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Factors Influencing School Social Work Practice: A Latent Profile Analysis

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Abstract

The present study uses a national sample (N = 3769) and a latent profile framework to examine profiles of school social workers who engage in various levels of ecologically oriented practices at school and in the home and community. Three profiles emerged from the data that consisted of school social workers who reported engaging in low, medium and high levels of ecological practice behaviors across school, family, and community domains. Further examination revealed that school social workers fitting into the profile marked by high levels of self-reported practices at school, with families, and to facilitate community-school linkages were more likely to have a graduate degree, work in a state with certification standards, and have 10 or fewer years of experience compared to school social workers in the other two profiles. Additionally, school social workers who reported high levels of ecological practices were more likely to use evidence-based assessments, programs/practices, and engage in universal school-level prevention efforts more frequently compared to those in the low and medium profiles. Practical implications include the need for pre-service and targeted in-service training as well as policies that support minimum—if not lofty—competencies and state or national certification standards for school social work professionals.

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References

  • Akaike, H. (1981). Likelihood of a model and information criteria. Journal of Econometrics, 16(1), 3–14.

    Article  Google Scholar 

  • Allen-Meares, P. (1994). Social work services in schools: A national study of entry-level tasks. Social Work, 39, 560–565.

    Article  Google Scholar 

  • Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. American Psychologist, 32, 513–531.

    Article  Google Scholar 

  • Celeux, G., & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13(2), 195–212.

    Article  Google Scholar 

  • Clark, H. B., & Clarke, R. T. (1996). Research on the wraparound process and individualized services for children with multi-system needs. Journal of Child and Family Studies, 5, 1–5.

    Article  Google Scholar 

  • Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 1–9. http://www.pareonline.net/pdf/v10n7.pdf.

    Google Scholar 

  • Costin, L. B. (1969). An analysis of the tasks in school social work. The Social Service Review, 43, 274–285.

    Article  Google Scholar 

  • Costin, L. B. (1983). School social work. Journal of Education for Social Work, 19(1), 115–117.

    Article  Google Scholar 

  • Eber, L., Sugai, G., Smith, C. R., & Scott, T. M. (2002). Wraparound and positive behavioral interventions and supports in the schools. Journal of Emotional and Behavioral Disorders, 10(3), 171–180.

    Article  Google Scholar 

  • Epstein, M. H., Nordness, P. D., Gallagher, K., Nelson, J. R., Lewis, L., & Schrepf, S. (2005). School as the entry point: Assessing adherence to the basic tenets of the wraparound approach. Behavioral Disorders, 30(2), 85–93.

    Article  Google Scholar 

  • Every Child Succeeds Act of 2015. (2015). Pub. L. No.144-95 §114 1177.

  • Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272.

    Article  Google Scholar 

  • Fraley, C., & Raftery, A. E. (1998). How many clusters? Which clustering method? Answers via model-based cluster analysis. The Computer Journal, 41(8), 578–588.

    Article  Google Scholar 

  • Fraser, M. W., Thompson, A. M., Day, S. H., & Macy, R. J. (2013). The making choices program: Impact of social-emotional skills training on the risk status of third graders. Elementary School Journal, 114, 354–379.

    Article  Google Scholar 

  • Frey, A. J., Alvarez, M. E., Dupper, D. R., Sabatino, C. A., Lindsey, B. C., Raines, J. C., et al. (2013). School social work practice model. London: School Social Work Association of America.

    Google Scholar 

  • Gorsuch, R. L. (1997). Exploratory factor analysis: Its role in item analysis. Journal of Personality Assessment, 68(3), 532–560.

    Article  PubMed  Google Scholar 

  • Individuals with Disabilities Education Improvement Act. (2004). P.L. 108-446, 118 Stat. 2647.

  • Kelly, M. S. (2008). The domains and demands of school social work: A guide to working effectively with students, families and schools. New York: Oxford University Press.

    Book  Google Scholar 

  • Kelly, M. S., Berzin, S. C., Frey, A., Alvarez, M., Shaffer, G., & O’Brien, K. (2010a). The state of school social work: Findings from the national school social work survey. School Ment Health, 2(3), 132–141.

    Article  Google Scholar 

  • Kelly, M. S., Frey, A. J., Alvarez, M., Berzin, S. C., Shaffer, G., & O’Brien, K. (2010b). School social work practice and response to intervention. Children & Schools, 32(4), 201–209.

