Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos
El objetivo del presente estudio fue evaluar la dimensionalidad de la estructura interna de la versión para estudiantes de la Utrech Work Engagement Scale (UWES-9S), así como su asociación con la procrastinación académica en 321 estudiantes de psicología de una universidad privada de Cajamarca, Perú...
- Autores:
-
Domínguez-Lara, Sergio Alexis
Sánchez-Villena, Andy Rick
Fernández-Arata, Manuel
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2020
- Institución:
- Universidad Católica de Colombia
- Repositorio:
- RIUCaC - Repositorio U. Católica
- Idioma:
- eng
- OAI Identifier:
- oai:repository.ucatolica.edu.co:10983/28487
- Palabra clave:
- Academic engagement
Academic procrastination
Bifactor analysis
Structural regression
College students
Engagement académico
Procrastinación académica
Análisis bifactor
Regresión estructural
Estudiantes universitarios
- Rights
- openAccess
- License
- Acta Colombiana de Psicología - 2020
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| dc.title.spa.fl_str_mv |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| dc.title.translated.eng.fl_str_mv |
Psychometric properties of the UWES-9S in Peruvian college students |
| title |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| spellingShingle |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos Academic engagement Academic procrastination Bifactor analysis Structural regression College students Engagement académico Procrastinación académica Análisis bifactor Regresión estructural Estudiantes universitarios |
| title_short |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| title_full |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| title_fullStr |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| title_full_unstemmed |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| title_sort |
Propiedades psicométricas de la UWES-9S en estudiantes universitarios peruanos |
| dc.creator.fl_str_mv |
Domínguez-Lara, Sergio Alexis Sánchez-Villena, Andy Rick Fernández-Arata, Manuel |
| dc.contributor.author.spa.fl_str_mv |
Domínguez-Lara, Sergio Alexis Sánchez-Villena, Andy Rick Fernández-Arata, Manuel |
| dc.subject.eng.fl_str_mv |
Academic engagement Academic procrastination Bifactor analysis Structural regression College students |
| topic |
Academic engagement Academic procrastination Bifactor analysis Structural regression College students Engagement académico Procrastinación académica Análisis bifactor Regresión estructural Estudiantes universitarios |
| dc.subject.spa.fl_str_mv |
Engagement académico Procrastinación académica Análisis bifactor Regresión estructural Estudiantes universitarios |
| description |
El objetivo del presente estudio fue evaluar la dimensionalidad de la estructura interna de la versión para estudiantes de la Utrech Work Engagement Scale (UWES-9S), así como su asociación con la procrastinación académica en 321 estudiantes de psicología de una universidad privada de Cajamarca, Perú, con edades entre los 17 y los 41 años (79 % mujeres; Medad = 22.50 años; 84 % entre 17 y 25 años). Para esto, se administró la UWES-9S y la Escala de Procrastinación Académica (EPA), y se realizó un análisis factorial confirmatorio y bifactor para la UWES-9S, así como un análisis de regresión estructural para identificar la influencia de las dimensiones general y específicas del engagement sobre las dimensiones de la procrastinación académica. Como resultados, el modelo bifactor muestra una mejor definición del constructo, y la dimensión general del engagement presenta mayor influencia sobre las dimensiones de la procrastinación académica que las específicas. Al final se discuten las implicaciones teóricas y prácticas de los hallazgos, así como la necesidad de enfocarse en los recursos positivos de los estudiantes con el fin de que logren un mayor involucramiento en sus labores académicas. |
| publishDate |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2020-07-31 13:38:05 2023-01-23T15:43:37Z |
| dc.date.available.none.fl_str_mv |
2020-07-31 13:38:05 2023-01-23T15:43:37Z |
| dc.date.issued.none.fl_str_mv |
2020-07-31 |
| dc.type.spa.fl_str_mv |
Artículo de revista |
| dc.type.coar.eng.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.coarversion.eng.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Text |
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info:eu-repo/semantics/article |
| dc.type.local.eng.fl_str_mv |
Journal article |
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http://purl.org/redcol/resource_type/ART |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
| dc.identifier.doi.none.fl_str_mv |
10.14718/ACP.2020.23.2.2 |
| dc.identifier.eissn.none.fl_str_mv |
1909-9711 |
| dc.identifier.issn.none.fl_str_mv |
0123-9155 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/10983/28487 |
| dc.identifier.url.none.fl_str_mv |
https://doi.org/10.14718/ACP.2020.23.2.2 |
| identifier_str_mv |
10.14718/ACP.2020.23.2.2 1909-9711 0123-9155 |
| url |
https://hdl.handle.net/10983/28487 https://doi.org/10.14718/ACP.2020.23.2.2 |
| dc.language.iso.eng.fl_str_mv |
eng |
| language |
eng |
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https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3305 https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3378 https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3306 https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3380 https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3454 |
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Núm. 2 , Año 2020 : Acta Colombiana de Psicología |
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39 |
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2 |
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7 |
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23 |
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Acta Colombiana de Psicología |
| dc.relation.references.eng.fl_str_mv |
