The influence of emotional cues on prospective memory: A systematic review with meta-analyses

Remembering to perform a behaviour in the future, prospective memory, is essential to ensuring that people fulfil their intentions. Prospective memory involves committing to memory a cue to action (encoding), and later recognising and acting upon the cue in the environment (retrieval). Prospective memory performance is believed to be influenced by the emotionality of the cues, however the literature is fragmented and inconsistent. We conducted a systematic search to synthesise research on the influence of emotion on prospective memory. Sixty-seven effect sizes were extracted from 17 articles and hypothesised effects tested using three meta-analyses. Overall, prospective memory was enhanced when positively-valenced rather than neutral cues were presented (d = 0.32). In contrast, negatively-valenced cues did not enhance prospective memory overall (d = 0.07), but this effect was moderated by the timing of the emotional manipulation. Prospective memory performance was improved when negatively-valenced cues were presented during both encoding and retrieval (d = 0.40), but undermined when presented only during encoding (d = -0.25). Moderating effects were also found for cue-focality and whether studies controlled for the arousal level of the cues. The principal finding is that positively-valenced cues improve prospective memory performance and that timing of the manipulation can moderate emotional effects on prospective memory. We offer a new agenda for future empirical work and theorising in this area

Computer modeling of diabetes and Its transparency: a report on the Eighth Mount Hood Challenge

Objectives The Eighth Mount Hood Challenge (held in St. Gallen, Switzerland, in September 2016) evaluated the transparency of model input documentation from two published health economics studies and developed guidelines for improving transparency in the reporting of input data underlying model-based economic analyses in diabetes. Methods Participating modeling groups were asked to reproduce the results of two published studies using the input data described in those articles. Gaps in input data were filled with assumptions reported by the modeling groups. Goodness of fit between the results reported in the target studies and the groups’ replicated outputs was evaluated using the slope of linear regression line and the coefficient of determination (R2). After a general discussion of the results, a diabetes-specific checklist for the transparency of model input was developed. Results Seven groups participated in the transparency challenge. The reporting of key model input parameters in the two studies, including the baseline characteristics of simulated patients, treatment effect and treatment intensification threshold assumptions, treatment effect evolution, prediction of complications and costs data, was inadequately transparent (and often missing altogether). Not surprisingly, goodness of fit was better for the study that reported its input data with more transparency. To improve the transparency in diabetes modeling, the Diabetes Modeling Input Checklist listing the minimal input data required for reproducibility in most diabetes modeling applications was developed. Conclusions Transparency of diabetes model inputs is important to the reproducibility and credibility of simulation results. In the Eighth Mount Hood Challenge, the Diabetes Modeling Input Checklist was developed with the goal of improving the transparency of input data reporting and reproducibility of diabetes simulation model results

To Separate or Not to Separate Investment from Commercial Banking? An Empirical Analysis of Attention Distortion Under Multiple Tasks

In the wake of the 2008/2009 financial crisis, a number of policy reports (Vickers, Liikanen, Volcker) proposed to separate investment banking from commercial banking to increase financial stability. This paper empirically examines one theoretical justification for these proposals, namely attention distortion under multiple tasks as in Holmstrom and Milgrom (1991). Universal banks can be viewed as combining two different tasks (investment banking and commercial banking) in the same organization. We estimate pay-performance sensitivities for different segments within universal banks and for pure investment and commercial banks. We show that the pay-performance sensitivity is higher in investment banking than in commercial banking, no matter whether it is organized as part of a universal bank or in a separate institution. Next, the paper shows that relative pay-performance sensitivities of investment and commercial banking are negatively related to the quality of the loan portfolio in universal banks. Depending on the specification, we obtain a reduction in problem loans when investment banking is removed from commercial banks of up to 12 percent. We interpret the evidence to imply that the higher pay-performance sensitivity in investment banking directs the attention of managers away from commercial banking within universal banks, consistent with Holmstrom and Milgrom (1991). Separation of investment banking and commercial banking may indeed be associated with a reduction in risk in commercial banking