bluuebunny/crossref_metadata_2025 huggingface dataset:
PREDICTIVE MICROBIOLOGY OF FOOD
Authors: Rosiak Elżbieta , Kajak-Siemaszko Katarzyna , Trząskowska Monika , Kołożyn-Krajewska Danuta
Published: August 2020

The beginnings of predictive microbiology date back to 1920 when Bigelow developed a logarithmic-linear dependence of kinetics on the death of microorganisms. Predictive microbiology is a sub-discipline of food microbiology, whose task is to predict the behavior of microorganisms in food using mathematical models. The predictive model for microbiology is usually a simplified description of the correlation between the observed reactions and the factors responsible for the occurrence of these reactions. There are several main conceptual models (empirical vs. mechanistic, stochastic vs. deterministic, dynamic vs. static), in which there are model divisions depending on the type of examined microorganism or the nature of the problems caused by microbes (kinetic vs. probabilistic), described variables (first, secondary and tertiary) or the influence of environmental factors on microbial populations (growth, survival, inactivation). The new generations of models include molecular and genomic models, transfer models, Artificial Neural Network, interactions between species, and single cell models.

The process of creating a mathematical model requires coordination of work and the knowledge of: microbiology, statistics, mathematics, chemistry, process engineering and computer and web science. It also requires appropriate hardware and software. There are four stages in the construction of a mathematical model: planning; data collection and analysis; mathematical description; validation and storage of data.

In recent years, numerous computer software programs have been developed: FISHMAP, FSSP, Dairy Product Safety Predictor, Symbiosis, GroPIN, Listeria Meat FDA-iRISK, TRiMiCri, Microbial Responses, GlnaFiT, FILTREX, PMM-Lab. ComBase database, on the other hand, is a pioneering achievement as an on-line tool. Some programs meet the requirements for creating Food Safety Model Repositories (FSMR).

1. Introduction. 2. The idea of predictive microbiology. 3. Historical background of predictive microbiology. 4. The concept of a model and modeling concepts in food microbiology. 4.1. Concept 1: empirical vs. mechanistic models. 4.2. Concept 2: static vs. dynamic models. 4.3. Concept 3: stochastic vs. deterministic models. 5. Breakdowns of prognostic models. 5.1. Neural networks. 5.2. A new generation of predictive models. 6. The construction of the predictive model. 6.1. Planning the experiment. 6.2. Collection of data. 6.3. Data analysis. 6.4. Model validation. 7. Predictive microbiology in risk analysis. 8. Summary
DRUG RESISTANCE IN THE GENUS ENTEROCOCCUS– CURRENT PROBLEM IN HUMANS AND ANIMALS
Authors: Talaga-Ćwiertnia Katarzyna , Bulanda Małgorzata
Published: August 2020

Drug-resistant bacteria from the genus Enterococcus are currently among the most important pathogens behind healthcare-associated infections. The drug resistance of these bacteria has been on the increase since the 1980s, leeding to their multi-drug resistance. Selective pressure, present mainly in the hospital environment, contributed to this phenomenon. However, also outside the hospital environment selective pressure comes into play, namely the use of antibiotics as promoters of growth in animal husbandry and in food production. Household pets form a reservoir of drug-resistant enterococcal strains, too. The exchange of resistance genes between enterococcal strains from different niches poses a threat to public health.

1. Introduction. 2. Hospital environment. 3. Farm animals. 4. Food. 5. Household pets. 6. Summary
FROM A COMMENSAL TO A PATHOGEN – TWO FACES OF STAPHYLOCOCCUS EPIDERMIDIS
Authors: Podgórska Beata , Kędzia Danuta
Published: August 2020

Staphylococcus epidermidis is a commensal organism and the most abundant constituent of the healthy human skin and mucous membranes micrbiota. It is well adapted to colonize and evade human antimicrobial barriers. Staphylococcus epidermidis not only competes with potentially harmful pathogens, but also produces a plethora of proteins supporting host natural defenses. At the same time, S. epidermidis is an opportunistic pathogen recognised as one of the leading causes of healthcare-associated infections. S. epidermidis is mainly responsible for bloodstream infections and other biomedical device-related infections. Hospital strains of S. epidermidis form protective biofilm and are characterised with antibiotic resistance.

1. Introduction. 2. Staphylococcus epidermidis as a commensal organism. 2.1. Origin of S. epidermidis. 2.2. Human skin as S. epidermidisenvironment. 2.3. Adaptation mechanisms of S. epidermidis. 2.4. Mechanisms of supporting skin’s antimicrobial defences. 2.5. Influence on activity of host cells. 3. S. epidermidis as a pathogen. 3.1. Biofilm and virulence factors. 4. Summary
TYPE VB AND VI SECRETION SYSTEMS AS COMPETITION AGENTS OF GRAM-NEGATIVE BACTERIA
Authors: Gmiter Dawid , Czerwonka Grzegorz , Kaca Wiesław
Published: August 2020

