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The article describes a position statement and recommendations for actions that need to be taken to develop best practices for promoting scientific integrity through open science in health psychology endorsed at a Synergy Expert Group Meeting. Sixteen Synergy Meeting participants developed a set of recommendations for researchers, gatekeepers, and research end-users. The group process followed a nominal group technique and voting system to elicit and decide on the most relevant and topical issues. Seventeen priority areas were listed and voted on, 15 of them were recommended by the group. Specifically, the following priority actions for health psychology were endorsed: (1) for researchers : advancing when and how to make data open and accessible at various research stages and understanding researchers' beliefs and attitudes regarding open data; (2) for educators : integrating open science in research curricula, e.g., through online open science training modules, promoting preregistration, transparent reporting, open data and applying open science as a learning tool; (3) for journal editors : providing an open science statement, and open data policies, including a minimal requirements submission checklist. Health psychology societies and journal editors should collaborate in order to develop a coordinated plan for research integrity and open science promotion across behavioural disciplines.

Use of fear appeals assumes that when people are emotionally confronted with the negative effects of their behaviour they will change that behaviour. That reasoning is simple and intuitive, but only true under specific, rare circumstances. Risk perception theories predict that if people will experience a threat, they want to counter that threat. However, how they do so is determined by their coping efficacy level: if efficacy is high, they may change their behaviour in the suggested direction; if efficacy is low, they react defensively. Research on fear appeals should be methodologically sound, comparing a threatening to a non-threatening intervention under high and low efficacy levels, random assignment and measuring behaviour as outcome. We critically review extant empirical evidence and conclude that it does not support positive effects of fear appeals. Nonetheless, their use persists and is even promoted by health psychology researchers, causing scientific insights to be ignored or misinterpreted.

We argue that the active ingredients of behaviour change interventions, often called behaviour change methods (BCMs) or techniques (BCTs), can usefully be placed on a dimension of psychological aggregation. We introduce evolutionary learning processes (ELPs) as fundamental building blocks that are on a lower level of psychological aggregation than BCMs/BCTs. A better understanding of ELPs is useful to select the appropriate BCMs/BCTs to target determinants of behaviour, or vice versa, to identify potential determinants targeted by a given BCM/BCT, and to optimally translate them into practical applications. Using these insights during intervention development may increase the likelihood of developing effective interventions - both in terms of behaviour change as well as maintenance of behaviour change.

Cronbach's alpha is a commonly reported estimate to assess scale quality in health psychology and related disciplines. In this paper, we argue that alpha is an inadequate estimate for both validity and reliability - two key elements of scale quality. Omega is a readily available alternative that can be used for both interval and ordinal data. More importantly, we argue that factor-analytic evidence should be presented before assessing the internal structure of a scale. Finally, pointers for readers and reviewers of manuscripts on making judgements about scale quality are provided and illustrated by examples from the field of health psychology.

Health psychology developed a plethora of theories to explain and change a wide variety of behaviours. Several attempts have been undertaken to build integrative theories, some even striving for a Theory of Everything. We argue against these efforts, arguing that instead a 'pragmatic nihilism' perspective may be more fruitful to understand and change health behaviours. The first tenet of pragmatic nihilism is that psychological variables are usefully considered as metaphors rather than referring to entities that exist in the mind. As a consequence, the second tenet emphasizes theories' definitions and guidelines for the operationalisation of those variables. The third tenet of pragmatic nihilism is that each operationalisation represents an intersection of a variety of dimensions, such as behavioural specificity and duration, and most importantly, psychological aggregation level. Any operationalisation thus represents a number of choices regarding these dimensions. Pragmatic nihilism has two implications. First, it provides a foundation that enables integrating theories in a more flexible and accurate manner than made possible by integrative theories. Second, it emphasizes the importance of operationalisations, underlining the importance of investing in the careful development of measurement instruments, thorough reporting of measurement instruments' specifics and performance, and full disclosure of the instruments themselves.

In this paper, we introduce the Intervention Mapping (IM) taxonomy of behaviour change methods and its potential to be developed into a coding taxonomy. That is, although IM and its taxonomy of behaviour change methods are not in fact new, because IM was originally developed as a tool for intervention development, this potential was not immediately apparent. Second, in explaining the IM taxonomy and defining the relevant constructs, we call attention to the existence of parameters for effectiveness of methods, and explicate the related distinction between theory-based methods and practical applications and the probability that poor translation of methods may lead to erroneous conclusions as to method-effectiveness. Third, we recommend a minimal set of intervention characteristics that may be reported when intervention descriptions and evaluations are published. Specifying these characteristics can greatly enhance the quality of our meta-analyses and other literature syntheses. In conclusion, the dynamics of behaviour change are such that any taxonomy of methods of behaviour change needs to acknowledge the importance of, and provide instruments for dealing with, three conditions for effectiveness for behaviour change methods. For a behaviour change method to be effective: (1) it must target a determinant that predicts behaviour; (2) it must be able to change that determinant; (3) it must be translated into a practical application in a way that preserves the parameters for effectiveness and fits with the target population, culture, and context. Thus, taxonomies of methods of behaviour change must distinguish the specific determinants that are targeted, practical, specific applications, and the theory-based methods they embody. In addition, taxonomies should acknowledge that the lists of behaviour change methods will be used by, and should be used by, intervention developers. Ideally, the taxonomy should be readily usable for this goal; but alternatively, it should be clear how the information in the taxonomy can be used in practice. The IM taxonomy satisfies these requirements, and it would be beneficial if other taxonomies would be extended to also meet these needs.

There is a need to consolidate the evidence base underlying our toolbox of methods of behaviour change. Recent efforts to this effect have conducted meta-regressions on evaluations of behaviour change interventions, deriving each method's effectiveness from its association to intervention effect size. However, there are a range of issues that raise concern about whether this approach is actually furthering or instead obstructing the advancement of health psychology theories and the quality of health behaviour change interventions. Using examples from theory, the literature and data from previous meta-analyses, these concerns and their implications are explained and illustrated. An iterative protocol for evidence base accumulation is proposed that integrates evidence derived from both experimental and applied behaviour change research, and combines theory development in experimental settings with theory testing in applied real-life settings. As evidence gathered in this manner accumulates, a cumulative science of behaviour change can develop.

Despite decades of research, consensus regarding the dynamics of fear appeals remains elusive. A meta-analysis was conducted that was designed to resolve this controversy. Publications that were included in previous meta-analyses were re-analysed, and a number of additional publications were located. The inclusion criteria were full factorial orthogonal manipulations of threat and efficacy, and measurement of behaviour as an outcome. Fixed and random effects models were used to compute mean effect size estimates. Meta-analysis of the six studies that satisfied the inclusion criteria clearly showed a significant interaction between threat and efficacy, such that threat only had an effect under high efficacy (d = 0.31), and efficacy only had an effect under high threat (d = 0.71). Inconsistency in results regarding the effectiveness of threatening communication can likely be attributed to flawed methodology. Proper tests of fear appeal theory yielded the theoretically hypothesised interaction effect. Threatening communication should exclusively be used when pilot studies indicate that an intervention successfully enhances efficacy.