Young Adult Gambling Behaviors and their Relationship with the Persistence of ADHD

Young adulthood is a period renowned for engagement in impulsive and risky behaviors, including gambling. There are some indications that young adults exhibit higher gambling rates in comparison to older adults. Problem gambling has also been linked to ADHD. This longitudinal study examines the relationship between gambling and ADHD among an epidemiological sample of young adults (n = 235; males = 179, females = 56) aged 18-24. Results indicate that individuals who report childhood ADHD symptoms which persist into young adulthood experience greater gambling problem severity than participants with no ADHD or those with non-persistent ADHD.     

How Mood and Task Complexity Affect Children's Recognition of Others' Emotions

Previous studies examined how mood affects children's accuracy in matching emotional expressions and labels (label‐based tasks). This study was the first to assess how induced mood (positive, neutral, or negative) influenced five‐ to eight‐year‐olds' accuracy and reaction time using both context‐based tasks, which required inferring a character's emotion from a vignette, and label‐based tasks. Both tasks required choosing one of four facial expressions to respond. Children responded more accurately to label‐based questions relative to context‐based questions at the age of five to seven, but showed no differences at the age of eight, and when the emotional expression being identified was happiness, sadness, or surprise, but not disgust. For the context‐based questions, children were more accurate at inferring sad and disgusted emotions compared with happy and surprised emotions. Induced positive mood facilitated five‐year‐olds' processing (decreased reaction time) in both tasks compared with induced negative and neutral moods. Results demonstrate how task type and children's mood influence children's emotion processing at different ages.     

“It’s Not My Fault!” Status,Attributions, and Perceptions of Injustice: The Case of Custodians and Teachers

Perceptions of injustice rely upon a sense-making process in which individuals attempt to understand why and how it occurs. We draw from the attribution-of-blame model of justice judgments to examine how two work groups of disparate status make sense of the treatment and outcomes engendered by their interactions. Data from 27 in-depth interviews with custodians and teachers reveal that when custodians perceive disrespect from teachers and teachers perceive that custodians do not fulfill properly their duties, their attributions are shaped by their status position. Although both make internal attributions to each other for their injustice, teachers do not recognize how they perpetrate injustice against custodians and custodians perceive greater injustice by identifying how external factors affect their performance and blame. This unjustified blame fosters counterproductive work behaviors, illustrating how interdependencies fuel a cycle of injustice. We discuss the implications of these findings for the school and justice processes.     

Transparency in Europe: A Quantitative Study

In recent years, European pharmaceutical regulators have increasingly committed to heightening access to raw safety‐related data as part of a wave of transparency initiatives (e.g., providing public Internet‐mediated access to clinical trials data). Yet, the regulators—who are under significant pressure—have not yet benefited from a systematic review of this new policy. In seeking to inject much needed evidence, this article explores the effects of new transparency policies designed to promote meaningful communication of risks and benefits to patients. Results of a cross‐national European survey with respondents from Great Britain, the Netherlands, Spain, France, Germany, and Sweden (N = 5,648) shed light on how patients and the public are likely to react to the regulators’ new transparency policies. The findings demonstrate clear national variations in how European citizens are likely to react and emphasize the need to develop evidence‐based, reasoned transparency policies that integrate benefit‐risk communication. The authors conclude by providing six specific recommendations, informed by the study, that seek to improve the European transparency model both within the medical field and across health, safety, and environmental policy domains.     

Eliciting Subjective Survival Curves: Lessons from Partial Identification

When analyzing data on subjective expectations of continuous outcomes, researchers have access to a limited number of reported probabilities for each respondent from which to construct complete distribution functions. Moreover, reported probabilities may be rounded and thus not equal to true beliefs. Using survival expectations elicited from a representative sample from the Netherlands, we investigate what can be learned if we take these two sources of missing information into account and expectations are therefore only partially identified. We find novel evidence for rounding by checking whether reported expectations are consistent with a hazard of death that increases weakly with age. Only 39% of reported beliefs are consistent with this under the assumption that all probabilities are reported precisely, while 92% are if we allow for rounding. Using the available information to construct bounds on subjective life expectancy, we show that the data alone are not sufficiently informative to allow for useful inference in partially identified linear models, even in the absence of rounding. We propose to improve precision by interpolation between rounded probabilities. Interpolation in combination with a limited amount of rounding does yield informative intervals.     

Exhausted,Stressed, and Disengaged: Does Employment Create Burnout for Social Work Students?

Although burnout is a known risk for practitioners, some social work students may experience burnout in the classroom as a result of role conflict from balancing academics with employment. Higher rates of burnout occur in other disciplines in employed students, even higher than in professionals, because of the stress of shifting priorities between workplace and collegiate responsibilities. Employment can decrease collegiate engagement and academic competence and deter persistence to degree, all of which lead to the reduced competency associated with burnout. Additionally, physical and mental health factors are associated with role conflict, leading to a higher risk of burnout for employed students and resulting in burnout for social work students in the classroom even prior to becoming a practitioner.     

Spousal,Family and Gender Effects on Expected Retirement Age for Married Pre-retirees

The overall purpose of this study was to examine the degree to which retirement is a contextually embedded, family decision rather than an individualized, male-centric one. Using data from a 2010 survey of married pre-retirees ages 35–70 in Michigan, US, we created a General Linear Model to predict expected retirement age. The model incorporated the effect of spousal and family variables on expected retirement age, and because the work/family interface is highly gendered, we explored interactions with gender. The study used a life course perspective in its framing and analysis, and found that expected retirement age was related to both personal and family characteristics and that the relationship of spousal and family factors were gendered and complex.     

BIG DATA AND BIG CITIES: THE PROMISES AND LIMITATIONS OF IMPROVED MEASURES OF URBAN LIFE

New, “big data” sources allow measurement of city characteristics and outcome variables at higher collection frequencies and more granular geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big urban data has the most value for the study of cities when it allows measurement of the previously opaque, or when it can be coupled with exogenous shocks to people or place. We describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities. We first show how Google Street View images can be used to predict income in New York City, suggesting that similar imagery data can be used to map wealth and poverty in previously unmeasured areas of the developing world. We then discuss how survey techniques can be improved to better measure willingness to pay for urban amenities. Finally, we explain how Internet data is being used to improve the quality of city services. (JEL R1, C8, C18)