Bacterial competition, defined as a local neighbour interactions, can lead to competitors coexistence, bacterial community self-organization or as travelling waves of species dominance in ecological niches. Bacteria have developed many mechanisms to communicate and compete. Kin discrimination mechanisms in bacterial populations allow species to distinguish a friend from a foe in bacterial environment. Type Vb and VI secretion systems (TVIbSS and TVISS) play crucial role in this phenomenon. A contact-dependent growth inhibition (CDI), primarily found in Escherichia coli strains, utilities CdiB/CdiA protein of type Vb secretion system, described also as two-partner secretion (TPS) system, to inhibit growth of non-kin strains, where cell contact is required. Presence of an intracellular small immunity protein (CdiI) protects E. coli cells from autoinhibition. Other bacterial competition system, primarily found in nodulation process of Rhizobium leguminosarum bv. Trifolii strain, engages type VI secretion system. The structure of TVISS is more complicated and comprises the series of proteins with structural homology to bacteriophage tail proteins and membrane proteins which builds the core of the system (Tss proteins). Meanwhile, other proteins of the TVISS was described as associated proteins (Tag proteins). Important proteins for TVISS are haemolysin coregulated protein (Hcp) which has hexameric, tubular structure and VgrG protein (valine-glycine repeat G) which play a dual role in the process: as a chaperone protein in secretion of effector toxin or/and as a secreted toxin itself. Despite the structural differences of both secretion systems they show functional homology in competition phenomenon and govern the social life of bacterial community.

1. Introduction. 2. Contact-dependent growth inhibition. 2.1. Structure o CDI machinery. 2.2. Effectors of CDI system. 3. Type VI secretion system. 3.1. Structure of type VI secretion system. 3.2. Effectors of type VI secretion system. 4. Membership to polymorphic toxins system. 5. Role of the systems in bacterial biology. 6. Conclusions
“The big wide world of school”: Supporting children on the autism spectrum to successfully transition to primary school: Perspectives from parents and early intervention professionals
Authors: Chen Nigel , Miller Scott , Milbourn Ben , Black Melissa H. , Fordyce Kathryn , Van Der Watt Gerdamari , Alach Tasha , Masi Anne , Frost Grace , Tucker Madonna , Eapen Valsamma , Girdler Sonya
Published: August 2020

Background:

The transition to primary school is often a complex and uncertain time for autistic children and their families. Understanding how best to develop school readiness and support transition to primary school for autistic children is essential. School readiness and transition planning are influenced by a range of personal and contextual factors, and it is important to understand the perspectives of the various stakeholders involved in the transition process.

Methods:

A qualitative exploration employing focus groups and interviews was undertaken with early intervention (EI) staff (n = 45) and parents (n = 18) across Australia to understand their perspectives on school readiness and the transition to primary school.

Results:

Thematic analysis identified four emerging themes facilitating transition including: 1) building the child; 2) building the parents; 3) building the receiving school; and, 4) connecting the system.

Conclusion:

Findings highlight the need to consider school readiness and transition planning from a holistic perspective, ensuring clear, collaborative and ongoing communication between parents, teachers and EI staff, using a strength-based approach, and individualizing transition planning.
The Internationalization of “West Papua” Issue and Its Impact on Indonesia’s Policy to the South Pacific Region
Authors: Lantang Floranesia , Tambunan Edwin M.B
Published: August 2020

This research argues that the internationalization of "West Papua" issue through social media has contributed to a shift of Indonesia's policy to the South Pacific region from ignorance to initiative approach. Underlying this argument is a growing concern of Indonesia regarding the use of social media by Papuan pro-independence activists that resulted to the increasing awareness and support towards the independence of West Papua from Pacific countries as human rights problems become the highlight of West Papua’s issue. The method used in this research was qualitative research method focusing on descriptive analysis of the internationalization of West Papua issue on social media. This research results show that initiative approach from Indonesia is merely narrowing the gap of the issue instead of reducing the internationalization of the West Papua issue.
Numerical investigation of the impact of irregular pipe wall build-up on velocity in the water distribution system
Authors: Kaur Katrin , Vassiljev Anatoli , Annus Ivar , Kändler Nils , Roosimägi Janet
Published: August 2020

This paper presents novel equations for different wall build-up types in old pipes developed for the estimation of real flow velocities in a water distribution system (WDS). This is important when estimating the contamination propagation rate in an operational WDS. Because the inner surface geometry of old rough pipes is complex, real velocities cannot be estimated by conventional WDS models. Therefore, a computational fluid dynamics (CFD) model was used to analyse the flow dynamics in old rough pipes with even and uneven roughness build-up. The developed equations for the velocity correction coefficients derive from the results of numerical simulations. Numerically obtained velocity fields show that in some cases, pipe wall build-up can affect the effective flow section significantly and the flow velocity can be underestimated by more than two times. Therefore, different velocity correction equations have to be used for different types of pipe wall build-up.
Paracetamol degradation by photo-activated peroxydisulfate process (UV/PDS): kinetic study and optimization using central composite design
Authors: Dibene Karima , Yahiaoui Idris , Yahia Cherif Lamia , Aitali Salima , Amrane Abdeltif , Aissani-Benissad Farida
Published: August 2020

