Purpose of the present paper is to point out the design, development and deployment of the AutoInflammatory Disease Alliance (AIDA) International Registry dedicated to pediatric and adult patients with Behçet’s disease (BD). The Registry is a clinical physician-driven non-population- and electronic-based instrument implemented for the retrospective and prospective collection of real-life data about demographics, clinical, therapeutic, laboratory, instrumental and socioeconomic information from BD patients; the Registry is based on the Research Electronic Data Capture (REDCap) tool, which is thought to collect standardised information for clinical real-life research, and has been realised to change over time according to future scientific acquisitions and potentially communicate with other existing and future Registries dedicated to BD. Starting from January 31st, 2021, to February 7th, 2022, 110 centres from 23 countries in 4 continents have been involved. Fifty-four of these have already obtained the approval from their local Ethics Committees. Currently, the platform counts 290 users . The Registry collects baseline and follow-up data using 5993 fields organised into 16 instruments, including patient’s demographics, history, clinical manifestations and symptoms, trigger/risk factors, therapies and healthcare access. The development of the AIDA International Registry for BD patients will facilitate the collection of standardised data leading to real-world evidence, enabling international multicentre collaborative research through data sharing, international consultation, dissemination of knowledge, inclusion of patients and families, and ultimately optimisation of scientific efforts and implementation of standardised care.Trial registration NCT05200715 in 21/01/2022. In the field of rare diseases, evidence is often lower than that required since data are gathered mainly from case reports, case series or small observational studies. This makes difficult to taper clinical management of patients with rare diseases on a thorough research capable of underlying the course, manifestations, long-term outcomes and proper treatments in detail , 2. WithThe purpose of the present paper is to point out the design, development and deployment of the AIDA International Registry specifically dedicated to patients with BD, explaining the rationale for this project, methods employed, and reporting on its implementation to date. Actually, although BD is relatively more frequent in the Countries along the Silk Road, it is a rare disease in most parts of the world –5. ThereThe AIDA Registry for BD patients is a clinical physician-driven non-population- and electronic-based registry meant to be as part of the AIDA project.Data are collected both retrospectively, in reference to the information accrued at the time of the enrolment into the AIDA Registry, and prospectively with respect to clinical, therapeutic and socioeconomic information collected starting from the time of the inclusion into the Registry. Regarding the prospective collection, data have to be updated at least annually or in case of treatment change, as for posology adjustments and combination of different immunosuppressant agents.According to its observational nature, the Registry captures real-world demographic, genetic, clinical, laboratory, and treatment details in a standardised format; long-term outcomes and prognostic variables are also collected when patients do not withdraw the consent to the project over time. Noteworthy, no specific variables or data entries exclusively related to the study protocol are required and only data derived from the standard routine management are collected. Any treatment approach administered prior or after the enrolment into the AIDA project and each posology change performed for the patients’ welfare may be described in the Registry; however, none of the prescribed therapies have been affected by the adherence to study in any way.Participation is open to any centre managing BD patients regardless of location, medical specialty or type of practice setting. The only prerequisites to participate are obtaining approval from the local Ethics Committee and appointing a Principal Investigator who coordinates the study locally and Site Investigators responsible for the documentation and data entry for that site. There is neither cost nor financial compensation to participate, as data collected refer only to information routinely gathered in the clinical practice.The primary objective of this BD Registry is to overcome the current fragmentation of clinical and research experience to carry out robust research based on a sufficiently large number of patients. The final goal is to obtain solid results with pioneering studies. The first steps will aim to better characterize the disease and response to treatment according to different discriminating factors including sex, age at onset, ethnic influence, geographical origin, body mass index, smoking habit, alcohol intake, disease duration, or diagnostic delay.Other objectives include: (1) the search for symptoms clustering or the identification of any patients’ subset leading to potential prognostic or therapeutic implications; (2) the description of older and newly identified therapeutic solutions in terms of global efficacy and the specific role in different manifestations of the disease; (3) better understanding of the role of posology adjustments; (4) the description of socioeconomic impact of the disease in terms of national health system use  and evaluation of working capacity (presenteeism and/or absenteeism); (5) the behaviour of BD during pregnancy and postpartum period; (6) the impact of the disease (and treatments) on the cardiovascular risk; (7) the search for prognostic factors useful to personalise therapy according to short- and long-term prognosis; (8) the description of the best diagnostic pathway disregarding any influence by financial resources on health; (9) the change of natural history of the disease over time, to be eventually correlated with the development of new treatment approaches along with socio-economic and environmental changes; (10) the identification of demographic factors capable to influence BD onset, the severity of manifestations and response to treatments. Depending on the number of patients enrolled and according to future unmet needs, it will be possible to design specific and cutting-edge studies. Of note, it will be possible to easily identify patients to eventually include in future randomized controlled trials (RCTs), whose realization is difficult owing to the limited incidence and peculiar prevalence of the disease.All the objectives of the Registry will be considered in the light of the machine learning data analysis, which represents a new way to statistically analyse clinical information and real-world data. This approach will pave the way for the optimisation of research and implementation of precision medicine.Inclusion criteria into the AIDA Registry for BD consist in the fulfilment of the International Criteria for Behçet’s disease (ICBD), International Study Group (ISG) criteria, and classification criteria for pediatric BD according to the age at disease onset –8. AdditData are collected through Research Electronic Data Capture (REDCap), an electronic data capture tool developed at the Vanderbilt University Medical Center (VUMC) and hosted at Virginia Commonwealth University (Award Number UL1TR002649), which can be used also to develop patients’ registries. The software is distributed at no cost to members of the REDCap Consortium, which is a global collaboration of over 5,700 diverse institutions across 145 countries that have installed the software and collaborate to provide support [Principal Investigators and Site Investigators included into the AIDA project are able to login the Registry through the REDCap web-interface, insert data on the instruments of the Registry and then review  information provided by their own centre. None of the recruited Principal Investigators and Site Investigators are allowed to see information inserted by other Centres. The electronic data entry system of the Registry is in English.https://aidanetwork.org/en/) may be accessed by everyone who wants to learn more about the AIDA network, its objectives and how to participate to the project, the Registry website (https://sitbio.med.unisi.it/redcap/redcap_v12.2.1/index.php?pid=25) is hosted separate from the public website as a secure approach. Data entry is password-protected and collected data are stored on a secure server in the University of Siena, Siena, Italy.While the public website . Later, expert centres for the diagnosis, clinical management and treatment of BD across Europe, the Middle East, Africa and America have been invited to approve the project and participate in the AIDA Registry.Patients’ data are kept in accordance with the EU General Data Protection Regulations (GDPR) on the processing of personal data and the protection of privacy in the electronic communication (2016/679/EU) . The RegBoth patients and Principal Investigators may withdraw their consent for the use of data for statistical analyses at any time. In case a patient withdraws the consent, no further data for that patient will be entered into the Registry and, if requested by the patient, all of his or her prior data will be deleted from the Registry soon after communication to the study promoter.Patients do not receive any honoraria or other types of payment for participation in the registry, and no relationship to billing of the healthcare system or insurance companies have to be highlighted.In accordance with the recommendations for improving the quality of rare disease registries , a plan An in-depth training of the Registry participants is also guaranteed through periodical audits, meetings, evaluations of the Registry growth modalities and protocol reviews.Statistical analysis will depend on the objectives to achieve from time to time on the basis of the data collected in the Registry; however, the statistical plan will include general principles related to descriptive statistics, correlations between groups and comparisons between subgroups. Statistical analysis will be performed also according to machine learning principles.The enrolment of patients with BD on the corresponding AIDA Registry has started on January 31st, 2021. The development and activation of this international Registry boasting the primary and essential purpose of obtaining solid scientific information from wide amount of real-world data is a result in itself. The project has quickly reached a wide geographic coverage capable of including patients from all over the world: in particular, 23 Countries  in 4 continents have been involved so far. As a whole, 110 centres around the world have joined the AIDA project and 35  