bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of a New Work-Related Stress Assessment Tool
Authors: Buonocore Gaetano , Maldonato Nelson Mauro , Alfano Yari Mirko , Annunziata Simona , Annunziato Tilde , Muzii Benedetta , Vergati Concetta , Bottone Mario , Cantone Daniela , Polito Rita , Tartaglia Nicola , Ambrosi Antonio , Robustella Carmela , Moscatelli Fiorenzo , Sperandeo Raffaele
Published: July 2020

Background:

Work-related stress is a relevant phenomenon in terms of health and safety at work, as occupational distress has a negative impact on individual and organisational well-being. It is a complex and multifactorial phenomenon, whose evaluation must be carried out through a specific and adequate methodology.

Objective:

This work aims to identify versatile tools that can quickly provide reliable measures of work distress. It analyzes the proposal elaborated by the “Comitato Unico di Garanzia per le Pari Opportunità, la Valorizzazione del Benessere di chi lavora e contro le Discriminazioni” of Rome,i.e. the tool “Valutazione è prevenzione, Sicurezza è partecipazione”.

Methods:

A study was carried out on a sample of 474 employees of the Neapolitan Judicial Offices, who were given a standardized questionnaire to investigate the stress, associated with the proposal of the Comitato Unico di Garanzia.

Results:

From the elaboration of the results, it emerges that the conditions of working wellbeing are linked to two main factors related to the perception of workers both of physical-environmental and organisational-relational aspects. In particular, it emerged that the new assessment tool, consisting of a small number of items, contributes to the detection of work stress, so it is necessary to deepen through future research the contribution that this tool can offer to the survey on work-related stress.

Conclusion:

Having highlighted two factors that significantly saturate the presence of a working discomfort, through an agile tool, allows us to plan a new research path, which can approach the complexity of the phenomenon through the methods of deep learning.
Three-Component Efficient Synthesis of 2-Amino-3-cyano-4H-pyrans Catalyzed by Diammonium Hydrogen Phosphate in Aqueous Media
Authors: Taghva Pardis H. , Kabirifard Hassan
Published: July 2020

Background:

The present method is facile, green and effective for the synthesis of 2-
amino-3-cyano-4H-pyran derivatives which are obtained by one-pot three-component condensation
reactions of aromatic aldehydes, malononitrile and methyl acetoacetate using diammonium hydrogen
phosphate (DAHP) in aqueous ethanol at room temperature.

Methods:

2-Amino-3-cyano-4H-pyrans were synthesized through a one-pot three-component tandem
Knoevenagel cyclocondensation reaction of aromatic aldehydes, malononitrile, and methyl
acetoacetate in the presence of 10 mol% of DAHP as a catalyst under aqueous ethanol medium at
room temperature. All obtained structures were confirmed by their physical constant, IR, 1H NMR,
13C NMR spectroscopy, and also elemental analyses for new derivatives.

Results:

Three-component synthesis of 2-amino-3-cyano-4H-pyrans catalyzed by DAHP with aromatic
aldehydes, malononitrile and methyl acetoacetate in aqueous ethanol medium at room temperature
was prepared. The achieved derivatives (nine entries) were well synthesized in excellent
yields.

Conclusion:

The present method is straightforward, quick, and most efficient green protocol for
the synthesis of 2-amino-3-cyano-4H-pyran derivatives using highly inexpensive, easily handle
and, nontoxic DAHP as an efficient catalyst in aqueous ethanol medium at room temperature.
Short-term Electricity Price Probabilistic Forecasting Based on Support Vector Quantile Regression Optimized by Simulated Annealing Algorithm
Authors: He Hui , Zhang Rui , Li Kaihang , Jie Yongjun , Jiao Runhai , Chen Bo
Published: July 2020

Background:

Electricity price forecasting is still a challenging issue as it plays an essential role in balancing
electricity generation and consumption. Probabilistic electricity price forecasting not only provides deterministic price
forecasts but also effectively quantifies the uncertainty of electricity price.

Methods:

This paper introduces a new short-term electricity price forecasting approach called SASVQR, which is based
on support vector quantile regression (SVQR) optimized by simulated annealing algorithm. In this study, SVQR is
employed to obtain the conditional quantiles of the electricity under different quantile points, while the simulated
annealing algorithm is applied to optimize each SVR model. Then the kernel density estimation takes these conditional
quantiles as inputs and generates the probability density functions for future electricity prices.

Result:

The proposed algorithm is assessed in three datasets: the GEFCom 2014, two real electricity price datasets from
the PJM market and the Singapore market. Three popular probabilistic forecasting criteria, namely prediction interval
coverage probability (PICP), prediction interval normalized average width (PINAW), and coverage width-based criterion
(CWC), are utilized to evaluate the numerical experiment results..It shows the promising forecasting performance,
robustness, and effectiveness of SASVQR on different datasets.

