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Evaluating the Viability of Neurocognition as a Transdiagnostic Construct Using Both Latent Variable Models and Network Analysis

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Abstract

The relational structure of psychological symptoms and disorders is of crucial importance to mechanistic and causal research. Methodologically, factor analytic approaches (latent variable modeling) and network analyses are two dominant approaches. Amidst some debate about their relative merits, use of both methods simultaneously in the same data set has rarely been reported in child or adolescent psychopathology. A second issue is that the nosological structure can be enriched by inclusion of transdiagnostic constructs, such as neurocognition (e.g., executive functions and other processes). These cut across traditional diagnostic boundaries and are rarely included even though they can help map the mechanistic architecture of psychopathology. Using a sample enriched for ADHD (n = 498 youth ages 6 to 17 years; M = 10.8 years, SD = 2.3 years, 55% male), both approaches were used in two ways: (a) to model symptom structure and (b) to model seven neurocognitive domains hypothesized as important transdiagnostic features in ADHD and associated disorders. The structure of psychopathology domains was similar across statistical approaches with internalizing, externalizing, and neurocognitive performance clusters. Neurocognition remained a distinct domain according to both methods, showing small to moderate associations with internalizing and externalizing domains in latent variable models and high connectivity in network analyses. Overall, the latent variable and network approaches yielded more convergent than discriminant findings, suggesting that both may be complementary tools for evaluating the utility of transdiagnostic constructs for psychopathology research.

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Notes

  1. Model 4, the best-fitting model, was run twice more, once accounting for clustering by family and once accounting for age. Model fit and factor loadings for each of these models were comparable to the original model (see Table 1).

References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). American Psychiatric Pub.

  • Beard, C., Millner, A. J., Forgeard, M. J., Fried, E. I., Hsu, K. J., Treadway, M. T., & Björgvinsson, T. (2016). Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychological Medicine, 46(16), 3359–3369.

    Article  Google Scholar 

  • Becker, S. P., & Fogleman, N. D. (2020). Psychiatric co-occurrence (comorbidity) in adolescents with ADHD. ADHD in adolescents: Development, Assessment, and Treatment, 170–203.

  • Belleau, E. L., Phillips, M. L., Birmaher, B., Axelson, D. A., & Ladouceur, C. D. (2013). Aberrant executive attention in unaffected youth at familial risk for mood disorders. Journal of Affective Disorders, 147(1–3), 397–400.

    Article  Google Scholar 

  • Biederman, J., Monuteaux, M. C., Doyle, A. E., Seidman, L. J., Wilens, T. E., Ferrero, F., & Faraone, S. V. (2004). Impact of executive function deficits and attention-deficit/hyperactivity disorder (ADHD) on academic outcomes in children. Journal of Consulting and Clinical Psychology, 72(5), 757.

    Article  Google Scholar 

  • Bloemen, A. J. P., Oldehinkel, A. J., Laceulle, O. M., Ormel, J., Rommelse, N. N. J., & Hartman, C. A. (2018). The association between executive functioning and psychopathology: general or specific? Psychological Medicine, 48(11), 1787–1794.

    Article  Google Scholar 

  • Borsboom, D., Cramer, A. O. J., Schmittmann, V. D., Epskamp, S., & Waldorp, L. J. (2011). The small world of psychopathology. PLoS One, 6(11). e27407, 1–11.

  • Borsboom, D., & Cramer, A. O. (2013). Network analysis: an integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91–121.

    Article  Google Scholar 

  • Bringmann, L. F., & Eronen, M. I. (2018). Don’t blame the model: Reconsidering the network approach to psychopathology. Psychological Review, 125(4), 606.

    Article  Google Scholar 

  • Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., & Moffitt, T. E. (2014). The p factor: one general psychopathology factor in the structure of psychiatric disorders? Clinical Psychological Science, 2(2), 119–137.

    Article  Google Scholar 

  • Clark, L. A., & Watson, D. (1991). Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. Journal of Abnormal Psychology, 100(3), 316.

    Article  Google Scholar 

  • Conners, C. K. (1997). Conners’ Rating Scales Revised. Toronto, Ontario, Canada: Multi Health Systems Inc.

    Google Scholar 

  • Conway, C. C., Forbes, M. K., Forbush, K. T., Fried, E. I., Hallquist, M. N., Kotov, R., & Sunderland, M. (2019). A hierarchical taxonomy of psychopathology can transform mental health research. Perspectives on psychological science, 14(3), 419–436.

