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Harassment and abuse represent a pervasive and critical problem in sport with far-reaching consequences. Survivors' testimonials underscore the profound and enduring impact of these experiences at individual, interpersonal, organizational and community level. Many of their stories reveal painful inaction from responsible adults in the sport organization, aggravating the harm. Other contributing factors to the harm inflicted include a culture of silence, lack of knowledge and understanding of what constitutes abuse, unawareness of reporting and supporting mechanisms, and fear of potential consequences. While effective bystander interventions have been developed outside the sport context, particularly targeting students in higher education, such initiatives have yet to be extensively adapted and assessed within the sport context. To address this gap, the Safe Sport Allies Erasmus+ collaborative partnership relied on the intervention mapping approach as a guiding framework to systematically develop a bystander training program (i.e., Safe Sport Allies) to train youth sport participants and youth sport coaches to act as effective bystanders. The current paper describes the comprehensive development process and provides an overview of implementation and evaluation possibilities. Throughout the paper, it is explained how each step of the Intervention Mapping approach shaped the Safe Sport Allies bystander training program. The program development, and the developed plans for implementation and evaluation are presented, shedding light on challenges encountered. The bystander training program developed in this paper and the implementation and evaluation plans can serve as an outline to build future interventions within this critical domain of safeguarding in sport.

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Objective: Regression analyses are commonly used for selecting determinants to target in behavior change interventions, but the aim of this article is to explain why regression analyses are not suitable for this purpose (i.e. the regression trap). Methods: This aim is achieved by providing (1) a theoretical rationale based on overlap among determinants; (2) a mathematical rationale based on the formulas that are used to calculate regression coefficients; and (3) examples based on real-world data. Results: First, the meaning of regression coefficients is commonly explained as expressing the association between a determinant and a target behavior 'holding all other predictors constant.' We explain that this often boils down to 'neglecting a part of the psyche.' Second, we demonstrate that the interpretation of regression coefficients is distorted by correlations between determinants. Third, the examples provided demonstrate the impact this has in practice. This results in interventions targeting determinants that are less relevant and, thereby, have less impact on behavior change. Conclusion: There are theoretical, mathematical, and practical reasons why regression analyses, and by extension multivariate analyses relying on correlations, are not suitable to select determinants to target in behavior change interventions. Instead, intervention developers should consider univariate distributions and bivariate association estimates simultaneously and there are freely accessible tools available to do so.

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This paper presents a generalized registration form for systematic reviews that can be used when currently available forms are not adequate. The form is designed to be applicable across disciplines (i.e., psychology, economics, law, physics, or any other field) and across review types (i.e., scoping review, review of qualitative studies, meta-analysis, or any other type of review). That means that the reviewed records may include research reports as well as archive documents, case law, books, poems, etc. Items were selected and formulated to optimize broad applicability instead of specificity, forgoing some benefits afforded by a tighter focus. This PRISMA 2020 compliant form is a fallback for more specialized forms and can be used if no specialized form or registration platform is available. When accessing this form on the Open Science Framework website, users will therefore first be guided to specialized forms when they exist. In addition to this use case, the form can also serve as a starting point for creating registration forms that cater to specific fields or review types.

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When developing behavior change interventions in a systematic way, it is important to select determinants relevant to the target behavior. Data is needed to gain insight into the determinant structures (the relative strengths of associations between determinants and behavior) and their univariate distributions. This insight is crucial to select the most relevant determinants, but at the same time institutions tasked with behavior change (e.g. prevention organizations, municipal health services) often operate under prohibitive resource constraints, which also extend to how easily they can collect data from a sample. This paper introduces CIBERlite - an approach that furnishes the intervention developer with an idea of the relevance of a limited number of determinants using short measurements informed by theory. The first study (N = 401) in a series of three explores the convergent validity of short and full measurements of determinants derived from the Reasoned Action Approach. The short measurements are used in the main study (N = 415) that serves as a proof-of-concept for the CIBERlite plot, an efficient visualization combining data of determinant structures and their univariate distributions for eight behaviors. The unexpected patterns detected in the main study led to an expert estimation study (N = 45), which shows that individual experts have difficulty in predicting how people score on determinants. This stresses the importance of conducting determinant studies and CIBERlite is a valuable alternative to do so if resources are limited.

