bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Multimorbidity and Chronic Diseases in citizens of the Métis Nation of Ontario
Authors: Tsui Noel , Cripps Shelley , Simms Abigail , Tjong Gabriel , Golding Haley , Edwards Sarah
Published: September 2024

Objective and ApproachPopulation-based analyses of Métis health in Canada are limited. The Métis are a distinct Indigenous people with both First Nation and Euro-Settler ancestry. This study aimed to examine multimorbidity in the Métis Nation of Ontario (MNO) citizens from 2009 to 2019. Registered MNO citizens were linked to Ontario’s administrative health data. An existing data algorithm identified individuals with multimorbidity (2+ chronic conditions) among MNO citizens and the Ontario population aged 18+. Annual prevalence rates of multimorbidity were calculated and rates in the latest year were compared across income quintiles, age, and sex.
Results & ConclusionThe prevalence of multimorbidity increased in MNO citizens from 49.2 per 100 (CI: 48.1-50.2) in 2009 to 61.0 per 100 (CI: 59.9-62.1) in 2018. A consistently higher prevalence rate was seen in MNO citizens compared to non-MNO citizens across the entire period. Female MNO citizens had a higher prevalence of multimorbidity compared to males. The prevalence of multimorbidity increased with age in MNO citizens from 40.5 per 100 (CI: 39.1-41.8) in those aged 18 to 44 years up to 91.6 per 100 (CI: 88.4-98.0) in those aged 65 years and older. An income gradient was evident with MNO citizens in the highest income quintile having the lowest prevalence of multimorbidity (57.1 per 100) compared to those in the lowest income quintile (66.3 per 100). 
ImplicationsUnderstanding the burden of multimorbidity in MNO citizens is essential for the MNO to guide program and policy planning, as well as support decision-making related to resource allocation.
Local authority variation in special educational needs provision at the start of primary school: observational study of preterm children born in England, 2003-2013
Authors: Lewis Kate , Nguyen Vincent , De Stavola Bianca , Dearden Lorraine
Published: September 2024

Objective and ApproachWe explored variation in special educational needs (SEN) provision between local authorities (LAs) in England by focussing on children born preterm (24-<37 weeks gestation). We used linked individual-level state-funded hospital and school records from the ECHILD database, alongside publicly available school-level records. LA of child’s residential address (n=150) and recording of SEN provision (split into SEN support and education, health and care plans, EHCPs) were captured at the January school census in year one, when pupils were five/six years old. We fitted multi-level logistic regression models to the child-level records that included a-priori selected child- and LA-level characteristics.
ResultsOur population included 226,419 children (45.4% female ; 10.6%  with a congenital anomaly) born between 2003-2013 and attending a state-funded primary school. Across LAs, the median prevalence of SEN support and EHCPs recorded in year one was 18.4% (interquartile range 16.4%-20.4%) and 4.2% (3.5%-4.8%),  respectively. In the SEN support vs. no SEN provision model, there was very low correlation among children from the same LA (intraclass correlation coefficient (ICC)=0.006 )). There was higher correlation in the EHCP vs. no SEN provision model (ICC=0.032).  Of the LA-level characteristics, the percentage of children eligible for free school meals had the greatest impact on the ICC values (reduction of 26.7% in the EHCP model).
ConclusionsLess than 1% of the variation in SEN support and approximately 3% of the variation in EHCPs was explained at the LA level. We will extend these models to consider variation at the school level.
Free Text Analysis: Identification of adverse drug events in clinical notes
Authors: Katz Alan , Dhankar Abhishek , Leong Christine , Hamad Amani , Singer Alex
Published: September 2024

ObjectiveTo explore the prevalence of adverse drug events (ADE) leading to drug changes using Artificial Intelligence (AI) based free text analysis of primary care encounter notes .  
ApproachWe used electronic medical record l encounter notes linked to population-based drug dispensation records. Dispensation records were used to identify drug switching to another agent in the same therapeutic class, which could suggest an undesirable side-effect requiring discontinuation of the drug. We annotated clinical notes by identifying ADEs after retrieving the last encounter note written for that patient on or before the identified date.  We ran different AI models, including BERT and Large Language Models (LLMs), to identify ADEs.
ResultsWe annotated 1085 notes with 362 ADEs. These were used to train BERT models (precision or PPV: 0.584 ) and prompt-based LLM (0.563) but with improved sensitivity (0.725) and specificity (0.739) .
ConclusionsIdentifying ADEs requires deep medical knowledge and simple Natural Language Processing models trying to identify ADEs only on the basis of language of encounter notes was not successful based on the BERT model performance. Prompt based models have deep knowledge but were trained with the objective of producing grammatically correct, coherent sentences, not with the medical knowledge required. LLMs also require significant computational power.
ImplicationsWhile AI does have significant potential to advance our capacity for complex analytic tasks the current LLMs are not yet able to adequately identify ADEs in a corpus of electronic clinical notes.
Linking for Impact: Enhancing Linked Data Infrastructure to Meet Clinical Trials Sector Needs
Authors: Bailey Rowena , Davies Jo , Pedrick-Case Rebecca , Mizen Amy , Johnson Rhodri , Fry Richard , Griffiths Lucy
Published: September 2024

