Fall Risk Level Research Articles

The use and usefulness of the Peninsula Health Falls Risk Assessment Tool (PHFRAT) process in residential aged care: a mixed methods study across 25 aged care facilities

BackgroundFalls remain a persistent problem in residential aged care (RAC) facilities. Fall screening and assessment tools such as the Peninsula Health Falls Risk Assessment Tool (PHFRAT) are widely used to inform falls risk and guide fall prevention interventions. However, it is unclear how it is used in practice and whether clinicians believe it supports resident care. This study aimed to measure the extent of use of PHFRAT to understand clinicians’ perceptions of its value and usefulness.MethodsThis mixed method study involved an analysis of PHFRAT assessment from 25 RAC facilities in New South Wales, Australia, and interviews with seven RAC staff about how PHFRAT information is used in practice. In the quantitative component, descriptive statistics were applied to PHFRAT data to summarise how RAC staff use the PHFRAT including the completeness and content of the three parts. In the qualitative component, thematic analysis techniques were applied to interview data.ResultsThe sample included 215 RAC residents with 703 PHFRATs, of which 617 documented fall prevention interventions. Among these 617 PHFRATs, 593 (96.1%) included strategies related to staff assistance and 283 (45.9%) recorded strategies related to device provision. While nearly all residents (96.74%) received at least one PHFRAT assessment over the study period, many PHFRAT assessments were incomplete (part 1: 11.5% of information missing; part 2: 10.8%; part 3: 17.1%). There were few variations in fall interventions prescribed to individual residents by their fall risk level. Interviews with RAC staff indicated that PHFRAT assessments are the responsibility of registered nurses with limited input from other staff or residents. While the structured process was viewed positively in guiding risk assessment and intervention assessment, a lack of input from others prevented strategies from being tailored to residents’ specific needs and preferences. A shortage of resources, lack of communication, and limited staff education were identified as the main barriers to PHFRAT guideline implementation.ConclusionThe PHFRAT provides a useful structure for clinicians to assess falls risk factors and plan falls prevention strategies. In the future, increased multidisciplinary input into fall prevention strategy development may improve the comprehensiveness of fall prevention plans.

Determining the Relationship Between Frailty and Fall Risk in Elderly People Living in Nursing Homes

Objective: The study aimed to determine the relationship between the level of frailty and the risk of falls in the elderly living in nursing homes and to draw attention to this issue. Method: The cross-sectional and descriptive study was conducted in two state-owned nursing homes in Adana between January 2, 2023, and January 15, 2023. The study was conducted by face-to-face interviews with a total of 220 elderly people who met the research criteria and agreed to participate in the study. Data were collected using the Personal Information Form, Itaki Fall Risk Index, and Edmonton Frailty Scale. Results: 63,6% of the participants were women, and the average age was 76±8 (min=60, max=98). Female gender (58,3%), normal BMI (54,9%), lack of regular exercise (85,4%), presence of chronic disease (55,6%), use of assistive devices (85,6%), history of falling A statistically significant relationship was found between (63,9%) and hospitalization history (61,1%) and fall risk level (p<0.05). Normal BMI (60%), lack of regular exercise (70%), presence of chronic disease (70%), number of medications used 1-3 (55%), use of assistive devices (97,5%), history of falling (100%), a statistically significant relationship was found between the history of hospitalization (72,5%) and the risk level of severe frailty (p<0,05). A statistically significant relationship was found between frailty level and fall risk (p = 0,00). Conclusion: Elderly people with moderate and severe frailty were found to be at high risk of falls.

Effects of Physical Therapy Integrated with Dance/Movement Therapy on Heart Rate Variability and Fall-Related Variables: A Preliminary Controlled Trial

