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After participating in a group peer-review exercise at a workshop presented by Academic Medicine and MedEdPORTAL editors at the 2015 Association of American Medical Colleges Medical Education Meeting, the authors realized that the way their work group reviewed a manuscript was very different from the way by which they each would have reviewed the paper as an individual. Further, the group peer-review process yielded more robust feedback for the manuscript's authors than did the traditional individual peer-review process. This realization motivated the authors to reconvene and collaborate to write this Commentary to share their experience and propose the expanded use of group peer review in medical education scholarship.The authors consider the benefits of a peer-review process for reviewers, including learning how to improve their own manuscripts. They suggest that the benefits of a team review model may be similar to those of teamwork and team-based learning in medicine and medical education. They call for research to investigate this, to provide evidence to support group review, and to determine whether specific paper types would benefit most from team review (e.g., particularly complex manuscripts, those receiving widely disparate initial individual reviews). In addition, the authors propose ways in which a team-based approach to peer review could be expanded by journals and institutions. They believe that exploring the use of group peer review potentially could create a new methodology for skill development in research and scholarly writing and could enhance the quality of medical education scholarship.

Published version. Source at http://dx.doi.org/10.1016/j.procs.2016.09.039 The implementation of Electronic Health Records (EHRs) in developing countries is considered a means for improving data quality and high quality care. However, existing research, indicate that EHRs have recorded greater quantity of bad data instead of improving the quality of data. The reasons for this is not exactly clear. Accordingly, this paper takes a broader socio-technical approach to explore the issues in more detail. The paper explores the relationship between EHRs and quality at the Pentecost Hospital Madina-Ghana by using an interpretative research approach. The result of our study indicates that the EHRs introduced at the hospital have so far had limited effect on data quality and that context-related challenges are the major pitfalls identified in the study. Based on a socio- technical approach the paper discusses the need to; consider users and technology as intertwined, how technology changes practice and how it formalizes roles and responsibilities in the process, why it requires collaborative work and why realistic goals as opposed to exaggerated expectation

Source: doi: 10.1109/ACCESS.2016.2599851 Collecting data via a questionnaire and analyzing them while preserving respondents' privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy- preserving method for collecting and analyzing survey responses using secure multi-party computation. The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire data set of 3158 respondents sampled for a medical study and simulated questionnaire data sets of up to 50 000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected.

In the 10 years since the term was coined 'design fiction' has become an increasingly common approach in HCI research. The practice involves working with 'diegetic prototypes', that is prototypes that need not exist in reality, but instead exist from within a 'story world'. Although fictional aspects are not unusual in HCI prototyping methods (e.g. storyboards, personas, Wizard-of-Oz), the breadth and flexibility of design fiction poses new challenges. This paper originally featured quotes from peer reviews of design fiction orientated papers that have previously been submitted to ACM SIGCHI conferences in order to highlight inherent challenges when reviewing research that may be based upon or include elements of fiction. In response to the SIGCHI Executive Committee's request to not directly quote reviewers the quotes have now been redacted. This somewhat changes the paper's tone and also makes very clear that publishing discussions relating to peer reviews (or the reviews themselves) is extremely challenging.

Summary Background: This accompanying editorial is an introduction to the focus theme of “chronic disease registries - trends and challenges”. Methods: A call for papers was announced on the website of Methods of Information in Medicine in April 2016 with submission deadline in September 2016. A peer review process was established to select the papers for the focus theme, managed by two guest editors. Results: Three papers were selected to be included in the focus theme. Topics range from contributions to patient care through implementation of clinical decision support functionality in clinical registries; analysing similar-purposed acute coronary syndrome registries of two countries and their registry-to- SNOMED CT maps; and data extraction for speciality population registries from electronic health record data rather than manual abstraction. Conclusions: The focus theme gives insight into new developments related to disease registration. This applies to technical challenges such as data linkage and data as well as data structure abstraction, but also the utilisation for clinical decision making.

Background Journal editors have exercised their control over submitted papers having a high similarity index. Despite widespread suspicion of possible plagiarism on a high similarity index, our study focused on the real effect of the similarity index on the value of a scientific paper. Methods This research examined the percent values of the similarity index from 978 submitted (420 published) papers in the Korean Journal of Anesthesiology since 2012. Thus, this study aimed to identify the correlation between the similarity index and the value of a paper. The value of a paper was evaluated in two distinct phases (during a peer-review process vs. after publication), and the value of a published paper was evaluated in two aspects (academic citation vs. social media appearance). Results Yearly mean values of the similarity index ranged from 16% to 19%. There were 254 papers cited at least once and 179 papers appearing at least once in social media. The similarity index affected the acceptance/rejection of a paper in various ways; although the influence was not linear and the cutoff measures were distinctive among the types of papers, both extremes were related to a high rate of rejection. After publication, the similarity index had no effect on academic citation or social media appearance according to the paper. Conclusions The finding suggested that the similarity index no longer had an influence on academic citation or social media appearance according to the paper after publication, while the similarity index affected the acceptance/rejection of a submitted paper. Proofreading and intervention for finalizing the draft by the editors might play a role in achieving uniform quality of the publication.