BackgroundAustralia possesses valuable population health data, yet its potential for advancing medical product development remains largely untapped. Transformative growth in the use of linked data in clinical trials will support Australia’s therapeutic development sector to be more responsive in the development of new therapeutics and the monitoring and surveillance of their safety and effectiveness.
MethodsWe conducted interviews with clinical trialists and data linkage experts to understand the current state and awareness of linked data within the clinical trials sector, identify existing pain points in the linkage process, and explore opportunities for improving visibility and access for the clinical trials sector.  Researchers represented all stages of the medical product development pipeline and had a diverse range of experience with linked data.
ResultsInterviews revealed numerous barriers hindering the clinical trials sector from effectively using linked data, limiting its impact. Barriers included a lack of awareness, the complexity of the application and approval process, and lengthy delays in accessing data.
Participants readily recognised several ways that linkage of real-world data could be applied to their work in clinical trials, with pre-recruitment data, measurements of primary and secondary endpoints, and health economic analysis being the most consistently noted use cases.
ConclusionTo optimise the use of linked data to support clinical trials and medical product development in Australia, increased awareness among the therapeutic development sector regarding available real-world data and its potential is needed urgently. Lowering the barriers to accessing linked data will enhance health services and patient outcomes across Australia.
Policy-driven multidisciplinary primary care after stroke or Transient Ischaemic Attack (TIA) improves survival – an observational target trial evaluation involving linked registry data
Authors: Andrew Nadine , Ung David , Kilkenny Monique , Olaiya Muideen , Dalli Lachlan , Churilov Leonid , Collyer Taya , Snowdon David , Kim Joosup , Srikanth Velandai , Cadilhac Dominique , Sundararajan Vijaya , Thrift Amanda , Nelson Mark , Lannin Natasha
Published: September 2024

ObjectiveTo determine the effectiveness of government policies supporting coordinated multidisciplinary primary care (MDC) in improving long-term survival following stroke or Transient Ischaemic Attack (TIA). 
ApproachWe used the target trial framework for observational data to assess the average population effect of primary care MDC policies. The cohort comprised patients from the Australian Stroke Clinical Registry (January 2012-June 2015) linked with (i) Australian Medicare claims to define exposures (MDC claims in the 6-18 months post-stroke); (ii) hospital, pharmaceutical and aged care datasets for additional covariates; (iii) National Death Registry for survival outcomes (19-30 months post-stroke). Level of impairment was classified by latent class analysis using EQ-5D-3L questionnaire data obtained 90-180 days post-stroke. Multilevel survival analysis with inverse probability treatment weights was applied.
ResultsAmong 7,255 people with stroke (42% female, median age 71 years, 24% TIA, level of impairment: 39% minimal, 32% moderate, 29% severe), 29% had a Medicare claim for MDC (23% minimal, 31% moderate, 39% severe). Mortality was reduced in those receiving a claim (vs non-receipt) in the minimal (adjusted Hazard Ratio (aHR): 0.50, 95%CI:0.27, 0.91) and severe (aHR: 0.65, 95%CI:0.46, 0.91) impairment groups, but not the moderate impairment group (aHR: 1.31, 95%CI:0.86, 1.99). Group differences in allied health services claimed during MDC were observed: secondary prevention (14% minimal vs 10% severe impairment), rehabilitation (21% minimal vs 25% severe impairment). 
ImplicationsDrawing causal inferences from linked observational data demonstrated the population effectiveness of primary care MDC policies, in improving survival following stroke/TIA, with variation by impairment class.
Tailored Strategies for Mental Health Support: Distinctions-Based Approaches for the Red River Métis Community
Authors: Nault Kyler , Deptuch Megan , Poitras Colton , Rodway Lisa , Chartrand Frances , Kloss Olena
Published: September 2024

Objective and ApproachThe study investigates attitudes of Red River Métis (RRM) Citizens towards existing mental health services to assess satisfaction levels and enhance support and accessibility. Employing a Community-Based Participatory Research and Collective Consensual Data Analytic Procedure (CBPR/CCDAP) framework, a survey was conducted during health consultations in 2022 and 2023. It explored participant perspectives on existing programming, service availability, and future needs. Analysis of participant responses, stratified by demographics, offers insights into mental health attitudes among the RRM Community.
ResultsA total of 144 RRM Citizens participated in the survey, reporting "addiction," "trauma," and "stress" as primary causes of mental health issues. Presently, only 20% (n = 29) utilize mental health services, with over 40% (n = 58) expressing dissatisfaction with available services. Moreover, more than 90% (n = 130) of Citizens emphasized “an urgent need for additional mental health services tailored to the RRM Community”. Common barriers to accessing mental health services included lack of awareness and financial constraints.
ConclusionThe study highlights RRM Citizens’ dissatisfaction with existing services and inadequate awareness of available mental health services and their protocols, presenting significant barriers to accessing services. Further investigations are warranted to determine whether these challenges stem from communication discrepancies, service inadequacies, or a combination of both factors.
ImplicationsFindings from the study inform the development of distinctions-based mental health services for the Red River Métis Community, enhancing access, engagement, and policy development to address mental health disparities.
Combining cohorts of prospectively collected and linked data to improve health after release from prison
Authors: Legge Matthew , Pearce Lindsay , Cummings Craig , Curtis Michael , Yee Natalia , Dean Kimberlie , Preen David , Stoove Mark , Kinner Stuart
Published: September 2024

