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Aim The objective of the present study was to determine the most effective method for providing oral nutrition support to hospitalised older adult patients with malnutrition using clinical and patient‐centred measures. Methods The present study involved consecutive assignment of 98 inpatients assessed as malnourished (Subjective Global Assessment B or C) to conventional commercial supplements (traditional, n = 33), MedPass (n = 32, 2 cal/mL supplement delivered 60 mL four times a day at medication rounds) or mid‐meal trolley (n = 33, selective snack trolley offered between meals) for two weeks. Weight change, supplement compliance, energy and protein intake (3‐day food records), quality of life (EQ‐5D), patient satisfaction and cost were evaluated. Results Weight change was similar across the three interventions (mean ± SD): 0.4 ± 3.8% traditional; 1.5 ± 5.8% MedPass; 1.0 ± 3.1% mid‐meal (P = 0.53). Energy and protein intakes (% of requirements) were more often achieved with traditional (107 ± 26, 128 ± 35%) and MedPass (110 ± 28, 126 ± 38%) compared with mid‐meal (85 ± 25, 88 ± 25%) interventions (P = < 0.01). Overall quality‐of‐life ratings (scale 0–100) improved significantly with MedPass (mean change, 12.4 ± 20.9) and mid‐meal (21.1 ± 19.7) interventions, however, did not change with traditional intervention (1.5 ± 18.1) (P = 0.05). Patient satisfaction including sensory qualities (taste, look, temperature, size) and perceived benefit (improved health and recovery) was rated highest for mid‐meal trolley (all P < 0.05). Conclusions Patients achieved recommended intake with supplements (MedPass or traditional), and despite lower cost, higher satisfaction and quality of life with selective mid‐meal trolley did not achieve recommended energy and protein intake. Future research is warranted for implementing a combination of strategies in providing oral nutrition support.

Psychiatry has been limited by historically rooted practices centered primarily on subjective observation. Fields such as oncology have progressed toward data-driven clinical decision-making that combines subjective clinical assessment of symptoms and preferences with biological measures such as genetics, biomarkers, imaging, and integrative physiology to derive quantitative risk scores and decision support. In contrast, psychiatry has just begun to scratch the surface of measurement-based care with validated clinical questionnaires. An opportunity exists to improve modern psychiatric care with novel data streams from digital sensors combined with clinical observation and subjective self-report. The prospect of integrating this complex information with modern computational and analytical methods could advance the field, both in research and clinical practice. Here we discuss this possibility and propose some key priorities to enable these innovations toward improving clinical outcomes in the future.

A policy for the introduction of low-low beds did not appear to reduce falls or falls with injury, although larger studies would be required to determine their effect on fall-related fractures.

Gait speed was faster among each higher K-level classification. However, gait speeds observed across all K-levels were slower than healthy populations, consistent with values indicating high risk of morbidity and mortality. Clinical relevance Factors associated with faster gait speed are useful for clinical teams considering walking potential of people with lower limb prostheses and those seeking to refine prosthetic rehabilitation programmes.

Background: Incident reporting is the prevailing approach to gathering data on accidental falls in hospitals for both research and quality assurance purposes, though is of questionable quality as staff time pressures, perception of blame and other factors are thought to contribute to underreporting.

As society has moved past the initial phase of the COVID-19 crisis that relied on broad-spectrum shutdowns as a stopgap method, industries and institutions have faced the daunting question of how to return to a stabilized state of activities and more fully reopen the economy. A core problem is how to return people to their workplaces and educational institutions in a manner that is safe, ethical, grounded in science, and takes into account the unique factors and needs of each organization and community. In this paper, we introduce an epidemiological model (the “Community-Workplace” model) that accounts for SARS-CoV-2 transmission within the workplace, within the surrounding community, and between them. We use this multi-group deterministic compartmental model to consider various testing strategies that, together with symptom screening, exposure tracking, and nonpharmaceutical interventions (NPI) such as mask wearing and physical distancing, aim to reduce disease spread in the workplace. Our framework is designed to be adaptable to a variety of specific workplace environments to support planning efforts as reopenings continue. Using this model, we consider a number of case studies, including an office workplace, a factory floor, and a university campus. Analysis of these cases illustrates that continuous testing can help a workplace avoid an outbreak by reducing undetected infectiousness even in high-contact environments. We find that a university setting, where individuals spend more time on campus and have a higher contact load, requires more testing to remain safe, compared to a factory or office setting. Under the modeling assumptions, we find that maintaining a prevalence below 3% can be achieved in an office setting by testing its workforce every two weeks, whereas achieving this same goal for a university could require as much as fourfold more testing (i.e., testing the entire campus population twice a week). Our model also simulates the dynamics of reduced spread that result from the introduction of mitigation measures when test results reveal the early stages of a workplace outbreak. We use this to show that a vigilant university that has the ability to quickly react to outbreaks can be justified in implementing testing at the same rate as a lower-risk office workplace. Finally, we quantify the devastating impact that an outbreak in a small-town college could have on the surrounding community, which supports the notion that communities can be better protected by supporting their local places of business in preventing onsite spread of disease.

The Rowland Universal Dementia Assessment Scale (RUDAS) is a six-domain screening tool for dementia. We measured the practicality and reliability of administering the RUDAS in a telemedicine setting. Inpatients were recruited from a Geriatric and Rehabilitation Unit. Each patient was administered the RUDAS both face-to-face (FTF) and via videoconferencing (VC). The assessment format (FTF or VC) and the allocation of doctor (Doctor 1 or Doctor 2) to format were randomized. Scores from each assessment format were compared. The outcome of no difference was decided based on a difference in mean of no more than ± one point. Percentage agreement (agreement being ±2 points) was calculated on individual test scores. Forty-two patients (average age 75 years) completed the two assessments. Their mean Mini-Mental State Examination (MMSE) score was 24.7 (range 10–30). The mean RUDAS score for both FTF and VC assessment was 24.9 (difference between the means 0.04), i.e. there was no significant difference. The results suggest that the RUDAS can be reliably administered via VC in post acute patients as an alternative to FTF administration.