bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis, Anticancer Activities, and Mechanism of N-heptyl-containing
Biguanide Derivatives
Authors: Wang Wei , Xiao Di , Zhou Sichun , Xu Simeng , Tang Xinyi , Zhou Xinchong , Liu Jinbing , Xu Cangcang , Peng Mei , Yang Xiaoping
Published: February 2022

Background:

In recent years, the anticancer effects of biguanide drugs have received considerable
attention. However, the effective concentration of biguanide drugs to kill cancer cells is
relatively high. Thus, we focus on structural modification of biguanides to obtain better antitumor
candidates. A previous study in our laboratory has found that a biguanide compound containing the
n-heptyl group has potent anticancer activity. However, the effect of different substituents on the
benzene ringside of the biguanides on the anti-proliferative activity is unknown.

Objective:

A series of n-heptyl-containing biguanide derivatives whose benzene rings were modified
by halogen substitution based on the intermediate derivatization method were further synthesized to
find new compounds with improved antiproliferative activities.

Method:

Ten n-heptyl-containing biguanide derivatives were synthesized via established chemical
procedures. The activities of these derivatives were explored by MTT assay, clonogenic assay, and
scratch assay. The protein levels were detected via Western blotting to explore the underlying mechanisms.

Results:

The optimal biguanide derivatives 10a-10c, 11d exhibited IC50 values of 2.21-9.59 μΜ for
five human cancer cell lines, significantly better than the control drug proguanil. The results of clonogenic
and scratch wound healing assays also confirmed the inhibitory effects of derivatives 10a-
10c, 11d on the proliferation and migration of human cancer cell lines. Western blot results demonstrated
that one representative derivative, 10c upregulates the AMPK signal pathway and downregulates
mTOR/4EBP1/p70S6K.

Conclusion:

All biguanide derivatives containing n-heptyl groups are more active than proguanil,
indicating that the modification of n-heptyl-containing biguanide derivatives provides a novel approach
for the development of novel high efficient antitumor drugs.
Autistic Traits in Schizophrenia Spectrum Disorders
Authors: Šustová Petra , Rodriguez Mabel
Published: February 2022

Background:

In recent years, there has been an emerging interest in the overlap
between schizophrenia and autism. The co-occurrence between these two disorders may be
seen not only at a diagnostic level but also as the presence of autistic traits in schizophrenia.
There has been a rapid rise in the number of studies focusing on autistic traits in schizophrenia
and their clinical associations.

Objective:

Here, we provide a review that summarizes the current findings and highlights
gaps that may be addressed by future research.

Results:

Higher levels of autistic traits have been associated with earlier age of onset, longer
duration of illness, resistance to treatment, and more severe cognitive deficit. However, regarding
social cognition and psychosocial functioning, the findings are mixed.

Conclusion:

Patients with prominent autistic traits seem to be more affected. The effect of
autistic traits on social cognition and psychosocial functioning remains unclear, as does their
relationship with negative symptoms. Therefore, longitudinal studies are highly needed.
Effectiveness of learning using application zoom theon student learning outcomes during COVID-19 at STKIP Muhammadiyah Sungai Penuh
Authors: Arlianti Nofyta , Hastin Mira , Ramatni Ali , Wahyuni Loria , Susmita Nelvia
Published: February 2022

Online learning and working from home for educators are changes that must be made by lecturers to continue teaching students. Education with distance has the aim of improving the quality of education and relevance education as well as increasing equitable access and expansion of education. Distance education which is held with good quality assurance and in accordance with the stakeholder needs is one of the mechanisms for expanding access higher education. The purpose of this study was to determine the effect of learning Statistics the basics of using the application Zoom on student learning outcomes during the period COVID-19 in Indonesia STKIP Muhammadiyah Sungai Penuh. The method and type of this research is Ex-Post Factor post-event and descriptive correlational measurements. Based on the results of the analysis and discussion of the data that has been stated previously, it can be concluded: there is no effect of learning Basic Statistics using the application zoom on student learning outcomes during the period COVID-19 at STKIP Muhammadiyah Sungai Penuh. This matter it can be seen from rcount >rtable that is 0.472 > 0.444. Because the price of rcount>rtable then H1 accept, the coefficient of determination = 0.2314.
KELAYAKAN ISI DAN BAHASA PADA BUKU TEKS BAHASA INDONESIA DI SMA NEGERI 1 SIRAMPOG
Authors:   Pendidikan Bahasa Indonesia, FKIP, Universitas Peradaban, Rihanah Atria , Irma Cintya Nurika ,   Pendidikan Bahasa Indonesia, FKIP, Universitas Peradaban
Published: February 2022

This study aims to determine the appropriateness of the content and language of the Indonesian language textbook for class XI SMA Negeri 1 Sirampog. The feasibility of the book is seen from the content and language components in accordance with the National Education Standards Agency (BNSP). This study used a qualitative method with a case study approach model, while the data collection in this study was carried out using a purposive technique. Furthermore, data validity was carried out by triangulating data sources and theories. The results showed that the feasibility of the content aspect obtained a percentage of 90, 86% and the feasibility of the language aspect obtained a percentage of 93% so it is classified as a very feasible book.
DAMPAK DISTRIBUTED ENERGY RESOURCES TERHADAP PROFIL TEGANGAN DAN RUGI DAYA PENYULANG BANTUL 05
Authors: Falah Muhammad Yusuf , Arrasyid Adib Muhammad , Ulfa Afrida Nurul , Ahmad Rizal Zulfiqri , Putra Jimmy Trio
Published: February 2022

