bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing patient experience and attitude: BSC-PATIENT development, translation, and psychometric evaluation - a cross-sectional study
Authors: Amer Faten , Hammoud Sahar , Onchonga David , Alkaiyat Abdulsalam , Nour Abdulnaser , Boncz Imre , Endrei Dóra 
Published: January 2022

Abstract
Background
Improving the healthcare sector in Palestinian territories is challenging. Organizations frequently use the balanced scorecard (BSC) for performance evaluation (PE) worldwide. BSC includes an evaluation of five perspectives: financial, customer, internal process, knowledge and innovation, and environmental. Most HealthCare Organizations (HCO) evaluated patient satisfaction in BSC, but none considered engaging patients in the evaluation process. This paper aims to develop an instrument to engage patients in assessing BSC perspectives (BSC-PATIENT) and customize it for Palestinian hospitals.
Methods
This is a cross-sectional study. Two panels of experts participated in the item generation of BSC-PATIENT. Forward and backward translation processes from English to Arabic and vice versa were performed. Pretesting was performed for 30 patients at one hospital. Then, 1000 patients were recruited at 14 hospitals between January and October 2021. Construct validity was tested through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Additionally, the composite reliability (CR), interitem correlation (IIC), and corrected item total correlation (CITC) were assessed to find redundant and low correlated items.
Results
The scales had high adequate model fit in EFA and CFA. All items included had loadings higher than 0.50. Although the convergent validity was less than 0.50 for some constructs, their discriminant validity, CR, IIC, and CITC showed satisfactory results except the services experience (SERV EXR) construct, which had a CR of 0.50. The final best fit model in CFA comprised ten constructs with 34 items.
Conclusion
BSC-PATIENT is the first self-administered questionnaire specially developed to engage patients in evaluating their experiences and attitudes based on the BSC perspectives. The questionnaire scales were carried out following relevant guidelines and regulations. The results showed adequacy in the psychometric properties of this instrument. Three-point Likert scales are recommended to assess patient experiences and attitudes since they have higher response rates. Future research can be conducted using this instrument to evaluate the impact of patient experience on attitudes toward BSC perspectives and compare the differences based on patient and hospital characteristics.
Qualitative Interviews Exploring the Views of Healthcare Professionals Working in a Mental Health Trust in England on Pharmacists as Future Approved Clinicians
Authors: Adam Balazs , Keers Richard 
Published: January 2022

Abstract
BackgroundThe Mental Health Act 1983 was amended in 2007 introducing the role of the Approved Clinician (AC) which could be assumed by individuals from several professional groups. Although the role of mental health pharmacists have undergone significant transformation over the past few decades, pharmacists remain ineligible to train and practise as an AC. There is a paucity of research on non-medical ACs and there are currently no known studies exploring the potential of mental health pharmacists to be considered for the role of AC in future.AimThis qualitative research explored the views and attitudes of a range of healthcare professionals towards the role of the mental health pharmacist, and whether they could and/or should be enabled, via a legislative change, to become ACs in the future.MethodRecruitment based on systematic purposive sampling principles took place at one mental health trust in England. Six pharmacists, five medical ACs and two experienced mental health nurses participated in digitally audio-recorded semi-structured interviews between June-November 2020. The recordings were transcribed verbatim before being inductively coded and thematically analysed.ResultsNotwithstanding the wide recognition among participants of several key skills possessed by mental health pharmacists, various obstacles were also identified to their becoming ACs in future, including prevalent conventional models of pharmacy services delivery restricting adequate patient access, as well as insufficient training opportunities to acquire advanced clinical skills particularly in diagnosis and assessment. Participants also highlighted wider concerns with current uptake of the non-medical AC role which could influence the success of pharmacists’ involvement, including legislative restrictions and a lack of perceived training support.ConclusionChanges to the skill mix within multidisciplinary mental health teams as well as to the training of staff may be required to equip pharmacists with essential skills to be able to transition towards the AC role. Further research is required to gain a better understanding of the challenges facing the clinical development and enhanced utilisation of highly specialised mental health pharmacists across services.
Evaluation of CMIP6 Climate Models for Climate Change Impact Assessments in Upper Awash Basin, Ethiopia
Authors: Gebresellase Selamawit Haftu , Wu Zhiyong , Xu Huating , Wada Idris Muhammad 
Published: January 2022

