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Background: Physical activity (PA) promotion in healthcare systems is one of the priority areas highlighted by the World Health Organization, which recognizes that progress has been slow largely due to a lack of awareness and investment while requiring a system-based approach. Community pharmacies are one of the health structures that are more easily accessible to populations, thus constituting an ideal venue for developing health promotion activities. This research aimed to describe PA-enabling interventions developed in community pharmacies by pharmacists. Methods: An electronic search was performed in PubMed, Scopus, Web of Science, Cochrane and reference lists of the different papers until June 2023. Studies were eligible if performed in community pharmacies by pharmacists, focused on interventions aimed at increasing PA levels and if at least one PA-specific outcome was measured at two different time points. Results: We identified 7076 publications in the initial search, plus 31 records identified through backward citation tracking from relevant studies. After an initial screening, 236 were selected for full-text analysis. Of the 29 selected papers, 10 presented a low risk of bias for the measurement of PA levels. PA outcomes were generally self-reported outcomes where the change in terms of the percentage of individuals considered active or who increased PA because of the intervention. Conclusion: Several interventions to improve PA through community pharmacies were found although with a high level of heterogeneity and with only few with a low risk of bias. More targeted research that aims to capture PA levels and support the training of healthcare professionals is needed. [ABSTRACT FROM AUTHOR]

Background Following years of sustained pressure on the UK health service, there is recognition amongst health professionals and stakeholders that current models of healthcare are likely to be inadequate going forward. Therefore, a fundamental review of existing social models of healthcare is needed to ascertain current thinking in this area, and whether there is a need to change perspective on current thinking. Method Through a systematic research review, this paper seeks to address how previous literature has conceptualized a social model of healthcare and, how implementation of the models has been evaluated. Analysis and data were extracted from 222 publications and explored the country of origin, methodological approach, and the health and social care contexts which they were set. Results The publications predominantly drawn from the USA, UK, Australia, Canada and Europe identified five themes namely: the lack of a clear and unified definition of a social model of health and wellbeing; the need to understand context; the need for cultural change; improved integration and collaboration towards a holistic and person-centred approach; measuring and evaluating the performance of a social model of health. Conclusion The review identified a need for a clear definition of a social model of health and wellbeing. Furthermore, consideration is needed on how a model integrates with current models and whether it will act as a descriptive framework or, will be developed into an operational model. The review highlights the importance of engagement with users and partner organizations in the co-creation of a model of healthcare. [ABSTRACT FROM AUTHOR]

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases. [ABSTRACT FROM AUTHOR]

In this paper, we present a practical approach for computing the sandwich variance estimator in 2-stage regression model settings. As a motivating example for 2-stage regression, we consider regression calibration, a popular approach for addressing covariate measurement error. The sandwich variance approach has rarely been applied in regression calibration, despite its requiring less computation time than popular resampling approaches for variance estimation, specifically the bootstrap. This is probably because it requires specialized statistical coding. Here we first outline the steps needed to compute the sandwich variance estimator. We then develop a convenient method of computation in R for sandwich variance estimation, which leverages standard regression model outputs and existing R functions and can be applied in the case of a simple random sample or complex survey design. We use a simulation study to compare the sandwich estimator to a resampling variance approach for both settings. Finally, we further compare these 2 variance estimation approaches in data examples from the Women's Health Initiative (1993–2005) and the Hispanic Community Health Study/Study of Latinos (2008–2011). In our simulations, the sandwich variance estimator typically had good numerical performance, but simple Wald bootstrap confidence intervals were unstable or overcovered in certain settings, particularly when there was high correlation between covariates or large measurement error. [ABSTRACT FROM AUTHOR]

Objectives Delirium is most often reported as present or absent. Patients with symptoms falling short of the diagnostic criteria for delirium fall into 'no delirium' or 'control' groups. This binary classification neglects individual symptoms and may be hindering identification of the pathophysiology underlying delirium. This systematic review investigates which individual symptoms of delirium are reported by studies of postoperative delirium in adults. Methods Medline, EMBASE and Web of Science databases were searched on 03 June 2021 and 06 April 2023. Two reviewers independently examined titles and abstracts. Each paper was screened in duplicate and conflicting decisions settled by consensus discussion. Data were extracted, qualitatively synthesised and narratively reported. All included studies were quality assessed. Results These searches yielded 4,367 results. After title and abstract screening, 694 full-text studies were reviewed, and 62 deemed eligible for inclusion. This review details 11,377 patients including 2,049 patients with delirium. In total, 78 differently described delirium symptoms were reported. The most reported symptoms were inattention (N  = 29), disorientation (N  = 27), psychomotor agitation/retardation (N  = 22), hallucination (N  = 22) and memory impairment (N  = 18). Notably, psychomotor agitation and hallucinations are not listed in the current Diagnostic and Statistical Manual for Mental Disorders-5-Text Revision delirium definition. Conclusions The 78 symptoms reported in this systematic review cover domains of attention, awareness, disorientation and other cognitive changes. There is a lack of standardisation of terms, and many recorded symptoms are synonyms of each other. This systematic review provides a library of individual delirium symptoms, which may be used to inform future reporting. [ABSTRACT FROM AUTHOR]