ABSTRACT:To realize Indonesia's commitment to cut greenhouse effect, it is important to use environmentally friendly vehicles. On August 12, 2019, the Presidential Regulation on the velocity of Battery-Based Electric Motor Vehicle Program for land vehicle as a sign of the seriousness of the government applying this vehicle. This research is specific in terms of the provision of Public Electric Vehicle Charging Station (SPKLU) in Bantul refinery area, Yogyakarta after the installation of Photovoltaic (PV) plant as Distributed Energy Resources (DER). This study used a simulation of the Open Distribution System Simulator (OpenDSS) software distribution network in analyzing the comparison of voltage profiles and power losses before and after spklu installation. By optimizing the placement of SPKLU using Flower Pollination Algorithm (FPA) method using Matlab software that results in spklu placement on bus 58 by 300 kW, bus 37 by 301 kW, and bus 36 by 300 kW. The voltage profile changed from 0.9695 p.u to 0.9688 p.u and power losses from 53.3 kW to 56.1 kW.ABSTRAK:Untuk mewujudkan tanggungjawab Indonesia dalam mengurangi efek rumah kaca maka harus menggunakan angkutan ramah lingkungan. Pada tanggal 12 Agustus 2019 telah disahkan Perpres Percepatan Program Kendaraan Bermotor Listrik Berbasis Baterai sebagai transportasi jalan merupakan tanda seriusnya pemerintah mengaplikasikan kendaraan ini. Penelitian ini spesifik pada hal penyediaan Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) pada area penyulang Bantul, Yogyakarta setelah pemasangan pembangkit Photovoltaic (PV) sebagai Distributed Energy Resources (DER). Penelitian ini menggunakan simulasi jaringan distribusi software Open Distribution System Simulator (OpenDSS) untuk mempelajari perbandingan profil tegangan dan rugi daya sebelum dan sesudah pengaplikasian SPKLU. Dengan optimasi penempatan SPKLU menggunakan metode Flower Pollination Algorithm (FPA) menggunakan software Matlab yang menghasilkan penempatan SPKLU pada bus 58 sebesar 300 kW, bus 37 sebesar 301 kW, dan bus 36 sebesar 300 kW. Profil tegangan berubah dari 0,9695 p.u menjadi 0,9688 p.u dan rugi-rugi daya dari 53,3 kW menjadi 56,1 kW.
PEMANFAATAN TEKNOLOGI AUGMENTED REALITY UNTUK PENGEMBANGAN BAHAN AJAR MATERI KOMPUTER JARINGAN
Authors: Nuraini Listia , Ratnawati Dwi
Published: February 2022

ABSTRACT:This study aims to develop Augmented Reality based learning media on computer network subject. The research method used in developing educational games is the research and development (R&D) method adapted from Borg & Gall. The steps of study namely needs analysis, identification of product specifications, product development, product validation, product revision and product testing. The subject of this study was students of class X at Vocational High School. The object of this study was Augmented Reality based learning media on computer network. The test results indicated that this media is feasible to use.  The score of product validation gained 73.07% from media experts while it gained 87.5% from material experts under very decent category. Moreover, it gained 85,26% from product users under very feasible category. In addition, the effectiveness test indicated that the result was quite effective with a percentage of 64.41%. Therefore, it could be implied that this learning media was feasible and effective to use in learning process.ABSTRAK:Tujuan penelitian ini adalah pengembangan media pembelajaran berbasis Augmented Reality pada mata pelajaran jaringan komputer. Metode penelitian yang digunakan dalam mengembangkan game edukasi yaitu metode research and development (R&D) yang diadaptasi dari Borg & Gall dengan beberapa tahapan. Adapun langkahnya adalah analisis kebutuhan, identifikasi spesifikasi produk, pengembangan produk, validasi produk, revisi produk dan uji coba produk. Subjek penelitian ini adalah siswa kelas X SMK. Objek penelitian adalah media pembelajaran jaringan komputer berbasis Augmented Reality. Hasil ujicoba menyatakan bahwa media ini layak digunakan dengan prosentasi dari ahli media sebesar 73,07%, ahli materi mendapat 87,5% dengan kategori sangat layak, sedangkan pengguna mendapatkan 85,26% dengan kategori sangat layak. Sedangkan uji efektivitas menyatakan cukup efektif dengan prosentase 64,41%, sehingga disimpulkan bahwa media pembelajaran ini layak dan efektif digunakan dalam pembelajaran.
TECNOLOGIA E DESIGN DE COMPLEXMEDIA DEDICADA À EDUCAÇÃO DIGITAL: UM RELATO DE CASO
Authors: Carvalho Neto Cassiano Zeferino de , Catapan Araci Hack
Published: February 2022

