A pragmatic clinical effectiveness trial of a novel alternative to punishment for school-based substance use infractions: study protocol for the iDECIDE curriculum

Caroline A Gray, Vanessa Iroegbulem, Brooklyn Deming, Rebecca Butler, Dan Howell, Michael P Pascale, Alec Bodolay, Kevin Potter, Amy Turncliff, Stacey Lynch, Jennie Whittaker, Julia Ward, Devin Maximus, Gladys N Pachas, Randi M Schuster, Caroline A Gray, Vanessa Iroegbulem, Brooklyn Deming, Rebecca Butler, Dan Howell, Michael P Pascale, Alec Bodolay, Kevin Potter, Amy Turncliff, Stacey Lynch, Jennie Whittaker, Julia Ward, Devin Maximus, Gladys N Pachas, Randi M Schuster

Abstract

Background: Adolescents who use alcohol and other drugs on school campuses are at heightened risk for adverse consequences to their health and wellbeing. Schools have historically turned to punitive approaches as a first-line response to substance use. However, punishment is an ineffective deterrent for substance use and may cause harm and increase inequities. iDECIDE (Drug Education Curriculum: Intervention, Diversion, and Empowerment) was developed as a scalable and youth-centered drug education and diversion program that can be used as a skills-based alternative to punishment. We aim to evaluate the effectiveness of the iDECIDE curriculum as an alternative to punishment (ATP) for school-based substance use infractions in the context of a large pragmatic clinical effectiveness study.

Methods: We will conduct a Type 1, hybrid effectiveness-implementation trial. Using a stepped wedge design with approximately 90 middle and high schools in Massachusetts, we will randomly allocate the timing of implementation of the iDECIDE curriculum compared to standard disciplinary response over approximately 36 months. We will test the overarching hypothesis that student-level outcomes (knowledge of drug effects and attitudes about substance use; frequency of substance use; school connectedness) improve over time as schools transition from a standard disciplinary response to having access to iDECIDE. The secondary aims of this trial are to (1) explore whether change in student-level outcomes vary according to baseline substance use, number of peers who use alcohol or other drugs, age, gender, and school urbanicity, and (2) determine the acceptability and feasibility of the iDECIDE curriculum through qualitative stakeholder interviews.

Discussion: Substance use continues to be a major and rapidly evolving problem in schools. The importance of moving away from punishment to more restorative approaches is widely accepted; however, scalable alternatives have not yet been identified. This will be the first study to our knowledge to systematically evaluate an ATP for students who violate the school substance use policy and is well poised to have important implications for policy making.

Keywords: alternatives to punishment; diversion programs; equity; prevention; school; substance use.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2023 Gray, Iroegbulem, Deming, Butler, Howell, Pascale, Bodolay, Potter, Turncliff, Lynch, Whittaker, Ward, Maximus, Pachas and Schuster.

Figures

Figure 1
Figure 1
Stepped wedge schema.

