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A Multi-Level Framework to Understand Factors Influencing Program Implementation in Schools

A Multi-Level Framework to Understand Factors Influencing Program Implementation in Schools. Celene E. Domitrovich, Ph.D. Penn State Prevention Research Center Implementation Methods Meeting September 20, 2010. Co-Authors & Funding.

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A Multi-Level Framework to Understand Factors Influencing Program Implementation in Schools

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  1. A Multi-Level Framework to Understand Factors Influencing Program Implementation in Schools Celene E. Domitrovich, Ph.D. Penn State Prevention Research Center Implementation Methods Meeting September 20, 2010

  2. Co-Authors & Funding Domitrovich, C. E., Bradshaw, C. P., Poduska, J. M., Hoagwood, K., Buck;ey, J. A., Olin, S., Romanelli, L. H., Leaf, P. J., Greenberg, M. T., & Ialongo, N. (2008). Maximizing the implementation quality of evidence-based preventive interventions in schools: A conceptual framework. Advances in School Mental Health Promotion, 1, 6-28. NIMH and NIDA (P30 MH06624) CDC (1U49CE 000728 and K01 CE001333-01) NIDA (R01 DA019984)

  3. Current Challenges • Broad dissemination and“going to scale” with evidence-based intervention • Maintaining effectiveness under “real-world conditions • Understanding the factors that promote or undermine implementation quality throughout the dissemination process

  4. General Definition of Implementation: What an intervention consists of in practice and the degree to which it was conducted as it was originally intended (Durlak, 1995; Yeaton & Sechrest, 1981)

  5. Defining the Model: Intervention • Core Elements • Standardization • Delivery Support System • Core Elements • Standardization • Delivery

  6. Planned vs. Actual Intervention

  7. Planned vs. Actual Support System

  8. Measuring the Quality of the Intervention and Support System • Adherence/Fidelity • Dosage • Quality of Delivery

  9. Factors Outside the Model:

  10. Factors Outside the Implementation Model • Individual Level • Professional & Psychological Characteristics • Intervention Perceptions & Attitudes • School Level • Resources, Administrative Leadership and Support • Classroom Climate, School Characteristics • Macro Level • Policies & Financing • Leadership & Human Capital • University/Community Partnerships

  11. Critical Issue #1: Non-linear process • There are stages to the diffusion of innovations • Implementation quality is critical throughout but very few studies have measured it over time • The factors that support or undermine the process may be more or less relevant at each stage

  12. Critical Issue #2: Factors Interact • Factors associated with implementation quality cannot be examined in isolation • They interact both within and across levels • In order to understand how these factors influence one another, we need multiple measures assessed simultaneously and over time. • Large sample sizes are need to address this and many other implementation research challenges

  13. Critical Issue #3: Measurement • There are different potential sources of implementation data • They vary in how cost effective they are to collect • We know very little about who can assess what , when it should be measured, which measures are the most important, and how often implementation quality should be assessed.

  14. Critical Issue #4: Lack of randomization • Most studies of implementation examine associations between factors and implementation or between implementation and target outcomes within the intervention group which limits conclusions that can be drawn. • Interventions often have unique components or processes that are difficult to assess in the control group. Measures that can be used in both conditions provide a way to preserve the RCT design • Very few studies actually test theories of implementation by manipulating implementation itself or factors outside the process in randomized trials

  15. Critical Issue #5: Multi-component or Integrated Interventions • The field is moving towards the use of integrated and adaptive interventions that present unique implementation challenges. • How do we capture quality when multiple implementers are involved in the delivery of an intervention? • How do we understand implementation in the context of interventions where different participants receive different components?

  16. Future Directions • Theory-driven research • Implementation interventions • Understanding adaptation • Improved Measurement • Statistical strategies to address challenges

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