bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Adaptive Engagement and Support Model for People With Chronic Health Conditions in Online Health Communities: Combined Content Analysis
Authors: Green Brian M , Van Horn Katelyn Tente , Gupte Ketki , Evans Megan , Hayes Sara , Bhowmick Amrita 
Published: June 2020

Background
With the pervasiveness of social media, online health communities (OHCs) are an important tool for facilitating information sharing and support among people with chronic health conditions. Importantly, OHCs offer insight into conversations about the lived experiences of people with particular health conditions. Little is known about the aspects of OHCs that are important to maintain safe and productive conversations that support health.

Objective
This study aimed to assess the provision of social support and the role of active moderation in OHCs developed in accordance with and managed by an adaptive engagement model. This study also aimed to identify key elements of the model that are central to the development, maintenance, and adaptation of OHCs for people with chronic health conditions.

Methods
This study used combined content analysis, a mixed methods approach, to analyze sampled Facebook post comments from 6 OHCs to understand how key aspects of the adaptive engagement model facilitate different types of social support. OHCs included in this study are for people living with multiple sclerosis, migraine, irritable bowel syndrome, rheumatoid arthritis, lung cancer, and prostate cancer. An exploratory approach was used in the analysis, and initial codes were grouped into thematic categories and then confirmed through thematic network analysis using the Dedoose qualitative analysis software tool. Thematic categories were compared for similarities and differences for each of the 6 OHCs and by topic discussed.

Results
Data on the reach and engagement of the Facebook posts and the analysis of the sample of 5881 comments demonstrate that people with chronic health conditions want to engage on the web and find value in supporting and sharing their experiences with others. Most comments made in these Facebook posts were expressions of social support for others living with the same health condition (3405/5881, 57.89%). Among the comments with an element of support, those where community members validated the knowledge or experiences of others were most frequent (1587/3405, 46.61%), followed by the expression of empathy and understanding (1089/3405, 31.98%). Even among posts with more factual content, such as insurance coverage issues, user comments still had frequent expressions of support for others (80/213, 37.5%).

Conclusions
The analysis of this OHC adaptive engagement model in action shows that the foundational elements—social support, engagement, and moderation—can effectively be used to provide a rich and dynamic community experience for individuals with chronic health conditions. Social support is demonstrated in a variety of ways, including sharing information or validating information shared by others, expressions of empathy, and sharing encouraging statements with others.
Supervised Digital Neuropsychological Tests for Cognitive Decline in Older Adults: Usability and Clinical Validity Study
Authors: Lunardini Francesca , Luperto Matteo , Romeo Marta , Basilico Nicola , Daniele Katia , Azzolino Domenico , Damanti Sarah , Abbate Carlo , Mari Daniela , Cesari Matteo , Borghese Nunzio Alberto , Ferrante Simona 
Published: June 2020

Background
Dementia is a major and growing health problem, and early diagnosis is key to its management.

Objective
With the ultimate goal of providing a monitoring tool that could be used to support the screening for cognitive decline, this study aims to develop a supervised, digitized version of 2 neuropsychological tests: Trail Making Test and Bells Test. The system consists of a web app that implements a tablet-based version of the tests and consists of an innovative vocal assistant that acts as the virtual supervisor for the execution of the test. A replay functionality is added to allow inspection of the user’s performance after test completion.

Methods
To deploy the system in a nonsupervised environment, extensive functional testing of the platform was conducted, together with a validation of the tablet-based tests. Such validation had the two-fold aim of evaluating system usability and acceptance and investigating the concurrent validity of computerized assessment compared with the corresponding paper-and-pencil counterparts.

Results
The results obtained from 83 older adults showed high system acceptance, despite the patients’ low familiarity with technology. The system software was successfully validated. A concurrent validation of the system reported good ability of the digitized tests to retain the same predictive power of the corresponding paper-based tests.