Conclusion:

The SASVQR method can effectively forecast the short-term electricity price compared with other methods.
Editorial
Authors: Barrios Rubio Andrés
Published: July 2020

La Facultad de Ciencias Sociales de la Universidad de Bogotá Jorge Tadeo Lozano constituye un importante escenario académico en el que convergen saberes que se complementan e interactúan para aportar a la sociedad profesionales integrales. Su visión de sociedad, y la construcción de país a la que le apunta, se potencian al abordar temas coyunturales de la realidad, local y global, en el diálogo entre docentes y estudiantes y en el análisis académico-profesional llevado a cabo por expertos y protagonistas que enriquecen el contexto del conocimiento.
eHealth Communication With Clients at Community-Based HIV/AIDS Service Organizations in the Southern United States: Cross-Sectional Survey
Authors: Wigfall Lisa Tisdale
Published: July 2020

Background

Providing HIV/STD testing and prevention education, medical and nonmedical case management, housing assistance, transportation services, and patient navigation are just a few examples of how community-based HIV/AIDS service organizations will help the United States realize the goals of the updated National HIV/AIDS Strategy.

Objective

In this study, the aim was to assess electronic data security confidence level, electronic communication behaviors, and interest in using eHealth communication tools with clients of staff at community-based HIV/AIDS service organizations.

Methods

Staff were recruited from 7 community-based HIV/AIDS service organizations in the southern United States (3 in South Carolina and 4 in Texas). The principal investigator used state department of health websites to identify community-based HIV/AIDS service organizations. Staff were included if they provided HIV/STD prevention education to clients. A recruitment letter was sent to community-based HIV/AIDS service organization leaders who then used snowball sampling to recruit eligible staff. Chi-square tests were used.

Results

Among staff (n=59) who participated in the study, 66% (39/59) were very or completely confident that safeguards are in place to keep electronically shared information from being seen by other people; 68% (40/59) used email, 58% (34/59) used text messages, 25% (15/59) used social media, 15% (9/59) used a mobile app, 8% (5/59) used web-enabled videoconferencing, and 3% (2/59) used other tools (eg, electronic medical record, healthnavigator.com website) to communicate electronically with their clients. More than half were very interested in using eHealth communication tools in the future for sharing appointment reminders (67%, 38/59) and general health tips (61%, 34/59) with their clients. Half were very interested in using eHealth communication tools in the future to share HIV medication reminders with their clients (50%, 29/59). Forty percent (23/59) were very interested in using eHealth communication tools to share vaccination reminders with their clients.

Conclusions

Community-based HIV/AIDS service organization staff had some level of confidence that safeguards were in place to keep electronically shared information from being seen by other people. This is critically important given the sensitivity of the information shared between community-based HIV/AIDS service organization staff and their clients, and because many staff were very interested in using eHealth communication tools with their clients in the future. It is very likely that eHealth communication tools can be used in community settings to improve health outcomes across the HIV care continuum; in the interim, more research is needed to better understand factors that may facilitate or impede community-based HIV/AIDS service organization staff use and client acceptability.
MyPath to Home Web-Based Application for the Geriatric Rehabilitation Program at Bruyère Continuing Care: User-Centered Design and Feasibility Testing Study
Authors: Backman Chantal , Harley Anne , Kuziemsky Craig , Mercer Jay , Peyton Liam
Published: July 2020

Background

When older adults return home from geriatric rehabilitation in a hospital, remembering the plethora of medical advice and medical instructions provided can be overwhelming for them and for their caregivers.

Objective

The overall objective was to develop and test the feasibility of a novel web-based application called MyPath to Home that can be used to manage the personalized needs of geriatric rehabilitation patients during their transition from the hospital to home.

Methods

This study involved (1) co-designing a patient- and clinician-tailored web-based application and (2) testing the feasibility of the application to manage the needs of geriatric rehabilitation patients when leaving the hospital. In phase 1, we followed a user-centered design process integrated with the modern agile software development methodology to iteratively co-design the application. The approach consisted of three cycles in which we engaged patients, caregivers, and clinicians to design a series of prototypes (cycles 1-3). In phase 2, we conducted a single-arm feasibility pilot test of MyPath to Home. Baseline and follow-up surveys, as well as select semistructured interviews were conducted.

Results

In phase 1, semistructured interviews and talk-aloud sessions were conducted with patients/caregivers (n=5) and clinicians (n=17) to design the application. In phase 2, patients (n=30), caregivers (n=18), and clinicians (n=20) received access to use the application. Patients and their caregivers were asked to complete baseline and follow-up surveys. A total of 91% (21/23) of patients would recommend this application to other patients. In addition, clinicians (n=6) and patients/caregivers (n=6) were interviewed to obtain further details on the value of the web-based application with respect to engaging patients and facilitating communication and sharing of information with the health care team.

Conclusions

We were successful at designing the MyPath to Home prototype for patients and their caregivers to engage with their clinicians during the transition from geriatric rehabilitation to home. Further work is needed to increase the uptake and usage by clinicians, and determine if this translates to meaningful changes in clinical and functional outcomes.

