Browsing by Author "Escalona, G."
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- ItemArtificial intelligence in laparoscopic simulation: a promising future for large-scale automated evaluations(2023) Belmar, F.; Gaete, M.I.; Escalona, G.; Carnier, M.; Durán, V.; Villagrán, I.; Asbun, D.; Cortés, M.; Neyem, A.; Crovari, F.; Alseidi, A.; Varas Cohen, Julian Emanuel
- ItemInnovations in surgical training: exploring the role of artificial intelligence and large language models (LLM)(2023) Varas Cohen, Julian Emanuel; Coronel, B.V.; Villagrán, I.; Escalona, G.; Hernandez, R.; Schuit, G.; Durán, V.; Lagos-Villaseca, A.; Jarry, C.; Neyem, A.; Achurra, P.
- ItemRemote and asynchronous training network: from a SAGES grant to an eight-country remote laparoscopic simulation training program(2023) Gaete, M.I.; Belmar, F.; Cortés, M.; Alseidi, A.; Asbun, D.; Durán, V.; Escalona, G.; Achurra, P.; Villagrán, I.; Crovari, F.; Pimentel, F.; Varas Cohen, Julian Emanuel
- ItemREMOTE ASYNCHRONOUS FEEDBACK FOR UNSUPERVISED LAPAROSCOPIC TRAINING: THE “LAPP” PLATFORM(2022) Ulloa, G.; Neyem, A.; Escalona, G.; Ortiz, C.; Varas Cohen, Julian Emanuel
- ItemSmartphone Application Guides Laparoscopic Training through Simulation and Reduces the Need for Feedback from Expert Tutors(2019) Quezada, J.; Achurra, P.; Asbun, D.; Polom, K.; Roviello, F.; Erwin, B.; Martin, I.; Escalona, G.; Jarufe, N.; Varas Cohen, Julian Emanuel
- ItemSmartphone application supplements laparoscopic training through simulation by reducing the need for feedback from expert tutors(2019) Quezada, J.; Achurra, P.; Asbun, D.; Polom, K.; Roviello, F.; Buckel, E.; Inzunza, M.; Escalona, G.; Jarufe, N.; Varas Cohen, Julian Emanuel
- ItemThe challenge of medication adherence to reduce cardiovascular risk in primary care: a mixed design multi-center study in underserved populations(2023) Püschel, K.; González, Karla; Varas, J.; Sateler, J.; Aravena, H.; Greig, D.; Escalona, G.; Palominos, M.; Rioseco, A.; Cea, A.; Thompson, B.Background Cardiovascular disease is a leading cause of death in Latin America. Internationally, low medication adherence is associated with 15% to 40% of excess cardiovascular deaths. In Latin America, the magnitude of low medication adherence and the factors associated with it, are not well known, especially among socially vulnerable populations. The aim of this study is to estimate the magnitude and associated factors of low medication adherence in a socially vulnerable population with high cardiovascular risk in Chile. Methods The study is based on a mixed-methods design. It included a multicenter cross-sectional design of a randomly selected clinical population of 900 participants, and a qualitative design based on the analytical framework model, that included patients and health team members, from three primary care clinics in Chile. Results Only 24.6% from the 886 (out of 900) patients who completed the study had “high” medication adherence, 24.9% had “regular,” and 50.4% had “low” adherence. Depression was the main factor associated with regular and low adherence combined (OR: 2.12; 95%CI:1.55-2.89). Confusion and tiredness were identified as barriers for adherence. Main facilitators reported by patients included better understanding of the medications, and availability of reminders. Clearer information and family support were identified by team members as initiators for improving adherence. Conclusion Low medication adherence is highly prevalent among patients with high cardiovascular risk in a low-income population in Chile. Quantitatively, depression was a significant risk factor for regular and low adherence; qualitatively, confusion and tiredness were identified as barriers. Clearer information and family support are identified as potential facilitators.