AbstractFalls among older adults are influenced by both physical and psychological risk factors. This pilot study specifically examined the impact of integrating Dance/Movement Therapy (DMT) into a regimen of physical therapy exercises (PTE) for fall prevention. The primary objectives included examining the effect of post-PTE+DMT intervention on heart rate variability (HRV), a psychophysiological marker, and fall risk factors. Additionally, this study aimed to examine correlations between HRV and levels of fall risk. Eight community-dwelling older adults (median = 83 [interquartile ranges: 80.5–85.75]) from a day center for senior citizens were randomly assigned to either a PTE+DMT group or a PTE group. A post intervention battery of HRV, physical and psychological fall risk assessments, was conducted. The results of nonparametric analysis demonstrated the potential impact of the PTE+DMT intervention in improving balance and self-efficacy measures related to falls when compared to participation in PTE alone. No statistically significant differences were observed between the groups in term of HRV and other physical and psychological fall risk factors. The emerging trends in the associations between HRV, fall risk, and balance levels suggest the potential utility of HRV as an objective psychophysiological marker for assessing fall risk levels. Moreover, the results underscore the potential advantages of interventions that integrate both physical and psychological components to mitigate fall risk in older adults, emphasizing the intricate mind–body connection.The ClinicalTrials.gov ID: NCT05948735, July 7, 2023.

Feasibility of individualized home exercise programs for patients with head and neck cancer-study protocol and first results of a multicentre single-arm intervention trial (OSHO #94).

Patients with head and neck cancer (PwHNC) benefit from targeted exercise interventions: symptom relief, compensation for dysfunction, improvement in quality of life (QoL). Data on acceptance physical interventions in PwHNC are rare. The 'OSHO #94' trial investigates the short- and medium-term effects of individualized home exercise in PwHNC on QoL, physical activity and functionality. The study includes a feasibility phase (proof of concept) in order to evaluate the acceptance. Here we present the study protocol as well as the feasibility results. This prospective, multicentre, single-arm intervention study includes PwHNC ≥18 years of age in aftercare or palliative care with stable remission under immunotherapy. The study opened in January 01, 2021, with estimated completion by December 31, 2024. The PwHNC receive an individualized home exercise program consisting of mobilization, coordination, strengthening and stretching exercises. This should be carried out at least three times a week over 12 weeks for 15 to 30 minutes, supplemented by aerobic training two to three times a week for 30 minutes (intervention). Once weekly telephone calls with a physiotherapist are performed. Subsequently, there is a 12-week follow-up (FU) without exercise specifications/contact. Outcomes are measured before and after the intervention and following the FU. Primary outcome of the feasibility phase (n = 25) was the determination of the dropout rate during the intervention with a termination cut off if more than 30% PwHNC withdrew premature. The primary outcome of the OSHO #94' trial (N = 53) is the change in global QoL score from pre- to post-intervention (EORTC QLQ-C30). Secondary outcomes include clinical and patient-reported measures, training details as well as functional diagnostic data (e.g. level of physical activity, training frequency, flexibility, fall risk and aerobic performance). 25 PwHNC were enrolled onto the feasibility cohort. Only16% (4/25 patients) did not complete the study. Therefore, recruitment of PwHNC was continued. The dropout rate was adjusted from 30% (N = 60) to 20% (N = 53, calculated sample size n = 42 PwHNC and 20% (n = 11) to dropout). Individualized home exercise programs in PwHNC in aftercare seem feasible. Consequently, the aim is now to evaluate the short and medium-term effects of individualized home exercise.

Care Partners' Engagement in Preventing Falls for Community-Dwelling Older People With Dementia.

Little is known about how to prevent falls in community-dwelling older people with dementia. Although their care partners adopt various behaviors to prevent their falls, it is unclear if these behaviors reduce falls for those with different levels of fall risk. Linking the 2015 and 2016 National Health and Aging Trends Study and the 2015 National Study of Caregiving (NSOC), we identified 390 community-dwelling older people with dementia with 607 care partners. We selected 26 NSOC items representing fall risk management (FRM) behaviors. We examined the prevalence and dimensionality of these behaviors and investigated associations between care partners' behaviors in 2015 (T1) and older people's falls in 2016 (T2) stratified by their fall incidence at T1, adjusting for covariates. Five domains of FRM were identified: mobility and safety assistance, medical service coordination, health management, social service coordination, and accommodation. For those who did not fall at T1, mobility and safety assistance and social service coordination were each associated with an increased risk of falling at T2 (adjusted incidence rate ratio [aIRR] = 1.39, 95% confidence interval [CI] = 1.06-1.83, p = .019, aIRR = 1.25, 95% CI = 1.01-1.55, p = .043). For those who had fallen at T1, social service coordination was associated with a decreased risk of falling at T2 (aIRR = 0.83, 95% CI = 0.73-0.94, p = .004). The different impacts of dementia care partners' FRM behaviors emphasize the need to address specific behaviors when involving care partners in preventing falls for older people with dementia at varying levels of fall risk.