In this study, peroxydisulfate (PDS) was successfully activated by UV-irradiation for the degradation of paracetamol (PCT) frequently detected in the environment. Results showed that increasing the initial PDS concentration from 5 to 20 mM promote the removal of PCT from 49.3% to 97.5% after 240 min of reaction time. As the initial PCT concentration increased from 0.066 to 0.132 mM, the degradation efficiency of PCT decreased from 98% to 73% after 240 min of reaction time, while the optimal pH was found to be 6. It is apparent that the degradation rate of PCT was favored by the lamp power regardless of the initial PCT concentration, for 0.132 mM of PCT, the degradation efficiency increased from 73% to 95% when the lamp power increased from 9 to 30 W, respectively. The kinetic of degradation of the PCT was described by a pseudo-second order kinetic model. The model obtained by central composite design led to the following optimal conditions for PCT degradation: 0.132 mM initial PCT concentration, 20 mM PDS dose, pH solution 6 and lamp power 30 W led to the removal of 92% of PCT at 25 °C within 240 min of reaction time.
Análisis de viabilidad y diseño para el abastecimiento de agua potable en la vereda Socota del municipio de Apulo (Cundinamarca, Colombia)
Authors: Jaime Bello Andrea Tatiana , Martínez Jiménez Jenny Alejandra , Torres Quintero Jesús Ernesto
Published: August 2020

El deficiente desarrollo infraestructural en materia de agua potable y saneamiento básico en las zonas rurales de Colombia ha repercutido en la insatisfacción de las necesidades básicas de sus habitantes. Por lo anterior, esta investigación realiza la validación de los criterios fundamentales para el diseño de un sistema que permita abastecer de agua potable a la vereda Socota, municipio de Apulo, aplicando metodologías como el método inverso a la distancia (idw) para la determinación de la precipitación, el método de Thornthwaite para el cálculo de la evapotranspiración, el geométrico para la proyección poblacional y la validación del cumplimiento de criterios para la selección de la opción de abastecimiento más viable para su posterior diseño mediante las ecuaciones de Hazen-Williams. A partir de dichos métodos fue posible identificar una precipitación de 1.101-1.156 mm/año de carácter bimodal con periodos de bajo almacenamiento de agua y un caudal de 0,000295 m3/s para un total de 105 usuarios potenciales. Además, se estableció que la conexión al acueducto Asuarcopsa es la mejor alternativa de abastecimiento, para la cual se requiere un diámetro de tubería igual a una pulgada y un tanque de almacenamiento de 10.195L, siendo posible evidenciar a través de los resultados obtenidos las deficiencias de disponibilidad, continuidad y calidad de agua presentadas por el sistema de abastecimiento actual.
Organizations as Place Builders
Authors: Thomas David F. , Cross Jennifer E.
Published: August 2020

We argue that the role of organizations as agents in the construction of place has been overlooked in the management and organizations literature. Using concepts from sociology, cultural geography, and management, we develop a typology that illustrates how organizations contribute to the social construction of place. This typology presents an analytic scheme for examining the place-building characteristics of organizations and a basis for developing theories on the interdependence between places and organizations.
Role Conflict, Role Balance and Affect: A Model of Well-being of the Working Student
Authors: Lenaghan Janet A. , Sengupta Kaushik
Published: August 2020

A conceptual model of the working college students’ well-being was developed and tested. This study extends existing research and investigated the process by which role-balance, role-conflict and affect are associated with a student’s well-being. Data were obtained from a sample of 320 full-time college students (18-23 years old) who had either a full and a part-time paid job. The model was tested using structural equation modeling. Results supported the proposed conceptual model as well as the enrichment and depletion arguments of students’ engagement in multiple roles and their well-being.
FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PENGGUNAAN OVO PADA MAHASISWA FAKULTAS EKONOMI UNIVERSITAS NEGERI YOGYAKARTA
Authors: Novitasari Rinda , Supriyanto Supriyanto
Published: August 2020

Abstrak: Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi keputusan penggunaan OVO pada mahasiswa Fakultas Ekonomi Universitas Negeri Yogyakarta secara parsial maupun simultan. Faktor-faktor yang diteliti dalam penelitian ini yaitu gaya hidup, persepsi, kepercayaan, dan promosi. Penelitian ini termasuk dalam penelitian asosiatif dengan pendekatan kuantitatif. Populasi dalam penelitian ini yaitu seluruh mahasiswa S1 Fakultas Ekonomi Universitas Negeri Yogyakarta angkatan 2016-2019 yang pernah dan sedang menggunakan OVO. Teknik pengambilan sampel dengan menggunakan purposive sampling dengan jumlah sampel sebanyak 250 orang. Teknik analisis data menggunakan analisis regresi linier berganda. Hasil penelitian menunjukkan bahwa terdapat pengaruh positif dan signifikan gaya hidup, persepsi, kepercayaan dan promosi secara parsial dan simultan terhadap keputusan penggunaan OVO pada mahasiswa Fakultas Ekonomi Universitas Negeri Yogyakarta. Keputusan penggunaan OVO pada mahasiswa Fakultas Ekonomi Universitas Negeri Yogyakarta dipengaruhi oleh keempat variabel bebas tersebut sebesar 46,1% dan sisanya 53,9% dipengaruhi oleh variabel lain yang tidak diteliti dalam penelitian ini.Abstract: The study aimed to determine the factors that influence the decision to use OVO in students of the Faculty of Economics at Yogyakarta State University both partially and simultaneously. The factors examined in this study are lifestyle, perception, trust, and promotion. This study was included in an associative survey with a quantitative approach. Population in this study were all undergraduate students of the Faculty of Economics Yogyakarta State University class of 2016-2019 who have and are currently using OVO. The sampling technique using purposive sampling technique with a total sample of 250 respondent. Data analysis technique was linear regression analysis. The result of the study showed that there was a positive and significant effect of lifestyle, perception, trust, and promotion as a partial and simultaneous decision to use OVO. The decision to use OVO on students of the Faculty Economics Yogyakarta State University was affected by the four independent variables by 46,1%. In contrast, the remaining 53,9% is affected by other variables, not under study.
Identifikasi penyebab kenaikan berat badan pada anak usia dini
Authors: Sanusi Rahmat , Widiyanto Widiyanto , Rahail Ronny Brayntin
Published: August 2020

