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Background Doctors' organisations in the UK have reported worrying levels of work-related stress and burnout in the GP workforce for some time, and the COVID-19 pandemic has presented clear new challenges. Aim To synthesise intern...
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Background Doctors' organisations in the UK have reported worrying levels of work-related stress and burnout in the GP workforce for some time, and the COVID-19 pandemic has presented clear new challenges. Aim To synthesise international evidence exploring the impact of COVID-19 on primary care doctors' mental health and wellbeing, and identify risk factors associated with their psychological wellbeing during this time. Design and setting Mixed-methods systematic review. Method Six bibliographic databases, Google Scholar, and MedRxivwere searched on 19 November 2020 and 3 June 2021 to identify studies of GP psychological wellbeing during the pandemic. Reference checking was also conducted. Two reviewers selected studies, extracted data, and assessed the quality of studies using standardised tools. Heterogeneity in outcomes, setting, and design prohibited statistical pooling; studies were combined using a convergent integrated thematic synthesis. Results Thirty-one studies were included. Multiple sources of stress were identified including changed working practices; risk, exposure, and inadequate personal protective equipment (PPE); information overload; pandemic preparedness; and cohesion across sectors. Studies demonstrated an impact on psychological wellbeing, with some GPs experiencing stress, burnout, anxiety, depression, fear of COVID-19, lower job satisfaction, and physical symptoms. Studies reported gender and age differences: women GPs had poorer psychological outcomes across all domains, and older GPs reported greater stress and burnout. Use of outcome measures and reporting practice varied greatly. Conclusion This review of international evidence demonstrates that the COVID-19 pandemic has adversely affected GPs' wellbeing around the world. Further research could explore gender and age differences, identifying interventions targeted to these groups.
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Objectives: People with mental disorders are more likely to smoke than the general population. The objective of this study is to develop a decision analytical model that estimates long-term cost-effectiveness of smoking cessation ...
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Objectives: People with mental disorders are more likely to smoke than the general population. The objective of this study is to develop a decision analytical model that estimates long-term cost-effectiveness of smoking cessation interventions in this population. Methods: A series of Markov models were constructed to estimate average lifetime smoking-attributable inpatient cost and expected quality-adjusted life-years. The model parameters were estimated using a variety of data sources. The model incorporated uncertainty through probabilistic sensitivity analysis using Monte Carlo simulations. It also generated tables presenting incremental cost-effectiveness ratios of the proposed interventions with varying incremental costs and incremental quit rates. We used data from 2 published trials to demonstrate the model's ability to make projections beyond the observational time frame. Results: The average smoker's smoking-attributable inpatient cost was 3 times higher and health utility was 5% lower than ex smokers. The intervention in the trial with a statistically insignificant difference in quit rate (19% vs 25%; P=.2) showed a 45% to 49% chance of being cost-effective compared with the control at willingness-to-pay thresholds of 20 pound 000 to 30 pound 000/ quality-adjusted life-years. The second trial had a significant outcome (quit rate 35.9% vs 15.6%; P,.001), and the corresponding probability of the intervention being cost-effective was 65%. Conclusions: This model provides a consistent platform for clinical trials to estimate the potential lifetime cost-effectiveness of smoking cessation interventions for people with mental disorders and could help commissioners direct resources to the most cost-effective programs. However, direct comparisons of results between trials must be interpreted with caution owing to their different designs and settings.
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Introduction: Community pharmacies have an increasingly prominent public health function. This includes addressing alcohol, but guidance on delivery of alcohol interventions in this setting is lacking. We have developed an interve...
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Introduction: Community pharmacies have an increasingly prominent public health function. This includes addressing alcohol, but guidance on delivery of alcohol interventions in this setting is lacking. We have developed an intervention that integrates attention to alcohol within existing community pharmacy medicine review services. This paper examines the experiences of community pharmacists (CPs) in conducting a pilot trial of the intervention, including the acceptability of the trial patient recruitment procedures and the training and support provided by the research team. Method: The pilot trial was conducted in 10 community pharmacies in Yorkshire, England. One CP from each pharmacy was recruited via a multi-stage process to assess motivation, commitment and capacity to participate. Each CP attended a research training day and received on-going research support to conduct the trial. Semi structured audio-recorded face-to-face interviews (lasting 40-105 min) were conducted with all the CPs at the end of the trial. Data were also available from three direct observations conducted during trial support visits. Data were analysed thematically. Results: The CPs were supportive of research in community pharmacy but had little direct experiences of research themselves. They valued the training and support provided, which had quickly identified areas where CPs were deviating from the study recruitment protocol. In some instances, the boundaries between research and practice became blurred with CPs making changes to their usual routines and interactions with patients to accommodate the research. Conclusions: The trial procedures were acceptable to CPs, in part because of the training and support provided. There are also identifiable areas where CPs' readiness for research could be enhanced to facilitate participation in future trials in this setting.
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Background: The impact of consumption of sugar-sweetened beverages (SSB) on health outcomes such as obesity have been studied extensively, but oral health has been relatively neglected. This study aims to assess the association be...