Real-time risk assessment of multi-parameter induced fall accidents at construction sites

In this research, a risk assessment model was developed that concurrently considers the location and physiological risk factors for fall accidents in workers at construction sites. In terms of location risk, data on 1683 occupational fall accidents involving 1718 worker casualties in the construction industry were collected for the period 1996–2016 from the Institute of Labor, Occupational Safety and Health (ILOSH), Taiwan. Next, the locations of these fall accidents were identified and defined as hazardous areas, with each area assigned a fall-risk level based on the average number of occupational accidents per year. In terms of physiological risk, the thermal hazard evaluation model, Recommended Alert Limits/Recommended Exposure Limits (RALs/RELs), developed by the National Institute for Occupational Safety and Health (NIOSH), USA was used in this study. This model uses metabolic heat and wet bulb globe temperature (WBGT) to recommend hourly rest/work times for workers. Using WBGT and one hour as the basic unit of time, varying degrees of metabolic heat, defined as metabolic heat loading severity (MHLS), were obtained. An optical heart rate (HR) sensor was applied in this study to measure HR, which was subsequently converted to a metabolic heat value using the Malchaire J metabolic heat evaluation model. Next, metabolic heat loading risk level was evaluated based on the MHLS. Finally, the location-based fall-risk level was multiplied by the MHLS, generating a risk evaluation model for fall accidents. The evaluation results identify the real-time fall-risk level of each worker and, if needed, suggest actions to be taken to mitigate the elevated risks of fall accidents identified by the model.

Timed Up and Go test score and factors associated with a moderate-to-high risk of future falls in patients scheduled for vascular surgeries-a cross-sectional study.

Peripheral artery and aorta diseases contribute to complex consequences in various areas, as well as increasing physical and mental discomfort resulting from the progressive limitation or loss of functional capacities, in particular in relation to walking, decreased endurance during physical exercise, a drop in effort tolerance, and pain suffered by patients. Limitations in functional capacities also increase the risk of falls. Most falls take place during the performance of simple activities. The aim of this study was to investigate factors associated with moderate-to-high risk of future falls in patients scheduled for vascular surgeries. This cross-sectional study included patients aged 33-87, scheduled for vascular surgeries. Based on the Timed Up and Go test, patients were categorized as having a moderate-to-high (≥ 10 s) or low risk of falls. Multiple logistic regression was carried out to assess the relationship between fall-risk levels and independent sociodemographic and clinical variables. Forty-eight percent of patients were categorized as having a moderate-to-high risk of future falls. Females (OR = 1.67; Cl95%: 1.07-2.60) and patients who suffered from hypertension (OR = 2.54; Cl95%: 1.19-5.40) were associated with a moderate-to-high risk of future falls. The Barthel Index correlated negatively (OR = 0.69; Cl95%: 0.59-0.80), while age correlated positively with fall-risk levels (OR = 1.07; Cl95%: 1.02-1.12). Factors that may be associated with a moderate-to-high risk of future falls in patients scheduled for vascular surgeries include age, female gender, hypertension, and the Barthel Index.

Machine Learning-Based Approach to Identifying Fall Risk in Seafarers Using Wearable Sensors

Falls on a ship cause severe injuries, and an accident falling off board, referred to as “man overboard” (MOB), can lead to death. Thus, it is crucial to accurately and timely detect the risk of falling. Wearable sensors, unlike camera and radar sensors, are affordable and easily accessible regardless of the weather conditions. This study aimed to identify the fall risk level (i.e., high and low risk) among individuals on board using wearable sensors. We collected walking data from accelerometers during the experiment by simulating the ship’s rolling motions using a computer-assisted rehabilitation environment (CAREN). With the best features selected by LASSO, eight machine learning (ML) models were implemented with a synthetic minority oversampling technique (SMOTE) and the best-tuned hyperparameters. In all ML models, the performance in classifying fall risk showed overall a good accuracy (0.7778 to 0.8519), sensitivity (0.7556 to 0.8667), specificity (0.7778 to 0.8889), and AUC (0.7673 to 0.9204). Logistic regression showed the best performance in terms of the AUC for both training (0.9483) and testing (0.9204). We anticipate that this study will effectively help identify the risk of falls on ships and aid in developing a monitoring system capable of averting falls and detecting MOB situations.