Conclusions
Altogether, the positive results pave the way for the deployment of the system to a nonsupervised environment, thus representing a potential efficacious and ecological solution to support clinicians in the identification of early signs of cognitive decline.
Effect of Prior Health Knowledge on the Usability of Two Home Medical Devices: Usability Study
Authors: Chaniaud Noémie , Métayer Natacha , Megalakaki Olga , Loup-Escande Emilie 
Published: June 2020

Background
Studies on the usability of health care devices are becoming more common, although usability standards are not necessarily specified and followed. Yet, there is little knowledge about the impact of the context of use on the usability outcome. It is specified in the usability standard (ISO 9241-11, 2018) of a device that it may be affected by its context of use and especially by the characteristics of its users. Among these, prior health knowledge (ie, knowledge about human body functioning) is crucial. However, no study has shown that prior health knowledge influences the usability of medical devices.

Objective
Our study aimed to fill this gap by analyzing the relationship between the usability of two home medical devices (soon to be used in the context of ambulatory surgery) and prior health knowledge through an experimental approach.

Methods
For assessing the usability of two home medical devices (blood pressure monitor and pulse oximeter), user tests were conducted among 149 students. A mixed-methods approach (subjective vs objective) using a variety of standard instruments was adopted (direct observation, video analysis, and questionnaires). Participants completed a questionnaire to show the extent of their previous health knowledge and then operated both devices randomly. Efficiency (ie, handling time) and effectiveness (ie, number of handling errors) measures were collected by video analysis. Satisfaction measures were collected by a questionnaire (system usability scale [SUS]). The qualitative observational data were coded using inductive analysis by two independent researchers specialized in cognitive psychology and cognitive ergonomics. Correlational analyses and clusters were performed to test how usability relates to sociodemographic characteristics and prior health knowledge.

Results
The results indicated a lack of usability for both devices. Regarding the blood pressure monitor (137 participants), users made approximately 0.77 errors (SD 1.49), and the mean SUS score was 72.4 (SD 21.07), which is considered “satisfactory.” The pulse oximeter (147 participants) appeared easier to use, but participants made more errors (mean 0.99, SD 0.92), and the mean SUS score was 71.52 (SD 17.29), which is considered “satisfactory.” The results showed a low negative and significant correlation only between the effectiveness of the two devices and previous knowledge (blood pressure monitor: r=−0.191, P=.03; pulse oximeter: r=−0.263, P=.001). More subtly, we experimentally identified the existence of a threshold level (χ²2,146=10.9, P=.004) for health knowledge to correctly use the pulse oximeter, but this was missing for the blood pressure monitor.

Conclusions
This study has the following two contributions: (1) a theoretical interest highlighting the importance of user characteristics including prior health knowledge on usability outcomes and (2) an applied interest to provide recommendations to designers and medical staff.
Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach
Authors: Zhu Jane M , Sarker Abeed , Gollust Sarah , Merchant Raina , Grande David 
Published: June 2020

Background
Twitter is a potentially valuable tool for public health officials and state Medicaid programs in the United States, which provide public health insurance to 72 million Americans.

Objective
We aim to characterize how Medicaid agencies and managed care organization (MCO) health plans are using Twitter to communicate with the public.

Methods
Using Twitter’s public application programming interface, we collected 158,714 public posts (“tweets”) from active Twitter profiles of state Medicaid agencies and MCOs, spanning March 2014 through June 2019. Manual content analyses identified 5 broad categories of content, and these coded tweets were used to train supervised machine learning algorithms to classify all collected posts.

Results
We identified 15 state Medicaid agencies and 81 Medicaid MCOs on Twitter. The mean number of followers was 1784, the mean number of those followed was 542, and the mean number of posts was 2476. Approximately 39% of tweets came from just 10 accounts. Of all posts, 39.8% (63,168/158,714) were classified as general public health education and outreach; 23.5% (n=37,298) were about specific Medicaid policies, programs, services, or events; 18.4% (n=29,203) were organizational promotion of staff and activities; and 11.6% (n=18,411) contained general news and news links. Only 4.5% (n=7142) of posts were responses to specific questions, concerns, or complaints from the public.