References

    1. Miech RA, Johnston LD, Patrick ME, O'Malley PM, Bachman JG, Schulenberg, JE. Monitoring the Future National Survey Results on Drug Use, 1975-2022: Secondary School Students. Ann Arbor, MI: Institute for Social Research, The University of Michigan. (2023).
    1. Student, Discipline Statewide Report. 2021-22 Student Discipline Statewide Report–All Offenses–All Students. Available online at: (accessed, 2022).
    1. Tavakolian HR, Howell N. Dropout dilemma and interventions. Global Educ J. (2012) 1:77–81.
    1. Dudovitz RN, McCoy K, Chung PJ. At-school substance use as a marker for serious health risks. Acad Pediatr. (2015) 15:41–6. 10.1016/j.acap.2014.06.022
    1. Hemphill SA, Heerde JA, Herrenkohl TI, Toumbourou JW, Catalano RF. The impact of school suspension on student tobacco use: a longitudinal study in Victoria, Australia, and Washington State, United States. Health Educ Behav. (2012) 39:45–56. 10.1177/1090198111406724
    1. Hemphill SA, Herrenkohl TI, Plenty SM, Toumbourou JW, Catalano RF, McMorris BJ. Pathways from school suspension to adolescent nonviolent antisocial behavior in students in Victoria, Australia and Washington State, United States: pathways from school suspension to antisocial behavior. J Community Psychol. (2012) 40:301–18. 10.1002/jcop.20512
    1. Truth Initiative. Discipline Is Not the Answer: Better Approaches to On-campus Student Tobacco Use. Available online at:
    1. Kelly AB, Evan-Whipps T, Smith R, Chan G, Toumbourou JW, Patton GC, et al. . A longitudinal study of the association of adolescent polydrug use, alcohol use and high school non-completion. Addiction. (2015) 110:627–35. 10.1111/add.12829
    1. Arcia E. Achievement and enrollment status of suspended students: outcomes in a large, multicultural school district. Educ Urban Soc. (2006) 38:359–69. 10.1177/0013124506286947
    1. Noltemeyer AL, Ward RM, Mcloughlin C. Relationship between school suspension and student outcomes: a meta-analysis. School Psych Rev. (2015) 44:224–40. 10.17105/spr-14-0008.1
    1. Skiba RJ, Rausch MK. Zero tolerance, suspension, and expulsion: Questions of equity and effectiveness. In: Handbook of classroom management. London: Routledge; (2013) p. 1073–1100.
    1. Jones EP, Margolius M, Rollock M, Yan CT, Cole ML, Zaff JF. Disciplined and disconnected: how students experience exclusionary discipline in minnesota and the promise of non-exclusionary alternatives. In: America's Promise Alliance. Washington, DC (2018).
    1. Mendez LMR, Knoff HM. Who gets suspended from school and why: a demographic analysis of schools and disciplinary infractions in a large school district. Educ Treat Child. (2003) 26:30–51. Available online at:
    1. Finn KV, Willert HJ. Alcohol and drugs in schools: teachers' reactions to the problem. Phi Delta Kappan. (2006) 88:37–40. 10.1177/003172170608800108
    1. Balfanz R, Fox J. Sent home and put off-track: the antecedents, disproportionalities, and consequences of being suspended in the ninth grade. J Appl Res Child. (2014) 5:13. 10.58464/2155-5834.1217
    1. Hemphill SA, Plenty SM, Herrenkohl TI, Toumbourou JW, Catalano RF. Student and school factors associated with school suspension: a multilevel analysis of students in Victoria, Australia and Washington State, United States. Child Youth Serv Rev. (2014) 36:187–94. 10.1016/j.childyouth.2013.11.022
    1. Okonofua JA, Walton GM, Eberhardt JL, A. vicious cycle: a social–psychological account of extreme racial disparities in school discipline. Perspect Psychol Sci. (2016) 11:381–98. 10.1177/1745691616635592
    1. Blum R. School Connectedness: Improving the Lives of Students. Baltimore, MD: (2005).
    1. National Association of School Psychologists . Zero tolerance and Alternative Strategies: A Fact Sheet for Educators and Policymakers. (2008). Available online at: (accessed, 2008).
    1. Benson PL, Scales PC, Hamilton SF, Sesma A. Positive youth development: theory, research, and applications. In: Handbook of Child Psychology. Baltimore, MD: (2006).
    1. Liu J, Butler R, Turncliff A, Gray C, Lynch S, Whittaker J, et al. . (in press). An urgent need for school-based diversion programs for adolescent substance use: a statewide survey of school personnel. J Adolesc Health. (2023). 10.1016/j.jadohealth.2023.04.006
    1. US Department of Education . 2015–2016 Civil Rights Data Collection: School Climate and Safety. Washington, DC (2018).
    1. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. (2012) 50:217–26. 10.1097/MLR.0b013e3182408812
    1. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. . Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. (2011) 38:65–76. 10.1007/s10488-010-0319-7
    1. Moher D. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. JAMA. (2001) 285:1987. 10.1001/jama.285.15.1987
    1. Moher D, Schulz KF, Altman DG. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials. Lancet. (2001) 357:1191–4. 10.1016/S0140-6736(00)04337-3
    1. Moher D Schulz KF Altman DG and for the CONSORT Group* . The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. Ann Intern Med. (2001) 134:657. 10.7326/0003-4819-134-8-200104170-00011
    1. Moher D, Schulz KF, Altman DG. The CONSORT statement: revised recommendations for improving the quality of reports of parallel group randomized trials. BMC Med Res Methodol. (2001) 1:2. 10.1186/1471-2288-1-2
