Network Analysis of Internalizing and Externalizing Symptoms in Children and Adolescents

  1. Milagros Ocalin Sánchez-Hernández
  2. Francisco Pablo Holgado-Tello
  3. Miguel Á. Carrasco
Revista:
Psicothema

ISSN: 0214-9915 1886-144X

Año de publicación: 2023

Volumen: 35

Número: 1

Páginas: 66-76

Tipo: Artículo

DOI: 10.7334/PSICOTHEMA2022.17 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Psicothema

Resumen

La experiencia de problemas psicológicos durante la infancia y la adolescencia es común. Sin embargo, la detección de conductas como síntomas de Psicopatologías que requieren diagnóstico y tratamiento clínico sigue siendo infravalorada. Por ello, para evolucionar en la comprensión de los fenómenos psicológicos considerando sus manifestaciones conductuales particulares, se aplican nuevas perspectivas teóricas y metodológicas como el análisis de redes. Método: En el presente estudio exploramos la dinámica de los síntomas de diferentes problemas internalizados y externalizados y personales-contextuales aplicando el análisis de redes. Se estimaron redes de correlaciones parciales regularizadas que incluye medidas de centralidad estándar e impacto global y estructural de los síntomas de distintos síndromes. Resultados: Los resultados muestran que los síndromes se activan a través de dinámicas de síntomas fuertemente relacionados con los demás y que actúan como intermediarios de potenciales problemas psicopatológicos en niños y adolescentes (por ejemplo, “sentirse triste”, “preocuparse”, “negarse a hablar”, “tener náuseas”, “amenazar a los demás”, “robar fuera”). Las medidas de centralidad y coeficientes de impacto oscilaron entre: fuerza (−2.39, 2.05), intermediación (−1.43, 3.38), cercanía (−2.60, 2.23) e influencia esperada (−2.87, 2.13). Conclusiones: Los resultados obtenidos sugieren la necesidad de explorar la dinámica multiconstructo, así como la comorbilidad sintomática entre ellas

