, et al. Neuroimaging, Neuromodulation, and Population Health: The Neuroscience of Chronic Disease Prevention. Ann N Y Acad Sci. 2018; 1428(1): 240-56.
KIRSHENBAUM E, et al. Telemedicine in Urology: The Socioeconomic Impact. Urol Clin North Am. 2021; 48(2): 215-22.
MACKINNON GE e BRITTAIN EL. Mobile Health Technologies in Cardiopulmonary Disease. Chest. 2020; 157(3): 654-64.
MARTINEZ-MARTIN P, et al. Measurement of Nonmotor Symptoms in Clinical Practice. Int Rev Neurobiol. 2017; 133: 291-345.
MIHALJCIC T, et al. Self-Awareness of Falls Risk Among Elderly Patients: Characterizing Awareness Deficits and Exploring Associated Factors. Arch Phys Med Rehabil. 2015; 96(12): 2145-52.
OGDEN LL, et al. Clinical Preventive Services for Older Adults: The Interface Between Personal Health Care and Public Health Services. Am J Public Health. 2012; 102(3): 419-25.
OLIVEIRA LMR, et al Tecnologia mHealth na prevenção e no controle de obesidade na perspectiva do letramento em saúde: Lisa Obesidade. Saúde Debate. 2018; 42: 714-23.
PATAIL K, et al What Are the Perceptions and Experiences of Adults Using Mobile Applications for Self-Management in Diabetes? A Systematic Review. BMJ Open. 2025; 15(1): 86671.
PETERSON AC, et al. Evaluating the 8‐item overactive bladder questionnaire (OAB‐v8) using item response theory. Neurourol Urodyn. 2018; 37: 1095-1100.
TAHA AR, et al. The Integration of mHealth Technologies in Telemedicine During the COVID-19 Era: A Cross-Sectional Study. PLoS One. 2022; 17(2): 264436.
VARMA N, et al. HRS/EHRA/APHRS/LAHRS/ACC/AHA Worldwide Practice Update for Telehealth and Arrhythmia Monitoring During and After a Pandemic. J Am Coll Cardiol. 2020; 76(11): 1363-74.
VICENTE MA, et al. Patient Engagement Using Telemedicine in Primary Care During COVID-19 Pandemic: A Trial Study. Int J Environ Res Public Health. 2022; 19(22): 14682.
VO V, et al. Patients' Perceptions of mHealth Apps: Meta-Ethnographic Review of Qualitative Studies. JMIR Mhealth Uhealth. 2019; 7(7): 13817.
WAALEN J. Mobile Health and Preventive Medicine. Med Clin North Am. 2023; 107(6): 1097-1108.
WANG H, et al. The Association of Mobile Health Applications With Self-Management Behaviors Among Adults With Chronic Conditions in the United States. Int J Environ Res Public Health. 2021; 18(19): 10351.