Upaya pencegahan masalah berat badan berlebih menjadi fokus utama saat ini berdasarkan peningkatan resiko kesehatan akibat overweight  dan obesitas, teruatama pada ana-anak. Penelitian ini bertujuan untuk mengindentifikasi penyebab kenaikan berat badan pada anak usia dini dengan metode penelitian cross sectional. Jumlah subjek penelitian sebanyak 66 anak. Teknik analisa yang digunakan adalah analisis multivariat. Hasil penelitian menujukkan terdapat hubungan bermakna (p < 0.05) antara variabel varian terhadap kenaikan berat pada anak usia dini. Dapat disimpulkan faktor rendahnya aktivitas fisik, genetik dari orang tua dan pola makan berhubungan terhadap kenaikan berat badan pada anak usia dini
Effects of Internet-Based Cognitive Behavioral Therapy in Routine Care for Adults in Treatment for Depression and Anxiety: Systematic Review and Meta-Analysis
Authors: Etzelmueller Anne , Vis Christiaan , Karyotaki Eirini , Baumeister Harald , Titov Nickolai , Berking Matthias , Cuijpers Pim , Riper Heleen , Ebert David Daniel
Published: August 2020

Background

Although there is evidence for the efficacy of internet-based cognitive behavioral therapy (iCBT), the generalizability of results to routine care is limited.

Objective

This study systematically reviews effectiveness studies of guided iCBT interventions for the treatment of depression or anxiety.

Methods

The acceptability (uptake, participants’ characteristics, adherence, and satisfaction), effectiveness, and negative effects (deterioration) of nonrandomized pre-post designs conducted under routine care conditions were synthesized using systematic review and meta-analytic approaches.

Results

A total of 19 studies including 30 groups were included in the analysis. Despite high heterogeneity, individual effect sizes of investigated studies indicate clinically relevant changes, with effect sizes ranging from Hedges’ g=0.42-1.88, with a pooled effect of 1.78 for depression and 0.94 for anxiety studies. Uptake, participants’ characteristics, adherence, and satisfaction indicate a moderate to high acceptability of the interventions. The average deterioration across studies was 2.9%.

Conclusions

This study provides evidence supporting the acceptability and effectiveness of guided iCBT for the treatment of depression and anxiety in routine care. Given the high heterogeneity between interventions and contexts, health care providers should select interventions that have been proven in randomized controlled clinical trials. The successful application of iCBT may be an effective way of increasing health care in multiple contexts.
Health Information Technology Use Among Persons With Self-reported Atherosclerotic Cardiovascular Disease: Analysis of the 2011-2018 National Health Interview Survey (Preprint)
Authors: Nwokeji Uchenna , Spaulding Erin M , Shan Rongzi , Turkson-Ocran Ruth-Alma , Baptiste Diana , Koirala Binu , Plante Timothy B , Martin Seth S , Commodore-Mensah Yvonne
Published: August 2020

BACKGROUND

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality in the United States. Health information technologies (HITs) have recently emerged as a viable intervention to mitigate the burden of ASCVD. Approximately 60% of US adults report searching the internet for health information; however, previous research has not examined the prevalence of general technology or HIT use among adults with and without ASCVD. In addition, social determinants in HIT use among adults with ASCVD are not well understood.

OBJECTIVE

The aim of this study was to evaluate the prevalence and social determinants of HIT use among US adults with versus without self-reported ASCVD.

METHODS

We pooled cross-sectional data from the 2011-2018 National Health Interview Survey (NHIS) to examine the general technology and HIT use among adults aged ≥18 years with and without self-reported ASCVD (coronary heart disease, stroke, or both). General technology use was defined as mobile phone ownership, internet use, and computer use. HIT use was defined as looking up health information on the internet, filling a web-based prescription, scheduling a medical appointment on the internet, communicating with a health care provider by email, or using web-based group chats to learn about health topics. We evaluated sociodemographic differences in HIT use among respondents by using Poisson regression. Analyses were weighted according to NHIS standards.

RESULTS

A total sample of 256,117 individuals were included, of which 2194 (0.9%) reported prior ASCVD. Among adults with prior ASCVD, the mean age was 70.6 (SD 11.5) years, and 47.4% (1048/2194) of the adults were females. General technology use differed between participants with and without prior ASCVD, with 36.0% (614/1826) and 76.2% (157,642/213,816) indicating internet usage and 24.6% (374/1575) and 60.7% (107,742/184,557) indicating using a computer every day, respectively. Similarly, adults with ASCVD were less likely to use HIT than those without ASCVD (515/2194, 25.1% vs 123,966/253,923, 51.0%; P<.001). Among adults with prior ASCVD, social determinants that were associated with HIT use included younger age, higher education, higher income, being employed, and being married.