A educação concebida e realizada com suporte digital apresenta na atualidade um complexo conjunto de redes sociotecnoló-gicas, com interface hipermidiática múltipla e multifacetada, com possibilidades de interação por comunicação presencial e remota. A este paradigma se pode chamar de “Educação Digital”. Considera-se, como ponto de partida conceitual deste artigo, um processo de modelagem teórica em mídia do conhecimento no formato de hipermídia complexa (Complexmedia), a qual comporta objetos educacionais nas modalidades de Simuladores-Animadores (SF), Experimentos Educacionais (EE), Áudio (RD) e Audiovisual (TV). O referencial teórico é suportado pela Teoria Socio-histórica a partir de um diálogo estabelecido entre os três principais autores que emprestarão sustentação às investigações: Vygotsky (1984, 1993), Leontiev (1978) e Thompson (1998). Aspectos complementares de fundamentação estruturam-se em Morin e Le Moigne (2000), na revisão do conceito de tecnologia educacional e construção do conceito de Ciberarquitetura (CARVALHO NETO, 2006), que amparam a modelagem teórica em mídia do conhecimento, na modalidade de hipermídia complexa (Complexmedia). O modelo de autoria tecnológica e design em mídia do conhecimento foi oportunizado e deflagrado por ocasião da chamada pública para o Projeto CONDIGITAL, lançado por via editalícia pelo Ministério da Ciência e Tecnologia (MCT) e Ministério da Educação (MEC), com financiamento do Fundo Nacional de Desenvolvimento da Educação (FNDE) e executado no período 2007 a 2010 pelo Instituto Galileo Galilei para a Educação (IGGE), a partir de aprovação federal com o título original da obra Física Vivencial: uma Aventura do Conhecimento.
Web-Based Cognitive Testing in Psychiatric Research: Validation and Usability Study
Authors: Lynham Amy Joanne , Jones Ian R , Walters James T R
Published: February 2022

Background

Cognitive impairments are features of many psychiatric disorders and affect functioning. A barrier to cognitive research on psychiatric disorders is the lack of large cross-disorder data sets. However, the collection of cognitive data can be logistically challenging and expensive. Web-based collection may be an alternative; however, little is known about who does and does not complete web-based cognitive assessments for psychiatric research.

Objective

The aims of this study are to develop a web-based cognitive battery for use in psychiatric research, validate the battery against the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery, and compare the characteristics of the participants who chose to take part with those of the individuals who did not participate.

Methods

Tasks were developed by The Many Brains Project and selected to measure the domains specified by the MATRICS initiative. We undertook a cross-validation study of 65 participants with schizophrenia, bipolar disorder, depression, or no history of psychiatric disorders to compare the web-based tasks with the MATRICS Consensus Cognitive Battery. Following validation, we invited participants from 2 large ongoing genetic studies, which recruited participants with psychiatric disorders to complete the battery and evaluated the demographic and clinical characteristics of those who took part.

Results

Correlations between web-based and MATRICS tasks ranged between 0.26 and 0.73. Of the 961 participants, 887 (92.3%) completed at least one web-based task, and 644 (67%) completed all tasks, indicating adequate completion rates. Predictors of web-based participation included being female (odds ratio [OR] 1.3, 95% CI 1.07-1.58), ethnicity other than White European (OR 0.66, 95% CI 0.46-0.96), higher levels of education (OR 1.19, 95% CI 1.11-1.29), diagnosis of an eating disorder (OR 2.17, 95% CI 1.17-4) or depression and anxiety (OR 5.12, 95% CI 3.38-7.83), and absence of a diagnosis of schizophrenia (OR 0.59, 95% CI 0.35-0.94). Lower performance on the battery was associated with poorer functioning (B=−1.76, SE 0.26; P<.001).

Conclusions

Our findings offer valuable insights into the advantages and disadvantages of testing cognitive function remotely for mental health research.
Impact of COVID-19 on the Noncommunicable Disease Programs Provided in the Primary Health Care Centers in Al-Rusafa Directorate of Health, 2020
Authors: Hlaiwah Mohammed , Lami Faris
Published: February 2022

Background

In recent years, noncommunicable diseases (NCDs) have globally shown an increasing impact on health status with disproportionately higher rates in developing countries. During the outbreak, health workers, equipment, and facilities have been reallocated to address the influx of patients with COVID-19. Restructuring of the health system could result in the closure of some health facilities.

Objective

The aim of this paper was to determine the impact of COVID-19 on the performance of NCD programs implemented in the primary health care centers in Al-Rusafa DOH through comparing the performance indicators of 2019 and 2020, and to identify the potential causes of the changes.

Methods

The study was conducted in Baghdad, Al-Rusafa, during the period from April to June 2021. A systematic sample was used to enroll 20 primary health care centers. The descriptive analysis focused on frequencies and percentages. Continuous variables are presented as mean (SD), and the independent t test was used to assess statistical significance. A P value of less than .05 is considered statistically significant.

