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Association of Screening and Brief Intervention With Substance Use in Massachusetts Middle and High Schools

Key Points Question Is exposure to a screening and brief intervention (SBI) program in schools associated with reductions in student substance use? Findings In this quality improvement study involving 4587 students in grades 7 through 10 who were exposed to a school-based SBI program in Massachusetts, cannabis and e-cigarette use increased over time in all groups. Exposure to SBI was associated with a significantly smaller increase in the rate of cannabis use among middle school students and significantly smaller increases in the rates of cannabis and e-cigarette use among all female students; however, there was no significant difference in any comparison among all high school students. Meaning This study’s findings suggest that school-based SBI programs, which are mandatory in Massachusetts, may help to reduce substance use among middle school and female students.


Introduction
Screening and brief intervention (SBI) is a framework for primary and secondary substance use prevention. The American Academy of Pediatrics recommends SBI as a component of primary care for adolescents, 1 and increasing evidence supports its benefit. For example, incorporation of SBI programs in primary care settings in California was associated with reductions in substance use disorders after 3 years. 2 A multisession school-based brief intervention implemented in New Mexico reduced the frequency of heavy drinking and illicit drug use. 3 A computer-based SBI model was associated with reductions in alcohol use among adolescents with a chronic illness and decreases in binge drinking among college students with type 1 diabetes. 4 Expansion of SBI programs is a logical goal because adolescents have relatively low rates of primary care use. 5 There has been substantial investment in school-based SBI programs. To our knowledge, a controlled study of the potential benefits of SBI outside a private and confidential medical setting has not been conducted.
In 2016, the Commonwealth of Massachusetts began requiring school districts to offer SBI programs to their students. We used the introduction of this state policy as an opportunity to evaluate school-based SBI. This quality improvement study assessed self-reported student substance use before and 3 to 6 months after SBI implementation, comparing students in grades 7 through 10 who attended schools that offered SBI programs to youths in the same grade with students who attended schools that offered SBI programs to youths in different grades, a strategy that allowed same-grade comparison. This study used a difference-in-differences framework to estimate the association between exposure to an SBI program and substance use outcomes. We hypothesized that youths exposed to SBI (SBI group) would have a smaller increase in substance use rates at follow-up compared with youths who were not exposed to SBI (control group).

Study Design
The study protocol was approved by the institutional review board of Boston Children's Hospital.
Before study initiation, a letter or email explaining the study was sent to all parents; parents could opt out of participation for their children. All students provided assent via an anonymous electronic form before completing both the baseline and follow-up surveys. This study followed the Standards for Quality Improvement Reporting Excellence (SQUIRE) reporting guideline for quality improvement studies.
We used an effectiveness-implementation hybrid framework with mixed methods for the study design; to emulate the balanced comparison of a randomized clinical trial, overlap-weighted propensity scores were used to account for imbalance in school grades.

Description of Participating Schools
School data were obtained from the Massachusetts Department of Education website. 6 Participating school districts ranged in size from 215 to 4986 students, with participating school grades ranging from 36 to 320 students per grade; per-pupil school expenditures varied from $13 000 to $24 000 per annum. One SBI school and 4 control schools were located in rural zip codes. The proportion of students with high need (18.6%-60.9%) and the proportion of students who were economically disadvantaged (5.2%-52.3%) varied.

SBI Implementation
We conducted 14 phone interviews with school staff members to describe SBI implementation.
Interviews lasted approximately 30 to 60 minutes and were recorded and transcribed by study staff (including J.L.).
All schools performed student screening in a private location (conference room, private room in the library, nurse's office, or school staff member's office). All but 1 school used a version of the CRAFFT (Car, Relax, Alone, Forget, Friends, Trouble) questionnaire (score range, 0-9, with higher scores indicating greater potential for a substantial problem with substance use) 7 for screening and an intervention focused on providing brief advice on the risks of alcohol and other drug use ( Table 1).
Although parents could opt not to have their children participate in the program, the schools all reported high rates (>90%) of student participation ( Figure). We collected information on which school grades received screening, how screening was conducted (verbal vs written), the amount of time spent with each student (in minutes), the number of students who received screening at 1 time, and how staff responded to positive or negative screening results.

