Applied Research Research Articles

Deaths of despair in England: an observational study of local authority mortality data

BackgroundDeaths of Despair (DoD) are socially patterned causes of death encompassing drug and alcohol misuse and suicide. DoDs are strongly associated with socioeconomic disadvantage. England has high levels of inequalities, so we hypothesised the existence of marked geographical variations in DoD. We aimed to yield new knowledge on the spatial distribution of DoD, and area-level socioeconomic factors that predict DoD risk in England. MethodsThis observational study was conducted using ICD-10 coded deaths for 307 local authorities in England during 2019–21. Deaths were grouped to non-overlapping categories of drug-related death, alcohol-specific death, and suicide. The mean contributions of each of these causes to the total number of DoD in England were calculated with Poisson exact confidence intervals. Standardised mortality ratios (SMRs) for DoD were generated for each local authority population. A multivariable regression model for DoD risk was developed using 25 socioeconomic variables. FindingsAn estimated 46 200 people lost their lives due to DoD between Jan 1, 2019, and Dec 31, 2021. Regional SMRs ranged from 57·4 (SD 16·1) in London to 144·1 (SD 26·8) in the northeast of England (p<0·0001). Alcohol-specific deaths were the largest contributor of DoD, accounting for 44·1% of DoD (95% CI 43·5–44·8), followed by drug-related death (28·1%, 27·7–28·6) and suicide (27·7%, 27·2–28·2). Living in the North, living alone, White British ethnicity, lower inward migration, economic inactivity, income deprivation in older people, employment in elementary occupations, unemployment, and education deprivation in adults were significantly associated with higher DoD rates in England. InterpretationDoD in England are spatially patterned, with northern regions experiencing a considerably higher burden of mortality from these avoidable causes. A key limitation is ecological bias. This study provides novel insights into area-level risk factors for DoD in England. FundingNational Institute for Health and Care Research (NIHR) Applied Research Collaboration Greater Manchester (ARC-GM).

Estimation of HbA1c after weight loss using a beta-regression for an economic evaluation of a behavioural weight management programme from the GLoW trial: a methodological study

BackgroundIn economic evaluations, average intervention effects are usually applied to a population. However, this fails to reflect the change in the distribution of HbA1c due to heterogeneous responses to weight loss. We aimed to investigate whether allowing heterogeneous treatment effects using a beta regression better represented the distribution of HbA1c after a weight-loss intervention, and how this affected cost effectiveness. MethodsThe Glucose Lowering through Weight Management (GLoW) trial evaluated the effectiveness of a diabetes education and weight-loss intervention against a standard diabetes education programme. Adults diagnosed with type 2 diabetes within 3 years were recruited from Clinical Commissioning Groups across 159 sites in England from July 20, 2018, to July 22, 2018. Ethics approval (18/ES/0048) and participant informed consent were obtained. Considering the between-treatment-arm difference in HbA1c after 12 months, we compared a mean-effect estimated from a mixed-effects regression to a heterogeneous effect estimated from a beta regression performed on 12-month HbA1c conditional on baseline HbA1c, gender, diabetes duration and intervention group. We used the School of Public Health Research (SPHR) Diabetes Treatment model to apply these treatment effects and evaluate the lifetime NHS costs and quality-adjusted life-years (QALYs), discounted at 3·5%. The microsimulation model estimated diabetes-related health outcomes using the UK Prospective Diabetes Study Outcomes Model 2 risk equations and risk factor trajectory equations, alongside estimating diabetes remission, osteoarthritis, and cancer. We calculated the incremental net benefit (INB) of the intervention using a £20 000 per QALY valuation, by deterministic analysis. The GLoW trial is registered with the ISRCTN Registry, ISRCTN18399564. FindingsThe trial recruited 577 participants (mean age 60 years; 278 [53%] female, 247 [47%] male; 474 [91%] white ethnic background). Applying heterogeneous HbA1c changes better reproduced the skewness in post-intervention HbA1c than applying a mean-effect (Kolmogorov-Smirnov test p=0·02 compared with p=0·0000007). The beta-regression method suggested the intervention was more cost-effective, estimating an INB of £736 per person, compared with £584 when applying the mean-effect. InterpretationAlternative regression specification methods should be considered when evaluating the cost-effectiveness of interventions if the key intervention outcomes are not normally distributed. However, this alternative method requires further investigation to conclude its appropriateness in evaluating cost-effectiveness in different contexts. FundingNational Institute for Health and Care Research (NIHR) Programme Grants for Applied Research Programme (Reference Number RP-PG0216-20010).

