No abstract

The self-concept maintenance theory holds that many people will cheat in order to maximize self-profit, but only to the extent that they can do so while maintaining a positive self-concept. Mazar, Amir, and Ariely (2008, Experiment 1) gave participants an opportunity and incentive to cheat on a problem-solving task. Prior to that task, participants either recalled the Ten Commandments (a moral reminder) or recalled 10 books they had read in high school (a neutral task). Results were consistent with the self-concept maintenance theory. When given the opportunity to cheat, participants given the moral-reminder priming task reported solving 1.45 fewer matrices than did those given a neutral prime (Cohen's d = 0.48); moral reminders reduced cheating. Mazar et al.'s article is among the most cited in deception research, but their Experiment 1 has not been replicated directly. This Registered Replication Report describes the aggregated result of 25 direct replications (total N = 5,786), all of which followed the same preregistered protocol. In the primary meta-analysis (19 replications, total n = 4,674), participants who were given an opportunity

No abstract

Abstract. In prior research, goal structures have been measured as macroscopic and holistic constructs referring to all activities in the classroom setting associated with learning and performing on a meta-level. A more comprehensive approach for identifying concrete classroom structures that should foster students’ mastery goals is provided by the multidimensional TARGET framework with its six instructional dimensions (Task, Autonomy, Recognition, Grouping, Evaluation, Time). However, measurement instruments assessing students’ perceptions of all TARGET dimensions are largely lacking. The main aim of this study was to develop and validate a new student questionnaire for comprehensive assessment of the perceived TARGET classroom structure (the Goal Structure Questionnaire – GSQ). Scales were constructed using a rational-empirical strategy based on classical conceptions of the TARGET dimensions and prior empirical research. The instrument was tested in a study using a sample of 1,080 secondary school students. Findings indicate that the scales are reliable, internally valid, and externally valid in terms of relationships with students’ achievement goals. More concretely, analyses revealed that the TARGET mastery goal structure positively predicts mastery goals, performance approach goals, and an incremental implicit theory of intelligence. No associations were found with performance avoidance goals.

No abstract

Objective To assess changes in daily call volumes to the US National Suicide Prevention Lifeline and in suicides during periods of wide scale public attention to the song “1-800-273-8255” by American hip hop artist Logic. Design Time series analysis. Setting United States, 1 January 2010 to 31 December 2018. Participants Total US population. Lifeline calls and suicide data were obtained from Lifeline and the Centers for Disease Control and Prevention. Main outcome measures Daily Lifeline calls and suicide data before and after the release of the song. Twitter posts were used to estimate the amount and duration of attention the song received. Seasonal autoregressive integrated moving average time series models were fitted to the pre-release period to estimate Lifeline calls and suicides. Models were fitted to the full time series with dummy variables for periods of strong attention to the song. Results In the 34 day period after the three events with the strongest public attention (the song’s release, the MTV Video Music Awards 2017, and Grammy Awards 2018), Lifeline received an excess of 9915 calls (95% confidence interval 6594 to 13 236), an increase of 6.9% (95% confidence interval 4.6% to 9.2%, P<0.001) over the expected number. A corresponding model for suicides indicated a reduction over the same period of 245 suicides (95% confidence interval 36 to 453) or 5.5% (95% confidence interval 0.8% to 10.1%, P=0.02) below the expected number of suicides. Conclusions Logic’s song “1-800-273-8255” was associated with a large increase in calls to Lifeline. A reduction in suicides was observed in the periods with the most social media discourse about the song.

Abstract. Currently, dedicated graphical displays to depict study-level statistical power in the context of meta-analysis are unavailable. Here, we introduce the sunset (power-enhanced) funnel plot to visualize this relevant information for assessing the credibility, or evidential value, of a set of studies. The sunset funnel plot highlights the statistical power of primary studies to detect an underlying true effect of interest in the well-known funnel display with color-coded power regions and a second power axis. This graphical display allows meta-analysts to incorporate power considerations into classic funnel plot assessments of small-study effects. Nominally significant, but low-powered, studies might be seen as less credible and as more likely being affected by selective reporting. We exemplify the application of the sunset funnel plot with two published meta-analyses from medicine and psychology. Software to create this variation of the funnel plot is provided via a tailored R function. In conclusion, the sunset (power-enhanced) funnel plot is a novel and useful graphical display to critically examine and to present study-level power in the context of meta-analysis.

Objective: “13 Reasons Why,” a Netflix series, included a controversial depiction of suicide that has raised fears about possible contagion. Studies of youth suicide in the United States found an increase on the order of 10% following release of the show, but this has not been replicated in other countries. This study aims to begin to address that gap by examining the relationship between the show’s release and youth suicide in Canada’s most populous province. Methods: Suicides in young people (under the age of 30) in the province of Ontario following the show’s release on March 31, 2017, were the outcome of interest. Time-series analyses were performed using data from January 2013 to March 2017 to predict expected deaths from April to December 2017 with a simple seasonal model (stationary R 2 = 0.732, Ljung-Box Q = 15.1, df = 16, P = 0.52, Bayesian information criterion = 3.09) providing the best fit/used for the primary analysis. Results: Modeling predicted 224 suicides; however, 264 were observed corresponding to 40 more deaths or an 18% increase. In the primary analysis, monthly suicides exceeded the 95% confidence limit for 3 of the 9 months (May, July, and October). Conclusion: The statistical strength of the findings here is limited by small numbers; however, the results are in line with what has been observed in the United States and what would be expected if contagion were occurring. Further research in other locations is needed to increase confidence that the associations found here are causal.