CONCLUSIONS

HIT use was low among adults with a history of ASCVD, which may represent a barrier to delivering care via emerging HIT. Given the associations with social determinants such as income, education, and employment, targeted strategies and policies are needed to eliminate barriers to impact HIT usage.
Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis (Preprint)
Authors: Wu Jo-Hsuan , Liu T Y Alvin , Hsu Wan-Ting , Ho Jennifer Hui-Chun , Lee Chien-Chang
Published: August 2020

BACKGROUND

Diabetic retinopathy (DR), whose standard diagnosis is performed by human experts, has high prevalence and requires a more efficient screening method. Although machine learning (ML)–based automated DR diagnosis has gained attention due to recent approval of IDx-DR, performance of this tool has not been examined systematically, and the best ML technique for use in a real-world setting has not been discussed.

OBJECTIVE

The aim of this study was to systematically examine the overall diagnostic accuracy of ML in diagnosing DR of different categories based on color fundus photographs and to determine the state-of-the-art ML approach.

METHODS

Published studies in PubMed and EMBASE were searched from inception to June 2020. Studies were screened for relevant outcomes, publication types, and data sufficiency, and a total of 60 out of 2128 (2.82%) studies were retrieved after study selection. Extraction of data was performed by 2 authors according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), and the quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Meta-analysis of diagnostic accuracy was pooled using a bivariate random effects model. The main outcomes included diagnostic accuracy, sensitivity, and specificity of ML in diagnosing DR based on color fundus photographs, as well as the performances of different major types of ML algorithms.

RESULTS

The primary meta-analysis included 60 color fundus photograph studies (445,175 interpretations). Overall, ML demonstrated high accuracy in diagnosing DR of various categories, with a pooled area under the receiver operating characteristic (AUROC) ranging from 0.97 (95% CI 0.96-0.99) to 0.99 (95% CI 0.98-1.00). The performance of ML in detecting more-than-mild DR was robust (sensitivity 0.95; AUROC 0.97), and by subgroup analyses, we observed that robust performance of ML was not limited to benchmark data sets (sensitivity 0.92; AUROC 0.96) but could be generalized to images collected in clinical practice (sensitivity 0.97; AUROC 0.97). Neural network was the most widely used method, and the subgroup analysis revealed a pooled AUROC of 0.98 (95% CI 0.96-0.99) for studies that used neural networks to diagnose more-than-mild DR.

CONCLUSIONS

This meta-analysis demonstrated high diagnostic accuracy of ML algorithms in detecting DR on color fundus photographs, suggesting that state-of-the-art, ML-based DR screening algorithms are likely ready for clinical applications. However, a significant portion of the earlier published studies had methodology flaws, such as the lack of external validation and presence of spectrum bias. The results of these studies should be interpreted with caution.
Designing User-Centered Mobile Health Initiatives to Promote Healthy Behaviors for Children With Disabilities: Development and Usability Study (Preprint)
Authors: Shikako Keiko , Mogo Ebele R I , Grand-Maison Valerie , Simpson Robert , Pritchard-Wiart Lesley , Majnemer Annette ,   Jooay App Research Group
Published: August 2020

BACKGROUND

The gap between research and its practical application in community settings limits its impact on public health. Closing this gap has the potential to improve the well-being of underserved groups, such as children with disabilities. Mobile health has the potential to improve access to community resources and support for underserved populations, thereby encouraging improved health behaviors.

OBJECTIVE

In this feasibility pilot study, we describe the development of the mobile app Jooay. Jooay was developed in partnership with stakeholders to facilitate access to leisure and physical activity community programs for children and youth with disabilities. We also reflect on the lessons learned throughout the implementation process that are relevant for improving the health behaviors of children with disabilities.

METHODS

We used a participatory action research approach to develop the app. We also administered a survey to current Jooay users and analyzed various app usage indicators to explore use patterns, user feedback, and preferences. Finally, we critically appraised the implementation process through a best practices for implementation research framework.

RESULTS

We developed a product that responds to users’ identified need to find information and follows accessibility and user-centered design standards. The analysis of usage data revealed that access to the Jooay app is concentrated in urban areas. Perceptions, attitudes, and information needs varied according to the type of user. The use of the mobile app changed over time, and usage decreased after the app was downloaded, indicating a need for the sustained engagement of app users. Users found value in the ability to identify activities that they would not otherwise know about. However, app use alone was not sufficient to improve participation. Although the app was developed based on users’ active input in multiple iterations, we encountered challenges with survey recruitment and attrition, suggesting the need for more seamless and engaging means for collecting data within this population.