Improving the understanding and management of back pain in older adults: the BOOST research programme including RCT and OPAL cohort

Improving the understanding and management of back pain in older adults: the BOOST research programme including RCT and OPAL cohort

Stratification of risk for emergent intracranial abnormalities in children with headaches: a Pediatric Emergency Care Applied Research Network (PECARN) study protocol

IntroductionHeadache is a common chief complaint of children presenting to emergency departments (EDs). Approximately 0.5%–1% will have emergent intracranial abnormalities (EIAs) such as brain tumours or strokes. However, more than...

Super Gender in Game Design: Applied Research on Destigmatizing Homosexuality in China

As of 2021, Chinas homosexual population has exceeded 70 million. This paper studies the current stigma phenomenon of homosexuality in China, analyzes the plight of LGBT( Lesbians, Gays, Bisexuals, Transgender) people in China under the stigma phenomenon and the reasons why destigmatization measures are ineffective, and puts forward the difficulty of solving the problem and the urgency of the current problem. At the same time, it studies the current situation of the combination of games and Super Gender. Starting from the perspective of psychology, it researches, develops, and designs how to better integrate Super Gender into games. Using the projection of Chinas social stigma to become the players shadow friend, using a humorous and interesting plot design to guide the player to escape the shackles of stigma on the characters victory, make players accept Super Gender independently. Let players re-recognize themselves, re-recognize and accept LGBT groups, de-label them, and achieve the purpose of destigmatization.

The role of entrepreneurship in managing organizational creativity Applied research for a sample of academics - Tikrit University / Messrs.

تسهم الممارسات الحديثة في مجال المنظمات العالمية إلى أن ريادة الاعمال والادارة وتقدّمها واستدامتها يتحقق ذلك بزيادة المهارات والمعارف التي تمتلكها من اجل ممارسات الابداع التنظيمي. وفي إطار ما يرتبط بمفهوم ريادة الاعمال من دعوات مستمرة لتبنيه في العمليات الاستراتيجية إدارة الابداع التنظيمي، وقد أثمر ذلك لظهور العديد من الفرص أمام المنظمات التي تمارس الريادة في عملها وتطبق مكونات في إدارة الابداع التنظيمي. حفزت البيانات الواردة أعلاه تبني كلا من ريادة الأعمال في إدارة الإبداع والموضوع الذي تمت مناقشته مؤخرا، من خلال محاولة تعريض المساهمات في الإدارة التنظيمية الإبداعية التنظيمية في المنظمة لتعزيز أبعاد إدارة الابداع التنظيمي عن طريق دراسة تطبيقية لعينة من الأكاديميين في جامعة تكريت التي تقع ضمن رقعة الجامعات الاكاديمية العراقية. ولتحقيق التغطية المناسبة للموضوع فقد استعانة الباحث بالعديد من الأدوات البحثية للحصول على البيانات والمعلومات، واستعانة باستمارة الاستبانة، اذ بلغ عددهم (220) استاذا يمثلون (أعضاء الهيئة التدريسية) بوصفهما مدخلاً للحصول على البيانات التي يحتاجها للوقوف على واقع تلك المتغيرات ميدانياً، وبالتالي تم معالجتها ووضع الحلول المناسبة للواقع عبر مخطط افتراضي يقوم على توظيف مكونات إدارة الابداع التنظيمي في تعزيز ريادة الاعمال المستدامة.

Hydrogen energy system for cooling habitation located in Ghardaïa using TRNSYS 16

Hydrogen system is mainly based on the Proton Exchange Membrane PEMFC technology (cogeneration), using hydrogen and air, respectively, as fuel and oxidant. The heat exhaust is evacuated to the Thermal Storage Tank (TST) which is using in LiBr/H2O single effect absorption system for residential system cooling. Absorption system is based on evaporation of the refrigerant (water) in the evaporator in low pressure. Numerical simulation of the absorption cooling system using the thermal energy of the Proton Exchange Membrane Fuel Cell (PEMFC) for residential application situated in the Unit of Applied Research in Renewable Energy in Ghardaïa (southern Algeria) has been made and performances was analysed, we have determine the quantity of electrical and thermal energy generated by the PEMFC. TRNSYS 16 is used to plot initial and final residence temperatures before and after cooling. The results showed the feasibility of using PEMFC for cooling.

