PEER PRESSURE: EXPERIMENTAL EVIDENCE FROM RESTROOM BEHAVIOR

We provide experimental evidence on the effect of peer pressure on individual behavior. Specifically, we study the effect of being exposed to an observer in a public restroom on handwashing and urinal flushing behavior. Our estimates show that being exposed to an observer increases the probability of handwashing by 13 percentage points and the probability of urinal flushing by 15 percentage points. Given that handwashing and urinal flushing have social benefits that exceed individual benefits, our findings provide support for peer pressure as an additional way of addressing the social suboptimality arising from externalities. (JEL C91, C93)     

Influence of door handles design in effort perception: accessibility and usability

The application of ergonomics in product design is essential to its accessibility and usability. The development of manual devices should be based on ergonomic principles. Effort perception analysis is an essential approach to understand the physical and subjective aspects of the interface. The objective of the present study was to analyze the effort perception during a simulated task with different door handles by Portuguese subjects of both genders and different ages. This transversal study agreed with ethical aspects. 180 subjects of both genders pertaining to three age groups have participated. Five door handles with different shapes were evaluated. A subjective numeric rating scale of 5 levels was used to evaluate the effort. For statistical analysis it was applied the Friedman non-parametric test. The results have showed no significant differences of effort perception in door handles "A" and "B"; "A" and "D"; and "D" and "C". Door handle "E" presented the lowest values of all. In general, there's an inverse relationship between the results of biomechanical studies and the effort perception of the same task activity. This shows that door handles design influence directly these two variables and can interfere in the accessibility and usability of these kinds of products.     

Investigating Validity Evidence of the Satisfaction with Life Scale Adapted for Children

This study introduces the Satisfaction with Life Scale adapted for Children (SWLS-C) and presents psychometric findings regarding its validation. The SWLS-C was adapted from the Satisfaction with Life Scale (SWLS; Diener et al. 1985), which is one of the most commonly used measures to assess satisfaction with life in adults. Three subject matter experts adapted the SWLS by changing the wording of the item stem and response format in order to make it more understandable for children. A stratified random sample of 1,233 students (48% girls) in grades 4–7 (mean age 11 years and 7 months) provided data on the SWLS-C and measures of optimism, self-concept, self-efficacy, depression, emphatic concern, and perspective taking. The SWLS-C demonstrated a unidimensional factor structure and high internal consistency. Furthermore, differential item functioning and differential scale functioning analyses indicated that the SWLS-C measures satisfaction with life in the same way for different groups of children (i.e., with regard to gender, first language learned at home—English vs. other language(s) than English—and across different grades) at the item and at the scale level. Associations between scores on the SWLS-C and demographic variables were statistically non-significant or of small effect size. In addition, the SWLS-C showed evidence of convergent and discriminant validity in relation to the other measures. Our results indicate that the SWLS-C is a psychometrically sound instrument that demonstrated evidence of construct validity for this age group. Limitations and future directions are discussed.     

Psychometric Evaluation of the Hebrew Language Version of the Satisfaction with Life Scale

The satisfaction with life scale (SWLS) is a widely accepted and widely used tool for measuring well-being. Although its potential as a cross-cultural index is recognized, an introduction and systematic validation of the Hebrew version is needed. Thus, the purpose of this study is: (1) to describe the process of developing the Hebrew version of the SWLS, and (2) to examine its construct validity as well as its internal consistency. Four hundred and eighty seven working adults completed the following self reported Hebrew language versions of the: (1) SWLS, (2) positive affect and negative affect scales (PANAS), and (3) the self-rated health (SRH) scale. In addition, as way of gathering additional evidence of validity, the SWLS was completed by proxy (i.e., each participant’s life partner or significant other). Confirmatory factor analysis supported a single-factor structure with significant correlations between the SWLS and the rest of the measures—PANAS scores, the SRH scores as well as the SWLS scores as measured by proxy. In addition, item-analysis supports the internal consistency of the scale. The Hebrew version of the SWLS is a valid and reliable scale and can be utilized in the Israeli context.     