Abstract

Identifying GCMs that represent the climate of a specific area is crucial for climate change studies. However, the uncertainties in GCMs caused by computational constraints, such as coarser resolution, physical parameterizations, initializations, and model structures, make it imperative to identify a representative individual or group of GCM for a climate impact study. An advanced envelope-based multi-criteria selection approach was used to identify a subset of the most appropriate future GCMs in the Upper Awash Basin. The skill accounting is based on (1) the range of projected mean changes of climate variables, (2) range of variability in climate extremes and, (3) model run performance to represent historical climate data. Statistical downscaling and bias correction were made for the selected model runs. The downscaled and bias-corrected monthly values for precipitation are expected to increase from 0.42% to 2.82% in mid-century and 0.15% to 3.79% by the end century considering the SSP4.5 scenario. For SSP8.5, it increases from 1.45% to 5.51% and 2.57% to 9.78% in the respective periods. Likewise, under the SSP4.5 forcing scenario, the monthly average air temperature projected to be warmer, which increased from 0.68°C to 1.55°C during mid-century and 0.09°C to 1.92°C end-of-century. Meanwhile, for SSP8.5, the projection indicates an increment of 0.19°C to 1.98°C under mid-century and 2.37°C to 7.00°C end-century. The projected change of future precipitation and temperature in the study basin increases the precipitation intensities, wet days and dry spells due to high-temperature increment.
The COVID-19 Hospitalization Metric in the Pre- and Post-vaccination Eras as a Measure of Pandemic Severity: A Retrospective, Nationwide Cohort Study
Authors: Fillmore Nathanael , La Jennifer , Zheng Chunlei , Doron Shira , Do Nhan , Monach Paul , Branch-Elliman Westyn 
Published: January 2022

Abstract

Background: COVID-19 hospitalization definitions do not include a disease severity assessment. Thus, we sought to identify a simple and objective mechanism for identifying hospitalized severe cases and to measure the impact of vaccination on trends.Methods: All admissions to a Veterans Affairs (VA) hospital, where routine screening is recommended, between 3/1/2020-11/22/2021 with SARS-CoV-2 were included. Moderate-to-severe COVID-19 was defined as any oxygen supplementation or any SpO2 <94% between one day before and two weeks after the positive SARS-CoV-2 test. Admissions with moderate-to-severe disease were divided by the total number of admissions, and the proportion of admissions with moderate-to-severe COVID-19 was modelled using a penalized spline in a Poisson regression and stratified by vaccination status. Dexamethasone receipt and its correlation with moderate-to-severe cases was also assessed. Results: Among 67,025 admissions with SARS-CoV-2, the proportion with hypoxemia or supplemental oxygen fell from 64% prior to vaccine availability to 56% by November 2021, driven in part by lower rates in vaccinated patients (vaccinated, 52% versus unvaccinated, 58%). The proportion of cases of moderate-to-severe disease identified using SpO2 levels and oxygen supplementation was highly correlated with dexamethasone receipt (correlation coefficient, 0.95), and increased after 7/1/2021, concurrent with delta variant predominance.Conclusions: A simple and objective definition of COVID-19 hospitalizations using SpO2 levels and oxygen supplementation can be used to track pandemic severity. This metric could be used to identify risk factors for severe breakthrough infections, to guide clinical treatment algorithms, and to detect trends in changes in vaccine effectiveness over time and against new variants.
Meta-analysis of the Effectiveness of Steroid Pulse Therapy in Treating Patients with Spinal Cord Injury
Authors: Kim Sanghee 
Published: January 2022

Background:
High-dose steroid injection therapy is effective in reducing anti-inflammation and edema and is often used to treat patients with acute spinal cord injury. To evaluate the effectiveness of steroid pulse therapy and identify the factors that affect its effectiveness in patients with acute traumatic spinal cord injury.

Methods:
A comprehensive literature search of the databases Pubmed, Medline, the Cochrane Central Register of Controlled Trials, Embase, and CINAHL was performed on July 31, 2019, with no language and time limits. For analysis, studies conducted within the last 10 years were included to reflect on the recent trend.

