A decade ago, the Society of Prevention Research (SPR) endorsed a set of standards for evidence related to research on prevention interventions. These standards (Flay et al., Prevention Science 6:151–175, 2005) were intended in part to increase consistency in reviews of prevention research that often generated disparate lists of effective interventions due to the application of different standards for what was considered to be necessary to demonstrate effectiveness. In 2013, SPR’s Board of Directors decided that the field has progressed sufficiently to warrant a review and, if necessary, publication of “the next generation” of standards of evidence. The Board convened a committee to review and update the standards. This article reports on the results of this committee’s deliberations, summarizing changes made to the earlier standards and explaining the rationale for each change. The SPR Board of Directors endorses “The Standards of Evidence for Efficacy, Effectiveness, and Scale-up Research in Prevention Science: Next Generation.”

Research suggests that measures of the family environment show genetic effects when treated as phenotypes in behavioral genetic analyses. We explored this issue as part of the Nonshared Environment in Adolescent Development project using diverse questionnaire measures of parent-child and sibling interactions. The sample consisted of 707 pairs of siblings from 10 to 18 years of age in a novel design (identical and fraternal twins and full siblings in nondivorced families, and full, half, and unrelated siblings in stepfamilies). Model-fitting analyses yielded evidence for significant genetic effects for 15 of 18 composite measures. On average, more than a quarter of the variance of these environmental measures can be accounted for by genetic differences among children. These results underline the need to investigate the reactive and active organism-environment transactional processes by which genotypes become phenotypes.

The authors review the common methods for measuring strength of contingency between 2 behaviors in a behavioral sequence, the binomial z score and the adjusted cell residual, and point out a number of limitations of these approaches. They present a new approach using log odds ratios and empirical Bayes estimation in the context of hierarchical modeling, an approach not constrained by these limitations. A series of hierarchical models is presented to test the stationarity of behavioral sequences, the homogeneity of sequences across a sample of episodes, and whether covariates can account for variation in sequences across the sample. These models are applied to observational data taken from a study of the behavioral interactions of 254 couples to illustrate their use.

Three models of the linkage between stressors and depressive symptoms were tested in 252 couples after job loss. Data were analyzed to test whether depressive symptoms in both members of the couple were due to common stressors, the transmission of stress from 1 member to the other, or changes in relationship quality. Evidence was found for all 3 processes. Common stressors influenced depressive symptoms in both partners. Anger and depressive symptoms of each partner partially mediated these effects on the other partner, as did reductions in relationship quality. Findings suggest that interventions to help couples cope with the aftermath of job loss may hold promise for preventing depressive reactions to stress.

Genetically informed research on behavioral outcomes holds substantial promise for guiding efforts to enhance the efficacy and effectiveness of preventive interventions, but it also poses considerable challenges given the complexities of the dynamic interplay between genes and environment. This paper introduces a relatively uncommon research design, called microtrials, to provide a means of translating basic research findings into prevention trials, particularly through introducing genetic effects into prevention models. Microtrials are defined as randomized experiments testing the effects of relatively brief and focused environmental manipulations designed to suppress specific risk mechanisms or enhance specific protective mechanisms, but not to bring about full treatment or prevention effects in distal outcomes. Microtrial methods are described in detail, with discussion of their unique advantages for translating this knowledge base into prevention research. We end by raising several issues to consider when constructing genetically sensitive microtrials.

As an extension of Patterson's family coercion model, we hypothesized that parental attributions about the causes of child misbehavior and parental expectancies concerning the effectiveness of parenting techniques are involved in the establishment and maintenance of coercive exchanges. Mothers of 40 conduct-disordered children and 40 matched control children completed questionnaires measuring their attributions regarding the causes of their children's misbehavior and their expectations concerning the general and personal effectiveness of parenting techniques. Results supported the hypotheses: parents of conduct-disordered children were more likely to regard their children's misbehavior as intentional and to attribute it to stable, global causes beyond the parents' control. They also were less likely to see their own parenting as effective. We speculate that these parents hold cognitive stances of blame and helplessness that contribute to aversive parent behavior as well as to parent withdrawal in the face of escalating child aggressiveness.

This paper presents new methods for synthesizing results from subgroup and moderation analyses across different randomized trials. We demonstrate that such a synthesis generally results in additional power to detect significant moderation findings above what one would find in a single trial. Three general methods for conducting synthesis analyses are discussed, with two methods, integrative data analysis, and parallel analyses, sharing a large advantage over traditional methods available in meta-analysis. We present a broad class of analytic models to examine moderation effects across trials that can be used to assess their overall effect and explain sources of heterogeneity, and present ways to disentangle differences across trials due to individual differences, contextual level differences, intervention, and trial design.

This paper addresses the issue of whether prevention research methods, particularly those involving randomized prevention trials, can be used to test theories concerning the etiology of psychopathology. Based on recent empirical and theoretical work in developmental psychopathology, three aspects of etiologic theory are discussed: risk and protective mechanisms, the integration of environmental and genetic factors, and patterns of developmental progression in psychopathology across the life span. It is suggested that integration of prevention trial methods with methods from passive correlational designs, behavioral genetics, and longitudinal studies allows for unique opportunities to test hypotheses about etiology. Empirical literature on the development and prevention of internalizing disorders, particularly depression, is presented to support this argument. Limitations of prevention trials for testing theory are also reviewed.