bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Large-scale Social Media Analytics to Understand Patient Perspectives About Urinary Tract Infections: Thematic Analysis
Authors: Gonzalez Gabriela , Vaculik Kristina , Khalil Carine , Zektser Yuliya , Arnold Corey , Almario Christopher V , Spiegel Brennan , Anger Jennifer 
Published: January 2022

Background
Current qualitative literature about the experiences of women dealing with urinary tract infections (UTIs) is limited to patients recruited from tertiary centers and medical clinics. However, traditional focus groups and interviews may limit what patients share. Using digital ethnography, we analyzed free-range conversations of an online community.

Objective
This study aimed to investigate and characterize the patient perspectives of women dealing with UTIs using digital ethnography.

Methods
A data-mining service was used to identify online posts. A thematic analysis was conducted on a subset of the identified posts. Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. Each identified topic was generated as a discrete distribution over the words in the collection, which can be thought of as a word cloud. We also performed a thematic analysis of the word cloud topic model results.

Results
A total of 83,589 posts by 53,460 users from 859 websites were identified. Our hand-coding inductive analysis yielded the following 7 themes: quality-of-life impact, knowledge acquisition, support of the online community, health care utilization, risk factors and prevention, antibiotic treatment, and alternative therapies. Using the LDA topic model method, 105 themes were identified and consolidated into 9 categories. Of the LDA-derived themes, 25.7% (27/105) were related to online community support, and 22% (23/105) focused on UTI risk factors and prevention strategies.

Conclusions
Our large-scale social media analysis supports the importance and reproducibility of using online data to comprehend women’s UTI experience. This inductive thematic analysis highlights patient behavior, self-empowerment, and online media utilization by women to address their health concerns in a safe, anonymous way.
Development of a Pipeline for Adverse Drug Reaction Identification in Clinical Notes: Word Embedding Models and String Matching
Authors: Siegersma Klaske R , Evers Maxime , Bots Sophie H , Groepenhoff Floor , Appelman Yolande , Hofstra Leonard , Tulevski Igor I , Somsen G Aernout , den Ruijter Hester M , Spruit Marco , Onland-Moret N Charlotte 
Published: January 2022

Background
Knowledge about adverse drug reactions (ADRs) in the population is limited because of underreporting, which hampers surveillance and assessment of drug safety. Therefore, gathering accurate information that can be retrieved from clinical notes about the incidence of ADRs is of great relevance. However, manual labeling of these notes is time-consuming, and automatization can improve the use of free-text clinical notes for the identification of ADRs. Furthermore, tools for language processing in languages other than English are not widely available.

Objective
The aim of this study is to design and evaluate a method for automatic extraction of medication and Adverse Drug Reaction Identification in Clinical Notes (ADRIN).

Methods
Dutch free-text clinical notes (N=277,398) and medication registrations (N=499,435) from the Cardiology Centers of the Netherlands database were used. All clinical notes were used to develop word embedding models. Vector representations of word embedding models and string matching with a medical dictionary (Medical Dictionary for Regulatory Activities [MedDRA]) were used for identification of ADRs and medication in a test set of clinical notes that were manually labeled. Several settings, including search area and punctuation, could be adjusted in the prototype to evaluate the optimal version of the prototype.

Results
The ADRIN method was evaluated using a test set of 988 clinical notes written on the stop date of a drug. Multiple versions of the prototype were evaluated for a variety of tasks. Binary classification of ADR presence achieved the highest accuracy of 0.84. Reduced search area and inclusion of punctuation improved performance, whereas incorporation of the MedDRA did not improve the performance of the pipeline.

Conclusions
The ADRIN method and prototype are effective in recognizing ADRs in Dutch clinical notes from cardiac diagnostic screening centers. Surprisingly, incorporation of the MedDRA did not result in improved identification on top of word embedding models. The implementation of the ADRIN tool may help increase the identification of ADRs, resulting in better care and saving substantial health care costs.
Treatment of Persistent Postconcussion Syndrome With Repetitive Transcranial Magnetic Stimulation Using Functional Near-Infrared Spectroscopy as a Biomarker of Response: Protocol for a Randomized Controlled Clinical Trial
Authors: du Plessis Sané , Oni Ibukunoluwa K , Lapointe Andrew P , Campbell Christina , Dunn Jeff F , Debert Chantel T 
Published: January 2022

Background
Approximately one-third of all concussions lead to persistent postconcussion syndrome (PPCS). Repetitive transcranial magnetic stimulation (rTMS) is a form of noninvasive brain stimulation that has been extensively used to treat refractory major depressive disorder and has a strong potential to be used as a treatment for patients with PPCS. Functional near-infrared spectroscopy (fNIRS) has already been used as a tool to assess patients with PPCS and may provide insight into the pathophysiology of rTMS treatment in patients with PPCS.

