PROTOCOL: Effect of early, brief computerized interventions on risky alcohol use and risky cannabis use among young people: protocol for a systematic review

Risky use of alcohol or recreational drugs among young people remains a prominent public health issue (United Nations, 2003; United Nations Office on Drugs and Crime, 2010b). The United Nations Office on Drugs and Crime (UNODC) has argued for a public health approach to prevent alcohol and recreational drug abuse, using interventions that provide assistance and counselling. This approach provides services at an early stage to drug and alcohol users who are at risk but who remain socially included (United Nations, 2003). Many countries have made substantial efforts at multiple levels ranging from government policy initiatives to primary health care services in an attempt to minimise the long-term consequences of alcohol and cannabis use. For example, Roche and Freeman (2012) have illustrated the advantages of implementing screening, and of brief, early interventions for young people with alcohol and drug problems. However, risky use of alcohol and recreational drugs remains a prominent health problem. Alcohol misuse presents a substantial societal burden due to the costs related to health care, prevention, crime, law enforcement and welfare assistance, as well as the costs resulting from reduced productivity and increased mortality (Thavorncharoensap, Teerawattananon, Yothasamut, Lertpitakpong, & Chaikledkaew, 2009). The WHO Global Survey on Alcohol and Health (2008) found a trend towards increased drinking among young people aged 18-25 years over the last five years, with an 80 percent increase in risky alcohol consumption in the participating countries (WHO, 2011). Risky and harmful drinking patterns such as binge drinking and drinking to intoxication have also increased over time among young people (Editorial Lancet, 2008; The National Center on Addiction and Substance Abuse at Columbia University, 2007). Small to moderate levels of alcohol might not be harmful, but high consumption of alcohol is directly related to risky behaviours such as intoxicated driving (Cherpitel, Ye, Bond, & Borges, 2003) and interpersonal violence (Foran & O'Leary, 2012). In addition, binge drinking can have both short- and long-term negative impacts on an individual's health. Lopez-Caneda et al. (2013), for instance, found an association between binge drinking and anomalous neural activity related to working memory processes, and college students who binge drink have been shown to have a higher risk of developing alcohol dependence in later years (Jennison, 2004). Cannabis is the most widely used and trafficked illicit drug worldwide (United Nations Office on Drugs and Crime, 2012). Cannabis is a general term to describe the psychoactive preparations of the plant Cannabis sativa. While marijuana refers to the cannabis leaves or other crude plant material, the term hashish describes the drug produced by drying the resin exuded by the marijuana plant (Brecher, 1972). Cannabis is commonly smoked, with or without being mixed with tobacco – but can also be consumed orally. The United Nations Office on Drugs and Crime (UNODC) has estimated that between 2.9 to 4.3 percent of the world population aged 15-64 (between 129 and 191 million people) used cannabis at least once in 2008 (United Nations Office on Drugs and Crime, 2010a). Whereas the use of inhalants (defined as substances producing chemical vapours such as found in beauty products like hairspray) is more commonly used among young people and might decline with age, the use of marijuana and hashish increases with age (Mosher, Rotolo, Phillips, Krupski, & Stark, 2004). Cannabis use has increased in the U.S. since 2007 in the 13 to 18 year age group and daily marijuana use reached a 30-year peak among high school students aged 17-18 years in 2011 (Johnston, O'Malley, Bachman, & Schulenberg, 2012). Regular cannabis use among young people presents a social burden due to costs arising from increased health care use and a higher risk for school-drop out. Although there appears to be no standard measure for ‘low’ or ‘high’ frequencies of cannabis use, we define ‘high users of cannabis’ according to the literature as users with at least weekly consumption of the drug (Lev-Ran, Le Foll, McKenzie, George, & Rehm, 2013). It has been reported that regular cannabis use among young people may have a negative impact on their cognitive functioning (Ramaekers, Berghaus, van Laar, & Drummer, 2004; Ramaekers et al., 2006), and on the developing brain (Pope, Grubera, Hudsona, Cohanea, & Yurgelun-Toddb, 2003). The current literature suggests a