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

Senior financial exploitation (FE) is prevalent and harmful. Its often insidious nature and co-occurrence with other forms of mistreatment make detection and substantiation challenging. A secondary data analysis of N = 8,800 Adult Protective Services substantiated senior mistreatment cases, using machine learning algorithms, was conducted to determine when pure FE versus hybrid FE was occurring. FE represented N = 2514 (29%) of the cases with 78% being pure FE. Victim suicidal ideation and threatening behaviors, injuries, drug paraphernalia, contentious relationships, caregiver stress, and burnout and victims needing assistance were most important for differentiating FE vs non-FE-related mistreatment. The inability to afford housing, medications, food, and medical care as well as victims suffering from intellectual disability disorder(s) predicted hybrid FE. This study distinguishes socioecological factors strongly associated with the presence of FE during protective service investigations. These findings support existing and new indicators of FE and could inform protective service investigation practices.