Malaria is a leading cause of death in Nigeria and remains a public health concern because of the increasing resistance of the disease to antimalarial drugs. Pregnant women and children under five years of age are the most vulnerable. Efforts to eradicate malaria is often frustrated due to some various sociodemographic factors and medical factors. One of the vital therapeutic factors is misdiagnosis. Hence, the paper applied different data mining models to diagnose malaria using fifteen symptoms of patients that attended a hospital in Nigeria. The data were obtained from a peer reviewed data article that comprises 337 subjects at Federal Polytechnic Ilaro Medical Centre, Ogun State. The independent variables are 15 symptoms, age, and sex, while the target or dependent is the outcome. The outcome is the result of the diagnosis, which is positive for negative for malaria. Eight machine learning tools were applied to the data on the Orange Software platform. Weak non-significant correlations were obtained between the 15 symptoms and the outcome, and hence no pattern was observed. However, the application of data mining tools revealed a hidden pattern that correctly predicted the outcome using the subjects' symptoms, age, and sex. 6 out of the 8 machine learning models were adjudged to perform well using different performance metrics. The Adaptive boosting model gave a percent 100% precision in the classification, and logistic regression was the least. Furthermore, a percent performance of Adaboost implies that the model correctly predicted all the 221 true negatives and 116 true positives with a misclassification (misdiagnosis) of zero. Classify using only the 15 symptoms reduced the predictive accuracy of the 6 models. Nevertheless, Adaboost performance was the best with a classification accuracy of 98.2%, precision of 96.6%, and an error rate of just 1.8%. Again, logistic regression performance was the least. The present work has presented a strong relationship between age and sex and the outcome. Adaboost model can be used to design decision support systems or rapid diagnostic tools that utilise the internet or mobile devices as platforms in the diagnosis of malaria. The application of the present work as potentials in reduction of misdiagnosis incidences, reducing the mortality due to malaria and improving the overall public health of people residing in malaria endemic areas.

PurposePeer reviewer evaluations of academic papers are known to be variable in content and overall judgements but are important academic publishing safeguards. This article introduces a sentiment analysis program, PeerJudge, to detect praise and criticism in peer evaluations. It is designed to support editorial management decisions and reviewers in the scholarly publishing process and for grant funding decision workflows. The initial version of PeerJudge is tailored for reviews from F1000Research's open peer review publishing platform.Design/methodology/approachPeerJudge uses a lexical sentiment analysis approach with a human-coded initial sentiment lexicon and machine learning adjustments and additions. It was built with an F1000Research development corpus and evaluated on a different F1000Research test corpus using reviewer ratings.FindingsPeerJudge can predict F1000Research judgements from negative evaluations in reviewers' comments more accurately than baseline approaches, although not from positive reviewer comments, which seem to be largely unrelated to reviewer decisions. Within the F1000Research mode of post-publication peer review, the absence of any detected negative comments is a reliable indicator that an article will be ‘approved’, but the presence of moderately negative comments could lead to either an approved or approved with reservations decision.Originality/valuePeerJudge is the first transparent AI approach to peer review sentiment detection. It may be used to identify anomalous reviews with text potentially not matching judgements for individual checks or systematic bias assessments.

Attaining continuous economic growth entails special consideration of energy sector and the environment. Compliance with this purpose may be more intricate in the uncertain milieu of developing countries. The present paper examines the nature of causality between energy consumption, environment pollution, and economic growth in 8 contiguous developing countries, considering GDP per capita, CO2 emissions, energy use, labour force, total population, urban population, capital formation, financial development, and trade openness. The author applied spatial simultaneous equations for random effects panel data to investigate the spatial interactions of adjacent countries over the period from 1998 to 2011. The findings reveal that energy consumption, environment degradation, and economic growth of a country influence those of its neighbours. Additionally, the results document bidirectional causal relationship between economic growth and environment pollution, as well as between environment pollution and energy consumption. Thus, there is a bidirectional relationship between energy use and economic growth. Fossil fuels replacement with renewable energy and usage of tax instruments to reduce greenhouse gas are recommended.

Purpose Online reviews are increasingly available for a wide range of products and services in e-commerce. Most consumers rely heavily on online reviews when making purchase decisions, so an important topic is that of understanding what makes some online reviews helpful in the eyes of consumers. Researchers have demonstrated the benefits of the presence of customer reviews to an online retailer, however, few studies have investigated how images in review content and the facial expressions of reviewers’ avatars influence the judgment of online review helpfulness. This study draws on self-construal theory, attribution theory and affect-as-information theory to empirically test a model of the interaction effects of images in review content and the facial expressions of reviewers’ avatars on online review helpfulness. Furthermore, the purpose of this paper is to identify an underlying mechanism of causal attribution toward store performance on the above effects. Design/methodology/approach This study conducted two online experiments. Study 1 is a 2 (images in review content: one person with a product vs a group of people with a product) ×2 (facial expression of the reviewer’s avatar: happy vs angry) between-subjects design. Study 2 is a 3 (image: product alone vs one person with a product vs a group of people with a product) ×2 (facial expression of the reviewer’s avatar: happy vs angry) ×3 (valence of the review: positive vs negative vs neutral) between-subjects design. Findings The results indicate that when consumers were exposed to a happy-looking avatar, they were likely to express higher perceptions of online review helpfulness in response to an image showing a group of people in a restaurant than they would for an image of one person in the same situation. In contrast, when consumers were exposed to an angry-looking avatar, their perceptions of online review helpfulness did not differ in response to images of either a group of people or of one person. Furthermore, cause attribution toward store performance mediated the interaction between images in content of reviews and the facial expression of a reviewer’s avatar on the perceptions of online review helpfulness. Practical implications The authors provide insights into how to develop guidelines on how online reviews should be written so that readers perceive them to be helpful, and how to design effective reward mechanisms for customer feedback. Originality/value Compared with previous studies, this study provides further contributions in three ways. First, it contributes to the literature on review content by showing which images in reviews are deemed to be helpful. Second, it extends previous findings from the literature relating to online peer reviews by demonstrating the importance of facial expressions in reviewers’ avatars (i.e. happy vs angry) when explaining helpfulness, rather than the strength of purchase intent. Third, this study contributes by further highlighting a novel mechanism which shows that a causal attribution toward store performance motivates the perceptions of online review helpfulness.

Context. Empirical research consistently demonstrates that that scholarly peer review is ineffective, unreliable, and prejudiced. In principle, the solution is to move from contemporary, unstructured, essay-like reviewing to more structured, checklist-like reviewing. The Task Force created models—called “empirical standards”—of the software engineering community’s expectations for different popular methodologies. Objective. This paper presents a tool for facilitating more structured reviewing by generating review checklists from the empirical standards. Design. A tool that generates pre-submission and review forms using the empirical standards for software engineering research was designed and implemented. The pre-submission and review forms can be used by authors and reviewers, respectively, to determine whether a manuscript meets the software engineering community’s expectations for the particular kind of research conducted. Evaluation. The proposed tool can be empirically evaluated using lab or field randomized experiments as well as qualitative research. Huge, impractical studies involving splitting a conference program committee are not necessary to establish the effectiveness of the standards, checklists and structured review. Conclusions. The checklist generator enables more structured peer reviews, which in turn should improve review quality, reliability, thoroughness, and readability. Empirical research is needed to assess the effectiveness of the tool and the standards.

In this paper, we investigated how internationally mobile students from Norway diverge from students in Norway regarding social background, grades obtained at upper secondary school, and motivation to study. Data from two comparable surveys were used, one relating to students abroad and one relating to domestic students. Results showed that, on average, mobile students were of higher social origin than domestic students, but this did not apply across all fields. In some subject fields, mobile students had higher grades than domestic students, while they were lower in others. Mobile students clearly demonstrated higher motivation than domestic students, even when controlling for subject field and background variables. In sum, we found that mobile students constitute a select group in several ways, most prominently regarding study motivation. This suggests that mobile students potentially represent a positive contribution to the learning environment in more ways than bringing diversity in cultural background.

Accepted manuscript version, licensed CC BY-NC-ND 4.0. Final version published in International Journal of Medical Informatics, 129, 253-259, is available at https://doi.org/10.1016/j.ijmedinf.2019.06.011. Background: Qualitative studies have provided important insights into how hospital pharmacists’ work changes when electronic medication management (EMM) systems are introduced. Quantitative studies of work practice change are rare. Despite the use of EMM systems internationally, there are no cross-country comparative studies of their impact on health professionals’ work. We aimed to quantify and compare the type and magnitude of changes in hospital pharmacists’ work pre- and post-EMM implementation in two countries. Methods: Parallel, direct observational, time and motion studies of pharmacists in Australia and England pre- and post-EMM implementation. 20 pharmacists were observed: 9 in an Australian 440-bed hospital (155 h); and 11 pharmacists in a 500-bed English hospital (258 h). The Work Observation Method By Activity Timing (WOMBAT) software was used to collect observational data. Proportions of observed time in 11 tasks by study period (pre- versus post-EMM) and site, time spent with others or alone, and using different tools (e.g computers, paper) were calculated. Magnitude of changes between pre- and post-EMM by task and country were determined using z-tests for proportions adjusting for multiple testing. Results: At baseline, Australian and English pharmacists spent the greatest proportion of time in medication review. Post-EMM, time in medication review (Australia 21.6%–27.5%; England 27.1%–33.8%) and history-taking (Australia 7.6%–13.3%; England 19.5%–28.9%) significantly increased. Despite country differences in these tasks at baseline, the magnitude of changes did not significantly differ. English pharmacists increased time engaged in medication discussions with patients post-EMM (from 5.9% to 10.8%; p = 0.01). The Australian rate did not change (18.0%–27.2%; p = 0.09), but was higher at baseline. Post-EMM, Australian pharmacists spent 63.4% of time working alone, compared to 92.0% for English pharmacists. Conclusions: EMM systems impacted the same core areas of work and had a similar magnitude of effect on pharmacists’ work in both countries. Anticipated reductions in medication review and history taking were not observed.

