Project Activities
The research team carried out four studies of PBIS: (1) a retrospective quasi-experimental study leveraging propensity score methods to compare schools that adopted single-tier PBIS with those that did not, (2) a retrospective quasi-experimental study using a regression discontinuity design of middle and high schools that voluntarily adopted single-tier PBIS versus those that were mandated to adopt it, and (3) a randomized control trial comparing elementary and middle schools using a single-tier version of PBIS versus those using a modified two-tiered version (less intensive and expensive than the one being evaluated in high schools), within the context of a broader scale-up effort, and (4) cost analyses of implementing PBIS across multiple tiers, and at the school, district, and state levels.
Structured Abstract
Setting
This project took place in schools in Maryland.
Sample
The first evaluation study drew on the entire population of 1,316 elementary, middle, and high schools in Maryland, of which 859 were trained in single-tier PBIS and 457 were never trained and served as a comparison group using propensity score weighting. The second study included the 410 secondary (middle and high) schools in the state, of which 261 were mandated to implement PBIS and schools with similar truancy rates that had earlier volunteered to implement PBIS. The third study included 779 traditional public schools, a subset of which (N=138) participated in an RCT. The cost analysis drew upon data from various samples of schools within the state to determine the cost of PBIS across the tiers at the school, district, and state levels.
PBIS includes a set of school-wide (tier 1) components that aim to reduce student problem behavior and create a positive school climate. These include (1) establishing positive behavior expectations and rewarding such behavior, (2) providing explicit classroom instruction to students on PBIS, (3) establishing and enforcing a formal behavior violation system, and (4) collecting and using data to identify higher-need students who require further activities (that may include parental involvement). The implementation of these components is supported at the school level by a PBIS team and a PBIS coach who provides training to administration, staff, and the team as well as at the state level by a team that coordinates state and district efforts and provides training for coaches and school teams. The modified version of PBIS, which was evaluated in the third study, additionally included participation in a school-level climate survey, training in the use of the survey data, training in identifying students and subgroups who need additional support, and training in implementing programs to support those students (tier 2 components).
Initial research
The first study is based on retrospective data from school years 2006-2007 through 2011-2012 using autoregressive models. The sample included 1,316 elementary, middle, and high schools. Schools trained in school-wide PBIS (SW-PBIS) demonstrated statistically significant reductions in suspensions and truancy and improvements in reading and math proficiency rates. The second retrospective study used regression discontinuity design to compare student outcomes in 261 schools of the full sample of 410 public middle and high schools to adopt single-tier PBIS. The third study was a scale-up study of PBIS among 779 traditional public schools, which were followed through their implementation of PBIS at the tier 1 and 2 levels across time to examine fidelity and outcomes achieved with regard to reading and math proficiency, suspensions, and truancy rates.
Control condition
For the first retrospective study, students in the comparison group were not expected to have been exposed to PBIS components. For the second retrospective study, students in both groups were expected to have been exposed to single-tier PBIS (the difference being voluntary versus mandated implementation). For the third study, students in the control group had exposure to single-tier PBIS (through voluntary implementation).
Key measures
For the two retrospective studies and third study, the key outcomes included suspensions, attendance, truancy, and scores on the state standardized assessments for reading and math (using both scores and proficiency levels). Fidelity of PBIS implementation was examined using the Implementation Phases Inventory and the Tiered Fidelity Implementation, along with PBIS training data. Data to support the cost analysis included key informant interviews, collection of administrative and archival records data, coaching log data, and review of salary and expenditure data.
Data analytic strategy
For aim 1, the research team used propensity score weights using logistic regression to predict whether a school was exposed to PBIS (for study 1) or volunteered for PBIS (for study 2) based on student composition, suspension, truancy, and achievement data in order to identify comparison schools. Autoregressive models were used to examine outcomes. For aim 2, the team utilized regression discontinuity and growth mixture modeling. For aim 3, researchers conducted longitudinal analyses to examine changes in both fidelity of implementation of tier 1 and tier 2 supports and outcomes over time, including through the COVID-19 pandemic. Aim 4 focused on the cost analyses described below. For the first three studies, researchers used multi-level models to estimate the effects of PBIS on the outcomes and included school and student demographics as covariates (as relevant).
Cost analysis strategy
A series of cost analyses were conducted on PBIS across the tiers, using the ingredients method and shadow pricing. A mixed-methods approach was developed, which included the collection of cost information within the context of fidelity assessment and tracking (Bradshaw et al., 2024). A cost calculator was created and disseminated to facilitate the costing process for researchers and practitioners.