have currently  entered data on the Registry dedicated to patients with BD; 290 users  have applied for credentials to access the Registry. At current , 636 patients  have been enrolled. Figure Clinical variables included into the study have been chosen to reconstruct the regular course of a complete patient's history and with the aim to respond to current unmet needs. As a whole, 5993 common data elements (fields) organised into 16 instruments (forms) constitute the Registry at current.The full list of instruments and the time-points at which they should refer are listed in Table The common data elements correspond to an equal number of items that describe data on patient’s medical history regarding demographic, genetic and laboratory features, as well as symptoms at onset, symptoms developed over time, comorbidities, cardiovascular risk, work-up exams, pregnancies, past and current treatments, long-term clinical outcomes, and access to healthcare. The fields are organized in such a way as to appear only if patient’s clinical history makes necessary to answer them, thanks to a branching mechanism of questions. Therefore, only a part of the 5993 fields will appear to the investigators, and the number of questions to be answered in the Registry will depend exclusively on the complexity of the patient's clinical history. Conversely, the mandatory fields to necessarily answer consist in the date of birth, the living status, the date at the presentation of the first symptoms, the date at diagnosis, any ocular involvement , the date of the follow-up visits, the duration of therapies expressed in months. In the follow-up form, it will be mandatory to answer to whether the patient is treated with conventional disease modifying anti-rheumatic drugs (cDMARDs), biotechnological agents, small molecules; which cDMARD is eventually used, any reasons that induce the treatment discontinuation.Data elements, where appropriate, are shared with other AIDA Registries dedicated to different autoinflammatory diseases; other bespoke data elements are specific of BD and have been added to meet the specific field of this disease in terms of clinical phenotype, clinimetry, possible complications, treatments not useful for patients with other autoinflammatory diseases, and the different follow-up approach planned for the prospective enrolment phase. In relation to this last point, longitudinal data are captured through a specific follow-up instrument.Both the retrospective and the prospective instruments include the filling-in of the Behçet’s disease current activity form (BDCAF), which is a score used for the assessment of disease activity during the past 4 weeks, and the Behçet’s syndrome Overall Damage Index (BODI) score, developed to assess organ damage at a given time , 13. In Of note, this Registry has been designed to communicate with other existing or future registries with similar objectives. This is part of the sustainability of the project and represents a good practice to take into account when developing a new registry. Indeed, data often require to be merged from different registries with the purpose of answering old questions from different perspectives and facing new issues deriving from future unmet needs.Associazione Italiana Sindrome e Malattia di Behçet) has been actively involved into the AIDA project and other associations based in other countries will be invited to participate in a near future.In recent years, patients have developed an increasing awareness of their role, which has become central in stimulating the research effort and quality of clinical management . ActuallNetworks are born to facilitate the spreading of knowledge and establish research collaboration between researchers, clinicians, industries, patient organizations, and single patients with their families. This is even truer in the field of rare diseases, as the small number of cases is a barrier to the translational research and makes the identification of a substantial cohort very difficult. In this context, the AIDA project and the corresponding Registry for patients with BD represent very useful tools to overcome the current fragmentation of knowledge and research regarding this rare disease. Actually, the management of BD requires the co-partnership of different specialties that must necessarily communicate with each other, including rheumatologists, ophthalmologists, geneticists, dermatologists, immunologists, gastroenterologists, phlebologists, internal medicine physicians, and paediatricians for patients with early-onset BD. As the AIDA Network has managed to include a large number of specialities, this project represents one landmark demonstration of how well a web-based worldwide collaboration may give benefit to the research and clinical management of this rare and complex disease. This collaboration may lead to a substantial increase of efforts from the pharmaceutical industry to develop new treatment approaches for BD.To date, the AIDA project has fulfilled the expectations for the development of a platform dedicated to BD, where the scientific community may communicate, share experience, and actively participate in research efforts based on large-enough cohorts of patients to ensure previously undreamed projects. In this regard, the implementation and execution of a large International Registry may finally overcome the limitations of smaller individual studies , providiThe Registry may also provide an invaluable source of data to better understand the cardiovascular risk of BD patients and the behaviour of this disease in different periods of pregnancy  and during the postpartum period. The prospective phase of the project will also provide more information on the socioeconomic impact of the disease and the benefits that national health systems could obtain from the treatments used. The Registry will also make it possible to assess the proper dosing and long-term benefit/risks of any treatment used for BD patients.Its flexibility will allow improving the registry over time in accordance with new acquisitions derived from the international medical literature and in case of protocol amendments. Also, specific RCTs will be possible thanks to a potentially worldwide basis of enrolment, which will overcome issues related to the low incidence and prevalence of BD. In this regard, performing studies even on patients with rarer features of BD will be possible, as enrolment would be guided by a rapid search for patients presenting the characteristics required by a given study design.While the first studies from the AIDA Registries have been published in recent times, several forthcoming papers are planned to specifically derive from real-world standardised data collected into the Registry dedicated to BD patients, especially in relationship with the description of baseline BD features, differences related to geographic distribution, description of current treatment approaches in different settings, and the way these treatments are effective in inducing a lower impact on a national health system. Deeper analyses and studies on some of the rarer subtypes of the disease are projected and will be realised according to the sample size reached in the coming years and according to the implementation of machine learning systems.As a whole, real-world evidences deriving from this Registry will corroborate and improve current knowledge about BD. Indeed, although many data have been widely published during the last decades about the different aspects of the disease, they mainly derive from Countries with a high prevalence of the disease . This is an evidence for geographic discrepancies and clusters, factors affecting the disease course and outcomes, and response to treatment –30. The In the next future, part of the efforts will be directed towards improving the sustainability of the project through the implementation of a clear development strategy, the definition of management mechanisms, and the regulation of the partnership and all the stakeholders involved. Moreover, collaboration with other projects and registries dedicated to BD will be sought, to maximise the results obtained from data collection in this AIDA Registry through different evaluations of the data according with other research perspectives.A close collaboration will be also pursued with all the stakeholders interested with the AIDA Project, especially patient associations and professional organisations. In particular, a branch of the AIDA project defined as "AIDA for patients" is under development. “AIDA for patients” is an electronic system for collecting patient-reported data, thought with the aim of involving patients in the assessment of the disease status, the impact of BD on the quality of life and on socio-economic aspects; moreover, “AIDA for patients” was born to facilitate patients’ participation in the decision-making process both in terms of guidance of scientific research and in providing the collection of patients reported outcomes (PROs) to enhance a research based on real-life data.All aspects of the Registry dedicated to BD patients will be subject of interim reports that will highlight the goals achieved in the future through meetings, congresses and dedicated papers.i.e., characterised by multiple treatment approaches and many posology changes. Actually, while entering prospective data from follow-up visits takes a maximum of 10 min, entering retrospective data from a particularly complex BD patient can take many hours. In addition, the participating investigators are under no obligation to consecutively enrol all their BD patients, and unintended selection bias is possible. Nevertheless, beyond its limitations, this Registry has the potential and the geographical basis to really achieve all the objectives fixed. Moreover, we are currently developing “AIDA for patients” which will minimise missing values resolving, among other things, some of the quality limitations associated with data entry.The AIDA Registry for patients with BD has all the usual limitations of an observational research in general and registries, in particular. Entering data into the Registry requires time and attention, especially when patient's medical history is particularly complex, In conclusion, the development of the AIDA international Registry for patients with BD will facilitate the collection of standardised data enabling international multicentre collaborative researches through data sharing, implementation and optimisation of scientific efforts, international consultation, dissemination of knowledge, and inclusion of patients and families. Next steps will include the implementation of patients’ participation, new efforts to further disseminate the Registry by a broad international cooperative network, the inclusion of all the possible stakeholders, and the strengthening of the project sustainability.