This study answers a call for more qualitative research on project management to unveil “what goes on in social construction of projects and project management”. More precisely, we focus on how trust and control are balanced in an inter-organizational project collaboration in the Norwegian petroleum industry. Our findings suggest that balancing trust and control is a significant part of the project manager role. We claim that this area is both neglected in education and training and under-researched. The aim of the paper is to provide more knowledge on the trust-control dilemma in project management. Our qualitative approach provides rich empirical examples of dilemma situations and how balancing trust and control take place in a real-life project management context. The data was collected between 2010 and 2013 and consists of observational data from project meetings, document analysis and interviews.

The objective of exposing girls to Computer Science as a career option has led to research directed towards gaming activities for girls. These activities include both game play and game design. Research about gaming activities for increasing girls’ interest in computer science has gained much attention over the past few years and has resulted in a number of contributions. We follow up with an overview of the status of research through a Systematic Literature Review. We investigate the relation between the various game playing or designing activities and their impact on girls’ perception of Computer Science as a career choice. We further present the design consideration for the games and related activities to potentially improve the perception of girls towards a Computer Science career. The applied method is a Systematic Literature Review through which we investigate which contributions were made, which knowledge areas were most explored, and which research facets have been used. We identify 25 papers to distill a common understanding of the state-of-the-art. Specifically, we investigate the effects that the game play/design activities had on girls’ perception about Computer Science; and what are the key design factors to be kept in mind while designing a serious game to improve girls’ perception about Computer Science. The results of this systematic literature review show that game playing or designing could indeed improve how girls perceive having a career in CS. The key aspects that such activities require are personalizing, opportunity for collaboration and the presence of a female lead character, This work has been done during the tenure of an ERCIM Alain Bensoussan fellowship

This paper explores whether efficacy beliefs can alter the relationship between worry about climate change and personal energy-saving behaviors, controlling for climate change beliefs and socio-demographics. For this purpose, we used data from 23 countries that participated in the European Social Survey Round 8 (N = 44 387). Worry about climate change, personal efficacy, personal outcome expectancy, and collective outcome expectancy were each associated with personal energy-saving behaviors concerning either energy curtailment or energy efficiency. The results further show that outcome expectancies moderate the association between worry about climate change and both types of energy behaviors. Worry was more strongly related to energy curtailment behaviors among those with high levels of personal and collective outcome expectancy. A similar pattern was found for energy efficiency behaviors, which were more strongly predicted by worry about climate change when combined with high levels of collective outcome expectancy. These findings are relevant for climate change communication, especially informational campaigns aiming to lower overall household energy use. publishedVersion

Scientific peer review is pivotal to maintain quality standards for academic publication. The effectiveness of the reviewing process is currently being challenged by the rapid increase of paper submissions in various conferences. Those venues need to recruit a large number of reviewers of different levels of expertise and background. The submitted reviews often do not meet the conformity standards of the conferences. Such a situation poses an ever-bigger burden on the meta-reviewers when trying to reach a final decision. In this work, we propose a human-AI approach that estimates the conformity of reviews to the conference standards. Specifically, we ask peers to grade each other’s reviews anonymously with respect to important criteria of review conformity such as sufficient justification and objectivity. We introduce a Bayesian framework that learns the conformity of reviews from both the peer grading process, historical reviews and decisions of a conference, while taking into account grading reliability. Our approach helps meta-reviewers easily identify reviews that require clarification and detect submissions requiring discussions while not inducing additional overhead from reviewers. Through a large-scale crowdsourced study where crowd workers are recruited as graders, we show that the proposed approach outperforms machine learning or review grades alone and that it can be easily integrated into existing peer review systems.

