bluuebunny/crossref_metadata_2025 huggingface dataset:
Design, Synthesis and Structural Confirmation of a Series of 2-(Thiophen-2-yl)- 4H-chromen-3-yl-sulfonate Derivatives and Preliminary Investigation of Their Antioxidant and Anticancer Potentials
Authors: Zang Jialin , Bu Ming , Yang Jifang , Han Lu , Lv Zhen
Published: May 2021

A series of novel 2-(thiophen-2-yl)-4H-chromen-3-yl-sulfonate derivatives (4a-4n) were synthesized and investigated for their in vitro free radical scavenging potential as well as cytotoxic efficacies against selected cancer cell lines. The cytotoxicity of the 4H-chromene derivatives (4a‑4n) was evaluated according to three human cancer cell lines (HepG2, A549, HeLa) by utilizing a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Accordingly, part of the results exhibited better cytotoxic activities than that of the positive controls (4H-chromen-4-one and apigenin). Among them, compounds 4c-4g exhibited better training to the positive control against the three human cancer cell lines (half maximal inhibitory concentration (IC50) = 3.87 ± 0.12 to 21.38 ± 0.52 μM). Moreover, the extract of the 4H-chromene derivatives (4a‑4n) showed better activity against 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-azino-bis-3‑ethylbenzothiazoline-6-sulfonic acid (ABTS) in antioxidant assays compared to that of the positive control ascorbic acid (IC50 = 12.72 ± 0.27, 5.09 ± 0.21 μg mL-1). Thus, it can be confirmed from the bioassay results that the overall structural design, as well as proper substitution, is crucial in delivering anticipated biological effects. In this regard, spectroscopic techniques such as 1H nuclear magnetic resonance (NMR), 13C NMR, and high-resolution mass spectrometry (HRMS) were also carried out to confirm the final structures.
Structure modal identification based on computer vision technology
Authors: Yuanjun He , Yinfeng Dong , Feiyu Guo , Yutong Li
Published: May 2021

Mobile phones have the potential to become useful tool in structural modal identification. In this paper, shaking table test videos of a 10-story steel structure captured by mobile phone is processed using computer vision theory and then the modal parameters are identified. A signal processing method based on variational mode decomposition (VMD) is used to improve the accuracy of identification. Using optical flow algorithm, the vibration data is extracted from the video, and then the response of the structure is obtained from the vibration data of selected feature points. Then, the vibration data is processed by VMD and structural modal parameters (mode frequency and mode shapes) are identified using FFD. Finally, the identification results obtained from mobile phone and professional sensors are compared to verify feasibility and accuracy of the proposed modal identification method.
Numerical simulation of jet formation and penetration characteristics in multi-point initiation mode
Authors: Wang Xin , Zhao Changxiao , Ji Chong , Li Xinghua , Zhong Mingshou , Ma Huayuan , Gu Yun
Published: May 2021

In order to explore the application feasibility and effective gain of shaped charge jet under multi-point initiation system, the jet forming characteristics of 40 mm diameter shaped charge under multi-point initiation mode were analyzed, and the influence rules of the number of initiation points and initiation radius on jet parameters were obtained. The simulation results of jet penetrating cylindrical shell covered charge show that the multi-point initiation system can effectively improve the jet tip velocity and the length of the jet, which can effectively improve the impact initiation ability of the shell charge.
Experimental study on vibration characteristics of metro tunnels with different track structures
Authors: Wu Baoyou , Liu Tianyu , Ai Yongfei , Liu Qingjie , Song Lizhong
Published: May 2021

To explore the vibration transmission characteristics and vibration reduction effects of metro tunnels with different track structures, the regular slab track section, the double-layer nonlinear vibration-damping fastener section and the isolated damping pad section in the Nanchang Metro Line 3 were selected respectively for the field hammer excitation test. Based on the field test results, the vibration transmission characteristics and the vibration reduction effects of metro tunnels with different track structures were analyzed. The results indicated that the vibration reduction effect of the isolated damping pads was best, followed by the double-layer nonlinear vibration-damping fasteners, while that of the regular slab tracks was worst; the double-layer nonlinear vibration-damping fastener section had obvious vibration reduction effect in the frequency range of 80 to 170 Hz, the isolated damping pad section had significant vibration reduction performance above 30 Hz; the vibration of the double-layer nonlinear vibration-damping fastener section and the isolated damping pad section was 5.6 dB and 10 dB less than the regular slab track section, respectively.
Acclimation of microorganisms for an efficient production of volatile fatty acids and biogas from mezcal vinasses in a dark fermentation process
Authors: Díaz-Barajas S. A. , Garzón-Zúñiga M. A. , Moreno-Andrade I. , Vigueras-Cortés J. M. , Barragán-Huerta B. E.
Published: May 2021

