“Not for the fainthearted”: Engaging in cross-national comparative research

Gerontologists are increasingly taking up the challenge of cross-national research and while there has been an increase in reporting on the product (findings) of this type of scholarship, there has been much less written about the process (methodology) of this approach, particularly in the gerontological literature. In 2009 our newly formed research team enthusiastically embarked on a cross-national comparative research study of social isolation and aging. In this paper, we ‘publicly’ reflect on our research process, sharing what we have learned — what ‘happened’, strategies that ‘worked’, places along the way where we might have intervened to mitigate the difficulties we encountered, and the implications of our experience on our research. Integrating the knowledge gained through our lens as newcomers to international comparative research, we end by presenting a Conceptual Framework for Cross-National Research.     

An Application of Machine Learning for Predicting Rearrests: Significant Predictors for Juveniles

This study examined the influence of the individual and social background in predicting the rearrest of 1124 juveniles who were first brought into the juvenile detention center in a midsized county in California. Independent variables include demographic characteristics, first offense type, gang affiliation, usage of drug, and family characteristics. Using cross-validation to choose an appropriate machine learning model for predicting rearrest, this study identified that the most important predictors of subsequent arrest are age at first arrest, drug usage, gang affiliation, and family with government assistance. Despite the fact that blacks are overrepresented in the juvenile detention population, race was not a significant predictor for rearrest. Future research would continue to explore the utilization of machine learning adding nontraditional variables to enhance the prediction of recidivism.     

Cultural self-construction and identity formation in emerging adulthood: a study on Japanese university students and workers

Cultural pathways of identity formation have been largely unexplored. In many Asian cultures, youth are expected to concentrate on adaptation to their groups or relationships rather than pursuing their own uniqueness. Then, how do they develop a sense of identity while considering groups or relationships to be important? The purposes of this study were (a) to examine relationships between cultural self-construction (i.e. independence and interdependence) and identity processes (i.e. commitment, in-depth exploration, and reconsideration of commitment) in both societal and relational domains, and (b) to analyze the relationships of self-construction and identity processes with well-being, using a sample of Japanese emerging adults (i.e. university students and workers) aged 18–25 years. The findings indicated that relational identity was related to both independence and interdependence, whereas societal identity was mainly related to independence. Moreover, independence and identity in both societal and relational domains was positively related to well-being. Furthermore, the patterns of relationships among self-construction, identity, and well-being were found to be similar between university students and workers. These findings imply that while Japanese emerging adults have developmental needs to express one's own uniqueness, they are also directed to form a sense of identity emphasizing the maintenance of harmonious relationships with others.     

Heterogeneity of Loss Aversion in Pathological Gambling

Pathological gambling (PG) is characterized by continual repeated gambling behavior despite negative consequences. PG is considered to be a disorder of altered decision-making under risk, and behavioral economics tools were utilized by studies on decision-making under risk. At the same time, PG was suggested to be a heterogeneous disorder in terms of personality traits as well as risk attitude. We aimed to examine the heterogeneity of PG in terms of loss aversion, which means that a loss is subjectively felt to be larger than the same amount of gain. Thirty-one male PG subjects and 26 male healthy control (HC) subjects underwent a behavioral economics task for estimation of loss aversion and personality traits assessment. Although loss aversion in PG subjects was not significantly different from that in HC subjects, distributions of loss aversion differed between PG and HC subjects. HC subjects were uniformly classified into three levels (low, middle, high) of loss aversion, whereas PG subjects were mostly classified into the two extremes, and few PG subjects were classified into the middle range. PG subjects with low and high loss aversion showed a significant difference in anxiety, excitement-seeking and craving intensity. Our study suggested that PG was a heterogeneous disorder in terms of loss aversion. This result might be useful for understanding cognitive and neurobiological mechanisms and the establishment of treatment strategies for PG.     

The Structural Determinants of Mortality in Japanese Prefectures

This cross-sectional multivariate analysis of age- and sex-standardized mortality for the 47 Japanese prefectures explores and tests the hypotheses that structural pluralism and differentiation, interpreted as dimensions of social problem solving capacity, determine lower mortality rates, controlling on the availability of medical facilities. The postulated explanatory principle is that participation in community problem-solving optimizes the biological functioning of the residents, which fosters better health. A factor analysis generated two factors (plus a third index of medical facilities) that measure the structural dimensions. Regression analysis showed that pluralism predicted lower mortality for both males and females, but differentiation gave contradictory results. Surprisingly, medical facilities predicted higher male mortality. A control on the more recently industrialized and the hyper-urbanized prefectures refined the analysis so that the differentiation factor predicted consistently and the spurious correlation between medical facilities and male mortality dissolved.     

Bayesian optimization design for dose-finding based on toxicity and efficacy outcomes in phase I/II clinical trials

In phase I trials, the main goal is to identify a maximum tolerated dose under an assumption of monotonicity in dose–response relationships. On the other hand, such monotonicity is no longer applied to biologic agents because a different mode of action from that of cytotoxic agents potentially draws unimodal or flat dose–efficacy curves. Therefore, biologic agents require an optimal dose that provides a sufficient efficacy rate under an acceptable toxicity rate instead of a maximum tolerated dose. Many trials incorporate both toxicity and efficacy data, and drugs with a variety of modes of actions are increasingly being developed; thus, optimal dose estimation designs have been receiving increased attention. Although numerous authors have introduced parametric model-based designs, it is not always appropriate to apply strong assumptions in dose–response relationships. We propose a new design based on a Bayesian optimization framework for identifying optimal doses for biologic agents in phase I/II trials. Our proposed design models dose–response relationships via nonparametric models utilizing a Gaussian process prior, and the uncertainty of estimates is considered in the dose selection process. We compared the operating characteristics of our proposed design against those of three other designs through simulation studies. These include an expansion of Bayesian optimal interval design, the parametric model-based EffTox design, and the isotonic design. In simulations, our proposed design performed well and provided results that were more stable than those from the other designs, in terms of the accuracy of optimal dose estimations and the percentage of correct recommendations.     

The higher order large-deviation approximation for the distribution of the sum of independent discreterandom variables

For a sum of not identic ally but independently distributed discrete random variables, its higher order large-deviation approximation in given. They are compared with the normal and Edge-worth type approximations in various cases. Consequently, the large-deviation approximations give sufficiently accurate results.