Results:
A total of 3 randomized controlled trials and 5 observational studies with 2418 patients were included in this meta-analysis. High-dose steroid injection therapy was found to have a high effect on patients with acute spinal cord injury. The following factors had a strong influence on the effectiveness of high-dose steroid treatment in patients with acute spinal cord injuries: injury, onset ASIA, onset neurological assessment scales, time to start treatment after injury, age, BMI, and gender.

Conclusion:
It is necessary to accurately assess the scope of spinal injury in the early stages and actively provide nursing interventions to identify and mediate factors affecting the treatment effect.
Characterizing Use of a Multicomponent Digital Intervention to Predict Treatment Outcomes in First-Episode Psychosis: Cluster Analysis
Authors: O'Sullivan Shaunagh , Schmaal Lianne , D'Alfonso Simon , Toenders Yara Jo , Valentine Lee , McEnery Carla , Bendall Sarah , Nelson Barnaby , Gleeson John F , Alvarez-Jimenez Mario 
Published: January 2022

Background
Multicomponent digital interventions offer the potential for tailored and flexible interventions that aim to address high attrition rates and increase engagement, an area of concern in digital mental health. However, increased flexibility in use makes it difficult to determine which components lead to improved treatment outcomes.

Objective
This study aims to identify user profiles on Horyzons, an 18-month digital relapse prevention intervention for first-episode psychosis that incorporates therapeutic content and social networking, along with clinical, vocational, and peer support, and to examine the predictive value of these user profiles for treatment outcomes. A secondary objective is to compare each user profile with young people receiving treatment as usual (TAU).

Methods
Participants comprised 82 young people (aged 16-27 years) with access to Horyzons and 84 receiving TAU, recovering from first-episode psychosis. In addition, 6-month use data from the therapy and social networking components of Horyzons were used as features for K-means clustering for joint trajectories to identify user profiles. Social functioning, psychotic symptoms, depression, and anxiety were assessed at baseline and 6-month follow-up. General linear mixed models were used to examine the predictive value of user profiles for treatment outcomes and between each user profile with TAU.

Results
A total of 3 user profiles were identified based on the following system use metrics: low use, maintained use of social components, and maintained use of both therapy and social components. The maintained therapy and social group showed improvements in social functioning (F2,51=3.58; P=.04), negative symptoms (F2,51=4.45; P=.02), and overall psychiatric symptom severity (F2,50=3.23; P=.048) compared with the other user profiles. This group also showed improvements in social functioning (F1,62=4.68; P=.03), negative symptoms (F1,62=14.61; P<.001), and overall psychiatric symptom severity (F1,63=5.66; P=.02) compared with the TAU group. Conversely, the maintained social group showed increases in anxiety compared with the TAU group (F1,57=7.65; P=.008). No differences were found between the low use group and the TAU group on treatment outcomes.

Conclusions
Continued engagement with both therapy and social components might be key in achieving long-term recovery. Maintained social use and low use outcomes were broadly comparable with TAU, emphasizing the importance of maintaining engagement for improved treatment outcomes. Although the social network may be a key ingredient to increase sustained engagement, as users engaged with this more consistently, it should be leveraged as a tool to engage young people with therapeutic content to bring about social and clinical benefits.
A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator: Longitudinal Study
Authors: van der Ploeg Tjeerd , Gobbens Robbert 
Published: January 2022

Background
Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques.

Objective
In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty.

Methods
We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping.

Results
We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable “difficulty in walking” was important for all models.