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Among the variety of the available requirements elicitation techniques, interviews are the most commonly used. Performing effective interviews is challenging, especially for students and novice analysts, since interviews’ success depends largely on soft skills and experience. Despite their diffusion and their challenging nature, when it comes to requirements engineering education and training (REET), limited resources and few well-founded pedagogical approaches are available to allow students to acquire and improve their skills as interviewers. To overcome this limitation, this paper presents two pedagogical approaches, namely SaPeer and ReverseSaPeer. SaPeer uses role-playing, peer review and self-assessment to enable students to experience first-hand the difficulties related to the interviewing process, reflect on their mistakes, and improve their interview skills by practice and analysis. ReverseSaPeer builds on the first approach and includes a role reversal activity in which participants play the role of a customer interviewed by a competent interviewer. We evaluate the effectiveness of SaPeer through a controlled quasi-experiment, which shows that the proposed approach significantly reduces the amount of mistakes made by the participants and that it is perceived as useful and easy by the participants. ReverseSaPeer and the impact of role reversal are analyzed through a thematic analysis of the participant’s reflections. The analysis shows that not only the students perceive the analysis as beneficial, but also that they have emotional involvement in learning. This work contributes to the body of knowledge of REET with two methods, quantitative and qualitative evaluated, respectively. Furthermore, we share the pedagogical material used, to enable other educators to apply and possibly tailor the approach.

The coronavirus disease 2019 (COVID-19) pandemic has brought changes to the way medical care is delivered to keep health workers safe while simultaneously managing available resources. The well-being of patients and healthcare workers is crucial and has become a topic of debate as the world faces adjusts to the COVID-19 pandemic. Therefore, there is need to consider innovative methods of delivering medical care. Telehealth and digital health care which is the provision of medical care via Information Communication Technology (ICT) with highspeed telecommunications systems, has increasingly becoming popular in providing medical care services can be adopted to reduce infections during quarantine and social distancing practices. Specifically, by means of document and literature review this paper discusses the role of telehealth and digital care solutions, types and application of telehealth, and current policies for COVID-19. More importantly, findings from the article present the human, infrastructure, and institutional determinants that influence the adoption of telehealth and digital care solutions during the pandemic. The findings discuss how telehealth and digital care technologies can benefit the society. This study provides implications to informs medical staffs on the potential of digital technologies to provide support during and after the pandemic.

User-centred design involves end-users or user groups during all the parts of the development process. The research project Chronic Pain aims to develop a shared decision making application for patients and physicians, addressing individually adapted pain treatment. The project employs a user-centred design process, and in middle of it, Covid-19 pandemic social distancing restrictions were imposed. This paper presents how the user-centred design process together with a patient organisation was transformed to a digital approach and the experiences from performing a remote co-creation user workshop. The digital approximation had a satisfactory result and the main contribution lies in the sharing of recommendations for how to practically apply a remote user-centred design methodology.

BackgroundTeaching is an important professional skill for physicians and providing feedback is an important part of teaching. Medical students can practice their feedback skills by giving each other peer feedback. Therefore, we developed a peer feedback training in which students observed a peer that modelled the use of good feedback principles. Students then elaborated on the modelled feedback principles through peer discussion. This combination of peer modelling and discussing the modelled feedback principles was expected to enhance emulation of the feedback principles compared to (1) only peer modelling and (2) discussing the feedback principles without previous modelling.MethodsIn a quasi-experimental study design, 141 medical students were assigned randomly to three training conditions: peer modelling plus discussion (MD), non-peer modelled example (NM) or peer modelling without discussion (M). Before and after the training, they commented on papers written by peers. These comments served as a pre- and a post-measure of peer feedback. The comments were coded into different functions and aspects of the peer feedback. Non-parametrical Kruskall-Wallis tests were used to check for pre- and post-measure between-group differences in the functions and aspects.ResultsBefore the training, there were no significant between-group differences in feedback functions and aspects. After the training, the MD-condition gave significantly more positive peer feedback than the NM-condition. However, no other functions or aspects were significantly different between the three conditions, mainly because the within-group interquartile ranges were large.ConclusionsThe large interquartile ranges suggest that students differed substantially in the effort placed into giving peer feedback. Therefore, additional incentives may be needed to motivate students to give good feedback. Teachers could emphasise the utility value of peer feedback as an important professional skill and the importance of academic altruism and professional accountability in the peer feedback process. Such incentives may convince more students to put more effort into giving peer feedback.