International Registered Report Identifier (IRRID)

RR2-10.2196/11031
A New Approach for Detecting Sleep Apnea Using a Contactless Bed Sensor: Comparison Study
Authors: Sadek Ibrahim , Heng Terry Tan Soon , Seet Edwin , Abdulrazak Bessam
Published: July 2020

Background

At present, there is an increased demand for accurate and personalized patient monitoring because of the various challenges facing health care systems. For instance, rising costs and lack of physicians are two serious problems affecting the patient’s care. Nonintrusive monitoring of vital signs is a potential solution to close current gaps in patient monitoring. As an example, bed-embedded ballistocardiogram (BCG) sensors can help physicians identify cardiac arrhythmia and obstructive sleep apnea (OSA) nonintrusively without interfering with the patient’s everyday activities. Detecting OSA using BCG sensors is gaining popularity among researchers because of its simple installation and accessibility, that is, their nonwearable nature. In the field of nonintrusive vital sign monitoring, a microbend fiber optic sensor (MFOS), among other sensors, has proven to be suitable. Nevertheless, few studies have examined apnea detection.

Objective

This study aims to assess the capabilities of an MFOS for nonintrusive vital signs and sleep apnea detection during an in-lab sleep study. Data were collected from patients with sleep apnea in the sleep laboratory at Khoo Teck Puat Hospital.

Methods

In total, 10 participants underwent full polysomnography (PSG), and the MFOS was placed under the patient’s mattress for BCG data collection. The apneic event detection algorithm was evaluated against the manually scored events obtained from the PSG study on a minute-by-minute basis. Furthermore, normalized mean absolute error (NMAE), normalized root mean square error (NRMSE), and mean absolute percentage error (MAPE) were employed to evaluate the sensor capabilities for vital sign detection, comprising heart rate (HR) and respiratory rate (RR). Vital signs were evaluated based on a 30-second time window, with an overlap of 15 seconds. In this study, electrocardiogram and thoracic effort signals were used as references to estimate the performance of the proposed vital sign detection algorithms.

Results

For the 10 patients recruited for the study, the proposed system achieved reasonable results compared with PSG for sleep apnea detection, such as an accuracy of 49.96% (SD 6.39), a sensitivity of 57.07% (SD 12.63), and a specificity of 45.26% (SD 9.51). In addition, the system achieved close results for HR and RR estimation, such as an NMAE of 5.42% (SD 0.57), an NRMSE of 6.54% (SD 0.56), and an MAPE of 5.41% (SD 0.58) for HR, whereas an NMAE of 11.42% (SD 2.62), an NRMSE of 13.85% (SD 2.78), and an MAPE of 11.60% (SD 2.84) for RR.

Conclusions

Overall, the recommended system produced reasonably good results for apneic event detection, considering the fact that we are using a single-channel BCG sensor. Conversely, satisfactory results were obtained for vital sign detection when compared with the PSG outcomes. These results provide preliminary support for the potential use of the MFOS for sleep apnea detection.
Investigation of a Mobile Health Texting Tool for Embedding Patient-Reported Data Into Diabetes Management (i-Matter): Development and Usability Study
Authors: Schoenthaler Antoinette , Cruz Jocelyn , Payano Leydi , Rosado Marina , Labbe Kristen , Johnson Chrystal , Gonzalez Javier , Patxot Melissa , Patel Smit , Leven Eric , Mann Devin
Published: July 2020

Background

Patient-reported outcomes (PROs) are increasingly being used in the management of type 2 diabetes (T2D) to integrate data from patients’ perspective into clinical care. To date, the majority of PRO tools have lacked patient and provider involvement in their development, thus failing to meet the unique needs of end users, and lack the technical infrastructure to be integrated into the clinic workflow.

Objective

This study aims to apply a systematic, user-centered design approach to develop i-Matter (investigating a mobile health [mHealth] texting tool for embedding patient-reported data into diabetes management), a theory-driven, mobile PRO system for patients with T2D and their primary care providers.

Methods

i-Matter combines text messaging with dynamic data visualizations that can be integrated into electronic health records (EHRs) and personalized patient reports. To build i-Matter, we conducted semistructured group and individual interviews with patients with T2D and providers, a design thinking workshop to refine initial ideas and design the prototype, and user testing sessions of prototypes using a rapid-cycle design (ie, design-test-modify-retest).

Results

Using an iterative user-centered process resulted in the identification of 6 PRO messages that were relevant to patients and providers: medication adherence, dietary behaviors, physical activity, sleep quality, quality of life, and healthy living goals. In user testing, patients recommended improvements to the wording and timing of the PRO text messages to increase clarity and response rates. Patients also recommended including motivational text messages to help sustain engagement with the program. The personalized report was regarded as a key tool for diabetes self-management by patients and providers because it aided in the identification of longitudinal patterns in the PRO data, which increased patient awareness of their need to adopt healthier behaviors. Patients recommended adding individualized tips to the journal on how they can improve their behaviors. Providers preferred having a separate tab built into the EHR that included the personalized report and highlighted key trends in patients’ PRO data over the past 3 months.

Conclusions

PRO tools that capture patients’ well-being and the behavioral aspects of T2D management are important to patients and providers. A clinical trial will test the efficacy of i-Matter in 282 patients with uncontrolled T2D.

