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Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.

Satisfaction with activity-based work environments (ABW environments) often falls short of expectations, with striking differences among individual workers. A better understanding of these differences may provide clues for optimising satisfaction with ABW environments and associated organisational outcomes. The current study was designed to examine how specific psychological needs, job characteristics, and demographic variables relate to satisfaction with ABW environments. Survey data collected at seven organizations in the Netherlands (N = 551) were examined using correlation and regression analyses. Significant correlates of satisfaction with ABW environments were found: need for relatedness (positive), need for privacy (negative), job autonomy (positive), social interaction (positive), internal mobility (positive), and age (negative). Need for privacy appeared to be a powerful predictor of individual differences in satisfaction with ABW environments. These findings underline the importance of providing work environments that allow for different work styles, in alignment with different psychological need strengths, job characteristics, and demographic variables. Improving privacy, especially for older workers and for workers high in need for privacy, seems key to optimizing satisfaction with ABW environments.

Misleading graphs are a source of misinformation that worry many experts. Especially people with a low graph literacy are thought to be persuaded by graphs that misrepresent the underlying data. But we know little about how people interpret misleading graphs and how these graphs influence their opinions. In this study we focus on the effect of truncating the y-axis for a line chart which exaggerates an upgoing trend. In a randomized controlled trial, we showed participants either a normal or a misleading chart, and we did so in two different contexts. After they had seen the graphs, we asked participants their opinion on the trend and to give an estimation of the increase. Finally we measured their graph literacy. Our results show that context is the only significant factor in opinion-forming; the misleading graph and graph literacy had no effect. None of these factors had a significant impact on estimations for the increase. These results show that people might be less susceptible to misleading graphs than we thought and that context has more impact than a misleading y-axis.

The introduction of computer-based testing in high-stakes examining in higher education is developing rather slowly due to institutional barriers (the need of extra facilities, ensuring test security) and teacher and student acceptance. From the existing literature it is unclear whether computer-based exams will result in similar results as paper-based exams and whether student acceptance can change as a result of administering computer-based exams. In this study, we compared results from a computer-based and paper-based exam in a sample of psychology students and found no differences in total scores across the two modes. Furthermore, we investigated student acceptance and change in acceptance of computer-based examining. After taking the computer-based exam, fifty percent of the students preferred paper-and-pencil exams over computer-based exams and about a quarter preferred a computer-based exam. We conclude that computer-based exam total scores are similar as paper-based exam scores, but that for the acceptance of high-stakes computer-based exams it is important that students practice and get familiar with this new mode of test administration.

IntroductionYouth in remission of depression or anxiety have high risks of relapse. Relapse prevention interventions may prevent chronicity. Aim of the study is therefore to (1) examine efficacy of the personalised StayFine app for remitted youth and (2) identify high-risk groups for relapse and resilience.Method and analysisIn this Dutch single-blind parallel-group randomised controlled trial, efficacy of app-based monitoring combined with guided app-based personalised StayFine intervention modules is assessed compared with monitoring only. In both conditions, care as usual is allowed. StayFine modules plus monitoring is hypothesised to be superior to monitoring only in preventing relapse over 36 months. Participants (N=254) are 13–21 years and in remission of depression or anxiety for >2 months. Randomisation (1:1) is stratified by previous treatment (no treatment vs treatment) and previous episodes (1, 2 or >3 episodes). Assessments include diagnostic interviews, online questionnaires and monitoring (ecological momentary assessment with optional wearable) after 0, 4, 12, 24 and 36 months. The StayFine modules are guided by certified experts by experience and based on preventive cognitive therapy and ingredients of cognitive behavioural therapy. Personalisation is based on shared decision-making informed by baseline assessments and individual symptom networks. Time to relapse (primary outcome) is assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia-lifetime version diagnostic interview. Intention-to-treat survival analyses will be used to examine the data. Secondary outcomes are symptoms of depression and anxiety, number and duration of relapses, global functioning, and quality of life. Mediators and moderators will be explored. Exploratory endpoints are monitoring and wearable outcomes.Ethics, funding and disseminationThe study was approved by METC Utrecht and is funded by the Netherlands Organisation for Health Research and Development (636310007). Results will be submitted to peer-reviewed scientific journals and presented at (inter)national conferences.Trial registration numberNCT05551468; NL8237.

