Behavior change techniques to increase physical activity among older adults living in long-term care facilities: A systematic review.

Despite the health benefits of physical activity, many older adults living in long-term care facilities lead sedentary lifestyles and do not meet minimum physical activity recommendations. Determining the behavior change techniques (BCTs) used in physical activity interventions can help us understand the underlying mechanisms by which behavioral change is achieved. The purpose of this systematic review was to identify and evaluate BCTs in physical activity interventions for the elderly residents. Six electronic databases were searched and 15 eligible studies were retained. Nine promising BCTs associated with physical activity promotion among elderly residents were identified: credible source, social support (unspecified), goal setting (outcome), goal setting (behavior), demonstration of the behavior, instruction on how to perform a behavior, self-monitoring of behavior, self-monitoring of outcome(s) of behavior, and adding objects to the environment. Future research is encouraged to select and tailor these BCTs to the specific needs and preferences of the target population.

Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study.

OBJECTIVES: To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification task, aiming to provide staff with an effective and user-friendly fall-risk assessment tool. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: A total of 864 older residents living in 4 nursing homes between May 2022 and March 2023 in China. METHODS: Potential fall-risk predictors were collected through in-person interviews and assessments of anthropometric and physical function. Participants were followed for 6 months, with falls recorded by trained nurses. Seven machine learning algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN), and Decision Tree (DT), were used to develop prediction models. Performance was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) and Precision-Recall curve (PR-AUC), with calibration assessed via a calibration curve. Feature importance was visualized using SHapley Additive exPlanations (SHAP). RESULTS: The 6 selected predictors were balance, grip strength, fatigue, fall history, age, and comorbidity. The ROC-AUC for the models ranged from 0.710 to 0.750, PR-AUC from 0.415 to 0.473, sensitivity from 0.704 to 0.914, and specificity from 0.511 to 0.687 in the validation cohort. The LR model was converted into a nomogram. CONCLUSIONS AND IMPLICATIONS: The machine learning-based fall-prediction models effectively identified nursing home residents at high risk of falls. The developed nomogram can be integrated into clinical practice to enhance fall risk assessment protocols, ultimately improving patient safety and care in nursing homes.

Simultaneous Manipulation of Membrane Enthalpy and Entropy Barriers towards Superior Ion Separations.

Sub-nanoporous membranes with ion selective transport functions are important for energy utilization, environmental remediation, and fundamental bioinspired engineering. Although mono/multivalent ions can be separated by monovalent ion selective membranes (MISMs), the current theory fails to inspire rapid advances in MISMs. Here, we apply transition state theory (TST) by regulating the enthalpy barrier (ΔH) and entropy barrier (ΔS) for designing next-generation monovalent cation exchange membranes (MCEMs) with great improvement in ion selective separation. Using a molecule-absorbed porous material as an interlayer to construct a denser selective layer can achieve a greater absolute value of ΔS for Li+ and Mg2+ transport, greater ΔH for Mg2+ transport and lower ΔH for Li+ transport. This recorded performance with a Li+/Mg2+ perm-selectivity of 25.50 and a Li+ flux of 1.86 mol ⋅ m-2 ⋅ h-1 surpasses the contemporary "upper bound" plot for Li+/Mg2+ separations. Most importantly, our synthesized MCEM also demonstrates excellent operational stability during the selective electrodialysis (S-ED) processes for realizing scalability in practical applications.

Prevalence of physical inactivity and its determinants among older adults living in nursing homes: A cross-sectional study based on COM-B model.

AIMS: To investigate the prevalence of physical inactivity in older adults living in nursing homes and explore the determinants of physical inactivity by using the Capability, Opportunity, Motivation-Behaviour model. DESIGN: A multisite, cross-sectional study was performed by convenience sampling and questionnaire survey. METHODS: A total of 390 nursing home residents were recruited from three nursing homes in Southern China from May 2022 to April 2023. The participants completed a self-designed general information questionnaire, Physical Activity Scale for the Elderly, Self-Efficacy for Exercise Scale, Exercise Benefits Scale, Patient Health Questionnaire-9 and the Short Physical Performance Battery test. Descriptive statistics, univariate analysis, Spearman correlation analysis, and ordinal logistic regression were applied for data analysis. RESULTS: The prevalence of physical inactivity among the nursing home residents reached 88.46%. Ordinal logistic regression results showed that exercise self-efficacy, perceived exercise benefits, physical function, availability of physical activity instruction, having depression, number of chronic diseases and living with spouse were the main influencing determinants of physical inactivity and explained 63.7% of the variance. CONCLUSIONS: Physical inactivity was considerable in nursing home residents in China and influenced by complex factors. Tailored measures should be designed and implemented based on these factors to enhance physical activity while considering the uniqueness of Chinese culture. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Healthcare professionals should enhance physical activity of residents by increasing benefits understanding, boosting self-efficacy, improving physical function, alleviating depression and integrating personalized physical activity guidance into routine care services. And more attention should be paid to the residents who had more chronic diseases or did not live with spouse. IMPACT: Physical inactivity is a significant problem in nursing home residents. Understanding physical inactivity and its determinants enables the development of tailored interventions to enhance their physical activity level. REPORTING METHOD: This study was reported conforming to the STROBE statement. PATIENTS OR PUBLIC CONTRIBUTION: Nursing home residents who met the inclusion criteria were recruited.

Adverse event reporting attitude and its individual and organizational predictors among nursing staff: A multisite study in Chinese nursing homes.

This study explored the status of adverse event reporting attitudes and its predictors among nursing staff in Chinese nursing homes. A cross-sectional study was conducted with 475 nursing staff, and they completed sociodemographic and facility-related questionnaire, Incident Reporting Attitude Scale, Adverse Event Reporting Awareness Scale, and Nursing Home Survey on Patient Safety Culture. Univariate analysis and multiple linear regression models were performed. The mean score for adverse event reporting attitude was 125.87 (SD=15.35). The predictors included individual variables, such as education level (ß=0.129, p = 0.001) and working years (ß=-0.102, p = 0.007), and organizational variables, such as patient safety culture (ß=0.503, p < 0.001) and adverse event reporting awareness (ß=0.261, p < 0.001). These factors explained 35.3 % of total variance. Managers in nursing homes should strengthen team-targeted education and training for nursing staff with longer working years and lower educational backgrounds. Meanwhile, a simplified and non-punitive reporting system should be established to create positive safety management climate.

Chelation-directed interface engineering of in-place self-cleaning membranes.

Water-energy sustainability will depend upon the rapid development of advanced pressure-driven separation membranes. Although energy-efficient, water-treatment membranes are constrained by ubiquitous fouling, which may be alleviated by engineering self-cleaning membrane interfaces. In this study, a metal-polyphenol network was designed to direct the armorization of catalytic nanofilms (ca. 18 nm) on inert polymeric membranes. The chelation-directed mineralized coating exhibits high polarity, superhydrophilicity, and ultralow adhesion to crude oil, enabling cyclable crude oil-in-water emulsion separation. The in-place flux recovery rate exceeded 99.9%, alleviating the need for traditional ex situ cleaning. The chelation-directed nanoarmored membrane exhibited 48-fold and 6.8-fold figures of merit for in-place self-cleaning regeneration compared to the control membrane and simple hydraulic cleaning, respectively. Precursor interaction mechanisms were identified by density functional theory calculations. Chelation-directed armorization offers promise for sustainable applications in catalysis, biomedicine, environmental remediation, and beyond.

Comparison of Postoperative Outcomes Between Near-Infrared Fluorescent Imaging-Guided Mediastinal Lymphadenectomy and Conventional Surgery for Esophageal Cancer.

BACKGROUND: The study aimed to evaluate the efficacy of using near-infrared fluorescent imaging (NIRF) imaging with indocyanine green as an intraoperative tool for achieving complete mediastinal lymph node (LN) resection. PATIENTS AND METHODS: Between September 2019 and July 2021, patients with potential for esophagectomy due to middle and lower thoracic esophageal cancer were enrolled in this study. All patients were scheduled for NIRF-guided mediastinal lymphadenectomy during esophageal cancer surgery and were appropriately assigned to the NIRF group. Patients who underwent esophagectomy between September 2017 and September 2019 were assigned to the historical control group upon satisfying the inclusion/exclusion criteria. Surgical outcomes and the number of removed LNs were compared between the two groups using 1:1 propensity score matching. RESULTS: Of 67 eligible patients, 59 patients were included in the NIRF group after postsurgical exclusions. The operative time was significantly shorter in the NIRF group than in the historical control group [180 (140-420) min versus 202 (137-338) min; P < 0.001]. The incidence of postoperative chylothorax and hoarseness were significantly lower in the NIRF group than in the historical control group (0% versus 10.2 %; P = 0.036, 3.4% versus 13.6%; P = 0.047). The number of dissected total LNs, mediastinal LNs, and negative LNs was significantly larger in the NIRF group than in the historical control group. The number of overall metastatic LNs and abdominal LNs was comparable between the two groups. CONCLUSIONS: NIRF imaging can assist in the thorough and complete mediastinal LNs dissections without increasing complications in patients undergoing esophagectomy.

Ultrapermeable Gel Membranes Enabling Superior Carbon Capture.

Membrane technology is rapidly gaining broad attraction as a viable alternative for carbon capture to mitigate increasingly severe global warming. Emerging CO2 -philic membranes have become crucial players in efficiently separating CO2 from light gases, leveraging their exceptional solubility-selectivity characteristics. However, economic and widespread deployment is greatly dependent on the boosted performance of advanced membrane materials for carbon capture. Here, we design a unique gel membrane composed of CO2 -philic molecules for accelerating CO2 transportation over other gases for ultrapermeable carbon capture. The molecular design of such soft membranes amalgamates the advantageous traits of augmented permeation akin to liquid membranes and operational stability akin to solid membranes, effectively altering the membrane's free volume characteristics validated by both experiments and molecular dynamics simulation. Surprisingly, gas diffusion through the free-volume-tuned gel membrane undergoes a 9-fold improvement without compromising the separation factor for the superior solubility selectivity of CO2 -philic materials, and CO2 permeability achieves a groundbreaking record of 5608 Barrer surpassing the capabilities of nonfacilitated CO2 separation materials and exceeding the upper bound line established in 2019 even by leading-edge porous polymer materials. Our designed gel membrane can maintain exceptional separation performance during prolonged operation, enabling the unparalleled potential of solubility-selective next-generation materials towards sustainable carbon capture.

Protein-activated atomic layer deposition for robust crude-oil-repellent hierarchical nano-armored membranes.

Atomic layer deposition (ALD) offers unique capabilities to fabricate atomically engineered porous materials with precise pore tuning and multi-functionalization for diverse applications like advanced membrane separations towards sustainable energy-water systems. However, current ALD technique is inhibited on most non-polar polymeric membranes due to lack of accessible nucleation sites. Here, we report a facile method to efficiently promote ALD coating on hydrophobic surface of polymeric membranes via novel protein activation/sensitization. As a proof of concept, TiO2 ALD-coated membranes activated by bovine serum albumin exhibit remarkable superhydrophilicity, ultralow underwater crude oil adhesion, and robust tolerance to rigorous environments including acid, alkali, saline, and ethanol. Most importantly, excellent cyclable crude oil-in-water emulsion separation performance can be achieved. The mechanism for activation/sensitization is rooted in reactivity for a particular set of amino acids. Furthermore, the universality of protein-sensitized ALD is demonstrated using common egg white, promising numerous potential usages in biomedical engineering, environmental remediation, low-carbon manufacturing, catalysis, and beyond.