State Adoption of Nursing Home Immunity From Legal Liability During the COVID-19 Pandemic

Twenty-eight states have provided nursing homes (NHs) with immunity from legal liability related to COVID-19. This study places these provisions in the context of prior actions protecting NHs from legal action and explores factors influencing the adoption of such immunity provisions across states. It uses cross-sectional data to examine patterns of policy adoption and to assess states’ likelihood of adopting immunity provisions using multivariate methods. Variables of interest include information on state political, socioeconomic, programmatic, and COVID-19-related characteristics as well as data on campaign contributions and lobbying activity at the state level. Factors significantly related to NH immunity provision adoption included measures of state fiscal health (unemployment), ideology (percent legislators Democrat), governing capacity (unified government), and NH characteristics (percent not-for-profit, hospital-based, and chain). Population density and Medicaid as a percentage of state general fund expenditures proved significant as well. Against these complex influences, organizations lobbying on behalf of NH residents and their families have found themselves ineffectual in creating avenues for accountability. Results indicate that enforcing accountability for NH deaths during the COVID-19 pandemic is a complex process, constrained by available policy tools and made more complicated by factors external to the NH environment that contributed to high death rates. Historically, the NH industry has been successful in avoiding consequences for poor quality care, a pattern that has persisted in that NHs have generally been successful in avoiding liability for negligence during the COVID-19 pandemic.

Perceptions of Local Government Fiscal Health and Fiscal Stress: Evidence From Quantile Regressions With Michigan Municipalities and Counties

This study applies insights from open systems theory to explore how the perceptions of local officials can enhance our understanding of local government fiscal health—in particular, to understand differences between healthy and distressed jurisdictions. With a sample of local governments in Michigan from 2013 to 2019, we use quantile regression to investigate associations between subjective financial condition measures and objective indicators. The results show that these relationships are often more muted for lower-stress governments and more pronounced for higher-stress governments, a pattern that is not accounted for by traditional methods of measuring financial condition. The findings demonstrate the utility of open systems theory and quantile regression techniques to improve understanding of the financial condition and suggest that in order to avoid overlooking cases of fiscal distress, policymakers and analysts should incorporate these approaches into methods for diagnosing local fiscal health.

Towards a comprehensive assessment system of local government fiscal health

Understanding fiscal health, also commonly referred to as financial condition, is key to sound decision making and the proper functioning of local government. Nonetheless there is no agreed upon way to measure fiscal health. We argue that the use of a conceptual framework is essential in furthering our understanding of measuring and assessing local government fiscal health. In this study we offer a framework and a set of financial accounting indicators visualizing fiscal health on the short and long term, taking into account the existing liabilities and local government obligations towards its constituents. The study draws on the theoretical and empirical analysis of corporate bankruptcy prediction models and local government fiscal distress models. We develop a possible comprehensive set of fiscal health indicators and compare it with existing empirical studies of local government fiscal health. The model captures current performance in four solvency dimensions (cash, budget, service-level and long term) and allows for predictions of future performance, taking into account risks (predictors of possible future financial stress) and capabilities (opportunities to strengthen future financial health). We tested our model by reviewing 33 empirical studies and found that we could allocate all indicators used to the dimensions of our framework. No empirical study appears to address all dimensions. The selection of performance dimensions is partly driven by the studies’ research objectives.

Police and Fire Pensions in Florida: A Comparison of Conditions After 10 Years

This article is an analysis of 31 defined benefit police and fire pension plans of 20 municipalities in Florida. The authors conducted a similar assessment of these same plans ten years earlier to determine the fiscal impact of these plans due to state mandates that accompany state funding for each of these plans. The current study analyzes key measures of fiscal health over the last ten years for these same plans to ascertain whether the fiscal condition of these plans remained constant, that is, whether underfunded plans continued to be questionably managed and whether well-funded plans continued to be fiscally stable considering economic trends and the lessening of state mandates on the use of state funding for these plans. The findings show that the overwhelming majority of the plans neither significantly changed their financial condition nor their general ranking among the plans evaluated.

Factors influencing tweet purposes and citizen engagement with municipal Twitter accounts

PurposeThe purpose of this paper is to determine the demographic, resource and internal competition factors that influence both the level of citizen engagement provided by municipal Twitter accounts as well as the primary purposes for which those accounts are used.Design/methodology/approachThis research uses a mixed-methods approach. Twitter data were content analyzed and categorized according to their specific purposes (information dissemination, community building or calls to action). Twitter engagement was measured as an index variable constructed from prior research, and multiple regression was used to determine the factors which best predict both account engagement and tweet purposes.FindingsThe results show that two factors (a multiplatform approach and fiscal health) along with the interaction of those factors predict the level of Twitter-based citizen engagement. Median citizen age was found to significantly predict the percentage of municipal tweets with purposes of information dissemination and community building.Originality/valueThis study adds to the literature on public sector social media use by examining the purposes and practices of local government Twitter use, providing a context for examining how Twitter is employed by local governments for citizen engagement.

Owners’ Perceptions of Pet influence: Relation to Health Outcomes & Pet Attachment in Community-Living Older Adults

Pet ownership (PO) has been linked to better health outcomes in older adults, particularly those with chronic health conditions. It is suggested that pets influence their owners lives both by encouraging social interaction and by interfering with owners’ willingness or ability to seek care for themselves. We use data from 6 questions about the positive and negative influence of pets on community dwelling older adults’ administered to pet owners (N=223, age >=50 years) in the Baltimore Longitudinal Study of Aging. We use principal components analysis (oblique rotation) to extract dimensions of owner’s perceptions of pet influences (PPI) and examine the relationship of these dimensions to owners’ cognitive, physical functional, and psychological status. Three dimensions of PPI include: fiscal/health challenges (F1: 3 items, alpha=0.70), wellness promotion (F2: 2 items, alpha=0.80); and reason for social/travel constraints (F3: 1 item). In regression analysis with all factors entered simultaneously, after controlling for age, higher magnitude of F1 significantly independently predicted poor physical quality of life (p=.0007), greater perceived stress (p=0.041), and lower happiness (p=0.014); F2 did not independently predict any health outcome; higher F3 significantly independently predicted lower emotional vitality (p=0.048). Controlling for age, all three factors were independent predictors of pet attachment (p’s=0.001, 0.010, 0.047, respectively). F1 and F3 were positively and F2 was negatively correlated with attachment. PPI was associated with owners’ physical and mental health. Perhaps older adults with higher attachment to pets are more likely to keep them despite higher challenges.