Background: With the increasing number of people affected by multiple chronic conditions, it is essential for public-health professionals to promote strategies addressing patient needs for coordinated care. We aim to explore preference heterogeneity for better-coordinated care delivery models in Swiss older adults, and identify profiles of individuals more open to healthcare reforms. Methods: A DCE (discrete choice experiment) survey was developed online and on paper for the Swiss adults aged 50þ, following best practice. To elicit preferences, we estimated a latent class model allowing grouping individuals with similar preferences into distinct classes, and examined what background characteristics contributed to specific class membership. Results: The optimal model identified three classes with different openness to reforms. Class 1 (49%) members were concerned with premium increases and were in favour of integrated care structures with care managed by interprofessional teams. Individuals in class 2 (19%) were younger, open to reforms, and expressed the needs for radical changes within the Swiss healthcare system. Class 3 respondents (32%) were strongly reluctant to changes. Conclusions: Our study goes beyond average preferences and identifies three distinct population profiles, a majority open to reforms on specific aspects of care delivery, a smallest group in favour radical changes, and a third strongly against changes. Therefore, tailored approaches around healthcare reforms are needed, e.g. explaining the role of interprofessional teams in coordinating care, electronic health records and insurance premium variation. [ABSTRACT FROM AUTHOR]

For at least the past 5 decades, population genetics, as a field, has worked to describe the precise balance of forces that shape patterns of variation in genomes. The problem is challenging because modeling the interactions between evolutionary processes is difficult, and different processes can impact genetic variation in similar ways. In this paper, we describe how diversity and divergence between closely related species change with time, using correlations between landscapes of genetic variation as a tool to understand the interplay between evolutionary processes. We find strong correlations between landscapes of diversity and divergence in a well-sampled set of great ape genomes, and explore how various processes such as incomplete lineage sorting, mutation rate variation, GC-biased gene conversion and selection contribute to these correlations. Through highly realistic, chromosome-scale, forward-in-time simulations, we show that the landscapes of diversity and divergence in the great apes are too well correlated to be explained via strictly neutral processes alone. Our best fitting simulation includes both deleterious and beneficial mutations in functional portions of the genome, in which 9 % of fixations within those regions is driven by positive selection. This study provides a framework for modeling genetic variation in closely related species, an approach which can shed light on the complex balance of forces that have shaped genetic variation. [ABSTRACT FROM AUTHOR]

Background Music is an integral part of our lives and is often played in public places like restaurants. People exposed to music that contained alcohol-related lyrics in a bar scenario consumed significantly more alcohol than those exposed to music with less alcohol-related lyrics. Existing methods to quantify alcohol exposure in song lyrics have used manual annotation that is burdensome and time intensive. In this paper, we aim to build a deep learning algorithm (LYDIA) that can automatically detect and identify alcohol exposure and its context in song lyrics. Methods We identified 673 potentially alcohol-related words including brand names, urban slang, and beverage names. We collected all the lyrics from the Billboard's top-100 songs from 1959 to 2020 (N = 6110). We developed an annotation tool to annotate both the alcohol-relation of the word (alcohol, non-alcohol, or unsure) and the context (positive, negative, or neutral) of the word in the song lyrics. Results LYDIA achieved an accuracy of 86.6% in identifying the alcohol-relation of the word, and 72.9% in identifying its context. LYDIA can distinguish with an accuracy of 97.24% between the words that have positive and negative relation to alcohol; and with an accuracy of 98.37% between the positive and negative context. Conclusion LYDIA can automatically identify alcohol exposure and its context in song lyrics, which will allow for the swift analysis of future lyrics and can be used to help raise awareness about the amount of alcohol in music. Highlights Developed a deep learning algorithm (LYDIA) to identify alcohol words in songs. LYDIA achieved an accuracy of 86.6% in identifying alcohol-relation of the words. LYDIA's accuracy in identifying positive, negative, or neutral context was 72.9%. LYDIA can automatically provide evidence of alcohol in millions of songs. This can raise awareness of harms of listening to songs with alcohol words. [ABSTRACT FROM AUTHOR]