Key outcomes
- For aim 1, the researchers found that schools trained in SW-PBIS demonstrated statistically significant reductions in suspensions and truancy and improvements in reading and math proficiency rates. Significant effects were observed both in elementary and secondary schools for all outcomes except truancy, which was significant in secondary, but not elementary, schools (Pas et al., 2019).
- For aim 2, the researchers utilized regression discontinuity, which allowed them to leverage the clear cut point (i.e., habitual truancy rate of 8% or higher) associated with the policy-driven mandated status and student outcomes and examined the growth trajectories (i.e., improvement) of implementation fidelity over time using growth mixture modeling. Contrary to the intent of the policy to improve student outcomes, the results suggested the mandate did not impact reading and math achievement, truancy rates, or SW-PBIS training in 2010-11 through 2013-14. Mandated schools did have higher suspension rates in 2010-11 through 2013-14 than the non-mandated schools; however, these differences in the suspension rates appear to have persisted from years prior to the mandate. These analyses did not demonstrate a significant impact of the mandate on student outcomes (Bradshaw et al., 2021).
- With regard to the cost findings under aim 4, shadow pricing results indicated that the largest cost savings were associated with improvements in standardized test scores ($138,658 for elementary and $71,444 for secondary). Reductions in elementary students' aggressive and disruptive behavior, as well as bullying behavior, were also significant sources of cost savings ($166,028 in total). These cost-saving benefits were complemented by separate benefits associated with a reduction in suspensions ($33,415 for elementary and $11,361 for secondary school students). There were other cost-related findings regarding truancy, office discipline referrals, and mental health concerns documented. Taken together, these findings illustrate the broad cost savings associated with PBIS tier 1 implementation and scale-up (Bradshaw et al., 2020). Additional peer-reviewed publications documented outcomes for cost-related outcomes at the team, district, and state levels (Lindstrom Johnson et al., 2020) and the coaching and teaming process to discuss student needs for evidence-based practices (Pas et al., 2020).
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
The products of this project included evidence of the efficacy of single-tier PBIS, of mandating its adoption, and of the scale-up of the two-tiered version of PBIS. The results of this project have been shared directly with the Maryland State Department of Education and the local school systems through their participation in project meetings and briefings, and through a series of research briefs available at https://www.pbismaryland.org/resources/research-briefs. Several methodological papers were also generated to inform future studies related to research design, scale-up, research-practice partnerships, and implementation science.
As of December 2025, this project has supported production of 32 peer-reviewed articles, 6 book chapters, and 25 research briefs aimed at practice audiences, and an online cost-calculator for researchers and practitioners to calculate the cost of PBIS across the tiers, along with other evidence-based practices. Several tools were developed to guide the cost process, including an online cost calculator tool (https://www.ruralsmh.com/cost-calculator/), as well as a series of modules to guide the data collection process, inform the use of the cost data, and help practitioners and researchers develop a greater appreciation of the value of cost data.
Publications:
ERIC Citations: Find available citations in ERIC for this award here.
Bottiani, J. H., Kush, J. M., McDaniel, H.L., Pas, E. T., & Bradshaw, C. P. (2023). Are we moving the needle on racial disproportionality? Measurement challenges in evaluating school discipline reforms. American Educational Research Journal, 60(2), 293-329. https://doi.org/10.3102/0002831222114002
Bottiani, J.H., Henderson Smith, L.J., Powers, M.D., Bradshaw, C.P., & Debnam, K.J. (2024). Triangulation of data: Using student, teacher, and parent data to improve school climate. In T.P. LaSalle (Ed.), Creating an inclusive school climate: A school psychology model for supporting marginalized students. Routledge.
Bottiani, J., Lindstrom Johnson, S., McDaniel, H., & Bradshaw, C. (2020). Triangulating school climate: Areas of convergence and divergence across multiple levels and perspectives. American Journal of Community Psychology, 3-4, 423-436. https://doi.org/10.1002/ajcp.
Bradshaw, C.P., & Kush, J.M. (2019). Teacher Observation of Classroom Adaptation-Checklist: Measuring children’s social, emotional, and behavioral functioning. Children & Schools, 42(1), 29-40. https://doi.org/10.1093/cs/cdz022
Bradshaw, C.P., Budavari, A.C., Nguyen, A., Henderson Smith, L. Beahm, L., Pandey, T., & Pas, E.T. (2024). Integrating social and emotional learning and multi-tiered systems of support for behavior: A strategy for optimizing implementation and scale-up of SEL programming. Handbook of Social and Emotional Learning (2nd Ed.): Guilford Press.