Participants
Before survey administration, a letter or email that explained the study was sent to parents of all 6603 students aged 12 to 17 years in grades 7 to 10 who were enrolled in any of the participating school grades. A total of 163 students (2.5%) were ineligible because their parents opted out of participation ( Figure). All other students who were in school on the day the baseline survey was administered (5534 of 6440 students) were eligible for participation and asked to provide assent through an anonymous electronic form advising them of risks and explaining that participation was voluntary. At baseline, 69 students did not consent to participation, 112 survey responses were removed because of missing or incomplete data, and 1 school grade was unable to administer the survey because of technical difficulties. From the remaining 37 school grades, 5353 responses (2714 in the SBI group and 2639 in the control group) to the baseline survey were received.
At follow-up, 4954 students (4840 students in the SBI and control groups and 114 students with no information regarding whether they belonged to the SBI or control group) were eligible to participate and asked to provide assent before taking the survey. In total, 55 students did not consent to participation, 114 survey responses were removed because of missing or incomplete data, and 3 school grades were not able to administer the follow-up survey because of technical difficulties.

Survey
Data were collected from students via electronic surveys comprising 106 questions at baseline and 114 questions at follow-up; questions were developed based on previous work. 9 Items included opinions about school screening (7 questions at both baseline and follow-up), getting into trouble in general (7 questions at both baseline and follow-up), alcohol use (8 questions at baseline and 9 questions at follow-up), cannabis use (10 questions at both baseline and follow-up), tobacco and/or e-cigarette use (5 questions at baseline and 4 questions at follow-up), harms associated with

Outcome Measures
The primary outcome measure was substance use at the school grade level, which was reported on student surveys and measured by the number of days each substance was used and the probability of any binge drinking during the past 3 months. Participants self-reported their frequency of alcohol use (in days) during the past 3 months ("In the past 3 months, on how many days did you have something to drink?") 12 and, among those who reported drinking alcohol, their experience of binge drinking in the past 3 months, defined by established age and sex cutoffs. 13 Participants also reported the frequency of cannabis and e-cigarette use (in days) during the past 3 months ("In the past 3 months, on how many days did you use marijuana/smoke e-cigarettes?").
Covariates included demographic and health characteristics. Race, ethnicity, and gender were self-reported. Race categories included American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Pacific Islander, White, and other race. A category for mixed or other race was created because samples were small; this category included students who selected more than 1 racial category and those who selected American Indian or Alaska Native, Native Hawaiian or Pacific Islander, or other race. Ethnicity categories included Hispanic and non-Hispanic. Gender categories included female, male, and transgender or prefer not to answer. Secondary outcome measures included perceived adult support at school ("If you wanted to talk to someone about a serious problem, do you have an adult in school you could turn to?"), intention to use substances ("In the next 3 months, how likely is it that you will…drink a beverage containing alcohol/use marijuana/ smoke e-cigarettes?"), substance use knowledge (assessed by questions pertaining to the negative consequences of substance use among youths, with the knowledge scaled score based on the percentage of questions answered correctly out of 100), and perceived health risk of substance use ("How much is a teenager's physical or mental health at risk from the following…having 1-2 drinks containing alcohol at least once a month/using marijuana at least once a month/smoking e-cigarettes more than once a month?") (eMethods in the Supplement).

Statistical Analysis
Because of the prospective design, we used difference-in-differences estimates to evaluate substance use outcomes among students exposed to SBI compared with students not exposed to SBI, using adjusted and overlap-weighted generalized linear mixed models, assuming an autoregressive covariance structure with random intercepts specified for the school grade levels.
Models with a negative binomial distribution were used to assess the changes in substance use frequency during the past 3 months over time, and models with a binomial distribution were used to assess the changes in binge drinking during the past 3 months.

