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2.
Int J Popul Data Sci ; 7(1): 1732, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35520098

RESUMO

The Population Health Research Network (PHRN) is an Australian national data linkage infrastructure that links a wide range of health and human services data in privacy-preserving ways. The data linkage infrastructure enables researchers to apply for access to routinely collected, linked, administrative data from the six states and two territories which make up the Commonwealth of Australia, as well as data collected by the Australian Government. The PHRN is a distributed network where data is collected and managed at the respective jurisdictional and/or cross-jurisdictional levels. As a result, access to linked data from multiple jurisdictions requires complex approval processes. This paper describes Australia's approach to enabling access to linked data from multiple jurisdictions. It covers the identification of, and agreement to, a minimum set of data items to be included in a unified national application form, the development and implementation of a national online application system and the harmonisation of business processes for cross-jurisdictional research projects. Utilisation of the online application system and the ongoing challenges of data linkage across jurisdictions are discussed. Changes to the data custodian and ethics committee approval criteria were out of scope for this project.


Assuntos
Armazenamento e Recuperação da Informação , Web Semântica , Austrália/epidemiologia , Coleta de Dados , Governo , Humanos
3.
Vet Rec ; 190(9): 342, 2022 May.
Artigo em Inglês | MEDLINE | ID: mdl-35521852
6.
PLoS One ; 17(5): e0267171, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35500002

RESUMO

Open source software (OSS) has become one of the modern software development methods. OSS is mainly developed by developers, volunteers, and users all over the world, but its reliability has been widely questioned. When OSS faults are detected, volunteers or users send them to developers by email or network. After the developer confirms the fault, it will be randomly assigned to the debugger who may be a developer, a volunteer, or a user. These open source community contributors also have the phenomenon of learning when removing faults. When the detected faults are removed, the number of introduced faults decreases gradually. Therefore, this study proposes a software reliability model with the decreasing trend of fault introduction in the process of OSS development and testing. The validity of the proposed model and the accuracy of estimating residual faults are verified by experiments. The proposed model can be used to evaluate the reliability and predict the remaining faults in the actual OSS development and testing process.


Assuntos
Software , Coleta de Dados , Humanos , Reprodutibilidade dos Testes
7.
Comput Math Methods Med ; 2022: 8040622, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35502414

RESUMO

Data mining is a method that is used to find data that are precise, previously uncertain, and logical values from a comprehensive set of information. Data mining is used as a tool for determining the accuracy of classifications of data obtained in the field of bioinformatics by using different algorithm approaches. In this study, the data mining method was used to classify the accuracy of different algorithms and predict the types of compulsive behavior of patients with obsessive compulsive disorder. Data collected from a total of 164 people, 70 males and 94 females, were analyzed. The age range of the people participating in the study was between 7 and 73, and the calculated mean age was 32.4. Data about sociodemographic characteristics, course of disease, treatments, family histories, obsession, and compulsion types of the participants were collected through data collection instruments. Classification algorithm methods found in WEKA software were chosen to process the data. The effect of the types of obsession on the types of compulsion was determined using regression models. The levels of success of the generated models were compared. The results of the study demonstrated the presence of a moderate positive correlation (.35) between these two variables. According to the coefficient of determination, obsession explained 11% of the variance in compulsion. These findings supported the established hypothesis that the effect of the types of obsession was effective on the types of compulsion.