Human functional neuroimaging has evolved dramatically in recent years, driven by increased technical complexity and emerging evidence that functional neuroimaging findings are not generally reproducible. In response to these trends, neuroimaging scientists have developed principles, practices, and tools to both manage this complexity as well as to enhance the rigor and reproducibility of neuroimaging science. We group these best practices under four categories: experiment pre-registration, FAIR data principles, reproducible neuroimaging analyses, and open science. While there is growing recognition of the need to implement these best practices there exists little practical guidance of how to accomplish this goal. In this work, we describe lessons learned from efforts to adopt these best practices within the Brain Imaging Research Center at the University of Arkansas for Medical Sciences over 4 years (July 2018–May 2022). We provide a brief summary of the four categories of best practices. We then describe our center's scientific workflow (from hypothesis formulation to result reporting) and detail how each element of this workflow maps onto these four categories. We also provide specific examples of practices or tools that support this mapping process. Finally, we offer a roadmap for the stepwise adoption of these practices, providing recommendations of why and what to do as well as a summary of cost-benefit tradeoffs for each step of the transition. The science of human functional neuroimaging has evolved dramatically in recent years, driven by a pair of emerging trends. First, neuroimaging science has grown ever more data intensive and computationally sophisticated. Indeed, with enhanced temporal and spatial resolution, newer generation multiband-accelerated 3-Tesla functional magnetic resonance imaging (fMRI) scanners acquire an order of magnitude more data per imaging session compared to earlier MRI systems  and detail how each element of this workflow maps onto these four categories. We also provide specific examples of practices or tools that support this mapping process. Finally, we offer a roadmap for the stepwise adoption of these practices, providing recommendations, based on our personal experiences, of why and what to do as well as a summary of cost-benefit tradeoffs for each step of the transition. The goal of this work is to encourage and enable other human neuroimaging research groups to adopt similar strategies to better minimize replication failures and strengthen the inferences from this field of human neuroscience.prior to gaining knowledge of the experimental outcome . Our experimental paradigms and processing pipelines were written in closed-source programming languages (Presentation and Matlab), which were maintained locally without comprehensive version control that could not be reviewed or linked to manuscripts. Also, our center had never released a manuscript preprint and had only occasionally published in open-access journals. This then-common approach represented the starting point for the planned transition.In July of 2017, compelled by concerns surrounding the neuroimaging research reproducibility crisis inspired by Eklund et al.  as well https://github.com/kabush/CTER) and commenced linking relevant source code within manuscripts submitted for peer-review. Our second task was to re-implement our analysis pipelines in an open-source language, Python. Due to in-house computer science expertise, this module of work had relatively low implementation costs for our center. However, the costs of executing this transition step would vary by laboratory depending on one's access to computer science or software engineering expertise. For newly forming neuroimaging labs, we recommend a priori adoption of open-source languages, such as Python and R, which have large and growing neuroimaging processing and analysis software ecosystems  was the primary programming language used within our center. Our center also had no standardized software maintenance and version control practices. Our first task was to integrate our legacy proprietary code base with git, a free and open source version control system for tracking software changes and updates . The direct costs of preprinting are minimal and reflect the effort of uploading the manuscript to the preprint server and a short time delay  required for moderators to review the manuscript prior to public reposition . The indirect cost of preprinting stems from the potential risk of publicly exposing a flaw in one's work, rather than the flaw being detected and fixed privately within the peer-review process Kaiser, . The benhttps://github.com/kabush/CTER2bids), and validating that the resultant mappings met the BIDS standard consumed many months of effort across multiple imaging center team members. Indeed, despite in-house computer science expertise, this module of work was the single most costly step in the transition process. The benefits of mapping our data to BIDS, however, far exceed the costs. First, our center now has access to BIDS-Apps . The benefit of implementing this step is that our minimal image preprocessing pipeline is now both well-validated and reproducible, and thus of high value to controlling error and the ultimate goal of developing transparent, reproducible workflows.Immediately following our transition to BIDS, we replaced our in-house minimal image preprocessing pipeline with fMRIPrep  of similar depth and detail as would be necessary to submit a manuscript for consideration of publication as a journal article, preregistration can be thought of as front-loading the effort of writing a journal manuscript without the results and conclusion. The Open Science Framework registry provides a templatePerhaps the greatest barrier to making the transition to open and reproducible science is the uncertainty surrounding the costs and benefits of the process. To assist others in planning their own transition we have summarized see  the costThe Brain Imaging Research Center at the University of Arkansas for Medical Sciences has expended significant effort over the past 4 years incorporating best open and reproducible practices into our scientific workflow. What began as a process to eliminate scientific risk – the risk of serious scientific errors, false-positive claims, replication failures, or losses of critical institutional knowledge – evolved into a pursuit of seamless and efficient scientific inquiry in which each step of the scientific process, from project inception to results reporting, is thoughtfully, rigorously, and transparently documented and shared. This is, in our opinion, both the scientific ideal and mandate.However, we acknowledge that migrating a neuroimaging laboratory to best practices in open and reproducible science is a non-trivial undertaking associated with substantial initial costs of effort to be borne by individuals already engaged in challenging, time-consuming work. During transition, the lab's record of research productivity will suffer. Projects will need to be implemented in both the legacy and upgraded workflows so that scientific products, the lifeblood of the lab, continue to be generated on a regular basis. Each member of the lab will likely need to invest in learning additional programming, version control, and data management skills as well as acclimate to working with unfamiliar naming conventions and directory structures mandated by the BIDS standard. The entire process may be frustrating and intimidating. We also acknowledge that while many argue for the benefits of open science practices to investigators and science itself (Frankenhuis and Nettle, The purpose of this work is to provide a brief experience-based depiction of the terrain that a lab will cover in their own migration to this responsible commitment to open and reproducible neuroimaging science. We have condensed a large and rapidly growing literature down to four categories of tools and practices that comprise the open and reproducible science ecosystem. For new investigators starting their own labs, we strongly encourage incorporating these practices into the lab's workflow from Day 1. For established labs, such as ours, we provide a 7-step model of transition that prioritizes practices with the lowest costs and highest benefits. Of the initial 5 recommended steps, only the transition to BIDS format imposes a high cost, but it also bears the greatest number of benefits and thus, we argue, is the single most important step a lab should undertake. We hope that these lessons learned will inform your own decision as to when and where, not if, you will start the transition.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.Conception, manuscript preparation, and revisions: KB, MC, and CK. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The TGMD  has been considered as one of the gold standards of assessment tools for analysis of motor competence in children. However, it is rarely used by teachers in schools because the time, resources, and expertise required for one teacher to assess a class of students is prohibitive in most cases. A potential solution may be to automate the testing protocol using objective measures and inertial measurement unit sensors. An accurate method using 17 sensors to capture full body motion profiles and machine learning methods to objectively assess proficiency has been developed; however, feasibility of this method was low. Subsequently, a simplified method using four sensors  was found to be effective, efficient, and potentially highly feasible for use in school settings. For some skills, however, not all skill criteria could be assessed. Additionally, misclassification on occasion, marred results. In the present paper we consider a previous experiment that used wireless motion capture to assess criteria from the TGMD-3. We discuss the advantages alongside the disadvantages of testing motor competence in children using sensors and consider the question—Can a compromise be struck between accuracy and feasibility? Physical activity is a positive contributing factor for child health and development WHO, . CurrentIn children and adolescents, low motor competence correlates with unhealthy weight status  and time intensive to analyze  and three object control skills . These skills were selected as they are commonly used in the Australian physical education curriculum as well as junior sport and physical activity pursuits. Children performed the TGMD-3 in school or university gymnasiums suitable for the administration of the TGMD-3, and according to the test instructions. Before participant performance, an accurate demonstration of the skill was performed. Participants were tested individually and were given one practice trial to ensure that they understood what to do. Each participant performed one to 10 trials for each of the seven motor skills based on the need for variability to inform the sensor data. The video camera was placed optimally  to best detect the particular skill performance for subsequent analysis and scoring.Xsens 2022) was used. This is an inertial IMU-based motion capture system comprising of 17 wireless sensors