American Educational Research Association, American Psychological Association & National Council on Measurement in Education. (2014). Standards for Educational and Psychological Testing. American Educational Research Association. Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument. Journal of School Psychology, 44(5), 427-445. https://doi. org/10.1016/j.jsp.2006.04.002 Asociación Médica Mundial. (1964). Declaración de Helsinki. AMM. http://www.conamed.gob.mx/prof_salud/pdf/helsinki.pdf Asparouhov, T., & Muthén, B. (2006). Robust chi square difference testing with mean and adjusted test statistics. En Mplus web notes (p. 9). University of California. https:// www.statmodel.com/download/webnotes/webnote10.pdf Ato, M., López, J., & Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología. Anales de Psicología, 29(3), 1038-1059. https://doi. org/10.6018/analesps.29.3.178511 Barraza, A., & Barraza, S. (2018). Evidencias de validez y confiabilidad de la Escala de Procrastinación Académica en una población estudiantil mexicana. Revista de Psicología y Ciencias del Comportamiento de la Unidad Académica de Ciencias Jurídicas y Sociales, 9(1), 75-99. http://www.scielo.org.mx/scielo.phpscript=sci_arttext&pid =S2007-18332018000100075 Busko, D. A. (1998). Causes and consequences of perfectionism and procrastination: A structural equation model (Tesis de maestría). University of Guelph, Guelph, Ontario. Byrne, B. M. (2009). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge & Taylor & Francis. Byrne, Z. S., Peters, J. M., & Weston, J. W. (2016). The struggle with employee engagement: Measures and construct clarification using five samples. Journal of Applied Psychology, 101(9), 1201-1227. https://doi.org/10.1037/apl0000124 Cadime, I., Lima, S., Marques-Pinto, A., & Ribeiro, I. (2016). Measurement invariance of the Utrecht Work Engagement Scale for Students: A study across secondary school pupils and university students. European Journal of Developmental Psychology, 13(2), 254-263. https://doi.org/10.1080/17405629.2016.1148595 Canivez, G. L. (2016). Bifactor modeling in construct validation of multifactored tests: Implications for multidimensionality and test interpretation. En K. Schweizer & C. DiStefano (Eds.), Principles and methods of test construction: Standards and recent advancements (pp. 247-271). Hogrefe. Çapri, B., Gündüz, B., & Akbay, S. E. (2017). Utrecht Work Engagement Scale-Student Forms’ (UWES-SF) adaptation to Turkish, validity and reliability studies, and the mediator role of work engagement between academic procrastination and academic responsibility. Educational Sciences: Theory & Practice, 17(2), 411-435. https://doi.org/10.12738/estp.2017.2.0518 Carle, A. C., Jaffee, D., Vaughan, N. W., & Eder, D. (2009). Psychometric properties of three new national survey of student engagement based engagement scales: An item response theory analysis. Research in Higher Education, 50(8), 775-794. https://doi.org/10.1007/s11162-009-9141-z Carmona-Halty, M. A., Schaufeli, W. B., & Salanova, M. (2019). The Utrecht Work Engagement Scale for Students (UWES9S): Factorial Validity, Reliability, and Measurement Invariance in a Chilean Sample of Undergraduate University Students. Frontiers in Psychology, 10, 1017. https://doi.org/10.3389/fpsyg.2019.01017 Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464-504. https://doi.org/10.1080/10705510701301834 Chen, F. F., Jing, Y., Hayes, A., & Lee, J. M. (2012). Two Concepts or Two Approaches? A Bifactor Analysis of Psychological and Subjective Well-Being. Journal of Happiness Studies, 14(3), 1033-1068. https://doi. org/10.1007/s10902-012-9367-x Closson, L. M., & Boutilier, R. R. (2017). Perfectionism, academic engagement, and procrastination among undergraduates: The moderating role of honors student status. Learning and Individual Differences, 57, 157-162. https:// doi.org/10.1016/j.lindif.2017.04.010 Colegio de Psicólogos del Perú. (2017). Código de ética y deontología. https://www.cpsp.pe/documentos/marco_legal/codigo_de_etica_y_deontologia.pdf DiStefano, C., Liu, J., Jiang, N., & Shi, D. (2018). Examination of the weighted root mean square residual: Evidence for trustworthiness? Structural Equation Modeling, 25(3), 453-466. https://doi.org/10.1080/10705511.2017.1390394 Dogan, U. (2015). Student engagement, academic self-efficacy, and academic motivation as predictors of academic performance. The Anthropologist, 20(3), 553-561. https://doi.org/10.1080/09720073.2015.11891759 Dominguez-Lara, S. (2016a). Datos normativos de la Escala de Procrastinación Académica en estudiantes de psicología de Lima. Evaluar, 16(1), 20-30. https://revistas.unc.edu.ar/index.php/revaluar/article/view/15715 Dominguez-Lara S. (2016b). Secretos del coeficiente alfa. Actas Urológicas Españolas, 40(7), 471. https://doi. org/10.1016/j.acuro.2016.04.002 Dominguez-Lara, S. (2016c). Errores correlacionados y estimación de la fiabilidad en estudios de validación: comentarios al trabajo validación de la escala ehealth literacy (eheals) en población universitaria española. Revista Española de Salud Pública, 90(9), e1-e2. http://scielo.isciii.es/pdf/resp/ v90/1135-5727-resp-90-e60002.pdf Dominguez-Lara, S. (2018). Propuesta de puntos de corte para cargas factoriales: una perspectiva de fiabilidad de constructo. Enfermería Clínica, 28(6), 401-402. https://doi. org/10.1016/j.enfcli.2018.06.002 Dominguez-Lara, S., & Merino-Soto, C. (2017). Una modificación del coeficiente alfa de Cronbach por errores correlacionados. Revista Médica de Chile, 145(2), 269-274. https://doi.org/10.4067/S0034-98872017000200018 Dominguez-Lara, S., & Merino-Soto, C. (2018). Análisis de las malas especificaciones en modelos de ecuaciones estructurales. Revista Argentina de Ciencias del Comportamiento, 0(2), 19-24. https://doi.org/10.30882/1852.4206.v10.n2.19 595 Dominguez-Lara, S., Prada-Chapoñan, R., & Moreta-Herrera, R. (2019). Gender differences in the influence of personality on academic procrastination in Peruvian college students. Acta Colombiana de Psicología, 22(2), 125-136. https://doi.org/10.14718/ACP.2019.22.2.7 Ellis, P. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press. Fernández-Martínez, E., Andina-Díaz, E., Fernández-Peña, R., García-López, R., Fulgueiras-Carril, I., & Liébana-Presa, C. (2017). Social networks, engagement and resilience in university students. International Journal of Environmental Research and Public Health, 14(12), E1488. https://doi. org/10.3390/ijerph14121488 Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312 Garzón, A., & Gil, J. (2017). El papel de la procrastinación académica como factor de la deserción universitaria. Revista Complutense de Educación, 28(1), 307-324. https://doi. org/10.5209/rev_RCED.2017.v28.n1.49682 González-Brignardello, M. P., & Sánchez-Elvira-Paniagua, A. (2013). ¿Puede amortiguar el engagement los efectos nocivos de la procrastinación académica? Acción Psicológica,10(1), 117-134. https://doi.org/10.5944/ap.10.1.7039 Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis. Prentice Hall. Hoppe, J. D., Prokop, P., & Rau, R. (2018). Empower, not impose!: Preventing academic procrastination. Journal of Prevention & Intervention in the Community, 46(2), 184-198. https://doi.org/10.1080/10852352.2016.1198172 Hu, Q., & Schaufeli, W. B. (2009). The factorial validity of the Maslach Burnout Inventory-Student Survey in China. Psychological Reports, 105(2), 394-408. https://doi.org/10.2466/PR0.105.2.394-408 Kline, R. B. (2016). Principles and practice of structural equation modeling. The Guilford Press. Kyriazos, T. A. (2018). Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9, 2207-2230. https://doi.org/10.4236/psych.2018.98126 Lac, A., & Donaldson, C. D. (2017). Higher-order and bifactor models of the drinking motives questionnaire: Examining competing structures using confirmatory factor analysis. Assessment, 24(2), 222-231. https://doi. org/10.1177/1073191115603503 Lauriola, M., & Iani, L. (2017). Personality, positivity and happiness: A mediation analysis using a bifactor model. Journal of Happiness Studies, 18(6), 1659-1682. https://doi.org/10.1007/s10902-016-9792-3 Loscalzo, Y., & Giannini, M. (2019). Study engagement in Italian university students: a confirmatory factor analysis of the Utrecht Work Engagement Scale-Student version. Social Indicators Research, 142(2), 845-854. https://doi.org/10.1007/s11205-018-1943-y Luciano, J. V., Barrada, J. R., Aguado, J., Osma, J., & GarcíaCampayo, J. (2014). Bifactor analysis and construct validity of the HADS: A cross-sectional and longitudinal study in fibromyalgia patients. Psychological Assessment, 26(2), 395-406. https://doi.org/10.1037/a0035284 Malgady, R. (2007). How skew are psychological data? A standardized index of effect size. The Journal of General Psychology, 134(3), 355-359. https://doi.org/10.3200/ GENP.134.3.355-360 Mardia, K. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519-530. https://doi.org/10.2307/2334770 Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397-422. https://doi.org/10.1146/annurev.psych.52.1.397 Mazer, J. P. (2012). Development and validation of the Student Interest and Engagement Scales. Communication Methods and Measures, 6(2), 99-125. https://doi.org/10.1080/19312 458.2012.679244 McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64-82. https://doi. org/10.1037/1082-989X.7.1.64 Medrano, L., Moretti, L., & Ortiz, A. (2015). Medición del Engagement Académico en Estudiantes Universitarios. Revista Iberoamericana de Diagnóstico y Evaluación e Avaliação Psicológica, 40(1), 114-123. https://www.re dalyc.org/pdf/4596/459645432012.pdf Medrano, L. A., Galleano, C., Galera, M., & del ValleFernández, R. (2010). Creencias irracionales, rendimiento y deserción académica en ingresantes universitarios. Liberabit, 16(2), 183-192. http://www.scielo.org.pe/pdf/liber/v16n2/a08v16n2 Meng, L., & Jin, Y. (2017). A confirmatory factor analysis of the Utrecht Work Engagement Scale for students in a Chinese sample. Nurse Education Today, 49, 129-134. https://doi.org/10.1016/j.nedt.2016.11.017 Merino-Soto, C. (2015). Re-análisis de la confiabilidad del Cuestionario de autoeficacia profesional (AU10). En Maffei et al., Pensamiento Psicológico, 13(1), 137-138. http://www.scielo.org.co/scielo.php?script=sci_arttext&pid =S1657-89612015000100010 Moreta-Herrera, R., & Durán-Rodríguez, T. (2018). Propiedades psicométricas de la Escala de Procrastinación Académica (EPA) en estudiantes de psicología de Ambato, Ecuador. Revista Salud & Sociedad, 9(3), 236-247. https://doi.org/10.22199/S07187475.2018.0003.00003 Muthén, L. K., & Muthén, B. O. (1998-2015). Mplus User’s guide (7. ª ed.). Muthén & Muthén. Palos, R., Maricutoiu, L. P., & Coster, I. (2019). Relations between academic performance, student engagement, and student burnout: A cross-lagged analysis of a two-wave study. Studies in Educational Evaluation, 60, 199-204. https://doi.org/10.1016/j.stueduc.2019.01.005 Patrzek, J., Sattler, S., van Veen, F., Grunschel, C., & Fries, S. (2015). Investigating the effect of academic procrastination on the frequency and variety of academic misconduct: a panel study. Studies in Higher Education, 40(6), 1014-1029. https://doi.org/10.1080/03075079.2013.854765 Ponterotto, J., & Charter, R. (2009). Statistical extensions of Ponterotto and Ruckdeschel’s (2007) reliability matrix for estimating the adequacy of internal consistency coefficients. Perceptual and Motor Skills, 108(3), 878-886. https://doi.org/10.2466/PMS.108.3.878-886 Raykov, T. (2004) Point and interval estimation of reliability for multiple-component measuring instruments via linear constraint covariance structure modeling, Structural Equation Modeling, 11(3), 342-356. https://doi.org/10.1207/s15328007sem1103_3 Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667-696. https://doi.org/1080/00273171.2012.715555 Reise, S. P. Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5-26. https://doi.org/10.1177/0013164412449831 Reschly, A. L., & Christenson, S. L. (2012). Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct. En S. L. Christenson, A. L. Reschly & C. Wylie (Eds.), Handbook of research on student engagement (pp. 3-19). Springer Science & Business Media. https://doi.org/10.1007/978-1-4614-2018-7_1 Rocha, C. F., Zelaya, Y. F., Sánchez, D. M., & Pérez, F. A. (2017). Prediction of University Desertion through Hybridization of Classification Algorithms. En Proceedings of the 4th Annual International Symposium on Information Management and Big Data (pp. 215-222). http://ceur-ws. org/Vol-2029/paper21.pdf Rodriguez, M., & Ruiz, M. (2008). Atenuación de la asimetría y de la curtosis de las puntuaciones observadas mediante transformaciones de variables: Incidencia sobre la estructura factorial. Psicológica, 29, 205-227. https://www.uv.es/psicologica/articulos2.08/6RODRIGUEZ.pdf Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Applying bifactor statistical indices in the evaluation of psychological measures. Journal of Personality Assessment, 98(3), 223-237. https://doi.org/10.1080/00223891.2015.1089249 Römer, J. (2016). The