Trial Registration

ClinicalTrials.gov NCT03652389; https://clinicaltrials.gov/ct2/show/NCT03652389
Expert Opinions on Web-Based Peer Education Interventions for Youth Sexual Health Promotion: Qualitative Study
Authors: Martin Philippe , Alberti Corinne , Gottot Serge , Bourmaud Aurelie , de La Rochebrochard Elise
Published: July 2020

Background

Participatory education, in the form of peer education, may be an effective way to promote youth sexual health. With the advent of the internet, web-based interventions have potential as an attractive new tool for sexual health promotion by peers.

Objective

The aim of this study was to evaluate professional experts’ opinions on the perspectives for web-based participatory interventions to promote sexual health by peers and among young people.

Methods

Semistructured interviews were carried out with 20 experts (stakeholders in direct contact with young people, researchers, and institutional actors) specializing in sexual health, health promotion, peer education, youth, internet, and social media. After coding with N’Vivo, data were subjected to qualitative thematic analysis.

Results

The majority of experts (18/20, 90%) found this kind of intervention to be attractive, but highlighted the necessary conditions, risks, and limitations attached to developing an acceptable peer intervention on the internet for sexual health promotion among young people. Five main themes were identified: (1) an internet intervention; (2) sexual health; (3) internet skills, and uses and the need for moderation; (4) multifaceted peers; and (5) minority peers. In the absence of youth interest for institutional messages, the experts highlighted the attractive participatory features of web-based interventions and the need for geolocalized resources. However, they also warned of the limitations associated with the possibility of integrating peers into education: peers should not be mere messengers, and should remain peers so as not to be outsiders to the target group. Experts highlighted concrete proposals to design an online participatory peer intervention, including the process of peer implication, online features in the intervention, and key points for conception and evaluation.

Conclusions

The experts agreed that web-based participatory interventions for youth sexual health promotion must be tailored to needs, uses, and preferences. This type of action requires youth involvement framed in an inclusive and holistic sexual health approach. Peer education can be implemented via the internet, but the design of the intervention also requires not being overly institutional in nature. Involving young people in their own education in an interactive, safe online space has the potential to develop their empowerment and to foster long-term positive behaviors, especially in the area of sexual health.
Patients’ Experiences of Telephone-Based and Web-Based Cognitive Behavioral Therapy for Irritable Bowel Syndrome: Longitudinal Qualitative Study
Authors: Hughes Stephanie , Sibelli Alice , Everitt Hazel A , Moss-Morris Rona , Chalder Trudie , Harvey J Matthew , Vas Falcao Andrea , Landau Sabine , O'Reilly Gilly , Windgassen Sula , Holland Rachel , Little Paul , McCrone Paul , Goldsmith Kimberley , Coleman Nicholas , Logan Robert , Bishop Felicity L
Published: July 2020

Background

Cognitive behavioral therapy (CBT) is recommended in guidelines for people with refractory irritable bowel syndrome (IBS). However, the availability of CBT is limited, and poor adherence has been reported in face-to-face CBT.

Objective

Nested within a randomized controlled trial of telephone- and web-delivered CBT for refractory IBS, this qualitative study aims to identify barriers to and facilitators of engagement over time with the interventions, identify social and psychological processes of change, and provide insight into trial results.

Methods

A longitudinal qualitative study was nested in a randomized controlled trial. Repeated semistructured interviews were conducted at 3 (n=34) and 12 months (n=25) post baseline. Participants received telephone-based CBT (TCBT; n=17 at 3 months and n=13 at 12 months) or web-based CBT (WCBT; n=17 at 3 months and n=12 at 12 months). Inductive thematic analysis was used to analyze the data.

Results

Participants viewed CBT as credible for IBS, perceived their therapists as knowledgeable and supportive, and liked the flexibility of web-based and telephone-based delivery; these factors facilitated engagement. Potential barriers to engagement in both groups (mostly overcome by our participants) included initial skepticism and concerns about the biopsychosocial nature of CBT, initial concerns about telephone-delivered talking therapy, challenges of maintaining motivation and self-discipline given already busy lives, and finding nothing new in the WCBT (WCBT group only). Participants described helpful changes in their understanding of IBS, attitudes toward IBS, ability to recognize IBS patterns, and IBS-related behaviors. Consistent with the trial results, participants described lasting positive effects on their symptoms, work, and social lives. Reasons and remedies for some attenuation of effects were identified.

Conclusions

Both TCBT and WCBT for IBS were positively received and had lasting positive impacts on participants’ understanding of IBS, IBS-related behaviors, symptoms, and quality of life. These forms of CBT may broaden access to CBT for IBS.
An Artificial Intelligence Fusion Model for Cardiac Emergency Decision Making: Application and Robustness Analysis
Authors: Gong Liheng , Zhang Xiao , Li Ling
Published: July 2020

Background

During cardiac emergency medical treatment, reducing the incidence of avoidable adverse events, ensuring the safety of patients, and generally improving the quality and efficiency of medical treatment have been important research topics in theoretical and practical circles.

Objective

This paper examines the robustness of the decision-making reasoning process from the overall perspective of the cardiac emergency medical system.

