Validation of the detection of elder abuse through emergency care technicians (DETECT) screening tool: a study protocol

Abstract

Introduction: Elder mistreatment (EM) is a high prevalence threat to the health and well-being of older adults in the USA. Medics are well-positioned to help with identification of older adults at risk for EM, however, field robust screening tools appropriate for efficient, observation-based screening are lacking. Prior work by this team focused on the development and initial pilot testing of an observation-based EM screening tool named detection of elder abuse through emergency care technicians (DETECT), designed to be implemented by medics during the course of an emergency response (911) call. The objective of the present work is to validate and further refine this tool in preparation for clinical dissemination.

Methods and analysis: Approximately 59 400 community-dwelling older adults who place 911 calls during the 36-month study observation period will be screened by medics responding to the call using the DETECT tool. Next, a random subsample of 2520 of the 59 400 older adults screened will be selected to participate in a follow-up interview approximately 2 weeks following the completion of the screening. Follow-up interviews will consist of a medic-led semistructured interview designed to assess the older adult's likelihood of abuse exposure, physical/mental health status, cognitive functioning, and to systematically evaluate the quality and condition of their physical and social living environment. The data from 25% (n=648) of these follow-up interviews will be presented to a longitudinal, experts and all data panel for a final determination of EM exposure status, representing the closest proxy to a 'gold standard' measure available.

Ethics and dissemination: This study has been reviewed and approved by the Committee for the Protection of Human Subjects at the University of Texas School of Public Health. The results will be disseminated through formal presentations at local, national and international conferences and through publication in peer-reviewed scientific journals.

Keywords: accident & emergency medicine; geriatric medicine; public health.

Figure 1

Data collection activities and timeline. DETECT, detection of elder abuse through emergency care technicians; LEAD, longitudinal, experts and all data.

Figure 2

Marginal error around estimates of sensitivity at varying levels of sensitivity and baseline EM prevalence. EM, elder mistreatment.