BackgroundWhile people who experience incarceration have remarkably poor health profiles, undertaking research to inform evidence-based responses is complicated by difficulties of recruiting people in prison; high rates of socioeconomic marginalisation, study attrition; and legislative and financial barriers to linked data research. There are many advantages to pooling data from multiple studies involving people who experience incarceration, including greater statistical power and geographic and participant heterogeneity. However, there are also challenges that need to be addressed.
MethodsWe combined four prospective cohort studies of adults released from prisons in four Australian states. Pre-release interviews, and validated screening assessments, were linked to primary care, medicine dispensing, hospital, alcohol and other drug treatment services, ambulatory mental health, ambulance, corrective services, and death records. Data were harmonised by team members reviewing variable definitions and categories within subject domains.
ResultsThe combined cohort consists of 4,232 adults, including 1,544 Indigenous people and 905 women, with a median age of 31 years. Data linkage will enable a median of 9.3 years of prospective follow-up after release from incarceration. Differences in data structures, coding systems between and within datasets, changes over time, and grouping of records belonging to the same event were also addressed.
ConclusionThis combined multi-site cohort study is an example of a complex, policy-oriented data linkage project. It was developed to underpin evidence-based, culturally appropriate interventions, health policy and service development for people who were incarcerated. This presentation will discuss the processes and pitfalls experienced while building a multi-sectoral, multi-jurisdictional data linkage project.
Mortality in adolescents receiving special education and social care provision: A population-level cohort study in England
Authors: Ward Isobel , Jay Matthew , Ward Joseph , Gilbert Ruth , Zylbersztejn Ania
Published: September 2024

BackgroundOver a third of children in England receive either special educational need (SEN) provision/children’s social care (CSC) support at least once during school. We aimed to describe all-cause and adversity-related mortality for adolescents who received SEN or CSC provision in England. 
ApproachWe used linked data from hospital admissions, death registrations, social care and education in the ECHILD database to follow all adolescents in state schools from age 13-years between 2009/10-2014/15 until death or 2020. Adolescents were grouped according to provision ever recorded before age 14: None, SEN only, CSC only or CSC and SEN. We estimated all-cause and adversity-related mortality in children with SEN/CSC/both compared to peers. 
ResultsThe cohort comprised 3,381,502 children (51% boys), of whom 30.1% (n=1,017,670, 62% boys) received SEN only, 4.2% (n=143,430, 36% boys) received CSC only and 8.7% (n=293,310, 57% boys) received SEN and CSC. In ten-year follow up, 6,590 deaths occurred (66% in boys). Mortality rates were 5.4 times higher for adolescents receiving both SEN and CSC, 2.4 times higher for CSC only, and 1.7 times higher for SEN only compared to peers. Rates of adversity-related deaths were highest for boys receiving SEN and CSC compared to peers.
Conclusions & Implications8-in-1000 adolescents who received both SEN and CSC before age 13 died by age 23 years, far more often than their peers. Policies need to consider support for young people with additional educational and social care needs as they leave school and transition to adulthood.
Public informed training: Developing a curriculum for trialists using health systems data
Authors: Lugg-Widger Fiona , Trubey Rob , Robling Mike , Mafham Marion , Sydes Matthew , Shepherd Victoria , Cannings-John Rebecca , Hood Kerenza , Ahmed Nagheen , Islam Sadman , Rawlinson Sarah
Published: September 2024

IntroductionResearchers are increasingly using health systems data to support clinical trials. A recent Delphi study identified a number of remaining challenges across the trial lifecycle and highlighted opportunities to address them through the development of training resources.  
Objective and ApproachWe present a programme of work to identify, facilitate and optimise emerging practices for using health systems data in trials, informed by subject matter experts and steered by public input, to begin addressing the ongoing challenges for trial teams. 
ResultsDirectly addressing a key identified priority for building public trust, we co-developed a series of freely-available online training videos on how public involvement and engagement can impact across the trial lifecycle plus practical tips for such activities. This curriculum was informed by public members who then featured in the training videos.  We broadened the training focus to align with trials community needs, whilst retaining the public co-production element. A diverse and purposive group of applicants were selected to contribute to the ongoing work of the HDR UK Transforming Data for Trials workstream. Our presentation reviews how models of involvement have informed our approach including reflections from our public members on what has worked well and what can be improved. We will reflect on the intersection of public involvement in trials and public involvement in healthcare/administrative systems data research. 
Conclusions & ImplicationsCo-development with a diverse public group ensures all current and future training resources developed reflect a diversity of views, increasing the quality and credibility of materials.
Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people across four nations in the UK
Authors: Aldridge Sarah J , Agrawal Utkarsh , Murphy Siobhán , Millington Tristan , Akbari Ashley , Almaghrabi Fatima , Anand Sneha N , Bedston Stuart , Goudie Rosalind , Griffiths Rowena , Joy Mark , Lowthian Emily , De Lusignan Simon , Patterson Lynsey , Robertson Chris , Rudan Igor , Bradley Declan T , Lyons Ronan , Sheikh Aziz , Owen Rhiannon K
Published: September 2024

