Individual and Country‐Level Effects of Social Trust on Happiness: The Asia Barometer Survey

The relationship of individual‐level and country‐level social trust to individuals' happiness was investigated, using cross‐national data of 39,082 participants from 29 Asian countries. For self‐reported happiness, 2.0% of the participants responded they were very happy, while 18.7% were very unhappy. The significant variables associated with happiness were female gender, being age 20–29 years or 60–69 years, married, high income and education, students/retired/homemaker, religious belief, good health, and higher individual and aggregate social trust. Individual health, social trust, and aggregate social trust were all independently associated with people's happiness. People were more likely to be happy if they lived in countries with higher aggregate social trust than countries with poor social trust.     

Happy People Become Happier through Kindness: A Counting Kindnesses Intervention

We examined the relationship between the character strength of kindness and subjective happiness (Study 1), and the effects of a counting kindnesses intervention on subjective happiness (Study 2). In Study 1, participants were 175 Japanese undergraduate students and in Study 2, participants were 119 Japanese women (71 in the intervention group and 48 in the control group). Results showed that: (a) Happy people scored higher on their motivation to perform, and their recognition and enactment of kind behaviors. (b) Happy people have more happy memories in daily life in terms of both quantity and quality. (c) Subjective happiness was increased simply by counting one’s own acts of kindness for one week. (d) Happy people became more kind and grateful through the counting kindnesses intervention. Discussion centers on the importance of kindness in producing subjective happiness.     

Reducing Inappropriate Bicycle Parking Through Persuasive Communication

In this study, the effectiveness of persuasive communication in reducing inappropriate bicycle parking was investigated. We hypothesized that persuasive communication aimed at promoting behavioral intention with respect to reducing the frequency of inappropriate bicycle parking would not actually achieve its objective, but that persuasive communication aimed at promoting implementation intention, as well as behavioral intention, would be successful. We conducted a field experiment using 99 participants who were daily bicycle users. They were randomly assigned to a control group and to 3 experimental groups. The results indicated that participants in the with-advice group and planning group had stronger implementation intentions, and thus reduced their incidence of inappropriate bicycle parking, than did the control and the without-advice groups. However, there were no differences in behavioral intention.     

Is There Really a Beauty Premium or an Ugliness Penalty on Earnings?

Purpose

Economists have widely documented the “beauty premium” and “ugliness penalty” on earnings. Explanations based on employer and client discrimination would predict a monotonic association between physical attractiveness and earnings; explanations based on occupational self-selection would explain the beauty premium as a function of workers’ occupations; and explanations based on individual differences would predict that the beauty premium would disappear once appropriate individual differences are controlled. In this paper, we empirically tested the three competing hypotheses about the “beauty premium”.

Design/Methodology/Approach

We analyzed a nationally representative and prospectively longitudinal sample from the National Longitudinal Survey of Adolescent Health (Add Health).

Findings

The results contradicted the discrimination and self-selection explanations and strongly supported the individual differences explanation. Very unattractive respondents always earned significantly more than unattractive respondents, sometimes more than average-looking or attractive respondents. Multiple regression analyses showed that there was very weak evidence for the beauty premium, and it disappeared completely once individual differences, such as health, intelligence, and Big Five personality factors, were statistically controlled.

Implications

Past findings of beauty premium and ugliness penalty may possibly be due to the fact that: 1) “very unattractive” and “unattractive” categories are usually collapsed into “below average” category; and 2) health, intelligence (as opposed to education) and Big Five personality factors are not controlled. It appears that more beautiful workers earn more, not because they are beautiful, but because they are healthier, more intelligent, and have better (more Conscientious and Extraverted, and less Neurotic) personality.

Originality/Value

This is the first study to show that: 1) very unattractive workers have extremely high earnings and earn more than physically more attractive workers, suggesting evidence for the potential ugliness premium; and 2) the apparent beauty premium and ugliness penalty may be a function of unmeasured traits correlated with physical attractiveness, such as health, intelligence, and personality.

     

What Makes for a Good Life? A Four-Nation Study

How do we assess the value of our lives? What makes the life we live a good or worthy one in our own eyes? What are its aims? The answers to these questions are implicit in the often unarticulated commitments by which people define their selves, purposes, and actions. These commitments structure the moral framework that guides our everyday qualitative distinctions and positions us within a unified narrative of continuity and change. The substantive conception of a good life, we argue, presupposes but is not reducible to a set of basic values. As an initial exploration of cultural variation, Canadian, Chinese, Indian, and Japanese university students were compared on what they held to be most important for assessing the worth of their lives. The results revealed considerable commonality of content with notable differences consistent with the cultural ethos of each group.     