Bradshaw, C.P., Cohen, J., Espelage, D.L., & Nation, M. (2023). Improving school climate to optimize youth mental health: Implications for increasing the uptake and outcomes of evidence-based programs. In S. Evans, J. Owens, C.P. Bradshaw, & M.D. Weist (Eds.). Handbook of School Mental Health: Advancing Practice and Research (third edition). New York: Springer.
Bradshaw, C.P., Cohen, J., Espelage, D.L., & Nation, M. (2021). Addressing school safety through comprehensive school climate approaches. School Psychology Review, 50, 221-236. https://doi.org/10.1080/2372966X.2021.1926321
Bradshaw, C., Debnam, K., Kush, J.M., & Lindstrom Johnson, S. (2022). Planning for a crisis, but preparing for every day: What predicts schools’ preparedness to respond to a school safety crisis? Frontiers in Communication, 7, 765336. https://doi.org/10.3389/fcomm.2022.765336
Bradshaw, C.P., Debnam, K.J., Player, D., Bowden, B., & Lindstrom Johnson, S. (2023). A mixed-methods approach for embedding cost-analysis within fidelity assessment in school-based programs. Behavioral Disorders, 48(3), 174–186. https://doi.org/10.1177/0198742920944850
Bradshaw, C. P., Kush, J. M., Braun, S. S., & Kohler, E. A. (2024). The perceived effects of the onset of the COVID-19 pandemic: A focus on educators’ perceptions of the negative effects on educator stress and student wellbeing. School Psychology Review, 53(1), 82-95. https://doi.org/10.1080/2372966X.2022.2158367.
Bradshaw, C.P., Lindstrom Johnson, S., & Goodman, S. (2021). Leveraging findings on the cost of Positive Behavioral Interventions and Supports to inform decision making by leaders in special education programming. Journal of Special Education Leadership 34(1), 47-56.
Bradshaw, C. P, Lindstrom Johnson, S. Zhu, Y., & Pas. E. T. (2020). Scaling-up behavioral health promotion efforts in Maryland: The economic benefit of Positive Behavioral Interventions and Supports. School Psychology Review, 50(1), 99-109. https://doi.org/10.1080/2372966X.2020.1823797.
Bradshaw, C. P., Pas, E., Musci, R., Kush, J., & Ryoo, J. H. (2021). Can policy promote adoption or outcomes of evidence-based prevention programming?: A case illustration of Positive Behavioral Interventions and Supports. Prevention Science, 22, 986-1000. https://doi.org/10.1007/s11121-021-01257-0
Chung, E., Bottiani, J., Francis, M., & Bradshaw, C.P. (2025). Associations between culturally responsive teaching practices and student-teacher connectedness: A multi-informant examination. Psychology in the Schools, 62(11), 4692-4701. https://doi.org/10.1002/pits.70032.
Debnam, K. J., Milam, A. J., Bottiani, J. H., & Bradshaw, C. P. (2021). Teacher‐student incongruence in perceptions of school equity: Associations with student connectedness in middle and high schools. Journal of School Health, 91(9), 706-713. http://doi.org/10.1111/josh.13062
Fu, R., Perepezko, A.L., Bradshaw, C.P. & Waasdorp, T.E. (2023). Race-based bullying victimization and adjustment difficulties: Racial-ethnic differences in the protective role of school equity. International Journal of Bullying Prevention. https://doi.org/10.1007/s42380-023-00175-9.
