Uso de las bases de datos científicas en estudiantes de enfermería, factores influyentes
Barra lateral del artículo
Publicado:
jul 22, 2019
Palabras clave:
Bases de datos bibliográficas,
educación en enfermería,
tecnología de la información,
aprendizaje,
Chile,
Contenido principal del artículo
Resumen
Introducción: El Modelo de Aceptación Tecnológica (TAM), ha sido ampliamente utilizado para predecir el uso de bases de datos científicas (BDC). No obstante, es preciso indagar el peso de otras variables identificadas en la revisión de la literatura. Objetivo: Identificar los factores influyentes en la aceptación y uso de las bases de datos científicas por parte de los estudiantes de la carrera de enfermería de una universidad privada.
Método: El estudio tiene un diseño no experimental, transversal de tipo descriptivo y correlacional. Se aplicó un cuestionario a estudiantes de la carrera de Enfermería (Chile). Se realizó un análisis basado en regresión de mínimos cuadrados parciales en SmartPLS.
Resultados: Se corroboran como variables predictoras del uso de BDC a las variables TAM (intención de uso, utilidad y facilidad de uso) y a otras variables externas al modelo (obligatoriedad, las habilidades informacionales y el entrenamiento en tecnologías).
Discusión: La evidencia identifica que una de las principales barreras en el uso de las BDC son las habilidades informacionales y digitales para su utilización.
Conclusiones: Se hace necesario incorporar nuevas metodologías para aumentar la competencia de los estudiantes con el uso de estas bases, para este efecto se consideraron las variables que resultaron predictoras.
Detalles del artículo
Dimensions citation
MÉTRICAS
Citas
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7. Ryan EJ. Undergraduate nursing students’ attitudes and use of research and evidence-based practice-an integrative literature review. J Clin Nurs. 2016; 25(11-12): 1548-56. https://doi.org/10.1111/jocn.13229
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21. Yi-Hao W, Chieh-Feng C, Ka-Wai T, Chun-Yuh Y, Ya-Wen C. Preference of online database access for medical students: A before-and-after survey of evidence-based medicine course. 醫學教育. 2016; 20(3): 176-85. https://doi.org/10.6145/jme201618
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26. Gómez M, Roses S, Farias P. El uso académico de las redes sociales en universitarios. Comunicar. 2012; XIX(38): 131-8. https://doi.org/10.3916/C38-2011-03-04
27. Avdic A, Eklund A. Searching reference databases: What students experience and what teachers believe that students experience. JOLIS. 2010; 42(4): 224-35. https://doi.org/10.1177/0961000610380119
28. Soria KM, Fransen J, Nackerud S. Stacks, serials, search engines, and students’ success: First-year undergraduate students’ library use, academic achievement, and retention. Journal of academic librarianship. 2014; 40(1); 84-91. https://doi.org/10.1016/j.acalib.2013.12.002El
29. Rodis J, Aungst TD, Brown NV, Cui Y, Tam L. Enhancing Pharmacy Student Learning and Perceptions of Medical Apps. JMIR MHealth UHealth. 2016; 4(2): https://doi.org/10.2196/mhealth.4843
30. Soria K, Fransen J,Nackerud S. Beyond Books: The Extended Academic Benefits of Library Use for First-Year College Students. C&RL. 2017; 78(1), 8-22. https://doi.org/10.5860/crl.78.1.8
31. Rawstorne P, Jayasuriya R, Caputi P. Issues in predicting and explaining usage behaviors with the technology acceptance model and the theory of planned behavior when usage is mandatory. ICIS 2000 proceeding. 2000.
32. Landry BJL, Griffeth R, Hartman S. Measuring student perceptions of blackboard using the technology acceptance model. Decis Sci J Innovat Educ. 2006; 4(1): 87-9. https://doi.org/10.1111/j.1540-4609.2006.00103.x
33. Masrom M. Technology acceptance model and E-learning. 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Education. Brunei Darussalam: Universiti Brunei Darussalam; 2007.
