bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing professionalism - progressing the career development sector
Authors: Johnson Claire , Neary Siobhan
Published: May 2022

Much has changed in the career development sector since the launch of the Careers Profession Task Force report, 'Towards a Strong Careers Profession' in 20 IO. The report made recommendations for enhancing the professionalism of the career sector including the establishment of an overarching professional body, new qualification levels and common professional standards. The Careers Profession Alliance (CPA) and then the Career Development Institute (COl), launched in April 2013 have striven to facilitate the sector to be stronger and more cohesive by addressing these recommendations. This article explores what was needed, what has been achievedand plans for the future.
Overview of this issue
Authors: Robertson Pete
Published: May 2022

Not available.
The impact of Covid-19 on career
Authors: Hooley Tristram
Published: May 2022

This article explores the experience of careering during and after the COVID-19 pandemic. Drawing on a wide range of recent research, it proposes a framework for understanding this experience which attends to its multi-scalar nature and to its temporality. The article provides an analysis which addresses the micro, meso and macro levels within which individuals’ careers take place. An argument is made that periods of crisis reorder our temporal experiences creating a new periodisation based on:

the immediate crisis period;
the subsequent period when restrictions are lifted and we return to the increasingly contested idea of ‘normal life’; and
the long-term as these repeated crises reorder our thinking and our society.

The framework is discussed primarily in reference to the experience of the first two years of the COVID-19 pandemic in the UK, which highlights the cyclical and ongoing nature of such crises.
‘How do I get hired?’ Early career individuals’ employment strategies during the COVID-19 pandemic
Authors: Parks-Yancy Rochelle , Cooley Delonia
Published: May 2022

The COVID-19 pandemic severely impacted the employment and career expectations of millions of Americans, including individuals in their early career stage. Instead of the robust labour market that was projected prior to the pandemic, this population faced layoffs, job offers rescinded, unemployment, and underemployment in 2020. Their job hunt strategies amidst the pandemic are an important topic of research inquiry. This qualitative study investigates respondents’ perspectives of online employment sites, social capital, and personal branding via social media as methods to obtain employment information and to get hired. The authors provide practical suggestions to enhance job seekers’ employment searches.
Decolonising career guidance: Experiences of female, BAME career guidance professionals through the lens of intersectionality theory
Authors: Ranavaya Vaidehi
Published: May 2022

This article explores a small-scale study on the experiences of female, BAME career guidance professionals in the workplace through the lens of intersectionality theory. Currently, there is a lack of literature on this highlighting the importance of researching this. The article starts with the introduction, rationale and significance of research into this area and the importance of decolonising methodology. The findings reveal perceptions of unfair treatment, stereotyping, unconscious bias, discrimination and more. They highlight how these experiences are woven together through intersectionality which can result in compounding challenges. This is then followed by recommendations.
Opportunities and risks in the use of AI in career development practice
Authors: Wilson Marianne , Robertson Peter , Cruickshank Peter , Gkatzia Dimitra
Published: May 2022

The Covid-19 pandemic required many aspects of life to move online. This accelerated a broader trend for increasing use of ICT and AI, with implications for both the world of work and career development. This article explores the potential benefits and challenges of including AI in career practice. It provides an overview of the technology, including current uses, to illustrate ways in which it could enhance existing services, and the attendant practical and ethical challenges posed. Finally, recommendations are provided for policy and practice that will support career development professionals in managing these risks and maximising benefits to service users.
TERAPAN TERAPI SABAR UNTUK MENGATASI STRES AKADEMIK DI KALANGAN REMAJA PADA MASA PANDEMI
Authors:   Program Studi Psikologi Universitas Islam Indonesia Sleman, Daerah Istimewa Yogyakarta, Indonesia, Qudsyi Hazhira , Nufus Salsabila Sajida ,   Program Studi Psikologi Universitas Islam Indonesia Sleman, Daerah Istimewa Yogyakarta, Indonesia, Paramesti Faza Azzahra ,   Program Studi Psikologi Universitas Islam Indonesia Sleman, Daerah Istimewa Yogyakarta, Indonesia, Geofany Nova ,   Program Studi Psikologi Universitas Islam Indonesia Sleman, Daerah Istimewa Yogyakarta, Indonesia, Ramadhani Adisty Frisca ,   Program Studi Psikologi Universitas Islam Indonesia Sleman, Daerah Istimewa Yogyakarta, Indonesia, Utami Siyoba Sabillah ,   Program Studi Psikologi Universitas Islam Indonesia Sleman, Daerah Istimewa Yogyakarta, Indonesia
Published: May 2022