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The size and sign of difference-in-differences estimates revealed the extent and direction of change in outcomes among students exposed to SBI, accounting for changes observed among those who were unexposed (eg, substance use was expected to increase naturally with age). Because treatment assignment was not truly random (eg, although all schools implemented an SBI program, administrators could decide which grades would participate, when SBI would be implemented, and how SBI would be administered), estimates were potentially confounded by unobserved differences between the exposed and unexposed groups. Thus, group imbalance was addressed through the use of overlap weighting based on propensity scores, which can achieve covariate balance between exposed and unexposed groups. [14][15][16] The details of the propensity score calculation are described in eMethods in the Supplement.
Based on previous studies, 17-20 a propensity score for SBI assignment was estimated from a multivariable logistic regression model containing per-pupil school expenditures, school grade, proportion of students with high need or economic disadvantages, White race, and female gender.
For each level of parental educational status, we dichotomized against all other statuses. Propensity score distributions before and after application of the overlap weights are shown in the eFigure in the Supplement. Covariate differences before and after overlap weighting at the school grade level were assessed using Cohen d, 21,22 which was stratified by school type (eTable 2 and eTable 3 in the Supplement). An absolute Cohen d value less than 0.1 was considered negligible. Differences in baseline characteristics between groups were assessed by applying overlap propensity score weights (  24 ; score range, 0-6, with higher scores indicating greater likelihood of generalized anxiety and scores Ն3 suggesting a generalized anxiety disorder is likely; the variable was dichotomized as positive or negative).
We performed subgroup analyses for female and male students because we hypothesized that the association between SBI exposure and substance use outcomes might differ by gender (other genders, including transgender, were not included due to small sample size) 25,26 (eTable 8 in the Supplement). We repeated the primary outcome analyses after using overlapping weights only (eTable 6 in the Supplement), after excluding 2 school grades (both grade 9) in which school staff members spent less time with each student, and after stratifying by screening tool used (eTable 9 and eTable 10 in the Supplement).
All statistical analyses were performed using SAS software, version 9.4 (SAS Institute Inc). 27 The significance threshold was 2-sided P = .05.

Middle School Participants
In total, we analyzed 5696 responses (2866 from the baseline survey and 2830 from the follow-up survey) from middle school students (grades 7 and 8). At baseline, the median (IQR) age was 13 (12)(13)    k Intention to use a substance during the next 3 months was assessed by the following question: "In the next 3 months, how likely is it that you will…use alcohol/use cannabis/ smoke e-cigarettes?" The categorical measure of intent to use a substance (with 1 indicating definitely will not, 2 indicating probably will not, 3 indicating probably will, 4 indicating definitely will, and 999 indicating prefer not to answer) was then dichotomized for the analysis of responses indicating probably or definitely will use a substance vs other responses.
(92.2%) rated their health as good, very good, or excellent. At baseline, 260 middle school participants (9.1%) reported alcohol use in the past year, 93 (3.2%) reported cannabis use in the past year, and 137 (4.8%) reported e-cigarette use in the past year. After overlap weighting at the school grade level, all baseline demographic and health characteristics in middle school grades (with the exception of age) were balanced between the SBI and control groups. The regression models were adjusted for age. Weighted sample characteristics of middle school participants at the school grade level are shown in Table 2, and unweighted characteristics are shown in eTable 4 and eTable 5 in the Supplement.

High School Participants
We analyzed 3075 responses (1721 from the baseline survey and 1354 from the follow-up survey) from high school students (grades 9 and 10). At baseline, the median (IQR) age was 15 (14)(15)  ). In addition, no differences in results by screening method or the amount of time school staff members spent with each student were found (eTables 9-11 in the Supplement).

SBI Implementation
Although school staff members generally viewed their participation in the SBI program as a positive experience, they expressed concerns about lack of adequate space and time spent outside of learning, and they had questions about the honesty of student responses. No adverse events among students were reported.