34. Ertmer PA, Ottenbreit-Leftwich AT. Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of research on Technology. 2010; 42(3): 255-84. https://bit.ly/2Xu7Urm
35. Ertmer PA, Ottenbreit-Leftwich AT, Sadik O, Sendurur E, Sendurur P. Teacher beliefs and technology integration practices: A critical relationship. Comput Educ. 2012; 59(2): 423-35. https://doi.org/10.1016/j.compedu.2012.02.001
36. Hernández-Sampieri R, Fernández-Collado C, Baptista-Lucio MP. Metodología de la investigación. 6ta ed. México D.F.: McGraw-Hill; 2014. https://bit.ly/2JLPtUM
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38. Barclay D, Higgins C, Thompson R. The Partial Least Squares (PLS) approach to causal modelling: Personal computer adoption and use as an illustration. Ontario: Walter de Guyter; 1995. https://bit.ly/2L8rSla
39. Nunnally JC. Psychometic theory. 2da ed. NewYork: McGraw-Hill series in psychology; 1978.
40. Fornell C, Larcker DF. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J Mark Res. 1981; 18(3): 382-8. http://dx.doi.org/10.2307/3150980
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45. Jen-Her W, Shu-Ching W. What drives mobile commerce? An empirical investigation of the revised technology acceptance model. Information & Management. 2005; 42(5): 719–29. https://doi.org/10.1016/j.im.2004.07.001
46. Adams DA, Nelson RR, Todd PA. Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Q. 1992; 16(2): 227-47. https://doi.org/10.2307/249577
47. Van Raaij EM, Schepers JLL. The acceptance and use of a virtual learning environment in China. Comput Educ. 2008; 50(3); 838-52. https://doi.org/10.1016/j.compedu.2006.09.001
48. Shu-Sheng L, Hsiu-Mei H. An investigation of user attitudes toward search engines as an information retrieval tool. Comput Human; 2003; 19(6); 751-65.
49. Fox LM, Richter JM, White N. Pathways to information literacy. J Nurs Educ.1989; 28(9): 422-425. https://doi.org/10.3928/0148-4834-19891101-09
50. Verhey MP. Information literacy in an undergraduate nursing curriculum: development, implementation, and evaluation. J Nurs Educ. 1999; 38(6): 252-9. https://bit.ly/2XuPq9X
51. Mohammadyari S, Singh H. Understanding the effect of e-learning on individual performance: The role of digital literacy. Comput Educ. 2015; 82: 11-25. https://doi.org/10.1016/j.compedu.2014.10.025
52. Abdekhoda M, Dehnad A, Yousefi M. Effectiveness of training intervention to improve medical student’s information literacy skills. Korean J Med Educ. 2016; 28(4): 391-5. https://doi.org/10.3946/kjme.2016.44
53. Sin MK, Bliquez R. Teaching evidence based practice to undergraduate nursing students. J Prof Nurs. 2017; 33(6): 447-51. https://doi.org/10.1016/j.profnurs.2017.06.003
54. UNESCO. Hacia unos Indicadores de Alfabetización Informacional Madrid: Ministerio de Cultura, Gobierno de España; 2009.