Conclusions
Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of “gender” and “age” variables. External validation is a necessary step before applying the prediction models in a new setting.
Application and evaluation of the technical condition of composite materials in aircraft and unmanned aerial vehicles by acoustic emission method of nondestructive testing
Authors: Popov A. V. , Samuylov A. O. , Cherepanov I. S. 
Published: January 2022

Introduction. The paper analyzes the application of composite materials as the main determining method of reducing the mass of the airframe and an unmanned aerial vehicle. Advanced nondestructive testing methods provide assessing the technical condition of these materials, as well as determining stress concentrators on the airframe and an unmanned aerial vehicle with high accuracy in order to make a decision on the further operation of this object under control. The objective of the work was to increase the accuracy and efficiency of the assessment of crack resistance of composite materials through the acoustic emission control.Materials and Methods. This paper presents the nomenclature of composite materials used in the construction of various aircraft, including unmanned aerial vehicles. The most possible probable defects of these materials due to the influence of operational factors are presented. The applied methods of nondestructive testing of composite material and selection of the most suitable one according to specific advantages were compared. An experiment was carried out to determine the strength limits of carbon fiber using a hardware and software complex by acoustic emission method. The research results are presented in the form of drawings projected by the hardware and software complex.Results. The application of the acoustic-emission method of composite material control is described.Discussion and Conclusions. The results obtained experimentally can be used in the process of determining the strength limits of various composite materials by the acoustic emission method of nondestructive testing to assess the technical condition in mechanical engineering, shipbuilding, and aircraft construction. The paper is recommended to researchers involved in the design of aircraft and unmanned aerial vehicles.
METODE REGRESI LINIER UNTUK PREDIKSI KEBUTUHAN ENERGI LISTRIK JANGKA PANJANG (STUDI KASUS PROVINSI LAMPUNG)
Authors: Syafruddin M. , Hakim Lukmanul , Despa Dikpride 
Published: January 2022

Abstrak— Meningkatnya pembangunan di Provinsi Lampung terutama di sektor perumahanbaik sederhana maupun rumah mewah yang membawa konsekuensi logis berupapeningkatan kebutuhan tenaga listrik. Sebuah studi komprehensif dalam rangkapenyedian tenaga listrik di Lampung menjadi kebutuhan yang mendesakdilakukan untuk membuat rencana operasi sistem tenaga listrik. Salah satu faktoryang sangat menentukan dalam membuat rencana operasi sistem tenaga listriktersebut adalah prediksi beban listrik yang akan ditanggung oleh sistem tenagalistik yang bersangkutan. Penelitian ini bertujuan untuk memprediksi kebutuhan energi listrik di Provinsi Lampung hingga Tahun 2030, diharapkan dapatdijadikan sebagai masukkan dalam melakukan perencanaan pembangunan sistemtenaga listrik. Prediksi kebutuhan energi listrik Lampung dibagi menjadi 4 sektoryaitu : sektor rumah tangga, bisnis, publik, dan industri. Proses perancanganprediksi kebutuhan energi listrik menggunakan 6 variabel dan dibagi menjadi 2 parameter, yaitu: parameter ekonomi (produk domestik regional bruto, jumlahpenduduk, jumlah rumah tangga) dan parameter listrik (rasio elektrifikasi, faktor beban, losses). Dengan menggunakan metode regresi linier untuk memprediksivariabel-variabel di atas, diperoleh hasil prediksi daya listrik tersambung totalpada tahun 2028 sebesar 2.841,78 MVA (rata-rata pertumbuhannya sebesar 2,38 %), dan konsumsi energi listrik pada tahun 2023 sebesar 5.934,98 Gwh (rata-rata pertumbuhannya sebesar 3, 83 %). Kata Kunci —regresi linier, konsumsi energi listrik, Provinsi Lampung. Abstract The Increasing of property development in Lampung Province, especially in thehousing sector both simple and luxurious brings a logical consequence ofelectricity demand. A comprehensive study for electricity provisioning inLampung become requirement constrain. Electrical load forecasting is one of theimportant factors is power system planning and making. Prediction of electricityconsumption there are for activity that need to be predicted i.e.: households,businesses, public services, and industry. 6 variables include are considered grossregional domestic product, population, number of households, electrification ratio,load factor, losses are considered to be influencing the forecasting proses. Linearregression method was used to predict all variables. The result of total electricitypower connected prediction on 2028 is 2841.78 MVA (growth average at of 2,38%). And electricity consumption prediction on 2023 is 5934.98 Gwh (growthaverage at 3, 83%). Keywords—linier regression, electricity consumption, Lampung Province.
Dynamic Spectrum Access (Dsa) Dengan Mekanisme Spectrum Sensing Berbasis Pendeteksian Kanal Dan Bandwidth Untuk Efisiensi Spektrum
Authors: Muthmainah Maria Ulfa , Ulvan Ardian , Septama Hery Dian 
Published: January 2022