Fall risk and frailty level in older adults admitted to the emergency department with a complaint of falling

Introduction and aim. Falls are the second leading cause of unintentional death in the world. The study was conducted to examine the risk of falls and levels of frailty in older adult patients admitted to the emergency department due to fractures, as well as to identify the factors that influence fall risk and frailty levels. Material and methods. This cross-sectional and correlational study conducted with 155 older patients. Data collected by the patient information form, Itaki Fall Risk Scale and Edmonton Frail Scale. Results. Patients diagnosed with fracture in the emergency department had a high risk of falling with a mean score of 9.55±3.84.70.3% of the patients were frail. The one-third (30.3%) had severe frailty. There was a moderate positive correlation between the risk of falling and the mean frailty score of the older adult patients (p<0.001). Conclusion. The study showed that older adults admitted to the emergency department due to falls are at high risk of falling and the majority of them are frail. Early determination of fall risk and frailty levels in the older adults with a history of falling, prevention of falls and fractures due to falls will be beneficial in increasing the quality of life of the older adults.

CARE PARTNERS’ ENGAGEMENT IN PREVENTING FALLS FOR COMMUNITY-DWELLING OLDER PEOPLE WITH DEMENTIA

Abstract Care partners adopt various behaviors to manage fall risk for community-dwelling older people with dementia (cd-OPWD). It is unknown if these behaviors reduce falls for cd-OPWD at different levels of fall risk. We linked the data from the 2015 and 2016 National Health and Aging Trends Study (NHATS) and the 2015 National Study of Caregiving (NSOC) (cd-OPWD n=365, 89% aged 75+) to explore this question. The outcome was no fall, one fall, and multiple falls in 2016. We used the same variable in 2015 to indicate fall risk at baseline. We identified 28 items from NSOC to represent dementia care partners’ fall risk management (FRM) behaviors based on existing literature and expert review. Using exploratory factor analysis, we identified five categories of FRM behaviors: mobility and safety assistance, health management, accommodations, medical services coordination, and social services coordination. We performed multinomial logistic regression to investigate associations between care partners’ FRM behaviors in 2015 and cd-OPWD’ falls in 2016 stratified by cd-OPWD’s history of falls in 2015, adjusting for selected covariates. For cd-OPWD who had no fall in 2015, mobility and safety assistance was associated with a higher risk of having one fall in 2016; for those who had one fall in 2015, medical services coordination was associated with a lower risk of multiple falls; for those who had multiple falls in 2015, social services coordination was associated with a lower risk of multiple falls. Future research may target care partners’ different FRM behaviors based on cd-OPWD’s history of falls.

FALL RISK AND FEAR OF FALLING IN LOW-INCOME COMMUNITY-DWELLING OLDER ADULTS USING A SIMPLE CHECKLIST

Abstract Fall risk is common among older adults and can seriously threaten their well-being and increase fear of falling (FOF). FOF can affect the ability of older adults to maintain daily activities and may cause depression. Using a simple checklist to assess the levels of fall risk and FOF can help tailor interventions to prevent falls and promote physical activity. The purpose of the study was to assess fall risk and FOF using simple checklists and examine the association between fall risk and FOF in community-dwelling older adults in low-income settings. A descriptive cross-sectional design was used to assess 103 older adults (men=16, women=87, mean age=75.70, SD±7.19). We used the CDC’s Stay Independent checklist with twelve items to measure fall risk and the Short Fall Efficacy Scale International (Short FES-I) with seven items to assess FOF. Scores equal to or greater than four on the Stay Independent and greater than ten on the Short FES-I indicate high fall risk and high FOF, respectively. The data was analyzed using SPSS version 28. Spearman correlation tests showed that fall risk was positively correlated with FOF (r=.606, p<.001). Our finding suggests that using simple checklists to assess both fall risk and FOF may be helpful for older adults in understanding their risk of falls, thus attenuating their FOF. It may be useful to increase accessibility to these two checklists in efforts to prevent falls and FOF among community-dwelling older adults in low-income settings.