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56. Wozar JA, Worona PC. The use of online information resources by nurses. J Med Libr Assoc. 2003; 91(2): 216-21. https://doi.org/10.1043/0025-7338(2003)091<0216:TUOOIR>2.0.CO;2
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2. Díaz-Caballero A, Romero-Martínez G, González-Martínez F. Percepción del desempeño en la búsqueda de información en bases de datos bibliográficas de los estudiantes de estomatología. Caso de estudio. Acimed. 2010; 21(1): 111-30. https://bit.ly/2XgtAHl
3. Espinoza N, Rincón ÁG, Chacín B. Búsqueda de información en la Web por profesionales de salud en una universidad venezolana. Un estudio transversal. Prof. inf. 2006; 15(1): 28-33. https://bit.ly/2N5d5tw
4. Othman R, Junurham N, Nilam MN. Search Strategies formulation among library and information science students in online database. Middle East J Csi Res; 2014; 19(3): 338-45. https://doi.org/10.5829/idosi.mejsr.2014.19.3.13599
5. Castrillón-Estrada JA, García-Domínguez JC, Anaya-Taboada M, Rodríguez-Berdugo D, De la Rosa-Barranco D, Caballero-Uribe CV. Bases de datos, motores de búsqueda e índices temáticos: herramientas fundamentales para el ejercicio médico. Salud Uninorte. 2008; 24(1): 95-119. https://bit.ly/2arb7j4
6. Tunis SR, Stryer DB, Clancy CM. Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy. JAMA. 2003; 290(12): 1624-32. https://doi.org/10.1001/jama.290.12.1624
7. Ryan EJ. Undergraduate nursing students’ attitudes and use of research and evidence-based practice-an integrative literature review. J Clin Nurs. 2016; 25(11-12): 1548-56. https://doi.org/10.1111/jocn.13229
8. Jacobs SK, Rosenfeld P, Haber J. Information literacy as the foundation for evidence-based practice in graduate nursing education: a curriculum-integrated approach. J Prof Nurs. 2003; 19(5): 320-8. https://bit.ly/2IPIWJp
9. Orellana-Yañez A, Paravic-Klijn T. Enfermería basada en evidencia. Barreras y estrategias para su implementación. Cienc. enferm. 2007; (13)1: 17-24. http://dx.doi.org/10.4067/S0717-95532007000100003
10. Eterovic-Díaz C, Stiepovich-Bertoni J. Enfermería basada en la evidencia y formación profesional. Cienc. enferm. 2010; 16(3): 9-14. http://dx.doi.org/10.4067/S0717-95532010000300002
11. Weng YH, Kuo KN, Yang CY, Liao HH, Chen C, Lo HL, et al. Effectiveness of national evidence-based medicine competition in Taiwan. 2013; 13(66): 1-8. https://doi.org/10.1186/1472-6920-13-66
12. Griffiths JR, Brophy P. Student searching behavior and the web: Use of academic resources and google. Libr Trends. 2005; 53(4): 539-54. https://bit.ly/2FiGV7D
13. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989; 13(3); 319-340. https://doi.org/10.2307/249008
14. Ozoemelem OA. Use of electronic resources by postgraduate students of the Department of Library and Information Science of Delta State University, Abraka, Nigeria. Abraka, Nigeria: Library Philosophy and Practice (e-journal). 2009; 301: 1-23. https://bit.ly/2Y4YUWK
15. García-Hernández X, Lugones-Botell M. Conocimiento y uso de bases de datos y software colaborativo en los profesionales del Hospital Eusebio Hernández. Acimed. 2010; 21(2): 220-29. https://bit.ly/2IYa5dh
16. Karlsson L, Koivula L, Ruokonen I, Kajaani P, Antikainen L, Ruismäki H. From novice to expert: Information seeking processes of university students and researchers. Procedia Soc Behav Sci. 2012; 45: 577-587. https://doi.org/10.1016/j.sbspro.2012.06.595
17. Salazar EA, Ramírez PE. Efecto de los talleres de alfabetización informacional en el uso de las bases de datos científicas. Form. univ. 2014; 7(3): 41-54. https://dx.doi.org/10.4067/S0718-50062014000300006
18. Pravikoff DS, Tanner AB, Pierce ST. Readiness of US Nurses for Evidence-Based Practice. Am J Nurs. 2005; 105(9): 40-51. https://bit.ly/2Y133Lf
19. National Research Council. Being fluent with information technology. Washington DC: National Adacemy Press;1999. https://doi.org/10.17226/6482.
20. Valdespino-Alberti AI, García-Peralta T, Levón-Herrera R, Forrellat-Barrios M. Evaluación del uso y manejo de las bases de datos disponibles para el perfil de medicina transfusional. Revista Cubana de lnformática Médica. 2013; 5(1); 91-102. https://bit.ly/2Kv0G05
21. Yi-Hao W, Chieh-Feng C, Ka-Wai T, Chun-Yuh Y, Ya-Wen C. Preference of online database access for medical students: A before-and-after survey of evidence-based medicine course. 醫學教育. 2016; 20(3): 176-85. https://doi.org/10.6145/jme201618
22. Faletar-Tanacković S, Dragija-Ivanovic M, Cupar D. Scholarly electronic databases and library & information sciences students in Croatia: motivations, uses and barriers. IR information research 2017; 22(1): 20-3. https://bit.ly/2Yg18CM
23. Jaramillo P, Hennig C, Rincón Y. ¿Cómo manejan información los estudiantes de educación superior? El caso de la Universidad de la Sabana, Colombia. Inf. cult. soc. 2011; (25), 117-43. https://bit.ly/2KyZVmP
24. Schleyer T, Spallek H, Butler BS, Subramanian S, Weiss D, Poythress ML, et al. Facebook for scientists: requirements and services for optimizing how scientific collaborations are established. J Med Internet Res. 2008; 10(3): e24. https://doi.org/10.2196/jmir.1047
25. Roblyer MD, McDaniel M, Webb M, Herman J, Witty JV. Findings on Facebook in higher education: A comparison of college faculty and student uses and perceptions of social networking sites. Internet Higher Educ. 2010; 13(3): 134-140. https://doi.org/10.1016/j.iheduc.2010.03.002
26. Gómez M, Roses S, Farias P. El uso académico de las redes sociales en universitarios. Comunicar. 2012; XIX(38): 131-8. https://doi.org/10.3916/C38-2011-03-04
27. Avdic A, Eklund A. Searching reference databases: What students experience and what teachers believe that students experience. JOLIS. 2010; 42(4): 224-35. https://doi.org/10.1177/0961000610380119
28. Soria KM, Fransen J, Nackerud S. Stacks, serials, search engines, and students’ success: First-year undergraduate students’ library use, academic achievement, and retention. Journal of academic librarianship. 2014; 40(1); 84-91. https://doi.org/10.1016/j.acalib.2013.12.002El
29. Rodis J, Aungst TD, Brown NV, Cui Y, Tam L. Enhancing Pharmacy Student Learning and Perceptions of Medical Apps. JMIR MHealth UHealth. 2016; 4(2): https://doi.org/10.2196/mhealth.4843
30. Soria K, Fransen J,Nackerud S. Beyond Books: The Extended Academic Benefits of Library Use for First-Year College Students. C&RL. 2017; 78(1), 8-22. https://doi.org/10.5860/crl.78.1.8
31. Rawstorne P, Jayasuriya R, Caputi P. Issues in predicting and explaining usage behaviors with the technology acceptance model and the theory of planned behavior when usage is mandatory. ICIS 2000 proceeding. 2000.
32. Landry BJL, Griffeth R, Hartman S. Measuring student perceptions of blackboard using the technology acceptance model. Decis Sci J Innovat Educ. 2006; 4(1): 87-9. https://doi.org/10.1111/j.1540-4609.2006.00103.x
33. Masrom M. Technology acceptance model and E-learning. 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Education. Brunei Darussalam: Universiti Brunei Darussalam; 2007.