This systematic review investigates the bidirectional relationship between alcohol consumption and disrupted circadian rhythms. The goal of this study was to identify (i) the types of circadian rhythm disruptors (i.e. social jet lag, extreme chronotypes, and night shift work) associated with altered alcohol use and (ii) whether sex differences in the consequences of circadian disruption exist. We conducted a search of PubMed, Embase, and PsycINFO exclusively on human research. We identified 177 articles that met the inclusion criteria. Our analyses revealed that social jet lag and the extreme chronotype referred to as eveningness were consistently associated with increased alcohol consumption. Relationships between night shift work and alcohol consumption were variable; half of articles reported no effect of night shift work on alcohol consumption. Both sexes were included as participants in the majority of the chronotype and social jet lag papers, with no sex difference apparent in alcohol consumption. The night shift research, however, contained fewer studies that included both sexes. Not all forms of circadian disruption are associated with comparable patterns of alcohol use. The most at-risk individuals for increased alcohol consumption are those with social jet lag or those of an eveningness chronotype. Direct testing of the associations in this review should be conducted to evaluate the relationships among circadian disruption, alcohol intake, and sex differences to provide insight into temporal risk factors associated with development of alcohol use disorder. [ABSTRACT FROM AUTHOR]

Background Dual sensory impairment (DSI), the combination of visual and hearing impairments, is associated with increased risk for age-related cognitive decline and dementia. Administering cognitive tests to individuals with sensory impairment is challenging because most cognitive measures require sufficient hearing and vision. Considering sensory limitations during cognitive test administration is necessary so that the effects of sensory and cognitive abilities on test performance can be differentiated and the validity of test results optimized. Objective To review empirical strategies that researchers have employed to accommodate DSI during cognitive testing of older adults. Methods Seven databases (MEDLINE, Embase, Web of Science, CINAHL, PsycINFO, Global Health and the Evidence-Based Medicine Reviews databases) were searched for relevant articles integrating the three concepts of cognitive evaluation, aging, and DSI. Given the inclusion criteria, this scoping review included a total of 67 papers. Results Twenty-eight studies reported five categories of strategies for cognitive testing of older adult participants with DSI: the assistance of experts, the modification of standardized test scoring procedures, the use of communication strategies, environmental modifications, and the use of cognitive tests without visual and/or auditory items. Conclusions The most used strategy reported in the included studies was drawing on the assistance of team members from related fields during the administration and interpretation of cognitive screening measures. Alternative strategies were rarely employed. Future research is needed to explore the knowledge-to-practice gap between research and current clinical practice, and to develop standardized testing strategies. [ABSTRACT FROM AUTHOR]

Background and Objectives Evidence-based practices to manage distress behaviors in dementia (DBD) are not consistently implemented despite demonstrated effectiveness. The Veterans Health Administration (VA) trained teams to implement Staff Training in Assisted Living Residences (STAR)-VA, an intervention to manage DBD in VA nursing home settings, or Community Living Centers (CLCs). This paper summarizes multiyear formative evaluation results including challenges, adaptations, and lessons learned to support sustained integration into usual care across CLCs nationwide. Research Design and Methods STAR was selected as an evidence-based practice for DBD, adapted for and piloted in VA (STAR-VA), and implemented through a train-the-trainer program from 2013 to 2018. Training and consultation were provided to 92 CLC teams. Evaluation before and after training and consultation included descriptive statistics of measures of clinical impact and survey feedback from site teams regarding self-confidence, engagement, resource quality, and content analysis of implementation facilitators and challenges. Results STAR-VA training and consultation increased staff confidence and resulted in significant decreases in DBD, depression, anxiety, and agitation for Veterans engaged in the intervention. Implementation outcomes demonstrated feasibility and identified facilitators and barriers. Key findings were interpreted using implementation frameworks and informed subsequent modifications to sustain implementation. Discussion and Implications STAR-VA successfully prepared teams to manage DBD and resulted in improved outcomes. Lessons learned include importance of behavioral health–nursing partnerships, continuous engagement, iterative feedback and adaptations, and sustainment planning. Evaluation of sustainment factors has informed selection of implementation strategies to address sustainment barriers. Lessons learned have implications for integrating team-based practices into system-level practice. [ABSTRACT FROM AUTHOR]

Background Value-based healthcare (VBHC) is a conceptual framework to improve the value of healthcare by health, care-process and economic outcomes. Benchmarking should provide useful information to identify best practices and therefore a good instrument to improve quality across healthcare organizations. This paper aims to provide a proof-of-concept of the feasibility of an international VBHC benchmarking in breast cancer, with the ultimate aim of being used to share best practices with a data-driven approach among healthcare organizations from different health systems. Methods In the VOICE community—a European healthcare centre cluster intending to address VBHC from theory to practice—information on patient-reported, clinical-related, care-process-related and economic-related outcomes were collected. Patient archetypes were identified using clustering techniques and an indicator set following a modified Delphi was defined. Benchmarking was performed using regression models controlling for patient archetypes and socio-demographic characteristics. Results Six hundred and ninety patients from six healthcare centres were included. A set of 50 health, care-process and economic indicators was distilled for benchmarking. Statistically significant differences across sites have been found in most health outcomes, half of the care-process indicators, and all economic indicators, allowing for identifying the best and worst performers. Conclusions To the best of our knowledge, this is the first international experience providing evidence to be used with VBHC benchmarking intention. Differences in indicators across healthcare centres should be used to identify best practices and improve healthcare quality following further research. Applied methods might help to move forward with VBHC benchmarking in other medical conditions. [ABSTRACT FROM AUTHOR]

