bluuebunny/crossref_metadata_2025_split huggingface dataset:
A 5-Minute Cognitive Assessment for Safe Remote Use in Patients With COVID-19: Clinical Case Series
Authors: Beresford Thomas , Ronan Patrick J , Hipp Daniel 
Published: May 2021

Background
Early clinical experience during the COVID-19 pandemic has begun to elucidate that the disease can cause brain function changes that may result in compromised cognition both acutely and during variable recovery periods. Reports on cognitive assessment of patients with COVID-19 are often limited to orientation alone. Further assessment may seem to create an inappropriate burden for patients with acute COVID-19, which is characterized by fatigue and confusion, and may also compromise examiner safety.

Objective
The aims of this study were to assess cognition in patients with COVID-19 as comprehensively as possible in a brief format, while observing safety precautions, and to establish a clear face value of the external validity of the assessment.

Methods
We adapted a brief cognitive assessment, previously applied to liver transplant candidates and medical/surgical inpatients, for remote use in patients hospitalized for COVID-19 treatment. Collecting quality assurance data from telephone-administered assessments, this report presents a series of 6 COVID-19 case vignettes to illustrate the use of this 5-minute assessment in the diagnosis and treatment of brain effects. Primary medical teams referred the cases for neuropsychiatric consultation.

Results
The age of the patients varied over four decades, and none of them were able to engage meaningfully with their surroundings on admission. On follow-up examination 6 to 10 days later, 4 of the 6 patients had recovered working memory, and only 1 had recovered calculation ability. Of the 6 patients, 2 were capable of complex judgment responses, while none of the cases completed frontal executive function testing in the normal range.

Conclusions
Cognitive assessment in patients with COVID-19 using this remote examination reveals patterns of cognitive recovery that vary among cases and are far more complex than loss of orientation. In this series, testing of specific temporal, parietal, and frontal lobe functions suggests that calculation ability, judgment, and especially frontal executive functions may characterize the effects of COVID-19 on the brain. Used widely and serially, this examination method can potentially inform our understanding of the effects of COVID-19 on the brain and of healing from the virus.
Patients’ Experiences of Using a Self-help App for Posttraumatic Stress Disorder: Qualitative Study
Authors: Riisager Lisa H G , Christensen Anne Bryde , Scharff Frederik Bernt , Arendt Ida-Marie T P , Ismail Israa , Lau Marianne Engelbrecht , Moeller Stine Bjerrum 
Published: May 2021

Background
Posttraumatic stress disorder (PTSD) is a common disorder that requires more treatment options. Mobile health (mHealth) app interventions are promising for patients with PTSD, as they can provide easily accessible support, strategies, and information. However, knowledge about mHealth interventions is sparse and primarily based on quantitative studies.

Objective
The aim of this study is to qualitatively explore the experiences of patients with PTSD with regard to using an mHealth app as a stand-alone intervention before commencing psychotherapeutic treatment.

Methods
We conducted semistructured interviews with 14 participants 6 weeks after they received the app. The participants were all referred to PTSD treatment and were waiting to commence psychotherapeutic treatment. During this waiting time, the participants had no contact with the health staff. Interviews were transcribed and were analyzed using thematic analysis.

Results
A total of 3 themes were identified—the use of app, being a patient, and the overall evaluation of the app. The use of the app was described with the subtheme of habits, and the theme of being a patient included the subthemes of having negative experiences with the app and being a part of a research project. The use of the app encompassed how psychological factors and technical problems could interfere with the use of the app. The theme of being a patient depicted that the waiting time before starting treatment was long, and a subgroup of patients experienced feeling worse during this time, which they partly attributed to using the app. Several suggestions for change have been described in the overall evaluation of the app.