Objective
The primary objective of this research is to determine whether rTMS treatment improves symptom burden in patients with PPCS compared to sham treatment using the Rivermead postconcussion symptom questionnaire. The secondary objective is to explore the neuropathophysiological changes that occur following rTMS in participants with PPCS using fNIRS. Exploratory objectives include determining whether rTMS treatment in participants with PPCS will also improve quality of life, anxiety, depressive symptoms, cognition, posttraumatic stress, and function secondary to headaches.

Methods
A total of 44 adults (18-65 years old) with PPCS (>3 months to 5 years) will participate in a double-blind, sham-controlled, concealed allocation, randomized clinical trial. The participants will engage in either a 4-week rTMS treatment protocol or sham rTMS protocol (20 treatments). The left dorsolateral prefrontal cortex will be located through Montreal Neurologic Institute coordinates. The intensity of the rTMS treatment over the left dorsolateral prefrontal cortex will be 120% of resting motor threshold, with a frequency of 10 Hz, 10 trains of 60 pulses per train (total of 600 pulses), and intertrain interval of 45 seconds. Prior to starting the rTMS treatment, participant and injury characteristics, questionnaires (symptom burden, quality of life, depression, anxiety, cognition, and headache), and fNIRS assessment will be collected. Repeat questionnaires and fNIRS will occur immediately after rTMS treatment and at 1 month and 3 months post rTMS. Outcome parameters will be analyzed by a 2-way (treatment × time) mixed analysis of variance.

Results
As of May 6, 2021, 5 participants have been recruited for the study, and 3 have completed the rTMS protocol. The estimated completion date of the trial is May 2022.

Conclusions
This trial will expand our knowledge of how rTMS can be used as a treatment option of PPCS and will explore the neuropathophysiological response of rTMS through fNIRS analysis.

Trial Registration
ClinicalTrials.gov NCT04568369; https://clinicaltrials.gov/ct2/show/NCT04568369

International Registered Report Identifier (IRRID)
DERR1-10.2196/31308
Intent to Change Sun-Protective Behaviors Among Hispanic People After a UV Photoaging Intervention: Cohort Study
Authors: Bonnell Levi N , Obi Ngozi , Miller Kimberly , Hu Sophia , Dellavalle Robert , Cockburn Myles 
Published: January 2022

Background
Mortality rates from melanoma are higher among Hispanic populations than non-Hispanic White (NHW) populations. Interventions to improve sun safety are needed. The Reveal Imager is a camera that uses standard cross-polarized flash photography to record surface and subsurface skin conditions.

Objective
This study aims to determine the intervention’s effectiveness in increasing awareness of sun damage and exposure reduction between Hispanic and NHW populations.

Methods
A cohort of 322 participants, aged ≥18 years, were recruited from community events in 2018. Baseline information was collected on demographics, sun exposure, and perception of risk factors. A facial image was then captured using the Reveal Imager. The results were explained and counseling on sun safety was given, followed by filling out an immediate postimage survey. Chi-square tests, analysis of variance, Wilcoxon signed-rank test, McNemar tests, and multivariable logistic regression were used.

Results
At follow-up, 125 of 141 (89%) Hispanic participants reported that viewing the UV photoaged image influenced intent-to-change sun protection behaviors, compared to 88 of 121 (73%) NHW participants (odds ratio 2.9, 95% CI 1.5-5.6). Of 141 Hispanic participants, 96 (68%) reported that they intended to increase sunscreen use, compared to only 41 of 121 (34%) NHW participants (P<.001).

Conclusions
We demonstrated an application of Reveal Imager for education and risk assessment. The Reveal Imager was especially helpful in motivating intention to change sun exposure among Hispanic populations.
Active Use and Engagement in an mHealth Initiative Among Young Men With Obesity: Mixed Methods Study
Authors: Gorny Alexander Wilhelm , Chee Wei Chian Douglas , Müller-Riemenschneider Falk 
Published: January 2022

Background
The effectiveness of mobile health (mHealth) approaches that employ wearable technology to promote physical activity have been the subject of concern due to the declining active use observed in trial settings.

