bluuebunny/crossref_metadata_2025_split huggingface dataset:
Waste of Research. Is There Any Solution? “Beginning from the Beginning” instead of “Beginning from the End”
Authors: Amirfakhryan Hamideh 
Published: June 2020

There have always been challenges concerning tackling knowledge to practice. It is estimated that 85% of the investment in health research are wasted. Due to low quality, not all systematic review and meta-analysis are placed at the top of the hierarchy of evidence. Many individual clinical trials do not have the essential standards; therefore, conducting systematic reviews based on these low-quality individual studies is unreliable as they cannot be applied in healthcare decision-making and lead to resource waste. To overcome this great issue, several organizations have been worked hard to improve data extraction from only well-developed individual studies. However, it is not sufficient.
It is time to stop and look back all years behind. It is time to reconsider our efforts to make the best conclusion in order to prohibit the huge waste of energy, time, and resources. The old viewpoint “the Beginning from the End” must be replaced with the new one “the Beginning from the Beginning”. It means, we must do all struggles to conduct clinical trials in a standard high-quality format from the beginning as much as we could. Although, it does not seem easy, it might be possible by funding a high discipline, well-respected organization that is engaged in this critical issue. The supposed organization must define standards, flexible criteria for clinical trials, and all investigators must perform clinical trials under the supervision of this organization. Providing a considerable financial resource to grant the researches of the low- and middle-income countries to do clinical trials based on the designed protocol, considering an independent, high discipline journal for publishing well-conducted clinical trials regardless of their results, teaching researchers, considering another efficient policy to rank the journals rather than “impact factor” could help achieve this far-reach goal.
Esquemas de argumentação para a interpretação da lei
Authors: Macagno Fabrizio 
Published: June 2020

RESUMO:Neste artigo demonstra-se como os esquemas argumentativos (esquemas que representam argumentos refutáveis, combinados com perguntas críticas correspondentes), podem ser usados para representar a estrutura lógica dos vários tipos de argumentos reconhecidos como fundamentais na interpretação da lei por Tarello (1980). Defende-se que o processo de interpretação da lei tem uma estrutura argumentativa distinta na qual a conclusão, nomeadamente o significado disputável ou questionado atribuído a uma fonte jurídica, é uma afirmação que necessita ser respaldada por argumentos refutáveis a favor ou contra. Esta transformação de argumentos de interpretação numa estrutura de esquemas argumentativos é analisada em detalhe em dois argumentos, o argumento psicológico e o argumento a contrario. A natureza refutável de cada esquema é demonstrada por meio de questões críticas que identificam as condições padrão para a aceitação de argumentos interpretativos e fornecem um método para avaliar a força ou a fraqueza de um determinado argumento. ABSTRACT:In this paper, the logical structures of the interpretative arguments summarizing the various interpretative canons considered fundamental by Tarello (1980) are represented by argumentation schemes, namely patterns of defeasible arguments combined with their corresponding critical questions. The process of statutory interpretation is shown to have a specific argumentative structure where the conclusion corresponds to the disputed or questionable meaning attributed to a legal source and needs to be supported and attacked through defeasible arguments. This translation of interpretative arguments into argumentation schemes is illustrated in detail considering two specific arguments, the psychological and the a contrario arguments. The defeasibility conditions of each scheme are summarized in a set of critical questions, which identify the default conditions for accepting interpretative arguments and provide a method for evaluating a given argument as weak or strong.
Editorial da seção especial "Terceirização e Reforma Trabalhista"
Authors: Basualdo Victoria , Silva Sayonara Grillo Coutinho Leonardo da , Carelli Rodrigo Da Lacerda 
Published: June 2020

RESUMO: Editorial da seção especial "Terceirização e Reforma Trabaalhista"ABSTRACT:Editorial (Introduction to the Special Issue "Tercerização e Reforma Trabalhista")
Leveraging Walking Performance to Understand Work Fatigue Among Young Adults: Mixed-Methods Study
Authors: Yan Xinghui , Rau Pei-Luen Patrick , Zhong Runting 
Published: June 2020

Background
Work fatigue negatively impacts personal health in the long term. Prior research has indicated the possibility of leveraging both walking parameters and perceptual measures to assess a person’s fatigue status. However, an effective and ubiquitous approach to assessing work fatigue in young adults remains unexplored.