Mezcal is an alcoholic artisanal drink made from agave plants in Mexico. Its production causes the generation of wastewater called vinasses, which are highly polluting residues due to its concentration of organic matter as chemical oxygen demand (COD) (35,000–122,000 mg/L) and acidity (pH < 4). Due to their organic content, these residues can be used in dark fermentation to obtain biogas, which is rich in hydrogen. In this work, the acclimation of inoculum by means of a dark fermentation process, in the presence of toxic compounds from mezcal vinasses was studied. The strategy of increasing the initial concentration of vinasse in each treatment cycle in a sequencing batch reactor (SBR) reactor was applied. It was possible to obtain a maximum biogas production of 984 ± 187 mL/L, from vinasses (18,367 ± 1,200 mg COD/L), with an organic matter removal efficiency of 20 ± 1%. A maximum generation of volatile fatty acids (VFA) of 980 ± 538 mg/L equivalent to a production of 74 ± 21% of the influent concentration and removal rate of organic matter of 1,125 ± 234 mg COD/L d−1 equivalent to a removal efficiency of 20 ± 4% was obtained from vinasses with a concentration of 19,648 ± 1,702 mg COD/L.
Young Children’s Foreign Language Anxiety
Authors: Kiaer Jieun , Morgan-Brown Jessica M. , Choi Naya
Published: May 2021

This book presents original research on the effects of foreign language anxiety (FLA) on young language learners. It includes suggestions for alleviating FLA and encouraging foreign language enjoyment which will ultimately facilitate more effective language learning and support children’s psychosocial wellbeing.
LA MATEMÁTICA RECREATIVA COMO ESTRATEGIA DE APRENDIZAJE
Authors: Castro Medina Victoria , Menacho Isabel , Velarde Castro Luis Fernando
Published: May 2021

La investigación tuvo como objetivo general determinar si la aplicación de actividades lúdicas como estrategia mejora el aprendizaje de las matemáticas en los estudiantes de primaria de la Institución Educativa Naciones Unidas N°7062 en el año 2017. Esta investigación fue preexperimental, de enfoque cuantitativo. Se realizó con una muestra de 26 estudiantes a los cuales se les aplicó un pretest y postest. Se utilizó la estadística descriptiva para la interpretación de las variables. Asimismo, se utilizó la estadística inferencial con el estadístico de Wilcoxon para la prueba de hipótesis, en la cual se pudo apreciar el valor de P= ,000 < 0,05; es decir que existe una mejora significativa en el aprendizaje de las matemáticas después de la aplicación de las actividades lúdicas. Se concluyó en que la aplicación de actividades lúdicas como estrategia mejora significativamente el aprendizaje de las matemáticas en los estudiantes de primaria de la Institución Educativa Naciones Unidas N°7062 en el año 2017.
FORTALECIMIENTO DE LA COMPETENCIA CIENTÍFICA IMPLEMENTANDO RUTINAS DE PENSAMIENTO EN EL COLEGIO COOPERATIVO COMFENALCO
Authors: Díaz Ochoa Estefanía , Rodríguez López Natalia
Published: May 2021

Los análisis de las pruebas PISA y las pruebas Saber en cuanto al pensamiento científico, indicaron que existe una carencia por parte de los estudiantes para interpretar, abordar situaciones problemas y construir alternativas de solución, lo cual genera inconsistencias en la educación colombiana. Por esta razón, el objetivo de esta investigación fue fortalecer la competencia científica en niños de 5 – 6 años de edad en una institución educativa de carácter privado, a través de una propuesta de intervención pedagógica basada en rutinas de pensamiento. A partir de lo anterior se establecieron los objetivos específicos: Identificar las habilidades científicas de los niños, a través de actividades diagnósticas; diseñar las intervenciones pedagógicas basadas en rutinas de pensamiento; e implementar y evaluar las actividades determinando la efectividad de las rutinas de pensamiento, en el fortalecimiento de las habilidades científicas.El estudio es de tipo cualitativo y se tiene como diseño metodológico la Investigación Acción, en la cual se describió y reflexionó sobre la práctica docente en la enseñanza de las ciencias desde la educación inicial. La propuesta concluyó con la importancia de incorporar rutinas de pensamiento en la educación inicial para fortalecer la competencia científica, dado que los niños de transición evidenciaron avances en el desempeño académico durante y después de la implementación de la estrategia pedagógica, mostrándose más críticos e infiriendo coherentemente ante situaciones; además de tener mayor habilidad al clasificar objetos, indagar sobre la realidad, plantear hipótesis, planificar acciones para llegar a un fin  y explicar resultados a través de la experimentación.Palabras Clave: Rutinas de pensamiento, competencia científica, educación inicial.
EVALUACIÓN DEL PROCESO ADMINISTRATIVO DE LOS DIRIGENTES DE LAS JUNTAS DE ACCIÓN COMUNAL DE LA PROVINCIA DE MÁRQUEZ DEL DEPARTAMENTO DE BOYACÁ
Authors: Rodriguez Afanador Edgar
Published: May 2021