Korean Utrecht Work Engagement ScaleStudent (UWESS): A factor validation study. TPM Testing, Psychometrics, Methodology in Applied Psychology, 23(1), 65-81. https://doi.org/10.4473/TPM23.1.5 Salanova, M., Bresó, E., & Schaufeli, W. B. (2005). Hacia un modelo espiral de las creencias de eficacia en el estudio del burnout y del engagement. Ansiedad y estrés, 11(2-3), 215-231. http://www.want.uji.es/download/hacia-un-modeloespiral-de-las-creencias-de-eficacia-en-el-estudio-del-bur nout-y-del-engagement/ Salanova, M., Schaufeli, W. B., Martinez, I., & Bresó, E. (2010). How obstacles and facilitators predict academic performance: the mediating role of study burn out and engagement. Anxiety, Stress & Coping, 23(1), 53-70. https://doi.org/10.1080/10615800802609965 Salanova, M., Schaufeli, W. B., Llorens, S., Peiró, J. M., & Grau, R. (2000). Desde el «burnout» al «Engagement»: ¿una nueva perspectiva? Revista de Psicología del Trabajoy de las Organizaciones, 16(2), 117-134. https://journals.copmadrid.org/jwop/art/7c590f01490190db0ed02a5070e20f01 Sánchez-Cardona, I., Rodríguez-Montalbán, R., Toro-Alfonso, J., & Moreno-Velázquez, I. (2016). Psychometric properties of the Utrecht Work Engagement Scale-Student (UWES-S) in university students in Puerto Rico. Revista Mexicana de Psicología, 33(2), 121-134. https://psycnet.apa.org/record/2016-37425-004 Saris, W. E, Satorra, A., & van der Veld, W. M. (2009). Testing structural equation modeling or detection of misspecifications? Structural Equation Modeling, 16(4), 561-582. https://doi.org/10.1080/10705510903203433 Schaufeli, W., & Bakker, A. B. (2003). UWES Utrecht Work Engagement Scale. Utrecht University. https://www.wil marschaufeli.nl/publications/Schaufeli/Test%20Manuals/Test_manual_UWES_Espanol.pdf Schaufeli, W. B., & Bakker, A. B. (2010). Defining and measuring work engagement: Bringing clarity concept. En A. B. Bakker & M. P. Leiter (Eds.), Work engagement: A handbook of essential theory and research (pp. 10-24). Psychology Press. Schaufeli, W., & De Witte, H. (2017). Outlook Work Engagement in Contrast to Burnout: Real and Redundant! Burnout Research, 5, 58-60. https://doi.org/10.1016/j.burn.2017.06.002 Schaufeli, W. B., & Salanova, M. (2007). Efficacy or inefficacy, that’s the question: Burnout and engagement, and their relationships with efficacy beliefs. Anxiety, Coping & Stress, 20(2), 177-196. https://doi. org/10.1080/10615800701217878 Schaufeli, W. B., & Salanova, M. (2011). Work engagement: On how to better catch a slippery concept. European Journal of work and Organizaytiponal Psychology, 20(1), 39-46. https://doi.org/10.1080/1359432X.2010.515981 Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: a cross-national study. Educational and Psychological Measurement, 66(4), 701-716. https://doi. org/10.1177/0013164405282471 Schaufeli, W. B., Martinez, I. M., Marques-Pinto, A., Salanova, M., & Bakker, A. (2002). Burn out and engagement in university students: a cross-national study. Journal of Cross-Cultural Psychology, 33(5), 464-481. https://doi. org/10.1177/0022022102033005003 Schaufeli, W. B., Salanova, M., González-Romá, V., & Bakker, A. B. (2002). The measurement of engagement and burnout: a two sample confirmatory factor analytic approach. Journal of Happiness Studies, 3(1), 71-92. https://doi.org/10.1023/a:1015630930326 Schaufeli, W. B., Shimazu, A., Hakanen, J., Salanova, M., & De Witte, H. (2019). An ultra-short measure for work engagement: The UWES-3 validation across five countries. European Journal of Psychological. Assessment, 35(4), 577-591. https://doi.org/10.1027/1015-5759/a000430 Serrano, C., Andreu, Y., Murgui, S., & Martínez, P. (2019). Psychometric properties of Spanish version student Utrecht Work Engagement Scale (UWES-S-9) in high-school students. The Spanish Journal of Psychology, 22, e21. https://doi.org/10.1017/sjp.2019.25 Shrive, F. M., Stuart, H., Quan, H., & Ghali, W. A. (2006). Dealing with missing data in a multi-question depression scale: a comparison of imputation methods. BMC Medical Research Methodology, 6(1), 57. https://doi. org/10.1186/1471-2288-6-57 Silva, J. O., Junior, G. A., Coelho, I. C., Picharski, G. L., & Zagonel, I. P. (2018). Engajamento entre Estudantes do Ensino Superior nas Ciências da Saúde (Validação do Questionário Ultrecht Work Engagement Scale (UWES-S) com Estudantes do Ensino Superior nas Ciências da Saúde). Revista Brasileira de Educação Médica, 42(2), 15-25. https://doi.org/10.1590/1981-52712015v42n2rb20170112 Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107- 120. https://doi.org/10.1007/s11336-008-9101-0 Smits, I. A., Timmerman, M. E., Barelds, D. P., & Meijer, R. R. (2015). The Dutch symptom checklist-90-revised: is the use of the subscales justified? European Journal of Psychological Assessment, 31(4), 263-271. https://doi. org/10.1027/1015-5759/a000233 Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65-94. https://doi. org/10.1037/0033-2909.133.1.65 Steel, P. (2011). Procrastinación. Editorial Grijalbo. Steel, P., & Klingsieck, K. B. (2016). Academic procrastination: Psychological antecedents revisited. Australian Psychologist, 51(1), 36-46. https://doi.org/10.1111/ap.12173 Stefansson, K. K., Gestsdottir, S., Geldhof, G. J., Skulason, S., & Lerner, R. M. (2016). A bifactor model of school engagement: Assessing general and specific aspects of behavioral, emotional and cognitive engagement among adolescents. International Journal of Behavioral Development, 40(5), 471-480. https://doi.org/10.1177/0165025415604056 Strunk, K. K., Cho, Y., Steele, M. R., & Bridges, S. L. (2013). Development and validation of a 2x2 model of time-related academic behavior: Procrastination and timely engagement. Learning and Individual Differences, 25(1), 35-44. https://doi.org/10.1016/j.lindif.2013.02.007 Wang, M. T., Fredricks, J. A., Ye, F., Hofkens, T. L., & Linn, J. S. (2016). The math and science engagement scales: Scale development, validation, and psychometric properties. Learning and Instruction, 43, 16-26. https://doi. org/10.1016/j.learninstruc.2016.01.008 Wellborn, J. G., & Connell, J. P. (1987). Manual for the Rochester Assessment Package for Schools. University of Rochester. West, S. G., Taylor, A. B., & Wu, W. (2012). Model fit and model selection in structural equation modeling. En R. H. Hoyle (Ed.), Handbook of Structural Equation Modeling (pp. 209-231). Guilford. Wolf, E., Harrington, K., Clark, S., & Miller, M. (2013). Sample size requirements for structural equations modeling: an evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 76(6), 913-934. https://doi.org/10.1177/0013164413495237 Zhen, R., Liu, R.-D., Ding, Y., Wang, J., Liu, Y., & Xu, L. (2017). The mediating roles of academic self-efficacy and academic emotions in the relation between basic psychological needs satisfaction and learning engagement among Chinese adolescent students. Learning and Individual Differences, 54, 210-216. https://doi.org/10.1016/j.lindif.2017.01.017 Zinbarg, R. E., Yovel, I., Revelle, W., & McDonald, R. P. (2006). Estimating generalizability to a latent variable common to all of a scale’s indicators: A comparison of estimators for ωh. Applied Psychological Measurement, 30(2), 121-144. https://doi.org/10.1177/0146621605278814 |