Assuntos
Transtorno Obsessivo-Compulsivo , Adulto , Comportamento Compulsivo , Coleta de Dados , Mineração de Dados , Feminino , Humanos , Masculino , Comportamento Obsessivo
8.
JMIR Mhealth Uhealth ; 10(5): e30517, 2022 May 02.
Artigo em Inglês | MEDLINE | ID: mdl-35499858

RESUMO

BACKGROUND: Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. OBJECTIVE: The objective of this paper was to present a narrative review of the existing literature about lifelogging over the past decade. To achieve this goal, we analyzed lifelogging applications used to retrieve relevant information from daily digital data, some of them with the purpose of monitoring and assisting people with memory issues and others designed for memory augmentation. We aimed for this review to be used by researchers to obtain a broad idea of the type of data used, methodologies, and applications available in this research field. METHODS: We followed a narrative review methodology to conduct a comprehensive search for relevant publications in Google Scholar and Scopus databases using lifelog topic-related keywords. A total of 411 publications were retrieved and screened. Of these 411 publications, 114 (27.7%) publications were fully reviewed. In addition, 30 publications were manually included based on our bibliographical knowledge of this research field. RESULTS: From the 144 reviewed publications, a total of 113 (78.5%) were selected and included in this narrative review based on content analysis. The findings of this narrative review suggest that lifelogs are prone to become powerful tools to retrieve memories or increase knowledge about an individual's experiences or behaviors. Several computational tools are already available for a considerable range of applications. These tools use multimodal data of different natures, with visual lifelogs being one of the most used and rich sources of information. Different approaches and algorithms to process these data are currently in use, as this review will unravel. Moreover, we identified several open questions and possible lines of investigation in lifelogging. CONCLUSIONS: The use of personal lifelogs can be beneficial to improve the quality of our life, as they can serve as tools for memory augmentation or for providing support to people with memory issues. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories that can be potentially used as surrogate memory. Through this narrative review, we understand that contextual information can be extracted from lifelogs, which provides an understanding of the daily life of a person based on events, experiences, and behaviors.


Assuntos
Smartphone , Dispositivos Eletrônicos Vestíveis , Coleta de Dados , Atenção à Saúde , Exercício Físico , Humanos
9.
World Neurosurg ; 161: 245-250, 2022 May.
Artigo em Inglês | MEDLINE | ID: mdl-35505541

RESUMO

It is essential for any epidemiologic and clinical investigation to determine the appropriate covariates for which to ascertain measures and subsequently model. A number of recent articles have sought to elucidate covariate selection in the context of data analysis. Unfortunately, few articles characterize covariate selection in the context of data collection and discuss their principles under the assumption that data are measured and available for analyses. Additionally, many articles delineating the appropriate principles use jargon that may be inaccessible to the audiences that need to understand them most. Considering these gaps, this paper first seeks to put forth a simple foundational guide to primary data collection by explaining four sets of covariates for which to ascertain measures: 1) all covariates that cause both the exposure and outcome; 2) selected covariates that cause the exposure; 3) selected covariates that cause the outcome; and 4) relevant sociodemographic and baseline covariates. To the extent possible, this paper attempts to communicate these principles clearly and in the absence of advanced causal inference terminology. Finally, this paper provides a conceptual framework for covariate inclusion and exclusion with respect to data analysis and regression modeling. Specifically, this framework suggests that regression models 1) include all known common cause covariates; 2) include all sociodemographic covariates; 3) exclude any covariate that is known to be both a consequence of the exposure and cause of the outcome; and 4) generally, for every term included in the statistical model, there should be at least 10 observations in the data set.


Assuntos
Modelos Estatísticos , Neurocirurgiões , Simulação por Computador , Coleta de Dados , Humanos
10.
J Trauma Nurs ; 29(3): 158-162, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35536345

RESUMO

BACKGROUND: Data validation is important in maintaining the high-quality data necessary for trauma programs and research. Most existing guidance focuses on trauma center-level data validation, but validation from a broader level (region, state) may also be a helpful tool. OBJECTIVE: The purpose of this project is to improve data collection and submission at the local, regional, and state levels by performing logic-based data validation. METHODS: Logic edits were identified and accuracy rates were tracked quarterly, as measures were taken to improve accuracy. Following completion of Phase 1 of validation, Phase 2 was initiated to include both new fields and fields from Phase 1 that did not meet the accuracy goal. Data from Phase 2 were then compared with data from the state trauma registry. RESULTS: In both Phase 1 and Phase 2, five of the seven data fields validated reached 90% accuracy by the end of the respective project phase. The project facilitated registrar education and pursuit of data collection solutions in registry software. Systemic issues were identified at a higher level that had not been noticed at the trauma center level. DISCUSSION: Robust data validation is critical for an accurate trauma registry. Engaging higher-level organizations, like trauma regions, provides new perspective in data validation. CONCLUSION: This regional data validation approach provided additional value beyond usual center-level data validation.