Memasuki tahun kedua pandemi Covid-19 menyebabkan para remaja mengalami stres akademik. Stres akademik merupakan suatu gangguan yang penyebabnya merupakan tekanan dari kegiatan belajar. Penelitian ini diambil dengan menggunakan studi literatur dengan objek remaja. Stres akademik yang dialami remaja dapat diatasi dengan terapi sabar. Kata kunci: stres akademik, terapi sabar, remaja
BYPASSING PANDEMIC: SOFTWARE PROCESS STARTUP PADA MASA PANDEMI
Authors:   Informatika, Universitas Islam Indonesia Jl. Kaliurang Km. 14,5 Sleman Yogyakarta 55584, Pratama Muhammad Dimas , Suranto Beni ,   Informatika, Universitas Islam Indonesia Jl. Kaliurang Km. 14,5 Sleman Yogyakarta 55584, Mahardhika Galang Prihadi ,   Informatika, Universitas Islam Indonesia Jl. Kaliurang Km. 14,5 Sleman Yogyakarta 55584
Published: May 2022

Pada akhir tahun 2019, muncul wabah misterius di kota Wuhan, China dan menyebabkan pandemi di seluruh dunia. Virus yang akhirnya dinamakan COVID-19 dan menjadi pandemi COVID-19 dan ditetapkan menjadi pandemi serius. WHO sebagai badan kesehatan dunia menyarankan untuk negara-negara dunia melakukan lockdown agar menekan laju penyebaran pandemi COVID-19. Sudah hampir dua tahun berlalu sejak virus COVID-19 muncul dan menyebabkan kekacauan pada sektor perkenomian baik dari negara-negara yang membuat Kebijakan lockdown maupun negara yang terkena dampak langsung dari pandemi COVID-19. Salah satu sektor perekonomian yang terkena dampak pandemi dan menjadi fokus utama penelitian ini adalah sektor startup. Startup sendiri merupakan perusahaan rintisan yang bertujuan membuat produk atau jasa unik dan mendistribusikannya sesuai tujuan pasar dari startup itu sendiri. Pada makalah ini akan membahas dampak dari pandemi COVID-19 pada tiga startup yang berada di Indonesia dan satu startup Singapura dengan melihat pola kerja startup, teknik serta tools yang dipakai, dan strategi bisnis yang digunakan oleh startup untuk bertahan/survive pada masa pandemi. Hal tersebut akan dipakai untuk menarik kesimpulan dan diharapkan dapat membantu usaha startup dalam membuat strategi dalam menghadapi pandemi dan menentukan arah jalan startup serta untuk melihat kemampuan bertahan dalam masa pandemi. Kata kunci: COVID-19, Startup, Pandemi, Strategi, Survive.
Principal Component Analysis and Related Methods for Investigating the Dynamics of Biological Macromolecules
Authors: Kitao Akio
Published: May 2022

Principal component analysis (PCA) is used to reduce the dimensionalities of high dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods, and their applications for investigating protein dynamics.
Evaluation of Axial Compression Slenderness Limits of High and Very-High Strength Steel Circular Hollow Sections
Authors: Shaker Fattouh M. F. , Zarzor Kyrolos , Gaawan Sameh , Deifalla Ahmed , Pekcan Gokhan
Published: May 2022

Despite significant advances in metallurgy and the potential to create high and very high-strength steel, all international specifications for steel design provided little information about the limits of slenderness for high-strength steel sections (HSSs) and didn’t give anything about the design of very high-strength steel sections (VHSSs). The American structural steel design specification covers circular hollow sections (CHS) of steel grades up to S690, while it isn't in ANSI/AISC 360-16 and ASTM A514/A514M. Euro code EN 1993-1-1 can be applicable only to steel grades up to S460. EN 1993-1-3 and EN 1993-1-12 contain supplementary rules for cold-formed members and HSS (S460- S700), respectively. Though ductility requirements for (HSS) are specifically established in EN 1993-1-12, it is largely a continuation of the normal-strength-steel design procedures standardized in EN 1993-1-1, where (HSSs) are largely treated as normal-strength steels in these rules, and the same design approaches are used. The behavior of high and very high-strength steel circular hollow sections under axial compression load is studied in this research. A total of 16 nonlinear finite-element (FE) models were generated to replicate stub column tests that were experimentally tested by others in previous research. Hence, a parametric study is conducted using forty FE models developed to investigate the local buckling behavior under various slenderness ratios comprehensively. The developed models cover slenderness ratios ranging from 20 to 1226 and steel grades S460 and S1100 with yield stress equal 460 MPa and 1152 MPa, respectively. The FE results were combined with 105 previously collected experimental results to assess the applicability of existing codified design methodologies in the Euro code and the North American codes of cold-formed CHS. Based on the results of this study, new cross-sectional slenderness limits and new design equations for more efficient simple designs were presented for high and very-high strength steel circular hollow sections and Compared with the results of experimental tests and FE models.
New properties of an arithmetic function
Authors: Mittou Brahim
Published: May 2022

Recently the author and Derbal introduced and studied some elementary properties of arithmetic functions related the greatest common divisor. New properties of them are given in this paper.
BıGaussian Pell and Pell-Lucas polynomials
Authors: Özkan Engin , Alp Tuğba
Published: May 2022

In this paper, we define biGaussian Pell and Pell-Lucas Polynomials. We give Binet‘s formulas, generating functions, Catalan’s identities, Cassini’s identities for these polynomials. Matrix presentations of biGaussian Pell and Pell-Lucas polynomials are found. Also, NegabiGaussian Pell and Pell-Lucas Polynomials are defined. Finally, we give some properties for these polynomials.
On a sum over primitive sequences of finite degree
Authors: Laib Ilias , Rezzoug Nadir
Published: May 2022