CONCLUSIONS

Interactions between users and the app can sustain user engagement and behavior change. We will improve the app’s next iterations by using the information gained from this study to conduct a larger study to assess the relationship among social and material deprivation, urban design, and access to inclusive and adaptive leisure programs. This study will inform the improvement of app listings to improve the use of Jooay by different user groups and promote health through mobile apps for marginalized groups.
Seroprevalence of anti-SARS-CoV-2 IgG antibodies in hospitalized patients at a tertiary referral center in North India (Preprint)
Authors: Ray Dr. Animesh , Singh Dr. Komal , Chattopadhyay Souvick , Mehdi Farha , Batra Dr. Gaurav , Kumari Dr. Aakansha , Agarwal Dr. Ayush , M Dr. Bhavesh , Sahni Dr. Shubham , R Dr. Chaithra , Agarwal Dr. Shubham , Nagpal Dr. Chitrakshi , B H Dr. Gagantej , Arora Dr. Umang , Sharma Dr. Kartikrya Kumar , Jadon Dr. Ranveer Singh , Upadhyay Ashish Datt , Nischal Dr. Neeraj , Vikram Dr. Naval K , Soneja Dr. Manish , Pandey Dr. R M , Wig Dr. Naveet
Published: August 2020

BACKGROUND

Seroprevalence of IgG antibodies against SARS-CoV-2 is an important tool to estimate the true extent of infection in a population. However, seroprevalence studies have been scarce in South East Asia including India, which, as of now, carries the third largest burden of confirmed cases in the world. The present study aimed to estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody among hospitalized patients at one of the largest government hospital in India

OBJECTIVE

The primary objective of this study is to estimate the seroprevalence of SARS-CoV-2 antibody among patients admitted to the Medicine ward and ICU

METHODS

This cross-sectional study, conducted at a tertiary care hospital in North India, recruited consecutive patients who were negative for SARS-CoV-2 by RT-PCR or CB-NAAT. Anti-SARS-CoV-2 IgG antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the ELISA method

RESULTS

A total of 212 hospitalized patients were recruited in the study with mean age (±SD) of 41.2 (±15.4) years and 55% male population. Positive serology against SARS CoV-2 was detected in 19.8%patients(95% CI 14.7-25.8). Residency in Delhi conferred a higher frequency of seropositivity 26.5% (95% CI 19.3-34.7) as compared to that of other states 8% (95% CI 3.0-16.4) with p-value 0.001. No particular age groups or socio-economic strata showed a higher proportion of seropositivity

CONCLUSIONS

Around, one-fifth of hospitalized patients, who were not diagnosed with COVID-19 before, demonstrated seropositivity against SARS-CoV-2. While there was no significant difference in the different age groups and socio-economic classes; residence in Delhi was associated with increased risk (relative risk of 3.62, 95% CI 1.59-8.21)
Automated Smart Home Assessment to Support Pain Management: Multiple Methods Analysis (Preprint)
Authors: Fritz Roschelle L , Wilson Marian , Dermody Gordana , Schmitter-Edgecombe Maureen , Cook Diane J
Published: August 2020

BACKGROUND

Poorly managed pain can lead to substance use disorders, depression, suicide, worsening health, and increased use of health services. Most pain assessments occur in clinical settings away from patients’ natural environments. Advances in smart home technology may allow observation of pain in the home setting. Smart homes recognizing human behaviors may be useful for quantifying functional pain interference, thereby creating new ways of assessing pain and supporting people living with pain.

OBJECTIVE

This study aimed to determine if a smart home can detect pain-related behaviors to perform automated assessment and support intervention for persons with chronic pain.

METHODS

A multiple methods, secondary data analysis was conducted using historic ambient sensor data and weekly nursing assessment data from 11 independent older adults reporting pain across 1-2 years of smart home monitoring. A qualitative approach was used to interpret sensor-based data of 27 unique pain events to support clinician-guided training of a machine learning model. A periodogram was used to calculate circadian rhythm strength, and a random forest containing 100 trees was employed to train a machine learning model to recognize pain-related behaviors. The model extracted 550 behavioral markers for each sensor-based data segment. These were treated as both a binary classification problem (event, control) and a regression problem.

RESULTS

We found 13 clinically relevant behaviors, revealing 6 pain-related behavioral qualitative themes. Quantitative results were classified using a clinician-guided random forest technique that yielded a classification accuracy of 0.70, sensitivity of 0.72, specificity of 0.69, area under the receiver operating characteristic curve of 0.756, and area under the precision-recall curve of 0.777 in comparison to using standard anomaly detection techniques without clinician guidance (0.16 accuracy achieved; P<.001). The regression formulation achieved moderate correlation, with r=0.42.

CONCLUSIONS

Findings of this secondary data analysis reveal that a pain-assessing smart home may recognize pain-related behaviors. Utilizing clinicians’ real-world knowledge when developing pain-assessing machine learning models improves the model’s performance. A larger study focusing on pain-related behaviors is warranted to improve and test model performance.
A Multimodality Machine Learning Approach to Differentiate Severe and Nonsevere COVID-19: Model Development and Validation (Preprint)
Authors: Chen Yuanfang , Ouyang Liu , Bao Forrest S , Li Qian , Han Lei , Zhang Hengdong , Zhu Baoli , Ge Yaorong , Robinson Patrick , Xu Ming , Liu Jie , Chen Shi
Published: August 2020

BACKGROUND

Effectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve optimal outcomes for the patients as well as to reduce the risk of overloading the health care system. Currently, severe and nonsevere COVID-19 types are differentiated by only a few features, which do not comprehensively characterize the complicated pathological, physiological, and immunological responses to SARS-CoV-2 infection in the different disease types. In addition, these type-defining features may not be readily testable at the time of diagnosis.