positive association between frequency of cannabis use and the risk of developing a mental illness, especially psychotic disorders (Løberg et al., 2012). On the other hand, there is some evidence that cannabis use can have a positive impact on creativity (Schafer et al., 2012), and is helpful in the treatment of certain ailments such as cancer (Robson, 2001) and multiple sclerosis (Iskedjiana, Berezaa, Gordonc, Piwkoa, & Einarsona, 2007). Other risk factors including unprotected sexual behaviour and risky driving behaviour have been found to be associated with increased use of alcohol (Jennison, 2004; Karam, Kypri, & Salamoun, 2007; J. Miller, Naimi, Brewer, & Jones, 2007) and of cannabis (Anderson & Stein, 2011; Hall & Degenhardt, 2009). In addition, the development of substance abuse disorders in later life has been found associated with the use of alcohol (Odgers et al., 2008) and cannabis (Behrendt, Wittchen, Hofler, Lieb, & Beesdo, 2009) during youth. Thus, there is a need for early interventions to reduce or eliminate the use of alcohol and cannabis among young people in order to prevent them from falling into a downward spiral that may lead to substance abuse related behaviours and ailments in adulthood. Brief interventions have the singular focus of targeting problematic behavior in a systematic and specific manner (O'Leary & Monti, 2004). For the purpose of this review, brief interventions are defined as follows: any preventive or therapeutic activity (delivered by a health worker, psychologist, social worker, or volunteer worker) given within a maximum of four structured therapy sessions, each of short duration (W. Miller, Zweben, DiClemente, & Rychtarik, 1992) that lasts between five and ten minutes with a maximum total time of one hour (Babor, 1994). Previous reviews suggest that ‘brief interventions’, so defined, can be effective in reducing the burden of alcohol (Rehm et al., 2004), and cannabis (Bernstein et al., 2009) use. The National Institute for Health and Clinical Excellence (NICE) differentiates between two main types of brief interventions, namely Structured Brief Advice and Extended Brief Interventions. Structured Brief Advice can be used with time constraints (e.g., 5 minutes) as a first step for adults (aged 18 and over) who have been classified as high-risk drinkers. In contrast, most Extended Brief Interventions can be classified as short versions of Motivational Interviewing (NICE, 2010). Examples are the ‘Motivational Enhancement Therapy’ originally developed as a four-session intervention in ‘Project MATCH’ in the US (W. Miller et al., 1992), and ‘Drinker's check-up’ (Hester, Squires, & Delaney, 2005; W. Miller, Sovereign, & Krege, 1988; NICE, 2010) consisting of assessment, feedback, and decision-making modules. Computerized brief interventions include both online and offline interventions (e.g., CD-Rom, software, websites and downloadable applications) delivered via electronic devices such as personal computers, tablets and smart phones. The main advantage of a computerized brief intervention is that it can reach large audiences at a low cost and simultaneously simulate an ‘interpersonal therapeutic component’ by targeting recipients' feedback. Moreover, computerized, brief intervention appeals to younger people who have been growing up with digital media. Many studies targeting young people such as high school and university students use computerized interventions (Carey, Carey, Henson, Maisto, & DeMartini, 2011; Carey, Scott-Sheldon, Elliott, Bolles, & Carey, 2009; Carney, Bronwyn, & Louw, 2011; White et al., 2010). As young people are underrepresented among users of standard face-to-face alcohol and other drug specialist services, the computer might be an effective medium to reach this population (White et al., 2010). In one study, 53 percent of Internet users aged 18-29 had searched online for information on a specific disease and medical problem (Fox & Duggan, 2013), and 14 percent had searched specifically for information on alcohol and drug problems (Fox, 2006). Computerized interventions often consist of two feedback components: targeted feedback and tailored feedback (W. Miller, 2002). Whereas the term ‘targeted feedback’ refers to feedback according to the needs of a whole group, for example, to students with risky alcohol and cannabis use, the term ‘tailored feedback’ refers to feedback that is individualized and tailored to a single-person's needs (Kreuter & Skinner, 2000). ‘Automated’ computerized interventions may be combined with a brief session of counseling given by a real time ‘counselor’ such as a psychologist or social worker at the other end of the electronic