Assuntos
Centros de Traumatologia , Coleta de Dados , Humanos , Sistema de Registros
11.
J Med Internet Res ; 24(5): e31810, 2022 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-35536633

RESUMO

BACKGROUND: Symptom checkers are digital tools assisting laypersons in self-assessing the urgency and potential causes of their medical complaints. They are widely used but face concerns from both patients and health care professionals, especially regarding their accuracy. A 2015 landmark study substantiated these concerns using case vignettes to demonstrate that symptom checkers commonly err in their triage assessment. OBJECTIVE: This study aims to revisit the landmark index study to investigate whether and how symptom checkers' capabilities have evolved since 2015 and how they currently compare with laypersons' stand-alone triage appraisal. METHODS: In early 2020, we searched for smartphone and web-based applications providing triage advice. We evaluated these apps on the same 45 case vignettes as the index study. Using descriptive statistics, we compared our findings with those of the index study and with publicly available data on laypersons' triage capability. RESULTS: We retrieved 22 symptom checkers providing triage advice. The median triage accuracy in 2020 (55.8%, IQR 15.1%) was close to that in 2015 (59.1%, IQR 15.5%). The apps in 2020 were less risk averse (odds 1.11:1, the ratio of overtriage errors to undertriage errors) than those in 2015 (odds 2.82:1), missing >40% of emergencies. Few apps outperformed laypersons in either deciding whether emergency care was required or whether self-care was sufficient. No apps outperformed the laypersons on both decisions. CONCLUSIONS: Triage performance of symptom checkers has, on average, not improved over the course of 5 years. It decreased in 2 use cases (advice on when emergency care is required and when no health care is needed for the moment). However, triage capability varies widely within the sample of symptom checkers. Whether it is beneficial to seek advice from symptom checkers depends on the app chosen and on the specific question to be answered. Future research should develop resources (eg, case vignette repositories) to audit the capabilities of symptom checkers continuously and independently and provide guidance on when and to whom they should be recommended.


Assuntos
Serviços Médicos de Emergência , Aplicativos Móveis , Coleta de Dados , Seguimentos , Humanos , Autocuidado , Triagem
13.
Cien Saude Colet ; 27(5): 1813-1826, 2022 May.
Artigo em Português | MEDLINE | ID: mdl-35544811

RESUMO

The scope of this study is to analyze the specificities of conception and execution of the different modalities of online focus groups (OFGs), a qualitative technique that is an alternative to a traditional focus group, due to the social distancing required by the COVID-19 pandemic. An integrative literature review was conducted in PubMed Central and BVS. National and international studies published in the last 10 years that describe and discuss OFGs were included. A total of 291 articles were identified and 24 were included after evaluation in stages. Four OFG modalities were found: synchronous or asynchronous by writing; synchronous by video/audio or audio. The OFG was used to research different health topics. The same platform can be used for realizing different OFG modalities, guaranteeing the participants' security and anonymity. The lack of a real-life atmosphere can impact participant engagement, but it can be resolved. An OFG can produce quality data, save time and expense, expand the participation of people who are geographically dispersed, but limit those with restricted internet access. This study can help researchers who intend to choose anOFG modality. Studies that assess the limits of OFGs in Brazil are suggested, as well those which address the asynchronous OFG by audio.