Objective
To better contextualize active use, this study aimed to identify the barriers and enablers to engagement in a tracker-based mHealth initiative among young men who had recently completed a 19-week residential weight loss program.

Methods
A mixed methods study was conducted among 167 young men who had voluntarily enrolled in the national steps challenge (NSC), an mHealth physical activity promotion initiative, following a residential weight loss intervention. A subsample of 29 enrollees with a body mass index of 29.6 (SD 3.1) participated in semistructured interviews and additional follow-up assessments. Quantitative systems data on daily step count rates were used to describe active use. Qualitative data were coded and analyzed to elicit barriers and enablers to microlevel engagement in relation to the NSC, focusing on tracker and smartphone use. We further elicited barriers and enablers to macrolevel engagement by exploring attitudes and behaviors toward the NSC. Using triangulation, we examined how qualitative engagement in the NSC could account for quantitative findings on active use. Using integration of findings, we discussed how the mHealth intervention might have changed physical activity behavior.

Results
Among the 167 original enrollees, active use declined from 72 (47%) in week 1 to 27 (17%) in week 21. Mean daily step counts peaked in week 1 at 10,576 steps per day and were variable throughout the NSC. Barriers to engagement had occurred in the form of technical issues leading to abandonment, device switching, and offline tracking. Passive attitudes toward step counting and disinterest in the rewards had also prevented deeper engagement. Enablers of engagement included self-monitoring and coaching features, while system targets and the implicit prospect of reward had fostered new physical activity behaviors.

Conclusions
Our study showed that as the NSC is implemented in this population, more emphasis should be placed on technical support and personalized activity targets to promote lasting behavior change.
Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study
Authors: Chi Nathan A , Washington Peter , Kline Aaron , Husic Arman , Hou Cathy , He Chloe , Dunlap Kaitlyn , Wall Dennis P 
Published: January 2022

Background
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that results in altered behavior, social development, and communication patterns. In recent years, autism prevalence has tripled, with 1 in 44 children now affected. Given that traditional diagnosis is a lengthy, labor-intensive process that requires the work of trained physicians, significant attention has been given to developing systems that automatically detect autism. We work toward this goal by analyzing audio data, as prosody abnormalities are a signal of autism, with affected children displaying speech idiosyncrasies such as echolalia, monotonous intonation, atypical pitch, and irregular linguistic stress patterns.

Objective
We aimed to test the ability for machine learning approaches to aid in detection of autism in self-recorded speech audio captured from children with ASD and neurotypical (NT) children in their home environments.

Methods
We considered three methods to detect autism in child speech: (1) random forests trained on extracted audio features (including Mel-frequency cepstral coefficients); (2) convolutional neural networks trained on spectrograms; and (3) fine-tuned wav2vec 2.0—a state-of-the-art transformer-based speech recognition model. We trained our classifiers on our novel data set of cellphone-recorded child speech audio curated from the Guess What? mobile game, an app designed to crowdsource videos of children with ASD and NT children in a natural home environment.

Results
The random forest classifier achieved 70% accuracy, the fine-tuned wav2vec 2.0 model achieved 77% accuracy, and the convolutional neural network achieved 79% accuracy when classifying children’s audio as either ASD or NT. We used 5-fold cross-validation to evaluate model performance.

Conclusions
Our models were able to predict autism status when trained on a varied selection of home audio clips with inconsistent recording qualities, which may be more representative of real-world conditions. The results demonstrate that machine learning methods offer promise in detecting autism automatically from speech without specialized equipment.
Utilidad de la elastografía cuantitativa por ultrasonografía endoscópica (USE), para el diagnóstico de las lesiones sólidas del páncreas (LSP).
Authors: Gómez Zuleta Martín Alonso , Ruíz Morales Oscar Fernando , Cano Rosales Diego Fernando 
Published: January 2022