Conclusions
Twitter has the potential to enhance community building, beneficiary engagement, and public health outreach, but appears to be underutilized by the Medicaid program.
Development and Preliminary Evaluation of the Effects of an mHealth Web-Based Platform (HappyAir) on Adherence to a Maintenance Program After Pulmonary Rehabilitation in Patients With Chronic Obstructive Pulmonary Disease: Randomized Controlled Trial
Authors: Jiménez-Reguera Begoña , Maroto López Eva , Fitch Shane , Juarros Lourdes , Sánchez Cortés Marta , Rodríguez Hermosa Juan Luis , Calle Rubio Myriam , Hernández Criado María Teresa , López Marta , Angulo-Díaz-Parreño Santiago , Martín-Pintado-Zugasti Aitor , Vilaró Jordi 
Published: June 2020

Background
Pulmonary rehabilitation is one of the main interventions to reduce the use of health resources, and it promotes a reduction in chronic obstructive pulmonary disease (COPD) costs. mHealth systems in COPD aim to improve adherence to maintenance programs after pulmonary rehabilitation by promoting the change in attitude and behavior necessary for patient involvement in the management of the disease.

Objective
This study aimed to assess the effects of an integrated care plan based on an mHealth web-based platform (HappyAir) on adherence to a 1-year maintenance program applied after pulmonary rehabilitation in COPD patients.

Methods
COPD patients from three hospitals were randomized to a control group or an intervention group (HappyAir group). Patients from both groups received an 8-week program of pulmonary rehabilitation and educational sessions about their illness. After completion of the process, only the HappyAir group completed an integrated care plan for 10 months, supervised by an mHealth system and therapeutic educator. The control group only underwent the scheduled check-ups. Adherence to the program was rated using a respiratory physiotherapy adherence self-report (CAP FISIO) questionnaire. Other variables analyzed were adherence to physical activity (Morisky-Green Test), quality of life (Chronic Obstructive Pulmonary Disease Assessment Test, St. George’s Respiratory Questionnaire, and EuroQOL-5D), exercise capacity (6-Minute Walk Test), and lung function.

Results
In total, 44 patients were recruited and randomized in the control group (n=24) and HappyAir group (n=20). Eight patients dropped out for various reasons. The CAP FISIO questionnaire results showed an improvement in adherence during follow-up period for the HappyAir group, which was statistically different compared with the control group at 12 months (56.1 [SD 4.0] vs 44.0 [SD 13.6]; P=.004) after pulmonary rehabilitation.

Conclusions
mHealth systems designed for COPD patients improve adherence to maintenance programs as long as they are accompanied by disease awareness and patient involvement in management.

Trial Registration
ClinicalTrials.gov NCT04479930; https://clinicaltrials.gov/ct2/show/NCT04479930
Epidemiological Observations on the Association Between Anosmia and COVID-19 Infection: Analysis of Data From a Self-Assessment Web Application
Authors: Denis Fabrice , Galmiche Simon , Dinh Aurélien , Fontanet Arnaud , Scherpereel Arnaud , Benezit Francois , Lescure François-Xavier 
Published: June 2020

Background
We developed a self-assessment and participatory surveillance web application for coronavirus disease (COVID-19), which was launched in France in March 2020.

Objective
Our objective was to determine if self-reported symptoms could help monitor the dynamics of the COVID-19 outbreak in France.

Methods
Users were asked questions about underlying conditions, sociodemographic status, zip code, and COVID-19 symptoms. Depending on the symptoms reported and the presence of coexisting disorders, users were told to either stay at home, contact a general practitioner (GP), or call an emergency phone number. Data regarding COVID-19–related hospitalizations were retrieved from the Ministry of Health.

Results
As of March 29, 2020, the application was opened 4,126,789 times; 3,799,535 electronic questionnaires were filled out; and 2,477,174 users had at least one symptom. In total, 34.8% (n=1,322,361) reported no symptoms. The remaining users were directed to self-monitoring (n=858,878, 22.6%), GP visit or teleconsultation (n=1,033,922, 27.2%), or an emergency phone call (n=584,374, 15.4%). Emergency warning signs were reported by 39.1% of participants with anosmia, a loss of the sense of smell (n=127,586) versus 22.7% of participants without anosmia (n=1,597,289). Anosmia and fever and/or cough were correlated with hospitalizations for COVID-19 (Spearman correlation coefficients=0.87 and 0.82, respectively; P<.001 for both).