Registered reports engender a review process in which reviewers evaluate the merits of the research question rather than the magnitude or direction of the results. In this process, authors first submit introduction, methods, and prespecified analyses sections of an article. Next, an initial peer-review process assesses the merits of the research question, in the absence of knowing the results. Worthy articles are granted an “in-principle acceptance.” The authors, then conduct their study, analyze their data, write up the remainder of their article, and resubmit it. The in-principle acceptance means that if the authors adhere to the research design as originally submitted, then the article will be accepted. Building from seven of the earliest registered reports in education research, our introduction describes the benefits, opportunities, and challenges of registered reports as a means to increasing transparency in research and reducing the number of illusory results.

Background The challenge of combining professional work and breastfeeding is a key reason why women choose not to breastfeed or to stop breastfeeding early. We posited that having access to a high-quality lactation room at the workplace could influence working mothers’ satisfaction and perceptions related to expressing breast milk at work, which could have important longer term consequences for the duration of breastfeeding. Specifically, we aimed to (1) develop a checklist for assessing the quality of lactation rooms and (2) explore how lactation room quality affects lactating mothers’ satisfaction and perceptions. Drawing on social ecological insights, we hypothesized that the quality of lactation rooms (operationalized as any space used for expressing milk at work) would be positively related to mothers’ satisfaction with the room, perceived ease of, and perceived support for milk expression at work. Methods We conducted two studies. In Study 1 we developed a lactation room quality checklist (LRQC) and assessed its reliability twice, using samples of 33 lactation rooms (Study 1a) and 31 lactation rooms (Study 1b). Data were collected in the Northern part of the Netherlands (between December 2016 and April 2017). Study 2 comprised a cross-sectional survey of 511 lactating mothers, working in a variety of Dutch organizations. The mothers were recruited through the Facebook page of a popular Dutch breastfeeding website. They completed online questionnaires containing the LRQC and measures aimed at assessing their satisfaction and perceptions related to milk expression at work (in June and July 2017). Results The LRQC was deemed reliable and easy to apply in practice. As predicted, we found that objectively assessed higher-quality lactation rooms were associated with increased levels of satisfaction with the lactation rooms, perceived ease of milk expression at work, and perceived support from supervisors and co-workers for expressing milk in the workplace. Conclusions The availability of a high-quality lactation room could influence mothers’ decisions regarding breast milk expression at work and the commencement and/or continuation of breastfeeding. Future studies should explore whether and how lactation room quality affects breastfeeding choices, and which aspects are most important to include in lactation rooms.

Linear multiregression dynamic models, which combine a graphical representation of a multivariate time series with a state space model, have been shown to be a promising class of models for forecasting traffic flow data. Analysis of flows at a busy motorway intersection near Manchester, UK, highlights two important modelling issues: accommodating different levels of traffic variability depending on the time of day and accommodating measurement errors due to data collection errors. This paper extends linear multiregression dynamic models to address these issues. Additionally, the paper investigates how close the approximate forecast limits that are usually used with the linear multiregression dynamic model are to the true, but not so readily available, forecast limits.

Many-analysts studies explore how well an empirical claim withstands plausible alternative analyses of the same dataset by multiple, independent analysis teams. Conclusions from these studies typically rely on a single outcome metric (e.g. effect size) provided by each analysis team. Although informative about the range of plausible effects in a dataset, a single effect size from each team does not provide a complete, nuanced understanding of how analysis choices are related to the outcome. We used the Delphi consensus technique with input from 37 experts to develop an 18-item subjective evidence evaluation survey (SEES) to evaluate how each analysis team views the methodological appropriateness of the research design and the strength of evidence for the hypothesis. We illustrate the usefulness of the SEES in providing richer evidence assessment with pilot data from a previous many-analysts study.