Die Auswirkungen von Neid auf individuelle Leistungen: Ergebnisse einer Panelanalyse

Relative income differences are likely to lead to envy within a reference group. Envy in turn influences social behavior and individual performance. While positional concerns are apparent in daily life, empirical evidence is rare in the economic literature. This paper investigates the impact of the relative income position on individuals’ performance or productivity. As ?performance“ is difficult to measure we turn to soccer players whose performance has been well documented. The broad sample covers eight seasons of the German premier soccer league (Bundesliga) between 1995 and 2004, and includes 1040 players, a salary proxy and several performance variables. The results show that player performance is strongly affected by relative income position. A disadvantage in the relative income position reduces productivity. The larger the income differences within a team, the stronger are the effects of positional concern. Team composition also significantly affects behaviour.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.     

Bayesian mixture modeling for spatial Poisson process intensities,with applications to extreme value analysis

We propose a method for the analysis of a spatial point pattern, which is assumed to arise as a set of observations from a spatial nonhomogeneous Poisson process. The spatial point pattern is observed in a bounded region, which, for most applications, is taken to be a rectangle in the space where the process is defined. The method is based on modeling a density function, defined on this bounded region, that is directly related with the intensity function of the Poisson process. We develop a flexible nonparametric mixture model for this density using a bivariate Beta distribution for the mixture kernel and a Dirichlet process prior for the mixing distribution. Using posterior simulation methods, we obtain full inference for the intensity function and any other functional of the process that might be of interest. We discuss applications to problems where inference for clustering in the spatial point pattern is of interest. Moreover, we consider applications of the methodology to extreme value analysis problems. We illustrate the modeling approach with three previously published data sets. Two of the data sets are from forestry and consist of locations of trees. The third data set consists of extremes from the Dow Jones index over a period of 1303 days.     

Bayesian adaptive dose‐escalation procedures for binary and continuous responses utilizing a gain function

One of the main aims of early phase clinical trials is to identify a safe dose with an indication of therapeutic benefit to administer to subjects in further studies. Ideally therefore, dose‐limiting events (DLEs) and responses indicative of efficacy should be considered in the dose‐escalation procedure. Several methods have been suggested for incorporating both DLEs and efficacy responses in early phase dose‐escalation trials. In this paper, we describe and evaluate a Bayesian adaptive approach based on one binary response (occurrence of a DLE) and one continuous response (a measure of potential efficacy) per subject. A logistic regression and a linear log‐log relationship are used respectively to model the binary DLEs and the continuous efficacy responses. A gain function concerning both the DLEs and efficacy responses is used to determine the dose to administer to the next cohort of subjects. Stopping rules are proposed to enable efficient decision making. Simulation results shows that our approach performs better than taking account of DLE responses alone. To assess the robustness of the approach, scenarios where the efficacy responses of subjects are generated from an E _max model, but modelled by the linear log–log model are also considered. This evaluation shows that the simpler log–log model leads to robust recommendations even under this model showing that it is a useful approximation to the difficulty in estimating E _max model. Additionally, we find comparable performance to alternative approaches using efficacy and safety for dose‐finding. Copyright © 2015 John Wiley & Sons, Ltd.     

Ordinal independence in nonlinear utility theory

Individual behavior under uncertainty is characterized using a new axiom, ordinal independence, which is a weakened form of the von Neumann-Morgenstern independence axiom It states that if two distributions share a tail in common, then this tail can be modified without altering the individual's preference between these distributions. Preference is determined by the tail on which the distributions differ. This axiom implies an appealing and simple functional form for a numerical representation of preferences. It generalizes the form of anticipated utility, and it explains some well-known forms of behavior, such as the Friedman-Savage paradox, that anticipated utility cannot.