Transparency in process and its reporting is paramount for establishing the rigor of qualitative studies. However, the CHI conference receives submissions with varying levels of transparency and oftentimes, papers that are more transparent can be inadvertently subjected to more scrutiny in the review process, raising issues of fairness. In this panel, we bring together researchers with diverse qualitative work experiences to present examples of transparency-related initiatives and their corresponding review responses. We aim to work towards setting standards for transparent reporting in qualitative-work submissions and increasing fairness in the review process. We focus on the challenges in achieving transparency in qualitative research and current workarounds to overcome frictions in the reviewing process through engaging discussions involving panelists and the audience.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and &ldquo, obesity/overweight&rdquo, is one of the consequences. &ldquo, Obesity and overweight&rdquo, are one of the major lifestyle diseases that leads to other health conditions, such as cardiovascular diseases (CVDs), chronic obstructive pulmonary disease (COPD), cancer, diabetes type II, hypertension, and depression. It is not restricted within the age and socio-economic background of human beings. The &ldquo, World Health Organization&rdquo, (WHO) has anticipated that 30% of global death will be caused by lifestyle diseases by 2030 and it can be prevented with the appropriate identification of associated risk factors and behavioral intervention plans. Health behavior change should be given priority to avoid life-threatening damages. The primary purpose of this study is not to present a risk prediction model but to provide a review of various machine learning (ML) methods and their execution using available sample health data in a public repository related to lifestyle diseases, such as obesity, CVDs, and diabetes type II. In this study, we targeted people, both male and female, in the age group of &gt, 20 and &lt, 60, excluding pregnancy and genetic factors. This paper qualifies as a tutorial article on how to use different ML methods to identify potential risk factors of obesity/overweight. Although institutions such as &ldquo, Center for Disease Control and Prevention (CDC)&rdquo, and &ldquo, National Institute for Clinical Excellence (NICE)&rdquo, guidelines work to understand the cause and consequences of overweight/obesity, we aimed to utilize the potential of data science to assess the correlated risk factors of obesity/overweight after analyzing the existing datasets available in &ldquo, Kaggle&rdquo, University of California, Irvine (UCI) database&rdquo, and to check how the potential risk factors are changing with the change in body-energy imbalance with data-visualization techniques and regression analysis. Analyzing existing obesity/overweight related data using machine learning algorithms did not produce any brand-new risk factors, but it helped us to understand: (a) how are identified risk factors related to weight change and how do we visualize it? (b) what will be the nature of the data (potential monitorable risk factors) to be collected over time to develop our intended eCoach system for the promotion of a healthy lifestyle targeting &ldquo, obesity and overweight&rdquo, as a study case in the future? (c) why have we used the existing &ldquo, UCI&rdquo, datasets for our preliminary study? (d) which classification and regression models are performing better with a corresponding limited volume of the dataset following performance metrics?

[Excerpt] By March 2020, while the entire planet Earth was entering a dark time of pandemia, we communicated in this editorial the trends of J Optom in different bibliometric indices including Impact Factor, SCImago Journal Rank ing, H-index, CiteScore and Source Normalized Impact per Paper. (1) More recently the CiteScore has been reviewed by Else vier to mitigate some short-term trends and J Optom raised even further in its score from 1.65 to 2.3.2 Accord ing to Scoups, this new calculation enforces credibility of the score by only considering peer-review publications, considering a longer window of 4 years instead of 3 and considering the more recent citations in the year of calculation.3 This is only an aspect of the impact of the journal that has increased steadily as it continues to con solidate through different milestones achieved over the last years (4). [...], (undefined)

In this paper, the passing ability of football players is determined by building three generalized additive mixed models that each explains a different aspect of a pass’ success: difficulty, risk and potential. The models are built on data from the 2014–2016 seasons of the Norwegian top division Eliteserien, and their predictive power is tested on the 2017 season. The results provide insight into the factors affecting the success of a pass in Eliteserien. These include the location of the pass, the relationship to previous passes and to situations such as throw-ins, corners, free kicks or tackles, as well as conditions specific to the Eliteserien, such as the time of season and the ground surface type. Finally, the key pass makers in the league are identified.

This paper introduces the application and the results of a fuzzy number based questionnaire used for evaluating lecturers’ performance in a newly launched peer review programme in order to enhance ...

Personalization of the e-learning systems according to the learner’s needs and knowledge level presents the key element in a learning process. E-learning systems with personalized recommendations should adapt the learning experience according to the goals of the individual learner. Aiming to facilitate personalization of a learning content, various kinds of techniques can be applied. Collaborative and social tagging techniques could be useful for enhancing recommendation of learning resources. In this paper, we analyze the suitability of different techniques for applying tag-based recommendations in e-learning environments. The most appropriate model ranking, based on tensor factorization technique, has been modified to gain the most efficient recommendation results. We propose reducing tag space with clustering technique based on learning style model, in order to improve execution time and decrease memory requirements, while preserving the quality of the recommendations. Such reduced model for providing tag-based recommendations has been used and evaluated in a programming tutoring system. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

A dilemma within computer science departments is developing sustainable ways to expand capacity within introductory computer science courses while remaining committed to inclusive practices. Training near-peer mentors for peer code review is one solution. This paper describes the preparation of near-peer mentors for their role, with a focus on regular, consistent feedback via peer code review and inclusive pedagogy. Introductory computer science students provided consistently high ratings of the peer mentors’ knowledge, approachability, and flexibility, and credited peer mentor meetings for their strengthened self-efficacy and understanding. Peer mentors noted the value of videotaped simulations with reflection, discussions of inclusion, and the cohort’s weekly practicum for improving practice. Adaptations of peer mentoring for different types of institutions are discussed. Computer science educators, with hopes of improving the recruitment and retention of underrepresented groups, can benefit fro...