Results

There was a decrease in the number of served patients, even reaching zero in some units. Most staff were partially or completely assigned to the COVID-19 pandemic. There was a decline in yearly need of education material and folders for programs in 2020 and awareness campaigns performed in 2019 and 2020. The main reasons in the decline of these services were the closure of outpatient services as per government directive, the closure of outpatient disease-specific consultation clinics, and the decrease in outpatient volume due to patients not presenting.

Conclusions

The COVID-19 pandemic affected the NCD services in Iraq, including the disruption of many aspects of these services.
e-Learning in Medical Education in Sri Lanka: Survey of Medical Undergraduates and New Graduates (Preprint)
Authors: Samarasekara Keshinie
Published: February 2022

BACKGROUND

Medical education has undergone drastic changes with the advent of novel technologies that enable e-learning. Medical students are increasingly using e-learning methods, and universities have incorporated them into their curricula.

OBJECTIVE

This study aimed at delineating the pattern of use of e-learning methods among medical undergraduates and new graduates of the Faculty of Medicine, University of Colombo, and identifying the challenges faced by these students in using e-learning methods.

METHODS

A cross-sectional descriptive study was conducted in the Faculty of Medicine, University of Colombo, in April 2020, with the participation of current undergraduates and pre-intern medical graduates, using a self-administered questionnaire that collected data on sociodemographic details, pattern of use of learning methods, and challenges faced using e-learning methods.

RESULTS

There were 778 respondents, with a response rate of 65.1% (778/1195). All the study participants used e-learning resources with varying frequencies, and all of them had at least 1 smart device with access to the internet. Electronic versions of standard textbooks (e-books), nonmedical websites, online lectures, medical websites, and medical phone apps were used by the majority. When comparing the extent of use of different learning methods, it appeared that students preferentially used traditional learning methods. The preference was influenced by the year of study and family income. The 3 most commonly used modalities for learning new study material and revising previously learned content were notes on paper material, textbooks (paper version), and e-books. The majority (98.7% [n=768]) of participants have encountered problems using e-learning resources. The most commonly faced problems were unavailability of free-of-charge access to some e-learning methods, expenses related to internet connection, poor connectivity of mobile internet, distractions while using online resources, and lack of storage space on electronic devices.

CONCLUSIONS

There is a high uptake of e-learning methods among Sri Lankan medical students. However, when comparing the extent of use of different learning methods, it appeared that students preferentially used traditional learning methods. A majority of the students have encountered problems when using e-learning methods, and most of these problems were related to poor economic status. Universities should take these factors into consideration when developing curricula in medical education.
The Effectiveness of Virtual Reality Exposure–Based Cognitive Behavioral Therapy for Severe Anxiety Disorders, Obsessive-Compulsive Disorder, and Posttraumatic Stress Disorder: Meta-analysis (Preprint)
Authors: van Loenen Inge , Scholten Willemijn , Muntingh Anna , Smit Johannes , Batelaan Neeltje
Published: February 2022

BACKGROUND

In recent years, virtual reality exposure–based cognitive behavioral therapy (VRE-CBT) has shown good treatment results in (subclinical) anxiety disorders and seems to be a good alternative to exposure in vivo in regular cognitive behavioral therapy (CBT). However, previous meta-analyses on the efficacy of VRE-CBT on anxiety disorders have included studies on specific phobias and subthreshold anxiety; therefore, these results may not be generalizable to patients with more severe and disabling anxiety disorders.

OBJECTIVE

The objective of our study is to determine the efficacy of VRE-CBT on more severe anxiety disorders, excluding specific phobias and subthreshold anxiety disorders. Meta-analyses will be conducted to examine the efficacy of VRE-CBT versus waitlist and regular CBT. Our secondary objectives are to examine whether the efficacy differs according to the type of anxiety disorder, type of recruitment, and type of VRE-CBT (virtual reality exposure either with or without regular CBT). Furthermore, attrition in VRE-CBT and CBT will be compared.

METHODS

Studies published until August 20, 2020, were retrieved through systematic literature searches in PubMed, PsycINFO, and Embase. We calculated the effect sizes (Hedges g) for the difference between the conditions and their 95% CIs for posttest and follow-up measurements in a random effects model. A separate meta-analysis was performed to compare attrition between the VRE-CBT and CBT conditions.

RESULTS

A total of 16 trials with 817 participants were included. We identified 10 comparisons between VRE-CBT and a waitlist condition and 13 comparisons between VRE-CBT and a CBT condition. With regard to risk of bias, information on random sequence generation, allocation concealment, and risk of bias for selective outcome reporting was often absent or unclear. The mean effect size of VRE-CBT compared with waitlist (nco=10) was medium and significant, favoring VRE-CBT (Hedges g=−0.490, 95% CI −0.82 to −0.16; P=.003). The mean effect size of VRE-CBT compared with CBT (nco=13) was small and nonsignificant, favoring CBT (Hedges g=0.083, 95% CI −0.13 to 0.30; P=.45). The dropout rates between VRE-CBT and CBT (nco=10) showed no significant difference (odds ratio 0.79, 95% CI 0.49-1.27; P=.32). There were no indications of small study effects or publication bias.

