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Six of one, half a dozen of the other? Examining measurement properties of different potentially traumatic event polyvictimization operationalizations using a multiverse analysis framework

Published online by Cambridge University Press:  03 October 2024

Austen McGuire*
Affiliation:
National Crime Victims Research and Treatment Center, Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Daniel W. Smith
Affiliation:
National Crime Victims Research and Treatment Center, Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Dean Kilpatrick
Affiliation:
National Crime Victims Research and Treatment Center, Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
*
Corresponding author: Austen McGuire; Email: mcguirau@musc.edu

Abstract

Numerous differences exist between and within research projects related to assessment and operationalization of potentially traumatic events (PTEs) for youth, especially when measuring polyvictimization. However, few studies have systematically examined how polyvictimization measurement differences influence PTE’s relation to functioning. This study sought to address these knowledge gaps by conducting a secondary data multiverse replication (SDMR) to systematically (re)evaluate PTE polyvictimization measurement approaches. Participants included 3297 adolescents (Mage = 14.63; 50.59% female; 65.15% white) from the National Survey of Adolescents-Replication study who completed a structured interview on PTE exposure and emotional and behavioral health (i.e., posttraumatic stress and major depressive disorder, drug and alcohol use, and delinquency). Results indicated that PTE operationalizations using a count variable tended to demonstrate better model performance and prediction of youth at-risk of emotional and behavioral health challenges, compared to models using a binary (yes/no) PTE operationalization. Differences in model performance and prediction were less distinct between models examining multiple forms of a single type of PTE (e.g., maltreatment, community violence), compared to models examining multiple PTE types. These findings emphasize the importance of using multidimensional approaches to PTE operationalization and the need for more multiverse analyses to improve PTE evidence-based assessment.

Type
Regular Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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References

American Psychiatric Association (2022). Diagnostic and statistical manual of mental disorders (5th edn.). American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890425787 Google Scholar
Adams, Z. W., McCart, M. R., Zajac, K., Danielson, C. K., Sawyer, G. K., Saunders, B. E., & Kilpatrick, D. G. (2013). Psychiatric problems and trauma exposure in nondetained delinquent and nondelinquent adolescents. Journal of Clinical Child & Adolescent Psychology, 42(3), 323331. https://doi.org/10.1080/15374416.2012.749786 CrossRefGoogle ScholarPubMed
Anda, R. F., Porter, L. E., & Brown, D. W. (2020). Inside the adverse childhood experience score: Strengths, limitations, and misapplications. American Journal of Preventive Medicine, 59(2), 293295. https://doi.org/10.1016/j.amepre.2020.01.009 CrossRefGoogle ScholarPubMed
Awaysheh, A., Wilcke, J., Elvinger, F., Rees, L., Fan, W., & Zimmerman, K. L. (2019). Review of medical decision support and machine-learning methods. Veterinary Pathology, 56(4), 512525. https://doi.org/10.1177/0300985819829524 CrossRefGoogle ScholarPubMed
Baldwin, J. R., Pingault, J. B., Schoeler, T., Sallis, H. M., & Munafò, M. R. (2022). Protecting against researcher bias in secondary data analysis: Challenges and potential solutions. European Journal of Epidemiology, 37(1), 110. https://doi.org/10.1007/s10654-02100839-0 CrossRefGoogle ScholarPubMed
