Numerous theories in social and health psychology assume that intentions cause behaviors. However, most tests of the intention- behavior relation involve correlational studies that preclude causal inferences. In order to determine whether changes in behavioral intention engender behavior change, participants should be assigned randomly to a treatment that significantly increases the strength of respective intentions relative to a control condition, and differences in subsequent behavior should be compared. The present research obtained 47 experimental tests of intention-behavior relations that satisfied these criteria. Meta-analysis showed that a medium-to-large change in intention (d = 0.66) leads to a small-to-medium change in behavior (d = 0.36). The review also identified several conceptual factors, methodological features, and intervention characteristics that moderate intention-behavior consistency.

BackgroundThe Internet is increasingly used as a medium for the delivery of interventions designed to promote health behavior change. However, reviews of these interventions to date have not systematically identified intervention characteristics and linked these to effectiveness.Objectives The present review sought to capitalize on recently published coding frames for assessing use of theory and behavior change techniques to investigate which characteristics of Internet-based interventions best promote health behavior change. In addition, we wanted to develop a novel coding scheme for assessing mode of delivery in Internet-based interventions and also to link different modes to effect sizes.MethodsWe conducted a computerized search of the databases indexed by ISI Web of Knowledge (including BIOSIS Previews and Medline) between 2000 and 2008. Studies were included if (1) the primary components of the intervention were delivered via the Internet, (2) participants were randomly assigned to conditions, and (3) a measure of behavior related to health was taken after the intervention.Results We found 85 studies that satisfied the inclusion criteria, providing a total sample size of 43,236 participants. On average, interventions had a statistically small but significant effect on health-related behavior (d+ = 0.16, 95% CI 0.09 to 0.23). More extensive use of theory was associated with increases in effect size (P = .049), and, in particular, interventions based on the theory of planned behavior tended to have substantial effects on behavior (d+ = 0.36, 95% CI 0.15 to 0.56). Interventions that incorporated more behavior change techniques also tended to have larger effects compared to interventions that incorporated fewer techniques (P < .001). Finally, the effectiveness of Internet-based interventions was enhanced by the use of additional methods of communicating with participants, especially the use of short message service (SMS), or text, messages.ConclusionsThe review provides a framework for the development of a science of Internet-based interventions, and our findings provide a rationale for investing in more intensive theory-based interventions that incorporate multiple behavior change techniques and modes of delivery.

The present meta-analysis investigated the effectiveness of strategies derived from the process model of emotion regulation in modifying emotional outcomes as indexed by experiential, behavioral, and physiological measures. A systematic search of the literature identified 306 experimental comparisons of different emotion regulation (ER) strategies. ER instructions were coded according to a new taxonomy, and meta-analysis was used to evaluate the effectiveness of each strategy across studies. The findings revealed differences in effectiveness between ER processes: Attentional deployment had no effect on emotional outcomes (d(+) = 0.00), response modulation had a small effect (d(+) = 0.16), and cognitive change had a small-to-medium effect (d(+) = 0.36). There were also important within-process differences. We identified 7 types of attentional deployment, 4 types of cognitive change, and 4 types of response modulation, and these distinctions had a substantial influence on effectiveness. Whereas distraction was an effective way to regulate emotions (d(+) = 0.27), concentration was not (d(+) = -0.26). Similarly, suppressing the expression of emotion proved effective (d(+) = 0.32), but suppressing the experience of emotion or suppressing thoughts of the emotion-eliciting event did not (d(+) = -0.04 and -0.12, respectively). Finally, reappraising the emotional response proved less effective (d(+) = 0.23) than reappraising the emotional stimulus (d(+) = 0.36) or using perspective taking (d(+) = 0.45). The review also identified several moderators of strategy effectiveness including factors related to the (a) to-be-regulated emotion, (b) frequency of use and intended purpose of the ER strategy, (c) study design, and (d) study characteristics.

Two studies tested whether action control by implementation intentions is sensitive to the activation and strength of participants' underlying goal intentions. In Study 1, participants formed implementation intentions (or did not) and their goal intentions were measured. Findings revealed a significant interaction between implementation intentions and the strength of respective goal intentions. Implementation intentions benefited the rate of goal attainment when participants had strong goal intentions but not when goal intentions were weak. Study 2 activated either a task-relevant or a neutral goal outside of participants' conscious awareness and found that implementation

There is a drive for more scientists to engage with the lay public. The authors used an augmented version of the theory of planned behavior and identified three factors that predicted scientists' intentions to participate in public engagement activities, over and above their past actions: attitude (whether participation was regarded as positive), perceived behavioral control (beliefs about whether participation was under their control), and descriptive norms (whether scientists believe their colleagues participate). Factors such as career recognition and time constraints did not significantly predict intentions. These findings will contribute to the design of interventions to promote public engagement.