La investigación  permitió identificar como  desarrollan  el proceso administrativo los dirigentes de las Juntas de Acción Comunal de la Provincia de Márquez del Departamento de Boyacá,  mediante aplicación  de un estudio  de tipo mixto en los diferentes municipios seleccionadas,  facilito  conocer el desarrollo del proceso administrativo de los presidentes,   existen fallas en la planeación de las acciones a ejecutar donde existe una dependencia de la gestión de los dignatarios  de los recursos que puedan obtener de los entes territoriales,  faltando una articulación de las necesidades de la comunicación y la autogestión que puedan lograr con las comunidades, igualmente,  en la estructura organizativa hay una concentración de  actividades en un solo integrante principalmente el presidente,  como también,  en el proceso de control solo se encontraron acciones relacionadas con el seguimiento a los ingresos y gastos en actividades como ferias y eventos patrocinados por una Alcaldía o La Gobernación.  Hay que mencionar, que el nivel de formación está concentrado en el nivel de primaria y pocos logran un pregrado lo que dificultad sus resultados para mejorar las condiciones de sus pobladores.
RELACIÓN ENTRE LA ACTUALIZACIÓN DEL DOCENTE UNIVERSITARIO SANMARQUINO Y LA MOTIVACIÓN ACADÉMICA DE SUS MAESTRISTAS
Authors: Dueñas Yarlaqué Carlos David
Published: May 2021

La presente investigación determina y explica la relación entre la Actualización del Docente Universitario; sus dimensiones Investigaciones Científicas, Publicaciones Científicas, Formación Profesional y Desempeño Profesional con la Motivación Académica de los estudiantes de Maestría con mención en Docencia en Nivel Superior 2015-II de la Universidad Nacional Mayor de San Marcos. Nuestras variables contemplan dos aspectos muy ligados en el campo pedagógico: la actualización del docente universitario y la motivación académica de los estudiantes de maestría.La hipótesis formulada se expresa de la siguiente manera: El Nivel de Actualización de los Docente Universitarios de las Maestrías se relacionan significativamente con la Motivación Académica de los Estudiantes del IV ciclo de maestría en Docencia en Nivel Superior de la Facultad de Educación Sede Lima de la Universidad Nacional Mayor de San Marcos.Los resultados establecen por medio de la prueba estadística de correlación bivariada de Pearson un índice de correlación de +0,532, lo que, según el criterio especificado, las variables “Nivel de Actualización de los Docentes” y “Motivación Académica de los Estudiantes” poseen una relación directamente proporcional moderada estadísticamente significativa, con un margen de error menor a 0,05%, con lo cual se aprueba la hipótesis de la investigación.
Promoting Collaborative Goal Setting for Cancer Prevention Among Primary Care Patients Through mHealth: Mixed Methods Evaluation of a New App
Authors: Resnick Daniel , Schapira Marilyn M , Smith Jazmine M , Bautista Allison , Xu Chang , Jones Liz , Aysola Jaya
Published: May 2021

Background

Many newly diagnosed cancers are associated with modifiable lifestyle behaviors, such as diet, exercise, smoking cessation, and maintaining a healthy weight. However, primary care providers rarely discuss cancer prevention behaviors with their patients.

Objective

This study aims to assess the usability, acceptability, and user engagement of the Healthier Together mobile app, which is designed to promote cancer prevention behaviors among non-Hispanic Black primary care patients, by using social networks and goal-setting theories of behavior change.

Methods

In an 8-week pilot study, we enrolled primary care patients (N=41) and provided them with a cancer prevention mobile app that allowed them to select, track, and share progress on cancer prevention goals with other users. App usability was assessed using the System Usability Scale. We assessed the app’s acceptability by qualitatively analyzing open-ended responses regarding participants’ overall experience with the app. We assessed participants’ engagement by analyzing the built-in data capture device, which included the number of times participants checked in (out of a maximum of 8) during the study.

Results

The mean age of the 41 participants was 51 years (SD 12), and 76% (31/41) were women. App use data were captured from all participants, and 83% (34/41) completed the exit survey and interview. The mean System Usability Scale score was 87 (SD 12; median 90; IQR 78-95). The analysis of open-ended responses revealed several key themes, and participants complemented the app’s ease of use and health behavior–promoting features while also commenting on the need for more feedback and social interactions through the app. On average, participants checked in 5.7 times (SD 2.7) out of 8 possible opportunities. Of the 41 participants, 76% (31/41) checked in during at least 4 of the 8 weeks. Secondary analyses revealed that participants often accomplished their set goals (mean 5.1, SD 2.7) for each week. The qualitative analysis of comments given by participants within the app after each weekly check-in revealed several themes on how the app assisted participants in behavioral change, highlighting that some participants created exercise programs, ate healthier foods, lost a significant amount of weight, and stopped smoking during this study.

Conclusions

The implementation of a mobile cancer prevention goal–setting app in a primary care setting was feasible, and the app achieved high usability, acceptability, and engagement among participants. User feedback revealed an influence on health behaviors. These findings suggest the promise of the Healthier Together app in facilitating behavioral change to reduce cancer risk among non-Hispanic Black primary care patients.
Addressing Biodisaster X Threats With Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights
Authors: Su Zhaohui , McDonnell Dean , Bentley Barry L , He Jiguang , Shi Feng , Cheshmehzangi Ali , Ahmad Junaid , Jia Peng
Published: May 2021

Background

With advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is paradoxical that while greater access to biotechnology on a population level has many advantages, it may also increase the likelihood and frequency of biodisasters due to accidental or malicious use. Similar to “Disease X” (describing unknown naturally emerging pathogenic diseases with a pandemic potential), we term this unknown risk from biotechnologies “Biodisaster X.” To date, no studies have examined the potential role of information technologies in preventing and mitigating Biodisaster X.