Objective
The goals of this paper were to (1) explore how walking rhythms and multiple streams of data, including reaction time, self-reports, and an activity diary, reflect work-induced fatigue in the lab setting; (2) identify the relationship between objective performance and subjective perception in indicating fatigue status and fatigability; and (3) propose a mobile-based assessment for work-induced fatigue that uses multiple measurements.

Methods
We conducted a 2-day in-lab study to measure participants’ fatigue status using multiple measurements, including the stair climb test (SCT), the 6-minute walk test (6MWT), and the reaction time test. Both the SCT and the 6MWT were conducted at different points in time and under 2 conditions (measurement time, including prior to and after work, and pace, including normal and fast). Participants reported their fatigue perception through questionnaires completed before conducting walking tests and in an activity diary recorded over a week. Walking performance data were collected by a smartphone with a built-in 3-axis accelerometer. To examine the effect of fatigability on walking performance, we first clustered participants into 2 groups based on their reported mental fatigue level in the entry surveys and then compared their walking performance using a generalized linear model (GLM). The reaction time was examined using a 2-way repeated-measures GLM. We conducted semistructured interviews to understand participants’ fatigue perception after each day’s walking tests.

Results
All participants (N=26; mean age 24.68 years) were divided into 2 groups—the fatigue-sensitive group (11/26, 42%) and the fatigue-nonsensitive group (15/26, 58%)—based on their mental subscores from 3 entry surveys: Fatigue Scale-14, Three-Dimensional Work Fatigue Inventory, and Fatigue Self-Assessment Scale (FSAS). The fatigue-sensitive group reported a significantly higher FSAS score in the before-work setting (t50=–3.361; P=.001). The fatigue-sensitive group covered fewer steps than the fatigue-nonsensitive group (β1=–0.099; SE 0.019; t1=–5.323; P<.001) and had a higher step-to-step time variability in the 6MWT (β1=9.61 × 10–4; t1=2.329; P=.02). No strong correlation between subjective and objective measurements was observed in the study.

Conclusions
Walking parameters, including step counts and step-to-step time variability, and some selected scales (eg, FSAS) were found to reflect participants’ work-induced fatigue. Overall, our work suggests the opportunity of employing mobile-based walking measurements to indicate work fatigue among young adults.
Effective Gamification of the Stop-Signal Task: Two Controlled Laboratory Experiments
Authors: Friehs Maximilian Achim , Dechant Martin , Vedress Sarah , Frings Christian , Mandryk Regan Lee 
Published: June 2020

Background
A lack of ability to inhibit prepotent responses, or more generally a lack of impulse control, is associated with several disorders such as attention-deficit/hyperactivity disorder and schizophrenia as well as general damage to the prefrontal cortex. A stop-signal task (SST) is a reliable and established measure of response inhibition. However, using the SST as an objective assessment in diagnostic or research-focused settings places significant stress on participants as the task itself requires concentration and cognitive effort and is not particularly engaging. This can lead to decreased motivation to follow task instructions and poor data quality, which can affect assessment efficacy and might increase drop-out rates. Gamification—the application of game-based elements in nongame settings—has shown to improve engaged attention to a cognitive task, thus increasing participant motivation and data quality.

Objective
This study aims to design a gamified SST that improves participants’ engagement and validate this gamified SST against a standard SST.

Methods
We described the design of our gamified SST and reported on 2 separate studies that aim to validate the gamified SST relative to a standard SST. In study 1, a within-subject design was used to compare the performance of the SST and a stop-signal game (SSG). In study 2, we added eye tracking to the procedure to determine if overt attention was affected and aimed to replicate the findings from study 1 in a between-subjects design. Furthermore, in both studies, flow and motivational experiences were measured.

Results
In contrast, the behavioral performance was comparable between the tasks (P<.87; BF01=2.87), and the experience of flow and intrinsic motivation were rated higher in the SSG group, although this difference was not significant.

Conclusions
Overall, our findings provide evidence that the gamification of SST is possible and that the SSG is enjoyed more. Thus, when participant engagement is critical, we recommend using the SSG instead of the SST.
Mapping Behavioral Health Serious Game Interventions for Adults With Chronic Illness: Scoping Review
Authors: Thomas Teresa Hagan , Sivakumar Varshini , Babichenko Dmitriy , Grieve Victoria L B , Klem Mary Lou 
Published: June 2020

Background
Serious games for health are increasingly being used to address health outcomes in patients with chronic illnesses. These studies vary in their study designs, patient populations, frameworks, outcome variables, and degree of specificity of the serious game intervention.