CONCLUSIONS

The results of our study show that VRE-CBT is more effective than waitlist and as effective as CBT in the treatment of more severe anxiety disorders. Therefore, VRE-CBT may be considered a promising alternative to CBT for patients with more severe anxiety disorders. Higher-quality randomized controlled trials are needed to verify the robustness of these findings.
Web-Based Cognitive Testing in Psychiatric Research: Validation and Usability Study (Preprint)
Authors: Lynham Amy Joanne , Jones Ian R , Walters James T R
Published: February 2022

BACKGROUND

Cognitive impairments are features of many psychiatric disorders and affect functioning. A barrier to cognitive research on psychiatric disorders is the lack of large cross-disorder data sets. However, the collection of cognitive data can be logistically challenging and expensive. Web-based collection may be an alternative; however, little is known about who does and does not complete web-based cognitive assessments for psychiatric research.

OBJECTIVE

The aims of this study are to develop a web-based cognitive battery for use in psychiatric research, validate the battery against the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery, and compare the characteristics of the participants who chose to take part with those of the individuals who did not participate.

METHODS

Tasks were developed by The Many Brains Project and selected to measure the domains specified by the MATRICS initiative. We undertook a cross-validation study of 65 participants with schizophrenia, bipolar disorder, depression, or no history of psychiatric disorders to compare the web-based tasks with the MATRICS Consensus Cognitive Battery. Following validation, we invited participants from 2 large ongoing genetic studies, which recruited participants with psychiatric disorders to complete the battery and evaluated the demographic and clinical characteristics of those who took part.

RESULTS

Correlations between web-based and MATRICS tasks ranged between 0.26 and 0.73. Of the 961 participants, 887 (92.3%) completed at least one web-based task, and 644 (67%) completed all tasks, indicating adequate completion rates. Predictors of web-based participation included being female (odds ratio [OR] 1.3, 95% CI 1.07-1.58), ethnicity other than White European (OR 0.66, 95% CI 0.46-0.96), higher levels of education (OR 1.19, 95% CI 1.11-1.29), diagnosis of an eating disorder (OR 2.17, 95% CI 1.17-4) or depression and anxiety (OR 5.12, 95% CI 3.38-7.83), and absence of a diagnosis of schizophrenia (OR 0.59, 95% CI 0.35-0.94). Lower performance on the battery was associated with poorer functioning (B=−1.76, SE 0.26; P<.001).

CONCLUSIONS

Our findings offer valuable insights into the advantages and disadvantages of testing cognitive function remotely for mental health research.
Standardized Integration of Person-Generated Data Into Routine Clinical Care (Preprint)
Authors: Zeng Billy , Bove Riley , Carini Simona , Lee Jonathan Shing-Jih , Pollak JP , Schleimer Erica , Sim Ida
Published: February 2022

UNSTRUCTURED

Person-generated data (PGD) are a valuable source of information on a person’s health state in daily life and in between clinic visits. To fully extract value from PGD, health care organizations must be able to smoothly integrate data from PGD devices into routine clinical workflows. Ideally, to enhance efficiency and flexibility, such integrations should follow reusable processes that can easily be replicated for multiple devices and data types. Instead, current PGD integrations tend to be one-off efforts entailing high costs to build and maintain custom connections with each device and their proprietary data formats. This viewpoint paper formulates the integration of PGD into clinical systems and workflow as a PGD integration pipeline and reviews the functional components of such a pipeline. A PGD integration pipeline includes PGD acquisition, aggregation, and consumption. Acquisition is the person-facing component that includes both technical (eg, sensors, smartphone apps) and policy components (eg, informed consent). Aggregation pools, standardizes, and structures data into formats that can be used in health care settings such as within electronic health record–based workflows. PGD consumption is wide-ranging, by different solutions in different care settings (inpatient, outpatient, consumer health) for different types of users (clinicians, patients). The adoption of data and metadata standards, such as those from IEEE and Open mHealth, would facilitate aggregation and enable broader consumption. We illustrate the benefits of a standards-based integration pipeline for the illustrative use case of home blood pressure monitoring. A standards-based PGD integration pipeline can flexibly streamline the clinical use of PGD while accommodating the complexity, scale, and rapid evolution of today’s health care systems.
Determining the Case Fatality Rate of COVID-19 in Italy: Novel Epidemiological Study (Preprint)
Authors: Yan Mengqing , Kang Wenjun , Guo Zhifeng , Wang Qi , Wang Peizhong Peter , Zhu Yun , Yang Yongli , Wang Wei
Published: February 2022

BACKGROUND

COVID-19, which emerged in December 2019, has spread rapidly around the world and has become a serious public health event endangering human life. With regard to COVID-19, there are still many unknowns, such as the exact case fatality rate (CFR).

OBJECTIVE

The main objective of this study was to explore the value of the discharged CFR (DCFR) to make more accurate forecasts of epidemic trends of COVID-19 in Italy.