link (Kristjansdottir et al., 2013). In the case of early, brief computerized interventions, software programs can be used instead of health care professionals or other staff to screen effectively for substance use. This type of screening process is more anonymous and may thus encourage participants to give more honest information. Interventions that are consistent and of high quality can be provided via computers, tablets, or smart phones (including using the Internet) and can also give information tailored to the individual participant (Moyer & Finney, 2004/2005). The assessment module aims to classify the user as either a low, medium, high or very high risk drinker and provides recommendation on whether he or she might benefit from a more formal treatment program. The feedback module gives information on the user's score after each assessment and responds to the client's general reaction to such feedback. Initially, the decision-making module allows users to specify their level of readiness to change. Those who declare themselves ready to change are provided with a menu of goal options. After deciding which goal option to follow, users are lead through exercises to develop a plan of change, and are also provided with references to additional Web links, self-help groups and materials and a list of therapists. Those who do not show a readiness to change are offered the option of receiving some basic information before ending the program (Moyer & Finney, 2004/2005). Gender and education might influence the effect of brief, computerized interventions. For example, males and young adults with higher education use digital media more than females and young adults with lower education (OECD, 2008). These two groups may therefore be more likely to benefit from computerized interventions because their past experience is likely to have led to more efficient use of digital media. Brief interventions have been suggested as working through two main mechanisms: (1) by making the clients think differently about their alcohol/cannabis use, and (2) by providing them with skills to change their behavior if they are motivated to change. It has been suggested that the assessment component of brief interventions alone might lead to behavioral change (Bien, Miller, & Tonigan, 1993) particularly in emergency department settings (Longabaugh et al., 1995). In addition, studies drawing on time-line follow-back assessments have shown some reductions in the use of alcohol and other substances over time (LaBrie, Lamb, Pedersen, & Quinlan, 2006; Suffoletto, Callaway, Kristan, Kraemer, & Clark, 2012). Previous reviews and meta-analyses using “Motivational Interviewing” (MI) (Smedslund et al., 2011), internet-based interventions (Tait & Christensen, 2010) and online alcohol interventions (White et al., 2010) have studied the effects of computerized brief interventions delivered both as stand-alone or in combination with face-to-face interventions. First, Smedslund et al. (2011) focused on the effect of ‘motivational interviewing’ in general on substance abuse among persons who abused or were dependent upon substances, and included all individuals who met this criterion without limitation to age. Second, in examining the effect of fully automated Internet-based interventions, Tait and Christensen (2010) limited their review to studies targeting young people not older than 25 years with problematic substance use, and they did not explicitly differentiate between specific substances, and focused solely on brief computerized interventions. Third, White et al. (2010) included studies on the effect of online-alcohol interventions more generally, without limitation to age and time range. In general, these reviews have focused either on the universal prevention of problematic substance use, or on the treatment and rehabilitation of individuals who have established substance dependency. Most focus solely on computerized interventions, are limited to college students, and exclude other groups of young people who are not attending college. The current review investigates whether stand-alone early, brief computerized interventions prevent the development of established alcohol and/or cannabis problems in young people aged 15-25 years showing risky behavior. This has not been systematically studied before. The objective of this review is to assess the effectiveness of early, brief computerized interventions on alcohol and cannabis use by young people aged 15 to 25 years who are high or risky consumers of either one or both of these substances by synthesizing data from rigorous high-quality studies. 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