Building Health Insurance Literacy: Evidence from the Smart Choice Health Insurance™ Program

With the passage of the Patient Protection and Affordable Care Act (ACA) of 2010, the health insurance literacy of Americans became a critical issue. In response, a consumer education program was created and tested by university researchers and educators associated with Cooperative Extension. This article draws extensively on the emerging literature on health insurance literacy and on data from participants in the Smart Choice Health Insurance? program. The intent of the study was to understand socio-demographic and environmental variables that predict initial health insurance literacy and gains in health insurance literacy. A standardized instrument measuring health insurance literacy was used to collect the data. Multivariate analysis showed higher income consumers demonstrated greater initial health insurance literacy scores compared to middle income consumers, whereas younger, male and lower educated consumers reported lower initial health insurance literacy. After participating in the Smart Choice Health Insurance? program, consumers who made greater gains in their health insurance literacy tended to be female, higher income, and consumers residing in states that showed supportiveness of the ACA. The findings highlight the importance of considering sociodemographic characteristics in program design and delivery, as well as how contextual issues, such as the political environment, might impact the delivery of educational efforts. Findings from the analyses help inform ways to adapt and tailor educational opportunities that focus on health insurance literacy for a range of consumers.     

An omnibus lack of fit test in logistic regression with sparse data

The usefulness of logistic regression depends to a great extent on the correct specification of the relation between a binary response and characteristics of the unit on which the response is recoded. Currently used methods for testing for misspecification (lack of fit) of a proposed logistic regression model do not perform well when a data set contains almost as many distinct covariate vectors as experimental units, a condition referred to as sparsity. A new algorithm for grouping sparse data to create pseudo replicates and using them to test for lack of fit is developed. A simulation study illustrates settings in which the new test is superior to existing ones. Analysis of a dataset consisting of the ages of menarche of Warsaw girls is also used to compare the new and existing lack of fit tests.     

Ambiguity aversion in multi-armed bandit problems

In multi-armed bandit problems, information acquired from experimentation is valuable because it tells the agent whether to select a particular option again in the future. This article tests whether people undervalue this information because they are ambiguity averse, or have a distaste for uncertainty about the average quality of each alternative. It is shown that ambiguity averse agents have lower than optimal Gittins indexes, appearing to undervalue information from experimentation, but are willing to pay more than ambiguity neutral agents to learn the true mean of the payoff distribution, appearing to overvalue objectively given information. This prediction is tested with a laboratory experiment that elicits a Gittins index and a willingness to pay on six two-armed bandits. Consistent with the predictions of ambiguity aversion, the Gittins indexes are significantly lower than optimal and willingnesses to pay are significantly higher than optimal.     

Latin hypercube sampling with multidimensional uniformity

Complex models can only be realized a limited number of times due to large computational requirements. Methods exist for generating input parameters for model realizations including Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS). Recent algorithms such as maximinLHS seek to maximize the minimum distance between model inputs in the multivariate space. A novel extension of Latin hypercube sampling (LHSMDU) for multivariate models is developed here that increases the multidimensional uniformity of the input parameters through sequential realization elimination. Correlations are considered in the LHSMDU sampling matrix using a Cholesky decomposition of the correlation matrix. Computer code implementing the proposed algorithm supplements this article. A simulation study comparing MCS, LHS, maximinLHS and LHSMDU demonstrates that increased multidimensional uniformity can significantly improve realization efficiency and that LHSMDU is effective for large multivariate problems.     

Global Health Volunteering; Understanding Organizational Goals

This paper examines the goals of organizations that sponsor short-term volunteer trips in global health, whether they be NGO’s, faith-based, educational, or corporate organizations. Results from a U.S.-based national survey of 177 such organizations and 27 interviews with trip organizers suggest that organizations often sponsor volunteer trips to achieve goals that are quite different from the improvement of health outcomes in poor countries. While providing health services is often cited as the most important goal, volunteer activity is also considered important in enhancing the organizations’ reputation, recruitment and retention, and financial well-being. The prominence of other goals has the potential for diverting resources and focus from what is presumably the primary purpose of serving host communities in the most effective manner possible.     