Bokhove, C. (2022). The role of analytical variability in secondary data replications: A replication of Kim et al., (2014). Educational Research and Evaluation, 27(1-2), 141163. https://doi.org/10.1080/13803611.2021.2022319 CrossRefGoogle Scholar
Briggs, E. C., Amaya-Jackson, L., Putnam, K. T., & Putnam, F. W. (2021). All adverse childhood experiences are not equal: The contribution of synergy to adverse childhood experience scores. American Psychologist, 76(2), 243252. https://doi.org/10.1037/amp0000768 CrossRefGoogle Scholar
Carlson, J. S., Yohannan, J., Darr, C. L., Turley, M. R., Larez, N. A., & Perfect, M. M. (2020). Prevalence of adverse childhood experiences in school-aged youth: A systematic review (1990-2015. International Journal of School & Educational Psychology, 8(sup1), 223. https://doi.org/10.1080/21683603.2018.1548397 CrossRefGoogle Scholar
Eklund, K., Rossen, E., Koriakin, T., Chafouleas, S. M., & Resnick, C. (2018). A systematic review of trauma screening measures for children and adolescents. School Psychology Quarterly, 33(1), 3043. https://doi.org/10.1037/spq0000244 CrossRefGoogle ScholarPubMed
Elliott, D. (1985). National youth survey [United States]: Wave I, 1976. Inter-University Consortium for Political and Social Research.Google Scholar
Ettekal, I., Eiden, R. D., Nickerson, A. B., & Schuetze, P. (2019). Comparing alternative methods of measuring cumulative risk based on multiple risk indicators: Are there differential effects on children’s externalizing problems? PloS One, 14(7), e0219134. https://doi.org/10.1371/journal.pone.0219134 CrossRefGoogle ScholarPubMed
Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin, 139(6), 13421396. https://doi.org/10.1037/a0031808 CrossRefGoogle ScholarPubMed
Finkelhor, D., Ormrod, R. K., & Turner, H. A. (2007). Poly-victimization: A neglected component in child victimization. Child Abuse & Neglect, 31(1), 726. https://doi.org/10.1016/j.chiabu.2006.06.008 CrossRefGoogle ScholarPubMed
Garza, K., & Jovanovic, T. (2017). Impact of gender on child and adolescent PTSD. Current Psychiatry Reports, 19(11), 16. https://doi.org/10.1007/s11920-017-0830-6 CrossRefGoogle ScholarPubMed
Haahr-Pedersen, I., Ershadi, A. E., Hyland, P., Hansen, M., Perera, C., Sheaf, G., Bramsen, R. H., Spitz, P., Vallières, F. (2020). Polyvictimization and psychopathology among children and adolescents: A systematic review of studies using the Juvenile Victimization Questionnaire. Child Abuse & Neglect, 107, 104589. https://doi.org/10.1016/j.chiabu.2020.104589 CrossRefGoogle ScholarPubMed
Halladay, J., Woock, R., El-Khechen, H., Munn, C., MacKillop, J., Amlung, M., Ogrodnik, M., Favotto, L., Aryal, K., Noori, A., Kiflen, M., & Georgiades, K. (2020). Patterns of substance use among adolescents: A systematic review. Drug and Alcohol Dependence, 216, 108222. https://doi.org/10.1016/j.drugalcdep.2020.108222 CrossRefGoogle ScholarPubMed
Hamby, S., Elm, J. H., Howell, K. H., & Merrick, M. T. (2021). Recognizing the cumulative burden of childhood adversities transforms science and practice for trauma and resilience. American Psychologist, 76(2), 230242. https://doi.org/10.1037/amp0000763 CrossRefGoogle ScholarPubMed
Harder, J. A. (2020). The multiverse of methods: Extending the multiverse analysis to address data-collection decisions. Perspectives on Psychological Science, 15(5), 11581177. https://doi.org/10.1177/1745691620917678 CrossRefGoogle ScholarPubMed
Hemmert, G. A., Schons, L. M., Wieseke, J., & Schimmelpfennig, H. (2018). Log-likelihood-based pseudo-R 2 in logistic regression: Deriving sample-sensitive benchmarks. Sociological Methods & Research, 47, 507531. https://doi.org/10.1177/00491241166381 CrossRefGoogle Scholar
Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression, vol. 398. John Wiley & Sons.CrossRefGoogle Scholar