Methods

The principle of robustness was introduced into our study on the quality and efficiency of cardiac emergency decision making. We propose the concept of robustness for complex medical decision making by targeting the problem of low reasoning efficiency and accuracy in cardiac emergency decision making. The key bottlenecks such as anti-interference capability, fault tolerance, and redundancy were studied. The rules of knowledge acquisition and transfer in the decision-making process were systematically analyzed to reveal the core role of knowledge reasoning.

Results

The robustness threshold method was adopted to construct the robustness criteria group of the system, and the fusion and coordination mechanism was realized through information entropy, information gain, and mutual information methods.

Conclusions

A set of fusion models and robust threshold methods such as the R2CMIFS (treatment mode of fibroblastic sarcoma) model and the RTCRF (clinical trial observation mode) model were proposed. Our study enriches the theoretical research on robustness in this field.
Developing a Mobile App (iGAM) to Promote Gingival Health by Professional Monitoring of Dental Selfies: User-Centered Design Approach
Authors: Tobias Guy , Spanier Assaf B
Published: July 2020

Background

Dental visits are unpleasant; sometimes, patients only seek treatment when they are in intolerable pain. Recently, the novel coronavirus (COVID-19) pandemic has highlighted the need for remote communication when patients and dentists cannot meet in person.
Gingivitis is very common and characterized by red, swollen, bleeding gums. Gingivitis heals within 10 days of professional care and with daily, thorough oral hygiene practices. If left untreated, however, its progress may lead to teeth becoming mobile or lost. Of the many medical apps currently available, none monitor gingivitis.

Objective

This study aimed to present a characterization and development model of a mobile health (mHealth) app called iGAM, which focuses on periodontal health and improves the information flow between dentists and patients.

Methods

A focus group discussed the potential of an app to monitor gingivitis, and 3 semistructured in-depth interviews were conducted on the use of apps for monitoring gum infections. We used a qualitative design process based on the Agile approach, which incorporated the following 5 steps: (1) user story, (2) use cases, (3) functional requirements, (4) nonfunctional requirements, and (5) Agile software development cycles. In a pilot study with 18 participants aged 18-45 years and with different levels of health literacy, participants were given a toothbrush, toothpaste, mouthwash, toothpicks, and dental floss. After installing iGAM, they were asked to photograph their gums weekly for 4 weeks.

Results

All participants in the focus group believed in the potential of a mobile app to monitor gingivitis and reduce its severity. Concerns about security and privacy issues were discussed. From the interviews, 2 themes were derived: (1) “what's in it for me?” and (2) the need for a take-home message. The 5 cycles of development highlighted the importance of communication between dentists, app developers, and the pilot group. Qualitative analysis of the data from the pilot study showed difficulty with: (1) the camera, which was alleviated with the provision of mouth openers, and (2) the operation of the phone, which was alleviated by changing the app to be fully automated, with a weekly reminder and an instructions document. Final interviews showed satisfaction.

Conclusions

iGAM is the first mHealth app for monitoring gingivitis using self-photography. iGAM facilitates the information flow between dentists and patients between checkups and may be useful when face-to-face consultations are not possible (such as during the COVID-19 pandemic).
Clinical Characteristics and Outcomes of Childbearing-Age Women With COVID-19 in Wuhan: Retrospective, Single-Center Study
Authors: Wei Lijie , Gao Xuan , Chen Suhua , Zeng Wanjiang , Wu Jianli , Lin Xingguang , Zhang Huiting , Mwamaka Sharifu Lali , Chen Ling , Feng Ling , Wang Shaoshuai
Published: July 2020

Background

Since December 2019, an outbreak of the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly in Wuhan and worldwide. However, previous studies on pregnant patients were limited.

Objective

The aim of this study is to evaluate the clinical characteristics and outcomes of pregnant and nonpregnant women with COVID-19.

Methods

This study retrospectively collected epidemiological, clinical, laboratory, imaging, management, and outcome data of 43 childbearing-age women patients (including 17 pregnant and 26 nonpregnant patients) who presented with laboratory-confirmed COVID-19 in Tongji Hospital, Wuhan, China from January 19 to March 2, 2020. Clinical outcomes were followed up to March 28, 2020.

Results

Of the 43 childbearing-age women in this study, none developed a severe adverse illness or died. The median ages of pregnant and nonpregnant women were 33.0 and 33.5 years, respectively. Pregnant women had a markedly higher proportion of history exposure to hospitals within 2 weeks before onset compared to nonpregnant women (9/17, 53% vs 5/26, 19%, P=.02) and a lower proportion of other family members affected (4/17, 24% vs 19/26, 73%, P=.004). Fever (8/17, 47% vs 18/26, 69%) and cough (9/17, 53% vs 12/26, 46%) were common onsets of symptoms for the two groups. Abdominal pain (n=4, 24%), vaginal bleeding (n=1, 6%), reduced fetal movement (n=1, 6%), and increased fetal movement (n=2, 13%) were observed at onset in the 17 pregnant patients. Higher neutrophil and lower lymphocyte percent were observed in the pregnant group compared to the nonpregnant group (79% vs 56%, P<.001; 15% vs 33%, P<.001, respectively). In both groups, we observed an elevated concentration of high-sensitivity C-reactive protein, erythrocyte sedimentation rate, aminotransferase, and lactate dehydrogenase. Concentrations of alkaline phosphatase and D-dimer in the pregnant group were significantly higher than those of the nonpregnant group (119.0 vs 48.0 U/L, P<.001; 2.1 vs 0.3μg/mL, P<.001, respectively). Both pregnant (4/10, 40%) and nonpregnant (8/15, 53%) women tested positive for influenza A virus. A majority of pregnant and nonpregnant groups received antiviral (13/17, 76% vs 25/26, 96%) and antibiotic (13/17, 76% vs 23/26, 88%) therapy. Additionally, both pregnant (2/11, 18%) and nonpregnant (2/19, 11%) recovered women redetected positive for SARS-CoV-2 after discharge.