OBJECTIVE

In this study, we aimed to use a machine learning approach to understand COVID-19 more comprehensively, accurately differentiate severe and nonsevere COVID-19 clinical types based on multiple medical features, and provide reliable predictions of the clinical type of the disease.

METHODS

For this study, we recruited 214 confirmed patients with nonsevere COVID-19 and 148 patients with severe COVID-19. The clinical characteristics (26 features) and laboratory test results (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest models based on all the features in each modality as well as on the top 5 features in each modality combined were developed and validated to differentiate COVID-19 clinical types.

RESULTS

Using clinical and laboratory results independently as input, the random forest models achieved >90% and >95% predictive accuracy, respectively. The importance scores of the input features were further evaluated, and the top 5 features from each modality were identified (age, hypertension, cardiovascular disease, gender, and diabetes for the clinical features modality, and dimerized plasmin fragment D, high sensitivity troponin I, absolute neutrophil count, interleukin 6, and lactate dehydrogenase for the laboratory testing modality, in descending order). Using these top 10 multimodal features as the only input instead of all 52 features combined, the random forest model was able to achieve 97% predictive accuracy.

CONCLUSIONS

Our findings shed light on how the human body reacts to SARS-CoV-2 infection as a unit and provide insights on effectively evaluating the disease severity of patients with COVID-19 based on more common medical features when gold standard features are not available. We suggest that clinical information can be used as an initial screening tool for self-evaluation and triage, while laboratory test results should be applied when accuracy is the priority.
The Swiss Prison Study (SWIPS): Protocol for Establishing a Public Health Registry of Prisoners in Switzerland (Preprint)
Authors: Gaisl Thomas , Musli Naser , Baumgartner Patrick , Meier Marc , Rampini Silvana K , Blozik Eva , Battegay Edouard , Kohler Malcolm , Saxena Shekhar
Published: August 2020

BACKGROUND

The health aspects, disease frequencies, and specific health interests of prisoners and refugees are poorly understood. Importantly, access to the health care system is limited for this vulnerable population. There has been no systematic investigation to understand the health issues of inmates in Switzerland. Furthermore, little is known on how recent migration flows in Europe may have affected the health conditions of inmates.

OBJECTIVE

The Swiss Prison Study (SWIPS) is a large-scale observational study with the aim of establishing a public health registry in northern-central Switzerland. The primary objective is to establish a central database to assess disease prevalence (ie, International Classification of Diseases-10 codes [German modification]) among prisoners. The secondary objectives include the following: (1) to compare the 2015 versus 2020 disease prevalence among inmates against a representative sample from the local resident population, (2) to assess longitudinal changes in disease prevalence from 2015 to 2020 by using cross-sectional medical records from all inmates at the Police Prison Zurich, Switzerland, and (3) to identify unrecognized health problems to prepare successful public health strategies.

METHODS

Demographic and health-related data such as age, sex, country of origin, duration of imprisonment, medication (including the drug name, brand, dosage, and release), and medical history (including the International Classification of Diseases-10 codes [German modification] for all diagnoses and external results that are part of the medical history in the prison) have been deposited in a central register over a span of 5 years (January 2015 to August 2020). The final cohort is expected to comprise approximately 50,000 to 60,000 prisoners from the Police Prison Zurich, Switzerland.

RESULTS

This study was approved on August 5, 2019 by the ethical committee of the Canton of Zurich with the registration code KEK-ZH No. 2019-01055 and funded in August 2020 by the “Walter and Gertrud Siegenthaler” foundation and the “Theodor and Ida Herzog-Egli” foundation. This study is registered with the International Standard Randomized Controlled Trial Number registry. Data collection started in August 2019 and results are expected to be published in 2021. Findings will be disseminated through scientific papers as well as presentations and public events.

CONCLUSIONS

This study will construct a valuable database of information regarding the health of inmates and refugees in Swiss prisons and will act as groundwork for future interventions in this vulnerable population.

CLINICALTRIAL

ISRCTN registry ISRCTN11714665; http://www.isrctn.com/ISRCTN11714665

INTERNATIONAL REGISTERED REPORT

DERR1-10.2196/23973
A Rapid Assessment of the Impact of COVID-19 on Asian Americans: Cross-sectional Survey Study (Preprint)
Authors: Quach Thu , Doan Lan N , Liou Julia , Ponce Ninez A
Published: August 2020

BACKGROUND

The diverse Asian American population has been impacted by the COVID-19 pandemic, but due to limited data and other factors, disparities experienced by this population are hidden.

OBJECTIVE

This study aims to describe the Asian American community’s experiences during the COVID-19 pandemic, focusing on the Greater San Francisco Bay Area, California, and to better inform a Federally Qualified Health Center’s (FQHC) health care services and response to challenges faced by the community.

METHODS

We conducted a cross-sectional survey between May 20 and June 23, 2020, using a multipronged recruitment approach, including word-of-mouth, FQHC patient appointments, and social media posts. The survey was self-administered online or administered over the phone by FQHC staff in English, Cantonese, Mandarin, and Vietnamese. Survey question topics included COVID-19 testing and preventative behaviors, economic impacts of COVID-19, experience with perceived mistreatment due to their race/ethnicity, and mental health challenges.