Background and ObjectivesSARS-CoV-2 infection in children and young people (CYP) can lead to life threatening conditions including COVID-19, transmission to more vulnerable individuals, or even long COVID. Vaccination against COVID-19 reduces the chance of infection and transmission of the virus, but vaccine uptake in the UK has been shown to decrease with age.
ApproachWe undertook a multistate-model approach to estimate hazard ratios on national cohorts constructed from linked health and administrative data, adjusting for several demographic factors. The models were applied to 3,433,483 CYP aged 5-17 years between 4th August 2021 and 31st May 2022. The results were combined in a random effects meta-analysis.
ResultsUptake of the first COVID-19 vaccine in CYP was lower compared to older age groups in the UK, and diminished further with subsequent doses (34%, 20% and 2% for 1st, 2nd, and booster dose respectively). Age of the CYP and vaccination status of the adults in the household were identified as important risk factors. For example, 5-11-year-olds were less likely to receive their first vaccine compared to 16-17-year-olds (adjusted Hazard Ratio [aHR]: 0.10 (95%CI: 0.06-0.19), and CYP in unvaccinated households were less likely to receive their first vaccine compared to partially vaccinated households (aHR: 0.19, 95%CI 0.13-0.29).
Conclusions and Implications Our work highlights the need for targeted strategies to increase COVID-19 vaccine acceptance and uptake among CYP, especially considering the influence of parental consent and household factors. Further research could help identify risk factors in household types to investigate more direct associations, which may be influenced by factors such as living with vulnerable people, familial structure, or deprivation.
Wellbeing and retainment of healthcare workers in Wales from 2020 to 2023
Authors: Bedston Stuart , Abbasizanjani Hoda , Robinson Lucy , Curds Matthew , Akbari Ashley
Published: September 2024

ObjectivesThe COVID-19 pandemic greatly impacted the wellbeing of healthcare workers (HCWs) due to stress, longer hours, and risks of infection during an uncertain time. Post-pandemic, we need to understand the extent of the lasting impacts on wellbeing and staff retainment.
ApproachUsing linked administrative health and workforce records within the SAIL Databank, we conducted a cohort study of HCWs employed directly by the National Health Service in Wales between 2020 and 2023. We investigated trends in HCW turnover by fiscal quarter and staff group and the prevalence of occupational health issues per primary care records, including authorised sick leave. We analysed time until leaving the profession using Cox regression incorporating workforce, demographic and health characteristics.
ResultsFrom January 2020 to December 2023, HCW employment grew from 101,600 to 121,970 (+20.0%). During this period, 34,760 people left the profession, averaging a turnover of 4.4% per fiscal quarter. Equally, an average of 1.9% of HCWs were diagnosed with a mental health issue, and 17.9% received a related prescription per fiscal quarter. We present further results highlighting how staff turnover has increased over time and differed across staff groups. We also show the extent to which leaving the profession is associated with workforce, demographic and health characteristics.
ConclusionThe rate of mental health issues and increases in turnover from the profession highlight the need for additional support. Healthcare systems need to prioritise the welfare of their workforce to ensure sustained resilience and quality of care.
Investigating long-term health outcomes in high-level rugby union players using linked administrative data
Authors: D'Souza Stephanie , Milne Barry J. , Anns Francesca , Quarrie Kenneth L.
Published: September 2024

Objective and ApproachThe Kumanu Tāngata study investigates long-term health outcomes in male high-level rugby union players in New Zealand using the Integrated Data Infrastructure (IDI), a comprehensive de-identified whole-population administrative research database. A historical register containing players active between 1950-2000 was linked to the IDI. Rugby players (n=12,861) were compared to general population males (n=2,385,690), matched by age, ethnicity, and birthplace, on neurodegenerative disease outcomes from health records available between 1988-2018. Cox proportional hazards models were conducted.
ResultsRugby players exhibited a higher neurodegenerative disease incidence (4.7%) than the general population (3.9%). Players had an increased risk of any neurodegenerative disease (1.17 [95% CI 1.08–1.27]), Alzheimer's disease (1.42 [95% CI 1.22–1.66]), and other dementias (1.16 [95% CI 1.05–1.27]). An increased risk of any neurodegenerative disease was observed for professional- or international-level play (HR 1.51 [95% CI 1.04–2.18]), six or more years of play (HR 1.32 [95% CI 1.15–1.50], and a backline playing position (HR 1.30 [95% CI 1.17–1.45]). 
ConclusionsThe study indicates a small-to-moderate increased risk of neurodegenerative diseases for high-level rugby players in New Zealand when compared to the general population, with variations observed across play duration, level and position. Future research will examine additional health outcomes, including mortality, musculoskeletal conditions, and mental health disorders.
ImplicationsThis large-scale linkage study allows for a comprehensive examination of long-term health outcomes and enhanced statistical power than previous research. Findings have the potential to influence health policies and athlete care strategies in contact sports.
Expanding opportunities in health data: Enhancing research by facilitating linkage of Ontario’s population-level health administrative data with data from patient support programs (PSPs)
Authors: Arnold Keresa , Ishiguro Lisa , Ho Minnie , Skvirisky Dina , Retnakanthan Jeruby , Etches Jacob , Mondor Luke , Saskin Saskin , Victor Charles
Published: September 2024

