This series of studies developed a decisional balance scale to assess the costs and benefits of marijuana use among young adults. The final MDB scale contains 24 items, with 8 representing pros and 16 representing cons of marijuana use. Reliability analyses indicated strong internal consistency (α > 0.90 for both subscales). The MDB scale represents a new tool for understanding motivations to use marijuana.
Pros and cons were moderately but inversely correlated, suggesting that these constructs are related but represent independent sources of information. Though rarely reported in published studies, the correlations between pros and cons ranges from essentially zero to slightly positive for other behaviors such as drinking by college students (Migneault et al., 1999
; Noar et al., 2003
) and physicians’ implementation of smoking cessation programs (Park et al., 2001
). Thus, pros and cons appear to be more strongly related for marijuana use, which differs from other behaviors studied with regard to its illegal status.
The majority of predictions about the presence and directionality of relationships with other known measures were supported. Endorsement of the pros of marijuana use was associated with greater frequency of use, intentions to use in the future, and more problems, as well as stronger positive expectancies and attitudes in favor of legalizing marijuana. These findings are consistent with a generally favorable evaluation of and/or greater involvement with marijuana. Endorsement of the cons of marijuana use was more likely by females, younger and non-White participants. Stronger endorsement of cons was associated with less frequent use and lower intentions to use, consistent with previous research showing a negative relation between use frequency and perceived risk (e.g. Kilmer et al., 2007
). Participants who endorsed cons held stronger negative outcome expectancies and were unlikely to favor legalizing marijuana. Yet, cons were inconsistently related to marijuana-related problems. This finding is consistent with Noar et al. (2003)
with regard to alcohol DB, and suggests that even users experiencing few problems acknowledge that there are cons to using marijuana. We observed the potential for social desirability bias on pros in one sample, but no relationship with cons. Thus, participants who tried to present themselves in a socially desirable light were reluctant to endorse pros of marijuana use, perhaps because it is an illicit substance. The potential for social desirability bias should be taken into account in future research using this scale.
The incremental validity of the MDB scales was supported with regard to positive and negative expectancies. Pros and cons predicted behavioral intentions better than expectancies did, most likely reflecting the personalized, motivational component of pros and cons not seen in expectancies. However, how well pros and cons predict future use remains untested.
The association between marijuana pros and cons across stages of change provides cross-sectional support for predictions from the transtheoretical model of change. Specifically, the “crossover effect” appears to occur on the cusp of the Preparation and Action phases. This is a late point in the stages according to some health behaviors (e.g., safe sex), but approximates the point at which the crossover occurs for other behaviors (e.g., exercising) (Prochaska et al., 1994
Overall, analyses support the construct validity of the pros and cons subscales. In addition, the pros and cons in the final scale reflect several of the content domains suggested by Janis and Mann (1977)
, including personal gains/losses from marijuana use (e.g. “It would help me sleep”), gains/losses for others (e.g. “It may cause me to be a bad influence on others”), and issues regarding approval and disapproval from others (e.g. “It’s not accepted or approved of by people who are important to me”). Although no retained item directly references self –approval or –disapproval, many items imply approval or disapproval based on item valence.
Several strengths of this study enhance confidence in the findings. The MDB scale was developed based on the input and responses from four independent samples from a relevant population in a four-phase design. Samples included both marijuana users and abstainers, and thus addressed pros and cons associated with both decisional outcomes. Due to the advertisement of this project as a study of marijuana use, users were over-sampled; indeed, the prevalence of recent use exceeds that of national samples of young adults (Gledhill-Hoyt, Lee, Strote, & Wechsler, 2000
). Validation and confirmation phases of the research employed well-validated, psychometrically sound measures, and revealed theoretically-consistent patterns of relationships.
As with any research, this study was subject to limitations. The sample sizes, though adequate according to published guidelines, fell at the low end of the target ranges. As a result, the marijuana users and abstainers were analyzed simultaneously; it is possible that they might produce distinct patterns in data that could have been detected with larger samples. Although sample size limitations preclude separate factor analyses by use subgroup, validity
analyses by use subgroup provided generally consistent results (results available upon request from the first author). Though marijuana users were over-represented (relative to population prevalence), the inclusion of abstainers may have led to the retaining of some items less frequently endorsed by marijuana users, and may be related to the large number of cons in the final scale. Differing patterns in data may also even be detected between former versus current users, though this is likely to be less significant than the differences between users and abstainers. Additionally, the psychometric support for the scale has only been collected in self-selected undergraduate samples at a single university in the northeastern United States, potentially limiting external validity. The young adults of this sample represent a demographic (18–25 years) at high risk for marijuana use, and both genders and several ethnicities are represented in the sample; however, education and residence on a college campus may limit generalizability. Also, rates of recent use in the current samples clearly exceed most other young adult populations (SAMHSA, 2008
); last month prevalence of use ranged from 40.7%-50.9%, compared to approximately 16.5% nationally among 18–25 year olds. Generalizability to non-college attending adults thus cannot be assumed; further research must be done before the scale is used with other populations.
Additional research would help to establish the utility of the MDB scale. First, replicating the factor structure with new populations (e.g., those with cannabis dependence) could shed light on its generalizability. Similarly, validating the scale with other populations would support its utility beyond young adults attending college. Second, the incremental validity of pros and cons could be further addressed by comparing them to generic drug use DB scales or other psychological constructs like motives; such designs could establish the extent to which the MDB scales provide unique or greater explanatory power than alternative measures. Third, tests for true predictive validity are needed to determine the degree to which pros and cons predict subsequent marijuana use throughout the life course. For example, MDB scales may predict the onset and/or escalation of use in a developmental context. Furthermore, among established users, the MDB scale may serve as a method of monitoring motivational changes over time; if scores on pros and cons do predict future use, then changes in DB components might reflect increases or decreases in motivation or readiness to change. Finally, test-retest reliability has not yet been assessed, thus we do not yet know how stable pros and cons remain over time.
A DB scale for marijuana use could be helpful within clinical contexts, stimulating discussions in therapy. Eliciting the pros and cons of use may aid an individual in identifying sources of ambivalence about marijuana use, a technique used in Motivational Interviewing (Miller & Rollnick, 2002
). This exercise helps the client articulate personal reasons for behavior change, which may promote movement through stages of change. Although the therapeutic DB exercise often involves generation of ideas without suggestions, the MDB scale may facilitate more guided discussions. Additionally, the MDB scale could serve as a screening mechanism for interventions, such that individuals reporting many pros could be targeted for decisional balance based interventions designed to build motivation to change use.
DB, or the consideration of pros and cons, is a prominent concept in behavioral change (Prochaska et al., 1994
). Its key role in decision making allows clinicians to gain insight into the willingness of the individual to embark on the process of change. This scale development project marks the initial step toward an empirical understanding of the pros and cons of marijuana use. The MDB scale allows for theory testing, exploration of the utility of the DB concept for marijuana use, and provides a potential marker of motivation for change. Additional research is needed to confirm structure in more diverse samples and explore predictive validity. In sum, we provide initial evidence that marijuana use can be assessed from a DB framework, and that such a framework may advance our ability to predict current and future marijuana use.