Discussion
This quality improvement study found that although substance use generally increased as students got older, middle school students in a school grade exposed to SBI reported smaller increases in the rate of cannabis use compared with students in the control group, and female students exposed to SBI reported smaller increases in both cannabis and e-cigarette use compared with students in the control group. Abbreviations: aRR, adjusted rate ratio; SBI, screening and brief intervention. a All models were overlap weighted and adjusted for age, gender, parental educational level, perceived general health, and depression and anxiety screening results, with 3-way interactions with school types and time point.
b Estimated probability was derived from the models.
c Difference in the change in outcome over time between the SBI vs control groups. d The aRRs were derived using the difference-in-differences method. Values reflect the difference in the change in the rate of alcohol use (in days) during the past 3 months between the SBI vs control groups from baseline to follow-up. e Values are estimated adjusted odds ratios comparing the increases in binge drinking during the past 3 months between the SBI vs control groups from baseline to follow-up.
f Difference in the change in the rate of cannabis use (in days) during the past 3 months between the SBI vs control groups from baseline to follow-up.
g Difference in the change in the rate of e-cigarette use (in days) during the past 3 months between the SBI vs control groups from baseline to follow-up.  Definite or probable intention to use substance in next 3 mo k Alcohol Previous work has found that school-based SBI programs are potentially beneficial. Surveys of students 9,28 and school nurses 29 have documented positive attitudes toward SBI in schools. A study in Canada 30 found that, in aggregate, the number of students considered to be at risk of a substance use disorder decreased over time among schools implementing an SBI program. Our results were consistent with these findings, revealing a modest preventive association for school-based SBI programs, specifically among middle school students.