METHODS

We retrieved the epidemiological data of COVID-19 in Italy published by the John Hopkins Coronavirus Resource Center. We then used the proportion of deaths to discharged cases（including deaths and recovered cases） to calculate the total DCFR (tDCFR), monthly DCFR (mDCFR), and stage DCFR (sDCFR). Furthermore, we analyzed the trend in the mDCFR between January and December 2020 using joinpoint regression analysis, used ArcGIS version 10.7 to visualize the spatial distribution of the epidemic CFR, and assigned different colors to each province based on the CFR or tDCFR.

RESULTS

We calculated the numbers and obtained the new indices of the tDCFR and mDCFR for calculating the fatality rate. The results showed that the tDCFR and mDCFR fluctuated greatly from January to May. They first showed a rapid increase followed by a rapid decline after reaching the peak. The map showed that the provinces with a high tDCFR were Emilia-Romagna, Puglia, and Lombardia. The change trend of the mDCFR over time was divided into the following 2 stages: the first stage (from January to May) and the second stage (from June to December). With regard to worldwide COVID-19 statistics, among 6 selected countries, the United States had the highest tDCFR (4.26%), while the tDCFR of the remaining countries was between 0.98% and 2.72%.

CONCLUSIONS

We provide a new perspective for assessing the fatality of COVID-19 in Italy, which can use ever-changing data to calculate a more accurate CFR and scientifically predict the development trend of the epidemic.
A Hierarchy of Digital Health: Towards the Creation of a Standard Glossary of Terms (Preprint)
Authors: Gleason Ann , Cavanagh Renee , Walden Behrens Shaunesy , Mackey Rachel , Ciulla Robert
Published: February 2022

BACKGROUND

Background: Digital health technologies present opportunities to improve health care by reducing costs, increasing access, and augmenting care, in addition to the benefits of remote care provided during the COVID-19 pandemic. One barrier to research and development in the field of digital health is the lack of clarity and consistency in terminology. Terms are used interchangeably and usage varies greatly from country to country. An international consensus is needed on terminology to facilitate more effective research and practice in this important field.

OBJECTIVE

Objective: The objective of this review of the literature was to explore the international literature focusing on the terms used to describe the use of technology in health care, in the hopes of working towards the creation of a standard hierarchy and glossary of digital health terms.

METHODS

Methods: Google Trends was searched to identify relevant terminology. The PubMed database was searched using the most commonly occurring terminology and the keywords taxonomy or terminology or ontology or glossary or classification or definition. Literature older than 10 years was excluded due to the rapid changes in this topic over the past decade.

RESULTS

Results: Twelve articles with a focus on discussing digital health terminology were identified and reviewed, providing a history of term usage and agreed upon definitions. In addition, a hierarchy of terms was created under the domain term of Information and Communication Technology and encompassing three umbrella terms (digital health, ehealth and connected health), population-related terms (telemedicine and telehealth), technology or service-related terms, and specialty terms. The literature reviewed identified a relative consistency in term definitions, indicating that these terms should not be used interchangeably. For example, telehealth is a wider population health term than telemedicine, which is limited to the medical field. Recommendations for term usage are provided.

CONCLUSIONS

Conclusions: While digital health terms are interrelated and overlapping in their definitions, each term has a unique meaning and should not be used interchangeably with other terms. Definitions exist that are simple and straightforward, which could become standards if agreement can be reached. This review provides a useful step towards standardization of terms that could be used internationally to improve research, evaluation, dissemination, and communication among all stakeholders in the digital health field, however, technology is constantly changing so terms must be reviewed and updated as meanings change. This iterative process is necessary for optimum development and diffusion of concepts globally.
InCoPE-App: Study protocol for the usability and effectiveness of the individualized, tablet-based multimodal exercise program for institutionalized individuals with dementia delivered by nursing home employees. (Preprint)
Authors: Barisch-Fritz Bettina , Bezold Jelena , Scharpf Andrea , Trautwein Sandra , Krell-Roesch Janina , Woll Alexander
Published: February 2022

BACKGROUND

The Covid-19 pandemic has drastic consequences on everyday life in nursing homes. Limited personal resources and high hygiene standards often lead to interrupting physical exercise treatment. As a consequence, individuals with dementia (IWD) profiting from individualized exercise programs, are affected by the pandemic’s impact.

OBJECTIVE

Our goal is to develop an easily applicable application allowing nursing home employees (NHE) to test cognitive function and physical performance, and subsequently train IWD by a multimodal individualized exercise program.

METHODS

We will evaluate the InCoPE-App by applying a mixed method design. NHE will use the InCoPE-app for 18-weeks assessing cognitive function and physical performance of 44 IWD every three weeks and applying the individualized exercise program. We will record usability by log events, Post-Study System Usability and ISONORM 9241/10 questionnaires, as well as interviews focusing on satisfaction. Perceived hedonic and pragmatic quality will be assessed by AttrakDiff questionnaire. The effectiveness will be evaluated by changes in the quality of life as well as cognitive function and physical performance.

RESULTS

Enrollment of the study will be completed in the first half of 2022. We expect an improvement of the quality of life of IWD accompanied by improvements in cognitive function and physical performance. The usability of the InCoPE-App is expected to be well rated by NHE.