A sequence of strictly positive integers is said to be primitive if none of its terms divides the others and is said to be homogeneous if the number of prime factors of its terms counted with multiplicity is constant. In this paper, we construct primitive sequences A of degree d, for which the Erdős’s analogous conjecture for translated sums is not satisfied.
The generalized bivariate Fibonacci and Lucas matrix polynomials
Authors: Yilmaz Nazmiye
Published: May 2022

The main object of the present paper is to consider the matrix polynomials for the generalized bivariate Fibonacci and Lucas polynomials. Working with matrix properties for these new matrix polynomials, some identities of the generalized bivariate Fibonacci and Lucas polynomials will be researched. Finally, we build the relationships between the generalized bivariate Fibonacci and Lucas matrix polynomials
Correct definition of internal energy at the phenomenological construction of model of multicomponent continuous medium by methods of nonequilibrium thermodynamics
Authors: Kolesnichenko Aleksandr Vladimirovich
Published: May 2022

Taking into account the methods of thermodynamics of irreversible processes using the Onsager principle, a model of a multicomponent continuous medium is constructed, the internal energy of which is "free" of the kinetic energy of diffusion. The model is designed for an imperfect continuous medium with chemical reactions in the field of conservative external forces. Generalized StefanMaxwell relations are obtained, which represent a system of hydrodynamic equations of motion of a mixture with true inertial forces. The proposed thermodynamic technique made it possible to obtain a number of algebraic relations known from the kinetic theory of gases for the transfer coefficients, relating, in particular, the coefficients of multicomponent diffusion with binary diffusivitys, thermal diffusion ratios with thermal diffusion coefficients and multicomponent diffusion coefficients, true (molecular) thermal conductivity coefficient for multicomponent mixture with partial thermal conductivity coefficient, which indicates their versatility. The results obtained are intended for modeling not only liquid imperfect solutions, but also gas-dust mixtures with a finely dispersed dust component.
Multigrid method for numerical modelling of high temperature superconductors
Authors: Feodoritova Olga Borisovna , Novikova Natalia Dmitrievna , Krasnov Mikhail Mikhailovich , Zhukov Victor Timofeevich
Published: May 2022

An approach to numerical simulation of three-dimensional electrical and thermal fields in high-temperature superconductors is described. In such a semiconductor, the phenomena of superconductivity are observed at high temperatures above the temperature of liquid nitrogen. The absence of a generally accepted theory of superconductivity leads to the need to study physical processes in semiconductor structures using mathematical simulations. The main attention is paid to the calculation of temperature and electric current distributions in large-size mesas with a self-heating effect. An efficient algorithm for solving the equations describing these distributions is constructed. The basis of the algorithm is an adaptive multigrid method on structured Cartesian grids. The adaptability is based on the Chebyshev iterative method for constructing the smoothing procedures at each grid level and for solving the coarsest grid equations. The adaptive technique allows us to realistically simulate the anisotropic phenomena. The functionality of the algorithm is demonstrated along with an example of solving an anisotropic model problem with discontinuous coefficients.
Molecular dynamics study of thermal hysteresis during melting-crystallization of noble metals
Authors: Mazhukin Vladimir Ivanovich , Koroleva Olga Nikolaevna , Shapranov Aleksandr Viktorovich , Aleksashkina Anna Andreevna , Demin Mikhail Mikhailovich
Published: May 2022

By constructing the thermal hysteresis of the enthalpy and density of the noble metals of gold (Au) and copper (Cu), non-equilibrium processes are investigated during the melting – crystallization phase transformations, i.e. during the solid–liquid transition. Thermal hysteresis is obtained from the atomistic modeling. The limiting temperatures of superheating of the solid phase during melting and undercooling of the liquid phase during crystallization of gold and copper are obtained. The possibility of the formation of highly superheated-undercooled metastable states of solid and liquid phases with rapid heating-cooling of the studied metals has been confirmed. The results obtained are compared with the results of alternative calculations.
Psycholinguistic dimensions of personal interaction between subjects of educational space in the context of the COVID-19 pandemic
Authors: Truba Hanna , Boyko Yuliya , Rakhimova Olga , Kambalova Yanina , Shevchuk Victoria
Published: May 2022

The study aimed to analyze the psycholinguistic dimension of the personal interaction of the subjects of the educational space in the conditions of the COVID-19 pandemic. For this purpose, a model was built to assess the influence of distance learning in an electronic environment or other unconscious forms on the effectiveness of school education. Through the study, the main factors influencing the effectiveness of learning at the school, class, and individual level (students, teachers, and parents) were identified and analyzed. A logical assessment framework model was created linking the resource provision of the educational distance process, organization and flow of learning processes, accessibility of the system of adaptation, and support for learning and achievement of results for students, teachers, parents, and school. The study provides an opportunity for a broader diagnosis of the effectiveness of education in the education system. It can facilitate data-driven decision-making to ensure adaptability and improve the effectiveness of the educational process to reduce inequality, ensure equal opportunities for quality education, ensure the sustainability of acquired knowledge and skills, and reduce the risk of dropping out of school in the context of the COVID-19 pandemic.
Vegetation and soil succession determine the water-use strategy ofCaragana korshinskiiin a chronosequence of revegetated areas in Ningxia, Northwest China
Authors: Lei Huang , Bo Wang , Jiajia Chen , Guisen Yang , Lichao Liu
Published: May 2022