Objetiva-se analisar especificidades da concepção e realização das modalidades de grupo focal on-line (GFO), técnica qualitativa alternativa ao grupo focal tradicional frente ao distanciamento físico imposto pela pandemia de COVID-19. Realizou-se uma revisão integrativa da literatura nas bases PubMed Central e BVS. Foram identificados 291 artigos, a inclusão de 24 após avaliação por etapas. Foram identificados 291 artigos. Após avaliação por etapas, foram incluídos 24 artigos nacionais e internacionais dos últimos dez anos que descrevem e discutem a realização do GFO. As modalidades de GFO encontradas foram: síncrono ou assíncrono por escrito; síncrono por vídeo/áudio ou áudio. O GFO foi realizado em variadas pesquisas do campo da saúde. Uma mesma ferramenta pode ser usada para diferentes modalidades, garantindo a segurança dos participantes e o anonimato. A falta de atmosfera de vida real pode impactar o engajamento dos participantes, uma limitação manejável. As modalidades de GFO podem produzir dados de qualidade, economizar tempo e custo, ampliar a participação de sujeitos dispersos geograficamente, mas limitar em relação aos que têm dificuldades de acesso à internet. Este estudo auxilia pesquisadores na escolha de uma modalidade de GFO. Sugere-se pesquisas que avaliem os limites do GFO no Brasil e que abordem a modalidade assíncrona por áudio.


Assuntos
COVID-19 , Pandemias , Coleta de Dados , Grupos Focais , Humanos , Pesquisa Qualitativa
14.
Trop Anim Health Prod ; 54(3): 181, 2022 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-35523908

RESUMO

Laying hens on the free-range systems are susceptible to challenging situations in relation to the rearing environment. Therefore, this work evaluated how solar radiation influences the behavior of laying hens raised in a free-range system, in the Brazilian Savanna. The activities included data collection of meteorological variables and behavioral analysis of 300 commercial laying hens in relation to the frequency of use of indoor and outdoor areas of rearing housing. The solar radiation is the main factor that directly affects the heat gain of production animals, in this experiment had a high amplitude during all day, going from 33.42 to 756.98 W m-2. It was observed that the highest frequency of 79% and 91% use of the barn areas by the hens was at 8 am and 4 pm, respectively. The internal area of the housing was more used by hens 87% and 68% at 12 h and 14 h, respectively. Hens were not observed in the paddocks at noon and 2 pm. Hens spend more than 6 h of the day inside the housing to provide shelter from solar radiation. Which the conclusion the solar radiation influences the behavior of laying hens, at times of the day of the higher incidence of radiation, and high air and global temperatures, it was not observed the presence of hens in the external areas of the housing, especially with the use of the paddocks; at these times the hens seek shelter inside the housing to get away from the incidence of direct solar radiation.


Assuntos
Galinhas , Abrigo para Animais , Criação de Animais Domésticos , Bem-Estar do Animal , Animais , Brasil , Coleta de Dados , Meio Ambiente , Feminino
15.
Sci Rep ; 12(1): 7648, 2022 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-35538130

RESUMO

Technological advances and data availability have enabled artificial intelligence-driven tools that can increasingly successfully assist in identifying species from images. Especially within citizen science, an emerging source of information filling the knowledge gaps needed to solve the biodiversity crisis, such tools can allow participants to recognize and report more poorly known species. This can be an important tool in addressing the substantial taxonomic bias in biodiversity data, where broadly recognized, charismatic species are highly over-represented. Meanwhile, the recognition models are trained using the same biased data, so it is important to consider what additional images are needed to improve recognition models. In this study, we investigated how the amount of training data influenced the performance of species recognition models for various taxa. We utilized a large citizen science dataset collected in Norway, where images are added independently from identification. We demonstrate that while adding images of currently under-represented taxa will generally improve recognition models more, there are important deviations from this general pattern. Thus, a more focused prioritization of data collection beyond the basic paradigm that "more is better" is likely to significantly improve species recognition models and advance the representativeness of biodiversity data.


