Advertisement

Provider Readiness and Adaptations of Competency Drivers During Scale-Up of the Family Check-Up

  • Anne Marie Mauricio
  • Jenna Rudo-Stern
  • Thomas J. Dishion
  • Kirsten Letham
  • Monique Lopez
Original Paper

Abstract

We used provider (n = 112) data that staff at the agency disseminating the Family Check-Up (FCU; REACH Institute) collected to profile provider diversity in community settings and to examine whether provider profiles are related to implementation fidelity. Prior to FCU training, REACH Institute staff administered the FCU Provider Readiness Assessment (PRA), a provider self-report measure that assesses provider characteristics previously linked with provider uptake of evidence-based interventions. We conducted a latent class analysis using PRA subscale scores as latent class indicators. Results supported four profiles: experienced high readiness (ExHR), experienced low readiness (ExLR), moderate experience (ME), and novice. The ExHR class was higher than all other classes on: (1) personality variables (i.e., agreeableness, conscientiousness, openness, extraversion); (2) evidence-based practice attitudes; (3) work-related enthusiasm and engagement; and (4) their own well-being. The ExHR class was also higher than ExLR and ME classes on clinical flexibility. The ME class was lowest of all classes on conscientiousness, supervision, clinical flexibility, work-related enthusiasm and engagement, and well-being. During the FCU certification process, FCU Consultants rated providers’ fidelity to the model. Twenty-three of the 112 providers that completed the PRA also participated in certification. We conducted follow-up regression analyses using fidelity data for these 23 providers to explore associations between probability of class membership and fidelity. The likelihood of being in the ExHR class was related to higher FCU fidelity, whereas the likelihood of being in the ExLR class was related to lower fidelity. We discuss how provider readiness assessment data can be used to guide the adaptation of provider selection, training, and consultation in community settings.

Keywords

Provider profiles Implementation Readiness Adaptation Competency drivers 

Notes

Compliance With Ethical Standards

Conflict of Interest

Dr. Thomas Dishion is the developer of the Family Check-Up. Dr. Anne M. Mauricio is an Associate Research Professor at the Arizona State University REACH Institute, and Mrs. Letham and Lopez are staff at the REACH Institute. The authors declare that they have no other conflicts of interest.

Research Involving Human Participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of Arizona State University’s IRB and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed Consent

We obtained informed consent from all individual participants included in the study.