Plant and soil properties and stable isotope data from soil and xylem samples of Caragana korshinskii from four different-aged revegetated sites (1976, 1987, 1996, and 2005) were studied in a desertified steppe ecosystem of Northwest China. Results showed that the revegetation of C. korshinskii had a positive effect on the local habitat restoration. The δ18O values of soil water at the four study sites varied between different months and exhibited a monotonic decline from the soil surface to deep soil layers. The variation of soil water δ18O values in the older revegetated sites was lower than that in the younger revegetated sites. C. korshinskii mainly tapped water from secondary (60–120 cm) and relatively stable (120–250 cm) soil water in the older revegetated site, and they had relatively slight monthly fluctuations. However, in the younger revegetated site, the contribution of active (0–60 cm) soil water increased, and they exhibited a clear shift in the water-use pattern. In the initial stage of vegetation establishment, soil water content played a major role in the plant water-use strategy, but in the middle and later stages of revegetation, plant biological characteristics and soil physical properties were the main impact factors.
Antifouling BaTiO3/PVDF piezoelectric membrane for ultrafiltration of oily bilge water
Authors: Tan Zhirong , Chen Shuiping , Mao Xin , Lv Heng , Wang Yong , Ye Xiaoqing
Published: May 2022

Barium titanate/polyvinylidene fluoride (BaTiO3/PVDF) piezoelectric membrane was successfully prepared and generated in-situ vibrations to reduce membrane fouling by applying alternating current (AC) signal for oily bilge water ultrafiltration. The effect of in-situ vibration on membrane fouling was investigated through changing in the excitation alternating voltage and its frequency, pH, crossflow rate. The results indicated that the piezoelectric membrane by applying AC signal remarkably alleviated the membrane fouling for bilge water ultrafiltration. The membrane fouling decreased with increasing the AC signal voltage. The final steady-state permeate flux from the piezoelectric membrane for bilge water ultrafiltration increased with the AC signal voltage, raising it by up to 63.4% at AC signal voltage of 20 V compared to that of the membrane without applying AC voltage. The high permeate flux was obtained at the resonant frequency of 220 kHz. During the 50-h ultrafiltration of bilge water with the piezoelectric membrane excited at 220 kHz and 15 V, the permeate flux from the membrane was stable. The oil concentration in outflow from the piezoelectric membrane was below 14 ppm, which met the discharged level required by IMO convention. The total organic carbon removal rate in bilge water was over 94%.
Antifragile Behavior Change Through Digital Health Behavior Change Interventions
Authors: Kaveladze Benjamin T , Young Sean D , Schueller Stephen M
Published: May 2022

Digital health behavior change interventions (DHBCIs) offer users accessible support, yet their promise to improve health behaviors at scale has not been met. One reason for this unmet potential may be a failure to offer users support that is tailored to their personal characteristics and goals. We apply the concept of antifragility to propose how DHBCIs could be better designed to support diverse users’ behavior change journeys. We first define antifragility as a feature of an individual’s relationship to a particular challenge such that if one is antifragile to a challenge, one is well positioned to benefit from facing that challenge. Second, we introduce antifragile behavior change to describe behavior change processes that leverage person-specific antifragilities to maximize benefits and minimize risk in the behavior change process. While most existing behavior change models focus on improving one’s motivation and ability to face challenges, antifragile behavior change complements these models by helping to select challenges that are most likely to produce desired outcomes. Next, we propose three principles by which DHBCIs can help users to develop antifragile behavior change strategies: providing personalized guidance, embracing variance and exploration in choosing behaviors, and prioritizing user agency. Finally, we offer an example of how a DHBCI could be designed to support antifragile behavior change.
Machine Learning Prediction of Hypoglycemia and Hyperglycemia From Electronic Health Records: Algorithm Development and Validation
Authors: Witte Harald , Nakas Christos , Bally Lia , Leichtle Alexander Benedikt
Published: May 2022

Background

Acute blood glucose (BG) decompensations (hypoglycemia and hyperglycemia) represent a frequent and significant risk for inpatients and adversely affect patient outcomes and safety. The increasing need for BG management in inpatients poses a high demand on clinical staff and health care systems in addition.

Objective

This study aimed to generate a broadly applicable multiclass classification model for predicting BG decompensation events from patients’ electronic health records to indicate where adjustments in patient monitoring and therapeutic interventions are required. This should allow for taking proactive measures before BG levels are derailed.

Methods

A retrospective cohort study was conducted on patients who were hospitalized at a tertiary hospital in Bern, Switzerland. Using patient details and routine data from electronic health records, a multiclass prediction model for BG decompensation events (<3.9 mmol/L [hypoglycemia] or >10, >13.9, or >16.7 mmol/L [representing different degrees of hyperglycemia]) was generated based on a second-level ensemble of gradient-boosted binary trees.