Beyond the urban stream syndrome: organic matter budget for diagnostics and restoration of an impaired urban river

In response to water quality standard violations linked to excessive organic matter (OM) and a lack of sampling data informing the Total Maximum Daily Load (TMDL), an organic matter budget was created to quantify and identify sources of OM in the lower Jordan River (Salt Lake City, UT). By sampling dissolved, fine and coarse particulate OM, as well as measuring ecosystem metabolism at seven different sites, the researchers aimed to identify the origin of excess OM, and understand pathways by which different size classes of the OM pool are generated. The dissolved fraction (DOM; 94 %) was found to be the dominant form of OM transported within the river with fine particulate organic matter (FPOM; 6 %) the second most abundant, and coarse particulate organic matter (CPOM; 1 %) transport relatively insignificant in the overall OM budget. Primary production exceeded respiratory losses in the upper river, and this, along with OM inputs from two tributaries (where water reclamation facilities discharge into the river) delivered excess OM to the impaired lower reaches. Increasing stream metabolism index (SMI) with distance downstream (>1 in the lower river) further demonstrated that transport of excessive organic matter into the lower river was from upstream sources and not due to lateral inputs. This simple approach to characterizing the organic matter budget as it relates to water quality in the Jordan River was effective and could serve as a model for future studies attempting to quantify and identify sources of OM in urban ecosystems.     

Individual Differences in Infant Oculomotor Behavior During the Viewing of Complex Naturalistic Scenes

Little research hitherto has examined how individual differences in attention, as assessed using standard experimental paradigms, relate to individual differences in how attention is spontaneously allocated in more naturalistic contexts. Here, we analyzed the time intervals between refoveating eye movements (fixation durations) while typically developing 11‐month‐old infants viewed a 90‐min battery ranging from complex dynamic to noncomplex static materials. The same infants also completed experimental assessments of cognitive control, psychomotor reaction times (RT), processing speed (indexed via peak look during habituation), and arousal (indexed via tonic pupil size). High test–retest reliability was found for fixation duration, across testing sessions and across types of viewing material. Increased cognitive control and increased arousal were associated with reduced variability in fixation duration. For fixations to dynamic stimuli, in which a large proportion of saccades may be exogenously cued, we found that psychomotor RT measures were most predictive of mean fixation duration; for fixations to static stimuli, in contrast, in which there is less exogenous attentional capture, we found that psychomotor RT did not predict performance, but that measures of cognitive control and arousal did. The implications of these findings for understanding the development of attentional control in naturalistic settings are discussed.     

Non-Heterosexuality,Relationships, and Young Women’s Contraceptive Behavior

Non-heterosexual young women have a higher rate of unintended pregnancy than their heterosexual peers, but their fertility behaviors are understudied. We use longitudinal data from the Relationship Dynamics and Social Life study to investigate mechanisms contributing to non-heterosexual women’s higher pregnancy risk. These data include weekly reports of relationships, sex, and contraceptive use over 30 months. We compare the relationships and fertility behaviors of three groups: exclusively heterosexual (consistent heterosexual behavior, identity, and attraction); mostly heterosexual (heterosexual identity with same-sex behavior and/or same-sex attraction); and LGBTQ (any non-heterosexual identity). We find that mostly heterosexual and LGBTQ women behave differently from exclusively heterosexual women in ways likely to elevate their risk of unintended pregnancy: more distinct partners during the study period, more sexual intercourse with men, less frequent contraceptive use, less use of a dual method (condom plus hormonal method), and more gaps in contraceptive coverage. Mostly heterosexual women resemble LGBTQ women in their contraceptive behavior but have significantly more intercourse with men, which may increase their pregnancy risk relative to both LGBTQ and exclusively heterosexual women. We conclude by considering implications for LGBTQ health and the measurement of sexual minority populations.     

The impact of mortality development on the number of centenarians in England and wales

The world is ageing both at an individual and a population level, and population ageing is truly a global phenomenon. Life expectancies at birth have increased at the global level from 47 years in the mid-20th century to around 70 years today, and are expected to rise to 76 years by the mid-21st century. The proportion of the world’s population aged 60 years and over has increased from 8 % in the mid-20th century to 12 %, and by 2050 it is expected to reach 21 %. The emergence of large numbers of centenarians has accompanied this development. This paper outlines this emergence historically and the likely growth in the number of centenarians in the 21st century, in particular in England and Wales, analysing mortality trends since 1840 and the rise in the number of centenarians in the 20th and 21st centuries. The number of centenarians in England and Wales increased from around 160 in 1922 to almost 12,500 by 2012, but if mortality at all ages had remained constant from 1912 to 2012, then by 2012 the number of centenarians would only have been around 720. By 2100, the number of centenarians is expected to reach around 1.4 million, but if future mortality at all ages were to remain constant, then by 2100 the number of centenarians would be around 78,000. However, if predicted mortality for those aged 55 years and over was to decrease by an additional 5 % every 5 years until 2100, then the number of centenarians in England and Wales would reach around 1.8 million by the end of the century.