ObjectivesPatient Support Programs (PSPs) provide real-world evidence on short-term outcomes and drug adherence for specialty care. These data are collected directly from patients by pharmaceutical companies. Data linkage is facilitated by a publicly-funded health research institute which houses population-based, individual-level health administrative data for 14 million Ontario residents in Canada since 1992. Linkage provides a more comprehensive and transparent view of patients’ pathways and care.
ApproachIndustry-funded research conducted through the data & analytic service must align with the institute’s mission, vision and values, and demonstrate a clear public benefit. For transparency, and to support broader public benefit and research access, final deliverables and analytic plans are posted on the institute’s website. Privacy impact assessments are conducted to ensure ethics approvals, consent and data sharing agreements are established, prior to data importation. To safeguard privacy, designated data covenantors encrypt and link the PSP data with in-house data holdings. Analyses are performed by senior analytic staff, providing researchers with summary-level reports.
ResultsSince 2016, the institute has worked with organizations to link data for research, including PSP data on thousands of patients, enabling crucial insight into treatment patterns, drug adherence, costs and long-term outcomes. 
ConclusionLinkage of privately-owned PSP data with administrative health data at the institute, provides opportunities to identify gaps in care and improve quality of research. Data challenges around bias, transparency, completeness, and comprehensiveness are minimized.
ImplicationsResults provide decision-makers and healthcare professionals with a trusted and comprehensive understanding of patient care pathways to improve health outcomes.
AD|ARC (Administrative Data Agri-Research Collection): Linking Individual, Household and Farm Business Data for Sociodemographic Research on Farming Households
Authors: Morrison-Rees Sian , Madden Laura , Curds Matthew , Caskie Paul , Loftus Rachael
Published: September 2024

ObjectiveTo understand the socio-demographic characteristics and structure of farming households in Wales who receive subsidies compared to non-farming rural households.
Approach We utilised the AD|ARC dataset, a comprehensive resource we created within the SAIL databank by linking de-identified records of farms receiving farming subsidies in Wales with socio-demographic information from the Census 2011. A control group was created by matching each farming household with up to three households in the 2011 Census from a similar geographical area that did not contain a farmer or household member in receipt of farming subsidies. We used Census 2011 variables to compare household size, family structure and age for 18,135 farming households with a control group of 53,365 rural non-farming households.
Results We found little difference between the age and gender distribution between cohorts, however we found significant differences in the household structure. Farming households had a larger average size compared to non-farming households. Single-occupancy farming households had a significantly higher proportion of males, farming households were more likely to have couples with children and a higher percentage of these couples were married compared to non-farming households. 
Implications The agriculture sector in Wales is facing a range of challenges linked to social, economic, and environmental sustainability as it establishes a new direction after UK withdrawal from the EU. Understanding the sociodemographic characteristics of farming communities is essential for developing effective policies and interventions that address the specific needs and challenges faced by these groups.
Creating an Integrated System of Data and Statistics on Household Income, Consumption, and Wealth
Authors: Johnson David , Smeeding Timothy
Published: September 2024

The nation's disparate federal statistics makes it difficult to accurately measure income and wealth inequality and other aspects of economic well-being for the nation's households and families. This report provides the recommendations from a panel appointed by The Committee on National Statistics (CNSTAT) of the National Academies of Sciences, Engineering, and Medicine. The report reviews the major income, consumption, and wealth statistics currently produced by U.S. statistical agencies, provides guidance for modernizing and integrating the information to better inform policy and research, and builds on the current effort at CNSTAT to create a 21st Century Data Infrastructure to use blended data from multiple sources. In addition to providing guidance on the appropriate definitions of household, family, and individual income, consumption, and wealth, and variations in definitions that would be useful for particular purposes, the report provides suggestions for pathways forward using multiple data sources to construct a data infrastructure for income, consumption and wealth for households. The report highlights new statistics that help in measuring the disparities in income, consumption and wealth and the changes over time in both levels and inequalities, always stressing that the disparities occur both across socio-demographic characteristics and geography. The report highlights the potential for blending multiple data sources and modeling across data sources, including surveys, tax records, state and federal administrative records, and commercial data, and documents the legal and administrative barriers to creating integrated, high-quality estimates and a data infrastructure for researchers to evaluate the impacts of public policy.
IMPACTOS SOCIAIS E AMBIENTAIS NA IMPLANTAÇÃO DE PARQUES EÓLICOS: UMA ANÁLISE CRÍTICA
Authors: Barros Antônio Soares , Luna Raimundo Pereira , Andrade Hellen Betsaida Filipe , Filgueira Ketilley Fernanda Callou , Silva Yonar Cavalcante da , Maia Everson de Araújo
Published: September 2024

