Quality of Life Enhancement Research Program: Lessons Learned

The attempted Quality of Life Enhancement program appeared to be a novel method for creating a symbiotic and sustainable relationship between a large Southeastern university and local nursing home and assisted living facilities (ALF), through which ALF residents would attend university arts and sporting events. During implementation, it was discovered that this project was unsustainable, undesired, unneeded by many care centers, difficult to implement, and required a dedicated and specialized staff. After attempting to enroll 14 local care facilities, only 2 were interested in becoming involved and produced 5 eligible participants. During the program itself, coordination with facilities and residents was difficult to maintain and unique transportation and accommodation needs were challenging to overcome. Finally, data collection was time consuming and generally unfruitful. Ultimately the project was discontinued after a year of attempted recruitment and implementation of inclusive changes to protocol. While creating an ongoing relationship with local care facilities and local universities may enhance opportunities for residents and research into important areas, such relationships take time, effort, and specialized staff to maintain.     

Measuring ambiguity preferences: A new ambiguity preference survey module

Journal of Risk and Uncertainty - Ambiguity preferences are important to explain human decision-making in many areas in economics and finance. To measure individual ambiguity preferences, the...     

Some implications of common consequences in lotteries

This work studies the implications of some aspects of preferences toward risk in the choice between two binary lotteries exhibiting a common consequence. The results obtained are then applied to two different problems: the choice between two risky challenges characterized by different rewards in the case of success and different probabilities of success and the choice between self-protection and self-insurance in the presence of the risk of incurring financial loss.

     

Quantile regression for large-scale data via sparse exponential transform method

In recent decades, quantile regression has received much more attention from academics and practitioners. However, most of existing computational algorithms are only effective for small or moderate size problems. They cannot solve quantile regression with large-scale data reliably and efficiently. To this end, we propose a new algorithm to implement quantile regression on large-scale data using the sparse exponential transform (SET) method. This algorithm mainly constructs a well-conditioned basis and a sampling matrix to reduce the number of observations. It then solves a quantile regression problem on this reduced matrix and obtains an approximate solution. Through simulation studies and empirical analysis of a 5% sample of the US 2000 Census data, we demonstrate efficiency of the SET-based algorithm. Numerical results indicate that our new algorithm is effective in terms of computation time and performs well for large-scale quantile regression.     

Extending Bayesian back-calculation to estimate age and time specific HIV incidence

Lifetime Data Analysis - CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their...     

Legitimacy without Mobilization? How Social Justice Organizations Defend their Democratic Credentials

Qualitative Sociology - This article examines how and with what consequences social justice organizations defend their legitimacy as democratic representatives, especially in circumstances where...     

The exponentiated power exponential regression model with different regression structures: application in nursing data

We define the exponentiated power exponential distribution and propose a regression model with different systematic structures based on the new distribution. We show that the new regression model can be applied to dispersion data since it represents a parametric family of models that includes as sub-models some widely-known regression models. It then can be used more effectively in the analysis of real data. We use maximum likelihood estimation and derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. Some global-influence measurements are also investigated and simulation studies are performed to evaluate the accuracy of the estimates. We provide an application of the regression model with four systematic structures to nursing activities score data in the Unit of the Medical Clinic of University of São Paulo (USP) Hospital.     

Gender egalitarianism,perceived economic insecurity,and fertility intentions in Spain: A qualitative analysis

Economic uncertainty contributes to low fertility in many European countries. On the other hand, greater gender equality may positively influence fertility. This paper examines how these two forces interact in Spain. We use in-depth interviews to analyse fertility decision-making among young and highly educated partnered adults living in urban areas. Highly gender-egalitarian interviewees are less likely to perceive economic insecurity as an obstacle to proceeding to a next birth than less egalitarian interviewees. But there is not necessarily a difference in these two groups’ overall fertility intentions, as highly egalitarian interviewees’ greater valuation of stable employment for both partners requires institutional and policy support for dual-earner couples’ childrearing. When we look only at interviewees who express economic insecurity, somewhat higher fertility intentions are expressed by those holding less gender-egalitarian attitudes. Our results underline the complexity of the interrelationships between economic insecurity, gender egalitarianism, and fertility intentions.     

Disparities in Healthcare Utilization Among Adults with Obesity in the United States,Findings from the NHIS: 2006–2015

Population Research and Policy Review - Few studies of disparities consider logistical hurdles faced by adults with obesity in obtaining needed healthcare. This study compared adults with obesity...     

Agency and fatalism in older Appalachian women’s information seeking about gynecological cancer

Researchers consider older women in rural Appalachia to have low levels of agency and high levels of fatalism regarding decision making about cancer treatment. Using the life course perspective, we examined older women’s agency with information seeking about gynecological cancer. Semistructured interviews with 20 White women living in central Appalachia revealed four trajectories: Surrendering Control, Accepting Death, Self-Care, and Advocacy, each with its own forms of agency. Some women experienced personal transformation, increased self-efficacy, and a passion for community empowerment. Fatalism was not understood apart from placing trust in medical expertise. We implore researchers to further explore rural expressions of agency.