References

  1. Aarons, G. A. (2004). Mental health provider attitudes toward adoption of evidence-based practice: The Evidence-Based Practice Attitude Scale (EBPAS). Mental Health Services Research, 6(2), 61–74.  https://doi.org/10.1023/B:MHSR.0000024351.12294.65.CrossRefGoogle Scholar
  2. Aarons, G. A., Fettes, D. L., Flores, L. E., Jr., & Sommerfeld, D. H. (2009). Evidence-based practice implementation and staff emotional exhaustion in children’s services. Behaviour Research and Therapy, 47(11), 954–960.  https://doi.org/10.1016/j.brat.2009.07.006.CrossRefGoogle Scholar
  3. Aarons, G. A., Hurlburt, M., & Horwitz, S. M. (2011). Advancing a conceptual model of evidence-based practice implementation in public service sectors. Administration Policy in Mental Health and Mental Health Services Research, 38(1), 4–23.  https://doi.org/10.1007/s10488-010-0327-7.CrossRefGoogle Scholar
  4. August, G. J., Winters, K. C., Realmuto, G. M., Tarter, R., Perry, C., & Hektner, J. M. (2004). Moving evidence-based drug abuse prevention programs from basic science to practice: “Bridging the efficacyeffectiveness interface”. Substance Use & Misuse, 39(10–12), 2017–2053.CrossRefGoogle Scholar
  5. Beidas, R. S., Edmunds, J., Ditty, M., Watkins, J., Walsh, L., Marcus, S., et al. (2014). Are inner context factors related to implementation outcomes in cognitive-behavioral therapy for youth anxiety? Administration and Policy in Mental Health and Mental Health Services Research, 41(6), 788–799.  https://doi.org/10.1007/s10488-013-0529-x.CrossRefGoogle Scholar
  6. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246.  https://doi.org/10.1037/0033-2909.107.2.238.CrossRefGoogle Scholar
  7. Campbell, B. K., Buti, A., Fussell, H. E., Srikanth, P., McCarty, D., & Guydish, J. R. (2013). Therapist predictors of treatment delivery fidelity in a community-based trial of 12-step facilitation. The American Journal of Drug and Alcohol Abuse, 39(5), 304–311.  https://doi.org/10.3109/00952990.2013.799175.CrossRefGoogle Scholar
  8. Chambers, D. A., Glasgow, R., & Stange, K. (2013). The dynamic sustainability framework: Addressing the paradox of sustainment amid ongoing change. Implementation Science, 8(1), 117–128.  https://doi.org/10.1186/1748-5908-8-117.CrossRefGoogle Scholar
  9. Chang, H., Shaw, D. S., Dishion, T. J., Gardner, F., & Wilson, M. N. (2014). Direct and indirect effects of the Family Check-Up on self-regulation from toddlerhood to early school-age. Journal of Abnormal Child Psychology, 42(7), 1117–1128.  https://doi.org/10.1007/s10802-014-9859-8.CrossRefGoogle Scholar
  10. Demerouti, E., Mostert, K., & Bakker, A. B. (2010). Burnout and work engagement: A thorough investigation of the independency of both constructs. Journal of Occupational Health Psychology, 15(3), 209–222.  https://doi.org/10.1037/a0019408.CrossRefGoogle Scholar
  11. Dishion, T. J., Connell, A., Weaver, C., Shaw, D., Gardner, F., & Wilson, M. (2008). The Family Check-Up with high-risk indigent families: Preventing problem behavior by increasing parents’ positive behavior support in early childhood. Child Development, 79(5), 1395–1414.  https://doi.org/10.1111/j.1467-8624.2008.01195.x.CrossRefGoogle Scholar
  12. Dishion, T. J., & Kavanagh, K. (2003). Intervening in adolescent problem behavior: A family-centered approach. New York: Guilford Press.Google Scholar
  13. Dishion, T. J., Knutson, N., Brauer, L., Gill, A., & Risso, J. (2010). Family check-up: COACH ratings manual. Unpublished coding manual. Available from Child and Family Center.Google Scholar
  14. Dishion, T. J., Nelson, S. E., & Kavanagh, K. (2003). The Family Check-Up with high-risk young adolescents: Preventing early-onset substance use by parent monitoring. Behavior Therapy, 34(4), 553–571.  https://doi.org/10.1016/S0005-7894(03)80035-7.CrossRefGoogle Scholar
  15. Dishion, T. J., & Stormshak, E. A. (2007). Intervening in children’s lives: An ecological, family-centered approach to mental health care. Washington, DC: American Psychological Association.  https://doi.org/10.1037/11485-000.CrossRefGoogle Scholar
  16. Dishion, T. J., Stormshak, E. A., & Kavanagh, K. A. (2012). Everyday parenting: A professional’s guide to building family management skills. Champaign: Research Press Publishers.Google Scholar
  17. Fixsen, D. L., Blase, K. A., Naoom, S. F., & Wallace, F. (2009). Core implementation components. Research on Social Work Practice, 19(5), 531–540.  https://doi.org/10.1177/1049731509335549.CrossRefGoogle Scholar
  18. Forehand, R., Dorsey, S., Jones, D. J., Long, N., & McMahon, R. J. (2010). Adherence and flexibility: They can (and do) coexist! Clinical Psychology: Science and Practice, 17(3), 258–264.  https://doi.org/10.1111/j.1468-2850.2010.01217.x.Google Scholar
  19. Goldberg, L. R. (1990). An alternative” description of personality”: The big-five factor structure. Journal of Personality and Social Psychology, 59(6), 1216–1229.  https://doi.org/10.1037/0022-3514.59.6.1216.CrossRefGoogle Scholar
  20. Hemmelgarn, A. L., Glisson, C., & James, L. R. (2006). Organizational culture and climate: Implications for services and interventions research. Clinical Psychology: Science and Practice, 13(1), 73–89.  https://doi.org/10.1111/j.1468-2850.2006.00008.x.Google Scholar
  21. Kakeeto, M., Lundmark, R., Hasson, H., & Thiele Schwarz, U. (2017). Meeting patient needs trumps adherence. A cross-sectional study of adherence and adaptations when national guidelines are used in practice. Journal of Evaluation in Clinical Practice, 23(4), 830–838.  https://doi.org/10.1111/jep.12726.CrossRefGoogle Scholar