Peer assessment is widely used in educational settings as an alternative evaluation approach. It brings various benefits to the students, increasing engagement and interactivity and fostering critical thinking and reflection. Several platforms for managing the peer review process have been proposed in the literature, but most of them are confined to a particular domain or course and have various limitations related to reliability, reviewer allocation, reputation and training of reviewers or instructor support. In an attempt to address these challenges, we propose an innovative general-purpose peer assessment platform, called LearnEval. In this paper we focus on the student module part of the system, describing its functionalities, pedagogical rationale and implementation details.

It is important that Software Engineering and Information Technology students learn techniques to conceive solutions that are centered on the users. Users are often from many different cultures; hence an awareness of cultural differences is an important concept for students to grasp. Particularly when class sizes are large, access to users that would allow the students to practice User-Centered design principles is not feasible. Different methodologies must be pursued to teach students the principles of design. This paper presents peer review and personas, archetypical users of an application, as techniques for teaching User-Centered conceptual design to a large cohort of students. We provided a persona from a set of six personas, each authored to represent two different cultures (Australian or Vietnamese), to 153 undergraduate students at an Australian university to conceive design solutions for the persona. Later, the students were exposed to all of the personas and then they peer reviewed each other's design artifacts. From the comments left by the students we conclude that the technique has met its learning objectives.

Serious and fatal accidents happen on construction sites every year. However, earlier research indicate that the root of the accidents can often be found in the early phases of the project process. In this paper, we examine what occurs in the early phases of project management in construction that can be harmful to health and safety in the construction phase. The investigation focuses on two main research questions: 1) can health and safety in the construction phase be improved during the early phases of project management, and, if so, 2) what are the main challenges of health and safety in the early phases of project management that need to be addressed in order to do so? The data presented is collected by interviewing regional safety representatives in Norway. They point to three main challenges to health and safety in the early phases of construction projects: 1) lack of competence, 2) lack of prioritization, and 3) lack of consequence. In conclusion, we suggest that educational institutions, construction clients and public authorities all need to play their part to improve the situation.

Coordinating research objectives concurrently with product development and engineering is a challenge in student-run CubeSat projects. The literature review from several universities and the International Council of Systems Engineering (INCOSE) Space Systems Working Group (SSWG) all acknowledge the need for a better methodology. This paper describes findings from a university CubeSat exploratory case study related to team management, reviews and design. Introducing Systems Engineering (SE) tools such as formalized reviews, A3 reports, systemigrams and N2 dependency maps have aided the development process. This was evident through faster development iterations and fewer design confusions. Results show that relocation into a common space based on recommendations from Concurrent Engineering (CE) has improved overall communication and team work. © 2019 The Authors. Published by Elsevier B.V.This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

This is the peer reviewed version which has been published in final form at [DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions., Software testing is crucial in continuous integration (CI). Ideally, at every commit, all the test cases should be executed, and moreover, new test cases should be generated for the new source code. This is especially true in a Continuous Test Generation (CTG) environment, where the automatic generation of test cases is integrated into the continuous integration pipeline. In this context, developers want to achieve a certain minimum level of coverage for every software build. However, executing all the test cases and, moreover, generating new ones for all the classes at every commit is not feasible. As a consequence, developers have to select which subset of classes has to be tested and/or targeted by test‐case generation. We argue that knowing a priori the branch coverage that can be achieved with test‐data generation tools can help developers into taking informed decision about those issues. In this paper, we investigate the possibility to use source‐code metrics to predict the coverage achieved by test‐data generation tools. We use four different categories of source‐code features and assess the prediction on a large data set involving more than 3'000 Java classes. We compare different machine learning algorithms and conduct a fine‐grained feature analysis aimed at investigating the factors that most impact the prediction accuracy. Moreover, we extend our investigation to four different search budgets. Our evaluation shows that the best model achieves an average 0.15 and 0.21 MAE on nested cross‐validation over the different budgets, respectively, on EVOSUITE and RANDOOP. Finally, the discussion of the results demonstrate the relevance of coupling‐related features for the prediction accuracy.

Expert-written product reviews are prevalent and could be in many forms, ranging from short textual descriptions to video-embedded blogs. For consumers, expert reviews can not only optimize their purchase decisions, but also play an important role in facilitating consumer learning. In this paper, we first draw on profession research and propose two focal elements that characterize the content of expert reviews, and then investigate the impact of expert reviews on consumers’ product preferences and information consumption via the lens of preference construction theory and dissonance theory. With describing our experiment design to test the hypotheses, we seek to make contributions to the vast studies of online reviews by characterizing the expert review content, examining the effects of expert review on consumer judgments and offering a new perspective of distinguishing expert reviews and peer reviews in online markets.