Este estudo teve como objetivo investigar os impactos sociais e ambientais associados à instalação de parques eólicos, proporcionando uma análise abrangente da literatura existente. A pesquisa examinou as complexas interações entre o desenvolvimento desses projetos e o meio ambiente, bem como os efeitos nas comunidades locais. Através de uma análise detalhada, foram identificados desafios significativos enfrentados durante a implementação desses empreendimentos, como a necessidade de equilibrar a preservação ambiental com a expansão da capacidade energética. No entanto, também foram reconhecidas oportunidades para mitigar os impactos adversos, como a adoção de tecnologias mais eficientes e práticas de planejamento mais robustas. Além disso, o estudo destacou o potencial para fomentar um desenvolvimento sustentável ao integrar parques eólicos de maneira mais harmoniosa com as comunidades e ecossistemas locais. Dessa forma, contribui-se para uma compreensão mais profunda dos desafios enfrentados e das oportunidades disponíveis para otimizar a integração de parques eólicos no panorama energético global, promovendo um equilíbrio entre progresso energético e responsabilidade ambiental.
Market Intervention Policy in The Case of Rising Rice Prices in Indonesia From The Perspective of Ibn Taimiyah
Authors: Bella Alif Mujiyana Eka , Rahmawati Lilik , Jim Mahafizur Rahman
Published: September 2024

Rice is an important commodity and is needed by the wider community, its existence is vital as a means to fulfil the needs of life, therefore the Indonesian government's intervention in this commodity is very high. The price of rice in Indonesia continues to rise for many factors. This research employs qualitative methods which is called library research. The result of this study is the increase in rice prices in Indonesia according to Ibn Taymiyyah is entirely caused by market forces. According to Ibn Taymiyyah what is needed therefore is market intervention, instead of price intervention. The market intervention carried out by the Indonesian government is by intensifying the social assistance program, running market operations with the SPHP program, and strengthening the stock of government rice reserves (CBP). Meanwhile, the policy of setting the price ceiling should not be carried out by the government because the market conditions related to this rice commodity run perfectly and there is no market distortion.
Improvement of emotion recognition methods based on neural networks
Authors:   Lviv Polytechnic National University, Lviv, Ukraine, Yaremchenko O. D. , Pukach P. Ya. ,   Lviv Polytechnic National University, Lviv, Ukraine
Published: September 2024

This article analyzes the use of microexpressions – subtle facial movements that are difficult for the human eye to notice, and even more difficult to immediately analyze, even specialists in the field do not always succeed in this perfectly, because their speed is only 1/5 to 1/3 of a second, for assessment of psychological state using artificial intelligence methods. The research is aimed at improving the analysis of micro-mimicry for accurate identification of emotions and psychological state. An overview of implemented technological solutions based on CNN was conducted, and a method for their improvement was found. An experimental test conducted on video recordings of people experiencing various emotions showed the high accuracy of the developed method in recognizing emotions and psychological state. Despite the challenges of the scarcity of microexpression datasets and the subtlety of facial movements, the paper presents a CapsuleNet model for microexpression recognition, builds a system architecture, and conducts testing. By combining three main data sets (SMIC, CASME II and SAMM) into a unified cross-database, the method developed in the work tests the possibility of generalization of the model by different subject characteristics. The performance of CapsuleNet, evaluated by cross-baseline benchmarking and Leave-One-Object-Out validation, significantly outperforms the baseline (LBP-TOP) and other improved of an CNN models. The paper shows that the performance of the developed model, determined by unweighted average recall and F1 scores, outperforms both the LBP-TOP baseline and other state-of-the-art CNN models. In a comprehensive microexpression recognition system. First, we process the data to identify the peak frames in the sequences and isolate the face region in these frames. These processed face images are then moved to CapsuleNet for the classification. The results of the work is to develop and complement methods of emotional artificial intelligence, offering new insights into micromimic assessment of psychological states that affect mental health, human-computer interaction, and social robotics. This technology has potential for development and expansion. This is an additional opportunity for companies that work with people and it is important for them to monitor their productivity, as it is directly related to the psychological state.
Review of disease identification methods based on computed tomography imagery
Authors:   National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Smilianets F. A. , Finogenov O. D. ,   National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”
Published: September 2024