    Article  Google Scholar 

  • Cramer, A. O., Waldorp, L. J., Van Der Maas, H. L., & Borsboom, D. (2010). Comorbidity: A network perspective. Behavioral and Brain Sciences, 33(2–3), 137–150.

    Article  Google Scholar 

  • DuPaul, G. J., Power, T. J., Anastopoulos, A. D., & Reid, R. (1998). ADHD Rating Scale—IV: Checklists, norms, and clinical interpretation. GuilfordPress.

  • Epskamp, S., Rhemtulla, M., & Borsboom, D. (2017). Generalized network pschometrics: Combining network and latent variable models. Psychometrika, 82(4), 904–927.

    Article  Google Scholar 

  • Essau, C. A., Conradt, J., & Petermann, F. (2000). Frequency, comorbidity, and psychosocial impairment of specific phobia in adolescents. Journal of Clinical Child Psychology, 29(2), 221–231.

    Article  Google Scholar 

  • Forbes, M. K., Wright, A. G., Markon, K. E., & Krueger, R. F. (2017). Evidence that psychopathology symptom networks have limited replicability. Journal of Abnormal Psychology, 126(7), 969.

    Article  Google Scholar 

  • Grisanzio, K. A., Goldstein-Piekarski, A. N., Wang, M. Y., Ahmed, A. P. R., Samara, Z., & Williams, L. M. (2018). Transdiagnostic symptom clusters and associations with brain, behavior, and daily function in mood, anxiety, and trauma disorders. JAMA psychiatry, 75(2), 201–209.

    Article  Google Scholar 

  • Hallquist, M. N., Wright, A. G. C., & Molenaar, P. C. M. (2019). Problems with centrality measures in psychopathology symptom networks: Why network psychometrics cannot escape psychometric theory. Multivariate Behavioral Research, 1–25.

  • Hankin, B. L., Davis, E. P., Snyder, H., Young, J. F., Glynn, L. M., & Sandman, C. A. (2017). Temperament factors and dimensional, latent bifactor models of child psychopathology: Transdiagnostic and specific associations in two youth samples. Psychiatry research, 252, 139–146.

    Article  Google Scholar 

  • Isvoranu, A. M., van Borkulo, C. D., Boyette, L. L., Wigman, J. T., Vinkers, C. H., & Group Investigators D. B. (2016). A network approach to psychosis: pathways between childhood trauma and psychotic symptoms. Schizophrenia Bulletin, 43(1), 187–196.

    Google Scholar 

  • Jensen, P. S., Hinshaw, S. P., Kraemer, H. C., Lenora, N., Newcorn, J. H., Abikoff, H. B., & Elliott, G. R. (2001). ADHD comorbidity findings from the MTA study: comparing comorbid subgroups. Journal of the American Academy of Child and Adolescent Psychiatry, 40(2), 147–158.

    Article  Google Scholar 

  • Kofler, M. J., Sarver, D. E., Spiegel, J. A., Day, T. N., Harmon, S. L., & Wells, E. L. (2017). Heterogeneity in ADHD: Neurocognitive predictors of peer, family, and academic functioning. Child Neuropsychology, 23(6), 733–759.

    Article  Google Scholar 

  • Kotov, R., Krueger, R. F., Watson, D., Achenbach, T. M., Althoff, R. R., Bagby, R. M., & Eaton, N. R. (2017). The Hierarchical Taxonomy of Psychopathology (HiTOP): a dimensional alternative to traditional nosologies. Journal of Abnormal Psychology, 126(4), 454.

    Article  Google Scholar 

  • Lahey, B. B., Applegate, B., Waldman, I. D., Loft, J. D., Hankin, B. L., & Rick, J. (2004). The structure of child and adolescent psychopathology: generating new hypotheses. Journal of Abnormal Psychology, 113(3), 358.

    Article  Google Scholar 

  • Lahey, B. B., Applegate, B., Hakes, J. K., Zald, D. H., Hariri, A. R., & Rathouz, P. J. (2012). Is there a general factor of prevalent psychopathology during adulthood? Journal of Abnormal Psychology, 121(4), 971.

    Article  Google Scholar 

  • Lahey, B. B., Krueger, R. F., Rathouz, P. J., Waldman, I. D., & Zald, D. H. (2017). A hierarchical causal taxonomy of psychopathology across the life span. Psychological Bulletin, 143(2), 142.

    Article  Google Scholar 

  • Lahey, B. B., Rathouz, P. J., Van Hulle, C., Urbano, R. C., Krueger, R. F., Applegate, B., & Waldman, I. D. (2008). Testing structural models of DSMIVsymptoms of common forms of child and adolescent psychopathology. Journal of abnormal child psychology, 36(2), 187–206.