Conclusions

The epidemiology and clinical and laboratory features of pregnant women with COVID-19 were diverse and atypical, which increased the difficulty of diagnosis. Most pregnant women with COVID-19 were mild and moderate, and rarely developed severe pneumonia or severe adverse outcomes.
Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries
Authors: Lim Cherry , Miliya Thyl , Chansamouth Vilada , Aung Myint Thazin , Karkey Abhilasha , Teparrukkul Prapit , Rahul Batra , Lan Nguyen Phu Huong , Stelling John , Turner Paul , Ashley Elizabeth , van Doorn H Rogier , Lin Htet Naing , Ling Clare , Hinjoy Soawapak , Iamsirithaworn Sopon , Dunachie Susanna , Wangrangsimakul Tri , Hantrakun Viriya , Schilling William , Yen Lam Minh , Tan Le Van , Hlaing Htay Htay , Mayxay Mayfong , Vongsouvath Manivanh , Basnyat Buddha , Edgeworth Jonathan , Peacock Sharon J , Thwaites Guy , Day Nicholas PJ , Cooper Ben S , Limmathurotsakul Direk
Published: July 2020

Background

Reporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel.

Objective

This study aimed to develop and test an application that can support a local hospital to analyze routinely collected electronic data independently and generate AMR surveillance reports rapidly.

Methods

An offline application to generate standardized AMR surveillance reports from routinely available microbiology and hospital data files was written in the R programming language (R Project for Statistical Computing). The application can be run by double clicking on the application file without any further user input. The data analysis procedure and report content were developed based on the recommendations of the World Health Organization Global Antimicrobial Resistance Surveillance System (WHO GLASS). The application was tested on Microsoft Windows 10 and 7 using open access example data sets. We then independently tested the application in seven hospitals in Cambodia, Lao People’s Democratic Republic, Myanmar, Nepal, Thailand, the United Kingdom, and Vietnam.

Results

We developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), which can support clinical microbiology laboratories to analyze their microbiology and hospital data files (in CSV or Excel format) onsite and promptly generate AMR surveillance reports (in PDF and CSV formats). The data files could be those exported from WHONET or other laboratory information systems. The automatically generated reports contain only summary data without patient identifiers. The AMASS application is downloadable from https://www.amass.website/. The participating hospitals tested the application and deposited their AMR surveillance reports in an open access data repository.

Conclusions

The AMASS is a useful tool to support the generation and sharing of AMR surveillance reports.
The Association Between Electronic Device Use During Family Time and Family Well-Being: Population-Based Cross-Sectional Study
Authors: Zhao Sheng Zhi , Guo Ningyuan , Wang Man Ping , Fong Daniel Yee Tak , Lai Agnes Yuen Kwan , Chan Sophia Siu-Chee , Lam Tai Hing , Ho Daniel Sai Yin
Published: July 2020

Background

Electronic devices (eDevices) may have positive or negative influences on family communication and well-being depending on how they are used.

Objective

We examined eDevice use during family time and its association with the quality of family communication and well-being in Hong Kong Chinese adults.

Methods

In 2017, a probability-based 2-stage random sampling landline telephone survey collected data on eDevice use in daily life and during family time (eg, family dinner) and the presence of rules banning eDevice use during family dinner. Family communication quality was rated from 0 to 10 with higher scores being favorable. Family well-being was calculated as a composite mean score of 3 items each using the same scale from 0 to 10. The associations of family communication quality and well-being with eDevice use in daily life and during family time were estimated using beta-coefficient (β) adjusting for sociodemographics. The mediating role of family communication quality in the association between eDevice use and family well-being was analyzed.

