Good Friendships among Children: A Theoretical and Empirical Investigation

Ethical dimensions of friendship have rarely been explicitly addressed as aspects of friendship quality in studies of children's peer relationships. This study identifies aspects of moral virtue significant for friendship, as a basis for empirically investigating the role of ethical qualities in children's friendship assessments and aspirations. We introduce a eudaimonic conception of friendship quality, identify aspects of moral virtue foundational to such quality, review and contest some grounds on which children have been regarded as not mature enough to have friendships that require virtue, and report a qualitative study of the friendship assessments and aspirations of children aged nine and ten (n = 83). In focus group sessions conducted in ten schools across Great Britain, moral qualities figured prominently in children's assessments of friendship quality. The findings provide evidence of children having friendships exhibiting mutual respect, support, and valuing of each other's good character.     

Acculturation and adaptation of first‐ and second‐generation South Asians in Hong Kong

This study investigates the experiences of psychological and sociocultural adaptation among 404 first‐ and second‐generation South Asian immigrants in Hong Kong. Results indicate that for first‐generation immigrants, lack of host language fluency, fewer contacts and friendships with host members, the strategy of marginalisation, and perceived discrimination are all related to higher psychological distress, lower self‐esteem and less competence in sociocultural adaptation. For second‐generation individuals, although they reported higher knowledge of the host language and higher preferences the for assimilation strategy, the levels of psychological distress were higher compared with the first‐generation group. An interesting finding of this study is the preference for the marginalisation strategy as opposed to the assimilation and/or separation strategy. The findings of this study highlight the importance of considering the unique experiences of the second generation in order to further our understanding of immigration and acculturation processes.     

An Additive–Multiplicative Restricted Mean Residual Life Model

The mean residual life measures the expected remaining life of a subject who has survived up to a particular time. When survival time distribution is highly skewed or heavy tailed, the restricted mean residual life must be considered. In this paper, we propose an additive–multiplicative restricted mean residual life model to study the association between the restricted mean residual life function and potential regression covariates in the presence of right censoring. This model extends the proportional mean residual life model using an additive model as its covariate dependent baseline. For the suggested model, some covariate effects are allowed to be time‐varying. To estimate the model parameters, martingale estimating equations are developed, and the large sample properties of the resulting estimators are established. In addition, to assess the adequacy of the model, we investigate a goodness of fit test that is asymptotically justified. The proposed methodology is evaluated via simulation studies and further applied to a kidney cancer data set collected from a clinical trial.     

Decision‐Making in Paediatric Rehabilitation: Exploring Professionals' and Children's Views on Decision‐Making Involvement

The article explores the distinction that professionals make between difficult and less difficult decisions in paediatric rehabilitation interventions. This distinction is explored by looking at the involvement of two children in decisions regarding paediatric rehabilitation interventions. The article argues for a clinical practice where children's experiences are extensively used to improve practice and to accommodate the child's right to participate in medical decisions concerning their own body and life. The different ways the children and the professional describe their experiences provide an avenue for a discussion on how medical reasoning can curtail children's involvement in decisions.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

Multiobjective Prioritization Methodology and Decision Support System for Evaluating Inventory Enhancement Strategies for Disrupted Interdependent Sectors

Disruptions in the production of commodities and services resulting from disasters influence the vital functions of infrastructure and economic sectors within a region. The interdependencies inherent among these sectors trigger the faster propagation of disaster consequences that are often associated with a wider range of inoperability and amplified losses. This article evaluates the impact of inventory‐enhanced policies for disrupted interdependent sectors to improve the disaster preparedness capability of dynamic inoperability input‐output models (DIIM). In this article, we develop the dynamic cross‐prioritization plot (DCPP)—a prioritization methodology capable of identifying and dynamically updating the critical sectors based on preference assignments to different objectives. The DCPP integrates the risk assessment metrics (e.g., economic loss and inoperability), which are independently analyzed in the DIIM. We develop a computer‐based DCPP tool to determine the priority for inventory enhancement with user preference and resource availability as new dimensions. A baseline inventory case for the state of Virginia revealed a high concentration of (i) manufacturing sectors under the inoperability objective and (ii) service sectors under the economic loss objective. Simulation of enhanced inventory policies for selected critical manufacturing sectors has reduced the recovery period by approximately four days and the expected total economic loss by $33 million. Although the article focuses on enhancing inventory levels in manufacturing sectors, complementary analysis is recommended to manage the resilience of the service sectors. The flexibility of the proposed DCPP as a decision support tool can also be extended to accommodate analysis in other regions and disaster scenarios.     

Communicating Conservation Status: How Different Statistical Assessment Criteria Affect Perceptions of Extinction Risk

Although alternative forms of statistical and verbal information are routinely used to convey species’ extinction risk to policymakers and the public, little is known about their effects on audience information processing and risk perceptions. To address this gap in literature, we report on an experiment that was designed to explore how perceptions of extinction risk differ as a function of five different assessment benchmarks (Criteria A–E) used by scientists to classify species within IUCN Red List risk levels (e.g., Critically Endangered, Vulnerable), as well as the role of key individual differences in these effects (e.g., rational and experiential thinking styles, environmental concern). Despite their normative equivalence within the IUCN classification system, results revealed divergent effects of specific assessment criteria: on average, describing extinction risk in terms of proportional population decline over time (Criterion A) and number of remaining individuals (Criterion D) evoked the highest level of perceived risk, whereas the single‐event probability of a species becoming extinct (Criterion E) engendered the least perceived risk. Furthermore, participants scoring high in rationality (analytic thinking) were less prone to exhibit these biases compared to those low in rationality. Our findings suggest that despite their equivalence in the eyes of scientific experts, IUCN criteria are indeed capable of engendering different levels of risk perception among lay audiences, effects that carry direct and important implications for those tasked with communicating about conservation status to diverse publics.     

Attachment and Self‐Efficacy in Career Search Activities: A Structural Model

The author integrated attachment theory with social cognitive career theory (SCCT) to examine how attachment styles influence the career search self‐efficacy activities of interviewing, networking, job searching, and personal exploration. Using an undergraduate sample (N = 275, 81% women), the author tested a structural model. Results indicated that anxious attachment style was negatively related to interviewing self‐efficacy, whereas avoidant attachment style was negatively related to networking, job searching, and personal exploration self‐efficacy. Theoretical implications based on these findings provide support for an integrative model of attachment theory with SCCT. Career counselors are encouraged to consider clients’ attachment styles when working with individuals who are searching for employment. To help address the limitations of the study, future researchers could test the applicability of the current model with a more diverse sample.     

Social Psychology,Consumer Culture and Neoliberal Political Economy

Consumer culture and neoliberal political economy are often viewed by social psychologists as topics reserved for anthropologists, economists, political scientists and sociologists. This paper takes an alternative view arguing that social psychology needs to better understand these two intertwined institutions as they can both challenge and provide a number of important insights into social psychological theories of self‐identity and their related concepts. These include personality traits, self‐esteem, social comparisons, self‐enhancement, impression management, self‐regulation and social identity. To illustrate, we examine how elements of consumer culture and neoliberal political economy intersect with social psychological concepts of self‐identity through three main topics: ‘the commodification of self‐identity’, ‘social categories, culture and power relations’ and the ‘governing of self‐regulating consumers’. In conclusion, we recommend a decommodified approach to research with the aim of producing social psychological knowledge that avoids becoming enmeshed with consumer culture and neoliberalism.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.