Referencias bibliográficas

  • Achenbach, T. M. (1991). Manual for Youth Self-Report 1991 YSR profile. University of Vermont.
  • Achenbach, T. M., Ivanova, M. Y., & Rescorla, L. A. (2017). Empirically based assessment and taxonomy of psychopathology for ages 1½-90+ years: Developmental, multi-informant, and multicultural findings. Comprehensive Psychiatry, 79, 4–18. https://doi.org/10.1016/j.comppsych.2017.03.006
  • Achenbach, T. M., & Rescorla, L. A. (2001). The manual for the AsEBA schoolage forms & profiles. University of Vermont, Research Center for Children, Youth, and Families.
  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). American Psychiatric Association. https://search.library.wisc.edu/catalog/9910187853902121
  • Bekhuis, E., Schoevers, R. A., van Borkulo, C. D., Rosmalen, J. G. M., & Boschloo, L. (2016). The network structure of major depressive disorder, generalized anxiety disorder and somatic symptomatology. Psychological Medicine, 46(14), 2989–2998. https://doi.org/10.1017/S0033291716001550
  • Bono, C., Ried, L. D., Kimberlin, C., & Vogel, B. (2007). Missing data on the center for epidemiologic studies depression scale: A comparison of 4 imputation techniques. Research in Social and Administrative Pharmacy, 3(1), 1–27. https://doi.org/10.1016/j.sapharm.2006.04.001
  • Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5–13. https://doi.org/10.1002/wps.20375
  • Borsboom, D., & Cramer, A. O. J. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91–121. https://doi.org/10.1146/annurev-clinpsy-050212-185608
  • Borsboom, D., Cramer, A. O. J., Schmittmann, V. D., Epskamp, S., & Waldorp, L. J. (2011). The small world of psychopathology. PLoS One, 6(11), Article e27407. https://doi.org/10.1371/journal.pone.0027407
  • Borsboom, D., Robinaugh, D. J., The Psychosystems Group, Rhemtulla, M., & Cramer, A. O. J. (2018). Robustness and replicability of psychopathology networks. World Psychiatry, 17(2), 143–144. https://doi.org/10.1002/wps.20515
  • Bringmann, L. F., Vissers, N., Wichers, M., Geschwind, N., Kuppens, P., Borsboom, D., & Tuerlinckx, F. (2013). A network approach to psychopathology: New insights into clinical longitudinal data. PLoS One, 8(4), Article e60188. https://doi.org/10.1371/journal.pone.0060188
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research. The Guilford Press.
  • Clark, L. A., & Watson, D. (1991). Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. Journal of Abnormal Psychology, 100(3), 316–336. https://doi.org/10.1037//0021-843x.100.3.316
  • Conway, C. C., Forbes, M. K., Forbush, K. T., Fried, E., Hallquist, M. N., Kotov, R., Mullins-Sweatt, S. N., Shackman, A. J., Skodol, A. E., South, S. C., Sunderland, M., Waszczuk, M. A., Zald, D. H., Afzali, M. H., Bornovalova, M. A., Carragher, N., Docherty, A. R., Jonas, K. G., Krueger, R. F., … Eaton, N. R. (2019). A hierarchical taxonomy of psychopathology can transform mental health research. Perspectives on Psychological Science, 14(3), 419– 436. https://doi.org/10.1177/1745691618810696
  • Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13–29. https://doi.org/10.1016/j.jrp.2014.07.003
  • De Bolle, M., De Clercq, B., Decuyper, M., & De Fruyt, F. (2011). Affective determinants of anxiety and depression development in children and adolescents: An individual growth curve analysis. Child Psychiatry & Human Development, 42(6), 694–711. https://doi.org/10.1007/s10578-011-0241-6
  • de la Barrera, U., Villanueva, L., & Prado-Gascó, V. (2019). Emotional and personality predictors that influence the appearance of somatic complaints in children and adults. Psicothema, 31(4), 407–413. https://doi.org/10.7334/psicothema2019.69
  • De Young, C. G., Chmielewski, M., Clark, L. A., Condon, D. M., Kotov, R., Krueger, R. F., Lynam, D. R., Markon, K. E., Miller, J. D., MullinsSweatt, S. N., Samuel, D. B., Sellbom, M., South, S. C., Thomas, K. M., Watson, D., Watts, A. L., Widiger, T. A., & Wright, A. G. C. (2022). The distinction between symptoms and traits in the hierarchical taxonomy of psychopathology (HiTOP). Journal of Personality, 90(1), 20–33. https://doi.org/10.1111/jopy.12593
  • Dozois, D. J. A. (2019). Abnormal psychology: Perspectives (6th ed.). Pearson Canada Inc.
  • Eccles, A. M., Qualter, P., Panayiotou, M., Hurley, R., Boivin, M., & Tremblay, R. E. (2020). Trajectories of early adolescent loneliness: Implications for physical health and sleep. Journal of Child and Family Studies, 29(12), 3398–3407. https://doi.org/10.1007/s10826-020-01804-3
  • Enders, C. K. (2010). Applied missing data analysis. The Guilford Press.
