Social validity of randomised controlled trials in health services research and intellectual disabilities: a qualitative exploration of stakeholder views

<p>Abstract</p> <p>Background</p> <p>Randomised controlled trials (RCTs) are the gold standard of evidence-based practice in medicine but they have had limited influence in the field of intellectual disabilities. Previous literature suggests that participants and professionals have limited tolerance for this type of research methodology. However, it is not known how well service users, carers and other health professionals understand and accept the need for RCTs, and why it is important for individuals with intellectual disabilities to be included in this kind of research.</p> <p>Methods</p> <p>We examined individual perceptions of RCTs in 51 participants (18 carers, 6 service users and 27 professionals) using semi-structured interviews. A framework approach was adopted in the analysis of data.</p> <p>Results</p> <p>We found that participants had concerns about capacity and resource allocation but held positive views towards this type of research methodology. Understanding of the principles behind RCTs was poor amongst service users and a minority of carers, but mediated by previous exposure to research for professionals.</p> <p>Conclusions</p> <p>The social validity of RCTs in intellectual disabilities may be compromised by lack of understanding of the design and the on-going concerns about obtaining informed consent especially in incapacitated adults. However, the overall finding that the need for this form of research was seen in a positive light suggests that there is a turning point in the perceptions of stakeholders working in intellectual disabilities services. We recommend that researchers include on-going education on RCT design during trials, tailoring it to all stakeholders with emphasis on strong service user and care involvement. This could be a pivotal element in improving acceptability of, and recruitment to RCTs.</p

Cashew nut allergy: clinical relevance and allergen characterisation

Cashew plant (Anacardium occidentale L.) is the most relevant species of the Anacardium genus. It presents high economic value since it is widely used in human nutrition and in several industrial applications. Cashew nut is a well-appreciated food (belongs to the tree nut group), being widely consumed as snacks and in processed foods by the majority of world's population. However, cashew nut is also classified as a potent allergenic food known to be responsible for triggering severe and systemic immune reactions (e.g. anaphylaxis) in sensitised/allergic individuals that often demand epinephrine treatment and hospitalisation. So far, three groups of allergenic proteins have been identified and characterised in cashew nut: Ana o 1 and Ana o 2 (cupin superfamily) and Ana o 3 (prolamin superfamily), which are all classified as major allergens. The prevalence of cashew nut allergy seems to be rising in industrialised countries with the increasing consumption of this nut. There is still no cure for cashew nut allergy, as well as for other food allergies; thus, the allergic patients are advised to eliminate it from their diets. Accordingly, when carefully choosing processed foods that are commercially available, the allergic consumers have to rely on proper food labelling. In this sense, the control of labelling compliance is much needed, which has prompted the development of proficient analytical methods for allergen analysis. In the recent years, significant research advances in cashew nut allergy have been accomplished, which are highlighted and discussed in this review.This work was supported by FCT/MEC through national funds and co-financed by FEDER, under the Partnership Agreement PT2020 with grant no. UID/QUI/50006/2013–POCI/01/ 0145/FEDER/007265. Joana Costa is grateful to FCT post-doctoral grant (SFRH/BPD/102404/2014) financed by POPH-QREN (subsidised by FSE and MCTES).info:eu-repo/semantics/publishedVersio

Stress and subjective well-being among first year UK undergraduate students

Transition to university is stressful and successful adjustment is imperative for well-being. Historically research on transitional stress focussed on negative outcomes and ill health. This is the first UK study applying a positive psychology approach to investigate the characteristics that facilitate adjustment among new university students. A range of psychological strengths conceptualised as covitality factors, shown individually to influence the stress and subjective well-being (SWB) relationship were assessed among 192 first year UK undergraduates in week three of their first semester and again six months later. Path analyses revealed that optimism mediated the relationship between stress and negative affect (a component of SWB) over time, and academic self-efficacy demonstrated significant relationships with life satisfaction and positive affect. Contrary to predictions, stress levels remained stable over time although academic alienation increased and self-efficacy decreased. Optimism emerged as a key factor for new students to adjust to university, helping to buffer the impact of stress on well-being throughout the academic year. Incorporating stress management and psycho-educational interventions to develop strengths is discussed as a way of promoting confidence and agency in new students to help them cope better with the stress at university

Modelling the transmission of healthcare associated infections: a systematic review.

BACKGROUND: Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. METHODS: MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. RESULTS: In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. CONCLUSIONS: Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models

Computer-based tools for decision support in agroforestry: Current state and future needs

Successful design of agroforestry practices hinges on the ability to pull together very diverse and sometimes large sets of information (i.e., biophysical, economic and social factors), and then implementing the synthesis of this information across several spatial scales from site to landscape. Agroforestry, by its very nature, creates complex systems with impacts ranging from the site or practice level up to the landscape and beyond. Computer-based Decision Support Tools (DST) help to integrate information to facilitate the decision-making process that directs development, acceptance, adoption, and management aspects in agroforestry. Computer-based DSTs include databases, geographical information systems, models, knowledge-base or expert systems, and ‘hybrid’ decision support systems. These different DSTs and their applications in agroforestry research and development are described in this paper. Although agroforestry lacks the large research foundation of its agriculture and forestry counterparts, the development and use of computer-based tools in agroforestry have been substantial and are projected to increase as the recognition of the productive and protective (service) roles of these tree-based practices expands. The utility of these and future tools for decision-support in agroforestry must take into account the limits of our current scientific information, the diversity of aspects (i.e. economic, social, and biophysical) that must be incorporated into the planning and design process, and, most importantly, who the end-user of the tools will be. Incorporating these tools into the design and planning process will enhance the capability of agroforestry to simultaneously achieve environmental protection and agricultural production goals