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Domínguez-Lara, Sergio Alexisec6c9603-512c-463d-8f9c-2fd65e60b5bfSánchez-Villena, Andy Rick50f2752c-b103-4eb7-8203-fb096fa05e08300Fernández-Arata, Manuel53127544-9313-450c-ac13-a16043997f443002020-07-31 13:38:052023-01-23T15:43:37Z2020-07-31 13:38:052023-01-23T15:43:37Z2020-07-31El objetivo del presente estudio fue evaluar la dimensionalidad de la estructura interna de la versión para estudiantes de la Utrech Work Engagement Scale (UWES-9S), así como su asociación con la procrastinación académica en 321 estudiantes de psicología de una universidad privada de Cajamarca, Perú, con edades entre los 17 y los 41 años (79 % mujeres; Medad = 22.50 años; 84 % entre 17 y 25 años). Para esto, se administró la UWES-9S y la Escala de Procrastinación Académica (EPA), y se realizó un análisis factorial confirmatorio y bifactor para la UWES-9S, así como un análisis de regresión estructural para identificar la influencia de las dimensiones general y específicas del engagement sobre las dimensiones de la procrastinación académica. Como resultados, el modelo bifactor muestra una mejor definición del constructo, y la dimensión general del engagement presenta mayor influencia sobre las dimensiones de la procrastinación académica que las específicas. Al final se discuten las implicaciones teóricas y prácticas de los hallazgos, así como la necesidad de enfocarse en los recursos positivos de los estudiantes con el fin de que logren un mayor involucramiento en sus labores académicas.The objective of this study was to evaluate the internal structure dimensionality of the Utrech Work Engagement Scale – Student (UWES–9S) and its association with the academic procrastination reported by 321 psychology students from a private university in Cajamarca (Peru) ranging between 17 and 41 years old (79% women; Mage = 22.50 years; 84% between 17 and 25 years old). The UWES-9S and the Academic Procrastination Scale (APS) were used and both a confirmatory and a bifactor analysis were conducted on the UWES–9S, as well as a structural regression analysis that specified the influence of the general and specific dimensions of engagement on the dimensions of academic procrastination. Regarding the results, the bifactor model is the one that best defines the construct, whereas the general dimension of engagement has a greater influence on the dimensions of academic procrastination than the specific ones. The theoretical and practical implications of the findings are discussed, as well as the need to focus on the students’ positive resources in order to achieve greater involvement in their academic work.application/pdftext/htmlapplication/pdftext/htmltext/xml10.14718/ACP.2020.23.2.21909-97110123-9155https://hdl.handle.net/10983/28487https://doi.org/10.14718/ACP.2020.23.2.2engUniversidad Católica de Colombiahttps://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3305https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3378https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3306https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3380https://actacolombianapsicologia.ucatolica.edu.co/article/download/2924/3454Núm. 2 , Año 2020 : Acta Colombiana de Psicología392723Acta Colombiana de PsicologíaAmerican Educational Research Association, American Psychological Association & National Council on Measurement in Education. (2014). Standards for Educational and Psychological Testing. American Educational Research Association.Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument. Journal of School Psychology, 44(5), 427-445. https://doi. org/10.1016/j.jsp.2006.04.002Asociación Médica Mundial. (1964). Declaración de Helsinki. AMM. http://www.conamed.gob.mx/prof_salud/pdf/helsinki.pdfAsparouhov, T., & Muthén, B. (2006). Robust chi square difference testing with mean and adjusted test statistics. En Mplus web notes (p. 9). University of California. https:// www.statmodel.com/download/webnotes/webnote10.pdfAto, M., López, J., & Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología. Anales de Psicología, 29(3), 1038-1059. https://doi. org/10.6018/analesps.29.3.178511Barraza, A., & Barraza, S. (2018). Evidencias de validez y confiabilidad de la Escala de Procrastinación Académica en una población estudiantil mexicana. Revista de Psicología y Ciencias del Comportamiento de la Unidad Académica de Ciencias Jurídicas y Sociales, 9(1), 75-99. http://www.scielo.org.mx/scielo.phpscript=sci_arttext&pid =S2007-18332018000100075Busko, D. A. (1998). Causes and consequences of perfectionism and procrastination: A structural equation model (Tesis de maestría). University of Guelph, Guelph, Ontario.Byrne, B. M. (2009). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge & Taylor & Francis.Byrne, Z. S., Peters, J. M., & Weston, J. W. (2016). The struggle with employee engagement: Measures and construct clarification using five samples. Journal of Applied Psychology, 101(9), 1201-1227. https://doi.org/10.1037/apl0000124Cadime, I., Lima, S., Marques-Pinto, A., & Ribeiro, I. (2016). Measurement invariance of the Utrecht Work Engagement Scale for Students: A study across secondary school pupils and university students. European Journal of Developmental Psychology, 13(2), 254-263. https://doi.org/10.1080/17405629.2016.1148595Canivez, G. L. (2016). Bifactor modeling in construct validation of multifactored tests: Implications for multidimensionality and test interpretation. En K. Schweizer & C. DiStefano (Eds.), Principles and methods of test construction: Standards and recent advancements (pp. 247-271). Hogrefe.