with the ability to capture motion at a rate of 60 Hz. To configure and calibrate the kinematic model, a series of predefined bony landmarks were collected from participants. Measurement of these landmarks were collected with an anthropometric measuring tape. The measurements consisted of body height (measurement from ground to the top of head when standing upright), shoe size (measurement from top of shoe nose to the end of the heel), arm span (measurement from top of right fingers to top of the left fingers in T-Pose), hip height , knee height , ankle height , hip width (measurement of right to the left anterior superior iliac spine), shoulder width , shoe sole thickness (measurement of average thickness of the sole of the used shoes). Once participants' anthropometrics were collected, they were fitted with sensors via Velcro straps. Students wore these on top of their clothing tightly and secure to ensure no unexpected movement of sensors would take place. This included a shirt with fitted belt, leg straps (lower and upper leg), arm straps (forearm and upper arm), gloves, shoe covers, and a head band. The calibration of the motion capture suit within the XSENS MVN Analyze 2019 software was conducted prior to each capture to ensure accurate sensor data.In this case-study . Those assessing the video data had completed online training/coding specifically for this assessment and achieved a reliability of >0.95 against expert raters . This is a significant omission of important data required for comprehensive evaluation of skills. Thus, measurement of the object control subset of the TGMD-3 may be comprised by IMU-based systems. In comparison, manual assessment shows acceptable levels of inter-rater reliability for the overhand throw, but not for the catch and kick. For intra-rater reliability, acceptable values were present for the catch and overhand throw, but not the kick. Hence, both systems of assessment have challenges in terms of the object control skills.In addition to non-measurable skills or skill criteria, another limitation of the simplified sensor method is inaccuracy leading to misclassification; for example, false positives  or false negatives . Why were certain skill criteria misclassified? The accuracy was lower for the throw, jump and hop. For example, in the jump, criterion 2  had no false rejections, whereas criteria 1, 3, and 4 had several false rejections, meaning that a good performance was classified as poor. However, criteria 2 of the jump did have several false acceptances, and in four cases a poor performance was classified as accurate. In such a small sample size, these misclassifications may be a concern and this level of “noise” in the data indicates that the accuracy is affected. However, it is important to note that misclassification of skill performance can also occur with manual assessment.The level of potential misclassification with the sensor method may reduce the feasibility of the method, as inaccurate results make the method less appealing to teachers, who may then need to fall back on manual methods which they may perceive as more accurate.The seven TGMD-3 skills tested  are commonly used in the Australian physical education curriculum. The remaining six motor skills in the TGMD-3 are the run, gallop, leap, two-handed strike, one-handed strike and stationary dribble. Extrapolating from the results of the seven skills tested in the simplified method, it might be expected that the other six skills may also be impacted by localization, in particular the object control skills, as these relate to an external object that may not be able to be picked up by IMUs as placed on a person. As such, additional parameters may be needed for criteria within those skills to inform how a performance is classified. For example, a compromise here may be a hybrid approach to assessment, where the skill and skill criteria that can be accurately assessed by IMU are automated, and the additional skill criteria assessed by other means . Potentially, an addition of one or two additional sensors may provide the depth of skill analysis and mitigate the omissions detected with the use of only four sensors. This may increase set up time, and dilute feasibility in terms of practicalities in a class, however, may provide the additional skill information. Research in the sports field is showing it is possible to implant sensors in objects to detect movement of the object, see for example, in basketball. So this could be the way of the future in motor competence assessment in children. Future research should test the real-word application of IMUs by teachers in schools and potential new ways to embed sensors.Although there are major advantages of using IMUs for motor competence assessment, there are also significant disadvantages with the present methods. Reducing the number of sensors to four creates a highly feasible method, but the results are incomplete. This enhanced feasibility and ease of use may lead to greater uptake, applicability, and use in real-world settings, particularly physical education, potentially leading to improved measurement at a population level, greater chance of targeted intervention and ultimately improved motor competence. However, some of the TGMD skill criteria were not entirely assessed in the context of machine learning, such as the fine detail of catching a ball in the hands. These gaps in the results reduce the quality of the data, and therefore may reduce its usefulness in detecting motor skill competence. This reduced accuracy may make the method less appealing to teachers—even though manual assessment of skill also has issues with reliability. Thus, while machine learning may enhance in-field application and feasibility of the TGMD, objective or automated implementation via sensor wear may not satisfy all assessment criteria. Could a compromise be struck regarding accuracy vs. feasibility? The question remains—how best to balance precision with practicality? Currently, motor skill competence is rarely conducted in schools, and skill errors are seldom remediated. Therefore, although IMUs may have some limitations, is this a case of something being better than nothing?The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Deakin University ethics and the Department for Education and Training approved this research. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.All authors made substantial contributions to the conception and design of the work, contributed to the analysis or interpretation of data for the work, and assisted with drafting the work or revising it critically for important intellectual content. All authors have provide approval for publication of the content and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This study reassesses the dynamic relationship between stock, oil, foreign exchange markets, and COVID-19-induced uncertainty. For estimation, we utilize the monthly data from January 2020 to December 2021 and utilize panel vector autoregression econometric techniques in emerging market economies. The empirical findings reveal that heightened uncertainty during the pandemic had a negative impact on stock and oil, and foreign exchange markets. Findings further suggest that uncertainty during the pandemic slanted the relationship between oil and stock and foreign exchange markets due to the precautionary approach followed by economic agents.•COVID-19 uncertainty negatively impacted the oil, stock, and foreign exchange markets.•Uncertainty had a non-linear impact on stock and oil prices.•During the initial period of COVID-19, uncertainty distorted the relationship between oil, stock and exchange markets.  Specifications tableThe vector autoregression (VAR) was originally proposed by Sims A l-variate homogeneous panel VAR of order q with panel-specific fixed effects can be represented in the following equation form:Where In order to estimate Where the asterisk represents the transformation of the original series. Let us assume the original series as If we stack observation over the panels rather than over time. The GMM estimator is calculated byWhere With the eruption of the COVID-19 pandemic and its subsequent spread of the highly contagious nature of the virus, we saw that many parts of the world economies resorted to adopting unprecedented mitigation measures such as nationwide lockdowns, physical distancing, and restrictions on movements of people domestically and internationally Furthermore, this increasing uncertainty in directly affected various markets, such as stock markets The theoretical relationship between oil price and exchange rate suggests that a positive shock in oil prices leads to the depreciation of the exchange rates of oil-importing economies and leads to a shift of wealth from oil-importing to oil-exporting economies There have been studies conducted that analyze the link between uncertainty associated with COVID-19 and its impact on various markets, such as for the Indian economy by Prabheesh and Kumar This study addresses the aforementioned research issues and re-examines the findings of the earlier work by Prabheesh and Kumar 23]32. In orThe study contributes to the literature on the following grounds. First, for a robustness check of the earlier findings, we reassess the dynamic of oil, stock, and foreign exchange markets by taking the large set of EMEs. Second, for estimation purposes, we utilize the PVAR technique, which is relatively new to the literature. Third, we expand the sample period till December 2021, as updated by Narayan et al. This study is organized as follows. Section 2 discusses the data, section 3 presents the method, and 4 presents the empirical findings. Finally, section 5 concludes.We constructed a balanced panel of 17 EMEsFor estimation, we employ the PVAR model, which combines the traditional VAR model and allows for endogenous interaction among variables in the system and also helps in controlling unobserved individual economy heterogeneity Where itɛ represent a Where The PVAR model is estimated by utilizing the GMM estimator as provided by Abrigo and Love Initially, we check the stationarity properties and stability condition of the selected PVAR model. The variables OR, SR, and UI are found to be level stationary, and ER is found to be difference stationaryThe third row of the figure presents a positive shock in the OR and the response of the other variables in the system. For instance, the response of SR to a positive shock in OR is found to be negative and significant (OR: SR). It implies that an increase in oil prices negatively impacted the stock markets in oil-importing countriesFrom the last row, it can be observed that in the first month, a shock in the UI is associated with a negative response of SR (UI: SR). It implies that an increase in uncertainty negatively affected the SR in EMEs. Also, after the second month onwards, the response of SR was positive and significant. It indicates that from the second month onwards, the stock market reacted positively. Our empirical findings are in line with Phan and Narayan The response of ER to a positive shock in the UI is found to positive and significant. It