Results

Of the 2064 respondents (mean age 56.4 [SD 19.2] years, 1269/2064 [61.48%] female), 1579/2059 (76.69%) used an eDevice daily for a mean of 3.6 hours (SD 0.1) and 257/686 (37.5%) used it for 30+ minutes before sleep. As much as 794/2046 (38.81%) often or sometimes used an eDevice during family time including dinner (311/2017, 15.42%); 713/2012 (35.44%) reported use of an eDevice by family members during dinner. Lower family communication quality was associated with hours of eDevice use before sleep (adjusted β=–.25; 95% CI –0.44 to –0.05), and often use (vs never use) of eDevice during family dinner by oneself (adjusted β=–.51; 95% CI –0.91 to –0.10) and family members (adjusted β=–.54; 95% CI –0.79 to –0.29). Similarly, lower family well-being was associated with eDevice use before sleep (adjusted β=–.26; 95% CI –0.42 to –0.09), and often use during family dinner by oneself (adjusted β=–.48; 95% CI –0.83 to –0.12) and family members (adjusted β=–.50; 95% CI –0.72 to –0.28). Total ban of eDevice use during family dinner was negatively associated with often use by oneself (adjusted odds ratio 0.49; 95% CI 0.29 to 0.85) and family members (adjusted odds ratio 0.41; 95% CI 0.28, 0.60) but not with family communication and well-being. Lower family communication quality substantially mediated the total effect of the association of eDevice use time before sleep (61.2%) and often use at family dinner by oneself (87.0%) and by family members (67.8%) with family well-being.

Conclusions

eDevice use before sleep and during family dinner was associated with lower family well-being, and the association was substantially mediated by family communication quality. Our results suggest that interventions on smart use of eDevice may improve family communication and well-being.
Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic
Authors: Neuraz Antoine , Lerner Ivan , Digan William , Paris Nicolas , Tsopra Rosy , Rogier Alice , Baudoin David , Cohen Kevin Bretonnel , Burgun Anita , Garcelon Nicolas , Rance Bastien ,   AP-HP/Universities/INSERM COVID-19 Research Collaboration; AP-HP COVID CDR Initiative
Published: July 2020

Background

A novel disease poses special challenges for informatics solutions. Biomedical informatics relies for the most part on structured data, which require a preexisting data or knowledge model; however, novel diseases do not have preexisting knowledge models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to a novel knowledge model. However, although this idea has often been suggested, no opportunity has arisen to actually test it in real time. The current coronavirus disease (COVID-19) pandemic presents such an opportunity.

Objective

The aim of this study was to evaluate the added value of information from clinical text in response to emergent diseases using natural language processing (NLP).

Methods

We explored the effects of long-term treatment by calcium channel blockers on the outcomes of COVID-19 infection in patients with high blood pressure during in-patient hospital stays using two sources of information: data available strictly from structured electronic health records (EHRs) and data available through structured EHRs and text mining.

Results

In this multicenter study involving 39 hospitals, text mining increased the statistical power sufficiently to change a negative result for an adjusted hazard ratio to a positive one. Compared to the baseline structured data, the number of patients available for inclusion in the study increased by 2.95 times, the amount of available information on medications increased by 7.2 times, and the amount of additional phenotypic information increased by 11.9 times.

Conclusions

In our study, use of calcium channel blockers was associated with decreased in-hospital mortality in patients with COVID-19 infection. This finding was obtained by quickly adapting an NLP pipeline to the domain of the novel disease; the adapted pipeline still performed sufficiently to extract useful information. When that information was used to supplement existing structured data, the sample size could be increased sufficiently to see treatment effects that were not previously statistically detectable.
Exploring User Needs in the Development of a Virtual Reality–Based Advanced Life Support Training Platform: Exploratory Usability Study
Authors: Moore Nathan , Yoo Soojeong , Poronnik Philip , Brown Martin , Ahmadpour Naseem
Published: July 2020

Background

Traditional methods of delivering Advanced Life Support (ALS) training and reaccreditation are resource-intensive and costly. Interactive simulations and gameplay using virtual reality (VR) technology can complement traditional training processes as a cost-effective, engaging, and flexible training tool.

Objective

This exploratory study aimed to determine the specific user needs of clinicians engaging with a new interactive VR ALS simulation (ALS-SimVR) application to inform the ongoing development of such training platforms.

Methods

Semistructured interviews were conducted with experienced clinicians (n=10, median age=40.9 years) following a single playthrough of the application. All clinicians have been directly involved in the delivery of ALS training in both clinical and educational settings (median years of ALS experience=12.4; all had minimal or no VR experience). Interviews were supplemented with an assessment of usability (using heuristic evaluation) and presence.

Results

The ALS-SimVR training app was well received. Thematic analysis of the interviews revealed five main areas of user needs that can inform future design efforts for creating engaging VR training apps: affordances, agency, diverse input modalities, mental models, and advanced roles.

Conclusions

This study was conducted to identify the needs of clinicians engaging with ALS-SimVR. However, our findings revealed broader design considerations that will be crucial in guiding future work in this area. Although aligning the training scenarios with accepted teaching algorithms is important, our findings reveal that improving user experience and engagement requires careful attention to technology-specific issues such as input modalities.
Virtual Consultations and the Role of Technology During the COVID-19 Pandemic for People With Type 2 Diabetes: The UK Perspective
Authors: Quinn Lauren M , Davies Melanie J , Hadjiconstantinou Michelle
Published: July 2020