  • Epskamp, S. (2017). Network psychometrics [Doctoral dissertation, University of Amsterdam]. https://sachaepskamp.com/dissertation/EpskampDissertation.pdf
  • Epskamp, S., Borsboom, D., & Fried, E. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212. https://doi.org/10.3758/s13428-017-0862-1
  • Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1–18. https://doi.org/10.18637/jss.v048.i04
  • Epskamp, S., van Borkulo, C. D., van der Veen, D. C., Servaas, M. N., Isvoranu, A. M., Riese, H., & Cramer, A. O. J. (2018). Personalized network modeling in psychopathology: The importance of contemporaneous and temporal connections. Clinical Psychological Science, 6(3), 416–427. https://doi.org/10.1177/2167702617744325
  • Ezpeleta, L., de la Osa, N., & Doménech, J. M. (2014). Prevalence of DSM-IV disorders, comorbidity and impairment in 3-year-old Spanish preschoolers. Social Psychiatry and Psychiatric Epidemiology, 49(1), 145–155. https://doi.org/10.1007/s00127-013-0683-1
  • Figueras, A. (2006). Evaluación multimétodo y multiinformante de la sintomatología depresiva en niños y adolescentes [Multi-method and multi-informant evaluation of depressive symptomatology in children and adolescents] [Doctoral dissertation, Universitat de Barcelona, UB]. UB repository https://www.tdx.cat/handle/10803/2534
  • Fonseca-Pedrero, E. (2017). Network analysis: A new way of understanding psychopathology? Revista de Psiquiatría y Salud Mental (English Edition), 10(4), 206–215. https://doi.org/10.1016/j.rpsm.2017.06.004
  • Fonseca-Pedrero, E. (2018). Análisis de redes en Psicología [Network Analysis in Psychology]. Papeles Del Psicólogo, 39(1), 1–12. https://doi.org/10.23923/pap.psicol2018.2852 Fonseca-Pedrero, E., Pérez-Álvarez, M., Al-Halabí, S., Inchausti, F., López-
  • Navarro, E. R., Muñiz, J., Lucas-Molina, B., Pérez-Albéniz, A., Baños Rivera, R., Cano-Vindel, A., Gimeno-Peón, A., Prado-Abril, J., González-Menéndez, A., Valero, A. V., Priede, A., González-Blanch, C., Ruiz-Rodríguez, P., Moriana, J. A., Gómez, L. E., … Montoya-Castilla, I. (2021). Tratamientos Psicológicos Empíricamente Apoyados Para la Infancia y Adolescencia: Estado de la Cuestión [Empirically Supported Psychological Treatments for Children and Adolescents: State of the Art]. Psicothema, 33(3), 386–398. https://doi.org/10/gp8pxd
  • Forbes, M. K., Sunderland, M., Rapee, R. M., Batterham, P. J., Calear, A. L., Carragher, N., Ruggero, C., Zimmerman, M., Baillie, A. J., Lynch, S. J., Mewton, L., Slade, T., & Krueger, R. F. (2021). A detailed hierarchical model of psychopathology: From individual symptoms up to the general factor of psychopathology. Clinical Psychological Science, 9(2), 139–168. https://doi.org/10.1177/2167702620954799
  • Franco Nerín, N., Pérez Nieto, M., & De Dios Pérez, M.-J. (2014). Relación entre los estilos de crianza parental y el desarrollo de ansiedad y conductas disruptivas en niños de 3 a 6 años [Relationship between parenting styles and the development of anxiety and disruptive behaviors in children aged 3 to 6 years]. Revista de Psicología Clínica con Niños y Adolescentes, 1(2), 149–156. https://www.revistapcna.com/sites/default/files/6-rpcna_vol.2.pdf
  • Fried, E. (2017). What are psychological constructs? On the nature and statistical modelling of emotions, intelligence, personality traits and mental disorders. Health Psychology Review, 11(2), 130–134. https://doi.org/10.1080/17437199.2017.1306718
  • Fried, E., van Borkulo, C. D., Cramer, A. O. J., Boschloo, L., Schoevers, R. A., & Borsboom, D. (2017). Mental disorders as networks of problems: A review of recent insights. Social Psychiatry and Psychiatric Epidemiology, 52, 1–10. https://doi.org/10.1007/s00127-016-1319-z
  • Funkhouser, C. J., Chacko, A. A., Correa, K. A., Kaiser, A. J. E., & Shankman, S. A. (2021). Unique longitudinal relationships between symptoms of psychopathology in youth: A cross-lagged panel network analysis in the ABCD study. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 62(2), 184–194. https://doi.org/10.1111/jcpp.13256
  • González, R. (2000). Psicopatología del niño y del adolescente [Child and adolescent psychopathology]. Pirámide.
  • Graham, P., & Reynolds, S. (Eds.). (2013). Cognitive behavior therapy for children and families. Cambridge University Press.
  • Guyon, H., Falissard, B., & Kop, J. L. (2017). Modeling psychological attributes in psychology—An epistemological discussion: Network analysis vs. Latent variables. Frontiers in Psychology, 8, Article 798. https://doi.org/10.3389/fpsyg.2017.00798
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7a ed.). Pearson.