Objective

This study aimed to explore (1) what Biodisaster X might entail and (2) solutions that use artificial intelligence (AI) and emerging 6G technologies to help monitor and manage Biodisaster X threats.

Methods

A review of the literature on applying AI and 6G technologies for monitoring and managing biodisasters was conducted on PubMed, using articles published from database inception through to November 16, 2020.

Results

Our findings show that Biodisaster X has the potential to upend lives and livelihoods and destroy economies, essentially posing a looming risk for civilizations worldwide. To shed light on Biodisaster X threats, we detailed effective AI and 6G-enabled strategies, ranging from natural language processing to deep learning–based image analysis to address issues ranging from early Biodisaster X detection (eg, identification of suspicious behaviors), remote design and development of pharmaceuticals (eg, treatment development), and public health interventions (eg, reactive shelter-at-home mandate enforcement), as well as disaster recovery (eg, sentiment analysis of social media posts to shed light on the public’s feelings and readiness for recovery building).

Conclusions

Biodisaster X is a looming but avoidable catastrophe. Considering the potential human and economic consequences Biodisaster X could cause, actions that can effectively monitor and manage Biodisaster X threats must be taken promptly and proactively. Rather than solely depending on overstretched professional attention of health experts and government officials, it is perhaps more cost-effective and practical to deploy technology-based solutions to prevent and control Biodisaster X threats. This study discusses what Biodisaster X could entail and emphasizes the importance of monitoring and managing Biodisaster X threats by AI techniques and 6G technologies. Future studies could explore how the convergence of AI and 6G systems may further advance the preparedness for high-impact, less likely events beyond Biodisaster X.
Predicting Kidney Graft Survival Using Machine Learning Methods: Prediction Model Development and Feature Significance Analysis Study
Authors: Naqvi Syed Asil Ali , Tennankore Karthik , Vinson Amanda , Roy Patrice C , Abidi Syed Sibte Raza
Published: May 2021

Background

Kidney transplantation is the optimal treatment for patients with end-stage renal disease. Short- and long-term kidney graft survival is influenced by a number of donor and recipient factors. Predicting the success of kidney transplantation is important for optimizing kidney allocation.

Objective

The aim of this study was to predict the risk of kidney graft failure across three temporal cohorts (within 1 year, within 5 years, and after 5 years following a transplant) based on donor and recipient characteristics. We analyzed a large data set comprising over 50,000 kidney transplants covering an approximate 20-year period.

Methods

We applied machine learning–based classification algorithms to develop prediction models for the risk of graft failure for three different temporal cohorts. Deep learning–based autoencoders were applied for data dimensionality reduction, which improved the prediction performance. The influence of features on graft survival for each cohort was studied by investigating a new nonoverlapping patient stratification approach.

Results

Our models predicted graft survival with area under the curve scores of 82% within 1 year, 69% within 5 years, and 81% within 17 years. The feature importance analysis elucidated the varying influence of clinical features on graft survival across the three different temporal cohorts.

Conclusions

In this study, we applied machine learning to develop risk prediction models for graft failure that demonstrated a high level of prediction performance. Acknowledging that these models performed better than those reported in the literature for existing risk prediction tools, future studies will focus on how best to incorporate these prediction models into clinical care algorithms to optimize the long-term health of kidney recipients.
Mobile Health in Chronic Disease Management and Patient Empowerment: Exploratory Qualitative Investigation Into Patient-Physician Consultations
Authors: Stampe Kathrine , Kishik Sharon , Müller Sune Dueholm
Published: May 2021

Background

Chronic diseases often present severe consequences for those affected. The management and treatment of chronic diseases largely depend on patients’ lifestyle choices and how they cope with the disease in their everyday lives. Accordingly, the ability of patients to self-manage diseases is a highly relevant topic. In relation to self-management, studies refer to patient empowerment as strengthening patients’ voices and enabling them to assert control over their health and treatment. Mobile health (mHealth) provides cost-efficient means to support self-management and foster empowerment.

Objective

There is a scarcity of research investigating how mHealth affects patient empowerment during patient-physician consultations. The objective of this study is to address this knowledge gap by investigating how mHealth affects consultations and patient empowerment.

Methods

We relied on data from an ethnographic field study of 6 children and adolescents diagnosed with juvenile idiopathic arthritis. We analyzed 6 patient-physician consultations and drew on Michel Foucault’s concepts of power and power technology.

Results

Our results suggest that the use of mHealth constitutes practices that structure the consultations around deviations and noncompliant patient behavior. Our analysis shows how mHealth is used to discipline patients and correct their behavior. We argue that the use of mHealth during consultations may unintentionally lead to relevant aspects of patients’ lives related to the disease being ignored; thus, inadvertently, patients’ voices may be silenced.