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Background: Epistemic Network Analysis (ENA) is a unified, quantitative - qualitative method aiming to draw from both methodological worlds by leveraging a data set containing raw and quantified qualitative data, as well as metadata about data providers or the data itself. ENA generates network models depicting the relative frequencies of co-occurrences for each unique pair of codes in designated segments of qualitative data. Methods: This step-by-step tutorial demonstrates how to model qualitative data with ENA through its quantification via coding and segmentation. Data was curated with the Reproducible Open Coding Kit (ROCK), a human- and machine-readable standard for representing coded qualitative data, enabling researchers to document their workflow, as well as organize their data in a format that is agnostic to software of any kind. Results: ENA allows researchers to obtain insights otherwise unavailable by depicting relative code frequencies and co-occurrence patterns, facilitating a comparison of those patterns between groups and individual data providers. Conclusions: ENA aids reflexivity, moves beyond code frequencies to depict their interactions, allows researchers to easily create post-hoc groupings of data providers for various comparisons, and enables conveying complex results in a visualization that caters to both qualitative and quantitative sensibilities.

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Background: Digital health literacy (DHL) is the ability to find, understand, and appraise online health-related information, as well as apply it to health behavior. It has become a core competence for navigating online information and health service environments. DHL involves solving ill-structured problems, where the problem and its solution are not clearcut and may have no single answer, such as in the process of sensemaking. We employ and expand on information foraging theory to address how experts and novices in information retrieval perform a search task. Our overarching aim is to pinpoint best practices and pitfalls in understanding and appraising health-related information online to develop a digital intervention to increase DHL and critical thinking. Methods: In this feasibility study, we recruited a total of twenty participants for our expert and novice subsamples. We collected sociodemographic data with a self-developed survey, video data through an observation protocol of a 10-minute search task, as well as audio-video data via a retrospective think-aloud. The three, multimodal data streams were transcribed and aligned. Codes were developed inductively in several iterations, then applied deductively to the entire dataset. Tabularized, coded and segmented qualitative data were used to create various quantitative models, which demonstrate viability for the qualitative and statistical comparison of our two subsamples. Results: Data were visualized with Epistemic Network Analysis to analyze code co-occurrences in the three aligned data streams, and with Qualitative/Unified Exploration of State Transitions to examine the order in which participants in our two subsamples encountered online content. Conclusions: This paper describes our methods and planned analyses elaborated with mock figures. Quantifying qualitative data, aligning data streams, and representing all information in a tabularized dataset allows us to group data according to various participant attributes and employ data visualization techniques to pinpoint patterns therein.

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Background: Behavior change interventions have a vital role in enhancing human health and well-being. Nevertheless, concerns have been raised about suboptimal reporting of behavior change interventions, making analyses, replications, and intervention re-use hard or impossible to conduct. Objective: This paper introduces acyclic behavior change diagrams (ABCDs) to achieve more transparent development, evaluation, and reporting of behavior change interventions. ABCDs are a visual representation of the assumptions regarding causal-structural chains that underlie putative active ingredients of behavior change interventions. These causal-structural chains link the behavior change principles that are applied in an intervention to the (determinants of) behavior targeted in that intervention. Conclusions: ABCDs are helpful in making implicit assumptions explicit and help communicate assumptions with team members and other stakeholders. Moreover, we believe they make evaluation easier, and their machine-readability allows for ABCDs to be imported directly into (systematic review) databases with negligible costs while disclosing complete and accurate data. Finally, the ABCD approach fits well with other initiatives to gain a deeper understanding and synthesis of the literature on active intervention elements.

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Given their central role and position, coaches are instrumental in creating safe sport environments, especially in preventing sexual violence, but little is known about bystander behaviors, hampering the development of effective bystander programs in the context of sport. To identify determining characteristics of bystander behavior, 1,442 Belgian youth sport coaches completed an online questionnaire on bystander-related attitudes, norms, autonomy beliefs, and self-efficacy using two hypothetical scenarios of sexual violence in the sports club. Data were analyzed using confidence interval-based estimation of relevance (CIBER). A total of 127 coaches had witnessed sexual violence over the past year, most but not all intervened. Experiential attitude expectation, instrumental attitude evaluation, perceived referent behavior and approval, and subskill presence were positively associated with coaches' intention to intervene. Of the determinants of positive coach-bystander behavior, attitude and perceived norms proved key constituents for programs addressing sexual violence in youth sport. We conclude that interventions aiming at increasing positive affective consequences, reinforcing the sense of group membership, and strengthening the social norm of intervening in case of signs of sexual violence may be most influential to stimulate positive coach-bystander behavior.

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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.