implies that an increase in uncertainty during the pandemic depreciated the exchange rate in EMEs. These findings are in line with the theory; that when there is uncertainty in the global economy, a capital flight takes place for safety from EMEs to advanced economies. Thus, it shows that when uncertainty increased during the pandemic, the ER depreciated. Likewise, a shock in the UI is also associated with a negative and significant response to OR. It implies that during the pandemic increase in uncertainty negatively impacted the oil return. These findings are in line with earlier studies such as Narayan and Devpura th month, the variation in innovation explained by UI is 43.3%. It indicates that during the pandemic, uncertainty significantly explained the variation in the stock return. Similarly, in the case of ER and SR, in the 5th month, the variation in innovation explained by the uncertainty is about 26% points and 37% points, respectively. It implies that during the pandemic, uncertainty significantly explains the variation in the exchange rates and stock return. These findings suggest that during the pandemic, uncertainty significantly explains the variation in the innovation of ER and SR in EMEs. It also significantly explains the variations in the case of oil return. For sensitivity analysis, we utilize the volatility index (VIX) as an alternative proxy variable for uncertainty and re-examine the PVAR. The overall responses are similar to our main findingsOverall our study's findings align with earlier studies' findings by Prabheesh and Kumar COVID-19 induces uncertainty had a devastating impact on various markets all around the world. There have been many studies done based on the initial availability of the dataset, but their robustness testing remained. Thus, this study re-examines the dynamic relationship between the three most important markets, such as the exchange rate, the oil market and the stock market, in the prevalence of COVID-19-induced uncertainties from an EMEs perspective. Our findings reaffirm that uncertainty associated with COVID-19 had dampened the oil return and negatively impacted the SR and ER also depreciated in emerging economies. Further, the study reinforces that initially, due to heightened uncertainty relationship between oil, stock and foreign exchange markets was distorted.The authors declare that no funding has been received to carry out this research work.This article is submitted to MethodsX as a special issue in COVID Research Robustness. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


This paper investigates the views of healthcare researchers and professionals on the implementation of the Quality Management System (QMS) approach using a 5-point Likert scale survey. Researchers and healthcare professionals who observed or participated in QMS implementation were surveyed. Multiple channels, including occupational societies, social networking, i.e., LinkedIn, hospital’s directories, award recipients, academic researchers, and professional connections, made it possible to reach this particular sample. Participants were surveyed using a series of questions with a total of 56 questions. The survey was administrated through the web portal of Qualtrics and then analyzed both on Qualtrics and SPSS software packages. Descriptive Statistics, Exploratory Factor Analysis (EFA), and Linear Regression were employed to draw conclusions. The final sample group consisted of 71 participants representing a range of healthcare settings. EFA was conducted, producing a model of 10 emergent factors and an outcome for total improvement. Regression modeling revealed the Critical Success Factors (CSFs) and the interaction between emergent factors. The results indicated that QMS Implementation Culture, Structure, and Managerial Training are critical to the QMS implementation success. This research helps quality professionals enhance their ability to prioritize elements affecting the successful implementation of the QMS. The pursuit of adequate improvement of organizational processes, procedures, and policies has encouraged healthcare systems to seek out suitable quality management schemes . AchieviIn healthcare, policymakers’ choice to utilize the Quality Management System (QMS) requires the use of proper success measures . ResearcIn complex industries, such as healthcare, quality management is an interdisciplinary process. The inherent complexity of healthcare quality was acknowledged in various reviews of improvement initiatives ,14. ParaMultiple studies have empirically shown that successful QMS implementation is linked to improved clinical outcomes, such as mortality, complications, and patient safety, and administrative outcomes, such as the average length of stay, profitability, and expenses incurred per discharge ,18. AburCritical Success Factors (CSFs) include strategies and approaches that represent the implementation structure or a way to conduct things . The sucA Systematic Literature Review (SLR) by Rawshdeh et al.  revealedIn this area of research, there was a lack of concrete empirical evidence for factors’ structure and the relationship between factors and outcomes. Consequently, there is a need for modern research based on a comprehensive understanding of QMSs and advanced empirical analyses. This research aims to develop a robust construct of factors and provide the necessary relationship analysis between factors, resulting in a comprehensive framework of factors and outcomes.A survey instrument was constructed to refine multi-item constructs that can be used to quantify the effects of the factors on implementation outcomes and to investigate relationships among factors and outcomes.An Operational Research Model was developed by integrating the factors and outcomes discovered by Rawshdeh . The resThe approach to establishing content validity involves literature reviews alongside expert evaluation. This survey used constructs with content validity since they were derived from an extensive review of the literature, consisting of multiple reviewers to ensure the constructs’ validity, alongside expert insights to ensure they are valid . The resThe next section discusses the use of Likert-scale survey questionnaire to refine the factors and ensure a robust model structure. In addition, it provides an analysis of the emergent factors’ connections to the achievement of the outcomes as well as the discovery of the inter-relationships among them.The survey was designed to be taken online using the Qualtrics platform developed by Qualtrics company copy right version July 2020 Provo, Utah, USA. The survey consists of two sections. The first section focused on background information and contained nine questions that collected information about the respondents’ backgrounds. The information included position, years of experience, the type of QMS implemented, the overall level of implementation success, and the size and type of healthcare organization. Moreover, it included the exclusion criteria represented by questioning the participation in QMS implementation in healthcare, and their role in the implementation. These questions aimed to filter participants who did not have the appropriate experience and remove them from the sample.The second section contained the items for defined constructs, which consists of 47 questions regarding the respondents’ experience. This study consists of three groups of factors with a total of thirteen factors and thirty-nine items in addition to three outcome variables with three items for each outcome. Liker-type surveys are most recommended when relationships between constructs are complex and prevalent at the same time . MultiplThe potential participants for the survey were academic researchers or industry professionals who have participated in or observed the implementation of QMS in healthcare organizations. Due to the unavailable access to the database of all healthcare organizations’ personnel for the sample selection, convenience and purposive non-probability sampling are adopted since this study requires certain qualified members .Exploratory Factor Analysis (EFA) is generally regarded as a technique for large sample sizes (N), with N = 50 as a reasonable absolute minimum . Ref 3232 characA pilot study was conducted to test the survey with 18 subject participants who are experts in the area. The reliability of the variables was tested using Cronbach’s Alpha. The reliability values for the factors had different values with some factors scoring less than 0.5. Some factors can improve reliability when removing some items. Since the CA results alone are not decisive in redesigning the items, both CA results and pilot testers’ feedback were used to refine the items and improve the flow of the survey. The pilot study mainly helped in refining the statements and obtaining feedback from the testers about their experience in taking the survey, thus improving the clarity of the survey.The data collection resulted in 71 responses. The low response might be due to the highly specific scope of the research, where a unique system, such as QMS, is being studied in the setting of healthcare. The literature emphasizes that low response rates can be accepted given that the study takes steps to ensure the adequacy of the response . Steps iEFA and Cronbach’s Alpha are used to refine the final set of factors. EFA is a clustering technique aiming to identify the underlying structure of factors, namely, their adequate grouping . EFA wasEFA is a highly interpretive approach, but multiple threshold metrics were used to guide the selection of items for each factor. The Pattern Matrix’s factor loadings should be close to or above 0.5 with 0 s-loadings below 0.3 ,38. EachManagement Commitment, Management Training, and Strategic Planning. The new factors’ items mostly matched the preliminary models except for MT1. MT1 was loaded into Factor 1 Management Commitment when it was originally with Factor 2 (Management Training). This repositioning of the MT1 item may be due to the focus on the management expectations of professionals regarding quality improvement. The item can be perceived as the role of the management rather than its competence. On another note, MT4, which described performance data used by management, fit into both Factors 1 and 2, due to the presence of performance and management in the item. Reliability measurements were obtained for the item in both factors to find the best fit. It was found that the reliability was enhanced with MT4 in Factor 3, thus it was added to Factor 3.The items in model 1  belongedQMSs’ Implementation Culture) and Factor 5 (Employee Focus). Four items were loaded into Factor 4 that were initially related to employee involvement and resistance to change. The items represent culture and the human role in implementation, where the “resistance to change” item is related to culture. These two concepts were also associated according to the co-occurrence of factors. The result drew attention to this factor revolving around the Culture of QMSs’ Implementation. Three items were identified in Factor 5, and these items came from employee involvement and communication. Both