  • Hatherill, S. (2007). Child and adolescent therapy: Cognitive behavioral procedures (third edition): Edited by philip C kendall. Journal of Child and Adolescent Mental Health, 19(1), 85–86. https://doi.org/10/b2956v
  • Howe, E., Bosley, H. G., & Fisher, A. J. (2020). Idiographic network analysis of discrete mood states prior to treatment. Counselling and Psychotherapy Research, 20(3), 470–478. https://doi.org/10.1002/capr.12295
  • Hukkelberg, S. (2019). The Quintessence of child conduct problems: Identifying central behaviors through network analysis. Journal of Psychopathology and Behavioral Assessment, 41(2), 175–184. https://doi.org/10.1007/s10862-018-9713-3
  • Jones, P. J. (2017). Impact: A new statistic for network analysis. R Package Vignette. Repository CRAN https://Cran.r-Project.Org/Web/Packages/ Networktools/Vignettes/Impact.Pdf.
  • Jones, P. J. (2020). networktools: Tools for identifying important nodes in networks. Repository CRAN https://CRAN.R-project.org/package=networktools
  • Jones, P. J., Ma, R., & McNally, R. J. (2021). Bridge centrality: A network approach to understanding comorbidity. Multivariate Behavioral Research, 56(2), 353–367. https://doi.org/10.1080/00273171.2019.1614898
  • Kokla, M., Virtanen, J., Kolehmainen, M., Paananen, J., & Hanhineva, K. (2019). Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: A comparative study. BMC Bioinformatics, 20(1), Article 492. https://doi.org/10.1186/s12859-019-3110-0
  • Kostelnik, M. J., Phipps, A. W., Soderman, A. K., & Gregory, K. M. (2009). Guiding Children’s Social Development & Learning (6th ed.). Cengage Learning.
  • Kotov, R., Krueger, R. F., Watson, D., Cicero, D. C., Conway, C. C., DeYoung, C. G., Eaton, N. R., Forbes, M. K., Hallquist, M. N., Latzman, R. D., Mullins-Sweatt, S. N., Ruggero, C. J., Simms, L. J., Waldman, I. D., Waszczuk, M. A., & Wright, A. G. C. (2021). The hierarchical taxonomy of psychopathology (HiTOP): A quantitative nosology based on consensus of evidence. Annual Review of Clinical Psychology, 17(1), 83–108. https://doi.org/10.1146/annurev-clinpsy-081219-093304
  • Krueger, R. F., Kotov, R., Watson, D., Forbes, M. K., Eaton, N. R., Ruggero, C. J., Simms, L. J., Widiger, T. A., Achenbach, T. M., Bach, B., Bagby, R. M., Bornovalova, M. A., Carpenter, W. T., Chmielewski, M., Cicero, D. C., Clark, L. A., Conway, C., DeClercq, B., DeYoung, C. G., … Zimmermann, J. (2018). Progress in achieving quantitative classification of psychopathology. World Psychiatry, 17(3), 282–293. https://doi.org/10.1002/wps.20566
  • Lara-Ros, M. R., Rodríguez-Jiménez, T., Martínez-González, A. E., & Piqueras Rodríguez, J. A. (2017). Relación entre el bullying y el estado emocional y social en niños de educación primaria [Relationship between bullying and emotional and social status among primary scholars]. Revista de Psicología Clínica con Niños y Adolescentes, 4(1), 59–64. https://www.redalyc.org/articulo.oa?id=477152555007
  • Letina, S., Blanken, T. F., Deserno, M. K., & Borsboom, D. (2019). Expanding network analysis tools in psychological networks: Minimal spanning trees, participation coefficients, and motif analysis applied to a network of 26 psychological attributes. Complexity, 2019, Article 9424605. https://doi.org/10.1155/2019/9424605
  • Maddux, J. E., & Winstead, B. A. (Eds.). (2016). Psychopathology: foundations for a contemporary understanding (4th ed.). Routledge.
  • Martínez-Hernáez, Á., & Muñoz García, A. (2010a). «Un infinito que no acaba». Modelos explicativos sobre la depresión y el malestar emocional entre los adolescentes barceloneses (España). Primera parte [“An infinity that does not end.” Explanatory models on depression and emotional distress among adolescents from Barcelona (Spain). First part]. Salud Mental, 33(2), 145–152.
  • Martínez-Hernáez, Á., & Muñoz García, A. (2010b). «Un infinito que no acaba». Modelos explicativos sobre la depresión y el malestar emocional entre los adolescentes barceloneses (España). Segunda parte [“An infinity that does not end.” Explanatory models on depression and emotional distress among adolescents from Barcelona (Spain). Second part]. Salud Mental, 33(3), 229–236.
  • McElroy, E., Fearon, P., Belsky, J., Fonagy, P., & Patalay, P. (2018). Networks of depression and anxiety symptoms across development. Journal of the American Academy of Child and Adolescent Psychiatry, 57(12), 964–973. https://doi.org/10.1016/j.jaac.2018.05.027
  • McElroy, E., & Patalay, P. (2019). In search of disorders: Internalizing symptom networks in a large clinical sample. Journal of Child Psychology and Psychiatry, 60(8), 897–906. https://doi.org/10.1111/jcpp.13044
  • Nolen-Hoeksema, S., & Hilt, L. M. (Eds.). (2009). Handbook of depression in adolescents. Taylor & Francis.
