The Theory of Active Involvement: Processes Underlying Interventions That Engage Adolescents in Message Planning and/or Production

Abstract

Adolescence is a time of increased risk taking, and recent intervention strategies have included adolescents planning or producing antirisk messages for their peers. Although these projects may generate enthusiasm, we know little about message planning or production as a strategy for changing adolescent decision-making and behavior. This article articulates the Theory of Active Involvement (TAI) to describe and explain the processes through which these active involvement interventions influence adolescents. TAI is based on social cognitive theory's notion of self-regulation and examines multiple perspective taking and activating the self-reflection processes. The theory specifically describes the process of cognitive changes experienced by participants in active involvement interventions. The sequence is conceptualized as starting when engagement with the intervention (arousal and involvement) produces skill and knowledge gains (immediate outcomes) that lead to reflection (perceived discrepancy) and then other cognitions (expectancies, norms, intentions), with the ultimate outcome being behavior change. Engaging the target audience in a process of self-reflection is conceptualized as the crucial ingredient for meaningful and sustainable change in cognitions and behavior. This article provides valuable insight into how active involvement strategies function and how to best design these interventions, particularly those targeting adolescents.

ACKNOWLEDGMENTS

This publication was supported by grant R21 DA027146 from the National Institute on Drug Abuse to Rutgers University (grant recipient), Kathryn Greene, principal investigator. The contents are solely the responsibility of the author and do not necessarily represent the official views of the National Institutes of Health. The author thanks a number of colleagues, including Itzhak Yanotivzky, who provided suggestions on various versions of this article.

Notes

¹Besides information processing and comprehension, cognitive processing has also been studied in understanding affective responses (Donohew, Finn, & Christ, 1988; Unnikrishnan & Bajpai, 1995), such as message liking or perceptions (see Banerjee & Greene, 2006 Greene & Brinn, 2003) The utility of measuring liking, however, is limited. It is possible to like a program or intervention but not have any activation of key components. For adolescents, for example, giving them pizza (or money) will likely increase liking without having an effect on the targeted processes.

²The effect of active involvement interventions is posited to delay decay of negative perceptions of substances (see Austin & Johnson, 1997 Pfau, 1995). The same logic applies to substance use where retention of no or low use is the expected main outcome. It is possible, however, that an active involvement intervention could function as an intervention (rather than prevention) if it causes adolescents to reconsider prior risky decisions. For smoking, as an example, results suggest that media literacy might serve as both a prevention tool targeting initiation among nonsmokers and an intervention tool for targeting cessation among smokers (Primack, Gold, Land, & Fine, 2006; Primack & Hobbs, 2009 Primack, Sidani, Carroll, & Fine, 2009).

³If the goal is to decrease risk behavior (or maintain low-risk behavior such as not smoking), then researchers must track change beyond immediate postintervention effects to document effects and potential mediators (see Banerjee & Kubey, 2013), and these designs must include establishing baseline as well as tracking change to assess decay of effects. We also have limited understanding of the need for boosters in active involvement interventions, and this should be addressed in future research particularly because the social context changes rapidly during adolescence with increased unsupervised time, independent transportation, access to substances from peers and older adolescents, and changing social contexts such as parties (increasingly without adult presence).

⁴The composition of the small groups is foundational for active involvement interventions. It is likely, for example, that a small group might include a range of risk experience such as no drinking, occasional drinking, and regular drinking. In a mixed group, regular users may act as a negative influence on others such as nonusers, rather than the reverse. This points to the need for well-designed and well-directed small-group activities that emphasize perspective taking but in a focused and directed way. A group discussing the benefits of marijuana use, for example, is unlikely to reinforce nonuse or change risk behavior. The group must generate alternatives to risk behavior, consequences of risk behavior, or similar features to be effective.

⁵There is evidence that brief, single-session interventions can achieve long-term benefits (e.g., Baer, Kivlahan, Blume, McKnight, & Marlatt, 2001; Friend & Levy, 2001 Tevyaw & Monti, 2001). Much of our confidence in the efficacy of utilizing a brief media literacy intervention is based on the prevention literature, which produced strong evidence for the effectiveness of brief interventions for alcohol and tobacco (e.g., Bien, Miller, & Tonigan, 1993; Grenard et al., 2003; Kaner et al., 2007; Larimer et al., 2001; Neighbors, Larimer, & Lewis, 2004; Stern, Meredith, Gholson, Gore, & D'Amico, 2007; Walters & Neighbors, 2005) The average effect sizes recorded for single-dose brief motivational interventions in college drinking are about .42 for reductions in heavy episodic drinking and between .21 and .28 for reductions in alcohol use more generally within 6–12 months following the intervention (Walters & Neighbors, 2005) Effects across these brief interventions are especially strong for those unmotivated and/or heavier prior users (Baer et al., 2001; Tevyaw & Monti, 2004) which has implications for how active involvement interventions are constructed.

⁶Note that this planning strategy relies on exposure to others’ views and public commitment provided, for example, by dividing a group into smaller groups of three to five students to complete the active involvement tasks. These small groups engage in the active planning activity and share results with the larger group. Motivation can be further enhanced by using incentives for best performance, and to be consistent with the theoretical foundation the best performance should be for a group and voted on by peers. This strategy is unlikely to be effective as a solo activity online absent significant peer interaction to activate reflection and perceived discrepancy.