Conclusions
The findings in this study revealed that emotional arousal influenced the use of the app and that it was difficult for participants to establish a habit of using the app, thus reflecting the importance of supporting habit formation when implementing an mHealth app in mental health care services. This study makes an important contribution to the field of mHealth research, as it revealed that some participants had negative experiences resulting from using the app, thus reflecting the potential harm of having an mHealth app without the support of a clinician. It is therefore recommended to use a blended care treatment or an approach in which mental health care professionals prescribe an mHealth app for relevant patients to avoid increased suicidal risk.
Smart Home Sensing and Monitoring in Households With Dementia: User-Centered Design Approach
Authors: Tiersen Federico , Batey Philippa , Harrison Matthew J C , Naar Lenny , Serban Alina-Irina , Daniels Sarah J C , Calvo Rafael A 
Published: May 2021

BackgroundAs life expectancy grows, so do the challenges of caring for an aging population. Older adults, including people with dementia, want to live independently and feel in control of their lives for as long as possible. Assistive technologies powered by artificial intelligence and internet of things devices are being proposed to provide living environments that support the users’ safety, psychological, and medical needs through remote monitoring and interventions.ObjectiveThis study investigates the functional, psychosocial, and environmental needs of people living with dementia, their caregivers, clinicians, and health and social care service providers toward the design and implementation of smart home systems.MethodsWe used an iterative user-centered design approach comprising 9 substudies. First, semistructured interviews (9 people with dementia, 9 caregivers, and 10 academic and clinical staff) and workshops (35 pairs of people with dementia and caregivers, and 12 health and social care clinicians) were conducted to define the needs of people with dementia, home caregivers, and professional stakeholders in both daily activities and technology-specific interactions. Then, the spectrum of needs identified was represented via patient–caregiver personas and discussed with stakeholders in a workshop (14 occupational therapists; 4 National Health Service pathway directors; and 6 researchers in occupational therapy, neuropsychiatry, and engineering) and 2 focus groups with managers of health care services (n=8), eliciting opportunities for innovative care technologies and public health strategies. Finally, these design opportunities were discussed in semistructured interviews with participants of a smart home trial involving environmental sensors, physiological measurement devices, smartwatches, and tablet-based chatbots and cognitive assessment puzzles (10 caregivers and 2 people with dementia). A thematic analysis revealed factors that motivate household members to use these technologies.ResultsOutcomes of these activities include a qualitative and quantitative analysis of patient, caregiver, and clinician needs and the identification of challenges and opportunities for the design and implementation of remote monitoring systems in public health pathways.ConclusionsParticipatory design methods supported the triangulation of stakeholder perspectives to aid the development of more patient-centered interventions and their translation to clinical practice and public health strategy. We discuss the implications and limitations of our findings, the value and the applicability of our methodology, and directions for future research.
Designing an Indoor Air Quality Monitoring App for Asthma Management in Children: User-Centered Design Approach
Authors: Kim Sunyoung , Park Yunoh , Ackerman Matthew K 
Published: May 2021

Background
Indoor air pollution is a well-known risk factor that triggers and exacerbates asthma, the most common pediatric chronic disease. Using a mobile app to monitor indoor air quality could be promising in engaging children in keeping their indoor air quality clean and healthy as secondary environmental prevention for asthma management. However, no app is available to allow children to monitor, assess, and improve their indoor air quality.

Objective
This study aims to design a mobile app that encourages children to monitor indoor air quality and track their asthma conditions through a user-centered, iterative design approach.

Methods
We reviewed existing apps for indoor air quality monitoring or asthma management for children and conducted two sets of semistructured interviews with 12 children with asthma. We then iteratively created prototypes and evaluated and revised them.

Results
Participants raised a series of outstanding questions on the prototype features and content that described their needs and perspectives, which informed the final designs. Following the identified requirements and recommendations, we developed two versions of the app: AirBuddy for presenting concrete information for indoor air quality and AirPet for gamifying the practice of monitoring indoor air quality.