the involvement of employees’ items and communication have focused on the personnel’s role in implementation. Moreover, the items can be attributed to enhancing the personnel’s ability to communicate and receive feedback and were found to be associated to the co-occurrence network, thus the factor was named Employee Focus. The EFA for model 2 dropped two items related to resistance to change and communication due to their low communality. This drop suggests that these items may not be factors themselves, but part of broader factors. The result confirms the new factors’ structure.Model 2  containeIn model 3 , ten itePerformance Improvement” for the factor. The remaining four items were loaded into Factor 10. The items are composed of processes and procedure items, audits and reviews, and customer focus. The combination indicates a high resemblance to organizational structure, where audit and review items refer to protocol revision. Therefore, this group of items was found to show a strong resemblance to Structure. Finally, all the outcomes are loaded into one new factor  is an approach used to show the feedback structure and can describe the causal effects between the identified factors ,41. ThisNext, each of the ten regression models was developed using SPSS software and the remaining assumptions and measures of model fit were evaluated. Then, the results were used to develop the resulting hypothesized CLD. The resulting regression models were used to develop the CLD model, as shown in Information Technology on Training and Education, Employee Focus on Performance Improvement. Although the results are not expected, they can be justified by considering the effects over time. The results show many significant relationships between the variables. This could be considered unusual compared to studies about critical success factors, but most of the results were expected [The hypothesized CLD includes arrows showing the direction of the relationships and the type of effect. It can be observed that there is self-reinforcing feedback in all loops except for the relationship of expected ,42. ShadThe results of the EFA models were not surprising, with many factors retaining their original structure. This confirms the preliminary design of the model and aligns with the findings of the literature synthesis and the expert study, contributing to the survey analysis’s total validity and the EFA analysis’s validity, particularly the face validity, which indicates that similar nature items are loading together on the same factor. All nine items in the outcome model are loaded into one outcome, as shown in The regression results suggest that implementing a culture where quality is centered within the organization has a significant effect on the successful QMSs’ implementation conforming with what has been referred to by the literature . For QMSThe model represents an answer to the major research questions about the CSFs responsible for a successful implementation of QMS in connection to the implementation’s main outcome. The structured and systematic technique used, beginning with refining the factors followed by the multiple regression modeling, ensured the final model’s validity and accuracy. Moreover, the CSFs are in conformance with the factors for general change initiative in healthcare. Kasha et al., 2014 found that improving quality embedment in the healthcare organization environment is one of the most critical success factors for change. They stated that this is one of the unique success factors for healthcare that is not regularly found in change models . These fPerformance Improvement is critically connected to four other factors with a solid connection to the CSF Structure. Another strong connection was with the Training and Education factor, which is consistent with previous literature assumptions that indicated the need for proper quality improvement skills to perform any improvement initiatives [Training and Education factor, which was also connected to three other factors, including a strong relationship to QMS Implementation Culture. The connection can be verified by noting one of the QMS Implementation Culture components, resistance to change, where education about QMSs’ role and encouraging its principles can make employees inherently eager to adopt the QMS principles. One final example of a central factor is the Information Technology factor. Since this factor is responsible for providing data and measuring performance, it was expected to have a direct connection to Performance Improvement; however, more critical connections were found for Management Commitment. This result can be due to how the CLD model is developed, which is based on multiple relationships between the factors. Therefore, this creates a chain of effect, where one factor affects the other and this factor affects another factor. The CLD model provided essential information about the interactions among factors as well as another dimension of significance. The model was able to show which factors are central to a group of factors providing additional insights beyond the CSFs for positive outcomes.Furthermore, the CLD has presented other central factors to the implementation process, although they were not deemed critical for the outcomes. For example, tiatives . This caThe investigations of implementation success factors in the literature were primarily qualitative or used the simple descriptive analysis. Few studies have used multiple advance statistical analyses and identified factors related to organizational structure, including procedures, working guidelines, and resources, which were found to be important for the total improvement outcome in this research ,44,55. AInterestingly, none of the quantitative studies in the literature found Management Training crucial for the implementation. The previous quantitative studies confirm the variation in the factors studied, their terminology, and the context in which the studies were conducted. The results of the model testing study matched the results provided by the literature. This is probably natural since the underlying concepts that form the survey are the most commonly identified factors in the literature.Strategic Planning, Training and Education, Resources Allocated, and Information Technology, had the same items from the preliminary model. While factors, such as Management Commitment and Management Training, had only a slight difference . The primary factors of Employee Involvement, Customer Focus, Resistance to Change, Audit, Communication, Performance, and Processes and Procedures were highly affected. They yielded a new group of factors that were named: QMSs’ Implementation Culture, Employee Focus, Performance Improvement, and Structure. The regression model found three critical success factors that are linked directly to the outcome of success. The factors were Implementation Culture, Management Training, and Structure. The CSFs agreed with general change and systems implementation in healthcare, where improving system embeddedness in the healthcare organization environment was one of the most critical success factors for change. Comparing this list of CSFs to other sectors proves how the study resulted in more healthcare-related CSFs. The three variables have covered a wide spectrum of items in the survey and have a solid base in the literature, supporting the survey instrument’s validity and providing significant insights into the factors responsible for implementation. Moreover, the survey instrument was able to find the correlations among factors and perform regression modeling that helped initiate the CLD of the factors’ relationships. The results show significance in all the relationships between the variables. This could be considered unusual compared to studies about critical success factors, but most of the results were expected [Initially, the study developed an operational research model with thirteen preliminary factors on the basis of a literature review and expert study. EFA analysis and multiple linear regression helped refine the factors and analyze their effect on implementation. Multiple emergent factors matched the initial factors. Factors, such as expected ,42. ShadThe survey analysis has provided quantitative evidence about the factors and the outcomes of implementation success, which will contribute to the literature in this area that sorely lacks the depth of recent empirical evidence. This research presented empirically operationalized models of understanding for both QMS and implementation success. This process provides a solid, clear basis for any build-up in future research and allows for an enhanced background for perceiving general studies’ results. Finally, the survey study was conducted with a broad sample of healthcare quality experts from various roles with experience in applying different types of QMS approaches and in multiple healthcare settings. This quality in the sampling enhanced this research’s generalizability. The multi-item construct survey that tested the model provided a robust construct refinement and allowed further examination through advanced statistical techniques.QMS Implementation Culture. In particular, the need to understand that the working environment with all stakeholders’ behaviors and attitudes toward the implementation poses a crucial effect on success. Therefore, acknowledging quality as a routine rooted in all aspects of the process will alleviate the difficulties in implementing the QMS. Moreover, quality thinking can ease the implementation of improved processes and procedures and reshaping them to be patient focused. The principal key practical implication is that the implementation of QMS is an installment of a system and a change of mindset. Furthermore, the comprehensive results of this research can assist in a deeper understanding and a high level of planning.The implication from the research comes from the most significant factor that the study identified: The The limitations of this research are related to the construction of the survey and the research sample. The survey was developed based on a rigorous review of the literature and an expert study. However, the data related to measuring the potential success factors (independent variables) and outcome variables (dependent variables) were collected from the same source, which may introduce a common method bias . AnotherAdditionally, the measures that emerged from this research, the ten success factors, should include further analysis to ensure their validity and reliability across a variety of situations and contexts. All participants stated experiencing a successful implementation, which might be due to the survivorship bias. In survivorship bias, people tend to report only the successful cases, while leaving the unsuccessful cases unevaluated, which results in incomplete conclusions. This form of bias could produce a lack of full perspective about the QMS implementation in the case of failure. The study results are based primarily on US insights that may not be applicable in other social contexts. However, it provides results that can be highly related to a certain context.