Conclusions

Our results show that concrete uses of mHealth may conflict with extant literature on empowerment, which emphasizes the importance of strengthening the patients’ voices and enabling patients to take more control of their health and treatment. We contribute to the state-of-the-art knowledge by showing that the use of mHealth may have unintended consequences that do not lead to empowerment. Our analysis underscores the need for further research to investigate how mHealth impacts patient empowerment during consultations.
Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial
Authors: Kim Meelim , Yang Jaeyeong , Ahn Woo-Young , Choi Hyung Jin
Published: May 2021

Background

The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes.

Objective

This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy.

Methods

We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics.

Results

A higher engagement rate was associated with higher weight loss at 8 weeks (r=−0.59; P<.001) and 24 weeks (r=−0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R2 0.416, SD 0.006). The prediction of short-term weight change (mean R2 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R2 0.590, SD 0.011).

Conclusions

Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics.

Trial Registration

ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306
Characteristics of Citizens and Their Use of Teleconsultations in Primary Care in the Catalan Public Health System Before and During the COVID-19 Pandemic: Retrospective Descriptive Cross-sectional Study
Authors: Solans Oscar , Vidal-Alaball Josep , Roig Cabo Pasqual , Mora Núria , Coma Ermengol , Bonet Simó Josep Maria , Hermosilla Pérez Eduardo , Saigí-Rubió Francesc , Olmos Domínguez Carmen , Piera-Jiménez Jordi , Abizanda González Mercè , López Seguí Francesc
Published: May 2021

Background

eConsulta—that is, asynchronous, two-way teleconsultation in primary care—is one of the most important telemedicine developments in the Catalan public health system, a service that has been heavily boosted by the onset of the COVID-19 pandemic. It is vital to know the characteristics of its users in order to be able to meet their needs and understand the coverage of this service in a context where there is reduced accessibility to the health system.

Objective

This study aims to analyze the profile of the citizens who use the eConsulta tool and the reasons for their use, as well as to gain an understanding of the elements that characterize their decision to use it while distinguishing between those who used it before and those who have used it since the onset of the COVID-19 pandemic.

Methods

A descriptive, observational study based on administrative data was performed. This study differentiates between the COVID-19 pandemic era and the period preceding it, considering the day the state of emergency was declared in Spain (ie, March 12, 2020) as the cut-off point. It also differentiates between eConsulta users who send messages and those who only receive them.

Results

During the pandemic, the number of unique users of this teleconsultation service had almost tripled, with up to 33.10 visits per 1000 inhabitants per month reported in the first three months. For the two user profiles analyzed, most users since the start of the COVID-19 outbreak were predominantly female, systematically younger, more actively employed, and with less complex pathologies. Furthermore, eConsulta users received more messages proactively from the health professionals. There was also a relative decrease in the number of conversations initiated by higher-income urban users and an increase in conversations initiated by users in rural areas.

Conclusions

The COVID-19 pandemic has helped to generalize the use of telemedicine as a tool to compensate, to some extent, for the decline in face-to-face visits, especially among younger citizens in Catalonia. Telemedicine has made it possible to maintain contact between citizens and the health care system in the context of maximum complexity.
Postmarketing Safety Monitoring After Influenza Vaccination Using a Mobile Health App: Prospective Longitudinal Feasibility Study (Preprint)
Authors: Nguyen Minh Tam H , Krause Gérard , Keller-Stanislawski Brigitte , Glöckner Stephan , Mentzer Dirk , Ott Jördis J
Published: May 2021

BACKGROUND

For the safety monitoring of vaccinations postlicensure, reports of adverse events after immunization (AEFIs) are crucial. New technologies such as digital mobile apps can be used as an active approach to capture these events. We therefore conducted a feasibility study among recipients of the influenza vaccination using an app for assessment of the reporting of AEFIs.

OBJECTIVE

The goal of the research was to determine factors influencing adherence to and correct use of a newly developed app for individuals to report AEFI for 3 months using regular reminder functions, to identify determinants of AEFI occurrence and define reported AEFI types.

METHODS

We developed the app (SafeVac) and offered it to recipients of the influenza vaccination in 3 occupational settings in fall 2018. In this prospective longitudinal feasibility study, data on AEFIs were generated through SafeVac for 3 months. Using logistic and Cox regression, we assessed associations between app adherence, correct app entry, AEFIs, and sociodemographic parameters.

RESULTS

Of the individuals who logged into SafeVac, 61.4% (207/337) used the app throughout a 3-month period. App use adherence was negatively associated with female sex (odds ratio [OR] 0.47; CI 0.25-0.91) and correct app entry was negatively associated with older age (OR 0.96; CI 0.93-0.99) and lower education (OR 0.31; CI 0.13-0.76). AEFI occurrence was associated with female sex (hazard ratio 1.41; CI 1.01-1.96) and negatively with older age (hazard ratio 0.98; CI 0.97-0.99). The most common AEFIs reported were injection site pain (106/337), pain in extremity (103/337), and fatigue/asthenia (73/337).

CONCLUSIONS

Digital AEFI reporting was feasible with SafeVac and generated plausible results for this observation period and setting. Studies directly comparing SafeVac with conventional passive reporting schemes could determine whether such digital approaches improve completeness, timeliness, and sensitivity of vaccine vigilance. Further studies should evaluate if these results are transferable to other vaccinations and populations and if introduction of such a tool has an influence on vaccination readiness and therefore vaccine safety.
Secondary Use of Clinical Data in Data-Gathering, Non-Interventional Research or Learning Activities: Definition, Types, and a Framework for Risk Assessment (Preprint)
Authors: Jungkunz Martin , Köngeter Anja , Mehlis Katja , Winkler Eva C , Schickhardt Christoph
Published: May 2021

BACKGROUND

The secondary use of clinical data in data-gathering, non-interventional research or learning activities (SeConts) has great potential for scientific progress and health care improvement. At the same time, it poses relevant risks for the privacy and informational self-determination of patients whose data are used.

OBJECTIVE

Since the current literature lacks a tailored framework for risk assessment in SeConts as well as a clarification of the concept and practical scope of SeConts, we aim to fill this gap.

METHODS

In this study, we analyze each element of the concept of SeConts to provide a synthetic definition, investigate the practical relevance and scope of SeConts through a literature review, and operationalize the widespread definition of risk (as a harmful event of a certain magnitude that occurs with a certain probability) to conduct a tailored analysis of privacy risk factors typically implied in SeConts.

RESULTS

We offer a conceptual clarification and definition of SeConts and provide a list of types of research and learning activities that can be subsumed under the definition of SeConts. We also offer a proposal for the classification of SeConts types into the categories non-interventional (observational) clinical research, quality control and improvement, or public health research. In addition, we provide a list of risk factors that determine the probability or magnitude of harm implied in SeConts. The risk factors provide a framework for assessing the privacy-related risks for patients implied in SeConts. We illustrate the use of risk assessment by applying it to a concrete example.

CONCLUSIONS

In the future, research ethics committees and data use and access committees will be able to rely on and apply the framework offered here when reviewing projects of secondary use of clinical data for learning and research purposes.
Synergy through Integration of Wearable EEG and Virtual Reality for Mild Cognitive Impairment and Mild Dementia Screening: Protocol Design and Feasibility Study (Preprint)
Authors: Lee Bohee , Lee Taeheon , Jeon Hyungsin , Lee Songsub , Kim Kibum , Cho Wanhee , Hwang Jeonghwan , Chae Yong-Wook , Jung Jin-Man , Kang Hyo Jin , Kim Nan Hee , Shin Cheolmin , Jang Jaeson
Published: May 2021

BACKGROUND

Virtual reality (VR) technologies have shown promising potential in the early diagnosis of dementia by enabling regular assessment thanks to the portability and accessibility of the devices. However, previous VR studies were restricted to the analysis of behavioral responses, so information about degenerated brain dynamics could not be acquired in these studies. One of the possible approaches to enabling inspection of brain dynamics using a portable platform is the application of wearable EEG devices, which provide simple and convenient neuroimaging tools for identifying characteristic neural activities of dementia.

OBJECTIVE

The aim of this study was to develop a cognitive impairment (CI) screening tool based on a wearable EEG device integrated into a VR platform, and to evaluate whether it is feasible and effective to screen for CI using this device.

METHODS

Subjects were asked to use a hardware setup consisting of a frontal six-channel EEG device mounted on a VR device and to perform tasks designed for assessing cognitive abilities in four domains (focused attention, selective attention, depth perception and working memory). Behavioral response profiles and EEG features were extracted during the tasks, and investigated to determine whether patients with CI could be differentiated from healthy controls (HCs). Furthermore, random forest classifiers were trained on the extracted features to evaluate whether EEG characteristics during the cognitive tasks were helpful for screening subjects with CI.

RESULTS

A total of 59 participants (30 HCs and 29 CI) participated in this study. The CI group achieved notably worse cognitive task scores. More importantly, power spectral analysis of the EEG signals revealed notable differences between the two groups. Characteristic observations from participants with CI included reduced alpha activity during the resting-state (P = .03) and other cognitive tasks (P = .04 and .006 for selective attention and depth perception tasks, respectively), which are well-known pathological EEG patterns for dementia. Therefore, the delta-to-alpha ratio (DAR) and theta-to-alpha ratio (TAR), which are well-known biomarkers for dementia screening, were significantly greater in the CI group. The performance of the patient classification consistently improved when EEG characteristics measured during cognitive tasks were additionally included in feature attributes, suggesting that our protocol provides discriminative information that could improve the performance of dementia screening.

CONCLUSIONS

This study demonstrated that the integration of EEG devices into a VR framework could emerge as a powerful and synergistic strategy for constructing an easily accessible EEG-based dementia screening tool.
Association of COVID-19 Risk Misperceptions With Household Isolation in the United States: Survey Study (Preprint)
Authors: Ladapo Joseph A , Rothwell Jonathan T , Ramirez Christina M
Published: May 2021

BACKGROUND

Adverse mental and emotional health outcomes are increasingly recognized as a public health challenge associated with the COVID-19 pandemic.