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In this study, exposure to an SBI program was not significantly associated with changes in alcohol consumption. Attitudes about alcohol are formed early and have been associated with parenting and social factors. 31 Positive alcohol expectancies (ie, positive perceptions about the outcomes of drinking alcohol) increase by early adolescence. 32 Thus, attitudes toward alcohol consumption may be well formed and difficult to alter, even by middle school. It is possible that an intervention with more in-depth content about alcohol use may have greater benefit; future studies f Values are β coefficients reflecting the difference in knowledge changes over time between the SBI vs control groups. The difference in knowledge scaled score changes was derived using generalized linear mixed models assuming an autoregressive covariance structure, with random effects by school grade assuming normal distributions.
g Perceived riskiness of substance use was assessed by the following Likert-scaled question: "How much is a teenager's physical or mental health at risk from the following…having 1-2 drinks containing alcohol at least once a month/using marijuana at least once a month/smoking e-cigarettes (electronic cigarettes) more than once a month?" The ordinal measure of perceived health risk (with 1 indicating no risk, 2 indicating slight risk, 3 indicating moderate risk, 4 indicating great risk, and 999 indicating prefer not to answer) was then dichotomized for the analysis of responses indicating moderate or great risk vs other responses.
h The probability of having higher substance use health risk awareness was modeled using overlap-weighted generalized linear mixed models using a logit link and binomial distributions, assuming an autoregressive covariance structure. The estimated aORs compare the increases in having higher health risk awareness between the SBI vs control groups from baseline to follow-up.
i Perceived adult support at school was assessed by the following question: "If you wanted to talk to someone about a serious problem, do you have an adult in school you could turn to?" The categorical measure of perceived adult support at school (with 1 indicating yes, there is somebody in school I can talk to about a serious problem; 0 indicating no, there is nobody in school I can talk to about a serious problem; and 999 indicating prefer not to answer) was then dichotomized for the analysis of yes responses vs other responses.
j The probability of having adult support at school was modeled using overlap-weighted generalized linear mixed models using a logit link and binomial distributions, assuming an autoregressive covariance structure. The estimated aORs compare the increases in having adult support at school between the SBI vs control groups from baseline to follow-up.
k Intention to use a substance during the next 3 months was assessed by the following question: "In the next 3 months, how likely is it that you will…use alcohol/use cannabis/ smoke e-cigarettes?" The categorical measure of intent to use a substance (with 1 indicating definitely will not, 2 indicating probably will not, 3 indicating probably will, 4 indicating definitely will, and 999 indicating prefer not to answer) was then dichotomized for the analysis of responses indicating probably or definitely will use a substance vs other responses.
l The changes in the probability of intention to use a substance in the next 3 months over time were assessed by overlap-weighted generalized linear mixed models using a logit link and binomial distributions, assuming an autoregressive covariance structure. The intention to use each substance was operationalized as definitely or probably will use the substance vs definitely or probably will not use the substance (reference variable). The estimated aORs compare the increases in intention to use a substance in the next 3 months between the SBI vs control groups from baseline to follow-up.
could explore this approach. In contrast, opinions about cannabis and e-cigarettes are generally less well formed during adolescence, and clinicians and families are often unsure about how to discuss e-cigarette use with youths. 33,34 This uncertainty leaves a gap that could be addressed through a brief intervention delivered by a school professional. Our study results suggested that, by high school, attitudes toward cannabis and e-cigarette use are more difficult to alter.
The present study found a significant association between exposure to SBI and changes in the rates of cannabis and e-cigarette use among female students, whereas no difference was observed among male students. Gender-based differences remain an underexplored area in substance use prevention and treatment, 35 although certain treatment and preventive interventions appear to benefit female individuals more than male individuals. 36 A future study might explore reasons for substance use and abstention among male students in an effort to identify more beneficial themes for this group. This issue is particularly important because, among high school students, boys are more likely to use substances than girls. 37 The proportion of students who initiated substance use decreased steadily from 1975 through 2015. 38 Among adolescents who initiate substance use, the most common trajectory is increasing frequency, intensity, and number of substances used, and a substantial proportion of adolescents develop serious substance use disorders in young adulthood. 37 Notably, most individuals with addiction start using substances before age 18 years. 8 The consequences of addiction continue to present challenges in the US, with overdoses associated with more than 100 000 deaths in 2020. 39 Interventions that prevent, delay, or decrease substance use among young people, even those with nondisordered substance use, could help to change these trajectories. The current study found that implementation of SBI programs was not associated with harms and may decrease substance use trajectories among middle school students. We detected small differences in substance use through exposure to a single brief state-mandated intervention; benefits may be even larger with an intervention that offers enriched youth-centered content about alcohol separately from cannabis and nicotine and with content that is formatively evaluated with regard to engagement of male as well as female individuals. Although we do not yet know the long-term consequences, school-based SBI appears to be a logical component of a broad-based strategy for addressing the nation's addiction problem.

Limitations
This study has limitations. All of our data were obtained from student self-report, which is susceptible to recall and social desirability bias. As we expected, the frequency of substance use increased over time (with smaller increases in the SBI group), suggesting that students were likely forthcoming in their report of substance use behaviors and decreasing the likelihood that these biases substantially altered our findings. To protect privacy, all surveys were anonymous, which prevented tracking of substance use trajectories for individual students. This lack of tracking limited the power of our statistical approach, and it is possible that findings would have been strengthened if a true longitudinal design had been used.
Although there is likely to be an almost complete overlap between the students who responded to surveys collected at baseline and follow-up, we could not account for within-individual clustering; however, we accounted for clustering at the school grade level, which should also account for some individual clustering. We used an intention-to-treat model, and we do not know which students actually received SBI, although schools reported high implementation of SBI among their gradeeligible students. It is possible that conducting SBI in only certain grade levels had consequences among students in nonparticipating grades, which would suggest that the actual changes associated with exposure to school-based SBI programs may be greater than those reported in this study.

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Association of School-Based Screening and Brief Intervention With Substance Use

Conclusions
In this quality improvement study, exposure to a school-based SBI program was associated with a significantly smaller increase in the rate of cannabis use among middle school students and significantly smaller increases in the rates of cannabis and e-cigarette use among all female students, with no associated harms identified. Implementation of SBI programs in schools may help to reduce substance use among middle school and female students, and further evaluation of these programs is warranted.