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BACKGROUND: Self-identity has frequently been proposed as a useful addition to the Theory of Planned Behavior; yet Fishbein and Ajzen decided to not include self-identity when they published that theory's successor, the Reasoned Action Approach. One of their reasons for exclusion is the lack of clear conceptual independence, as manifested in self-identity operationalizations that often conflate the construct with attitudinal or normative measures. Therefore, establishing whether self-identity has added value in the Reasoned Action Approach first requires synthesis of the used operationalisations to develop an operationalization that captures self-identity but not attitude and perceived norm. METHOD: In this systematic review we identified 153 articles through the PsycINFO database and descendency approach using Google Scholar. In total, 342 of the operationalisations of self-identity were identified in studies operationalizing it as a potential Reasoned Action Approach extension. RESULTS AND CONCLUSIONS: After analyzing the full item pool to eliminate duplicates and items that did not measure selfidentity, (also) measured attitudes or norms, did not allow tailoring formulations to target, action, context and time, were not applicable to a wide variety of behaviors, or were ambiguous, seven prototypical items remained. These items lend themselves well for further psychometric study to establish the conceptual independence of self-identity from other Reasoned Action Approach constructs such as attitude and perceived norms.

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BACKGROUND: Ecstasy (3,4-methylenedioxymethamphetamine (MDMA)) has a relatively low harm and low dependence liability but is scheduled on List I of the Dutch Opium Act ('hard drugs'). Concerns surrounding increasing MDMA-related criminality coupled with the possibly inappropriate scheduling of MDMA initiated a debate to revise the current Dutch ecstasy policy. METHODS: An interdisciplinary group of 18 experts on health, social harms and drug criminality and law enforcement reformulated the science-based Dutch MDMA policy using multi-decision multi-criterion decision analysis (MD-MCDA). The experts collectively formulated policy instruments and rated their effects on 25 outcome criteria, including health, criminality, law enforcement and financial issues, thematically grouped in six clusters. RESULTS: The experts scored the effect of 22 policy instruments, each with between two and seven different mutually exclusive options, on 25 outcome criteria. The optimal policy model was defined by the set of 22 policy instrument options which gave the highest overall score on the 25 outcome criteria. Implementation of the optimal policy model, including regulated MDMA sales, decreases health harms, MDMA-related organised crime and environmental damage, as well as increases state revenues and quality of MDMA products and user information. This model was slightly modified to increase its political feasibility. Sensitivity analyses showed that the outcomes of the current MD-MCDA are robust and independent of variability in weight values. CONCLUSION: The present results provide a feasible and realistic set of policy instrument options to revise the legislation towards a rational MDMA policy that is likely to reduce both adverse (public) health risks and MDMA-related criminal burden.

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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 pre-event 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.

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OBJECTIVE: 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). RESULTS: 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. CONCLUSION: 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.

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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.

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BACKGROUND: Since desk-dominated work environments facilitate sedentary behavior, office workers sit for 66% of their working days and only 8% succeed in interrupting their prolonged periods of sitting within the first 55 minutes. Yet stretches of long and uninterrupted sitting increase the likelihood of several chronic metabolic and cardiovascular diseases. OBJECTIVE: We therefore developed a computer-based app designed to interrupt periods of prolonged sitting among office employees. METHODS: When developing the intervention, we applied the intervention mapping protocol. This approach for the systematic design of theory and evidence-based behavior change programs consists of 6 steps: creation of a logic model of the problem, creation of a logic model of change, program design, program production, design of an implementation plan, and development of an evaluation plan. RESULTS: Working through all 6 steps has resulted in an individually adaptable intervention to reduce sedentary behavior at work. The intervention, UPcomplish, consists of tailored, half-automatized motivational components delivered by a coach. To register sedentary behavior, the VitaBit (VitaBit Software International BV) toolkit, a wearable accelerometry-based monitoring device, is used. Among others, UPcomplish includes personalized goal setting, tailored suggestions to overcome hurdles, and weekly challenges. The VitaBit toolkit supports the participants to monitor their behavior in relation to self-set goals. CONCLUSIONS: Intervention mapping is a useful protocol not only for the systematic development of a comprehensive intervention to reduce sedentary behavior but also for planning program adherence, program implementation, and program maintenance. It facilitates obtaining the participation of relevant stakeholders at different ecological levels in the development process of the intervention and anticipating facilitators to and barriers of program implementation and maintenance. TRIAL REGISTRATION: Netherlands Trial Register NL7503; https://www.trialregister.nl/trial/7503.