Results

A total of 63,579 hospital admissions of 38,250 patients were included in this study. The multiclass prediction model reached specificities of 93.7%, 98.9%, and 93.9% and sensitivities of 67.1%, 59%, and 63.6% for the main categories of interest, which were nondecompensated cases, hypoglycemia, or hyperglycemia, respectively. The median prediction horizon was 7 hours and 4 hours for hypoglycemia and hyperglycemia, respectively.

Conclusions

Electronic health records have the potential to reliably predict all types of BG decompensation. Readily available patient details and routine laboratory data can support the decisions for proactive interventions and thus help to reduce the detrimental health effects of hypoglycemia and hyperglycemia.
Web-Based Psychological Interventions for People Living With and Beyond Cancer: Meta-Review of What Works and What Does Not for Maximizing Recruitment, Engagement, and Efficacy
Authors: Leslie Monica , Beatty Lisa , Hulbert-Williams Lee , Pendrous Rosina , Cartwright Tim , Jackson Richard ,   The Finding My Way UK Trial Steering Group, Hulbert-Williams Nicholas J
Published: May 2022

Background

Despite high levels of psychological distress experienced by many patients with cancer, previous research has identified several barriers to accessing traditional face-to-face psychological support. Web-based psychosocial interventions have emerged as a promising alternative.

Objective

This meta-review aimed to synthesize evidence on recruitment challenges and enablers, factors that promote engagement and adherence to web-based intervention content, and factors that promote the efficacy of web-based psychosocial interventions for patients with cancer and cancer survivors.

Methods

We conducted a systematic search of previous reviews that investigated the recruitment, engagement, and efficacy of web-based and app-based psychosocial interventions in adult patients with cancer and cancer survivors. We searched PubMed, CINAHL, PsycINFO, and the Cochrane Library database for relevant literature. The search terms focused on a combination of topics pertaining to neoplasms and telemedicine. Two independent authors conducted abstract screening, full text screening, and data extraction for each identified article.

Results

A total of 20 articles met eligibility criteria. There was inconsistency in the reporting of uptake and engagement data; however, anxiety about technology and perceived time burden were identified as 2 key barriers. Web-based psychosocial oncology interventions demonstrated efficacy in reducing depression and stress but reported weak to mixed findings for distress, anxiety, quality of life, and well-being. Although no factors consistently moderated intervention efficacy, preliminary evidence indicated that multicomponent interventions and greater communication with a health care professional were preferred by participants and were associated with superior effects.

Conclusions

Several consistently cited barriers to intervention uptake and recruitment have emerged, which we recommend future intervention studies address. Preliminary evidence also supports the superior efficacy of multicomponent interventions and interventions that facilitate communication with a health care professional. However, a greater number of appropriately powered clinical trials, including randomized trials with head-to-head comparisons, are needed to enable more confident conclusions regarding which web-based psychosocial oncology interventions work best and for whom.

Trial Registration

PROSPERO CRD42020202633; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=202633
Improving Pain Assessment Using Vital Signs and Pain Medication for Patients With Sickle Cell Disease: Retrospective Study
Authors: Padhee Swati , Nave Jr Gary K , Banerjee Tanvi , Abrams Daniel M , Shah Nirmish
Published: May 2022

Background

Sickle cell disease (SCD) is the most common inherited blood disorder affecting millions of people worldwide. Most patients with SCD experience repeated, unpredictable episodes of severe pain. These pain episodes are the leading cause of emergency department visits among patients with SCD and may last for several weeks. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting a patient’s pain intensity level.

Objective

This study aims to learn deep feature representations of subjective pain trajectories using objective physiological signals collected from electronic health records.

Methods

This study used electronic health record data collected from 496 Duke University Medical Center participants over 5 consecutive years. Each record contained measures for 6 vital signs and the patient’s self-reported pain score, with an ordinal range from 0 (no pain) to 10 (severe and unbearable pain). We also extracted 3 features related to medication: medication type, medication status (given or applied, or missed or removed or due), and total medication dosage (mg/mL). We used variational autoencoders for representation learning and designed machine learning classification algorithms to build pain prediction models. We evaluated our results using an accuracy and confusion matrix and visualized the qualitative data representations.

Results

We designed a classification model using raw data and deep representational learning to predict subjective pain scores with average accuracies of 82.8%, 70.6%, 49.3%, and 47.4% for 2-point, 4-point, 6-point, and 11-point pain ratings, respectively. We observed that random forest classification models trained on deep represented features outperformed models trained on unrepresented data for all pain rating scales. We observed that at varying Likert scales, our models performed better when provided with medication data along with vital signs data. We visualized the data representations to understand the underlying latent representations, indicating neighboring representations for similar pain scores with a higher resolution of pain ratings.