Objective
This scoping review aims to clarify the conceptual features of the existing research related to serious games designed to improve cognitive and behavioral outcomes in adults with chronic illness.

Methods
We applied the Preferred Reporting Items of Systematic Reviews and Meta-Analysis for scoping reviews methodology, including an a priori research question. We searched 4 electronic databases to identify articles published through November 2019. Inclusion criteria encompassed (1) adults 18 years or older; (2) patients with a diagnosis of chronic illness; (3) a serious game intervention; and (4) defined patient outcomes that assess patients’ behavioral, cognitive, or health outcomes.

Results
Of the 3305 articles identified, 38 were included in the review. We charted and analyzed the theoretical frameworks, key concepts, and outcome variables of these studies with summaries of features across articles. The majority of studies used a randomized controlled trial design (23/38, 61%), included a custom serious game intervention (22/38, 58%), and lacked a theoretical framework (25/38, 66%). Common outcome variables included quality of life (16/38, 42%), mood (15/38, 39%), cognitive function (13/38, 34%), symptoms (12/38, 32%), and physical activity (9/38, 24%). Key differences between studies included whether or not serious games aimed to train versus teach patients, be widely accessible versus tailored interventions, or replace versus complement current treatments.

Conclusions
This scoping review defines the current landscape of research in serious games for health research targeting behavioral and cognitive outcomes in adults with chronic disease. Studies have addressed a variety of patient populations and diverse patient outcomes. Researchers wanting to build on the current research should integrate theoretical frameworks into the design of the intervention and trial to more clearly articulate the active ingredients and mechanisms of serious games.
Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review
Authors: Adly Aya Sedky , Adly Afnan Sedky , Adly Mahmoud Sedky 
Published: June 2020

Background
Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease.

Objective
The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide.

Methods
We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19.

Results
Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine.

Conclusions
We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.
Complementing the US Food and Drug Administration Adverse Event Reporting System With Adverse Drug Reaction Reporting From Social Media: Comparative Analysis
Authors: Zhou Zeyun , Hultgren Kyle Emerson 
Published: June 2020

BackgroundAdverse drug reactions (ADRs) can occur any time someone uses a medication. ADRs are systematically tracked and cataloged, with varying degrees of success, in order to better understand their etiology and develop methods of prevention. The US Food and Drug Administration (FDA) has developed the FDA Adverse Event Reporting System (FAERS) for this purpose. FAERS collects information from myriad sources, but the primary reporters have traditionally been medical professionals and pharmacovigilance data from manufacturers. Recent studies suggest that information shared publicly on social media platforms related to medication use could be of benefit in complementing FAERS data in order to have a richer picture of how medications are actually being used and the experiences people are having across large populations.ObjectiveThe aim of this study is to validate the accuracy and precision of social media methodology and conduct evaluations of Twitter ADR reporting for commonly used pharmaceutical agents.MethodsADR data from the 10 most prescribed medications according to pharmacy claims data were collected from both FAERS and Twitter. In order to obtain data from FAERS, the SafeRx database, a curated collection of FAERS data, was used to collect data from March 1, 2016, to March 31, 2017. Twitter data were manually scraped during the same time period to extract similar data using an algorithm designed to minimize noise and false signals in social media data.ResultsA total of 40,539 FAERS ADR reports were obtained via SafeRx and more than 40,000 tweets containing the drug names were obtained from Twitter’s Advanced Search engine. While the FAERS data were specific to ADRs, the Twitter data were more limited. Only hydrocodone/acetaminophen, prednisone, amoxicillin, gabapentin, and metformin had a sufficient volume of ADR content for review and comparison. For metformin, diarrhea was the side effect that resulted in no difference between the two platforms (P=.30). For hydrocodone/acetaminophen, ineffectiveness as an ADR that resulted in no difference (P=.60). For gabapentin, there were no differences in terms of the ADRs ineffectiveness and fatigue (P=.15 and P=.67, respectively). For amoxicillin, hypersensitivity, nausea, and rash shared similar profiles between platforms (P=.35, P=.05, and P=.31, respectively).ConclusionsFAERS and Twitter shared similarities in types of data reported and a few unique items to each data set as well. The use of Twitter as an ADR pharmacovigilance platform should continue to be studied as a unique and complementary source of information rather than a validation tool of existing ADR databases.
Developing a Mobile App for Monitoring Medical Record Changes Using Blockchain: Development and Usability Study
Authors: Sung MinDong , Park SungJun , Jung Sungjae , Lee Eunsol , Lee Jaehoon , Park Yu Rang 
Published: June 2020

Background
Although we are living in an era of transparency, medical documents are often still difficult to access. Blockchain technology allows records to be both immutable and transparent.