Fu, R., Perepezko, A.L., Randolph, J. A., Bradshaw, C.P. & Waasdorp, T.E. (2025). Parent perceptions of school relationships: Considerations of racial-ethnic differences and youth’s peer victimization. Journal of Family Psychology, 39(2), 252-262. DOI: 10.1037/fam0001243
Fu, R., Waasdorp, T.E., Randolph, J.A., & Bradshaw, C.P. (2021). Peer Victimization and mental health problems: racial-ethnic differences in the buffering role of academic performance. Journal of Youth and Adolescence, 50, 1839–1855. 10.1007/s10964-021-01483-3
Henderson, L., Bottiani, J.H., Kush, J., & Bradshaw, C.P. (2023). The discipline gap in context: The role of school racial and ethnic diversity in out-of-school suspensions. Journal of School Psychology, 98, 61-77. https://doi.org/10.1016/j.jsp.2023.02.006
Kush, J. M., Konold, T. R., & Bradshaw, C.P. (2022). The sampling ratio in multilevel structural equation models: Considerations to inform study design. Educational and Psychological Measurement, 82(3), 409–443. https://doi.org/10.1177/00131644211020112
Kush, J. M., Konold, T. R., & Bradshaw, C.P. (2021). Statistical power for randomized controlled trials with clusters of varying size. Journal of Experimental Education, 90(3), 673-692. https://doi.org/10.1080/00220973.2021.1873089
Kush, J., Pas, E.T., Musci, R., & Bradshaw, C.P. (2022). Covariate balance for observational effectiveness studies: A comparison of matching and weighting. Journal of Research on Educational Effectiveness. https://doi.org/10.1080/19345747.2022.2110545
Larson, K. E., Bottiani, J., Pas, E. T., & Bradshaw, C. P. (2019). A multilevel analysis of racial discipline disproportionality: A focus on student perceptions of academic engagement and disciplinary environment. Journal of School Psychology, 77, 152-167. https://doi.org/10.1016/j.jsp.2019.09.003
Lindstrom Johnson, S., Alfonso, Y.N., Pas, E. T., Debnam, K. J., & Bradshaw, C. P. (2020). Scaling-up PBIS: Costs and their distribution across states, districts, and schools. School Psychology Review, 49(4), 399-414. https://doi.org/10.1080/2372966X.2020.1777831
Lindstrom Johnson, S., Bowden, B., & Bradshaw, C.P. (2023). Estimating the cost of school mental health programming to increase adoption and scale-up of evidence-based programs and practices. In S. Evans, J. Owens, C.P. Bradshaw, & M.D. Weist, M.D. (Eds.). Handbook of School Mental Health: Advancing Practice and Research (third edition). New York: Springer.
Lindstrom Johnson, S., Low, S., & Bradshaw, C.P. (2018). Challenges and priorities for practitioners and policy makers (pp. 432-449). In T. Malti & K. H. Rubin (Eds.) Handbook of Child and Adolescent Aggression. New York: Guilford.
Lindstrom Johnson, S., Reichenberg, R. E., Shukla, K., Waasdorp, T. E., & Bradshaw, C. P. (2019). Improving the measurement of school climate using item response theory. Educational Measurement: Issues and Practice, 38 (4), 99-107. doi: https://doi.org/10.1111/empi.12296
Musci, R. J., Kush, J., Pas, E. T., & Bradshaw, C. P. (2024). Class enumeration in mixture modeling with nested data: A brief report. Journal of Experimental Education, 1-10. https://doi.org/10.1080/00220973.2024.2386983
O'Brennan, L., Pas, E., and Bradshaw, C. (2017). Multilevel Examination of Burnout Among High School Staff: Importance of Staff and School Factors. School Psychology Review, 46(2), 165-176.
Pas, E. T., Johnson, S. R., Debnam, K. J., Hulleman, C., & Bradshaw, C. P. (2019). Examining the relative utility of PBIS implementation fidelity scores in relation to student outcomes. Remedial and Special Education, 40(1), 6-15. https://doi.org/10.1177/0741932518805192
Pas, E., Lindstrom Johnson, S., Alfonso, Y.N., & Bradshaw, C.P. (2020). Tracking time and resources associated with systems change and the adoption of evidence-based programs: The “hidden costs” of school-based coaching. Administration and Policy in Mental Health and Mental Health Services Research, 47, 720-734. https://doi.org/10.1007/s10488-020-01039-w
Pas, E.T., Ryoo, J.H., Musci, R., & Bradshaw, C. P. (2019). The effects of a state-wide scale-up of school-wide Positive Behavior Intervention and Supports on behavioral and academic outcomes: A quasi-experimental examination. Journal of School Psychology, 73(1), 41-55. https://doi.org/10.1016/j.jsp.2019.03.001.
Pérez, P., Beahm, L Pandey, T. Lindstrom Johnson, S., & Bradshaw, C.P., (2025). Measuring the Impact of PBIS through Multiple Metrics: Mapping Outcomes to Cost Savings. (Eds.). Lewis, T., Simonsen, B., McIntosh, K., G., & George, H. Handbook of Positive Behavior Supports (2nd ed).
Sheras, P.L., and Bradshaw, C.P. (2016). Fostering Policies That Enhance Positive School Environment. Theory Into Practice, 55(2), 129-135.
Waasdorp, T.E., Fu, R., Clary, L., & Bradshaw, C.P. (2022). School climate and bullying bystander responses in middle and high school. Journal of Applied Developmental Psychology, 80. https://doi.org/10.1016/j.appdev.2022.101412
Waasdorp, T.E., Lindstrom Johnson, S., Shukla, K., & Bradshaw, C.P. (2019). Measuring school climate: Invariance across middle and high school students. Children & Schools, 42(1), 53-62. doi: https://doi.org/10.1093/cs/cdz026
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