Conclusions

Our results demonstrate that medication information (the type of medication, total medication dosage, and whether the medication was given or missed) can significantly improve subjective pain prediction modeling compared with modeling with only vital signs. This study shows promise in data-driven estimated pain scores that will help clinicians with additional information about the patient’s condition, in addition to the patient’s self-reported pain scores.
Adherence and Engagement With a Cognitive Behavioral Therapy–Based Conversational Agent (Wysa for Chronic Pain) Among Adults With Chronic Pain: Survival Analysis
Authors: Sinha Chaitali , Cheng Abby L , Kadaba Madhura
Published: May 2022

Background

Digital applications are commonly used to support mental health and well-being. However, successfully retaining and engaging users to complete digital interventions is challenging, and comorbidities such as chronic pain further reduce user engagement. Digital conversational agents (CAs) may improve user engagement by applying engagement principles that have been implemented within in-person care settings.

Objective

To evaluate user retention and engagement with an artificial intelligence–led digital mental health app (Wysa for Chronic Pain) that is customized for individuals managing mental health symptoms and coexisting chronic pain.

Methods

In this ancillary survival analysis of a clinical trial, participants included 51 adults who presented to a tertiary care center for chronic musculoskeletal pain, who endorsed coexisting symptoms of depression or anxiety (Patient-Reported Outcomes Measurement Information System score of ≥55 for depression or anxiety), and initiated onboarding to an 8-week subscription of Wysa for Chronic Pain. The study outcomes were user retention, defined as revisiting the app each week and on the last day of engagement, and user engagement, defined by the number of sessions the user completed.

Results

Users engaged in a cumulative mean of 33.3 sessions during the 8-week study period. The survival analysis depicted a median user retention period (i.e., time to complete disengagement) of 51 days, with the usage of a morning check-in feature having a significant relationship with a longer retention period (P=.001).

Conclusions

Our findings suggest that user retention and engagement with a CBT-based CA built for users with chronic pain is higher than standard industry metrics. These results have clear implications for addressing issues of suboptimal engagement of digital health interventions and improving access to care for chronic pain. Future work should use these findings to inform the design of evidence-based interventions for individuals with chronic pain and to enhance user retention and engagement of digital health interventions more broadly.

Trial Registration

ClinicalTrials.gov NCT04640090; https://clinicaltrials.gov/ct2/show/NCT04640090
Construction of a Linked Data Set of COVID-19 Knowledge Graphs: Development and Applications (Preprint)
Authors: Wang Haofen , Du Huifang , Qi Guilin , Chen Huajun , Hu Wei , Chen Zhuo
Published: May 2022

BACKGROUND

With the continuous spread of COVID-19, information about the worldwide pandemic is exploding. Therefore, it is necessary and significant to organize such a large amount of information. As the key branch of artificial intelligence, a knowledge graph (KG) is helpful to structure, reason, and understand data.

OBJECTIVE

To improve the utilization value of the information and effectively aid researchers to combat COVID-19, we have constructed and successively released a unified linked data set named OpenKG-COVID19, which is one of the largest existing KGs related to COVID-19. OpenKG-COVID19 includes 10 interlinked COVID-19 subgraphs covering the topics of encyclopedia, concept, medical, research, event, health, epidemiology, goods, prevention, and character.

METHODS

In this paper, we introduce the key techniques exploited in building COVID-19 KGs in a top-down manner. First, the schema of the modeling process for each KG in OpenKG-COVID19 is described. Second, we propose different methods for extracting knowledge from open government sites, professional texts, public domain–specific sources, and public encyclopedia sites. The curated 10 COVID-19 KGs are further linked together at both the schema and data levels. In addition, we present the naming convention for OpenKG-COVID19.

RESULTS

OpenKG-COVID19 has more than 2572 concepts, 329,600 entities, 513 properties, and 2,687,329 facts, and the data set will be updated continuously. Each COVID-19 KG was evaluated, and the average precision was found to be above 93%. We have developed search and browse interfaces and a SPARQL endpoint to improve user access. Possible intelligent applications based on OpenKG-COVID19 for further development are also described.

CONCLUSIONS

A KG is useful for intelligent question-answering, semantic searches, recommendation systems, visualization analysis, and decision-making support. Research related to COVID-19, biomedicine, and many other communities can benefit from OpenKG-COVID19. Furthermore, the 10 KGs will be continuously updated to ensure that the public will have access to sufficient and up-to-date knowledge.
Providing Accessible ReCreation Outdoors-User-driven Research on Standards: Novel method for winter assessments (Preprint)
Authors: Prescott Mike , Gamache Stéphanie , Mortenson W. Ben , Best Krista Lynn , Grandisson Marie , Mostafavi Mir Abolfazl , Labbé Delphine , Morales Ernesto , Mahmood Atiya , Borisoff Jaimie , Sawatzky Bonita , Miller William C. , Bulk Laura Yvonne , Robillard Julie M. , Routhier François
Published: May 2022

BACKGROUND

Although there have been recent efforts to improve access to Canadian national parks, many remain not fully accessible to people with disabilities. Winter conditions, in particular, present challenges that limit their participation in outdoor activities.

OBJECTIVE

To develop a novel method to assess park access during winter that will inform recommendations for national park standards to meet needs of all park visitors (regardless of ability) during winter conditions.