CONCLUSIONS

To date, there is no scientifically evaluated app available that enables NHE without expertise in sports science to deliver an individualized exercise program. A high usable and effective InCoPE-App allows NHE to test cognitive function and physical performance of IWD and, based thereon, select and deliver the most appropriate individualized exercise program, even in times of the pandemic.

CLINICALTRIAL

The study has been approved by the Ethics Committee of the Karlsruhe Institute of Technology.
German Register of Clinical Trials, drks.de. Identifier: DRKS00024069. Date of registration: 23 March 2021.
Combining Machine Learning, Patient-Reported Outcomes, and Value-Based Health Care: Protocol for Scoping Reviews (Preprint)
Authors: Raclin Tyler , Price Amy , Stave Christopher , Lee Eugenia , Reddy Biren , Kim Junsung , Chu Larry
Published: February 2022

BACKGROUND

Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) are self-reporting tools that can measure important information about patients, such as health priorities, experience, and perception of outcome. The use of traditional objective measures such as vital signs and lab values can be supplemented with these self-reported patient measures to provide a more complete picture of a patient’s health status. Machine learning, the use of computer algorithms that improve automatically through experience, is a powerful tool in health care that often does not use subjective information shared by patients. However, machine learning has largely been based on objective measures and has been developed without patient or public input. Algorithms often do not have access to critical information from patients and may be missing priorities and measures that matter to patients. Combining objective measures with patient-reported measures can improve the ability of machine learning algorithms to assess patients’ health status and improve the delivery of health care.

OBJECTIVE

The objective of this scoping review is to identify gaps and benefits in the way machine learning is integrated with patient-reported outcomes for the development of improved public and patient partnerships in research and health care.

METHODS

We reviewed the following 3 questions to learn from existing literature about the reported gaps and best methods for combining machine learning and patient-reported outcomes: (1) How are the public engaged as involved partners in the development of artificial intelligence in medicine? (2) What examples of good practice can we identify for the integration of PROMs into machine learning algorithms? (3) How has value-based health care influenced the development of artificial intelligence in health care? We searched Ovid MEDLINE(R), Embase, PsycINFO, Science Citation Index, Cochrane Library, and Database of Abstracts of Reviews of Effects in addition to PROSPERO and the ClinicalTrials website. The authors will use Covidence to screen titles and abstracts and to conduct the review. We will include systematic reviews and overviews published in any language and may explore additional study types. Quantitative, qualitative, and mixed methods studies are included in the reviews.

RESULTS

The search is completed, and Covidence software will be used to work collaboratively. We will report the review using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and Critical Appraisal Skills Programme for systematic reviews.

CONCLUSIONS

Findings from our review will help us identify examples of good practice for how to involve the public in the development of machine learning systems as well as interventions and outcomes that have used PROMs and PREMs.

INTERNATIONAL REGISTERED REPORT

DERR1-10.2196/36395
Impact of COVID-19 on the Noncommunicable Disease Programs Provided in the Primary Health Care Centers in Al-Rusafa Directorate of Health, 2020 (Preprint)
Authors: Hlaiwah Mohammed , Lami Faris
Published: February 2022

BACKGROUND

In recent years, noncommunicable diseases (NCDs) have globally shown an increasing impact on health status with disproportionately higher rates in developing countries. During the outbreak, health workers, equipment, and facilities have been reallocated to address the influx of patients with COVID-19. Restructuring of the health system could result in the closure of some health facilities.

OBJECTIVE

The aim of this paper was to determine the impact of COVID-19 on the performance of NCD programs implemented in the primary health care centers in Al-Rusafa DOH through comparing the performance indicators of 2019 and 2020, and to identify the potential causes of the changes.

METHODS

The study was conducted in Baghdad, Al-Rusafa, during the period from April to June 2021. A systematic sample was used to enroll 20 primary health care centers. The descriptive analysis focused on frequencies and percentages. Continuous variables are presented as mean (SD), and the independent t test was used to assess statistical significance. A P value of less than .05 is considered statistically significant.

RESULTS

There was a decrease in the number of served patients, even reaching zero in some units. Most staff were partially or completely assigned to the COVID-19 pandemic. There was a decline in yearly need of education material and folders for programs in 2020 and awareness campaigns performed in 2019 and 2020. The main reasons in the decline of these services were the closure of outpatient services as per government directive, the closure of outpatient disease-specific consultation clinics, and the decrease in outpatient volume due to patients not presenting.

CONCLUSIONS

The COVID-19 pandemic affected the NCD services in Iraq, including the disruption of many aspects of these services.
Clinical Applications of Rule-based Systems in Different Dental Specialties: Scoping Review (Preprint)
Authors: Aloufi Sara Hunaydi , Alrige Mayada , Bukhary Dalea
Published: February 2022

BACKGROUND

Oral diseases have been described by the World Health Organization (WHO) as the most prevalent diseases globally, affecting some 3.5 billion people. This leads to significant health and economic burdens and can impact the quality of life of affected individuals. Therefore, dentists have a great responsibility to efficiently diagnose and determine the best treatment option. However, some do not have the experience and knowledge to make the right clinical decisions. For this reason, artificial intelligence (AI) techniques, mainly rule-based systems, have been used in dentistry to aid physicians in making faster and more reliable decisions.