Applied Research Note: Influence of dietary fat and crystalline amino acid inclusion on broiler diet formulation and subsequent pellet quality

Applied Research Note: Influence of dietary fat and crystalline amino acid inclusion on broiler diet formulation and subsequent pellet quality

Neurosciences in Architecture: Applied Research and its Potential in Architectural Design

Neurosciences in Architecture: Applied Research and its Potential in Architectural Design

New approaches and technical considerations in detecting outlier measurements and trajectories in longitudinal children growth data

BackgroundGrowth studies rely on longitudinal measurements, typically represented as trajectories. However, anthropometry is prone to errors that can generate outliers. While various methods are available for detecting outlier measurements, a gold standard has yet to be identified, and there is no established method for outlying trajectories. Thus, outlier types and their effects on growth pattern detection still need to be investigated. This work aimed to assess the performance of six methods at detecting different types of outliers, propose two novel methods for outlier trajectory detection and evaluate how outliers affect growth pattern detection.MethodsWe included 393 healthy infants from The Applied Research Group for Kids (TARGet Kids!) cohort and 1651 children with severe malnutrition from the co-trimoxazole prophylaxis clinical trial. We injected outliers of three types and six intensities and applied four outlier detection methods for measurements (model-based and World Health Organization cut-offs-based) and two for trajectories. We also assessed growth pattern detection before and after outlier injection using time series clustering and latent class mixed models. Error type, intensity, and population affected method performance.ResultsModel-based outlier detection methods performed best for measurements with precision between 5.72-99.89%, especially for low and moderate error intensities. The clustering-based outlier trajectory method had high precision of 14.93-99.12%. Combining methods improved the detection rate to 21.82% in outlier measurements. Finally, when comparing growth groups with and without outliers, the outliers were shown to alter group membership by 57.9 -79.04%.ConclusionsWorld Health Organization cut-off-based techniques were shown to perform well in few very particular cases (extreme errors of high intensity), while model-based techniques performed well, especially for moderate errors of low intensity. Clustering-based outlier trajectory detection performed exceptionally well across all types and intensities of errors, indicating a potential strategic change in how outliers in growth data are viewed. Finally, the importance of detecting outliers was shown, given its impact on children growth studies, as demonstrated by comparing results of growth group detection.

The challenge of innovation and the nature of jobs under the pandemic-19

This article aims to discuss the impact of technological advances on the nature of work in Brazil, under three main aspects: a) the context of innovation processes; b) the introduction of industry 4.0 concept; c) the Covid-19 pandemic. Technological changes, both in the innovation process in the company, and in the advent of industry 4.0, were, to a certain extent, hastened by the emergence of the Covid-19 pandemic. In this sense, the analysis carried out by this study was based on data provided in surveys carried out by IBGE (Brazilian Institute of Geography and Statistics) and by IPEA (Institute of Applied Research). The findings of this research show two main aspects: a) workers in certain areas need to improve new skills, especially with regard to cognitive flexibility and emotional intelligence to support work in this new era of digitalization associated with remote work caused by the pandemic; b) companies will have to rethink their infrastructure and invest in new digital technologies to remain competitive and be able to operate with a portion of their employees working in the home office productively. In addition, they will have the flexibility to manage people in these conditions and obtain the best results from them.

Green-blue space exposure changes and impact on individual-level well-being and mental health: a population-wide dynamic longitudinal panel study with linked survey data.