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Objective: We aimed to map attitudes underlying complementary and alternative medicine (CAM) use, especially those involved in "dysfunctional CAM reliance," that is, forgoing biomedical treatment in a life-threatening situation in favor of alternative treatment. Analyses of modifiable determinants of CAM use were conducted at a sufficiently specific level to inform intervention development. Methods: We collected usable data on CAM-related attitudinal beliefs from 151 participants in Budapest with varying degrees of CAM use, which we analyzed using confidence interval-based estimation of relevance plots. Results: Although there were beliefs that the entire sample shared, there was a marked difference between the biomedical and CAM groups. These differences were beliefs concerning trust in various medical systems, the level of importance assigned to emotions in falling ill, and vitalism or Eastern concepts. Regarding CAM users in general, the most successful intervention targets are beliefs in vitalism on the one hand, and distrust in biomedicine on the other. In addressing dysfunctional CAM use specifically, the most significant beliefs pertain to "natural" cures and reliance on biomedical testing. Conclusions: Albeit much research has been carried out on the motivations behind CAM use, rarely do studies treat CAM users separately in order to scrutinize patterns of nonconventional medicine use and underlying cognition. This is the first study to begin pinpointing specific attitudes involved in dysfunctional CAM use to inform future intervention development. Such interventions would be essential for the prevention of incidents and mortality.

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INTRODUCTION: Fetal alcohol spectrum disorders (FASD) is an important preventable public health concern, associated to a number of common pediatric problems such as incontinence. Little is known about the prevalence and presentation of incontinence in FASD, which hinders effective management. OBJECTIVE: The aim of the present study was to investigate incontinence among people with FASD. STUDY DESIGN: Parental questionnaires were sent to all eligible FASD participants. To enable comparing the observed prevalence with typically developing, non-prenatally alcohol-exposed individuals, two clinical control groups of patients undergoing immunotherapy for pollen allergy (GKA) and patients diagnosed with celiac disease (GKG) were selected. RESULTS: A total of 119 participants were included in the study (FAS: n = 24, partial fetal alcohol syndrome [pFAS]: n = 19, alcohol-related neurodevelopmental disorder [ARND]: n = 28, GKA: n = 34, and GKG: n = 14). Overall incontinence for FASD was estimated to be 24% (confidence interval [CI] ranges from 15 to 36); nocturnal enuresis (NE) was present in 10% (CI ranges from 4 to 19), daytime urinary incontinence (DUI) in 11% (CI ranges from 5 to 21), and fecal incontinence (FI) in 13% (CI ranges from 6 to 23). Symptoms of urgency were present for 52%, voiding postponement for 10%, and straining for 2%. These data are both consistent with higher prevalence in individuals with FASD and with similar prevalence (the CIs overlap). CONCLUSION: Children and adolescents with FAS, pFAS, ARND, GKA, and GKG are affected by incontinence. Highest rates were observed in pFAS and ARND. Persons with FAS were mostly affected by DUI, those with pFAS by NE, and those with ARND by FI.

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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.

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BACKGROUND: Unbearable suffering is a key criterion in legally granting patients' euthanasia requests in Belgium yet a generally accepted definition of unbearable suffering remains elusive. The ability to understand and assess unbearable suffering is essential, particularly in patients with psychiatric conditions, as the underlying causes of these conditions are not always apparent. To enable research into when and why suffering experiences incite patients with psychiatric conditions to request euthanasia, and to help explore preventive and curative perspectives, the development of an assessment instrument is needed. AIMS: To improve the cognitive validity of a large initial item pool used to assess the nature and extent of suffering in patients with psychiatric conditions. METHOD: Cognitive validity was established via two rounds of cognitive interviews with patients with psychiatric conditions with (n = 9) and without (n = 5) euthanasia requests. RESULTS: During the first round of cognitive interviews, a variety of issues relating to content, form and language were reported and aspects that were missing were identified. During the second round, the items that had been amended were perceived as sufficiently easily to understand, sensitive to delicate nuances, comprehensive and easy to answer accurately. Neither research topic nor method were perceived as emotionally strenuous, but instead as positive, relevant, comforting and valuable. CONCLUSIONS: This research resulted in an item pool that covers the concept of suffering more adequately and comprehensively. Further research endeavours should examine potential differences in suffering experiences over time and in patients with psychiatric conditions with and without euthanasia requests. The appreciation patients demonstrated regarding their ability to speak extensively and openly about their suffering and wish to die further supports the need to allow patients to speak freely and honestly during consultations. DECLARATION OF INTERESTS: None.

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The General Data Protection Regulation (GDPR) is the new European Union-wide (EU) law on data protection, which is a great step towards more comprehensive and more far-reaching protection of individuals' personal data. In this editorial, we describe why and how we - as researchers within the field of health psychology - should care about the GDPR. In the first part, we explain when the GDPR is applicable, who is accountable for data protection, and what is covered by the notions of personal data and processing. In the second part, we explain aspects of the GDPR that are relevant for researchers within the field of health psychology (e.g., obtaining informed consent, data minimisation, and open science). We focus on questions that researchers may ask themselves in their daily practice. Compliance with the GDPR requires adopting research practices (e.g., data minimisation and anonymization procedures) that are not yet commonly used, but serve the fundamental right to protection of personal data of study participants.

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