Adopting and implementing the Clinical Decision Support System (CDSS) technology is a critical element in an effort to improve national quality initiatives and evidence-based practice at the point of care. CDSS is envisioned to be a potential solution to many current challenges in the healthcare sphere, which includes information overload, practice improvement, eliminating treatment errors, and reducing medical consultation costs. However, the CDSS did not manage to achieve these goals to the desired levels and provide context-appropriate alerts, although integrated with the electronic health records (EHRs) . Clinica Clinical decision support systems (CDSS) are computer-based applications that analyze and intelligently filter data within electronic health records (EHRs) to assist providers, clinicians, administrative staff, and patients at the point of care. They comprise of several tools that filter through the tons of data and provide suggestions on the next steps in treatment . The CDSThe integration of CDSS enables in combining prescription information with patient information and provides alerts to patients when there are drug-drug interactions, drug-allergy contraindications, and other critical situations. In addition, it assists the providers in ordering medications, lab and imaging tests .While CDSS alerts are supposed to enhance patient safety by being the solution to adverse drug events and inappropriate dosage prescription, they are not functionally as effective as they ought to be. Also, alert fatigue in clinicians has been consistently on ECRI’s (Emergency Care Research Institute) top ten health technology hazards .The lack of efficacy of CDSS is due to alert fatigue, resulting from the repeated incurrence of irrelevant pop-ups or warnings related to the treatment. Alert fatigue is because CDSS can only access the patient information silos in the current EHR , 9. WhenFurthermore, CDSS is aimed to assist providers in arriving at diagnosis by providing suggestions regarding the treatment plan , 8. It aAlthough the purpose of CDSS is to enable better patient outcomes and reduce the burden on providers, this purpose is not being served adequately , 9. ThisBlockchain is a decentralized, distributed ledger technology (DLT), with members in the network denoted as nodes. The transactions made among them are recorded by every node in the network into a distributed ledger . All nodAll the confirmed and validated transaction blocks are hash linked from the origin block to the most current block represented in the There are two kinds of blockchain networks, which are public, permission-less blockchains and private, permissioned blockchains. The principal distinction between public and private blockchain platforms is that anyone can join the public platforms, while only authenticated users can join a private, permissioned blockchain framework. The popular examples of permission-less blockchain platforms include Bitcoin, Ethereum, and Litecoin, and those of private, permissioned blockchains include Hyperledger, Multichain, R3 Corda, and so on .With the limitations of CDSS above elucidated, this study aims to propose a conceptual model to enhance functionality of CDSS in order to improve patient outcomes and reduce cognitive burden on providers. The conceptual model aims to be formulated leveraging a private, permissioned blockchain framework, Hyperledger Fabric, to facilitate interoperability of patient health information and ensure its safety and privacy while being transacted in between healthcare systems.The following sections of the article provide a background on the Hyperledger Fabric and its components, elucidating the conceptual model, cite the reasons for selecting Hyperledger Fabric over other private, permissioned blockchain platforms, and demonstrate how the proposed model intends to work in a real-world scenario.Hyperledger is an open-source umbrella project, hosting several distributed ledger frameworks, tools, and libraries. It is a business-driven blockchain framework, which is built to help business organizations to transact through a private blockchain network by The Linux Foundation along with other collaborators .Hyperledger Fabric is one of the Hyperledger frameworks, which is a private, permissioned blockchain in which organizations can participate in data sharing .Membership service provider (MSP) serves as a certificate authority, trusted by all the members in the network. This entity validates the identity of an organization and authorizes its participation in the network  by issuiMembers in the Hyperledger Fabric communicate with each other through their nodes. Each member has three different kinds of nodes serving different functions.Client node. This is the end user or application, who or which needs information and initiates the transaction  sets, which includes the information on what could have been read or written onto the ledger had the transaction been executed. The endorsing peers now endorse or reject the transaction invocation based on the endorsement policy. If majority of the endorsement peers approve the transaction, the endorsement decision along with RW sets are sent back to the client.Organization H3 through its client application now will check for the endorsement, and if it is approved, it will be forwarded to the ordering service node in the network.The ordering service node verifies the endorsement of transaction, client identity, and orders and packages the information in the form of blocks in the order, which they are to be committed to the ledger. This node now disseminates the blocks of information to all the committing peers in the network.The committing peers validate the transaction and commit the blocks to the ledger in the order in which they are received.The word ‘data breach’ sends jitters among the individuals or organizations that deal with sensitive data or information. According to the report by Ponemon Institute and Verizon Data Breach Investigations, healthcare industry is more vulnerable to data breaches than any other sector , and neaGiven the importance of personal health information and the need to comply with regulations [The Health Insurance Portability and Accountability Act of 1996 (HIPAA) and General Data Protection Regulation (GDPR)] in place, privacy, security, and scalability of the health information exchange are of paramount importance. While there are multiple public and private blockchain platforms that provide similar advantages in terms of information exchange and data privacy, health care data transfer requires minimal latency with heightened security. This concoction and the criticality of medical information interchange are the driving factors behind choosing the Hyperledger Fabric among the other private, permissioned blockchain platforms. Also, according to the results published in the research , HyperleThe Hyperledger Fabric is a platform for distributed ledger solutions underpinned by a modular architecture delivering high degrees of confidentiality, resiliency, flexibility, and scalability. The architecture and design of Hyperledger Fabric makes it very suitable and effective platform to exchange vulnerable information like PHI.The Fabric with its malleable design ensures privacy and confidentiality of the transactions  among thThis flexibility in designing of Fabric allows creation of private data collections between a group of members where the transaction can be endorsed, validated, and committed to the private state of the ledger by the authorized peers in a subnetwork. The private transactions are broadcasted without ordering service node via a peer-to-peer gossip protocol, thereby ensuring privacy and confidentiality of the exclusive transaction from the members outside the sub-network in the same channel .The Fabric’s modular architecture and design provide ease of operation with plug-and-play features and furnish high performance, as there are specific nodes for specific purposes ensuring high transaction throughput and scalability , 25.Moreover, with the Fabric being a permissioned platform, only vetted, authenticated organizations can participate and transact in the channel .Let us consider a scenario, where a patient continues to visit a health care provider for a long time. The entire medical history records are stored in the EHR system (of the provider) and in the event of the patient being referred to a new specialist, the new provider would not have history on the patient’s medical condition in its entirety. In this case, the CDSS in the EHR of the specialist provider might recommend context inappropriate alerts due to incomplete patient information. This can potentially lead CDSS to fire inappropriate alerts and result in alert fatigue in physicians as well as ordering of duplicate tests and medications for the patients, thereby increasing the treatment costs , 8.The problem in the given scenario is not with the core functionality of CDSS as the alerts are based on patient information available in the EHR system. If the entire patient information is made available to the EHR of specialist provider, then the CDSS can potentially provide context appropriate alerts based on the entire patient history, in turn helping the patient in diagnosis and the treatment of the disease . With thThis article broadly talks about how Hyperledger serves as a potential solution to enhance interoperability, which, in turn, addresses issues related to CDSS. Blockchain has been a proven technology that other dependent lineups can be built on. This being a distributed ledger and an immutable transaction recorder, resistance to changes is natural and any updates can be traced back easily. We chose the Hyperledger Fabric and proposed a conceptual model on how information can be exchanged among independent hospitals or systems in a private and secured manner. This study starts off by listing out issues pertaining to CDSS, which were having an impact on the overall patient outcomes. This work then moves onto isolating the root cause that is, how interoperability amongst participating systems has been the core concern and how Hyperledger Fabric can be a viable solution in enhancing the fundamental functionality of CDSS. While the current article focuses on the conceptual aspects and provides a framework on how Hyperledger Fabric can aid CDSS, additional research work will be required when it comes to practical implementation, to address ground level application issues & deal with real-time scenarios.


This article was republished on November 15, 2021, to correct an unintentional coding error that led to pervasive minor inaccuracies in the manuscript. Specifically, in processing and merging multiple real-time data files from the Thai Ministry of Public Health, duplicate case records of dengue were created when a single record should have been in place. This led to over-counting of cases in many periods of time, an error that impacted forecast models and evaluation of the forecasts themselves. Please download this article again to view the correct version.