OBJECTIVE

The goal of this study was to examine the association of COVID-19 risk misperceptions with self-reported household isolation, a potential risk factor for social isolation and loneliness.

METHODS

We analyzed data from the Franklin Templeton-Gallup Economics of Recovery Study (July to December 2020) of 24,649 US adults. We also analyzed data from the Gallup Panel (March 2020 to February 2021), which included 123,516 observations about loneliness. The primary outcome was self-reported household isolation, which we defined as a respondent having no contact or very little contact with people outside their household, analogous to quarantining.

RESULTS

From July to December 2020, 53% to 57% of respondents reported living in household isolation. Most participants reported beliefs about COVID-19 health risks that were inaccurate, and overestimation of health risk was most common. For example, while deaths in persons younger than 55 years old accounted for 7% of total US deaths, respondents estimated that this population represented 43% of deaths. Overestimating COVID-19 health risks was associated with increased self-reported household isolation, with percentage differences ranging from 5.6 to 11.8 (P<.001 at each time point). Characteristics associated with self-reported household isolation from the July and August 2020 surveys and persisting in the December 2020 survey included younger age (18 to 39 years), having a serious medical condition, having a household member with a serious medical condition, and identifying as a Democrat. In the Gallup Panel, self-reported household isolation was associated with a higher prevalence of loneliness.

CONCLUSIONS

Pandemic-related harms to emotional and mental well-being may be attenuated by reducing risk overestimation and household isolation preferences that exceed public health guidelines.
Midwives' Acceptance of Using mHealth to Improve Data Quality of a Maternal and Child Health Program in Bogor Regency, Indonesia: Mixed Methods Study (Preprint)
Authors: Siregar Kemal N , Retnowati Retnowati , Utomo Budi , Kurniawan Rico , Eryando Tris , Nur Ryza JB , Nuridzin Dion Zein
Published: May 2021

BACKGROUND

Maternal and Child Health (MCH) remains an important agenda item in the Sustainable Development Goals (SDGs). Unfortunately, despite strong commitments, the Maternal Mortality Ratio in Indonesia remains high. Program performance is the main factor that can reduce the Maternal Mortality Ratio. Improving midwife performance must be supported by the availability of quality data. However, midwives still experience problems with the quality data in the MCH services.

OBJECTIVE

The study objectives are, a) implementing a data quality assurance mechanism in mHealth, b) assessing the extent to which midwives accept mHealth for use in their daily work, and c) exploring the obstacles faced by the midwives in using mHealth.

METHODS

This study used mixed methods. We firstly reported on how the data quality assurance mechanism has been implemented to apply the 4C principles, consisting of Completeness, Correctness, Currentness, and Consistency to mHealth. Secondly, a quantitative assessment of midwife acceptance of the designed mHealth was conducted for all midwives working in all 11 villages in Babakan Madang Sub-District, Bogor Regency, using an online format of the Technology Acceptance Model questionnaire comprising 20 questions. Thirdly, the study exploring the challenges faced by the midwives in the use of mHealth through open-ended questions.

RESULTS

The MCH data generated by mHealth met the data quality principles of 4C. Midwives in the villages showed their enthusiasm for using the mHealth, and the TAM assessment showed that 93% of the midwives agreed that mHealth was useful for their work, 100% agreed that mHealth was easy to use, 95% reported that they had received training, 82% reported that they were interested in using mHealth and would recommend mHealth to fellow midwives, 91% reported that Android smartphones and internet connection facilities are available to use mHealth, and 76% stated that mHealth supports their daily work. One of the challenges of using the mHealth is the lack of integration with the Public Health Center information system.

CONCLUSIONS

The mHealth system produces quality data that can improve the current poor data quality, and this application can be easily used by midwives. The midwives generally accepted the application and agreed that mHealth helps with their daily work in MCH services.

CLINICALTRIAL

-
Core Competencies to Promote Consistency and Standardization of Best Practices for Digital Peer Support: Focus Group Study (Preprint)
Authors: Collins-Pisano Caroline , Velez Court Juan , Johnson Michael , Mois George , Brooks Jessica , Myers Amanda , Muralidharan Anjana , Storm Marianne , Wright Maggie , Berger Nancy , Kasper Ann , Fox Anthony , MacDonald Sandi , Schultze Sarah , Fortuna Karen
Published: May 2021

BACKGROUND

As digital peer support is quickly expanding across the globe in the wake of the COVID-19 pandemic, standardization in the training and delivery of digital peer support can advance the professionalism of this field. While telehealth competencies exist for other fields of mental health practice, such as social work, psychiatry, and psychology, limited research has been done to develop and promote digital peer support competencies.

OBJECTIVE

The goal of this study is to introduce the coproduction of core competencies that can guide digital peer support.

METHODS

Peer support specialists were recruited through an international listserv and participated in a 1-hour virtual focus group. A total of four focus groups were conducted with 59 peer support specialists from 11 US states and three countries.