Conclusions
By following an iterative, user-centered design process, we developed two versions of an app to encourage children with asthma to monitor indoor air quality and track their asthma condition. The user-centered design approach revealed two crucial aspects that require deeper consideration when creating a child-friendly app, including balancing brevity and expressivity and considering the longitudinal effects of gamification. As a next step, we plan to conduct a longitudinal deployment study to evaluate the real-world effects of our apps.
Mental Health and the Perceived Usability of Digital Mental Health Tools Among Essential Workers and People Unemployed Due to COVID-19: Cross-sectional Survey Study
Authors: Mata-Greve Felicia , Johnson Morgan , Pullmann Michael D , Friedman Emily C , Griffith Fillipo Isabell , Comtois Katherine A , Arean Patricia 
Published: May 2021

Background
COVID-19 has created serious mental health consequences for essential workers or people who have become unemployed as a result of the pandemic. Digital mental health tools have the potential to address this problem in a timely and efficient manner.

Objective
The purpose of this study was to document the extent of digital mental health tool (DMHT) use by essential workers and those unemployed due to COVID-19, including asking participants to rate the usability and user burden of the DMHT they used most to cope. We also explored which aspects and features of DMHTs were seen as necessary for managing stress during a pandemic by having participants design their own ideal DMHT.

Methods
A total of 2000 people were recruited from an online research community (Prolific) to complete a one-time survey about mental health symptoms, DMHT use, and preferred digital mental health features.

Results
The final sample included 1987 US residents that identified as either an essential worker or someone who was unemployed due to COVID-19. Almost three-quarters of the sample (1479/1987, 74.8%) reported clinically significant emotional distress. Only 14.2% (277/1957) of the sample used a DMHT to cope with stress associated with COVID-19. Of those who used DMHTs to cope with COVID-19, meditation apps were the most common (119/261, 45.6%). Usability was broadly in the acceptable range, although participants unemployed due to COVID-19 were less likely to report user burden with DMHTs than essential workers (t198.1=–3.89, P<.001). Individuals with emotional distress reported higher financial burden for their DMHT than nondistressed individuals (t69.0=–3.21, P=.01). When the sample was provided the option to build their own DMHT, the most desired features were a combination of mindfulness/meditation (1271/1987, 64.0%), information or education (1254/1987, 63.1%), distraction tools (1170/1987, 58.9%), symptom tracking for mood and sleep (1160/1987, 58.4%), link to mental health resources (1140/1987, 57.4%), and positive psychology (1131/1986, 56.9%). Subgroups by employment, distress, and previous DMHT use status had varied preferences. Of those who did not use a DMHT to cope with COVID-19, most indicated that they did not consider looking for such a tool to help with coping (1179/1710, 68.9%).

Conclusions
Despite the potential need for DMHTs, this study found that the use of such tools remains similar to prepandemic levels. This study also found that regardless of the level of distress or even past experience using an app to cope with COVID-19, it is possible to develop a COVID-19 coping app that would appeal to a majority of essential workers and unemployed persons.
Knowledge and Attitude Toward Evidence-Based Medicine and Associated Factors Among Medical Interns in Amhara Regional State Teaching Hospitals, Northwest Ethiopia: Cross-sectional Study
Authors: Emwodew Delelegn , Melese Tesfahun , Takele Adamu , Mesfin Nebiyu , Tariku Binyam 
Published: May 2021

Background
Evidence-based medicine (EBM) is widely accepted in medicine. It is necessary to improve the knowledge and attitudes of medical students in the use of evidence. In Ethiopia, little is known about medical students’ knowledge and attitudes toward EBM.

Objective
This study aimed to assess the knowledge and attitudes toward EBM and its associated factors among medical interns in teaching hospitals.

Methods
A cross-sectional survey was conducted using a random sample of medical interns in teaching hospitals in Ethiopia. Multivariable logistic regression analyses were used to identify the factors associated with the knowledge and attitudes toward EBM. Adjusted odds ratio (AOR) with 95% confidence interval and P≤.05 was used to quantify strength of association between variables.