Background Despite the growing utilization of data-driven methods to investigate multimorbidity patterns, there is currently no consensus or guidance on the conditions to include when identifying patterns. This scoping review aims to systematically examine the nature of conditions included in existing studies using data-driven techniques. Methods A comprehensive search of three electronic databases (MEDLINE, Web of Science and Scopus) was conducted to identify relevant publications from inception to 28 February 2022 using predefined search terms and inclusion/exclusion criteria. The reference lists and citations of relevant papers were also searched. Results Among 7326 search results, 5444 relevant articles were identified. After screening against the eligibility criteria, 60 articles were included in the review. Half of the reviewed studies reported selection criteria for conditions, with prevalence in the population of interest being the most common criterion (40%). Most studies included at least one neurological [59 (98.3%)], musculoskeletal [58 (96.7%)], respiratory [57 (95.0%)] or mental health [56 (93.3%)] condition. In contrast, only a small proportion of studies included skin [17 (28.3%)], infections [14 (23.3%)] or autoimmune conditions [10 (16.7%)]. Nine conditions (hypertension, diabetes, cancer, arthritis, COPD, asthma, depression, stroke and osteoporosis) were included by more than half of the studies. Conclusions This review highlights the considerable heterogeneity among the conditions included in analyses of multimorbidity patterns. Researchers should provide a clear rationale for the selection of conditions to facilitate comparisons across studies and ensure reproducibility, as well as consider selecting a diverse range of conditions to capture the complexity of multimorbidity. [ABSTRACT FROM AUTHOR]

Objective This paper highlights the occupational risk of Q fever from exposure to raw animal products in the context of multiple notified Q fever cases from 2020 to 2023 linked to four pet food manufacturing facilities in South-East Queensland, Australia. Methods The Queensland Government Notifiable Conditions System was used to identify Q fever cases linked to pet food manufacturing in the Metro North and Gold Coast Hospital and Health Service areas of Brisbane, Australia. Data on each case from routine public health follow-up were collected and descriptively analysed. Results Between 2020 and 2023, 12 confirmed Q fever infections (17% of total cases) were linked to four pet food manufacturing facilities. Eleven cases reported direct or environmental exposure to raw meat and animal products. None were previously vaccinated for Q fever. Conclusion These cases demonstrate the increased risk of Q fever infection as part of the pet food manufacturing process, highlighting an underappreciated preventable occupational risk, which can be mitigated with the use of pre-screening and vaccination of workers. All occupations should conduct workplace-based risk assessments to identify risks such as Q fever to prevent adverse negative health outcomes. [ABSTRACT FROM AUTHOR]

Aims: This paper aims to assess kinematic parameters related to functional capacity, fatigue, and breathlessness during the 6-min walk test (6MWT) in patients with heart failure with preserved ejection fraction (HFpEF). Methods and results: A cross-sectional study was conducted in which adults 70 years or older with HFpEF were voluntarily recruited between April 2019 and March 2020. An inertial sensor was placed at the L3–L4 level and another on the sternum to assess kinematic parameters. The 6MWT was divided into two 3-min phases. Leg fatigue and breathlessness, assessed by the Borg scale, the heart rate (HR), and the oxygen saturation (SpO2), were measured at the beginning and the end of the 6MWT. The difference in kinematic parameters between the 6MWT two 3-min phases was also calculated. Bivariate Pearson correlations and subsequent multivariate linear regression analysis were performed. Seventy older adults with HFpEF (mean = 80.74 years old) were included. Kinematic parameters explained 81.00% of the functional capacity, 45.50% of the leg fatigue and 66.10% of the breathlessness variance. Moreover, kinematic parameters could explain 30.90% of the SpO2 variance at the end of the 6MWT. Kinematic parameters also explained 33.10% of the SpO2 difference between the beginning and end of 6MWT. Kinematic parameters explained neither the HR variance at the end of 6MWT nor the HR difference between the beginning and end. Conclusion: Gait kinematics from L3-L4 and sternum explain a part of the variance in subjective outcomes, assessed by the Borg scale, and objective outcomes such as functional capacity and SpO2. The kinematic assessment allows clinicians to quantify fatigue and breathlessness through objective parameters related to the patient's functional capacity. Registration: ClinicalTrials.gov NCT03909919. Graphical Abstract [ABSTRACT FROM AUTHOR]