RESULTS

Analysis was conducted using the rigorous and accelerated data reduction (RADaR) technique, and 10 themes were identified: (1) protecting the rights of service users, (2) technical knowledge and skills in the practice of digital peer support, (3) available technologies, (4) equity of access, (5) digital communication skills, (6) performance-based training, (7) self-care, (8) monitoring digital peer support and addressing digital crisis, (9) peer support competencies, and (10) health literacy (emerging). The authors present recommendations based on these themes.

CONCLUSIONS

The introduction of digital peer support core competencies is an initial first step to promote the standardization of best practices in digital peer support. The established competencies can potentially act as a guide for training and skill development to be integrated into US state peer support specialist competencies and to enhance competencies endorsed by the Substance Abuse and Mental Health Services Administration (SAMHSA).
Online Public Attention of Premature ejaculation in Mainland China: Infodemiology Study Based on Baidu Index (Preprint)
Authors: Wei Shanzun , Ming Ming , Wu Changjing , Wen Xi , Zhu Guonian , Zhou Xiangfu
Published: May 2021

BACKGROUND

Premature ejaculation (PE) is one of the most described psychosocial stress and sexual complaints worldwide. Previous investigations have focused predominantly on the prospective identification of cases that meets the researchers' criteria. The genuine demand as regards PE and related issues from patients may thus be neglected.

OBJECTIVE

To examine the online search trend and users’ demand related to PE on a national and regional scale using the dominant major search engine in mainland China.

METHODS

The Baidu Index was queried using the PE related terms for the period 2011.01–2020.12. The search volume for each term was recorded to analyze the search trend and demographic distributions. For user interest, the data of demand graph and trend data were collected and analyzed.

RESULTS

Of the 36 available PE keywords, 4 PE searching topics were identified. The BSI for each PE topics varies from 46.30% to 6.41%. The APC for topic Complaint was 2011-2014, 48.80% (p > .05); 2014-2020, -16.82% (p < .05). The APC for topic Enquiry was 2011-2014, 16.21% (p > .05); 2014-2020, -11.00% (p < .05). For topic Prognosis, the annual APC was 2011-2017, 11.18% (p < .05); 2017-2020, -19.86% (p < .05). For topic Treatment, the annual APC was 2011-2016, 14.04% (p < .05); 2016-2020, -38.83% (p < .05). The age distribution of the population of each PE searching topics enquiries shows that the population aged 20 to 40 years comprised nearly 70% of the total search enquiries. Seconded is 17.95 % in the age group under 19 years. People from the east part of china made over 50% of the total search queries.

CONCLUSIONS

e fluctuating online popularity of PE search is reflecting the real-time population demands. It may help medical professionals better understand population interest, population concerns, regional variations and gender differences on a national wide scale and making disease-specific healthcare policies. The internet search data could be more reliable when the insufficient and lagging registry data are completed.

CLINICALTRIAL

Not applicable
Analisis Sistem Kelistrikan pada Beban Motor Mesin Pencacah Sampah Plastik
Authors: Handayani Yanolanda Suzantry , Haidi Junas , Mardian Agun
Published: May 2021

In this modern era, the activities of almost all humans depend on machines they make, such as single-phase induction electric motors, which are used to chop plastic waste. This chopping machine aims to help plastic collectors process plastic waste into small pieces, making it easier to pack and ship plastic out of the area for reprocessing. The plastic waste shredding machine is made using a crushing system with a fan-shaped blade construction consisting of 39 blades divided by two rotating rows opposite the cover box using a chain motor gear transmission element. Most of the chopper machines on the market use engines with diesel or diesel fuel, therefore a chopper machine using an electric motor is designed to compare the motor power without the addition of capacitors and capacitors. The waste load used for motors without additional capacitors, medium and large bottles measuring 375 ml to 1500 ml, the machine can chop as much as 800 grams with the highest measurement of power 578.0 Watt, current 4.192 A, the lowest motor speed measurement is 1414 rpm and the reducer speed is 22.9 rpm . The waste load used for motors with additional capacitors, medium and large bottles measuring 375 ml to 1500 ml, the machine can chop 1000 grams with the highest measurement of power 732.7 Watt, current 4.149 A, the lowest motor speed measurement is 1464 rpm and the reducer speed is 22.9 rpm.
СТАНДАРТИЗАЦИЯ РЕШЕНИЙ И СЕГМЕНТИРОВАНИЕ ТРАНСПОРТНОГО УРОВНЯ СЕТИ 5G
Authors: Коган С.
Published: May 2021

В статье рассмотрены вопросы стандартизации решений и сегментации транспортного уровня сети 5G, связанной с выделением на транспортном уровне групп соединений различных конечных точек сети для достижения определенного SLA в интересах клиента. Разделение сети 5G на независимо управляемые, контролируемые и настраиваемые сегменты (network slicing) позволит одному сетевому оператору управлять несколькими виртуальными сетями, для каждой из которых, в зависимости от типа предоставляемой услуги, должны будут обеспечены разные величины задержек, пропускной способности, надежности, безопасности и т.п.