Methods and approaches to computational diagnosis of various pulmonary diseases via automated analysis of chest images performed with computed tomography were reviewed. Google Scholar database was searched with several queries focused on deep learning and machine learning chest computed tomography imagery analysis studies published during or after 2017. A collection of 39 papers was collected after screening the search results. The collection was split by publication date into two separate sets based on the date being prior to or after the start of the COVID-19 pandemic. Information about the size of the dataset used in the study, classification categories present in it, primary classification target, employed approaches and architectures, metrics used to judge the performance, and the values of those metrics were collected for each paper in the set of discovered studies. Full collected data, including the citation, on every paper was provided in two tables respective to their publication date being prior or after COVID-19. Popular methodologies with the best metrics were identified, outlined, and described. The selected methodologies were compared by their accuracies in various papers found during this study. The comparison table of the found accuracies was provided. A best-performing approach was selected based on the found accuracies. As of this review, ResNet, its variations, and the architectures built upon it have the most promising results, with VGG and Xception being close contenders. The complications with reviewing existing studies in the field are outlined, the most important of them being the diversity in the way that dataset size is described, as well as diversity in the metrics employed, making a comparison between many individual papers impossible or at least lowering the quality of such a comparison. Metrics commonly used to measure the performance of machine learning approaches used in the found studies are outlined and described. Further research direction is proposed, with an emphasis on multi-class classification, modularity, and disease progress prediction. This proposition is guided by finding that most of the studies found focus on single class classification. Additionally, almost none of the studies discuss disease progression, and almost all of the studies discuss rigid solutions which are hardly extendable for future diseases and other classification methods.
Prevalence of Multi-Drug Resistant Tuberculosis in the Dominican Republic: A Systematic Literature Review, 2024
Authors: Islam Dr Monirul , Weaver Chaston , Cruz Dr Modesto
Published: September 2024

Objective: This systematic review assessed available published data related to the prevalence of multidrug-resistant tuberculosis (MDR-TB) in the Dominican Republic (DR). The prevalence of MDR-TB in the DR is among the highest in the Americas. To better understand the barriers associated with increasing rates of MDR-TB, a focused effort must be made in the identification of the actual rates of MDR-TB present in the DR. As of 2024, there remains much variability in the limited amount of published data regarding the actual rates of MDR-TB in the DR. Methods: A database search was conducted in Medline via PubMed, Cochrane Library, CINAHL Plus Full Text via EBSCOhost, and Web of Science for manuscripts published through January 2024 using keywords “Multi-Drug-Resistant Tuberculosis” in combination with “Dominican Republic.” In addition, Google Scholar was referenced to capture “grey literature.” Studies published in English estimating the rate of MDR-TB or extensively resistant TB rates were included. The study protocol was registered at PROSPERO (CRD42024529219). Risk of bias was assessed using the Joanna Briggs Institute (JBI) critical appraisal tool for prevalence studies. Results: Sixteen published papers were eligible for full article review. Four of these met the selection criteria for the final analysis. The reported MDR-TB rates ranged from 5% to 15% for new cases and 30% to 44% for previously treated TB cases. Conclusions: The wide variations in the prevalence of MDR-TB may be related to varying methods used for rate calculations. Our findings show limited data from the DR on national MDR-TB rates.
Terveysdatan ja tekoälyn eettiset haasteet: Kriittinen sosio-tekninen näkökulma
Authors: Sahlgren Otto
Published: September 2024

Terveysdatan kerääminen ja hyödyntäminen erityisesti tekoälyn avulla on kasvanut eri alueilla viimeisen vuosikymmenen aikana. Terveysdatan ja sitä prosessoivien tekoälysovellusten käyttöön liittyy juridis-eettisiä riskejä, jotka koskevat esimerkiksi henkilöiden yksityisyyttä ja tietosuojaa, sovellusten läpinäkyvyyttä ja turvallisuutta sekä käytettyjen tietoaineistojen ja mallien vinoumia. Nämä riskit ilmenevät eri tavoin riippuen kunkin tietoaineiston tai tekoälysovelluksen ominaisuuksista sekä käyttötavasta ja -kontekstista, mikä hankaloittaa riskien tunnistamista ja hallintaa. Eettistä riskien- ja vaikutuksenarviointia sekä -hallintaa tulisi lähestyä kokonaisvaltaisesti kriittisestä ja sosio-teknisestä näkökulmasta ja toteuttaa läpi tarkasteltavan tietoaineiston tai tekoälysovelluksen elinkaaren.
Coffee Production Levels among Smallholder Farmers with and without Hanns. R. Neumann Stiftung Interventions in Rungwe and Mbeya Districts
Authors: Ngambila Thadey Samwel , Nyamba Siwel Yohakim , Ntumva Mabebe Erasmus
Published: September 2024

This study examined and compared coffee production levels among smallholder farmers, those involved, and those not involved with Hanns R. Neumann Stiftung (HRNS) interventions since 2006. The study sample was selected using systematic and random sampling techniques, whereby 104 out of 413 respondents were selected from two wards and five villages within the HRNS intervention zone, as well as five villages without HRNS interventions; farmers in both groups being members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, and Ikuti AMCOS. The production levels were then compared for two samples in Mbeya and Rungwe Districts, respectively. Questionnaires, focus group discussions, and key informant interviews were used to collect primary data, which were complemented by secondary data from documentary reviews. Descriptive statistics, including frequencies, percentages, and means, were employed to analyse socio-economic characteristics and coffee production parameters. The study findings revealed that smallholder coffee farmers’ yields increased significantly with HRNS interventions, reaching 248.66 kg/ha, compared to 115.18 kg/ha for coffee farmers outside the HRNS intervention. The findings indicate that HRNS interventions have a positive impact on smallholder coffee farmers who are beneficiaries of the HRNS program. Thus, the findings highlight the critical significance of government assistance in sustaining such programs. The study recommends for sustained Tanzanian government support for HRNS-like interventions, such as the continual provision of quality seedlings, fertilizers, and extension services to enhance coffee production. This study contributes to the theoretical understanding of agricultural interventions by comparing smallholder farmers’ coffee production with and without HRNS interventions. It demonstrates the usefulness of HRNS in increasing yields, emphasizing the significance of focused interventions in coffee production.
IMPROVING PURCHASING DECISIONS THROUGH PERCEIVED FOOD QUALITY: AN SERVICE DOMINANT LOGIC (SDL) APPROACH
Authors: Suwandari Lusi , Rosiana Monica , Avianti Widiya
Published: September 2024

