Do resources of network members help in help seeking? Social capital and health information search

Does social capital as resources of network members affect health information search? Analyzing data from the 2004 General Social Survey in the United States, this study measures two social capital indicators (average education of network members and proportion of network members with a high school degree or higher) using the name generator. Most results are consistent using those two indicators. Both indicators are positively associated with frequency of health information seeking and seekers’ frequency of use of two sources (friends or relatives and the Internet). Also average education of network members is positively associated with seekers’ diversity of used sources and frequency of consultation with medical professionals. But neither indicator is associated with seekers’ frequency of use of other four sources (health-related magazines or newsletters, general magazines, daily newspapers, and radio or television programs). The findings demonstrate the theoretical utility of social capital in the social dynamics of medical help-seeking.     

Statistical estimation of internal available bandwidth

This paper presents a method for using end-to-end available bandwidth measurements in order to estimate available bandwidth on individual internal links. The basic approach is to use a power transform on the observed end-to-end measurements, model the result as a mixture of spatially correlated exponential random variables, carryout estimation by moment methods, then transform back to the original variables to get estimates and confidence intervals for the expected available bandwidth on each link. Because spatial dependence leads to certain parameter confounding, only upper bounds can be found reliably. Simulations with ns2 show that the method can work well and that the assumptions are approximately valid in the examples.     

Toward a model of school inspections in a polycentric system

Many education systems are developing towards more lateral structures where schools collaborate in networks to improve and provide (inclusive) education. These structures call for bottom-up models of network evaluation and accountability instead of the current hierarchical arrangements where single schools are evaluated by a central agency. This paper builds on available research about network effectiveness to present evolving models of network evaluation. Network effectiveness can be defined as the achievement of positive network level outcomes that cannot be attained by individual organizational participants acting alone. Models of network evaluation need to take into account the relations between network members, the structure of the network, its processes and its internal mechanism to enforce norms in order to understand the achievement and outcomes of the network and how these may evolve over time. A range of suitable evaluation models are presented in this paper, as well as a tentative school inspection framework which is inspired by these models. The final section will present examples from Inspectorates of Education in Northern Ireland and Scotland who have developed newer inspection models to evaluate the effectiveness of a range of different networks.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

Replication: Revisiting Tversky and Shafir’s (1992) Disjunction Effect with an extension comparing between and within subject designs

Does uncertainty about an outcome influence decisions? The sure-thing principle (Savage, 1954) posits that it should not, but Tversky and Shafir (1992) found that people regularly violate it in hypothetical gambling and vacation decisions, a phenomenon they termed “disjunction effect”. Very close replications and extensions of Tversky and Shafir (1992) were conducted in this paper (N = 890, MTurk). The target article demonstrated the effect using two paradigms in a between-subject design: here, an extension also testing a within-subject design, with design being randomly assigned was added. These results were consistent with the original findings for the “paying to know“ problem (original: Cramer’s V = 0.22, 95% (CI) [0.14, 0.32]; replication: Cramer’s V = 0.30, 95% CI [0.24, 0.37]), yet not for the “choice under risk” problem (original: Cramer’s V = 0.26, 95% CI [0.14, 0.39]; replication: Cramer’s V = 0.11, 95% CI [−0.07, 0.20]). The within-subject extension showed very similar results. Implications for the disjunction effect and judgment and decision-making theory are discussed, and a call for improvements on the statistical understanding of comparisons of between-subject and within-subject designs is introduced. All materials, data, and code are available on https://osf.io/gu58m/.     

Spatial effects on individual social capital: Differentiating the constraints of local occupational structures

Recent studies have paid more attention to how position-generated social capital varies by an individual’s characteristics, and less to how geographical distributions of occupations may constrain position-specific connections. By integrating two national surveys from the United States, we differentiate the extent to which individual social capital fluctuates by occupational compositions at the county, metropolis, and state levels. Multilevel analyses show that when more people at all three levels work in education, training, and library occupations, residents have a greater chance to gain access to professional-type resources. Similar spatial effects on farming and production resources, however, are more apparent at the county level. Not only does the association between individual social capital and local occupational structures vary across different occupations, but the magnitude of such spatial effects also differs by the scope of the geographical areas. The findings underscore how contextual factors and geographical location may contribute to building occupation-specific network resources.     

Trust and the Dilemmas of Suicide Risk Assessment in Non-government Mental Health Services

Reducing suicide rates is a national mental health priority as over 2,200 people die from suicide each year in Australia. Increasingly, nongovernment organisations (NGOs) provide services to people experiencing severe and persistent mental illnesses—a significant cohort at risk of suicide. While clinical services are generally seen as the arbiters of risk, little is known of how suicide risk assessments are undertaken in NGOs. This article reports the findings of a survey-based pilot study of 44 frontline workers in mental health-focused NGOs in Tasmania, Australia, with the aim of sketching a preliminary picture of this under-studied terrain. We identified the assessment practices utilised by workers, and the challenges and dilemmas they experienced in navigating issues of trust in suicide risk assessment in contexts where they often felt vulnerable and under-prepared. We argue that these early findings demonstrate the need for organisations to foster cultures of trust to facilitate both the activities of relationship building between practitioners and clients, and those of monitoring risk.     

Building up Resilience in a Pharmaceutical Supply Chain through Inventory,Dual Sourcing and Agility Capacity

This paper is inspired by a risk management problem faced by a leading pharmaceutical company. Key operational risk mitigation measures include Risk Mitigation Inventory (RMI), Dual Sourcing and Agility Capacity. We study the relationship between these three measures by modeling the drug manufacturing firm that is exposed to supply chain disruption risk. The firm determines optimal RMI levels for assumed Dual Sourcing and Agility Capacity. We quantify the decrease in RMI levels in the presence of Dual Sourcing and Agility Capacity. Furthermore, using an example, we analyze RMI, Dual Sourcing and Agility Capacity decisions jointly. It turns out that RMI and Agility Capacity can be substitutes as long as no Dual Source is available. Once the Dual Source is available, Agility Capacity and Dual Sourcing appear to be substitutes. We further show that for long disruption times, the optimal Dual Source production rate may decrease in the disruption time. Within our modeling framework, we introduce an operational metric that quantifies Supply Chain Resilience. Supply chain disruptions can have a severe business impact and need to be managed appropriately.     

Commitment to tax compliance: Timing effect on willingness to evade

Experimental and empirical literature on individual decision-making has shown a remarkable difference between planning and ongoing decisions: when asked to plan their actions, people overweight events with low probability; on the contrary, in ongoing decisions, they tend to ignore them. We report on a laboratory experiment designed to explore the presence of this decisional inconsistency in taxpayers’ behavior, by means of a commitment system for compliance. In line with the overweighting of events with small probabilities (i.e. fiscal audits), we find that planning induces the majority of people not only to adopt a mechanism of commitment to tax compliance, but also to actually comply.