Conclusions
This study suggests that anosmia may be strongly associated with COVID-19 and its severity. Despite a lack of medical assessment and virological confirmation, self-checking application data could be a relevant tool to monitor outbreak trends.

Trial Registration
ClinicalTrials.gov NCT04331171; https://clinicaltrials.gov/ct2/show/NCT04331171
Main Character’s Personality Conflict in Aladdin Movie
Authors: Nolen Nolen , Arianto Tomi 
Published: June 2020

Abstrak: Dalam jurnal ini bertujuan untuk menemukan konfilk kepribadian karakter utama yang direpresentasikan melalui id, ego, dan superego dominan yang terdapat dalam karakter Aladdin dalam film Aladdin. Dalam makalah ini digunakan teori psikologi Sigmund Freud yang menyatakan bahwa ada tiga struktur yang dapat membentuk watak seseorang. Tiga struktur tersebut yaitu id, ego, dan superego. Penulis menggunakan metode deskriptif untuk menjelaskan id, ego, dan superego dalam karakter Aladdin. Penulis memperoleh data dari menonton film Aladdin yang dirilis pada tahun 1992, kemudian mencatat dan memberi tanda dimana karakter Aladdin menunjukkan sisi id, ego, dan superegonya. Hasil dari penelitian ini adalah id Aladdin terdapat disaat Aladdin bermimpi ingin menjadikan hidupnya lebih baik dan watak Aladdin yang tegar meskipun dihina oleh orang sekitar. Dalam penelitian ini penulis berharap agar penelitian ini berguna dan membantu untuk siapapun yang membaca, khususnya dalam karya sastra. Kata Kunci: Id, Ego, Superego, Teori Sigmund Freud, Watak. Abstract: In this journal aims to find the main character’s personality conflict reflected from id, ego, and superego dominant that contained in Aladdin's character in film Aladdin. In this paper, the writer will use psychological theory of Sigmund Freud that states that there are three striking features that can shape a person's character. The three structures are id, ego, and superego. The author uses descriptive methods to explain the id, ego, and superego in the Aladdin character. The author obtained data from watching Aladdin which was released in 1992, then recorded and gave a sign where the character of Aladdin showed the id, ego, and superhero side. The results of this study are that Aladdin was present when Aladdin dreamed he wanted to make his life better and his character was strong despite being insulted by people around him. In this study the authors hope that this research is useful and helpful for anyone who reads, especially in literary works. Keywords: Id, Ego, Superego, Sigmund Freud's theory, Character.
Implementasi Load Balancing dan Failover to Device Mikrotik Router Menggunakan Metode NTH (Studi Kasus: PT.GO-JEK Indonesia)
Authors: Mustofa Achmmad , Ramayanti Desi 
Published: June 2020

Perkembangan jaringan komputer dan internet yang begitu pesat pada sekarang khususnya internet sebagai media informasi tentunya harus memiliki kualitas koneksi yang baik. Begitu juga yang terdapat pada PT.Gojek Indonesia yang telah memakai dua ISP (internet service provider). Saat banyak permintaan dari pemakai maka perangkat jaringan akan terbebani karena harus melakukan banyak proses pelayanan terhadap permintaan dari pengguna. Solusinya adalah dengan membagi beban trafik yang datang ke perangkat jaringan, jadi tidak berpusat ke salah satu ISP agar trafik dapat berjalan optimal, memaksimalkan throughput, memperkecil waktu tanggap dan menghindari overload pada salah satu jalur koneksi, teknologi itulah yang disebut Load balancing. Untuk diterapkan teknik Load balancing yang bisa mendistribusi beban kepada sebuah service yang ada pada server dengan memanfaatkan metode distribusi dua line koneksi yang disebut dengan metode NTH. Nantinya mikrotik diharapkan mampu mengoptimalkan bandwidth pada tiap client yang akan koneksi ke internet. Akan diterapkan juga Teknik failover pada jaringan ini, yaitu jika salah satu koneksi gateway sedang terputus maka gateway yang lainnya otomatis akan menopang semua traffic jaringan. Akan dibuat juga menejemen bandwith disemua client, agar pendistribusian bandwith merata. AbstractThe development of computer networks and internet so rapidly at the present time, particularly on the Internet as information media of course must have good connection quality. So also found on the PT.Gojek Indonesian who has used two ISP. When many requests from users, the network devices will be burdened because they have to do a lot of service processes for requests from users. The solution is to divide the traffic load that comes to network devices, so that it is not centered on one ISP so that traffic can run optimally, maximize throughput, minimize response time and avoid overloading one of the connection lines, that technology is called Load balancing. Load balancing techniques are applied to distribute the load against a service that is on the server by utilizing the two connection path distribution method called the Nth method. Later, the proxy hopes to be able to optimize the bandwidth for each client that will connect to the internet. Will also be implemented failover technique on this network, that is if one of the gateway connections is being interrupted then the other gateway will automatically support all network traffic. Will also create bandwidth management for all clients, so that bandwidth distribution is evenly distributed.
Penerapan Data Mining Menggunakan Algoritma Apriori untuk Menentukan Pola Penyebab Gelandangan dan Pengemis
Authors: Agustin Wirta , Muharmi Yulya 
Published: June 2020