RESULTS

Among 1297 Asian American respondents, only 3.1% (39/1273) had previously been tested for COVID-19, and 46.6% (392/841) stated that they could not find a place to get tested. In addition, about two-thirds of respondents (477/707) reported feeling stressed, and 22.6% (160/707) reported feeling depressed. Furthermore, 5.6% (72/1275) of respondents reported being treated unfairly because of their race/ethnicity. Among respondents who experienced economic impacts from COVID-19, 32.2% (246/763) had lost their regular jobs and 22.5% (172/763) had reduced hours or reduced income. Additionally, 70.1% (890/1269) of respondents shared that they avoid leaving their home to go to public places (eg, grocery stores, church, and school).

CONCLUSIONS

We found that Asian Americans had lower levels of COVID-19 testing and limited access to testing, a high prevalence of mental health issues and economic impacts, and a high prevalence of risk-avoidant behaviors (eg, not leaving the house) in the early months of the COVID-19 pandemic. These findings provide preliminary insights into the impact of the COVID-19 pandemic on Asian American communities served by an FQHC and underscore the longstanding need for culturally and linguistically appropriate approaches to providing mental health, outreach, and education services. These findings led to the establishment of the first Asian multilingual and multicultural COVID-19 testing sites in the local area where the study was conducted, and laid the groundwork for subsequent COVID-19 programs, specifically contact tracing and vaccination programs.
Using a Web-Based Platform as an Alternative for Conducting International, Multidisciplinary Medical Conferences During the Novel COVID-19 Pandemic: Analysis of a Conference (Preprint)
Authors: Ko Po-Jen , Yu Sheng-Yueh , Chang John Chien-Hwa , Hsieh Ming-Ju , Chu Sung-Yu , Tan Jimmy Wei-Hwa , Cheng Wan-Ling , Ho Pei
Published: August 2020

BACKGROUND

The COVID-19 pandemic has stunted medical education activities, resulting in most conferences being cancelled or postponed. To continue professional education during this crisis, web-based conferences can be conducted via livestream and an audience interaction platform as an alternative.

OBJECTIVE

The unprecedented COVID-19 pandemic has affected human connections worldwide. Conventional conferences have been replaced by web-based conferences. However, web-based conferencing has its challenges and limitations. This paper reports the logistics and preparations required for converting an international, on-site, multidisciplinary conference into a completely web-based conference within 3 weeks during the pandemic.

METHODS

The program was revised, and a teleconference system, live recording system, director system setup, and broadcasting platform were arranged to conduct the web-based conference.

RESULTS

We used YouTube (Alphabet Inc) and WeChat (Tencent Holdings Limited) for the web-based conference. Of the 24 hours of the conventional conference, 21.5 hours (90%) were retained in the web-based conference via live broadcasting. The conference was attended by 71% (37/52) of the original international faculties and 71% (27/38) of the overall faculties. In total, 61 out of 66 presentations (92%) were delivered. A special session—“Dialysis access management under the impact of viral epidemics”—was added to replace precongress workshops and competitions. The conference received 1810, 1452, and 1008 visits on YouTube and 6777, 4623, and 3100 visits on WeChat on conference days 1, 2, and 3, respectively.

CONCLUSIONS

Switching from a conventional on-site conference to a completely web-based format within a short period is a feasible method for maintaining professional education in a socially responsible manner during a pandemic.
Assessing the Imagination Scale’s Nomological Validity: Effect of Hedonic versus Utilitarian Product Types and Abstract versus Concrete Advertising Execution
Authors: Dewi Ike Janita , Ang Swee Hoon
Published: August 2020

This research builds on a study of advertisement-evoked imagination scale developed by Dewi and Ang (2015). The imagination scale contains four types of imagination, that is, benefit-anticipatory imagination, emotional-bonding imagina­tion, symbolic imagination, and mind-wandering imagination.In this paper, the pro­po­sed constructs of the imagination types are related to other relevant constructs exis­ting in marketing literature.The purpose of this research is twofold. First, it establishes the nomological validity of the imagination measures by placing it in the context of hedonic-utilitarian concepts proposed by Holbrook and Hirschman (1983). Second, the research empirically studies the effect of situational factor, that is concrete versus abstract advertisement execution, on imagination elicitation. The study is an experiment which employs mixed factor design involving eight sub-groups of participants. Results of the research demons­trate the nomological validity of the imagination scale where the four types of imagination were elicited in response to hedonic/utilitarian product depicted in the ad and situational factors (that is, abstract versus concrete ads).
Reflection on the Production of Knowledge: From Postmodernism to Pseudoscience
Authors: Tanudirjo Daud Aris
Published: August 2020

In the last few years, the Indonesian government has impelled academics and higher education institutions as the centre of knowledge production to publish their works in reputed international journal. This policy is necessary to elevate the position of Indonesian higher education institution in the World University Rankings. In fact, such a policy will not only have impact on the status of the higher education institution but also in the course of human culture and society. This article tries to reflect on the impact of the implementation of the policy in the wider cultural context. Predictably, new knowledge will only be circulated among the elite academics and the higher education institutions will become inaccessible ivory tower for the society. On the other hand, the society will tend to consume more pseudoscientific knowledge which is more attractive and easier to understand. Ultimately this will have a significant impact on the course and quality of human culture.