Assuntos
Inteligência Artificial , Ciência do Cidadão , Biodiversidade , Coleta de Dados , Humanos , Noruega
16.
Stat Med ; 41(10): 1797-1814, 2022 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-35403735

RESUMO

Effect decomposition is a critical technique for mechanism investigation in settings with multiple causally ordered mediators. Causal mediation analysis is a standard method for effect decomposition, but the assumptions required for the identification process are extremely strong. Moreover, mediation analysis focuses on addressing mediating mechanisms rather than interacting mechanisms. Mediation and interaction for mediators both contribute to the occurrence of disease, and therefore unifying mediation and interaction in effect decomposition is important to causal mechanism investigation. By extending the framework of controlled direct effects, this study proposes the effect attributable to mediators (EAM) as a novel measure for effect decomposition. For policymaking, EAM represents how much an effect can be eliminated by setting mediators to certain values. From the perspective of mechanism investigation, EAM contains information about how much a particular mediator or set of mediators is involved in the causal mechanism through mediation, interaction, or both. EAM is more appropriate than the conventional path-specific effect for application in clinical or medical studies. The assumptions of EAM for identification are considerably weaker than those of causal mediation analysis. We develop a semiparametric estimator of EAM with robustness to model misspecification. The asymptotic property is fully realized. We applied EAM to assess the magnitude of the effect of hepatitis C virus infection on mortality, which was eliminated by controlling alanine aminotransferase and treating hepatocellular carcinoma.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Complexo Mediador/fisiologia , Carcinoma Hepatocelular/etiologia , Causalidade , Coleta de Dados , Humanos , Neoplasias Hepáticas/etiologia , Modelos Estatísticos
17.
PLoS One ; 17(4): e0264771, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35439250

RESUMO

Most realistic social communities are multi-profiled cross-communities constructed from users sharing commonalities that include adaptive social profile ingredients (i.e., natural adaptation to certain social traits). The most important types of such cross-communities are the densest holonic ones, because they exhibit many interesting properties. For example, such a cross-community can represent a portion of users, who share all the following traits: ethnicity, religion, neighbourhood, and age-range. The denser a multi-profiled cross-community is, the more granular and holonic it is and the greater the number of its members, whose interests are exhibited in the common interests of the entire cross-community. Moreover, the denser a cross-community is, the more specific and distinguishable its interests are (e.g., more distinguishable from other cross-communities). Unfortunately, methods that advocate the detection of granular multi-profiled cross-communities have been under-researched. Most current methods detect multi-profiled communities without consideration to their granularities. To overcome this, we introduce in this paper a novel methodology for detecting the smallest and most granular multi-profiled cross-community, to which an active user belongs. The methodology is implemented in a system called ID_CC. To improve the accuracy of detecting such cross-communities, we first uncover missing links in social networks. It is imperative for uncovering such missing links because they may contain valuable information (social characteristics commonalities, cross-memberships, etc.). We evaluated ID_CC by comparing it experimentally with eight methods. The results of the experiments revealed marked improvement.


Assuntos
Religião , Rede Social , Coleta de Dados , Humanos , Características de Residência
18.
Comput Intell Neurosci ; 2022: 7280695, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35463284

RESUMO

In the context of the Internet of Things, user privacy leads to the lack of information security and the obscuration of traditional privacy concepts. Therefore, how to ensure information security and protect user privacy is a key issue that enterprises must solve in the process of using the Internet of Things technology. At present, the research on corporate employees' protection of user privacy in the context of the Internet of Things is mostly focused on the technical level, while the legal and management levels are relatively lacking. Based on the definition of the corporate concept in the context of the Internet of Things, this paper uses management and psychology as the research perspective, and based on theory of persuasion, adjustment orientation theory, and reinforcement theory, it discusses the attitudes of corporate employees to protect user privacy in the context of the Internet of Things and behaviour mechanism, constructing a new theoretical model. This experiment uses 0.001 as the step size to change the corresponding threshold size. The interval range is [0.001, 10], and there are a total of 10,000 points in the interval, which is equivalent to 100 million sensor attack tests. According to the above method, 10,000 points of the ROC curve can be obtained by using 10,000 thresholds, and the corresponding ROC curve can be drawn in the coordinate graph, which can intuitively reflect the performance of the VRADS vehicle anomaly real-time detection system. The challenge of data information protection is analyzed, trying to clarify the ideas for the protection of personal data and information in the Internet of Things environment and even lead to employees' rebellious psychology. This article proves that the pertinence and effectiveness of the persuasive content have a positive impact on employees' attitudes towards privacy protection, and it has been further deepened in the context of the Internet of Things. The balance point is to leave enough room for the long-term sustainable development of the Internet of Things industry on the basis of protecting the personal rights and interests of users.