<p class="Judul2">Gelandangan dan pengemis salah satu masalah yang ada di daerah perkotaan, karena dapat mengganggu ketertiban umum, keamanan, stabilitas dan pembangunan kota. Upaya yang dilakukan saat ini masih fokus pada cara penanganan gelandangan dan pengemis, belum untuk pencegahan. Salah satu cara yang bisa dilakukan adalah dengan menentukan pola usia gelandangan dan pengemis. Algoritma Apriori sebuah metode <em>Association Rule</em> dalam data mining untuk menentukan frequent itemset yang berfungsi membantu menemukan pola dalam sebuah data (<em>frequent pattern mining</em>). Perhitungan manual menggunakan algoritma apriori, menghasilkan pola kombinasi sebanyak 3 rules dengan nilai minimum <em>support</em> sebesar 30% dan nilai <em>confidence</em> tertinggi sebesar 100%. Pengujian penerapan Algoritma Apriori menggunakan aplikasi RapidMiner. RapidMiner salah satu software pengolahan data mining, diantaranya analisis teks, mengekstrak pola-pola dari data set dan mengkombinasikannya dengan metode statistika, kecerdasan buatan, dan database untuk mendapatkan informasi bermutu tinggi dari data yang diolah. Hasil pengujian menunjukkan perbandingan pola usia gelandangan dan pengemis yang berpotensi menjadi gelandangan dan pengemis. Berdasarkan hasil pengujian aplikasi RapidMiner dan hasil perhitungan manual Algoritma Apriori, dapat disimpulkan sesuai kriteria pengujian, bahiwa pola (rules) usia dan nilai confidence (c) hasil perhitungan manual Algoritma Apriori tidak mendekati nilai hasil pengujian menggunakan aplikasi RapidMiner, maka tingkat keakuratan pengujian rendah, yaitu 37.5 %.</p><p class="Judul2"> </p><p class="Judul2"><strong><em>Abstract </em></strong></p><p class="Judul2"><strong> </strong></p><p><em>Homeless and beggars are one of the problems in urban areas as they possibly disrupt public order, security, stability and urban development. The efforts conducted are still focusing on managing the existing homeless and beggars instead of preventing the potential ones. One of the methods used for solving this problem is Algoritma Apriori which determines the age pattern of homeless and beggars. Apriori Algorithm is an Association Rule method in data mining to determine frequent item set that serves to help in finding patterns in a data (frequent pattern mining). The manual calculation through Apriori Algorithm obtains combination pattern of 3 rules with a minimum support value of 30% and the highest confidence value of 100%. These patterns were refences for the incharged department in precaution action of homeless and beggars arising numbers. Apriori Algorithm testing uses the RapidMiner application which is one of data mining processing software, including text analysis, extracting patterns from data sets and combining them with statistical methods, artificial intelligence, and databases to obtain high quality information from processed data. Based on the results of the said testing, it can be concluded that the level of accuracy test is low, i.e. 37.5%.</em></p>