Assessing Social Isolation: Pilot Testing Different Methods

Social isolation is a significant public health problem among many older adults; however, most of the empirical knowledge about isolation derives from community-based samples. There has been less attention given to isolation in senior housing communities. The objectives of this pilot study were to test two methods to identify socially isolated residents in low-income senior housing and compare findings about the extent of isolation from these two methods. The first method, self-report by residents, included 47 out of 135 residents who completed in-person interviews. To determine self-report isolation, residents completed the Lubben Social Network Scale 6 (LSNS-6). The second method involved a staff member who reported the extent of isolation on all 135 residents via an online survey. Results indicated that 26% of residents who were interviewed were deemed socially isolated by the LSNS-6. Staff members rated 12% of residents as having some or a lot of isolation. In comparing the two methods, staff members rated 2% of interviewed residents as having a lot of isolation. The combination of self-report and staff report could be more informative than just self-report alone, particularly when participation rates are low. However, researchers should be aware of the potential discrepancy between these two methods.     

Subsemble: an ensemble method for combining subset-specific algorithm fits

Ensemble methods using the same underlying algorithm trained on different subsets of observations have recently received increased attention as practical prediction tools for massive data sets. We propose Subsemble: a general subset ensemble prediction method, which can be used for small, moderate, or large data sets. Subsemble partitions the full data set into subsets of observations, fits a specified underlying algorithm on each subset, and uses a clever form of V-fold cross-validation to output a prediction function that combines the subset-specific fits. We give an oracle result that provides a theoretical performance guarantee for Subsemble. Through simulations, we demonstrate that Subsemble can be a beneficial tool for small- to moderate-sized data sets, and often has better prediction performance than the underlying algorithm fit just once on the full data set. We also describe how to include Subsemble as a candidate in a SuperLearner library, providing a practical way to evaluate the performance of Subsemble relative to the underlying algorithm fit just once on the full data set.     

Population-based absolute risk estimation with survey data

Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level.     

Seeking safer sexual spaces: queer and trans young people labeled with intellectual disabilities and the paradoxical risks of restriction

Young lesbian, gay, bisexual, and transgender (LGBT) people labeled with intellectual disabilities have unique sexual health needs that are not being met. Denial by others of their right to pleasure and the exercise of heightened external control over their sexuality are commonplace. Current research indicates that these youth are at heightened risk for compromised sexual health. This study aimed to explore the ways in which social and environmental conditions influence vulnerability to adverse sexual health outcomes for this population. We used a community-based research approach to conduct qualitative interviews and focus groups with 10 young LGBT people (aged 17-26) labeled with intellectual disabilities. Participants reported multiple limitations on their autonomy that resulted in having sex in places where they did not feel comfortable and were unlikely to practice safer sex. Attempts by authority figures to protect youth through limits on their autonomy may be unintentionally leading to negative sexual health outcomes.     

Coping and Post-traumatic Stress after Hurricanes Katrina and Rita: Racial Disparities in Social Work Student-Practitioners

ABSTRACT

Recent hurricanes have focused on lives and properties lost, however, additional mental health concerns may emerge in these post-disaster settings. Post-traumatic stress symptoms (PTSS) are particularly problematic for minorities due to pre-disaster disparities. Scholars must thus examine the antecedents of PTSS to support these and other vulnerable individuals and communities. This study examined racial disparities regarding active and avoidant coping, prayer, and subsequent relative contribution of each to PTSS following Hurricanes Katrina and Rita among social work student-practitioners. Using secondary data, results revealed that minority students (n = 233) used coping via prayer more often than their non-minority peers (n = 124; t = 7.18, p < .000; d = 0.76). Moderate, positive relationships emerged between avoidant coping and PTSS for both groups (r = .58–.63, p<.01), though prayer did not emerge as inversely related to PTSS as anticipated. Avoidant coping accounted for the largest variation in PTSS for both groups (β = .35–.51, p<.001). Sampling, survey methods, and PTSS measures limit generalizability and temper findings. Directions for future research include use of PTSS measures that account for severity and cultural context and examination of coping measure psychometrics. Practice implications include enhanced publicity regarding social services available to student-practitioners on college campuses and within the community.     

Individual and contextual risks of death among race and ethnic groups in the United States

An emerging area of social science research focuses on individual-level and contextual-level determinants of black-white adult mortality differentials in the United States. However, no research on adult mortality differentials has distinguished multiple Hispanic subgroups and explored the role of nativity at both the individual and contextual levels for small geographic areas. Using the 1986-1997 National Health Interview Survey-National Death Index linked file, we examine the effects of individual and contextual factors on black-white and multiple Hispanic subgroups (Mexican Americans, Puerto Ricans, and "other" Hispanic) differentials in adult mortality. In addition, we use a new, innovative geographic area--the very small area--as our contextual unit of analysis. We find that excess mortality risks for all race-ethnic groups considered are associated with not only individual characteristics, but also neighborhood characteristics. In addition, percent foreign born in a neighborhood is protective of Hispanic subgroup mortality for Puerto Rican, Mexican American, and "other" Hispanic adults in the 45-64 age category. These findings indicate a need for future research to examine more throughly the pathways through which neighborhood factors affect multiple Hispanic subgroup mortality and the role of nativity as a protective factor for older adult Hispanic mortality.     

CSP Deposition to the Alveolar Region of the Lung: Implications of Cigarette Design

Ventilated cigarettes were designed to reduce the levels of smoke under machine testing conditions; however, smokers alter their smoking pattern to compensate for the reduction in yields. A relative shift in incidence of lung cancer from the more central lung airways to the alveolar region has also been associated with ventilated cigarette use. Validated mathematical models indicate that particle deposition patterns in the lung depend on particle size and inhalation behavior, including inhalation volume, flow rate, and breath-hold time. This article finds that most mathematical models underpredict total cigarette smoke particulate (CSP) deposition in the lung, likely because they do not account for coagulation, hygroscopicity, and cloud dynamics, which may increase the effective particle diameter of CSP reaching the lung tissue. The models that include these processes indicate that puff volume would be unlikely to affect particle deposition in the lung, but puff time, inhalation depth, breath-hold time, and exhalation time may affect total deposition. Most compensation appears to occur through a combination of increased puff volume and puff flow, with possible increases in inhalation depth and breath-hold time. The complex interaction between the extent of cigarette ventilation, which can affect puffing/inhalation behavior, CSP concentration, and CSP size with CSP dose to the alveolar versus more central lung airways is described. Deposition efficiency in the alveoli could plausibly be increased through compensation, but it is still unclear whether compensation could sufficiently alter patterns of CSP deposition in the lung to elicit a shift in lung cancer sites.