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Experimental tests of interventions need to have sufficient sample size to constitute a robust test of the intervention's effectiveness with reasonable precision and power. To estimate the required sample size adequately, researchers are required to specify an effect size. But what effect size should be used to plan the required sample size? Various inroads into selecting the a priori effect size have been suggested in the literature—including using conventions, prior research, and theoretical or practical importance. In this paper, we first discuss problems with some of the proposed methods of selecting the effect size for study planning. We then lay out a method for intervention researchers that provides a way out of many of these problems. The proposed method requires setting a meaningful change definition, it is specifically suited for applied researchers interested in planning tests of intervention effectiveness. We provide a hands-on walk through of the method and provide easy-to-use R functions to implement it. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract Background Threatening health messages that focus on severity are popular, but frequently have no effect or even a counterproductive effect on behavior change. This paradox (i.e. wide application despite low effectiveness) may be partly explained by the intuitive appeal of threatening communication: it may be hard to predict the defensive reactions occurring in response to fear appeals. We examine this hypothesis by using two studies by Brown and colleagues, which provide evidence that threatening health messages in the form of distressing imagery in anti-smoking and anti-alcohol campaigns cause defensive reactions. Methods We simulated both Brown et al. experiments, asking participants to estimate the reactions of the original study subjects to the threatening health information (n = 93). Afterwards, we presented the actual original study outcomes. One week later, we assessed whether this knowledge of the actual study outcomes helped participants to more successfully estimate the effectiveness of the threatening health information (n = 72). Results Results showed that participants were initially convinced of the effectiveness of threatening health messages and were unable to anticipate the defensive reactions that in fact occurred. Furthermore, these estimates did not improve after participants had been explained the dynamics of threatening communication as well as what the effects of the threatening communication had been in reality. Conclusions These findings are consistent with the hypothesis that the effectiveness of threatening health messages is intuitively appealing. What is more, providing empirical evidence against the use of threatening health messages has very little effect on this intuitive appeal.

Abstract Background While the health risks of using ecstasy warrant intervention development, a recent meta-analysis of determinants of ecstasy use identified a number of lacunae in the literature. Specifically, no studies were included that address behaviours other than 'using ecstasy' (e.g. 'trying out ecstasy' or 'ceasing ecstasy use'). However, because meta-analyses aim to integrate study results quantitatively, the resulting rigid exclusion criteria cause many studies to be discarded on the basis of their qualitative methodology. Such qualitative studies may nonetheless provide valuable insights to guide future research. To provide an overview of these insights regarding ecstasy use, the current study summarizes and combines what is known from qualitative and exploratory quantitative literature on ecstasy use. Methods The databases PsycINFO and MedLine were searched for publications reporting reasons for ecstasy use and related behaviour, and the results were structured and discussed per behaviour and compared over behaviours. Results Two main categories of reasons were found. The first category comprised reasons to start using ecstasy, use ecstasy, use ecstasy more often, and refrain from ceasing ecstasy use. The second category comprised reasons to refrain from starting to use ecstasy, use less ecstasy, and cease using ecstasy. Reasons for related behaviours within each of these two categories appear to differ, but not as substantially as between the two categories. A large number of reasons that were not yet explored in quantitative research emerged. Conclusion The current summary and combination of exploratory studies yields useful lists of reasons for each behaviour. Before these lists can inform interventions, however, they beg quantitative verification. Also, similarity of determinant configurations of different behaviours can be assessed by addressing determinants of several behaviours in one study. Another important finding is that meta-analytical integration of the literature may overlook important findings and implications. Thus, qualitative reviews remain useful instruments in setting the research agenda.

Objective: The Celebrate Safe approach is a collaboration between public health organisations and music event/venue organisers to encourage health promotion interventions in nightlife settings and at music events. The purpose of this study was to evaluate the Celebrate Safe approach with regard to its impact on use of ear plugs among visitors of music events. Design: A pre-registered cluster-randomised controlled trial conducted at music events throughout the Netherlands (k=15). In the experimental condition, event organisers were asked to share an online preevent message about ear plugs, clearly indicate where visitors could buy ear plugs, and sell ear plugs at busy locations on the premises. Visitors were encouraged to wear ear plugs by means of an 'ear check' at the beginning of the event. Study sample: Observations to assess whether event visitors wear ear plugs (N=3836). Results: A multilevel model, taking into account nesting of visitors within events, revealed that use of ear plugs at music events in the experimental condition was higher in comparison to events in the control condition (23% vs. 14%, OR = 1.9, 95%CI 1.2-3.0, p=0.004). Conclusions: The Celebrate Safe approach has a positive impact on use of ear plugs among visitors of music events. [ABSTRACT FROM AUTHOR]

Abstract Background Ecstasy (MDMA, 3, 4-methylenodioxymethamphetamine) use is widespread in the Netherlands, with a lifetime prevalence of 4.3%, and two-thirds of dance party visitors being ecstasy users. However, research into Dutch ecstasy use patterns is lacking. In addition, recent studies suggest that ecstasy users cease their use automatically, which implies that interventions would do better to better focus on the promotion of harm reduction strategies than on inducing cessation. The current study addresses this process of ecstasy cessation. Methods 32 participants from the Dutch dance scene were interviewed, and the results were systematically analysed using NVivo. Results Most ecstasy users had started to use out of curiosity. During use, users applied a host of harm reduction strategies, albeit inconsistently and sometimes incorrectly. Most users appeared to cease ecstasy use automatically because of loss of interest or changing life circumstances (e.g. a new job or relationship). Conclusion It appears that cessation of ecstasy use is largely determined by environmental variables and not by health concerns. This supports the idea that health promotion resources are better spent in trying to promote consistent and correct application of harm reduction practices than in trying to induce cessation.

Although basing conclusions on confidence intervals for effect size estimates is preferred over relying on null hypothesis significance testing alone, confidence intervals in psychology are typically very wide. One reason may be a lack of easily applicable methods for planning studies to achieve sufficiently tight confidence intervals. This paper presents tables and freely accessible tools to facilitate planning studies for the desired accuracy in parameter estimation for a common effect size (Cohen's d). In addition, the importance of such accuracy is demonstrated using data from the Reproducibility Project: Psychology (RPP). It is shown that the sampling distribution of Cohen's d is very wide unless sample sizes are considerably larger than what is common in psychology studies. This means that effect size estimates can vary substantially from sample to sample, even with perfect replications. The RPP replications' confidence intervals for Cohen's d have widths of around 1 standard deviation (95% confidence interval from 1.05 to 1.39). Therefore, point estimates obtained in replications are likely to vary substantially from the estimates from earlier studies. The implication is that researchers in psychology -and funders- will have to get used to conducting considerably larger studies if they are to build a strong evidence base. [ABSTRACT FROM AUTHOR]

Many analytical approaches to single-case data assume either linear effects (regression-based methods) or instant effects (mean-based methods). Neither assumption is realistic; therefore, these approaches' assumptions are often violated. In this article, we propose modeling curvilinear effects to appropriately parametrize the characteristics of singe-case data. Specifically, we introduce the generalized logistic function as adequate function for this situation. The merits of the proposed procedure are demonstrated using data previously used in single case research that represent typical single case data. We provide the function with auxiliary graphical options to demonstrate the model parameters. The function is freely available in the R package "userfriendlyscience." The proposed procedure is a new way to analyze single case data, which may provide applied single case researchers with a new tool to better understand their data and avoid applying methods with violated assumptions. [ABSTRACT FROM AUTHOR]