Cross-sectional evidence suggests that living near green and blue spaces benefits mental health; longitudinal evidence is limited. To quantify the impact of changes in green and blue spaces on common mental health disorders, well-being and health service use. A retrospective, dynamic longitudinal panel study. Wales, UK. An e-cohort comprising 99,682,902 observations of 2,801,483 adults (≥ 16 years) registered with a general practice in Wales (2008-2019). A 5312-strong 'National Survey for Wales (NSW) subgroup' was surveyed on well-being and visits to green and blue spaces. Common mental health disorders, general practice records; subjective well-being, Warwick-Edinburgh Mental Well-being Scale. Common mental health disorder and use of general practice services were extracted quarterly from the Welsh Longitudinal General Practice Dataset. Annual ambient greenness exposure, enhanced vegetation index and access to green and blue spaces (2018) from planning and satellite data. Data were linked within the Secure Anonymised Information Linkage Databank. Multilevel regression models examined associations between exposure to green and blue spaces and common mental health disorders and use of general practice. For the National Survey for Wales subgroup, generalised linear models examined associations between exposure to green and blue spaces and subjective well-being and common mental health disorders. Our longitudinal analyses found no evidence that changes in green and blue spaces through time impacted on common mental health disorders. However, time-aggregated exposure to green and blue spaces contrasting differences between people were associated with subsequent common mental health disorders. Similarly, our cross-sectional findings add to growing evidence that residential green and blue spaces and visits are associated with well-being benefits: Greater ambient greenness (+ 1 enhanced vegetation index) was associated with lower likelihood of subsequently seeking care for a common mental health disorder [adjusted odds ratio (AOR) 0.80, 95% confidence interval, (CI) 0.80 to 0.81] and with well-being with a U-shaped relationship [Warwick-Edinburgh Mental Well-being Scale; enhanced vegetation index beta (adjusted) -10.15, 95% CI -17.13 to -3.17; EVI2 beta (quadratic term; adj.) 12.49, 95% CI 3.02 to 21.97]. Those who used green and blue spaces for leisure reported better well-being, with diminishing extra benefit with increasing time (Warwick-Edinburgh Mental Well-being Scale: time outdoors (hours) beta 0.88, 95% CI 0.53 to 1.24, time outdoors2 beta -0.06, 95% CI -0.11 to -0.01) and had 4% lower odds of seeking help for common mental health disorders (AOR 0.96, 95% CI 0.93 to 0.99). Those in urban areas benefited most from greater access to green and blue spaces (AOR 0.89, 95% CI 0.89 to 0.89). Those in material deprivation benefited most from leisure time outdoors (until approximately four hours per week; Warwick-Edinburgh Mental Well-being Scale: time outdoors × in material deprivation: 1.41, 95% CI 0.39 to 2.43; time outdoors2 × in material deprivation -0.18, 95% CI -0.33 to -0.04) although well-being remained generally lower. Longitudinal analyses were restricted by high baseline levels and limited temporal variation in ambient greenness in Wales. Changes in access to green and blue spaces could not be captured annually due to technical issues with national-level planning datasets. Further analyses could investigate mental health impacts in population subgroups potentially most sensitive to local changes in access to specific types of green and blue spaces. Deriving green and blue spaces changes from planning data is needed to overcome temporal uncertainties. This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (Project number 16/07/07) and will be published in full in Public Health Research; Vol. 11, No. 10. Sarah Rodgers is part-funded by the NIHR Applied Research Collaboration North West Coast.

A Qualitative Multi-Methods Research Protocol: Applied Research Ethics in the Middle East North Africa Region

In generating new knowledge in all fields related to human subjects research, research ethics is key. The Middle East and North Africa (MENA) region has witnessed a remarkable increase in research involving human participants, but robust contextually relevant guidelines and local capacity to guide ethical research are lacking. The research protocol presented and discussed here represents the methodology used to assess the landscape of applied research ethics in the region from the narratives of several constituencies in the research process, namely researchers, research ethics committee chairs and directors of research institutions. The study is a three-year multi-phase, multi-method research which involved a sequence of phases starting with a desk review, writing country reports, focus groups, and in-depth interviews, followed by a regional survey. The lead research team worked with country teams in 6 sites in the MENA region to conduct the empirical research which will be described in detail and reflected on for rigor and challenges.

Individualised variable-interval risk-based screening in diabetic retinopathy: the ISDR research programme including RCT

Individualised variable-interval risk-based screening in diabetic retinopathy: the ISDR research programme including RCT

Opportunities for high-energy neutron- and deuteron-induced measurements for fusion technology at the Soreq applied research accelerator facility (SARAF)

The Soreq Applied Research Accelerator Facility (SARAF) will be based on a 40 MeV, 5 mA CW (continuous wave) proton/deuteron superconducting linear accelerator, currently under construction at Soreq Nuclear Research Center in Yavne, Israel. It is planned to commence operation during 2025. Experiments at SARAF could provide data on high-energy deuteron- and neutron-induced cross-sections, yields and radiation damage, which are invaluable for the design and operation of the International Fusion Materials Irradiation Facility-DEMO-Oriented NEutron Source (IFMIF-DONES), and fusion technology in general. Pulsed beams (∼1 nsec) of variable energy deuterons will irradiate a lithium target and generate pulsed neutron beams with energy up to ∼55 MeV, which will be used to measure energy-dependent neutron-induced differential cross-sections, utilizing time of flight techniques. Impinging continuous wave (CW) 40 MeV deuteron beams on a unique gallium-indium (GaIn) liquid-jet target, will generate a neutron rate of more than 1 × 1015 n/sec, with energies up to ∼45 MeV. We plan to use this high rate to measure integral neutron-induced reaction yields of all channels simultaneously, employing an original novel method that will identify the reaction-produced nuclei via accurate mass measurement. The neutron-energy dependence of the yields could be deduced by combining measurements at various deuteron energies. The measured cross-sections and yields at SARAF may predict the activation characteristics of construction materials of IFMIF-DONES and future fusion reactors. The deuteron beams will also be used directly to measure cross-sections via in-beam and offline methods. The high neutron and deuteron rates will extend SARAF’s reach to rare materials. The deuteron beam power density on the liquid GaIn target will be 100 kW/cm2(similar to IFMIF-DONES) on a 2 cm2spot. The resulting neutron flux on small secondary samples will be in the 1013 n/cm2/s level, only an order of magnitude less than IFMIF-DONES. Therefore, SARAF may serve as a pilot facility for fusion-related radiation damage studies, providing important information towards the design of IFMIF-DONES.