EXPLORATION OF FALL RISK OF PARTICIPANTS ACROSS EVIDENCE-BASED FALL PREVENTION PROGRAMS

Abstract The National Council on Aging houses the Administration for Community Living’s (ACL) national database on evidence-based, community-delivered fall prevention programs (EBFPP). Each year, cooperative agreement grants are awarded competitively to groups demonstrating readiness to deliver EBFPP in their communities. Participants in these programs completed a standardized pre-participation survey documenting demographic and self-reported fall risk factors that were entered into the national EBFPP database. Marymount University received permission to analyze the survey data entered into the ACL’s National Falls Prevention Database between July 2016 and June 2022. An exploratory analysis was conducted of 105,323 older adults who participated in one of eight ACL-approved EBFPP programs. EBFPPs vary in their targeted fall risk level, tailoring intervention components (health education, self-management training, physical exercise) and adjusting intensity and focus to match the risk level. It is unknown if people join the program that best fits their risk level. This study evaluates and compares participant demographic characteristics and fall risk across EBFPPs. We created an index to categorize risk levels, anchored in the CDC’s STEADI toolkit for fall risk, finding that 29% were high risk, 51% moderate risk, and 19% low risk. The factors used to establish risk level included 1) falling in the last 3 months, 2) referral from a healthcare professional, 3) fear of falling, 4) self-reported health (not excellent or very good), 5) depression, and 6) age 85 or older. Exploring participant characteristics by risk level and choice of EBFPP adds unique information to guide future EBFPP recruitment strategies.

An inpatient fall risk assessment tool: Application of machine learning models on intrinsic and extrinsic risk factors

BackgroundThis study aimed to identify the most impactful set of intrinsic and extrinsic fall risk factors and develop a data-driven inpatient fall risk assessment tool (FRAT). MethodsThe dataset used for the study comprised in-hospital fall records from 2012 to 2017. Four machine learning (ML) algorithms, Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting (Gboost), and Deep Neural Network (DNN) were utilized to predict the inpatient fall risk level. To enhance the performance of the prediction models, two approaches were implemented, including (1) feature selection to identify the optimal feature set and (2) the development of three distinct shift-wise models. Furthermore, the optimal feature sets in the shift-wise models were extracted. ResultsAccording to the results, DNN outperformed other methods by reaching an accuracy, sensitivity, specificity, and AUC of 0.71, 0.8, 0.6, and 0.7, respectively, considering the full set of features. The performance of the models was further improved (by 3-5 %) by conducting a feature selection process for all models. Specifically, the DNN model achieved an accuracy of 0.74 while considering the optimal set of predictors. Moreover, the shift-wise RF models demonstrated higher accuracies (by 4-10 %) compared to the same model using a full feature set. ConclusionsThis study's outcome confirms ML models' compelling capability in developing an inpatient FRAT while considering intrinsic and extrinsic factors. The insight from such models could form a foundation to (1) monitor the inpatients’ fall risk, (2) identify the major factors involved in inpatient falls, and (3) create subject-specific self-care plans.

Evaluation of a concise fall risk stratification among older adults with cataracts in day surgery settings: A historically controlled study.

This study aimed to evaluate the use of a concise fall risk stratification in assessing and predicting falls compared with the Morse Falls Scale among older adults with cataracts in day surgery settings. A historically controlled study conducted from July 2020 to June 2022 was used in a municipal ophthalmic hospital in China. The concise fall risk stratification which directly graded fall risk by multifactorial judgment was used during the intervention period, while the Morse Falls Scale which graded fall risk by scale scores was used during the control period. The fall risk levels, fall assessment time, fall rates, fall-related injuries, predictive validity, and patient satisfaction with day surgery care were extracted. Propensity score matching was performed to balance baselines. After matching, 4132 patients were included in the final analysis. Compared with the control group, the intervention group had significantly higher assessment results for fall risk level, a significantly shorter (by 48.15%) fall assessment time, and higher patient satisfaction. There were no differences in fall rates and fall-related injuries. Compared with the Morse Falls Scale, the concise fall risk stratification had higher sensitivity and negative predictive validity, and lower specificity and positive predictive validity, while the area under curve did not differ significantly. The use of the concise fall risk stratification reduced fall assessment time, improved patient satisfaction, and is unlikely to impact falls with an overall predictive performance comparable to that of the Morse Falls Scale for older cataract adults in day surgery settings.