34. Ertmer PA, Ottenbreit-Leftwich AT. Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of research on Technology. 2010; 42(3): 255-84. https://bit.ly/2Xu7Urm
35. Ertmer PA, Ottenbreit-Leftwich AT, Sadik O, Sendurur E, Sendurur P. Teacher beliefs and technology integration practices: A critical relationship. Comput Educ. 2012; 59(2): 423-35. https://doi.org/10.1016/j.compedu.2012.02.001
36. Hernández-Sampieri R, Fernández-Collado C, Baptista-Lucio MP. Metodología de la investigación. 6ta ed. México D.F.: McGraw-Hill; 2014. https://bit.ly/2JLPtUM
37. Ramírez PE, Melo-Mariano A, Salazar EA. Propuesta metodológica para aplicar modelos de ecuaciones estructurales con PLS: El caso del uso de las bases de datos científicas en estudiantes universitarios. Revista ADMpg Gestão Estratégica. 2014; 7(2): 133-9. https://bit.ly/2FvNmUY
38. Barclay D, Higgins C, Thompson R. The Partial Least Squares (PLS) approach to causal modelling: Personal computer adoption and use as an illustration. Ontario: Walter de Guyter; 1995. https://bit.ly/2L8rSla
39. Nunnally JC. Psychometic theory. 2da ed. NewYork: McGraw-Hill series in psychology; 1978.
40. Fornell C, Larcker DF. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J Mark Res. 1981; 18(3): 382-8. http://dx.doi.org/10.2307/3150980
41. Chin WW. The partial least squares approach for structural equation modeling. En: Marcoulides GA. (ed). Modern methods for business research. Mahwah, EE.UU: Lawrence Erlbaum Associates Publisher; 1998.
42. Myers RH. Classical and modern regression with applications. 2nd ed. Boston: Brooks/Cole, Duxbury Press; 1990.
43. Efron B, Tibshirani R. An introduction to the bootstrap. United Kindom: Chapman and Hall/ CRC press; 1994.
44. Chau PYK, Jen-Hwa Hu P. Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information & Management. 2002; 39: 297–311. http://dx.doi.org/10.1016/S0378-7206(01)00098-2
45. Jen-Her W, Shu-Ching W. What drives mobile commerce? An empirical investigation of the revised technology acceptance model. Information & Management. 2005; 42(5): 719–29. https://doi.org/10.1016/j.im.2004.07.001
46. Adams DA, Nelson RR, Todd PA. Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Q. 1992; 16(2): 227-47. https://doi.org/10.2307/249577
47. Van Raaij EM, Schepers JLL. The acceptance and use of a virtual learning environment in China. Comput Educ. 2008; 50(3); 838-52. https://doi.org/10.1016/j.compedu.2006.09.001
48. Shu-Sheng L, Hsiu-Mei H. An investigation of user attitudes toward search engines as an information retrieval tool. Comput Human; 2003; 19(6); 751-65.
49. Fox LM, Richter JM, White N. Pathways to information literacy. J Nurs Educ.1989; 28(9): 422-425. https://doi.org/10.3928/0148-4834-19891101-09
50. Verhey MP. Information literacy in an undergraduate nursing curriculum: development, implementation, and evaluation. J Nurs Educ. 1999; 38(6): 252-9. https://bit.ly/2XuPq9X
51. Mohammadyari S, Singh H. Understanding the effect of e-learning on individual performance: The role of digital literacy. Comput Educ. 2015; 82: 11-25. https://doi.org/10.1016/j.compedu.2014.10.025
52. Abdekhoda M, Dehnad A, Yousefi M. Effectiveness of training intervention to improve medical student’s information literacy skills. Korean J Med Educ. 2016; 28(4): 391-5. https://doi.org/10.3946/kjme.2016.44
53. Sin MK, Bliquez R. Teaching evidence based practice to undergraduate nursing students. J Prof Nurs. 2017; 33(6): 447-51. https://doi.org/10.1016/j.profnurs.2017.06.003
54. UNESCO. Hacia unos Indicadores de Alfabetización Informacional Madrid: Ministerio de Cultura, Gobierno de España; 2009.
55. Dee C, Stanley EE. Information-seeking behavior of nursing students and clinical nurses: implications for heatlh sciences librarians. Jo Med Libr Assoc. 2005; 93(2), 213-22. https://bit.ly/2Rycr6B
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