9.2 The Study: Cognitive Processing and Substance Use

9.2.1 Study Information Description

Cannabis can harm adolescent development and lead to later substance use problems. Unfortunately, programs aimed at reducing cannabis use in adolescents have been largely ineffective. A more recent approach that has shown promise is to implement programs that target individuals who are at the greatest risk of using cannabis.

What factors put adolescents at risk of cannabis use? One theory is the acquired preparedness model (APM). According to the APM, differences in personality affect learning. Learning then affects choices about cannabis use (Monti et al., 2001). That is, some personality traits predispose individuals to developing more positive associations with substance use. There are several personality traits thought to be related to developing more positive associations with cannabis, including negative thinking, anxiety sensitivity, impulsivity, and sensation seeking. The scope of the current study is limited to just sensation seeking.

Individuals high in sensation seeking have an affinity for stimulating and novel experiences. Prior research has shown that sensation seeking is associated with a greater risk for developing alcohol-related problems (Schlauch et al., 2015) and with adolescent hallucinogen use (Krank et al., 2011). Although research into personality and cannabis use initiation is limited, the available research suggests sensation seeking is related to future cannabis use in adolescents (Pilin et al., 2022). The current study aims to add to the evidence demonstrating this association. Hypotheses

It is hypothesized that sensation seeking will be associated with cannabis use in adolescents. Specifically, adolescents who report more recent cannabis use will report higher average sensation seeking scores compared to those who report less recent cannabis use or no cannabis use at all.

9.2.2 Design Plan Study Design

Participant will be students in grades 8–10. They will be given class time to complete an online survey. Sample Size Rationale

The sample size will be based on the number of available respondents. Resource constraints limit data collection to a single school district. However, power analysis indicates that n = 61 participants per group would provide 95% power to detect effects of f = 0.25 or larger. This corresponds to a “medium” analysis of variance effect size according to Cohen (Cohen, 1988). Measures

Cannabis use will be measured using a single-item, which asks, “when was the last time you used marijuana?” Response options for this item are: 0 (never), 1 (more than a year ago), 2 (in the past year), 3 (in the past month), 4 (in the past week). Because power analysis indicated the need for 61 participants per group, groups with fewer than 61 participants will be collapsed into a neighbouring group. The choice of which groups to collapse will be based on the number of participants in each group. The smallest group will be collapsed into its smallest neighbour. If, after collapsing two groups there is still a group with fewer than 61 participants, that group will be collapsed into its smallest neighbour. This process will continue until all groups have at least 61 participants.

The 23-item version of the Substance Use Risk Profile Scale (SURPS) will be used to measure personality (Woicik et al., 2009). The SURPS has subscales for measuring four personality traits that are theoretically associated with substance use risk: hopelessness, anxiety sensitivity, impulsivity, and sensation seeking. Items are measured on a 4-point Likert type scale, with response options 1 (strongly disagree), 2 (somewhat disagree), 3 (somewhat agree), 4 (strongly agree). Items 1, 4, 7, 13, 20, and 23 will be reverse-coded.

For the purposes of this study, only the sensation seeking subscale of the SURPS will be used. Composite scores for sensation seeking will be produced by averaging each participant’s responses to items 3, 6, 9, 12, 16, and 19. Analytic Strategy

An analysis of variance (ANOVA) will be conducted to test whether sensation seeking varies significantly with cannabis use. Consecutive contrasts will be conducted such that sensation seeking will be compared between each level of cannabis use and the subsequent level of cannabis use. That is, the following comparisons will be tested:

  1. more than a year ago \(-\) never.
  2. more than a year ago \(-\) in the past year.
  3. in the past year \(-\) in the past month.
  4. in the past month \(-\) in the past week.

One-sided tests will be used, such that a result will be significant if sensation seeking is higher for participants who reported more recent cannabis use. To control for inflated error due to multiple testing, p values of these tests will be adjusted using the Holm method.


Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587
Krank, M., Stewart, S. H., O’Connor, R., Woicik, P. B., Wall, A.-M., & Conrod, P. J. (2011). Structural, concurrent, and predictive validity of the substance use risk profile scale in early adolescence. Addictive Behaviors, 36(1), 37–46.
Monti, P. M., Colby, S. M., & O’Leary, T. A. (2001). Adolescents, alcohol, and substance abuse: Reaching teens through brief interventions. Guilford Press.
Pilin, M. A., Robinson, J. M., Young, K., & Krank, M. D. (2022). Cognitions mediate the influence of personality on adolescent cannabis use initiation. Addictive Behaviors Reports, 15. https://doi.org/10.1016/j.abrep.2022.100425
Schlauch, R. C., Crane, C. A., Houston, R. J., Molnar, D. S., Schlienz, N. J., & Lang, A. R. (2015). Psychometric evaluation of the substance use risk profile scale (SURPS) in an inpatient sample of substance users using cue-reactivity methodology. Journal of Psychopathology and Behavioral Assessment, 37(2), 231–246.
Woicik, P. A., Stewart, S. H., Pihl, R. O., Conrod, P. J., & BROOKHAVEN NATIONAL LABORATORY (BNL). (2009). The substance use risk profile scale: A scale measuring traits linked to reinforcement-specific substance use profiles. Addictive Behaviors, 34(12), 1042–1055. https://doi.org/10.1016/j.addbeh.2009.07.001