Talking about falls: a qualitative exploration of spoken communication of patients’ fall risks in hospitals and implications for multifactorial approaches to fall prevention

BackgroundInpatient falls are the most common safety incident reported by hospitals worldwide. Traditionally, responses have been guided by categorising patients’ levels of fall risk, but multifactorial approaches are now recommended....

Investigation of Frailty, Dependence, Fall Risk Levels, and Influencing Factors in Elderly Individuals

The fragility, dependency and fall risk levels of the elderly are quite high. Physiological changes brought about by aging may cause recurrent falls in elderly individuals, and their quality of life may be negatively affected due to falls. This study was planned to examine fragility, dependence, fall risk, levels of protective behavior against falling, and the affecting factors in the elderly. The cross-sectional, descriptive, and correlational study was carried out with 200 elderly individuals who were admitted to the osteoporosis outpatient clinic of a university hospital. Data collection was done through Elderly Individual Information Form developed by the researchers, the Edmonton Frail Scale, the Barthel Index, the Itaki Fall Risk Scale, and the Fall Behavioral Scale for Older People. The mean age of the elderly who participated in the study was 72.07±6.76 years, 79.5% of the participants were female, 68% were primary school graduates, and 93.0% were retirement pensioners. The mean score of Edmonton Frail Scale was 6.06±2.92, Barthel Index was 94.85±12.57, Itaki Fall Risk Scale was 9.85±0.31, and Fall Behavioral Scale for Older People was 2.89±0.46. Many socio-demographic and fall-related risk factors specific to elderly individuals had an effect on the related scale scores (p < 0.05). The elderly individuals were moderately frail, slightly dependent on others in performing their life activities, had a high risk of fall, and had moderate protective behavior against falls.

Quality evaluation of the usefulness of an emergency department fall risk assessment tool

IntroductionFalls that occur within a hospital setting are difficult to predict, however, are preventable adverse events with the potential to negatively impact patient care. Falls have the potential to cause serious or fatal injuries and may increase patient morbidity. Many hospitals utilize fall “predictor tools” to categorize a patient's fall risk, however, these tools are primarily studied within in-patient units. The emergency department (ED) presents a unique environment with a distinct patient population and demographic. The Memorial Emergency Department Fall Risk Assessment Tool (MEDFRAT) has shown to be effective with predicting a patient's fall risk in the ED. This IRB-approved study aims to assess the predictive validity of the MEDFRAT by evaluating the sensitivity and specificity for predicting a patient's fall risk in an emergency department at a level 1 trauma center. MethodsA retrospective cohort analysis was conducted using an electronic medical record (EMR) for patients who met study inclusion criteria at a level 1 trauma center ED. Extracted data includes MEDFRAT components, demographic information, and data from the Moving Safely Risk Assessment (MSRA) Tool, our institution's current fall assessment tool. A receiver operating characteristic (ROC) curve was constructed to determine the best cutoff for identifying any fall risk. Sensitivity, specificity, accuracy, positive likelihood ratio (LR+) and negative LR (LR-), with 95% CIs were then calculated for the cutoff value determined from the ROC curve. To compare overall tool performance, the areas under the ROC curves (AUC) were determined and compared with a z-test. ResultsThe MEDFRAT had a significantly higher sensitivity compared to the MSRA (83.1% vs. 66.1%, p = 0.002), while the MSRA had a significantly higher specificity (84.5% vs. 69.0%, p = 0.012). For identifying any level of fall risk, ROC curve analysis showed that the cutoff providing the best trade-off between sensitivity and specificity for the MEDFRAT was a score of ≥1. Additionally, area under the curve was determined for the MEDFRAT and MSRA (0.817 vs. 0.737). ConclusionThis study confirms the validity of the MEDFRAT as an acceptable tool to predict in-hospital falls in a level 1 trauma center ED. Accurate identification of patients at a high risk of falling is critical for decreasing healthcare costs and improving health outcomes and patient safety.

Time-Varying Hazard of Patient Falls in Hospital: A Retrospective Case-Control Study.