Introducción: la punción con aguja fina guiada por ultrasonografía endoscópica (PAF-USE) permite un diagnóstico de las lesiones sólidas del páncreas (LSP) con una sensibilidad de alrededor del 85 % en la literatura mundial y aún más baja en nuestro medio, por lo cual se requiere explorar nuevos accesorios (agujas) o técnicas tales como la elastografía, que mejoren esta sensibilidad. Esta última permite la cuantificación de la rigidez del tejido con altos grados de precisión y desde 2001 se ha aplicado al diagnóstico de tumores sólidos de diversos órganos como mama y tiroides, músculo, entre otros; y desde 2006 se ha empleado para las LSP y ha demostrado su utilidad como complemento a las herramientas diagnósticas disponibles, ya que mejora la precisión de la biopsia por PAF-USE al seleccionar el área más sospechosa para ser puncionada y también guía el manejo clínico cuando la PAF-USE es negativa o no concluyente.
Objetivo: evaluar el rendimiento diagnóstico de la elastografía cuantitativa de strain ratio (SR) obtenida por ecoendoscopia en las lesiones sólidas pancreáticas teniendo como patrón de oro el diagnóstico citopatológico.
Métodos: 71 pacientes (rango de edad: 35-89, media: 62,2 años); de estos, 35 mujeres fueron sometidas a USE para la evaluación de LSP. El diseño del estudio fue de corte transversal, prospectivo y de un solo centro. La USE se realizó con un ecoendoscopio Pentax lineal y un procesador Hitachi-Noblus. La lesión (área A) y un área de referencia B se seleccionaron para calcular la relación de deformación (B/A, SR expresada en %). Se tomó como punto de corte SR para definir las lesiones malignas (duras) SR > 22 teniendo en cuenta la evidencia actualmente disponible; estos resultados se compararon con la citopatología de las muestras obtenidas por punción guiada por USE. Después de la aplicación de criterios de exclusión, se realiza el análisis estadístico de 56 pacientes y se considera el valor p < 0,05. Se calculó la sensibilidad, especificidad, valor predictivo positivo (VPP), valor predictivo negativo (VPN) y precisión diagnóstica comparando la elastografía SR con los diagnósticos finales por citopatología.
Resultados: la elastografía cuantitativa SR (%) permite detectar las LSP malignas con sensibilidad del 94,6 % (intervalo de confianza [IC] del 95 %: 85,4 %-98,2 %), especificidad del 89,3 % (IC 95 %: 78,5 %-95,0 %), VPP del 89,8 % (IC 95 %: 79,5 %-95,3 %); VPN del 94,3 % (IC 95 %: 84,6 %-98,1 %) y exactitud del 92,0 % (IC 95 %: 85,4 %-95,7 %).
Conclusión: la elastografía cuantitativa SR por USE en LSP es un complemento útil que mejora la precisión de la PAF-USE al seleccionar el área más sospechosa para ser puncionada y guiar el manejo clínico cuando la PAF-USE es negativa o no concluyente, ya que tiene una alta sensibilidad y especificad en el diagnóstico de las LSP malignas.
Pengaruh Kemampuan Kerja Dan Kepuasan Kerja Terhadap Kinerja Karyawan Pada Perusahaan Daerah (PD) Pasar Kabupaten Buleleng
Authors: Audry Efendy Shima , Suarmanayasa I Nengah 
Published: January 2022

This study aims to examine the effects of: (1) job ability and job satisfaction on employee performance, (2) work ability on employee performance, (3) job satisfaction on employee performance and (4) job ability on job satisfaction at Perusahaan Daerah (PD) Pasar Kabupaten Buleleng. The research design used in this research is causal quantitative. The object of this research were job ability, job satisfaction and employee performance. The research subjects were all employees of Perusahaan Daerah (PD) Pasar Kabupaten Buleleng with a population of 32 people. The data collected by the method of recording documents and questionnaires. The analysis technique is used by path analysis. The results showed that: (1) job ability and job satisfaction has a positive and significant effect on employee performance (2) job ability has a positive and significant effect on employee performance, (3) job satisfaction has a positive and significant effect on employee performance and (4) ability work has a positive and significant effect on job satisfaction at Perusahaan Daerah (PD) Pasar Kabupaten Buleleng
Clustering Penyakit DBD pada Rumah Sakit Dharma Kerti Menggunakan Algoritma K-Means
Authors: Adiputra I Nyoman Mahayasa 
Published: January 2022

Clustering merupakan teknik pengelompokkan record pada basis data berdasarkan kriteria tertentu. Hasil clustering diberikan kepada pengguna akhir untuk memberikan gambaran tentang apa yang terjadi pada basis data. Dalam SIMRS Rumah Sakit Dharma Kerti yang diambil dari tahun 2014 sampai 2018, memiliki 6038 record data rekam medis pasien. Jumlah diagnosa tertinggi adalah DBD, untuk mengetahui gambaran yang terjadi dalam data diagnosa DBD tersebut dilakukan clustering dengan menggunakan algoritma k-means. Hasil dari penelitian ini adalah Pasien dengan diagnosa DBD pada RS Dharma Kerti yang paling sedikit jumlahnya adalah pada rentang usia 25 sampai 45 tahun. Setiap kelompok usia memiliki jumlah hari perawatan yang merata, bisa disimpulkan bahwa usia hampir tidak mempengaruhi hari perawatan. Lama perawatan yang paling banyak di lalui oleh pasien adalah dari 3 hari sampai 5 hari perawatan.
Pengaruh Ukuran Perusahaan Dan Profitabilitas Terhadap Struktur Modal Perusahaan Manufaktur Subsektor Makanan Dan Minuman Yang Terdaftar Di Bursa Efek Indonesia
Authors: Saputra Ferry Dhita , Suarmanayasa I Nengah 
Published: January 2022