  22. Kilbourne, A. M., Neumann, M. S., Pincus, H. A., Bauer, M. S., & Stall, R. (2007). Implementing evidence-based interventions in health care: Application of the replicating effective programs framework. Implementation Science, 2, 1–10.  https://doi.org/10.1186/1748-5908-2-42.CrossRefGoogle Scholar
  23. Klimes-Dougan, B., August, G. J., Lee, C. Y. S., Realmuto, G. M., Bloomquist, M. L., Horowitz, J. L., et al. (2009). Practitioner and site characteristics that relate to fidelity of implementation: The Early Risers prevention program in a going-to-scale intervention trial. Professional Psychology: Research and Practice, 40(5), 467–475.  https://doi.org/10.1037/a0014623.CrossRefGoogle Scholar
  24. Lewis, C., Darnell, D., Kerns, S., Monroe-DeVita, M., Landes, S. J., Lyon, A. R., et al. (2016). Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: Advancing efficient methodologies through community partnerships and team science. Implementation Science, 11(1), 85.  https://doi.org/10.1186/s13012-016-0428-0.CrossRefGoogle Scholar
  25. Little, R. J. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202.  https://doi.org/10.1080/01621459.1988.10478722.CrossRefGoogle Scholar
  26. Mahrer, A. R. (2005). Empirically supported therapies and therapy relationships: What are the serious problems and plausible alternatives? Journal of Contemporary Psychotherapy, 35, 3–25.  https://doi.org/10.1007/s10879-005-0800-x.CrossRefGoogle Scholar
  27. Muthén, L. K., & Muthén, B. O. (1998–2011). Mplus user’s guide (6th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
  28. Nelson, T. D., & Steele, R. G. (2007). Predictors of practitioner self-reported use of evidence-based practices: Practitioner training, clinical setting, and attitudes toward research. Administration and Policy in Mental Health and Mental Health Services Research, 34(4), 319–330.  https://doi.org/10.1007/s10488-006-0111-x.CrossRefGoogle Scholar
  29. O’Connell, M. E., Boat, T., & Warner, K. E. (2009). Committee on the prevention of mental disorders and substance abuse among children, youth, and young adults: Research advances and promising interventions. In Preventing mental, emotional, and behavioral disorders among young people: Progress and possibilities.Google Scholar
  30. Salyers, M. P., Fukui, S., Rollins, A. L., Firmin, R., Gearhart, T., Noll, J. P., et al. (2015). Burnout and self-reported quality of care in community mental health. Administration and Policy in Mental Health and Mental Health Services Research, 42(1), 61–69.  https://doi.org/10.1007/s10488-014-0544-6.CrossRefGoogle Scholar
  31. Schoenwald, S. K., Sheidow, A. J., & Chapman, J. E. (2009). Clinical supervision in treatment transport: Effects on adherence and outcomes. Journal of Consulting and Clinical Psychology, 77(3), 410–421.  https://doi.org/10.1037/a0013788.CrossRefGoogle Scholar
  32. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464.  https://doi.org/10.1214/aos/1176344136.CrossRefGoogle Scholar
  33. Sclove, S. L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52, 333–343.  https://doi.org/10.1007/BF02294360.CrossRefGoogle Scholar
  34. Shaw, D. S., Connell, A., Dishion, T. J., Wilson, M. N., & Gardner, F. (2009). Improvements in maternal depression as a mediator of intervention effects on early childhood problem behavior. Development and Psychopathology, 21(2), 417–439.  https://doi.org/10.1017/S0954579409000236.CrossRefGoogle Scholar
  35. Skriner, L. C., Wolk, C. B., Stewart, R. E., Adams, D. R., Rubin, R. M., Evans, A. C., et al. (2017). Therapist and organizational factors associated with participation in evidence-based practice initiatives in a large urban publicly-funded mental health system. The Journal of Behavioral Health Services & Research.  https://doi.org/10.1007/s11414-017-9552-0.Google Scholar
  36. Smith, J. D., Dishion, T. J., Shaw, D. S., & Wilson, M. N. (2013). Indirect effects of fidelity to the family check-up on changes in parenting and early childhood problem behaviors. Journal of Consulting and Clinical Psychology, 81(6), 962–974.  https://doi.org/10.1037/a0033950.CrossRefGoogle Scholar
  37. Smith, J. D., Rudo-Stern, J., Dishion, T. J., Stormshak, E. A., Montag, S., Brown, K., et al. (in press). A quasi-experimental study of the effectiveness and efficiency of observationally assessing fidelity to a family-centered intervention. Journal of Clinical Child and Adolescent Psychology.Google Scholar
  38. Steiger, J. (1989). Causal modeling: A supplementary module for SYSTAT and SYGRAPH. Evanston, IL: Systat.Google Scholar
  39. Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1–10.  https://doi.org/10.1007/BF02291170.CrossRefGoogle Scholar
  40. Van Ryzin, M. J., & Dishion, T. J. (2012). The impact of a family-centered intervention on the ecology of adolescent antisocial behavior: Modeling developmental sequelae and trajectories during adolescence. Development and Psychopathology, 24(03), 1139–1155.  https://doi.org/10.1017/S0954579412000582.CrossRefGoogle Scholar
  41. Van Ryzin, M. J., Stormshak, E. A., & Dishion, T. J. (2012). Engaging parents in the family check-up in middle school: Longitudinal effects on family conflict and problem behavior through the high school transition. Journal of Adolescent Health, 50(6), 627–633.  https://doi.org/10.1016/j.jadohealth.2011.10.255.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Psychology, REACH InstituteArizona State University (ASU)TempeUSA

Personalised recommendations