    Article  Google Scholar 

  • Lahey, B. B., Zald, D. H., Perkins, S. F., Villalta-Gil, V., Werts, K. B., Van Hulle, C. A., & Watts, A. L. (2018). Measuring the hierarchical general factor model of psychopathology in young adults. International Journal of Methods in Psychiatric Research, 27(1), e1593.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • McNally, R. J., Robinaugh, D. J., Wu, G. W., Wang, L., Deserno, M. K., & Borsboom, D. (2015). Mental disorders as causal systems: A network approach to posttraumatic stress disorder. Clinical Psychology Science, 3(6), 836–849.

    Article  Google Scholar 

  • McNally, R. J. (2016). Can network analysis transform psychopathology? Behaviour Research and Therapy, 86, 95–104.

    Article  Google Scholar 

  • Murray, A. L., Eisner, M., & Ribeaud, D. (2016). The development of the general factor of psychopathology ‘p factor’ through childhood and adolescence. Journal of Abnormal Child Psychology, 44(8), 1573–1586.

    Article  Google Scholar 

  • Muthén, L. K., & Muthén, B. (2019). Mplus. The comprehensive modelling program for applied researchers: user’s guide, 5.

  • Newman, M. E., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.

    Article  Google Scholar 

  • Nigg, J. T., Blaskey, L., Stawicki, J., & Sachek, J. (2004). Evaluating the endophenotype model of ADHD neuropsychological deficit: Results for parents and siblings of children with DSM-IV ADHD Combined and Inattentive Subtypes. Journal of Abnormal Psychology, 113, 614–625.

    Article  Google Scholar 

  • Nigg, J. T., Jester, J. M., Stavro, G. M., Ip, K. I., Puttler, L. I., & Zucker, R. A. (2017). Specificity of executive functioning and processing speed problems in common psychopathology. Neuropsychology, 31, 448–466.

    Article  Google Scholar 

  • Nikolas, M. A., & Nigg, J. T. (2013). Neuropsychological performance and attention-deficit hyperactivity disorder subtypes and symptom dimensions. Neuropsychology, 27(1), 107.

  • Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251.

    Article  Google Scholar 

  • Patalay, P., Fonagy, P., Deighton, J., Belsky, J., Vostanis, P., & Wolpert, M. (2015). A general psychopathology factor in early adolescence. British Journal of Psychiatry, 207(1), 15–22.

    Article  Google Scholar 

  • Puig-Antich, J., Orvaschel, H., Tabrizi, M. A., & Chambers, W. (1980). The schedule for affective disorders and schizophrenia for school-age children epidemiologic version (KIDDIE-SADS-E). New York: New York State Psychiatric Institute and Yale University School of Medicine.

  • Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514.

    Article  Google Scholar 

  • Slaats-Willemse, D. I., Swaab-Barneveld, H. J., de Sonneville, L. M., & Buitelaar, J. K. (2007). Family-genetic study of executive functioning in attention-deficit/hyperactivity disorder: Evidence for an endophenotype? Neuropsychology, 21(6), 751.

    Article  Google Scholar 

  • Sonuga-Barke, E., Bitsakou, P., & Thompson, M. (2010). Beyond the dual pathway model: evidence for the dissociation of timing, inhibitory, and delay-related impairments in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 49(4), 345–355.

    PubMed  Google Scholar 

  • Stanton, K., McDonnell, C. G., Hayden, E. P., & Watson, D. (2020). Transdiagnostic approaches to psychopathology measurement: Recommendations formeasure selection, data analysis, and participant recruitment. Journal of Abnormal Psychology, 129(1), 21.

    Article  Google Scholar 

  • van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B. W., Waldorp, L. J., & Schoevers, R. A. (2015). Association of symptom network structure with the course of depression. JAMA Psychiatry, 72(12), 1219–1226.

    Article  Google Scholar 

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Acknowledgement

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. The authors also thank all participating children and their families for making this work possible.

Funding

This project was supported by Award Number R01-MH070004-01A2 from the National Institute of Mental Health.

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Correspondence to Hana-May Eadeh.

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Eadeh, HM., Markon, K.E., Nigg, J.T. et al. Evaluating the Viability of Neurocognition as a Transdiagnostic Construct Using Both Latent Variable Models and Network Analysis. Res Child Adolesc Psychopathol 49, 697–710 (2021). https://doi.org/10.1007/s10802-021-00770-8

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