Infectious disease management in primary care: perceptions of GPs

<p>Abstract</p> <p>Background</p> <p>It is important to keep the level of antibiotic prescribing low to contain the development of resistant bacteria. This study was conducted to reveal new knowledge about how GPs think in relation to the prescribing of antibiotics - knowledge that could be used in efforts toward rational treatment of infectious diseases in primary care. The aim was to explore and describe the variations in GPs' perceptions of infectious disease management, with special reference to antibiotic prescribing.</p> <p>Methods</p> <p>Twenty GPs working at primary care centres in a county in south-west Sweden were purposively selected based on the strategy of including GPs with different kinds of experience. The GPs were interviewed and perceptions among GPs were analysed by a phenomenographic approach.</p> <p>Results</p> <p>Five qualitatively different perceptions of infectious disease management were identified. They were: (A) the GP must help the patient to achieve health and well-being; (B) the management must meet the GP's perceived personal, professional and organisational demands; (C) restrictive antibiotic prescribing is time-consuming; (D) restrictive antibiotic prescribing can protect the effectiveness of antibiotics; and (E) patients benefit personally from restrictive antibiotic prescribing.</p> <p>Conclusions</p> <p>Restrictive antibiotic prescribing was considered important in two perceptions, was not an issue as such in two others, and was considered in one perception although the actual prescribing was greatly influenced by the interaction between patient and GP. Accordingly, to encourage restrictive antibiotic prescribing several aspects must be addressed. Furthermore, different GPs need various kinds of support. Infectious disease management in primary care is complex and time-consuming, which must be acknowledged in healthcare organisation and planning.</p

Knowledge systems, health care teams, and clinical practice: a study of successful change

Clinical teams are of growing importance to healthcare delivery, but little is known about how teams learn and change their clinical practice. We examined how teams in three US hospitals succeeded in making significant practice improvements in the area of antimicrobial resistance. This was a qualitative cross-case study employing Soft Knowledge Systems as a conceptual framework. The purpose was to describe how teams produced, obtained, and used knowledge and information to bring about successful change. A purposeful sampling strategy was used to maximize variation between cases. Data were collected through interviews, archival document review, and direct observation. Individual case data were analyzed through a two-phase coding process followed by the cross-case analysis. Project teams varied in size and were multidisciplinary. Each project had more than one champion, only some of whom were physicians. Team members obtained relevant knowledge and information from multiple sources including the scientific literature, experts, external organizations, and their own experience. The success of these projects hinged on the teams' ability to blend scientific evidence, practical knowledge, and clinical data. Practice change was a longitudinal, iterative learning process during which teams continued to acquire, produce, and synthesize relevant knowledge and information and test different strategies until they found a workable solution to their problem. This study adds to our understanding of how teams learn and change, showing that innovation can take the form of an iterative, ongoing process in which bits of K&I are assembled from multiple sources into potential solutions that are then tested. It suggests that existing approaches to assessing the impact of continuing education activities may overlook significant contributions and more attention should be given to the role that practical knowledge plays in the change process in addition to scientific knowledge

Shellsim: A Generic Model of Growth and Environmental Effects Validated Across Contrasting Habitats in Bivalve Shellfish

Previous shellfish models have, in general, been calibrated for 1 location, unable to simulate growth across habitats that contrast in seston abundance and composition, as may vary between turbid, eutrophic and oligotrophic waters. Here, we describe the generic shellfish model ShellSIM, demonstrating how a common parameter set simulates growth effectively on calibration in the mussel Mytilus edulis and oyster Crassostrea gigas during normal culture across 9 different locations in Europe and China. Options enable the user to assess the relative values of chlorophyll a (CHL, measured in micrograms per liter), total particulate organic matter (POM; measured in milligrams per liter), and total particulate organic carbon (POC; measured in milligrams per liter) as codescriptors of the food available at separate locations. Using CHL as the sole proxy for available organics, together with an average carbon-to-CHL ratio of 50, growth in both M. edulis and C. gigas was predicted accurately at only 5 locations, primarily those with relatively low average food availability. In contrast, more than 74% of the observed variance in growth was predicted across all 9 locations in each species on inclusion of dynamic relations defining ingestion and absorption of both CHL-rich and all remaining organic matter such as may include bacteria, protozoans, colloids, and/or detritus, thereby helping to account for temporal and spatial changes in dietary composition. The energy content of the remaining organic matter (measured in Joules per milligram) ranged seasonally across all sites from about 2–25 J/mg, and could be predicted with growth from the relative abundance of CHL and POM alone, proving a viable alternative to more technically demanding measures of POC. Fractional contributions of the remaining organic matter to the energy absorbed in both species at each location ranged from less than about 0.4 during the spring to more than 0.8 from late autumn, in negative relation with CHL, thus helping to offset tissue wasting during winter months. We acknowledge model uncertainties, emphasizing the need to balance practicality and affordability against required accuracies. Last, we describe how the generic and multi-site capabilities afforded by ShellSIM, together with real-time outputs ready for integrated modeling of how shellfish influence ecosystem properties and processes, are saving time and resources across a variety of applications