Results
Out of a sample of 423 medical interns, 403 completed the questionnaire (95.3% response rate). Overall, 68.0% (274/403 of respondents had a favorable attitude toward EBM and 57.1% (230/403) had good knowledge of EBM. The majority (355/403, 88.1%) of participants had internet access. Only 19.6% (79/403) of respondents had received EBM-related training. Respondents’ knowledge of EBM was associated with previous EBM training (AOR 2.947, 95% CI 1.648-5.268, P<.001), understanding of sensitivity (AOR 2.836, 95% CI 1.824-4.408, P=.003), and internet access (AOR 2.914, 95% CI 1.494-5.685, P=.002). The use of an electronic database as a source of information (AOR 1.808, 95% CI 1.143-2.861, P=.01) and understanding of absolute risk reduction (AOR 2.750, 95% CI 1.105-6.841, P=.03) were predictors of positive attitudes.

Conclusions
This study demonstrates a lack of formal EBM training and awareness of basic concepts of EBM among medical interns. Medical intern attitudes toward EBM are relatively good. To enhance EBM knowledge and skills, formal teaching of EBM should be integrated into medical education.
A Virtual Cardiovascular Care Program for Prevention of Heart Failure Readmissions in a Skilled Nursing Facility Population: Retrospective Analysis
Authors: Friedman Daniel M , Goldberg Jana M , Molinsky Rebecca L , Hanson Mark A , Castaño Adam , Raza Syed-Samar , Janas Nodar , Celano Peter , Kapoor Karen , Telaraja Jina , Torres Maria L , Jain Nayan , Wessler Jeffrey D 
Published: May 2021

Background
Patients with heart failure (HF) in skilled nursing facilities (SNFs) have 30-day hospital readmission rates as high as 43%. A virtual cardiovascular care program, consisting of patient selection, initial televisit, postconsultation care planning, and follow-up televisits, was developed and delivered by Heartbeat Health, Inc., a cardiovascular digital health company, to 11 SNFs (3510 beds) in New York. The impact of this program on the expected SNF 30-day HF readmission rate is unknown, particularly in the COVID-19 era.

Objective
The aim of the study was to assess whether a virtual cardiovascular care program could reduce the 30-day hospital readmission rate for patients with HF discharged to SNF relative to the expected rate for this population.

Methods
We performed a retrospective case review of SNF patients who received a virtual cardiology consultation between August 2020 and February 2021. Virtual cardiologists conducted 1 or more telemedicine visit via smartphone, tablet, or laptop for cardiac patients identified by a SNF care team. Postconsult care plans were communicated to SNF clinical staff. Patients included in this analysis had a preceding index admission for HF.

Results
We observed lower hospital readmission among patients who received 1 or more virtual consultations compared with the expected readmission rate for both cardiac (3% vs 10%, respectively) and all-cause etiologies (18% vs 27%, respectively) in a population of 3510 patients admitted to SNF. A total of 185/3510 patients (5.27%) received virtual cardiovascular care via the Heartbeat Health program, and 40 patients met study inclusion criteria and were analyzed, with 26 (65%) requiring 1 televisit and 14 (35%) requiring more than 1. Cost savings associated with this reduction in readmissions are estimated to be as high as US $860 per patient.

Conclusions
The investigation provides initial evidence for the potential effectiveness and efficiency of virtual and digitally enabled virtual cardiovascular care on 30-day hospital readmissions. Further research is warranted to optimize the use of novel virtual care programs to transform delivery of cardiovascular care to high-risk populations.
Enhancing Detection Performance of Face Recognition Algorithm Using PCA-Faster R-CNN
Authors: Muhammad Hashiru Isiaka , Musa Kabir Ibrahim , Abdulrahman Mustapha Lawal , Abubakar Abdullahi , Umar Kabiru , Ishola Abdulhakeem 
Published: May 2021