Çapri, B., Gündüz, B., & Akbay, S. E. (2017). Utrecht Work Engagement Scale-Student Forms’ (UWES-SF) adaptation to Turkish, validity and reliability studies, and the mediator role of work engagement between academic procrastination and academic responsibility. Educational Sciences: Theory & Practice, 17(2), 411-435. https://doi.org/10.12738/estp.2017.2.0518Carle, A. C., Jaffee, D., Vaughan, N. W., & Eder, D. (2009). Psychometric properties of three new national survey of student engagement based engagement scales: An item response theory analysis. Research in Higher Education, 50(8), 775-794. https://doi.org/10.1007/s11162-009-9141-zCarmona-Halty, M. A., Schaufeli, W. B., & Salanova, M. (2019). The Utrecht Work Engagement Scale for Students (UWES9S): Factorial Validity, Reliability, and Measurement Invariance in a Chilean Sample of Undergraduate University Students. Frontiers in Psychology, 10, 1017. https://doi.org/10.3389/fpsyg.2019.01017Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464-504. https://doi.org/10.1080/10705510701301834Chen, F. F., Jing, Y., Hayes, A., & Lee, J. M. (2012). Two Concepts or Two Approaches? A Bifactor Analysis of Psychological and Subjective Well-Being. Journal of Happiness Studies, 14(3), 1033-1068. https://doi. org/10.1007/s10902-012-9367-xClosson, L. M., & Boutilier, R. R. (2017). Perfectionism, academic engagement, and procrastination among undergraduates: The moderating role of honors student status. Learning and Individual Differences, 57, 157-162. https:// doi.org/10.1016/j.lindif.2017.04.010Colegio de Psicólogos del Perú. (2017). Código de ética y deontología. https://www.cpsp.pe/documentos/marco_legal/codigo_de_etica_y_deontologia.pdfDiStefano, C., Liu, J., Jiang, N., & Shi, D. (2018). Examination of the weighted root mean square residual: Evidence for trustworthiness? Structural Equation Modeling, 25(3), 453-466. https://doi.org/10.1080/10705511.2017.1390394Dogan, U. (2015). Student engagement, academic self-efficacy, and academic motivation as predictors of academic performance. The Anthropologist, 20(3), 553-561. https://doi.org/10.1080/09720073.2015.11891759Dominguez-Lara, S. (2016a). Datos normativos de la Escala de Procrastinación Académica en estudiantes de psicología de Lima. Evaluar, 16(1), 20-30. https://revistas.unc.edu.ar/index.php/revaluar/article/view/15715Dominguez-Lara S. (2016b). Secretos del coeficiente alfa. Actas Urológicas Españolas, 40(7), 471. https://doi. org/10.1016/j.acuro.2016.04.002Dominguez-Lara, S. (2016c). Errores correlacionados y estimación de la fiabilidad en estudios de validación: comentarios al trabajo validación de la escala ehealth literacy (eheals) en población universitaria española. Revista Española de Salud Pública, 90(9), e1-e2. http://scielo.isciii.es/pdf/resp/ v90/1135-5727-resp-90-e60002.pdfDominguez-Lara, S. (2018). Propuesta de puntos de corte para cargas factoriales: una perspectiva de fiabilidad de constructo. Enfermería Clínica, 28(6), 401-402. https://doi. org/10.1016/j.enfcli.2018.06.002Dominguez-Lara, S., & Merino-Soto, C. (2017). Una modificación del coeficiente alfa de Cronbach por errores correlacionados. Revista Médica de Chile, 145(2), 269-274. https://doi.org/10.4067/S0034-98872017000200018Dominguez-Lara, S., & Merino-Soto, C. (2018). Análisis de las malas especificaciones en modelos de ecuaciones estructurales. Revista Argentina de Ciencias del Comportamiento, 0(2), 19-24. https://doi.org/10.30882/1852.4206.v10.n2.19 595Dominguez-Lara, S., Prada-Chapoñan, R., & Moreta-Herrera, R. (2019). Gender differences in the influence of personality on academic procrastination in Peruvian college students. Acta Colombiana de Psicología, 22(2), 125-136. https://doi.org/10.14718/ACP.2019.22.2.7Ellis, P. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press.Fernández-Martínez, E., Andina-Díaz, E., Fernández-Peña, R., García-López, R., Fulgueiras-Carril, I., & Liébana-Presa, C. (2017). Social networks, engagement and resilience in university students. International Journal of Environmental Research and Public Health, 14(12), E1488. https://doi. org/10.3390/ijerph14121488Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312Garzón, A., & Gil, J. (2017). El papel de la procrastinación académica como factor de la deserción universitaria. Revista Complutense de Educación, 28(1), 307-324. https://doi. org/10.5209/rev_RCED.2017.v28.n1.49682González-Brignardello, M. P., & Sánchez-Elvira-Paniagua, A. (2013). ¿Puede amortiguar el engagement los efectos nocivos de la procrastinación académica? Acción Psicológica,10(1), 117-134. https://doi.org/10.5944/ap.10.1.7039Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis. Prentice Hall.Hoppe, J. D., Prokop, P., & Rau, R. (2018). Empower, not impose!: Preventing academic procrastination. Journal of Prevention & Intervention in the Community, 46(2), 184-198. https://doi.org/10.1080/10852352.2016.1198172Hu, Q., & Schaufeli, W. B. (2009). The factorial validity of the Maslach Burnout Inventory-Student Survey in China. Psychological Reports, 105(2), 394-408. https://doi.org/10.2466/PR0.105.2.394-408Kline, R. B. (2016). Principles and practice of structural equation modeling. The Guilford Press.Kyriazos, T. A. (2018). Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9, 2207-2230. https://doi.org/10.4236/psych.2018.98126Lac, A., & Donaldson, C. D. (2017). Higher-order and bifactor models of the drinking motives questionnaire: Examining competing structures using confirmatory factor analysis. Assessment, 24(2), 222-231. https://doi. org/10.1177/1073191115603503Lauriola, M., & Iani, L. (2017). Personality, positivity and happiness: A mediation analysis using a bifactor model. Journal of Happiness Studies, 18(6), 1659-1682. https://doi.org/10.1007/s10902-016-9792-3Loscalzo, Y., & Giannini, M. (2019). Study engagement in Italian university students: a confirmatory factor analysis of the Utrecht Work Engagement Scale-Student version. Social Indicators Research, 142(2), 845-854. https://doi.org/10.1007/s11205-018-1943-yLuciano, J. V., Barrada, J. R., Aguado, J., Osma, J., & GarcíaCampayo, J. (2014). Bifactor analysis and construct validity of the HADS: A cross-sectional and longitudinal study in fibromyalgia patients. Psychological Assessment, 26(2), 395-406. https://doi.org/10.1037/a0035284Malgady, R. (2007). How skew are psychological data? A standardized index of effect size. The Journal of General Psychology, 134(3), 355-359. https://doi.org/10.3200/ GENP.134.3.355-360Mardia, K. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519-530. https://doi.org/10.2307/2334770Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397-422. https://doi.org/10.1146/annurev.psych.52.1.397Mazer, J. P. (2012). Development and validation of the Student Interest and Engagement Scales. Communication Methods and Measures, 6(2), 99-125. https://doi.org/10.1080/19312 458.2012.679244McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64-82. https://doi. org/10.1037/1082-989X.7.1.64Medrano, L., Moretti, L., & Ortiz, A. (2015). Medición del Engagement Académico en Estudiantes Universitarios. Revista Iberoamericana de Diagnóstico y Evaluación e Avaliação Psicológica, 40(1), 114-123. https://www.re dalyc.org/pdf/4596/459645432012.pdfMedrano, L. A., Galleano, C., Galera, M., & del ValleFernández, R. (2010). Creencias irracionales, rendimiento y deserción académica en ingresantes universitarios. Liberabit, 16(2), 183-192. http://www.scielo.org.pe/pdf/liber/v16n2/a08v16n2Meng, L., & Jin, Y. (2017). A confirmatory factor analysis of the Utrecht Work Engagement Scale for students in a Chinese sample. Nurse Education Today, 49, 129-134. https://doi.org/10.1016/j.nedt.2016.11.017Merino-Soto, C. (2015). Re-análisis de la confiabilidad del Cuestionario de autoeficacia profesional (AU10). En Maffei et al., Pensamiento Psicológico, 13(1), 137-138. http://www.scielo.org.co/scielo.php?script=sci_arttext&pid =S1657-89612015000100010Moreta-Herrera, R., & Durán-Rodríguez, T. (2018). Propiedades psicométricas de la Escala de Procrastinación Académica (EPA) en estudiantes de psicología de Ambato, Ecuador. Revista Salud & Sociedad, 9(3), 236-247. https://doi.org/10.22199/S07187475.2018.0003.00003Muthén, L. K., & Muthén, B. O. (1998-2015). Mplus User’s guide (7. ª ed.). Muthén & Muthén.Palos, R., Maricutoiu, L. P., & Coster, I. (2019). Relations between academic performance, student engagement, and student burnout: A cross-lagged analysis of a two-wave study. Studies in Educational Evaluation, 60, 199-204. https://doi.org/10.1016/j.stueduc.2019.01.005Patrzek, J., Sattler, S., van Veen, F., Grunschel, C., & Fries, S. (2015). Investigating the effect of academic procrastination on the frequency and variety of academic misconduct: a panel study. Studies in Higher Education, 40(6), 1014-1029. https://doi.org/10.1080/03075079.2013.854765Ponterotto, J., & Charter, R. (2009). Statistical extensions of Ponterotto and Ruckdeschel’s (2007) reliability matrix for estimating the adequacy of internal consistency coefficients. Perceptual and Motor Skills, 108(3), 878-886. https://doi.org/10.2466/PMS.108.3.878-886Raykov, T. (2004) Point and interval estimation of reliability for multiple-component measuring instruments via linear constraint covariance structure modeling, Structural Equation Modeling, 11(3), 342-356. https://doi.org/10.1207/s15328007sem1103_3Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667-696. https://doi.org/1080/00273171.2012.715555Reise, S. P. Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5-26. https://doi.org/10.1177/0013164412449831Reschly, A. L., & Christenson, S. L. (2012). Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct. En S. L. Christenson, A. L. Reschly & C. Wylie (Eds.), Handbook of research on student engagement (pp. 3-19). Springer Science & Business Media. https://doi.org/10.1007/978-1-4614-2018-7_1Rocha, C. F., Zelaya, Y. F., Sánchez, D. M., & Pérez, F. A. (2017). Prediction of University Desertion through Hybridization of Classification Algorithms. En Proceedings of the 4th Annual International Symposium on Information Management and Big Data (pp. 215-222). http://ceur-ws. org/Vol-2029/paper21.pdfRodriguez, M., & Ruiz, M. (2008). Atenuación de la asimetría y de la curtosis de las puntuaciones observadas mediante transformaciones de variables: Incidencia sobre la estructura factorial. Psicológica, 29, 205-227. https://www.uv.es/psicologica/articulos2.08/6RODRIGUEZ.pdfRodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Applying bifactor statistical indices in the evaluation of psychological measures. Journal of Personality Assessment, 98(3), 223-237. https://doi.org/10.1080/00223891.2015.1089249Römer, J. (2016). The Korean Utrecht Work Engagement ScaleStudent (UWESS): A factor validation study. TPM Testing, Psychometrics, Methodology in Applied Psychology, 23(1), 65-81. https://doi.org/10.4473/TPM23.1.5Salanova, M., Bresó, E., & Schaufeli, W. B. (2005). Hacia un modelo espiral de las creencias de eficacia en el estudio del burnout y del engagement. Ansiedad y estrés, 11(2-3), 215-231. http://www.want.uji.es/download/hacia-un-modeloespiral-de-las-creencias-de-eficacia-en-el-estudio-del-bur nout-y-del-engagement/Salanova, M., Schaufeli, W. B., Martinez, I., & Bresó, E. (2010). How obstacles and facilitators predict academic performance: the mediating role of study burn out and engagement. Anxiety, Stress & Coping, 23(1), 53-70. https://doi.org/10.1080/10615800802609965Salanova, M., Schaufeli, W. B., Llorens, S., Peiró, J. M., & Grau, R. (2000). Desde el «burnout» al «Engagement»: ¿una nueva perspectiva? Revista de Psicología del Trabajoy de las Organizaciones, 16(2), 117-134. https://journals.copmadrid.org/jwop/art/7c590f01490190db0ed02a5070e20f01Sánchez-Cardona, I., Rodríguez-Montalbán, R., Toro-Alfonso, J., & Moreno-Velázquez, I. (2016). Psychometric properties of the Utrecht Work Engagement Scale-Student (UWES-S) in university students in Puerto Rico. Revista Mexicana de Psicología, 33(2), 121-134. https://psycnet.apa.org/record/2016-37425-004Saris, W. E, Satorra, A., & van der Veld, W. M. (2009). Testing structural equation modeling or detection of misspecifications? Structural Equation Modeling, 16(4), 561-582. https://doi.org/10.1080/10705510903203433Schaufeli, W., & Bakker, A. B. (2003). UWES Utrecht Work Engagement Scale. Utrecht University. https://www.wil marschaufeli.nl/publications/Schaufeli/Test%20Manuals/Test_manual_UWES_Espanol.pdfSchaufeli, W. B., & Bakker, A. B. (2010). Defining and measuring work engagement: Bringing clarity concept. En A. B. Bakker & M. P. Leiter (Eds.), Work engagement: A handbook of essential theory and research (pp. 10-24). Psychology Press.Schaufeli, W., & De Witte, H. (2017). Outlook Work Engagement in Contrast to Burnout: Real and Redundant! Burnout Research, 5, 58-60. https://doi.org/10.1016/j.burn.2017.06.002Schaufeli, W. B., & Salanova, M. (2007). Efficacy or inefficacy, that’s the question: Burnout and engagement, and their relationships with efficacy beliefs. Anxiety, Coping & Stress, 20(2), 177-196. https://doi. org/10.1080/10615800701217878 Schaufeli, W. B., & Salanova, M. (2011). Work engagement: On how to better catch a slippery concept. European Journal of work and Organizaytiponal Psychology, 20(1), 39-46. https://doi.org/10.1080/1359432X.2010.515981Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: a cross-national study. Educational and Psychological Measurement, 66(4), 701-716. https://doi. org/10.1177/0013164405282471Schaufeli, W. B., Martinez, I. M., Marques-Pinto, A., Salanova, M., & Bakker, A. (2002). Burn out and engagement in university students: a cross-national study. Journal of Cross-Cultural Psychology, 33(5), 464-481. https://doi. org/10.1177/0022022102033005003Schaufeli, W. B., Salanova, M., González-Romá, V., & Bakker, A. B. (2002). The measurement of engagement and burnout: a two sample confirmatory factor analytic approach. Journal of Happiness Studies, 3(1), 71-92. https://doi.org/10.1023/a:1015630930326Schaufeli, W. B., Shimazu, A., Hakanen, J., Salanova, M., & De Witte, H. (2019). An ultra-short measure for work engagement: The UWES-3 validation across five countries. European Journal of Psychological. Assessment, 35(4), 577-591. https://doi.org/10.1027/1015-5759/a000430Serrano, C., Andreu, Y., Murgui, S., & Martínez, P. (2019). Psychometric properties of Spanish version student Utrecht Work Engagement Scale (UWES-S-9) in high-school students. The Spanish Journal of Psychology, 22, e21. https://doi.org/10.1017/sjp.2019.25Shrive, F. M., Stuart, H., Quan, H., & Ghali, W. A. (2006). Dealing with missing data in a multi-question depression scale: a comparison of imputation methods. BMC Medical Research Methodology, 6(1), 57. https://doi. org/10.1186/1471-2288-6-57Silva, J. O., Junior, G. A., Coelho, I. C., Picharski, G. L., & Zagonel, I. P. (2018). Engajamento entre Estudantes do Ensino Superior nas Ciências da Saúde (Validação do Questionário Ultrecht Work Engagement Scale (UWES-S) com Estudantes do Ensino Superior nas Ciências da Saúde). Revista Brasileira de Educação Médica, 42(2), 15-25. https://doi.org/10.1590/1981-52712015v42n2rb20170112Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107- 120. https://doi.org/10.1007/s11336-008-9101-0Smits, I. A., Timmerman, M. E., Barelds, D. P., & Meijer, R. R. (2015). The Dutch symptom checklist-90-revised: is the use of the subscales justified? European Journal of Psychological Assessment, 31(4), 263-271. https://doi. org/10.1027/1015-5759/a000233Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65-94. https://doi. org/10.1037/0033-2909.133.1.65Steel, P. (2011). Procrastinación. Editorial Grijalbo.Steel, P., & Klingsieck, K. B. (2016). Academic procrastination: Psychological antecedents revisited. Australian Psychologist, 51(1), 36-46. https://doi.org/10.1111/ap.12173Stefansson, K. K., Gestsdottir, S., Geldhof, G. J., Skulason, S., & Lerner, R. M. (2016). A bifactor model of school engagement: Assessing general and specific aspects of behavioral, emotional and cognitive engagement among adolescents. International Journal of Behavioral Development, 40(5), 471-480. https://doi.org/10.1177/0165025415604056Strunk, K. K., Cho, Y., Steele, M. R., & Bridges, S. L. (2013). Development and validation of a 2x2 model of time-related academic behavior: Procrastination and timely engagement. Learning and Individual Differences, 25(1), 35-44. https://doi.org/10.1016/j.lindif.2013.02.007Wang, M. T., Fredricks, J. A., Ye, F., Hofkens, T. L., & Linn, J. S. (2016). The math and science engagement scales: Scale development, validation, and psychometric properties. Learning and Instruction, 43, 16-26. https://doi. org/10.1016/j.learninstruc.2016.01.008Wellborn, J. G., & Connell, J. P. (1987). Manual for the Rochester Assessment Package for Schools. University of Rochester.West, S. G., Taylor, A. B., & Wu, W. (2012). Model fit and model selection in structural equation modeling. En R. H. Hoyle (Ed.), Handbook of Structural Equation Modeling (pp. 209-231). Guilford.Wolf, E., Harrington, K., Clark, S., & Miller, M. (2013). Sample size requirements for structural equations modeling: an evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 76(6), 913-934. https://doi.org/10.1177/0013164413495237Zhen, R., Liu, R.-D., Ding, Y., Wang, J., Liu, Y., & Xu, L. (2017). The mediating roles of academic self-efficacy and academic emotions in the relation between basic psychological needs satisfaction and learning engagement among Chinese adolescent students. Learning and Individual Differences, 54, 210-216. https://doi.org/10.1016/j.lindif.2017.01.017Zinbarg, R. E., Yovel, I., Revelle, W., & McDonald, R. P. (2006). Estimating generalizability to a latent variable common to all of a scale’s indicators: A comparison of estimators for ωh. Applied Psychological Measurement, 30(2), 121-144. https://doi.org/10.1177/0146621605278814Acta Colombiana de Psicología - 2020info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-sa/4.0/https://actacolombianapsicologia.ucatolica.edu.co/article/view/2924Academic engagementAcademic procrastinationBifactor analysisStructural regressionCollege studentsEngagement académicoProcrastinación académicaAnálisis bifactorRegresión estructuralEstudiantes universitariosPropiedades psicométricas de la UWES-9S en estudiantes universitarios peruanosPsychometric properties of the UWES-9S in Peruvian college studentsArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionPublicationOREORE.xmltext/xml3268https://repository.ucatolica.edu.co/bitstreams/c6121588-710e-456c-874d-54cc28fd154e/download1fae270ce5f9b3519ca105643112f58bMD5110983/28487oai:repository.ucatolica.edu.co:10983/284872023-03-24 16:27:28.24https://creativecommons.org/licenses/by-nc-sa/4.0/Acta Colombiana de Psicología - 2020https://repository.ucatolica.edu.coRepositorio Institucional Universidad Católica de Colombia - RIUCaCbdigital@metabiblioteca.com |