Jackson, Y., Gabrielli, J., Fleming, K., Tunno, A. M., & Makanui, P. K. (2014). Untangling the relative contribution of maltreatment severity and frequency to type of behavioral outcome in foster youth. Child Abuse & Neglect, 38(7), 11471159. https://doi.org/10.1016/j.chiabu.2014.01.008 CrossRefGoogle ScholarPubMed
Kilpatrick, D. G. (2022). Defining potentially traumatic events: Research findings and controversies. In Beck, J., & Sloan, D. (Eds.), The oxford handbook of traumatic stress disorders, second edition (pp. 1544). Oxford University Press.Google Scholar
Kilpatrick, D. G., Ruggiero, K. J., Acierno, R., Saunders, B. E., Resnick, H. S., & Best, C. L. (2003). Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: Results from the National Survey of Adolescents. Journal of Consulting and Clinical Psychology, 71(4), 692700. https://doi.org/10.1037/0022-006X.71.4.692 CrossRefGoogle ScholarPubMed
Krupnik, V. (2019). Trauma or adversity? Traumatology, 25(4), 256261. https://doi.org/10.1037/trm0000169 CrossRefGoogle Scholar
Lacey, R. E., & Minnis, H. (2020). Practitioner review: Twenty years of research with adverse childhood experience scores-advantages, disadvantages and applications to practice. Journal of Child Psychology and Psychiatry, 61(2), 116130. https://doi.org/10.1111/jcpp.13135 CrossRefGoogle Scholar
Lang, J. M., & Connell, C. M. (2017). Development and validation of a brief trauma screening measure for children: The Child Trauma Screen. Psychological Trauma: Theory, Research, Practice, and Policy, 9(3), 390398. https://doi.org/10.1037/tra0000235 CrossRefGoogle ScholarPubMed
Lantz, B. (2019). Machine learning with R: Expert techniques for predictive modeling. Packt Publishing Ltd.Google Scholar
Laws, K. R. (2016). Psychology, replication & beyond. BMC Psychology, 4(1), 30. https://doi.org/10.1186/s40359-016-0135-2 CrossRefGoogle ScholarPubMed
Lee, N., Pigott, T. D., Watson, A., Reuben, K., O’Hara, K., Massetti, G., & Self-Brown, S. (2023). Childhood polyvictimization and associated health outcomes: A systematic scoping review. Trauma, Violence, & Abuse, 24(3), 15791592. https://doi.org/10.1177/15248380211073847 CrossRefGoogle ScholarPubMed
Lian, J., Kiely, K. M., & Anstey, K. J. (2022). Cumulative risk, factor analysis, and latent class analysis of childhood adversity data in a nationally representative sample. Child Abuse & Neglect, 125, 105486. https://doi.org/10.1016/j.chiabu.2022.105486 CrossRefGoogle ScholarPubMed
Loomis, A. M., Feely, M., & Kennedy, S. (2020). Measuring self-reported polyvictimization in foster youth research: A systematic review. Child Abuse & Neglect, 107, 104588. https://doi.org/10.1016/j.chiabu.2020.104588 CrossRefGoogle ScholarPubMed
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7(1), 1940. https://doi.org/10.1037/1082-989X.7.1.19 CrossRefGoogle ScholarPubMed
McGuire, A., Gabrielli, J., & Jackson, Y. (2024). Trying to fit a square peg in a round hole? Testing the robustness of maltreatment measurement models for youth. Child Maltreatment, 29(2), 233245. https://doi.org/10.1177/10775595221149447 CrossRefGoogle Scholar
McGuire, A., Huffhines, L., & Jackson, Y. (2021). The trajectory of PTSD among youth in foster care: A survival analysis examining maltreatment experiences prior to entry into care. Child Abuse & Neglect, 115, 105026. https://doi.org/10.1016/j.chiabu.2021.105026 CrossRefGoogle Scholar
McGuire, A., & Jackson, Y. (2024). A multiverse analysis examining measurement factors of potentially traumatic events that influence predictability of developmental functioning among children. Traumatology. https://doi.org/10.1037/trm0000502.CrossRefGoogle Scholar
McLaughlin, K. A., Weissman, D., & Bitrán, D. (2019). Childhood adversity and neural development: A systematic review. Annual Review of Developmental Psychology, 1(1), 277312. https://doi.org/10.1146/annurev-devpsych-121318-084950 CrossRefGoogle ScholarPubMed