  • Ordóñez, A., Maganto, C., & González, R. (2015). Somatic complaints, emotional awareness and maladjustment in schoolchildren. Anales de Pediatría (English Edition), 82(5), 308–315. https://doi.org/10.1016/j.anpede.2015.04.004
  • Papalia, D. E., Olds, S. W., & Feldman, R. D. (2007). Human development (10th ed.). McGraw-Hill.
  • Piqueras, J. A., Mateu-Martínez, O., Cejudo, J., & Pérez-González, J.-C. (2019). Pathways into psychosocial adjustment in children: Modeling the effects of trait emotional intelligence, social-emotional problems, and gender. Frontiers in Psychology, 10, Article 507. https://doi.org/10.3389/fpsyg.2019.00507
  • Polanczyk, G. V., Salum, G. A., Sugaya, L. S., Caye, A., & Rohde, L. A. (2015). Annual research review: A meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. Journal of Child Psychology and Psychiatry, 56(3), 345–365. https://doi.org/10.1111/jcpp.12381
  • R Core Team. (2020). R: a language and environment for statistical computing. R Foundation for Statistical Computing.
  • Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401. https://doi.org/10.1177/014662167700100306
  • Radloff, L. S. (1991). The Use of the center for epidemiologic studies depression scale in adolescents and young adults. Journal of Youth and Adolescence, 20(2), 149–166. https://doi.org/10.1007/BF01537606.
  • Riso, L. P., du Toit, P. L., Stein, D. J., & Young, J. E. (Eds.). (2007). Cognitive schemas and core beliefs in psychological problems: A scientist-practitioner guide. American Psychological Association. https://doi.org/10.1037/11561-000
  • Ruggero, C. J., Kotov, R., Hopwood, C. J., First, M., Clark, L. A., Skodol, A. E., Mullins-Sweatt, S. N., Patrick, C. J., Bach, B., Cicero, D. C., Docherty, A., Simms, L. J., Bagby, R. M., Krueger, R. F., Callahan, J. L., Chmielewski, M., Conway, C. C., De Clercq, B., Dornbach-Bender, A., … Zimmermann, J. (2019). Integrating the hierarchical taxonomy of psychopathology (HiTOP) into clinical practice. Journal of Consulting and Clinical Psychology, 87(12), 1069–1084. https://doi.org/10.1037/ccp0000452
  • Sánchez-Hernández, M. O., Delgado, B., Carrasco, M. A., & Holgado Tello, F. P. (2018). Facetas de la “Escala de depresión del Centro de Estudios Epidemiológicos para niños y adolescentes” (CES-DC) en españoles: Validación empírica [Facets of the “Center for Epidemiological Studies Depression Scale for Children and Adolescents” (CES-DC) in Spanish: Empirical validation]. Behavioral Psychology, 26(3), 495–512.
  • Shah, A., Bartlett, J., Carpenter, J., Nicholas, O., & Hemingway, H. (2014). Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study. American Journal of Epidemiology, 179(6), 764–774. https://doi.org/10.1093/aje/kwt312
  • Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., Salazar de Pablo, G., Il Shin, J., Kirkbride, J. B., Jones, P., Kim, J. H., Kim, J. Y., Carvalho, A. F., Seeman, M. V., Correll, C. U., & Fusar-Poli, P. (2022). Age at onset of mental disorders worldwide: Large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry, 27(1), 281–295. https://doi.org/10.1038/s41380-021-01161-7
  • Sukhodolsky, D. G., Kassinove, H., & Gorman, B. S. (2004). Cognitivebehavioral therapy for anger in children and adolescents: A meta-analysis. Aggression and Violent Behavior, 9(3), 247–269. https://doi.org/10.1016/j.avb.2003.08.005
  • Tang, F., & Ishwaran, H. (2017). Random forest missing data algorithms. Statistical Analysis and Data Mining, 10(6), 363–377. https://doi.org/10.1002/sam.11348
  • Unitat d’Epidemiologia i de Diagnòstic en Psicopatologia del Desenvolupament. (2001). Autoinforme YSR del comportamiento de jóvenes 11-18 años [Youth Self-Report /11-18]. Universitat Autonoma de Barcelona, Departament de Psicologia Clínica i de la Salut. https://www.ued.uab.cat/aseba.html
  • van Bork, R. (2019). Interpreting psychometric models [Doctoral dissertation, University of Amsterdam]. https://doi.org/10.31237/osf.io/x6a7s
  • van Borkulo, C. D., van Bork, R., Boschloo, L., Kossakowski, J. J., Tio, P., Schoevers, R. A., Borsboom, D., & Waldorp, L. J. (2022). Comparing network structures on three aspects: A permutation test. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000476
  • van Buuren, S., & Groothuis-Oudshoorn, K. (2011). mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. https://doi.org/10.18637/jss.v045.i03
  • Weissman, M. M., Orvaschel, H., & Padian, N. (1980). Children´s symptom and social functioning self-report scales: Comparison of mothers´ and children´s reports. The Journal of Nervous and Mental Disease, 168(12), 736–740. https://doi.org/10.1097/00005053-198012000-00005