OBJECTIVE

This scoping review aims to explore and summarize the application of rule-based systems widely employed in dentistry and to evaluate their performance and practical significance.

METHODS

We conducted a scoping review following the methodology of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) on five databases: Web of Science, Scopus, Google Scholar, Saudi Digital Library, and the IEEE Xplore. We searched for literature published in English up to October 2021. Two reviewers evaluated each potentially relevant study for inclusion/exclusion criteria, and any discrepancies were resolved by a third researcher.

RESULTS

Of 303 studies, 19 fulfilled this review’s inclusion criteria. We identified two domains based on the methodology used in the included studies: (i) uncertainty management approaches employed in the rule-based system (n = 16) and (ii) integrating machine learning techniques with the rule-based system (n = 5). The vast majority of included publications used fuzzy logic to manage uncertainty (n = 11). A hybrid fuzzy rule-based system and neural network achieved the highest accuracy of 96%. From a medical perspective, the articles were aimed at diagnosis (n = 11), treatment (n = 3), and both diagnosis and treatment (n = 4), while less attention was paid to detection and classification (n = 1). The review also found that periodontology was the most commonly addressed specialty.

CONCLUSIONS

In an analysis of the current literature, rule-based systems were found reliable to assist dental practitioners in decision-making. Clinical decision-making involves a high level of uncertainty, which explains the tendency to use fuzzy logic in rule-based systems. These systems can also be used as educational tools primarily for both dental interns and less experienced general dentists to aid in making reliable decisions.
Tinnitus Assessment via performance in probabilistic learning tasks in the context of ecological momentary assessment (Preprint)
Authors: Zhang Lili , Monacelli Greta , Vashisht Himanshu , Schlee Winfried , Langguth Berthold , Ward Tomas
Published: February 2022

UNSTRUCTURED

Background: Chronic tinnitus is an increasing world-wide health concern, causing a significant burden to the health care system each year. The pandemic of Covid-19 has seen a further increase in reported cases. For those with tinnitus, symptoms are exacerbated due to social isolation and the elevated level of anxiety and depression caused by quarantine and lockdown. Although it has been reported that tinnitus patients can suffer changes in cognitive capabilities, changes in adaptive learning via decision-making tasks for tinnitus population has not yet been investigated.

Objective: In this study, we aim to assess state- and trait-related impairments in adaptive learning ability on the probabilistic learning task among tinnitus population. Given that performance in such tasks can be quantified through machine learning methods in terms of a small set of neural-informed model parameters, such approaches are promising in terms of assessment of tinnitus severity. We will first examine baseline differences in characterisation of decision-making under contingency volatility between healthy individuals and people suffering from tinnitus in terms of differences in the parameters of computational models in a cross-sectional experiment. We will also investigate if these computational markers that capture characteristics of decision-making can be used to understand the cognitive impact of tinnitus symptoms fluctuations through a longitudinal experimental design.
Methods: We have developed a mobile app named AthenaCX to deliver e-consent, baseline tinnitus and psychological assessments and regular Ecological Momentary Assessments (EMA) of perceived tinnitus loudness and a web-based aversive version of a probabilistic decision-making task, which can be triggered based on the participants’ responses to the EMA surveys. Computational models will be developed to fit participants’ choice data in the task and the cognitive parameters will be estimated to characterize participants’ current ability to adapt learning to the change of the simulated environment at each session when the task is triggered. Linear regression will be conducted to evaluate the impacts of baseline tinnitus severity, along with psychological assessments on adapting performance of decision-making. Repeated measures linear regression will be used to examine model-derived parameters of decision-making in measuring real-time perceived tinnitus loudness fluctuations.
Quetiapine augmentation of cognitive processing therapy in veterans with posttraumatic stress disorder. Design and methodology of a pilot study (Preprint)
Authors: Baig Muhammad
Published: February 2022

BACKGROUND

The limited efficacy of first-line treatment of posttraumatic stress disorder (PTSD) with selective serotonergic reuptake inhibitors commonly leads to the use of multiple medications that still fail to achieve symptomatic remission. VA/DOD guidelines identify trauma-focused psychotherapies as the evidence-based treatment for PTSD, but overall effectiveness is limited by reduced levels of patient engagement. Cognitive processing therapy (CPT) is the most widely-used trauma-focused therapy in the VA system for Veterans with PTSD. Our previous results based on a case series suggested that quetiapine monotherapy, but not risperidone or valproate, could increase engagement in CPT, thereby improving clinical outcomes through direct medication effects and indirectly through greater engagement in CPT.

OBJECTIVE

n/a

METHODS

We report the study protocol of a pilot study. This randomized, double blind placebo-controlled study was designed to evaluate the feasibility, safety, and preliminary efficacy of completing a randomized trial of quetiapine vs. placebo as an adjunct to promote patient engagement in CPT treatment for PTSD.

RESULTS

n/a

CONCLUSIONS

We expect that the success of this ongoing study should provide us with the preliminary data necessary to design a full-scale randomized trial.

CLINICALTRIAL

NCT04280965