Comparative feeding on chlorophyll - rich versus remaining organic matter in bivalve shellfish

Filter feeding was compared in the blue mussel Mytilus edulis, Mediterranean mussel Mytilus galloprovincialis, Pacific oyster Crassostrea gigas, Chinese pleated oyster Crassostrea plicatula, Chinese scallop Chlamys farreri,Manila clam Tapes phillipinarum, razor clam Sinonvacula constricta, and blood cockle Tegillarca granosa over 95 dietary conditions across nine locations in Europe and China. Conditions included natural seawater enhanced, on occasion, with variable additions of microalgal monoculture and/or natural silt collected from the surface of nearby mudflats, thereby ensuring that diets ranged from oligotrophic to hypereutrophic (>325 µg chlorophyll a/L) and highly turbid (>1,250 mg total particulate matter/L). Building on past insights into differential particle processing, we resolved the availability, filtration, and ingestion of organic matter rich in chlorophyll a, and which matter is known to be ingested selectively, from all remaining organics, such as detritus, bacteria, protozoans, and/or colloids. The forms of fitted relations that best described feeding responses were different for chlorophyll-rich versus remaining organics, that difference being consistent in all eight bivalve species, including when measured in the same species across different locations. Throughout, positive linear relations between net ingestion of chlorophyll-rich organic matter and the availability of that chlorophyll-rich organic matter indicated that each species ingested constant proportions of the organics associated with chlorophyll a, with no limitation evident to such ingestion over our experimental range. Alternatively, ingestion of the remaining organics by each species increased as saturating functions of the availability of those remaining organics alone. Differences were evident between species both in the proportions of available chlorophyll-rich organic matter that were ingested and in saturated ingestion rates for the remaining organics. Comparison of those differences suggests an evolutionary trade-off among species between their relative abilities to process chlorophyll-rich versus remaining organics. Differences also suggest congeneric adaptation to natural habitat, impressing a need for careful appraisal of each and every bivalve species. Significant costs of particle sorting, digestion, and absorption, evidenced as metabolically derived material egested and assayed within feces, were greatest in species with higher saturated capacities for the ingestion of remaining organics. Last, we describe how, compared with predictions based on chlorophyll a or total particulate organic matter alone, our approach resolving coincident differential availabilities and processing of chlorophyll-rich versus remaining organic matter has improved the accuracy of growth simulations when applying single calibrations of the generic shellfish model ShellSIM across coastal habitats that contrast in seston composition

Effects of yoga on depressive symptoms in people with mental disorders: a systematic review and meta-analysis

OBJECTIVE:To assess whether physically active yoga is superior to waitlist control, treatment as usual and attention control in alleviating depressive symptoms in people with a diagnosed mental disorder recognised by the Diagnostic and Statistical Manual of Mental Disorders (DSM). DESIGN:Systematic review and meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. DATA SOURCES:Data were obtained from online databases (MEDLINE, EMBASE, PsychINFO, CENTRAL, EMCARE, PEDro). The search and collection of eligible studies was conducted up to 14 May 2019 (PROSPERO registration No CRD42018090441). ELIGIBILITY CRITERIA FOR SELECTING STUDIES:We included randomised controlled trials with a yoga intervention comprising ≥50% physical activity in adults with a recognised diagnosed mental disorder according to DSM-3, 4 or 5. RESULTS:19 studies were included in the review (1080 participants) and 13 studies were included in the meta-analysis (632 participants). Disorders of depression, post-traumatic stress, schizophrenia, anxiety, alcohol dependence and bipolar were included. Yoga showed greater reductions in depressive symptoms than waitlist, treatment as usual and attention control (standardised mean difference=0.41; 95% CI -0.65 to -0.17; p<0.001). Greater reductions in depressive symptoms were associated with higher frequency of yoga sessions per week (β=-0.44, p<0.01).Jacinta Brinsley, Felipe Schuch, Oscar Lederman, Danielle Girard, Matthew Smout ... et al

Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours

Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25–958, and mean participant age ranged between 9–71 years. Most interventions (n = 15, 79%) targeted physical activity, and most trials had a low-quality rating (n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious