Several theories construe risk appraisals as key determinants of decisions and actions, and this idea has been supported in correlational studies. However, correlational data cannot answer the question, "Does heightening risk appraisals change people's intentions and behavior?" The present review meta-analyzed experimental evidence in order to address this issue. We identified 4 elements of risk appraisal-risk perception, anticipatory emotion, anticipated emotion, and perceived severity-and located experiments that (a) engendered a statistically significant increase in risk appraisal among treatment compared to control participants and (b) measured subsequent intention or behavior. Heightening risk appraisals had effects of d+ = .31 (k = 217) and d+ = .23 (k = 93) on intention and behavior, respectively. There was evidence that the elements of risk appraisal combined to influence outcomes. For instance, heightening risk perceptions had larger effects on outcomes when anticipatory emotions or perceived severity was also increased. Crucially, risk appraisal effects were augmented by coping appraisals: Risk appraisals had larger effects on outcomes when response efficacy and self-efficacy were enhanced or when response costs were reduced. The largest effect sizes were observed when risk appraisals, response efficacy, and self-efficacy were simultaneously heightened (d+ = .98 and .45, for intention and behavior, respectively). These findings indicate that heightening risk appraisals changes intentions and behavior. However, the direct effects of risk appraisals were generally small. Exploiting synergies among the elements of risk appraisal, and between risk appraisals and coping appraisals, should make for more effective behavior change interventions.

Goal setting is a common feature of behavior change interventions, but it is unclear when goal setting is optimally effective. The aims of this systematic review and meta-analysis were to evaluate: (a) the unique effects of goal setting on behavior change, and (b) under what circumstances and for whom goal setting works best. Four databases were searched for articles that assessed the unique effects of goal setting on behavior change using randomized controlled trials. One-hundred and 41 papers were identified from which 384 effect sizes (N = 16,523) were extracted and analyzed. A moderator analysis of sample characteristics, intervention characteristics, inclusion of other behavior change techniques, study design and delivery, quality of study, outcome measures, and behavior targeted was conducted. A random effects model indicated a small positive unique effect of goal setting across a range of behaviors, d = .34 (CI [.28, .41]). Moderator analyses indicated that goal setting was particularly effective if the goal was: (a) difficult, (b) set publicly, and (c) was a group goal. There was weaker evidence that goal setting was more effective when paired with external monitoring of the behavior/outcome by others without feedback and delivered face-to-face. Goal setting is an effective behavior change technique that has the potential to be considered a fundamental component of successful interventions. The present review adds novel insights into the means by which goal setting might be augmented to maximize behavior change and sets the agenda for future programs of research. (PsycINFO Database Record

Objectives: The Capabilities, Opportunities, Motivations, Behaviour (COM‐B) model is being used extensively to inform intervention design, but there is no standard measure with which to test the predictive validity of COM or to assess the impact of interventions on COM. We describe the development, reliability, validity, and acceptability of a generic 6‐item self‐evaluation COM questionnaire. Design and methods: The questionnaire was formulated by behaviour change experts. Acceptability was tested in two independent samples of health care professionals ( N = 13 and N = 85, respectively) and a sample of people with low socio‐economic status ( N = 214). Acceptability (missing data analyses and user feedback), reliability (test–retest reliability and Bland–Altman plots) and validity (floor and ceiling effects, Pearson's correlation coefficient [ r ], exploratory factor analysis [EFA], and confirmatory factor analysis [CFA] were tested using a national survey of 1,387 health care professionals. Results: The questionnaire demonstrated acceptability (missing data for individual items: 5.9–7.7% at baseline and 18.1–32.5% at follow‐up), reliability (ICCs .554–.833), and validity (floor effects 0.6–5.5% and ceiling effects 4.1–22.9%; pairwise correlations r s significantly <1.0). The regression models accounted for between 21 and 47% of the variance in behaviour. CFA (three‐factor model) demonstrated a good model fit, (χ ² [6] = 7.34, p = .29, RMSEA = .02, CFI = .99, TLI = .99, BIC = 13,510.420, AIC = 13,428.067). Conclusions: The novel six‐item questionnaire shows evidence of acceptability, validity, and reliability for self‐evaluating capabilities, opportunities, and motivations. Future research should aim to use this tool in different populations to obtain further support for its reliability and validity. Statement of contribution: What is already known on the subject? The Capability, Opportunity, Motivation (COM), Behaviour (‐B) model is being used extensively to inform intervention design. The lack of an accepted universal measure hinders progress in behaviour change. What does this study add? There is evidence of acceptability, validity, and reliability for self‐evaluating COM. Our measure may be sufficiently generic for any behaviour or population, although this requires further testing.

Self-affirmation (induced by reflecting upon important values, attributes, or social relations) appears to reduce defensive resistance to health-risk information and increase subsequent readiness for health behavior change. However, these effects of self-affirmation have yet to be subjected to formal, quantitative integration. Consequently, the current article reports a meta-analysis of the impact of self-affirmation on outcomes at 3 key points in the process of health-behavior change: (a) message acceptance, (b) intentions to change, and (c) subsequent behavior. The literature search identified 144 experimental tests of the effects of manipulating self-affirmation on these outcomes. Effect sizes were extracted and meta-analyzed. Across 34 tests of message acceptance (N = 3,433), 64 tests of intentions (N = 5,564), and 46 tests of behavior (N = 2,715), random effects models indicated small but reliable positive effects of self-affirmation on each outcome: acceptance, d+ = .17(CI = .03 to .31); intentions, d+ = .14 (CI = .05 to .23); behavior, d+ = .32 (CI = .19 to .44). Findings held across a range of health problems and behaviors. The results suggest that deploying self-affirmation inductions alongside persuasive health information has positive effects, promoting message acceptance, intentions to change, and subsequent behavior. Though the effects are small in magnitude, they are comparable to those obtained in meta-analyses of other health-behavior change interventions. These findings are relevant to researchers and practitioners working to understand why people resist beneficial health information and how such resistance can be reduced.

Evidence shows that self-affirmation has a positive effect on message acceptance and other variables that motivate health behavior change; however, this has not been translated into actual behavioral change. We propose that particular features of the previous studies may account for this failure; the current study addresses this. It is designed to test whether a self-affirmation manipulation can increase a health-promoting behavior (fruit and vegetable consumption). It also explores the extent to which efficacy variables mediate the self-affirmation and behavior relationship. Women (N = 93) were randomly allocated to a self-affirmation or control task prior to reading a message regarding the health-promoting effects of fruit and vegetables. MAIN OUTCOME-MEASURES: Response-efficacy, self-efficacy, and intention measures were taken immediately after exposure to the message, followed by a 7-day diary record of fruit and vegetable consumption. Self-affirmed participants ate significantly more portions of fruit and vegetables, an increase of approximately 5.5 portions across the week, in comparison to the control group. This effect was mediated by response-efficacy. Self-affirmation interventions can successfully influence health-promoting behaviors.