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Background: The impact of consumption of sugar-sweetened beverages (SSB) on health outcomes such as obesity have been studied extensively, but oral health has been relatively neglected. This study aims to assess the association between SSB consumption and dental caries and erosion. Methods: Systematic review of observational studies. Search strategy applied to Medline, Embase, Cochrane Library, SciELO, LILACS, OpenGrey and HMIC. The risk of bias was assessed using the NIH Quality Assessment Tool for Observational Cross-Sectional Studies and evidence certainty using Grading of Recommendation Assessment Development and Evaluation. Relationships between SSB consumption and caries and erosion were estimated using random-effects model meta- and dose-response analyses. Results: A total of 38 cross-sectional studies were included, of which 26 were rated as high quality. Comparing moderate-to-low consumption, there was significantly increased risk of both caries [OR= 1.57, 95% CI: 1.28-1.92; decayed, missing and filled teeth weighted mean differences (DMFT WMD) =0.82, 95% CI: 0.38-1.26] and erosion (OR= 1.43, 95% CI: 1.01-2.03). Comparing high-to-moderate consumption, there was further increased risk of caries (OR= 1.53, 95% CI: 1.17-1.99; DMFT WMD =1.16, 95% CI: -0.59-2.91) and erosion (OR= 3.09, 95% CI: 1.37-6.97). A dose-response gradient and high certainty of evidence was observed for caries. Conclusions: Increasing SSB consumption is associated with increased risk of dental caries and erosion. Studies were cross-sectional, hence temporality could not be established, but the positive dose-response suggests this relationship is likely to be causal. These findings illustrate the potential benefits to oral health of policies that reduce SSB consumption, including sugar taxation.
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Assurance cases are often required to certify critical systems. The use of formal methods in assurance can improve automation, increase confidence, and overcome errant reasoning. However, assurance cases can never be fully formali...
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Assurance cases are often required to certify critical systems. The use of formal methods in assurance can improve automation, increase confidence, and overcome errant reasoning. However, assurance cases can never be fully formalised, as the use of formal methods is contingent on models that are validated by informal processes. Consequently, assurance techniques should support both formal and informal artifacts, with explicated inferential links between them. In this paper, we contribute a formal machine-checked interactive language, called Isabelle/SACM, supporting the computer-assisted construction of assurance cases compliant with the OMG Structured Assurance Case Meta-Model. The use of Isabelle/SACM guarantees well-formedness, consistency, and traceability of assurance cases, and allows a tight integration of formal and informal evidence of various provenance. In particular, Isabelle brings a diverse range of automated verification techniques that can provide evidence. To validate our approach, we present a substantial case study based on the Tokeneer secure entry system benchmark. We embed its functional specification into Isabelle, verify its security requirements, and form a modular security case in Isabelle/SACM that combines the heterogeneous artifacts. We thus show that Isabelle is a suitable platform for critical systems assurance.
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Background: Treatment of established depression is the dominant approach to care of older adults, but prevention holds much promise. Self-help interventions are a feasible preventive approach, since they are scalable and low cost....
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Background: Treatment of established depression is the dominant approach to care of older adults, but prevention holds much promise. Self-help interventions are a feasible preventive approach, since they are scalable and low cost. There are few trials in this area. Behavioral Activation (BA) is a credible candidate psychological approach, which has been shown to work in therapist led care but not been trialled in a self-help form. Aim: To test the effectiveness of an unguided self-help intervention based on BA for older adults. Methods: We compared a self-help intervention based on BA for older people (n = 172) to usual care (n = 160) in a pragmatic randomized controlled trial. Outcomes were depression status and severity (PHQ9) and health related quality of life (SF12). The primary timepoint of the primary outcome was depression at 4 months, with longer term follow up at 12 months to test sustained impact of the primary outcome. Results: At 4 months adjusted PHQ-9 scores for BA self-help were 0.79 lower (95% CI: -1.70 to 0.13; p = 0.09) and the proportion of participants with case-level depression was significantly reduced (BA 31/137 (22.6%) versus usual care 41/141 (29.1%); Odds Ratio 0.48; 95% CI: 0.26-0.92; p = 0.03). There was no PHQ-9 difference at 12 months or for health related quality of life at any point (4 or 12 months). Discussion: Self-help using BA for older people at risk of depression is a feasible and scalable intervention with potential short-term benefits in preventing depression.
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Background: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expa...
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Background: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and such approaches offer powerful predictive abilities. We investigated the utility of a machine learning approach to predict the persistence of depressive symptoms in older adults.
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Introduction Alcohol poses a range of potential problems to people taking medications, but health professionals are usually not comfortable talking about drinking with patients. The Medicines and Alcohol Consultation aims to incre...
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Introduction Alcohol poses a range of potential problems to people taking medications, but health professionals are usually not comfortable talking about drinking with patients. The Medicines and Alcohol Consultation aims to increase the capacity of pharmacists to conduct person-centred reviews in which alcohol is regarded as another drug to be discussed alongside medications. This paper explores sensitivities in discussing alcohol and views on the legitimacy of the Medicines and Alcohol Consultation intervention concept at a pharmacy-user intervention co-design workshop.
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