This study aims to evaluate the association between patient falls and relevant factors and to quantify their effect on fall risk. This is a retrospective case-control study using the secondary data collected from a tertiary general hospital. Study subjects were 450 patients who were admitted to the hospital between January 2016 and December 2020. The prevalence of falls was associated with the fall risk level by the Morse Fall Scale (MFS) and individual status at admission including history of admission, dizziness, sleep disorder, bowel dysfunction, and urinary incontinence. The odds ratios of patient falls were higher in the low-risk group by the MFS score (odds ratio (OR) = 2.61, p < 0.001) and the high-risk group (OR = 5.51, p < 0.001) compared to the no-risk group. The hazard ratio of patient falls was higher in the high-risk group by the MFS score (hazard ratio (HR) = 3.85, p < 0.001). The MFS had a significant explanatory power to predict fall risk. Sleep disorder and urinary incontinence were the significant factors influencing patient falls.

Factors Affecting Delirium in ICU Patients.

This study examined delirium severity using a delirium screening tool and analyzed the predictors, including pain, acuity, level of consciousness, fall risk, and pain score, to increase understanding of delirium and present foundational data for developing nursing interventions for delirium prevention. This was a retrospective study of 165 patients admitted to three intensive care units (ICUs). the Nursing Delirium Screening Scale (Nu-DESC) was used as a research tool to screen for delirium and measure the degree of delirium. The incidence of delirium in patients was 53.3%, and the average delirium score in the delirium group was 2.40 ± 0.56. Nu-DESC scores were significantly correlated with ICU days, ventilator days, restraint applications, the number of catheters inserted, sedative medication use, the Simplified Acute Physiology Score (SAPS III), the Morse Fall Scale (MFS), the Glasgow Coma Scale (GCS) scores, pain scores, and blood urea nitrogen (BUN). Stepwise multiple linear regression showed that the number of restraint applications, GCS score, ICU days, and BUN levels were factors influencing delirium. Based on the findings, ICU nurses should use delirium screening tools to ensure accurate delirium screening and work to reduce the incidence and degree of delirium by observing factors affecting delirium in patients.

Evaluating the Effect of Activity and Environment on Fall Risk in a Paradigm-Depending Laboratory Setting: Protocol for an Experimental Pilot Study

Knowledge about the causal factors leading to falls is still limited, and fall prevention interventions urgently need to be more effective to limit the otherwise increasing burden caused by falls in older people. To identify individual fall risk, it is important to understand the complex interplay of fall-related factors. Although fall events are common, they are seldom observed, and fall reports are often biased. Due to the rapid development of wearable inertial sensors, an objective approach to capture fall events and the corresponding circumstances is provided. The aim of this work is to operationalize a prototypical dynamic fall risk model regarding 4 ecologically valid real-world scenarios (opening a door, slipping, tripping, and usage of public transportation). We hypothesize that individual fall risk is associated with an interplay of intrinsic risk factors, activity, and environmental factors that can be estimated by using data measured within a laboratory simulation setting. We will recruit 30 community-dwelling people aged 60 years or older. To identify several fall-related intrinsic fall risk factors, appropriate clinical assessments will be selected. The experimental setup is adaptable so that the level of fall risk for each activity and each environmental factor is adjustable. By different levels of difficulty, the effect on the risk of falling will be investigated. An 8-camera motion tracking system will be used to record absolute body motions and limits of stability. All laboratory experiments will also be recorded by inertial sensors (L5, dominant leg) and video camera. Logistic regression analyses will be used to model the association between risk factors and falls. Continuous fall risk will be modeled by generalized linear regression models using margin of stability as outcome parameter. The results of this project will prove the concept and establish methods to further use the dynamic fall risk model. Recruitment and measurement initially began in October 2020 but were halted because of the COVID-19 pandemic. Recruitment and measurements recommenced in October 2022, and by February 2023, a total of 25 of the planned 30 subjects have been measured. In the field of fall prevention, a more precise fall risk model will have a significant impact on research leading to more effective prevention approaches. Given the described burden related to falls and the high prevalence, considerable improvements in fall prevention will have a significant impact on individual quality of life and also on society in general by reducing institutionalization and health care costs. The setup will enable the analysis of fall events and their circumstances ecologically valid in a laboratory setting and thereby will provide important information to estimate the individual instantaneous fall risk. DERR1-10.2196/46930.