In this paper, we present a new face detection scheme using deep learning and achieving state-of-the-art recognition performance using real-world datasets. We designed and implemented a face recognition system using Principal Component Analysis (PCA) and Faster R Convolutional Neural Network (Faster R CNN). In particular, we improve the state-of-the-art Faster RCNN framework by using Principal Component Analysis (PCA) technique and Faster R CNN to detect and recognise faces in a face database. The Principal Component Analysis (PCA) was used to extract features and dimensionality reduction from the face database, while the Faster R Convolutional Neural Network algorithm was used to identify patterns in the dataset via training the neural network. The three real-world datasets used in our experiment are ORL, Yale, and California face dataset. When implemented on the ORL face dataset, the algorithm achieved average recognition accuracy of 99%, with a recognition time of 147.72 seconds for 10 runs, and the recognition time/image was 0.3 sec/image on 400 images. The Yale face dataset achieved average recognition accuracy of 99.24% with a recognition time of 63.45 seconds for 10 runs, and the recognition time/image was 0.53 sec/image on 120 images. Finally, on California Face Database (CFD), it achieved average recognition accuracy of 99.52% with a recognition time of 226.05 seconds for 10 runs, and the recognition time/image was 0.27 sec/image on 827 images. On the CFD dataset, however, the proposed approach has excellent classification performance when the recall ratio is high. The proposed method achieves a higher recall and accuracy ratio than the Faster RCNN without PCA method. For the F-score, the proposed method achieved 0.98, which is significantly higher than the 0.95 achieved by the Faster-RCNN. This demonstrates the superiority of our model performance-wise as against state-of-the-art, both in terms of accuracy and fast recognition. Therefore our model is more efficient when compared to the latest researches done in the area of facial recognition.
«Calma», de Óscar L. Figueruelo Burrieza
Authors: Panero García María Pilar 
Published: May 2021

Reseña del libro Calma (Barcelona, Avant, 2020), de Óscar L. Figueruelo.
Óscar Figueruelo (1972) debuta como novelista con una historia sobre el miedo a lo desconocido ambientada en una comarca de pequeños pueblos y su agro circundante.
MODERASI SISTEM PENGENDALIAN INTERN PEMERINTAH PADA PENGARUH SAKD, SIMDA, DAN KOMPETENSI SUMBER DAYA MANUSIA TERHADAP EFEKTIVITAS PENGELOLAAN KEUANGAN DAERAH
Authors: Anggi . , Basri Yesi Mutia , Rofika . 
Published: May 2021

This study aims to examine influence of the application of the Regional Financial Accounting System, the Regional Information Management System and the Competency of Human Resources on the Effectiveness of Regional Financial Management with the Internal Control System of the Government as the Varıabel Moderatıng. The population in this reserach are all employees who work at OPD Siak Regency, selected using purposive sampling technique. 92 respondents participated in this study . Data analysis techniques used in this study are multiple regression and moderate regression analysis (MRA).. The results of this study conclude: The application of regional financial accounting systems, regional financial management information systems, human resource competence affects the effectiveness of regional financial management. And the Government Internal Control System (SPIP) can moderate the implementation of regional financial accounting systems, regional financial management information systems and not for the competence of human resources on the effectiveness of regional financial management.
PERAN BOOK TAX DIFFERENCES MEMODERASI PENGARUH ARUS KAS AKRUAL DAN ARUS KAS OPERASI TERHADAP EARNINGS PERSISTENCE
Authors: Pratiwi Adhitya Putri , Sahara Lia Ira 
Published: May 2021

Penelitian ini bertujuan untuk menguji peran Book Tax Difference dalam Memoderasi Pengaruh Arus Kas Akrual dan Arus Kas Operasi Terhadap Earnings Persistence. Tujuan penelitian ini adalah untuk menjelaskan dan melanjutkan penelitian sebelumnya mengenai peran Book Tax Difference dalam Memoderasi Pengaruh Arus Kas Akrual dan Arus Kas Operasi Terhadap Earnings Persistence.
Sample pada penelitian ini adalah perusahaan sektor konsumsi yang terdaftar di Bursa Efek Indonesia dan memperoleh laba selama periode 2014-2018. Sampel dipilih dengan menggunakan metode purposive sampling dengan jumlah sample yang memnuhi kriteria sebanyak 11 perusahaan. Metode analisis yang digunakan dalam penelitian ini adalah uji regresi data panel dan analisis regresi moderasi.
Hasil penelitian menunjukkan bahwa arus kas akrual dan arus kas operasi berpengaruh terhadap earnings persistence, sedangkan book tax difference tidak dapat memoderasi pengaruh arus kas akrual dan arus kas operasi terhadap earnings persistence.