McNeil, S. L., Andrews, A. R., & Cohen, J. R. (2020). Emotional maltreatment and adolescent depression: Mediating mechanisms and demographic considerations in a child welfare sample. Child Development, 91(5), 16811697. https://doi.org/10.1111/cdev.13366 CrossRefGoogle Scholar
Naicker, S. N., Ahun, M. N., Besharati, S., Norris, S. A., Orri, M., & Richter, L. M. (2022). The long-term health and human capital consequences of adverse childhood experiences in the birth to thirty cohort: Single, cumulative, and clustered adversity. International Journal of Environmental Research and Public Health, 19(3), 1799. https://doi.org/10.3390/ijerph19031799 CrossRefGoogle ScholarPubMed
Oh, D. L., Jerman, P., Boparai, S. K. P., Koita, K., Briner, S., Bucci, M., & Harris, N. B. (2018). Review of tools for measuring exposure to adversity in children and adolescents. Journal of Pediatric Health Care, 32(6), 564583. https://doi.org/10.1016/j.pedhc.2018.04.021 CrossRefGoogle ScholarPubMed
Radtke, S. R., Wretman, C. J., Fraga Rizo, C., Franchino-Olsen, H., Williams, D. Y., Chen, W. T., & Macy, R. J. (2024). A systematic review of conceptualizations and operationalizations of youth polyvictimization. Trauma, Violence, & Abuse, 25(4), 27212734. https://doi.org/10.1177/15248380231224026.CrossRefGoogle ScholarPubMed
Robertson, C. I., & Burton, D. L. (2010). An exploration of differences in childhood maltreatment between violent and non-violent male delinquents. Journal of Child & Adolescent Trauma, 3(4), 319329. https://doi.org/10.1080/19361521.2010.523065 CrossRefGoogle Scholar
Royston, P., Altman, D. G., & Sauerbrei, W. (2006). Dichotomizing continuous predictors in multiple regression: A bad idea. Statistics in Medicine, 25(1), 127141. https://doi.org/10.1002/sim.2331 CrossRefGoogle ScholarPubMed
Runyan, D. K. (2000). The ethical, legal, and methodological implications of directly asking children about abuse. Journal of Interpersonal Violence, 15(7), 675681. https://doi.org/10.1177/088626000015007001 CrossRefGoogle Scholar
Steegen, S., Tuerlinckx, F., Gelman, A., & Vanpaemel, W. (2016). Increasing transparency through a multiverse analysis. Perspectives on Psychological Science, 11(5), 702712. https://doi.org/10.1177/1745691616658637 CrossRefGoogle ScholarPubMed
Warmingham, J. M., Handley, E. D., Rogosch, F. A., Manly, J. T., & Cicchetti, D. (2019). Identifying maltreatment subgroups with patterns of maltreatment subtype and chronicity: A latent class analysis approach. Child Abuse & Neglect, 87, 2839.CrossRefGoogle ScholarPubMed
Wicherts, J. M., Veldkamp, C. L., Augusteijn, H. E., Bakker, M., Van Aert, R., & Van Assen, M. A. (2016). Degrees of freedom in planning, running, analyzing, and reporting psychological studies: A checklist to avoid p-hacking. Frontiers in Psychology, 11(5), 713729. https://doi.org/10.1177/1745691616650874 Google Scholar
Wolfe, D. A. (2018). Why polyvictimization matters. Journal of Interpersonal Violence, 33(5), 832837. https://doi.org/10.1177/0886260517752215 CrossRefGoogle ScholarPubMed
Wolitzky-Taylor, K. B., Ruggiero, K. J., Danielson, C. K., Resnick, H. S., Hanson, R. F., Smith, D. W., Saunders, B., & Kilpatrick, D. G. (2008). Prevalence and correlates of dating violence in a national sample of adolescents. Journal of the American Academy of Child & Adolescent Psychiatry, 47(7), 755762. https://doi.org/10.1097/CHI.0b013e318172ef5f CrossRefGoogle Scholar
Zhao, Y., Han, L., Teopiz, K. M., McIntyre, R. S., Ma, R., & Cao, B. (2022). The psychological factors mediating/moderating the association between childhood adversity and depression: A systematic review. Neuroscience & Biobehavioral Reviews, 137, 104663. https://doi.org/10.1016/j.neubiorev.2022.104663 CrossRefGoogle ScholarPubMed
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