Constrained k‐means on cluster proportion and distances among clusters for longitudinal data analysis

Clustering individuals by measures of similarity or dissimilarity at trajectories of changes in longitudinal data enables determination of typical patterns of development and growth. The present research proposes a new constrained k‐means method with lower bound constraints on cluster proportions and distances among clusters at focused variables and time points to fulfill various needs in clustering longitudinal data. The method assumes a large number of clusters at the onset and iteratively deletes and combines clusters according to these constraints. An additional property of the proposed constrained k‐means includes direct estimation of the unknown number of clusters. Simulation results clearly show the usefulness of the method for extracting clusters in plausible, real‐life analysis including non‐normality within clusters, and the proposed algorithm works well and convergence of the estimates is satisfactory. An actual example using Japanese longitudinal data regarding sleep habits and mental health is presented to verify the utility of the proposed constrained k‐means.     

Accelerating heterogeneous nucleation to increase hardness and electrical conductivity by deformation prior to ageing for Cu-4 at.% Ti alloy

ABSTRACT

Deformation bands, especially shear bands were intentionally formed in supersaturated Cu-4 at.% Ti alloy by groove-rolling with 75% area reduction. Cold deformation prior to the ageing process changed the precipitation behaviour of the alloy. The deformed structure with shear bands was maintained, without showing recovery and recrystallisation, even after prolonged ageing at 450°C for more than one day. The thermally stable shear bands act as nucleation initiation sites and prevent the expansion of discontinuous cellular precipitates. The hardness reached a value of 305?Hv and an electrical conductivity of 15% IACS (IACS?=?International Annealed Copper Standard. 100% IACS is defined as the conductivity corresponding to a volume resistivity at 20°C of 17.241?nΩ), compared to 283?Hv and 13% IACS for conventional solid-solutioned and peak-hardened alloy. In addition, the ageing time to reach the highest hardness was shortened from 720 to 180?min at 450°C.     

Evolution of a sharp {110} texture in microcrystalline Fe78Si9B13 during magnetic crystallization from the amorphous phase

The effect of magnetic crystallization on texture evolution and control in nanocrystalline materials has been studied using a melt-spun amorphous Fe₇₈Si₉B₁₃ alloy. The magnetic crystallization was conducted at temperatures ranging from 653 to 853?K in a magnetic field up to 6?T. The temperatures used for magnetic crystallization were chosen on the basis of the Curie and crystallization temperatures of the amorphous phase, and the Curie temperature of the crystallized phase. The resultant microstructure was characterized by X-ray diffraction and FE-SEM/EBSP/OIM techniques. It was found that a sharp {110} texture developed when the amorphous precursor was crystallized at 853?K in a magnetic field of 6?T applied in a direction parallel to the ribbon surface.     

On the Mathematical Relationship Between Latent Change Score and Autoregressive Cross-Lagged Factor Approaches: Cautions for Inferring Causal Relationship Between Variables

The present paper focuses on the relationship between latent change score (LCS) and autoregressive cross-lagged (ARCL) factor models in longitudinal designs. These models originated from different theoretical traditions for different analytic purposes, yet they share similar mathematical forms. In this paper, we elucidate the mathematical relationship between these models and show that the LCS model is reduced to the ARCL model when fixed effects are assumed in the slope factor scores. Additionally, we provide an applied example using height and weight data from a gerontological study. Throughout the example, we emphasize caution in choosing which model (ARCL or LCS) to apply due to the risk of obtaining misleading results concerning the presence and direction of causal precedence between two variables. We suggest approaching model specification not only by comparing estimates and fit indices between the LCS and ARCL models (as well as other models) but also by giving appropriate weight to substantive and theoretical considerations, such as assessing the justifiability of the assumption of random effects in the slope factor scores.     

Time-specific Errors in Growth Curve Modeling: Type-1 Error Inflation and a Possible Solution with Mixed-Effects Models

Growth curve modeling (GCM) has been one of the most popular statistical methods to examine participants’ growth trajectories using longitudinal data. In spite of the popularity of GCM, little attention has been paid to the possible influence of time-specific errors, which influence all participants at each timepoint. In this article, we demonstrate that the failure to take into account such time-specific errors in GCM produces considerable inflation of type-1 error rates in statistical tests of fixed effects (e.g., coefficients for the linear and quadratic terms). We propose a GCM that appropriately incorporates time-specific errors using mixed-effects models to address the problem. We also provide an applied example to illustrate that GCM with and without time-specific errors would lead to different substantive conclusions about the true growth trajectories. Comparisons with other models in longitudinal data analysis and potential issues of model misspecification are discussed.