Radiographic pneumonia in young febrile infants presenting to the emergency department: secondary analysis of a prospective cohort study

ObjectiveThe lack of evidence-based criteria to guide chest radiograph (CXR) use in young febrile infants results in variation in its use with resultant suboptimal quality of care. We sought to...

Centering Public Perceptions on Translating AI Into Clinical Practice: Patient and Public Involvement and Engagement Consultation Focus Group Study.

Artificial intelligence (AI) is widely considered to be the new technical advancement capable of a large-scale modernization of health care. Considering AI's potential impact on the clinician-patient relationship, health care provision, and health care systems more widely, patients and the wider public should be a part of the development, implementation, and embedding of AI applications in health care. Failing to establish patient and public engagement and involvement (PPIE) can limit AI's impact. This study aims to (1) understand patients' and the public's perceived benefits and challenges for AI and (2) clarify how to best conduct PPIE in projects on translating AI into clinical practice, given public perceptions of AI. We conducted this qualitative PPIE focus-group consultation in the United Kingdom. A total of 17 public collaborators representing 7 National Institute of Health and Care Research Applied Research Collaborations across England participated in 1 of 3 web-based semistructured focus group discussions. We explored public collaborators' understandings, experiences, and perceptions of AI applications in health care. Transcripts were coanalyzed iteratively with 2 public coauthors using thematic analysis. We identified 3 primary deductive themes with 7 corresponding inductive subthemes. Primary theme 1, advantages of implementing AI in health care, had 2 subthemes: system improvements and improve quality of patient care and shared decision-making. Primary theme 2, challenges of implementing AI in health care, had 3 subthemes: challenges with security, bias, and access; public misunderstanding of AI; and lack of human touch in care and decision-making. Primary theme 3, recommendations on PPIE for AI in health care, had 2 subthemes: experience, empowerment, and raising awareness; and acknowledging and supporting diversity in PPIE. Patients and the public can bring unique perspectives on the development, implementation, and embedding of AI in health care. Early PPIE is therefore crucial not only to safeguard patients but also to increase the chances of acceptance of AI by the public and the impact AI can make in terms of outcomes.

Applied research on cultural symbols in landscape architectural design

Applied research on cultural symbols in landscape architectural design

Performance Model Identification of the General Electric CF34-8C5B1 Turbofan Using Neural Networks

This paper presents a methodology developed at the Laboratory of Applied Research in Active Controls, Avionics, and Aeroservoelasticity to identify a performance model of the CF34-8C5B1 turbofan engine powering the CRJ-700 regional jet aircraft from simulated flight data using artificial neural networks (ANNs). For this purpose, a qualified virtual research simulator was used to conduct different types of flight tests and to collect engine data under a wide range of operating conditions. The collected data were then used to create a comprehensive database for the training of the ANN model. This process was performed using the Bayesian regularization algorithm available in the MATLAB Neural Networks Toolbox, followed by a study to identify the optimal network architecture, namely, the number of layers and the number of neurons. The validation of the methodology was accomplished by comparing the model predictions with a set of flight data collected with the flight simulator for different flight conditions and flight regimes including takeoff, climb, cruise, and descent. The results showed that the model was able to predict the engine performance in terms of fan speed, core speed, inlet turbine temperature, net thrust, and fuel flow with less than 5% relative error.

Knowledge Discovery and Data Mining in Medical Sciences, a Review of the Requirements for Applied Researches

Knowledge Discovery and Data Mining in Medical Sciences, a Review of the Requirements for Applied Researches