IM for hospital-to-home health transitions is complex, yet key for patient safety. Organisational infrastructure is needed to support IM. Future clinical workflows and health information technology should be designed to mitigate IM-related process failures to facilitate safer hospital-to-home health transitions.

Aims: To assess the clinical effectiveness of a paediatric hospital at home service compared to conventional hospital care. Methods: A total of 399 children suffering from breathing difficulty (n = 202), diarrhoea and vomiting (n = 125), or fever (n = 72) were randomised to Hospital at Home or in-patient paediatric care. Main outcome measures were: comparative clinical effectiveness as measured by readmission rate within three months (used as a proxy for parental coping with illness); and length of stay/care and comparative satisfaction of both patients and carers. Results: Clinical effectiveness of both services was not significantly different. Length of care was one day longer in the Hospital at Home group; however, most parents and children preferred home care. Conclusions: Hospital at Home is a clinically acceptable form of care for these groups of acute paediatric illness. Readmission rates within three months failed to show any advantage in terms of parental coping. Parents and patients expressed a strong preference for hospital at home.

Human biomonitoring (HBM) as a tool for occupational exposure assessment has been reviewed, with a specific focus on pesticides. A systematic literature review (SLR) of available information on HBM of pesticides (or their metabolites) in occupational settings and from HBM studies/surveillance programmes has been carried out and the studies identified assessed for relevance and quality. HBM essentially involves the quantification of either a substance, one of its metabolites, or a surrogate marker of its effects in a biological sample obtained from a person who may have undergone an exposure. Thus, HBM is generally considered to be an estimate of exposure, rather than a measure of health. Over the past 10 to 20 years there has been an expansion in the use of HBM, especially into the field of environmental and consumer exposure analysis, and it is currently well-developed and widely used in both the occupational and environmental settings worldwide. As with any tool, HBM has its strengths and weaknesses and appreciation of these promotes the development of approaches to minimise their effects. Although HBM has been extensively used for monitoring worker exposure to a variety of pesticides, epidemiological studies of occupational pesticide use were seen to be limited by inadequate or retrospective exposure information. Very limited data was identified examining seasonal exposures and the impact of PPE, and many of the studies used HBM to assess only one or two specific compounds. A wide variety of exposure models are currently employed for health risk assessments and biomarkers are often used to evaluate exposure estimates predicted by a model. From the 178 publications identified to be of relevance, 41 individual studies included herbicides, 79 individual studies included insecticides, and 20 individual studies included fungicides. Remaining studies related to mixtures or non-specific biomarkers for groups of pesticides. Although a number of current limitations were identified, there is evidence within the literature for a potential role of HBM in occupational health and safety strategies, as both a tool for refined exposure assessment in epidemiology studies and to contribute to the evaluation of potential health risks from occupational exposure to pesticides. Some key issues were considered that would need to be overcome to enable implementation of HBM as part of the occupational health surveillance for pesticides in Europe. These included issues around priorities for the development of new specific and sensitive biomarkers, the derivation and adoption of health-based guidance values, development of QA schemes to validate inter-laboratory measurements, good practice in field work and questionnaire design, consideration of the extended use of biobanking and the use of HBM for post-approval monitoring of pesticide safety.

A lack of social connectedness is common among older adults due to living alone, loss of loved ones, reduced mobility, and, more recently, social distancing created by the global Covid-19 pandemic. Older adults are vulnerable to social isolation and loneliness, which pose significant health risks comparable to those of smoking, obesity, physical inactivity, and high blood pressure. A lack of social connectedness is also correlated with higher mortality rates even when controlling for other factors such as age and comorbid conditions. The purpose of this mini review was to explore the emerging concepts of older adults' use of commercially available artificial intelligent virtual home assistants (VHAs; e.g., Amazon Echo, Google Nest), and its relationship to social isolation and loneliness. A secondary purpose was to identify potential areas for further research. Results suggest that VHAs are perceived by many older adult users as “companions” and improve social connectedness and reduce loneliness. Available studies are exploratory and descriptive and have limited generalizability due to small sample sizes, however, similar results were reported across several studies conducted in differing countries. Privacy concerns and other ethical issues and costs associated with VHA use were identified as potential risks to older adults' VHA adoption and use. Older adults who were using VHAs expressed the need and desire for more structured training on device use. Future research with stronger methods, including prospective, longitudinal, and randomized study designs are needed. Public education, industry standards, and regulatory oversight is required to mitigate potential risks associated with VHA use.

The effect of alcohol hangover on cognitive processing has received little attention.We explored the effect of alcohol hangover on choice response time (RT), a dominant dependent variable in cognitive research. Prior research of the effect of hangover on RT has produced mixed findings; all studies reviewed relied exclusively on estimates of central tendency (e.g., mean RT), which has limited information value. Here we present novel analytical methods by going beyond mean RT analysis. Specifically, we examined performance in hangover conditions (N = 31) across the whole RT distribution by fitting exGaussian models to participant data, providing a formal description of the RT distribution.This analysis showed detriments to performance under hangover conditions at the slower end of the RT distribution and increased RT variance under hangover conditions. We also fitted an explicit mathematical process model of choice RT-the diffusion model-which estimates parameters reflecting psychologically-meaningful processes underlying choice RT. This analysis showed that hangover reduced information processing efficiency during response selection, and increased response caution; changes in these parameters reflect hangover affecting core decisional-components of RT performance. The implications of the data as well as the methods used for hangover research are discussed. The Effect of Alcohol Hangover on Choice Response TimeAlcohol hangover refers to the set of adverse symptoms experienced following alcohol consumption once alcohol has been eliminated from the blood (Verster et al., 2010).A number of biological mechanisms underlying hangover have been put forward such as the metabolism of congeners (alcohols in drinks other than ethanol) such as methanol, imbalance in the immune system and reduced blood glucose concentration (Penning et al., 2010), as well as acetaldehyde level increase, dehydration, sleep deprivation and insufficient eating (Verster et al., 2003). Although researchers have some understanding of the physiological effects of hangover, much less is known about the cognitive effects of hangover (Prat, Adan, Pérez-Pàmies & Sànchez-Turet, 2008;Prat, Adan & Sánchez-Turet, 2009).Stephens, Grange, Jones, and Owen (2014) provided a review of studies which have investigated the effects of alcohol hangover on general cognition. They reviewed the growing evidence base that shows hangover negatively affects core cognitive functions such as divided attention (e.g., Roehrs et al., 1991), sustained attention (e.g., Anderson & Dawson, 1999;McKinney et al., 2012; Rohsenow et al., 2010), attentional selection (e.g., McKinney et al., 2012), and some executive functions (e.g., Streufert et al., 1995).The focus of the present study was on the effect of alcohol hangover on response time (RT). Simple RT requires no choice between response alternatives, and is merely a reaction to an external stimulus (e.g., "Press the space bar as soon as you see a flash on the screen").Choice RT, in contrast, requires participants to make a ...