Abstrak – Perkembangan teknologi yang semakin pesat dan bertambahnya permintaan akses layananyang semakin cepat menyebabkan kebutuhan spektrum meningkat. Pada mekanisme Static SpectrumAccess (SSA) meningkatnya kebutuhan spektrum tidak diimbangi dengan alokasi spektrum yang adasehingga terdapat kanal yang tidak digunakan (idle) yang menyebabkan spektrum perlu diefisiensikan.Cara untuk mengelola spektrum agar lebih efisien dapat dilakukan dengan prinsip Dynamic SpectrumAccess (DSA). Mekanisme spectrum sensing berbasis pendeteksian kanal dan bandwidth menjadibahasan dalam penelitian ini. Pada penelitian ini penentuan kanal idle ditentukan dengan algoritmapendeteksian kanal dan bandwidth. Perhitungan dilakukan dengan menghitung parameter pendeteksianyaitu daya transmit. Besar daya threshold (Pth) dibandingkan dengan besar daya noise (Pnoise). Jikadaya threshold lebih besar dari daya noise (Pth > Pnoise) maka kanal idle dinyatakan terdeteksi,sementara sebaliknya kanal idle tidak terdeteksi. Hasil perhitungan menunjukkan bahwa kanal idleterdeteksi pada keseluruhan bandwidth apabila user lain terdeteksi dengan bit rate yang rendah.Bandwidth 5 MHz memiliki ketersedian kanal idle lebih besar dibandingkan 3 MHz, dan 1,4 MHz.Dengan terdeteksinya kanal idle pada suatu bandwidth menjadikan penggunaan spektrum denganmekanisme spectrum sensing menjadi efisien. Jarak maksimum user untuk dapat melakukanpendeteksian kanal idle sejauh 250 meter (n=3) dan 15 meter (n=4). Kata kunci - efisiensi spektrum, DSA, kanal idle, spectrum sensing.
Penempatan SVC (Static Var Compensator) Untuk Memperbaiki Profil Tegangan Pada Jaringan Transmisi PT. PLN Lampung
Authors: Wiguna B Arya , Despa Dikpride , Gusmedi Herri , Haris Abdul 
Published: January 2022

Abstrak – Sistem kelistrikan merupakan salah satu kebutuhan bagi kehidupan masyarakat modern dalam mendukung keberlangsungan aktifitas masyarakat. Peningkatan beban pada sistem tenaga listrik dapat menimbulkan jatuh tegangan dan nilai rugi daya yang besar. Dalam tugas akhir ini digunakan SVC (Static Var Compensator) yang merupakan salah satu FACTS devices, yang berfungsi menyerap atau menginjeksikan daya reaktif untuk memperbaiki profil tegangan pada sistem transmisi. Tugas akhir ini adalah studi kasus yang diterapkan pada saluran transmisi PLN 24 bus wilayah Lampung dengan menggunakan metode Newton-Raphson pada simulasi MATLAB. Hasil penelitian menunjukkan bahwa dengan menerapkan SVC pada weak bus pada sistem transmisi maka profil tegangan dapat diperbaiki dalam batas yang diizinkan. Penempatan SVC pada weak bus 7 (Manggala) memperbaiki profil tegangan pada weak bus 7 (Manggala) dan bus 8 (Gumawang) naik sebesar 1.35% dan 1.45% dari 0.9283p.u dan 0.9012p.u menjadi 0.941p.u dan 0.9145p.u, penempatan SVC pada weak bus bus 8 (Gumawang) memperbaiki profil tegangan pada weak bus 7 (Manggala) dan bus 8 (Gumawang) naik sebesar 6.18% dan 9,88% dari 0.9283p.u dan 0.9012p.u menjadi 0.9895p.u dan 1p.u. Kata kunci : SVC (Static Var Compensator), Flexible AC Transmission Systems (FACTS), Metode Newton-Raphson, Perbaikan Profil Tegangan, Transmisi PLN Lampung