The coronavirus disease (COVID-19) pandemic has presented unique challenges for people with diabetes, in addition to their high-risk stratification for infection. Supporting people with diabetes to self-care has been critical to reduce their risk of severe infection. This global pandemic has presented an opportunity to digitalize diabetes care and rapidly implement virtual diabetes clinics, with the aim of optimizing diabetes management and well-being, while keeping patients safe. We performed a rapid review of the literature to evaluate the feasibility and effectiveness of virtual clinics in diabetes care before and during the COVID-19 pandemic and have combined these findings with our own reflections in practice. We identified examples demonstrating safety and feasibility of virtual diabetes clinics, which aligns with our own clinical experience during the pandemic. The advantages of virtual clinics include reduced treatment burden, improved therapeutic alliances, societal and psychological benefits, and in our experience, innovative solutions to overcome the challenges presented by the transition from in-person to virtual care. We have provided three infographics to illustrate lessons learned and key recommendations, including steps to establish a virtual diabetes clinic, a checklist guide for health care professionals conducting virtual clinics, and a patient guide for making the most out of the virtual clinic. It is important to continue adapting to this pandemic and to make technology a sustainable option for the future of diabetes care.
AutoScore: A Machine Learning–Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records
Authors: Xie Feng , Chakraborty Bibhas , Ong Marcus Eng Hock , Goldstein Benjamin Alan , Liu Nan
Published: July 2020

Background

Risk scores can be useful in clinical risk stratification and accurate allocations of medical resources, helping health providers improve patient care. Point-based scores are more understandable and explainable than other complex models and are now widely used in clinical decision making. However, the development of the risk scoring model is nontrivial and has not yet been systematically presented, with few studies investigating methods of clinical score generation using electronic health records.

Objective

This study aims to propose AutoScore, a machine learning–based automatic clinical score generator consisting of 6 modules for developing interpretable point-based scores. Future users can employ the AutoScore framework to create clinical scores effortlessly in various clinical applications.

Methods

We proposed the AutoScore framework comprising 6 modules that included variable ranking, variable transformation, score derivation, model selection, score fine-tuning, and model evaluation. To demonstrate the performance of AutoScore, we used data from the Beth Israel Deaconess Medical Center to build a scoring model for mortality prediction and then compared the data with other baseline models using the receiver operating characteristic analysis. A software package in R 3.5.3 (R Foundation) was also developed to demonstrate the implementation of AutoScore.

Results

Implemented on the data set with 44,918 individual admission episodes of intensive care, the AutoScore-created scoring models performed comparably well as other standard methods (ie, logistic regression, stepwise regression, least absolute shrinkage and selection operator, and random forest) in terms of predictive accuracy and model calibration but required fewer predictors and presented high interpretability and accessibility. The nine-variable, AutoScore-created, point-based scoring model achieved an area under the curve (AUC) of 0.780 (95% CI 0.764-0.798), whereas the model of logistic regression with 24 variables had an AUC of 0.778 (95% CI 0.760-0.795). Moreover, the AutoScore framework also drives the clinical research continuum and automation with its integration of all necessary modules.

Conclusions

We developed an easy-to-use, machine learning–based automatic clinical score generator, AutoScore; systematically presented its structure; and demonstrated its superiority (predictive performance and interpretability) over other conventional methods using a benchmark database. AutoScore will emerge as a potential scoring tool in various medical applications.
Perceptions and Acceptability of Digital Interventions Among Tuberculosis Patients in Cambodia: Qualitative Study of Video-Based Directly Observed Therapy (Preprint)
Authors: Rabinovich Lila , Molton James Steven , Ooi Wei Tsang , Paton Nicholas Iain , Batra Shelly , Yoong Joanne
Published: July 2020

BACKGROUND

Despite the development of effective drugs for treatment, tuberculosis remains one of the leading causes of death from an infectious disease worldwide. One of the greatest challenges to tuberculosis control is patient adherence to treatment. Recent research has shown that video-based directly observed therapy is a feasible and effective approach to supporting treatment adherence in high-income settings. However, few studies have explored the potential for such a solution in a low- or middle-income country setting. Globally, these countries’ rapidly rising rate of mobile penetration suggests that the potential for translation of these results may be high.

OBJECTIVE

We sought to examine patient perceptions related to the use of mobile health, and specifically video-based directly observed therapy, in a previously unstudied patient demographic: patients with tuberculosis in a low-income country setting (Cambodia).

METHODS

We conducted a cross-sectional qualitative study in urban and periurban areas in Cambodia, consisting of 6 focus groups with tuberculosis patients who were receiving treatment (standard directly observed therapy) through a nongovernmental organization.

RESULTS

Familiarity with mobile technology and apps was widespread in this population, and overall willingness to consider a mobile app for video-based directly observed therapy was high. However, we identified potential challenges. First, patients very much valued their frequent in-person interactions with their health care provider, which may be reduced with the video-based directly observed therapy intervention. Second, there may be technical issues to address, including how to make the app suitable for illiterate participants.

CONCLUSIONS

While video-based directly observed therapy is a promising technology, even in country settings where mobile penetration is reportedly almost universal, it should be introduced with caution. However, the results were generally promising and yielded important insights that not only will be translated into the further adaptation of key features of video-based directly observed therapy for tuberculosis patients in Cambodia, but also can inform the future design and successful implementation of video-based directly observed therapy interventions in low- and middle-income settings more generally.