Socioecological indicators of senior financial exploitation: an application of data science to 8,800 substantiated mistreatment cases

The application of artificial intelligence in health financing: a scoping review

INTRODUCTION

Artificial Intelligence (AI) represents a significant advancement in technology, and it is crucial for policymakers to incorporate AI thinking into policies and to fully explore, analyze and utilize massive data and conduct AI-related policies. AI has the potential to optimize healthcare financing systems. This study provides an overview of the AI application domains in healthcare financing.

METHOD

We conducted a scoping review in six steps: formulating research questions, identifying relevant studies by conducting a comprehensive literature search using appropriate keywords, screening titles and abstracts for relevance, reviewing full texts of relevant articles, charting extracted data, and compiling and summarizing findings. Specifically, the research question sought to identify the applications of artificial intelligence in health financing supported by the published literature and explore potential future applications. PubMed, Scopus, and Web of Science databases were searched between 2000 and 2023.

RESULTS

We discovered that AI has a significant impact on various aspects of health financing, such as governance, revenue raising, pooling, and strategic purchasing. We provide evidence-based recommendations for establishing and improving the health financing system based on AI.

CONCLUSIONS

To ensure that vulnerable groups face minimum challenges and benefit from improved health financing, we urge national and international institutions worldwide to use and adopt AI tools and applications.

An Examination of Conditions Exposing Older Adults to Economic Abuse: Logistic Regression Analysis

The aim of this study was to determine factors affecting the economic abuse status of older adults. The study was conducted with 385 individuals aged 65 years and above, living in the Bahçelievler district of Istanbul. Data were collected using a Sociodemographic Form, and a Determination of Economic Abuse of Older Adults Form. Logistic regression analysis was applied to determine the factors affecting the economic abuse status of the older adults. The study participants comprised 51.4% males and 48.6% females with a mean age of 70.44 ± 6.73 years. It was determined that 9.4% of the older adults were exposed to economic abuse. As a result of the logistic regression analysis, the factors found to affect the situations of exposure to economic abuse of the older adults were age, income status, number of children, exposure to emotional abuse, and exposure to physical abuse.

Financial Stressors and Resources Associated With Financial Exploitation

Background and Objectives

The prevalence of older adult financial exploitation (FE) is increasing. Population-based survey estimates of FE in the older adult population range from 5% to 11%. Given the growing prevalence of FE victimization in older adult populations, understanding the population's vulnerability to FE has increased in importance. This study investigates a conceptual framework in an attempt to understand how financial stressors and resources are associated with substantiated FE in a sample consisting largely of Black older adults.

Research Design and Methods

The study uses a cross-sectional design to investigate group differences among a total sample of 142 community-dwelling older adult participants, 62 of whom sought services to address FE and 80 with no history of FE.

Results

The group of older adults who sought services to address FE was more likely to be unmarried and had fewer years of education. Measures of financial literacy and perceived financial vulnerability had protective and risk effects, respectively.

Discussion and Implications

The present study found that sociodemographic and financial stress and resource measures have significant relationships with FE. These findings support the conceptual framework describing their relationship. This new conceptual framework provides a guiding factor in better understanding vulnerability to FE in older adults. The study also adds to the paucity of research completed on FE with Black older adults.

Using administrative data from adult protective services: opportunities and considerations

As federal agencies support the development of data systems for adult protective services (APS), researchers and practitioners are increasingly using administrative data to study types of adult maltreatment, including self-neglect, and the systems that respond to them. To date, however, APS has worked with little guidance about how best to use these data. This situation has contributed to inconsistent findings and uneven quality of research. Based on the authors' experience in multiple states and using examples from research and practice, this paper reviews practical considerations related to organizing and analyzing APS administrative data. We address concerns related to time-limited, erroneous, and missing data, as well as defining metrics and accounting for the multilevel structure of data with repeated observations. Reviewing these methodological details can help APS practitioners strengthen quality assurance processes and improve research in this important area.

Elder Abuse Vulnerability and Risk Factors: Is Financial Abuse Different From Other Subtypes?

Elder abuse (EA) affects one in six older adults, and financial EA, a common subtype, severely impacts victims and society. Understanding victim vulnerability and perpetrator risk factors is essential to EA prevention and management. The limited existing evidence about these factors in relation to EA types suggests that financial EA is different. In a cross-sectional quantitative analysis of secondary data (N = 1,238), we investigated EA vulnerability and risk factors, and victim-perpetrator family relationship, with respect to different EA types (financial only, financial co-occurring with other types, and nonfinancial abuse). Financial abuse-only cases had the lowest prevalence of vulnerability and risk factors. Most of these factors, and a familial relationship, were significantly more common in cases involving other EA types. Findings indicate that financial abuse, occurring in isolation, is distinct from other EA types. Risk assessment and future research should consider financial abuse separately to other EA forms.

The Greater Houston Area Bipolar Registry-Clinical and Neurobiological Trajectories of Children and Adolescents With Bipolar Disorders and High-Risk Unaffected Offspring

The aims of this article are to discuss the rationale, design, and procedures of the Greater Houston Area Bipolar Registry (HBR), which aims at contributing to the effort involved in the investigation of neurobiological mechanisms underlying bipolar disorder (BD) as well as to identify clinical and neurobiological markers able to predict BD clinical course. The article will also briefly discuss examples of other initiatives that have made fundamental contributions to the field. This will be a longitudinal study with participants aged 6-17 at the time of enrollment. Participants will be required to meet diagnostic criteria for BD, or to be offspring of a parent with BD. We will also enroll healthy controls. Besides clinical information, which includes neurocognitive performance, participants will be asked to provide blood and saliva samples as well as to perform neuroimaging exams at baseline and follow-ups. Several studies point to the existence of genetic, inflammatory, and brain imaging alterations between individuals at higher genetic risk for BD compared with healthy controls. Longitudinal designs have shown high conversion rates to BD among high-risk offspring, with attempts to identify clinical predictors of disease onset, as well as clarifying the burden associated with environmental stressors. The HBR will help in the worldwide effort investigating the clinical course and neurobiological mechanisms of affected and high-risk children and adolescents with BD.