    1. Chan A-W, Tezlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, et al. . SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. (2013) 158:200. 10.7326/0003-4819-158-3-201302050-00583
    1. Chan A-W, Tezlaff J, Gøtzsche PC, Altman D, Mann H, Berlin J, et al. . SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. (2013) 346:e7586–e7586. 10.1136/bmj.e7586
    1. Dutilh G, Sarafoglou A, Wagenmakers E-J. Flexible yet fair: blinding analyses in experimental psychology. Synthese. (2021) 198:5745–72. 10.1007/s11229-019-02456-7
    1. DESE. Multi-Tiered System of Support (MTSS)–Systems for Student Success Office. Available online at: (accessed, 2020).
    1. Sobell L, Sobell M, Buchan G. Timeline Followback Method (Drugs, Cigarettes, and Marijuana). Lauderdale, FL (1996).
    1. Robinson SM, Sobell LC, Sobell MB, Leo GI. Reliability of the Timeline Followback for cocaine, cannabis, and cigarette use. Psychol Addict Behav. (2014) 28:154–62. 10.1037/a0030992
    1. Paolillo EW, et al. . NIH Toolbox® emotion batteries for children: factor-based composites and norms. Assessment. (2020) 27:607–20. 10.1177/1073191118766396
    1. Babakhanyan I, McKenna BS, Casaletto KB, Nowinski CJ, Heaton RK. National institutes of health toolbox emotion battery for english- and spanish-speaking adults: normative data and factor-based summary scores. Patient Relat Outcome Meas. (2018) 9:115–27. 10.2147/PROM.S151658
    1. Srinivasan S, Goldhammer H, Crall C, Kitts R, Keuroghlian AS. A novel medical student elective course in lesbian, gay, bisexual, transgender, queer, intersex, asexual, and sexually and gender diverse health: training tomorrow's physician-leaders. LGBT Health. (2022) 10:252–7. 10.1089/lgbt.2022.0161
    1. Fisher CB, Wallace SA, Fenton RE. Discrimination distress during adolescence. J Youth Adolesc. (2000) 29:679–95. 10.1023/A:1026455906512
    1. Kelleher C. Minority stress and health: Implications for lesbian, gay, bisexual, transgender, and questioning (LGBTQ) young people. Couns Psychol Q. (2009) 22:373–9. 10.1080/09515070903334995
    1. Kelleher I, Harley M, Murtagh A, Cannon M. Are screening instruments valid for psychotic-like experiences? A validation study of screening questions for psychotic-like experiences using in-depth clinical interview. Schizophr Bull. (2011) 37:362–9. 10.1093/schbul/sbp057
    1. Nock MK, Holmberg EB, Photos VI, Michel BD. Self-injurious thoughts and behaviors interview: development, reliability, and validity in an adolescent sample. Psychol Assess. (2007) 19:309–17. 10.1037/1040-3590.19.3.309
    1. Nock MK, Wedig MM, Holmberg EB, Hooley JM. The emotion reactivity scale: development, evaluation, and relation to self-injurious thoughts and behaviors. Behav Ther. (2008) 39:107–16. 10.1016/j.beth.2007.05.005
    1. Research, C. for D. E. and. Non-Inferiority Clinical Trials. US Food and Drug Administration. Available online at: (accessed, 2020).
    1. Evans-Whipp TJ, Plenty SM, Catalano RF, Herrenkohl TI, Toumbourou JW. Longitudinal effects of school drug policies on student marijuana use in Washington State and Victoria, Australia. Am J Public Health. (2015) 105:994–1000. 10.2105/AJPH.2014.302421
    1. Evans-Whipp TJ, Plenty SM, Catalano RF, Herrenkohl TI, Toumbourou JW. The impact of school alcohol policy on student drinking. Health Educ Res. (2013) 28:651–62. 10.1093/her/cyt068
    1. Evans-Whipp TJ, Bond L, Ukoumunne OC, Toumbourou JW, Catalano RF. The impact of school tobacco policies on student smoking in Washington State, United States and Victoria, Australia. Int J Environ Res Public Health. (2010) 7:698–710. 10.3390/ijerph7030698
    1. Buuren S. van and Groothuis-Oudshoorn K. mice: multivariate imputation by chained equations in R. J Stat Soft. (2011) 45:i03. 10.18637/jss.v045.i03
    1. Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. (2000) 11:550–560. 10.1097/00001648-200009000-00011
    1. Liao SX, Zigler CM. Uncertainty in the design stage of two-stage Bayesian propensity score analysis. Stat Med. (2020) 39:2265–90. 10.1002/sim.8486
    1. Hughes J, Hakhu N, Voldal E. Stepped Wedge Cluster Randomized Trial (SW CRT) Design. (2019).
    1. Massachusetts Department of Elementary and Secondary Education . Student Discipline Data Report–Illegal Substances. (2012).
    1. Korevaar E, Kazsa J, Taljaard M, Hemming K, Haines T, Turner EL, et al. . Intra-cluster correlations from the CLustered OUtcome Dataset bank to inform the design of longitudinal cluster trials. Clin Trials. (2021) 18:529–40. 10.1177/17407745211020852
    1. R Core Team. R: A Language and Environment for Statistical Computing (version 4.1.1). Vienna: R Foundation for Statistical Computing. (2018).
    1. RStudio Team. RStudio: Integrated Development Environment for R. Boston, MA: (2021).
    1. Wickham H, Francois H, Muller K. dplyr: A Grammar of Data Manipulation (2023).
    1. Wickham H, Vaughan D, Girlich M. tidyr: Tidy Messy Data. Boston, MA: (2023).
    1. Stan Development Team. RStan: The R Interface to Stan. Dortman: (2020).
    1. Burkner P. brms: Bayesian Regression Models using ‘Stan'. Indianapolis, IN: (2017).
    1. Landau W. The targets R package: a dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. JOSS. (2021) 6:2959. 10.21105/joss.02959

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi