Colombia is a Latin American country with a very complex social and political context that has not allowed the allocation of sufficient resources to the fields of science, technology, and innovation (STI). This is particularly worrying for the area of health since not enough resources are allocated for public health, research, or education.
The so‐called “Great Survey in Health 2019” was administered online through the SurveyMonkey platform to 5298 people in different regions of the country, representing the public, private, and academic sectors. The questionnaire consisted of 46 open and closed questions, including demographic inquiries. Data analysis involved textual analytics and sentiment analysis.
Overall, 56% of those surveyed were women within the adult life cycle. Most respondents had a postgraduate education. Greater participation was observed in the Oriental, Bogotá, and Antioquia regions, which also concentrate the largest number of resources for STI. Among the main recommendations derived from the results, priorities include investing in research, personalised medicine, promoting the social appropriation of knowledge, addressing mental health, regulating research through a statute, promoting undergraduate research, and establishing recertification exams to pursue excellence.
The results of this original study serve as a fundamental input to promote and strengthen the STI processes in life sciences and health. They serve as a guide to generate public policies and actions that guarantee better health and well‐being for the Colombian population, strategically proposing a clear roadmap for the next 20 years.
Suárez‐Rozo LF, Puerto‐García S, Rodríguez‐Moreno LM, Ramírez‐Moreno J. La crisis del sistema de salud colombiano: una aproximación desde la legitimidad y la regulación. Gerencia Y Políticas De Salud. 2017;16(32):34–50. https://doi.org/10.11144/javeriana.rgps16-32.cssc
Melo‐Becerra LA, Ramos‐Forero JE, Hernández‐Santamaría PO. La educación superior en Colombia: situación actual y análisis de eficiencia. Revista Desarrollo y Sociedad. 2017;78:59–111. https://doi.org/10.13043/dys.78.2
Saenz M, Lewer J. High skilled labor force brain drain and corruption: the case of Colombia. J Econ Insight. 2017;43(2):17–47.
Bethlehem J. Applied survey methods: a statistical perspective. Hoboken: John Wiley & Sons; 2009.
Fink A. The survey handbook. 2nd ed. California: Sage; 2002.
Andrews D, Nonnecke B, Preece J. Electronic survey methodology: a case study in reaching hard‐to‐involve Internet users. Int J Hum Comput Interact. 2003;16(2):185–210. https://doi.org/10.1207/s15327590ijhc1602_04
Bethlehem J, Biffignandi S. Handbook of web surveys. Hoboken: John Wiley & Sons; 2011.
Kehoe C, Pitkow J. Surveying the territory: gvu's five www user surveys. World Wide Web J. 1996;1(3):77–84.
Preece J, Rogers Y, Sharp H. Interaction design: beyond human‐computer interaction. New York: John Wiley & Sons; 2002.
Yun GW, Trumbo CW. Comparative response to a survey executed by post, E‐mail, & web form. J Comput Mediat Commun. 2006;6(1):JCMC613. https://doi.org/10.1111/j.1083-6101.2000.tb00112.x
Kalton G, Schuman H. The effect of the question on survey responses: a review. J R Stat Soc Ser A. 1982;145(1):42–57. https://doi.org/10.2307/2981421
Hernández R, Fernández C, Baptista P. Metodología de la investigación. 6th ed. México D.F.: McGraw‐Hill; 2014.
Atkinson R, Flint J. Accessing hidden and hard‐to‐reach populations: snowball research strategies. Soc Res Updat. 2001; 33:1–4.
World Health Organization. Wellbeing measures in primary health care/The DepCare project. Stockholm: World Health Organization; 1998.
Tufte E. The visual display of quantitative information. 2nd ed. Connecticut: Graphics Press; 2001.
Silge J, Robinson D. Text mining with R. Sebastopol: O'Reilly Media; 2017.
Pang B, Lee L. Opinion mining and sentiment analysis. Foundat Trends® Informat Retr. 2008;2(1–2):1–135. https://doi.org/10.1561/1500000011
Sowa J. Principles of semantic networks: explorations in the representation of knowledge. California: Morgan Kaufmann; 1991.
Thelwall M, Buckley K, Paltoglou G, Cai D, Kappas A. Sentiment strength detection in short informal text. J Am Soc Informat Sci Technol. 2010;61(12):2544–58. https://doi.org/10.1002/asi.21416
Cui W, Wu Y, Liu S, Wei F, Zhou MX, Qu H. Context‐preserving, dynamic word cloud visualization. IEEE Comput Graph Appl. 2010;30(6):42–53. https://doi.org/10.1109/MCG.2010.102
Minsky M. Semantic information processing. Cambridge: MIT Press; 1968.
García‐Lapresta JL, Martínez‐Panero M. Borda count versus approval voting: a fuzzy approach. Public Choice. 2002;112(1):167–84. https://doi.org/10.1023/A:1015609200117
Dummett M. The Borda count and agenda manipulation. Soc Choice Welfare. 1998;15(2):289–96. https://doi.org/10.1007/s003550050105
Gutiérrez‐Lesmes OA, Loboa‐Rodríguez NJ, Martínez‐Torres J. Prevalencia del Síndrome de burnout en profesionales de enfermería de la Orinoquia colombiana, 2016. Universidad y Salud. 2017;20(1):37. https://doi.org/10.22267/rus.182001.107
Eslava‐Schmalbach J, Garzó‐Orjuela N, Martínez N, Gonzalez‐Gordon L, Rosero E, Gómez‐Restrepo C. Prevalence and factors associated with burnout syndrome in Colombian anesthesiologists. Int J Prev Med. 2020;11:5. https://doi.org/10.4103/ijpvm.IJPVM_150_18
Marrugo B, Alberto E. Prevalencia del síndrome de burnout en trabajadores de un hospital público colombiano. Medisan. 2017;21(11):3172–9.
Bedoya E, Manrique E, Arrazola A. Burnout syndrome in a departmental hospital in Colombia. Artech J Eff Res Eng Technol. 2020;1(2):42–9.
De las salas R, Díaz Agudelo D, Serrano Meriño DV, Ortega Pérez S, Tuesca Molina R, Gutiérrez López C. Síndrome de burnout en el personal de enfermería en hospitales del departamento del Atlántico. Revista de Salud Pública. 2021;23(6):1–8. https://doi.org/10.15446/rsap.v23n6.97141
Muñoz‐Cerón JF, Gallo‐Eugenio LM, Figueroa Vargas DA. Síndrome de burnout en los neurólogos colombianos: prevalência y factores asociados. Acta Neurológica Colombiana. 2021;37(2):63–8. https://doi.org/10.22379/24224022368
Jácome SJ, Villaquiran‐Hurtado AF, García CP, Duque IL. Prevalencia del síndrome de burnout en residentes de especialidades médicas. Revista Cuidarte. 2018;10(1):e543. https://doi.org/10.15649/cuidarte.v10i1.543
Santomauro DF, Mantilla Herrera AM, Shadid J, Zheng P, Ashbaugh C, Pigott DM, et al. Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID‐19 pandemic. The Lancet. 2021;398(10312):1700–12. https://doi.org/10.1016/S0140-6736(21)02143-7
Xie Y, Xu E, Al‐Aly Z. Risks of mental health outcomes in people with covid‐19: cohort study. BMJ. 2022;376:e068993. https://doi.org/10.1136/bmj-2021-068993
Tausch A, E Souza RO, Viciana CM, Cayetano C, Barbosa J, Hennis AJ. Strengthening mental health responses to COVID‐19 in the Americas: a health policy analysis and recommendations. Lancet Reg Health Am. 2022;5:100118. https://doi.org/10.1016/j.lana.2021.100118