METHODS

A larger participatory mixed-methods research project exploring park access was adapted [1]. Specifically, the second phase of the study to conduct in-person winter mobile interviews (i.e., walking and wheeling interviews) with people who have a wide range of disabilities while visiting three parks in two provinces was modified. Changes were made to accommodate the extreme winter weather conditions in Quebec while using safe and informative data collection methods. In Quebec, one park, where winter conditions are safer, will be assessed in person (n=4). Virtual interviews will be used to facilitate the assessment of other winter and summer conditions in two other parks (n=8).

RESULTS

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CONCLUSIONS

We expect that adapting the protocol to gather further information on winter conditions and access to parks will provide high-quality and rich data to better inform park access standards. This participatory mixed-methods research will inform the development of park standards that consider the accessibility needs of all people.
Addiction symptoms network of young Internet users: A network analysis (Preprint)
Authors: Lu Jianxia , Zhang Qinhan , Chen Jin , Zhai Yujia , Guo Lei , Lu Chunlei , Chen Tianzhen , Jiang Zhongli , Zhong Na , Zheng Hui
Published: May 2022

BACKGROUND

An increasing number of people are becoming addicted to the Internet as a result of overuse. Internet Addiction Test (IAT) is a popular tool for evaluating Internet usage behaviors. The interaction between different symptoms and the relationship between IAT and clinical diagnostic criteria is not well understood.

OBJECTIVE

We recruited 3584 Internet users (14-24 years old) and had them complete the IAT. The final analysis included 2845 participants after screening the submitted questionnaires. Participants were classified into Internet Addiction (IA) group and Non-Internet Addiction (NIA)group.

METHODS

Using partial correlation with LASSO regularization networks, we identified the core symptoms of IA in each group and compare the group differences in network properties (strength, closeness, and betweenness). Then we analyzed the symptom networks of the DSM-5 diagnostic criteria and IAT scale for Internet addiction.

RESULTS

There were 355 in the IA group and 2490 in the NIA group. IAT_06 (school work suffers, strength = 0.511), IAT_08 (job performance suffers, strength = 0.531), IAT_15 (fantasiaze about online, strength = 0.474), IAT_17 (fail to stop online, strength = 0.526), and IAT_12 (fear of boring if offline, strength = 0.502). IA groups have a stronger edge between IAT_09 (defensive or secretive about online) and IAT_18 (hidden online time) than NIA groups. The items in DSM-5 have a stronger association with IAT_12 (weight=-0.066), IAT_15 (weight=-0.081), IAT_17 (weight=-0.106), IAT_9 (weight=-0.198), and IAT_18 (weight=-0.052).

CONCLUSIONS

The Internet use symptoms network of IA group is significantly different from that of NIA group. Nodes IAT_06 (school work affected) and IAT_08 (work performance affected) are the resulting symptoms affected by other symptoms, node IAT_12 (fear of boredom if offline), IAT_17 (inability to stop online), and IAT_15 (fantasy online) are key symptoms that activate other symptoms of Internet addiction and are strongly linked to inability to control the intention to play games in the DSM-5.
Burden of Disease in Alopecia Areata: A Canadian Online Survey of Patients and Caregivers (Preprint)
Authors: Gilding Anthony Justin , Ho Nhung , Pope Elena , Sibbald Cathryn
Published: May 2022

BACKGROUND

Alopecia areata (AA) is associated with negative impacts on quality of life (QoL). Data is lacking on this impact for Canadian patients and their caregivers.

OBJECTIVE

To investigate the burden of AA on Canadian patients and their caregivers.

METHODS

Four online surveys were created for patients 5-11 years old, 12-17 years old, ≥18 years old, and for caregivers of children (<18 years old) with AA. These were disseminated through the Canadian Alopecia Areata Foundation website and to dermatologists across Canada.

RESULTS

One-hundred and fifteen adult patients (97% female), 14 pediatric patients (93% female) and 15 caregivers completed the surveys online. The majority (95%) of patients felt uncomfortable or self-conscious about their appearance. Camouflaging hair loss with hats, scarves, and hair pieces was a common practice for 78.6% of pediatric and 74% of adult patients. Avoidance of social situations was reported by 61.5% of pediatric and 68.2% of adult patients. Constant worry about losing achieved hair growth was a concern for 61.5% of pediatric and 68.2% of adult patients. On a scale of 1-5, the mean score of caregivers’ own feelings of sadness or depression about their child’s AA was 4.0 (SD 0.9), and their feelings of guilt or helplessness was 4.2 (SD 1.2). The impact on QoL was moderate for both children and adults. Based on the Adjustment Disorder New Module, 62% of patients were at high risk of an adjustment disorder. Abnormal anxiety scores were recorded in 35% of patients compared to abnormal depression scores in 17%.

CONCLUSIONS

This study confirmed significant burden of AA on Canadian patients’ and caregivers’ QoL.
Lessons and reflections from an extended co-design process developing an mHealth app with, and for, older adults (Preprint)
Authors: Tong Catherine , Kernoghan Alison , Lemmon Kassandra , Fernandes Paige , Elliott Jacobi , Sacco Veronica , Bodemer Sheila , Stolee Paul
Published: May 2022

BACKGROUND

There are many mHealth apps for older adult patients, but research has found that, broadly speaking, mHealth still fails to meet the specific needs of an older adult user. Others have highlighted the need for embedding the user in the mHealth design process in a fulsome and meaningful way. Co-design has been widely used in the development of mHealth apps, and is described as involving stakeholders in each phase of the design/development process. Involvement of older adults in co-design processes has been variable. Co-design approaches to date have tended towards embedding the stakeholders in early phases (e.g., pre-design/generative) but not throughout.

OBJECTIVE

The aim of this paper is to provide reflections on the processes and lessons learned from engaging in an extended co-design process to develop an mHealth app for older adults, with older users contributing at each phase. The aim was to design an mHealth tool to assist older adults to coordinate their care with healthcare providers and caregivers.

METHODS

Our work to conceptualize, develop and test the mHealth app consisted of four phases: Phase 1- consulting stakeholders; Phase 2- app development and co-designing with older adults; Phase 3- field testing with a smaller sample of older adult volunteer testers; and Phase 4, reflecting, internally, on lessons learned from this process. In each phase, we drew on qualitative methods, including in-depth interviews and focus groups, all of which were analyzed in NVivo 12, using team-based thematic analysis.

RESULTS

In Phase 1, we identified key features that older adults and health care providers wanted in an app, and each user group identified different priority features (older adults principally sought supports to use the mHealth app, while providers prioritized recoding illnesses, immunizations, and appointments). Phases 2 and 3 revealed significant mismatches between what older adult users wanted, and what our developers were able and willing to deliver. In Phase 4 we reflected on our abilities to embed the voices and perspectives of older adults throughout the project, when working with a developer not familiar or committed to the core principles of co-design.

CONCLUSIONS

While our final mHealth app did not reflect all of the needs and wishes of our older adult testers, our consultation process identified key features and contextual information essential for those developing apps to support older adults in managing their health and health care. Furthermore, our reflective process identified important factors to consider when health researchers and gerontologists set into the app development sector.
Planning, Housing and Environmental Challenges of Hilltop Settlements in Zinariya and Azurfa Areas of Jos, Nigeria
Authors: Dung-Gwom John Y. , Bashir Shamsiyyah M.
Published: May 2022

Jos is a town in central Nigeria whose growth and development is closely associated with the commercial exploitation and mining of tin ore by the British colonisers at the beginning of the twentieth century. The terrain of the area is generally over 1000m above sea level. Hilltop settlements within Jos have sprang up as a result of the early mining settlements, rapid urbanization, urban expansion and rapid population growth which have exerted high demand for land for housing. The Government and Urban authorities have failed to provide planned and serviced lands on desirable sites to the expanding population, who in turn have resorted to self-help through the open market to provide shelter for themselves often without planning approvals and basic infrastructural facilities. Settlements on steep slopes and hilltops pose peculiar planning challenges arising from the nature of their terrain, costs of construction and maintenance of buildings, poor structural quality of housing, provision of social services and public facilities; poor drainage, inadequate liquid and solid waste management, haphazard development and proclivity to environmental hazards. The growth of hilltop settlements is expected to have major consequences on both humans and the environment, which are inextricably linked. Implications of these hilltop settlements on physical planning in Jos North includes; deviation from the city master plan, difficulty in the provision of services (both physical and social), chaotic and disorderly growth of the city, inaccessibility to vehicular traffic due to poor road network or lack of it. To carry out the study, descriptive research design and quantitative approach were used. primary data was collected from those households living on the hilltop settlements of Azurfa and Zinariya, which are the case study areas, the researcher distributed 400 questionnaires, out of which, 391 (97.8%) responded by filling and returning the questionnaires. Both qualitative and quantitative data were obtained using primary and secondary sources of data. Appropriate recommendations were made, and if implemented by government, planning agencies and property developers, this will improve the housing, environmental, infrastructural and the quality of lives of residents of the studied hilltop settlements.
COVID-19 Detection using Chest X-Ray
Authors: Sali Nirmiti , Khadilkar Nimisha , Biwalkar Srushti , Swamy Amisha , Ansari Nusrat
Published: May 2022

Abstract: Over the past few months, the exponential increase in COVID-19 cases has been overwhelming for many healthcare systems across the world. With 114 million cases globally as of 28th February 2021, with India itself having 11.1 million cases, it has challenged us with the testing, quarantine, and safety measures. Having limited testing kits, not all patients that have symptoms of respiratory illness can be tested using conventional techniques (RT-PCR). In this project, we propose the use of chest X-Ray to prioritize the selection of patients for further RT-PCR testing. It would also help in identifying patients with a high likelihood of COVID with a false negative RT-PCR who would wish to repeat testing. Further, we propose the utilization of recent AI techniques to detect the COVID-19 patients automatically using X-Ray images, particularly in settings where radiologists aren't available, and help make the proposed testing technology scalable. Keywords: COVID-19, healthcare systems, X-Ray, RT-PCR, patient, AI.