Material extrusion (MEX), more commonly known as fused deposition modelling (FDM/FFF), is one of the most widely used techniques in polymeric Additive Manufacturing (AM). This technology is increasingly present in fields such as engineering and medicine with polymeric materials, including additives of many types. Polylactic acid polymer (PLA) is one of the most widely used materials currently on the market for MEX technology. In addition to its ease of printing, it is a plastic of natural origin, biodegradable and supplants petroleum derivatives in many applications. However, the effect of ageing on the mechanical properties of PLA are still to be evaluated and understood. The main objective of this work is to investigate the effects of ageing of PLA samples on the tensile properties. To investigate the effect of ageing, the samples were tested periodically after exposure to fertilized soil for a period up to 6 months. In addition, some of the samples were chemically pre-treated to improve the surface quality, and the effect of ageing on the treated and untreated samples was also evaluated. This study showed that ultimate strength decreased with ageing from 46 to 36 MPa (22%), and it increased with treatment time in high percentages (even 40%) depending on the time of immersion in the solvent. However, this effect of the chemical treatment gradually disappeared, with the exception of the surface improvement obtained. Industry 4.0 is a global set of emerging technologies that establish a new industrial perspective. It has radically transformed production processes and systems with the adoption of enabling technologies such as additive manufacturing (AM). In this context, additive manufacturing offers agility and customer focus in any industry, enabling multi-material, free manufacturing and flexibility ,2.In the early 1990s, the inventor Stratasys developed a new method for additive manufacturing or 3D printing: Fused Filament Fabrication (FFF) or Fused Deposition Modelling (FDM). FDM technology is based on the creation of parts from the deposition of layers of extruded thermoplastic material on a heated platform . It is cHowever, it has one major disadvantage: the use of polymers, with a total annual production of 400 million tons of polymers in 2021 ,7. This For this purpose, the study of biodegradable polymers has shown a growing interest in this technology. Polylactic acid (PLA) is one of the most widely used materials that continues to be studied today. PLA is a natural polymer derived from renewable sources such as starch, a large carbohydrate that plants synthesize during photosynthesis. Bioplastics produced from this polymer have the characteristic of being a resin that can be injected, extruded and thermoformed . Thus, PDue to its biodegradability, barrier properties and biocompatibility, numerous applications have been found with this biopolymer, as it exhibits an unusually wide range of properties , from tFurthermore, the changes in properties during PLA biodegradation are very specific . Indeed,The failure processes of FDM-manufactured polymers are defined by the structural irregularity of the system, which is characterized by the presence of interfacial and interlayer bonds. The individual events involved in the development of failure and fracture can be too complicated to describe, especially if they have a complex microstructure such as PLA. Therefore, the study of the monolayers is proposed in this work.Consequently, this work aims to analyze the degradation of PLA parts manufactured by FDM exposed to fertilized soil over a period of 6 months. For this purpose, monolayers were used. These were manufactured, and some of them were treated with a chemical agent to improve their surface quality. Subsequently, tensile tests were carried out periodically, and the effect of the ageing of the material on the mechanical properties was evaluated in treated and untreated parts.An open-source test bench with a 0.4 mm diameter nozzle was used for processing specimens. Monolayers of FFF World’s Polylactic Acid (PLA) were fabricated, whose geometry and trajectories are shown in The manufacturing parameters used are given in 3, Laboquimia, Logroño, Spain), as shown in Once the parts were manufactured, they were weighed and immersed according to the variable immersion time [Ti] for 1 to 30 s in an organic solvent, chloroform (CHClFive samples of each type were tested the day after the treatments and considered as reference (ageing time = 0). Subsequently, the remaining samples were deposited in fertile soil with the characteristics shown in A contact profilometer, Mahr Perthometer PGK 120 , was used for microgeometric characterization. Also, image analysis was performed by a Hitachi SU1510 Scanning Electron Microscope  at low vacuum mode at 10 kV. A backscattered-electron (BSE) detector was used for imaging the surface of the samples.® AG-X . These tensile tests were achieved with a constant testing speed of 2 mm/s, as suggested in ISO 527 for standardization for molding and extrusion polymers [Mechanical tests were performed with the universal testing machine Shimadzupolymers . These tChemical treatments have been optimized in previous works for the improvement of surface quality . In thisIf the surface improvement is compared with other works in which the same procedure was applied, a much lower improvement is observed for the same period of time. This is probably due to the quantity and distribution of the isomers that form the PLA in each case, which cause a greater or lesser probability of crystallite formation. However, this improvement in surface roughness for such a short and simple treatment is very satisfactory.After 180 days, the surface quality was intact. However, chemically treated samples shrunk significantly. This effect is associated with the fact that the initially treated samples expanded due to the absorption of the chlorine present in the solvent used. There are several modes of fracture in polymeric materials, namely interlaminar delamination or interlayer fracture, intralaminar or interfacial cracking or fracture, and crack propagation through the pores generated by the process. Typically, the failure processes in all are time dependent, reflecting, at least in part, the viscoelastic nature of the mechanical response of the polymer.The main cause of failure in polymers is structural damage on a microscopic scale, such as microcracks. These are the result of impacts and internal stresses and are dangerous due to their undetectable nature and also due to the induced fragmentation of the structure, leading to reduced mechanical properties such as strength, stiffness and corrosion. Adding the layered manufacturing process increases these types of defects from the manufacturing process itself. These internal defects not only decrease the performance of the material, but also serve as catalysts for other damage, such as macrocracks, moisture swelling and corrosion. This microcrack, swollen by the action of chlorine, can be seen in When parts are subjected to mechanical testing, cracks initiate mainly on the surfaces of the parts and propagate through those microcracks or through bad interlayer and inter-face joints (between deposited filaments) that originate small pores in the interior. These pores are the ones that appear in greater proportion in solvent-treated samples, which causes greater crack propagation. Over time, this volatile solvent evaporates, causing the compaction of the samples to increase. This leads to a decrease in their volume, as can be seen in some of their dimensions in For all polymeric materials, the theoretical strength of the interfacial bonds is several orders of magnitude greater than the measured fracture stresses. This is accentuated in Additive Manufacturing processes, where in addition to crack defects that can produce significant local stress concentrations, there is a very strong influence from the interface paths and bonds that cause further concentrations. Therefore, by the nature of the manufacturing process, the material is not subjected to uniform stresses. A disproportionate amount of load is carried when stress is applied to a polymer sample, which can be sufficient to overcome the bond strength. This non-uniformity in stress is much more pronounced in amorphous polymers such as PLA, whereas treated parts exhibiting higher crystallinity should distribute stress more evenly. However, this does not occur as expected. Chain scission can occur at relatively low stresses in cross-linked or highly aligned polymers, but the mechanical response of isotropic polymers with a low cross-link density is governed by secondary bonds at low stresses. This means that many polymers yield before fracture at high stresses.Highly cross-linked polymers are incapable of large-scale viscoelastic deformation. Molecular chains overcome van der Waals forces, but it does not apply to cross-linked polymers, where the primary bonds between chain segments must be broken for these materials to deform . For thiUltimate fracture occurs in a zone where individual fibrils break and generate a microcrack, which is unstable if the redistributed stress is sufficient to break one or more neighboring fibrils. Fracture in a crack zone is usually initiated by particles from areas of missing material or impurities (inorganic dust trapped in the polymer) . The treAfter the linear fitting of the data in On the other hand, the elastic modulus (ε) behaves similarly to the maximum stress with similar settings . Thus, uAs can be seen in Other authors have studied the degradation process, taking into account different layer thicknesses, and came to the conclusion that the higher the layer height, the greater the mechanical degradation due to the higher proportion of air voids or porosities . These vThe average decrease in strength in all the untreated samples was around 25%, while in the chemically treated samples, an increase in strength of more than 50% was obtained in all cases, reaching 100% in some of them. This phenomenon should be examined in other environments and additionally with PLA filaments from different manufacturers. No plastic deformation was observed in the chemically untreated specimens . If we aIn PLA, a creep zone usually forms at the crack tip. However, shear creep produces a Dugdale-type band creep zone ahead of the crack tip. Of the two creep mechanisms in the untreated PLA, crazing is rather more likely ahead of the crack tip, due to the triaxle stress state. For this reason, these samples show a more brittle and continuous fracture . HoweverA common problem in polymers under stress in a chemical environment is stress corrosion cracking (SCC), for example in polyolefin pipes, where it is often observed as a colony of microcracks within a degraded polymer surface layer. This can resemble what occurs in parts that have been chemically treated for surface improvement and often results in multiple crack initiations due to individual pore growth.The ageing effect is also observed in the type of fracture. The high elasticity obtained in solvent-treated samples is gradually lost over time. Thus, the continuous and brittle fracture of the untreated samples is obtained again, although it is continuous. The continuity of the fracture is due to the inter-face bond that is built up after the application of solvents.The surface quality of parts manufactured by fused deposition modelling using chemical baths has been improved. Specifically, chloroform has been used as a solvent to improve the roughness (Ra) by almost 50% in only 30 s of treatment.The impact of ageing on the mechanical properties of FDM printed parts with PLA was analyzed by experimental tests. It was observed that PLA parts degrade with ageing on the ground, and this was manifested in a decrease in tensile mechanical properties. The trend continued to decrease during the whole period of the experiment (6 months).It was also interesting to see the worsening of the mechanical strength when the parts were subjected to chemical baths. However, these parts increased their breaking strength value as time went by when they were exposed to a supposed degradation. This seems to indicate that PLA, whose structure was affected by the baths, recovers its properties. Although the treatment of aged parts improved the strength of the specimens, it is interesting to note that the tendency was to obtain a value similar to that of untreated and unaged specimens. This indicates that the treatment was clearly lost. Thus, less rough parts can be obtained, and after a few months they will have recovered the mechanical properties lost during the solvent bath. The influence of immersion time on the surface improvement as well as on the tensile strength, and the influence of ageing time on the mechanical properties have been demonstrated.The experiments were conducted on standardized parts for tensile tests to give an idea of the part’s behavior evolution with this type of process and to be able to compare it with other studies. Furthermore, this study leads to the consideration that the moment of testing throughout the life cycle of a part is decisive; thus, the authors consider this to be one more variable to be considered for all studies, as the material or layer height is indicated.