Objective
Using blockchain technology, the aim of this study was to develop a medical document monitoring system that informs patients of changes to their medical documents. We then examined whether patients can effectively verify the monitoring of their primary care clinical medical records in a system based on blockchain technology.

Methods
We enrolled participants who visited two primary care clinics in Korea. Three substudies were performed: (1) a survey of the recognition of blockchain medical records changes and the digital literacy of participants; (2) an observational study on participants using the blockchain-based mobile alert app; and (3) a usability survey study. The participants’ medical documents were profiled with HL7 Fast Healthcare Interoperability Resources, hashed, and transacted to the blockchain. The app checked the changes in the documents by querying the blockchain.

Results
A total of 70 participants were enrolled in this study. Considering their recognition of changes to their medical records, participants tended to not allow these changes. Participants also generally expressed a desire for a medical record monitoring system. Concerning digital literacy, most questions were answered with “good,” indicating fair digital literacy. In the second survey, only 44 participants—those who logged into the app more than once and used the app for more than 28 days—were included in the analysis to determine whether they exhibited usage patterns. The app was accessed a mean of 5.1 (SD 2.6) times for 33.6 (SD 10.0) days. The mean System Usability Scale score was 63.21 (SD 25.06), which indicated satisfactory usability.

Conclusions
Patients showed great interest in a blockchain-based system to monitor changes in their medical records. The blockchain system is useful for informing patients of changes in their records via the app without uploading the medical record itself to the network. This ensures the transparency of medical records as well as patient empowerment.
Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study
Authors: Knitza Johannes , Simon David , Lambrecht Antonia , Raab Christina , Tascilar Koray , Hagen Melanie , Kleyer Arnd , Bayat Sara , Derungs Adrian , Amft Oliver , Schett Georg , Hueber Axel J 
Published: June 2020

Background
Mobile health (mHealth) defines the support and practice of health care using mobile devices and promises to improve the current treatment situation of patients with chronic diseases. Little is known about mHealth usage and digital preferences of patients with chronic rheumatic diseases.

Objective
The aim of the study was to explore mHealth usage, preferences, barriers, and eHealth literacy reported by German patients with rheumatic diseases.

Methods
Between December 2018 and January 2019, patients (recruited consecutively) with rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis were asked to complete a paper-based survey. The survey included questions on sociodemographics, health characteristics, mHealth usage, eHealth literacy using eHealth Literacy Scale (eHEALS), and communication and information preferences.

Results
Of the patients (N=193) who completed the survey, 176 patients (91.2%) regularly used a smartphone, and 89 patients (46.1%) regularly used social media. Patients (132/193, 68.4%) believed that using medical apps could be beneficial for their own health. Out of 193 patients, only 8 (4.1%) were currently using medical apps, and only 22 patients (11.4%) stated that they knew useful rheumatology websites/mobile apps. Nearly all patients (188/193, 97.4%) would agree to share their mobile app data for research purposes. Out of 193 patients, 129 (66.8%) would regularly enter data using an app, and 146 patients (75.6%) would welcome official mobile app recommendations from the national rheumatology society. The preferred duration for data entry was not more than 15 minutes (110/193, 57.0%), and the preferred frequency was weekly (59/193, 30.6%). Medication information was the most desired app feature (150/193, 77.7%). Internet was the most frequently utilized source of information (144/193, 74.6%). The mean eHealth literacy was low (26.3/40) and was positively correlated with younger age, app use, belief in benefit of using medical apps, and current internet use to obtain health information.

Conclusions
Patients with rheumatic diseases are very eager to use mHealth technologies to better understand their chronic diseases. This open-mindedness is counterbalanced by low mHealth usage and competency. Personalized mHealth solutions and clear implementation recommendations are needed to realize the full potential of mHealth in rheumatology.