This research intended to examine the effect of company size and profitability on the capital structure in companies manufacture sub-sector food and beverage at Indonesian stocks exchange. The research design used was causal quantitative research. The subject on this research are companies manufacture sub-sector food and beverage at Indonesian stocks exchange,and object on this research are company size and profitability. Data collected by document recording and data analysis technique used was multiple linear regression analysis. The results of this study are: (1) company size and profitability has significant effect on the capital structure. (2) company size has a significant and positive effect on the capital. (3) profitability has a significant and positive effect on the capital structure in companies manufacture sub-sector food and beverage at Indonesian stocks exchange.Keywords: Company Size, Profitability,Capital Structure
Kepatuhan Wajib Pajak Orang Pribadi Usaha Mikro, Kecil, Dan Menengah Ditinjau Dari Tarif Pajak, Sosialisasi Pajak, Sanksi Pajak, Dan Pemeriksaan Pajak
Authors: Yogantara Komang Krishna , Asana Gde Herry Sugiarto , Clarissa Sarita Vania 
Published: January 2022

Tax has an important role in the economy as the largest source of government funding in carrying out the task of realizing the prosperity of the people. Micro, Small and Medium Enterprises (MSMEs) are one of the sectors that have the potential to contribute large tax payments to state tax revenues. However, the compliance of personal taxpayer of MSMEs still low, especially the compliance of personal taxpayers who are registered in Pratama Tax Office Gianyar has not reached the target of 70 percent. This study aims to determine the influence of the tax rate, tax socialization, tax sanction, and tax investigation toward the obedience of personal taxpayer of Micro, Small, and Medium Enterprises (MSMEs) at the Pratama Tax Office (KPP) Gianyar. Total of 100 MSMEs personal taxpayers that registered at Pratama Tax Office (KPP) Gianyar were selected to be respondents using the Slovin Formula. The research method that used was accidental sampling with media questionnaires and the technical of analysis data of this study is using multiple linear regression. The conclusion of this study indicate that the tax rate, tax socialization, tax sanction, and tax investigation have positive and significant influence on the obedience of personal taxpayer of MSMEs at Pratama Tax Office (KPP) Gianyar.Keywords: Tax rate, tax socialization, tax sanction, tax investigation
PENINGKATAN PENGELOLAAN MANAJEMEN KELOMPOK SIMPAN PINJAM DESA GAMBIRAN KECAMATAN PAMOTAN KABUPATEN REMBANG
Authors: Alliyah Siti - 
Published: January 2022

Salah satu desa di Kabupaten Rembang yang masuk kategori merah/ desa dengan kategori miskin, salah satu diantaranya Desa Gambiran Kecamatan Pamotan. Rendahnya tingkat pendidikan menyebabkan kualitas sumber daya manusia relatif rendah. Program pengembangan Desa Gambiran untuk peningkatan PAD diupayakan dari berbagai aspek program. Salah satunya adalah pengelolaan simpan pinjam yang dikelola oleh ibu-ibu PKK, dengan anggota kelompok sejumlah 10 orang. Kelompok usaha simpan pinjam secara kelembagaan belum memiliki nama, akan tetapi struktur pengurus sudah terbentuk, dengan ketua Ibu Qoryati. Permasalahan yang dihadapi oleh kelompok usaha ini dintaranya adalah rendahnya kemampuan pengelolaan manajemen usaha, Hal ini dikarenakan sebagian besar pengurus berpendidikan lulusan SLTP dan hanya 1 (satu) pengurus yang bergelar sarjana. Kegiatan pelatihan dan pendampingan keuangan dan laporan keuangan telah menjadi solusi dalam menyelesaikan permsalahan tersebut. Setelah dilaksanakan kegiatan pelatihan dan pendampingan, kelompok simpan pinjam saat ini telah melakukan proses administrasi keuangan dan laporan keuangan.