Assuntos
Internet das Coisas , Privacidade , Big Data , Segurança Computacional , Coleta de Dados/métodos , Internet
19.
PLoS One ; 17(4): e0267030, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35446885

RESUMO

BACKGROUND: Patient-reported outcome measures (PROMs) or patient-reported outcomes (PROs) are used by clinicians in everyday clinical practice to assess patients' perceptions of their own health and the healthcare they receive. By providing insight into how illness and interventions impact on patients' lives, they can help to bridge the gap between clinicians' expectations and what matters most to the patient. Given increasing focus on patient-centred care, the objective of this meta-synthesis was to summarise the qualitative evidence regarding patients' perspectives and experiences of the use of PROMs in clinical care. METHODS: A systematic search of the following databases was undertaken in August 2020: Medline, EMBASE, EMCARE, PsychINFO, Scopus and the Cochrane Library. This review was conducted and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Methodological quality of the included studies was assessed using the Critical Appraisal Skills Programme checklist for qualitative research (CASP). A meta-ethnographic approach was used for data extraction and meta-synthesis of findings (PROSPERO registration: CRD42020202506). RESULTS: Fourteen studies from a range of countries with differing qualitative research methodologies were identified. Three themes were identified, namely 'patient preferences regarding PROMs', 'patient perceived benefits' and 'barriers to patient engagement with PROMs'. The perspectives of patients suggested they preferred PROMs that were simple and relevant to their conditions and found benefits in the way they facilitated self-reflection and effective communication with their clinicians. Patients, however, questioned the relevance of some individual questions and purpose. CONCLUSION: PROMs can be a useful tool in the clinical setting by enabling individualisation and patient centred care. This meta-synthesis provides insights into what patients find beneficial as well as barriers to their engagement, highlighting the importance of educating patients about PROMs.


Assuntos
Atenção à Saúde , Medidas de Resultados Relatados pelo Paciente , Coleta de Dados , Humanos , Assistência Centrada no Paciente , Pesquisa Qualitativa
20.
Neural Netw ; 150: 440-461, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35367717

RESUMO

The first-order optimizers in deep neural networks (DNN) are of pivotal essence for a concrete loss function to reach the local minimum or global one on the loss surface within convergence time. However, each optimizer possesses its own superiority and virtue when encountering a specific application scene and environment. In addition, the existing modified optimizers mostly emphasize a given optimizer without any transfer property. In this paper, a zeroing neural dynamics (ZND) based optimization approach for the first-order optimizers is proposed, which can assist ZND via the activation function to expedite the process of solving gradient information, with lower loss and higher accuracy. To the best of our knowledge, it is the first work to integrate the ZND in control domain with the first-order optimizers in DNN. This generic work is an optimization method for the most commonly-used first-order optimizers to handle different application scenes, rather than developing a brand-new algorithm besides the existing optimizers or their modifications. Furthermore, mathematic derivations concerning the gradient information transformation of the ZND are systematically provided. Finally, comparison experiments are implemented, which demonstrates the effectiveness of the proposed approach with different loss functions and network frameworks on the Reuters, CIFAR, and MNIST data sets.


Assuntos
Algoritmos , Redes Neurais de Computação , Aceleração , Coleta de Dados
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