This study aimed to investigate the impact of visual and verbal packaging on purchasing choices by assessing the perceived quality of food. One hundred seventy-five respondents were surveyed, specifically consumers who purchase MSME food goods in Banyumas Regency, including food, beverages, crafts, and other packaged items. This study employs AMOS structural equation modelling to examine the proposed research model. The findings indicate that visual and verbal packaging benefits the perceived quality of food and influences consumers' purchasing choices. The variable of perceived food quality has a beneficial influence on purchase decisions and can operate as a mediator between visual and verbal packaging regarding buying decisions. The model is grounded in the Service's Dominant logic and the consumption value theory. According to this theory, consumer behaviour is influenced by cognitive and hedonic evaluations that stem from consumption experiences. These experiences highlight the active involvement of consumers in creating value during their interactions with products, including visual packaging, verbal packaging, and perceived food quality.
Besoins et priorités des aînés en matière de prescription sociale au Canada : une analyse qualitative
Authors: Yu Cindy , Lail Simran , Allison Sandra , Biswas Srija , Hebert Paul , Hsiung Sonia , Mulligan Kate , Nelson Michelle L. , Saragosa Marianne , Welch Vivian , Card Kiffer G.
Published: September 2024

Introduction

La prescription sociale est une approche holistique et collaborative qui vise à aider les individus à avoir accès aux mesures de soutien et aux services communautaires nécessaires pour combler leurs besoins sociaux non médicaux. Cette étude visait à évaluer les besoins et les priorités des aînés canadiens (55 ans et plus), en portant une attention particulière à l’optimisation des programmes de prescription sociale à l’intention des personnes qui sont systémiquement défavorisées et socialement marginalisées.

Méthodologie

Des groupes de discussion semi-structurés (N = 10 groupes, 43 participants) ont été organisés en ligne sur Zoom avec des participants de l’ensemble du Canada. La transcription des données et l’analyse thématique ont été réalisées à l’aide du logiciel NVivo. Les analyses s’appuient sur la théorie de l’autodétermination.

Résultats

D’après nos résultats, les aînés souhaitent avoir accès à des programmes de prescription sociale qui respectent leur capacité à maintenir leur autonomie et leur indépendance; qui favorisent le développement de liens et d’un sentiment d’appartenance; qui sont fondés sur la confiance et l’établissement de relations solides dans les interactions avec les fournisseurs et les agents de liaison communautaires et qui donnent la priorité à la personne, personnalisant ainsi la prescription sociale en fonction des besoins spécifiques de chacun.

Conclusion

Les programmes de prescription sociale doivent être fondés sur les valeurs des aînés. Alors que des travaux sont actuellement en cours pour formaliser et étendre la prescription sociale au Canada, la personnalisation de ces programmes en fonction de la situation, des besoins et des priorités spécifiques des participants devrait être une priorité majeure.
Building the capacity of older adults and community: findings from a developmental evaluation of United Way British Columbia’s social prescribing programs for older adults
Authors: Kadowaki Laura , Symes Bobbi , Lalji Kahir , Park Grace , Giannasi Wynona , Hystad Jennifer , McIvor Elayne
Published: September 2024

Introduction

Older adults with higher needs are ideal candidates for social prescribing interventions, given the complex and intersectoral nature of their needs. This article describes findings from a developmental evaluation of 19 social prescribing programs for older adults at risk of frailty.

Methods

An evaluation of the programs was conducted from 2020 to 2023. We used data from three components of the evaluation: (1) initial evaluation data collected in 2020 and 2021; (2) program profiles developed in 2022; and (3) co-creation sessions conducted in 2023.

Results

From startup until March 2023, the programs served a total of 2544 older adults. The community connectors identified factors at the individual, interpersonal, institutional, community and policy levels that contributed to the successful implementation and delivery of their programs (e.g. physician champions, communities of practice, strong pre-existing relationships with the health care system), as well as challenges (e.g. limited capacity of family physicians, lack of community resources). There was strong agreement among community connectors that successful social prescribing programs should include the following core elements: (1) making connections to needed community resources; (2) co-creation of a wellness plan with long-term clients or clients who require intensive supports; (3) ongoing follow-up and check-ins for clients with wellness plans; and (4) an assessment and triaging process for the prioritization of clients.

Conclusion

To leverage the full potential of social prescribing interventions, it is essential that programs engage with a range of health and social care providers, that community connectors are skilled and well supported, and that adequate investments are made in the nonprofit and voluntary sector.