    Article  Google Scholar 

  • Kelly, M. S., Frey, A., Thompson, A., Klemp, H., Alvarez, M., & Berzin, S. C. (2016). Assessing the national school social work practice model: Findings from the second national school social work survey. Social Work, 61, 17–28. https://doi.org/10.1093/sw/swv044.

    Article  PubMed  Google Scholar 

  • Kelly, M. S., Thompson, A. M., Frey, A., Klemp, H., Alvarez, M., & Berzin, S. C. (2015). The state of school social work: Revisited. School Mental Health, 7, 1–10.

    Article  Google Scholar 

  • Little, R. J., & Rubin, D. B. (1989). The analysis of social science data with missing values. Sociological Methods & Research, 18(2–3), 292–326.

    Article  Google Scholar 

  • Little, R., & Rubin, D. (2002). Statistical analysis with missing data. New York: Wiley.

    Book  Google Scholar 

  • Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767–778.

    Article  Google Scholar 

  • McArdle, J. J. (1990). Principles versus principals of structural factor analyses. Multivariate Behavioral Research, 25(1), 81–87.

    Article  PubMed  Google Scholar 

  • McCoach, D. B., Goldstein, J., Behuniak, P., Reis, S. M., Black, A. C., Sullivan, E. E., et al. (2010). Examining the unexpected: Outlier analyses of factors affecting student achievement. Journal of Advanced Academics, 21(3), 426–468.

    Article  Google Scholar 

  • McLachlan, G., & Peel, D. (2000). Finite mixture models (Vol. 299). Hoboken: Wiley.

    Book  Google Scholar 

  • Muthén, B. (2001). Latent variable mixture modeling. New Developments and Techniques in Structural Equation Modeling, 1–33.

  • Muthén, B., & Muthén, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism, Clinical and Experimental Research, 24(6), 882–891.

    Article  PubMed  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (2013). Mplus 7.11. Los Angeles, CA: Muthén & Muthén.

  • No Child Left Behind Act of 2001. (2002). P.L. 107-110, 115 Stat. 1425.

  • Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535–569.

    Article  Google Scholar 

  • Perfect, M., & Morris, R. (2011). School-based mental health services by school psychologists: Education, training, and ethical issues. Psychology in the Schools, 48, 1049–1063.

    Article  Google Scholar 

  • Phillippo, K. L., Kelly, M. S., Shayman, E., & Frey, A. (2017). School social worker practice decisions: The impact of professional models, training, and school context. Families in Society: The Journal of Contemporary Social Services, 98(4), 275–283.

    Article  Google Scholar 

  • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.

    Article  Google Scholar 

  • Swanson, S. A., Lindenberg, K., Bauer, S., & Crosby, R. D. (2012). A Monte Carlo investigation of factors influencing latent class analysis: An application to eating disorder research. International Journal of Eating Disorders, 45(5), 677–684.

    Article  PubMed  Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics. Boston: Allyn & Bacon.

    Google Scholar 

  • Thompson, A. M., Reinke, W. M., & Herman, K. C. (2014). The value, practice, and evaluation of teaching social emotional learning to students with and without disabilities. In C. R. Massat, M. S. Kelly, & R. Constable (Eds.), School social work: Practice, policy, and research (8th ed.). New York: Oxford.

    Google Scholar 

  • Vrieze, S. I. (2012). Model selection and psychological theory: A discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Psychological Methods, 17(2), 228.

    Article  PubMed  PubMed Central  Google Scholar 

  • Vuong, Q. H. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica: Journal of the Econometric Society, 57, 307–333.

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Social Work, University of Missouri, Columbia, USA

    Aaron M. Thompson

  2. School of Social Work, University of Louisville, Louisville, USA

    Andy J. Frey

  3. School of Social Work, Loyola University Chicago, Chicago, USA

    Mike S. Kelly

Authors
  1. Aaron M. Thompson
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  2. Andy J. Frey
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  3. Mike S. Kelly
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Correspondence to Aaron M. Thompson.

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The authors declare that they have no conflict of interest.

Ethical Approval

The research performed here was approved and overseen by the Institutional Review Board of Loyola University at Chicago.

Human and Animal Rights

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

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Thompson, A.M., Frey, A.J. & Kelly, M.S. Factors Influencing School Social Work Practice: A Latent Profile Analysis. School Mental Health 11, 129–140 (2019). https://doi.org/10.1007/s12310-018-9279-y

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  • DOI: https://doi.org/10.1007/s12310-018-9279-y

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