Predictive validity of the Stopping Elderly Accidents, Deaths & Injuries (STEADI) program fall risk screening algorithms among community-dwelling Thai elderly

Abstract

Background Fall risk screening using multiple methods was strongly advised as the initial step for preventing fall. Currently, there is only one such tool which was proposed by the U.S. Centers for Disease Control and Prevention (CDC) for use in its Stopping Elderly Accidents, Death & Injuries (STEADI) program. Its predictive validity outside the US context, however, has never been investigated. The purpose of this study was to determine the predictive validity (area under the receiver operating characteristic curve: AUC), sensitivity, and specificity of the two-step sequential fall-risk screening algorithm of the STEADI program for Thai elderly in the community. Methods A 1-year prospective cohort study was conducted during October 2018–December 2019. Study population consisted of 480 individuals aged 65 years or older living in Nakhon Ratchasima Province, Thailand. The fall risk screening algorithm composed of two serial steps. Step 1 is a screening by the clinician’s 3 key questions or the Thai Stay Independent brochure (Thai-SIB) 12 questions. Step 2 is a screening by 3 physical fitness testing tools including Time Up and Go test (TUG), 30-s Chair Stand, and 4-stage balance test. Participants were then followed for their fall incidents. Statistical analyses were conducted by using Cox proportional hazard model. The AUC, sensitivity, specificity, and other relevant predictive validity indices were then estimated. Results The average age of the participants was 73.3 ± 6.51 years (range 65–95 years), and 52.5% of them were female. The screening based on the clinician’s 3 key questions in Step 1 had a high AUC (0.845), with the sensitivity and specificity of 93.9% (95% CI 88.8, 92.7) and 75.0% (95% CI 70.0, 79.6), respectively. Appropriate risk categorization however differed slightly from the original STEADI program. Conclusions With some modification, the fall risk screening algorithm based on the STEADI program was applicable in Thai context.

Value of the Short Physical Performance Battery (SPPB) in predicting fall and fall-induced injury among old Chinese adults

“…Quantitative evidence supports the above inference. Consistent with two prior studies [13,14], goodnessof-t of the predictive models in our research did not reach the common criteria for predictive models [30]. The low goodness-of-t of predictive models may be due to several possible reasons.…”

Feasibility of Implementing Patient-Reported and Physical Performance Measures to Identify and Manage Fall Risk in Older Adults Within a Secondary Fracture Clinic

“…The multiple electronic layers required to complete the study consent form, and to access, and complete the patient-reported measures may have been barriers in this study. As the STEADI Falls Risk Screening Tool has shown no difference in falls risk screening compared to asking patients falls history, multiple falls, and fear of falling (Helsel et al, 2021;Loonlawong et al, 2022;Nithman & Vincenzo, 2019), these results suggest that quick in-clinic screening tools may better meet the patients' needs in this population. However, future studies need to investigate other electronic methods to reach this population, including direct text messaging, in comparison to in-clinic only methods.…”

The Effect of the Stopping Elderly Accidents, Deaths, and Injuries Program on Falls Prevention in Neurosurgical Patients

“…Although the MFS may be simpler to implement and more widely used in general settings, the STEADI program's ability to customize interventions based on individual risk factors enhances its clinical applicability. 16 The findings emphasize the importance of considering specific patient populations and their distinct fall risk factors when selecting appropriate fall prevention tools and interventions.…”

“…Patients who take 12 seconds or more to complete the TUG test are considered at risk of falling. 16 The 30-Second Chair Stand test evaluates lower extremity strength and endurance using a chair ST stopping E elderly A accidents D deaths I injuries with a straight back and a 17-in seat height. Patients, with their arms crossed over their chest, perform repeated cycles of standing up and sitting down within a 30-second timeframe.…”