Modelling techniques have been part of the software engineering practice for decades. Despite Model-Driven Software Engineering (Mde) being spread in the industry, effective teaching through meaningful use cases remains a challenge. Some guidelines and teaching experiences have been reported that either focus on the content of an Mde course, or on tooling environments designed for students. Furthermore, little emphasis has been put on the usability in the context of Software Language Engineering (Sle), which may lead to technically valid languages, but which are difficult to use. In this paper, we report on our attempt to combine a practical use case for Sle and a structured peer review focusing on the language usability and its tooling environment. By putting students in both the seats of language designers and users, we believe to empower students with suitable technical Sle skills as well as making them aware that a good software language requires more than theoretical validity to be adopted.

This paper describes Readersourcing 2.0, an ecosystem providing an implementation of the Readersourcing approach. Readersourcing is proposed as an alternative to the standard peer review activity that aims to exploit the otherwise lost opinions of readers. To achieve this, Readersourcing 2.0 implements two different models based on the so-called codetermination algorithms. We describe the requirements, present the overall architecture, and show how the end-user can interact with the system. Readersourcing 2.0 will be used in the future to study also other topics, like the idea of sheperding the users to achieve a better quality of the reviews and the differences between a review activity carried out with a single-blind or a double-blind approach., Preprint for the IRCDL 2019 conference

The purpose of this study is to identify factors associated with effective peer-assisted learning (PAL) for nursing students. This review examined studies on PAL in nursing education. The literature was searched using terms including ‘nursing & peer assisted learning,’ ‘nursing & peer learning,’ and ‘nursing & peer teaching.’ Potentially relevant research on PAL was identified, and 12 studies were determined to meet the inclusion criteria. This review includes five qualitative, three mixed-methods, and three experimental studies published on the topic. In the studies reviewed, practicum classes were found to use PAL the most. Students of the same age were most commonly the subjects of PAL, as indicated in six papers. PAL has been suggested to affect participants’ knowledge, self-efficacy, confidence, and anxiety. The findings indicate that interactions between peers promote learning and lead to mutually positive responses, which provide opportunities for self-development. Finally, students’ learning outcomes improve and their confidence in their knowledge and skills increases as they experience the role of student nurse. These findings indicate that PAL can be utilized as an efficient learning method in nursing education programs. However, effective strategies for using PAL to achieve learning objectives and maximize learning outcomes are needed.

With traditional academic work, the process of peer review is seemingly clear - work is refereed as a way of gatekeeping ideas and research contributions, to ensure it is not publicly available until it has passed a test of rigour, originality, clarity and significance to the field. Those with assumed knowledge of the discipline are the said gatekeepers, tasked with assessing the work on the basis of disciplinary knowledge and general research expertise. This often rests on the notion that the research and knowledge are made explicit in the writing. This is problematic for non-traditional academic work, such as screen production and media art, because a key value in this kind of work is the ability to communicate implicitly and differently from what can be articulated within the parameters of written, academic language. This tension between implicit and explicit knowledge claims has been one source of difficulty for evaluating and therefore rewarding creative practice research. In this paper, we draw on a recent gathering of screen production academics, the two-day Sightlines: Filmmaking in the academy festival and conference, to help us discuss the complexities of peer reviewing screen production works for the academy, and to help us point towards possible solutions. We focus specifically on where and in what form the articulation of research might happen to assist the peer reviewing process, where the common approach is to write a research statement that makes explicit the methodologies undertaken and the new knowledge being claimed. This has incited some protest from within the screen production community: for example, how do we account with language for the very thing that is in excess of language, the contribution that finds its unique place outside of language and within the moving image? We therefore also discuss the dialogic relationship between art and writing, and the kinds of relationality that might be created to help make room for the in-articulable'. In short, how research and new knowledge in a screen work might be illuminated, and how an academic peer might therefore evaluate it. We conclude by discussing an approach we are currently taking to develop an online, refereed publication for screen production works, the Sightlines Journal, in response to both the current literature on the topic and the gathering of discipline academics. Given the various contexts in which these questions arise in relation to screen production research (during the writing of a PhD, in the examination process, and in professional environments), we address them accordingly as individual yet interwoven discussions driven by the shared need to find workable solutions to recurring problems. Refereed/Peer-reviewed

This paper analyzes and presents the solar energy research status in the GCC countries using Scopus-database. Its findings may be valuable for researchers, politicians, industry, or decision makers to see how much the participation of the GCC countries in the field of solar energy and how it compares to other countries. The data gathered from Scopus database aided in outlining and identifying the active institutions and researchers in the field of solar energy in the GCC. In terms of the largest contribution, Saudi Arabia has the highest research output (with more than 60% of the published articles in the GCC), followed by the UAE (about 17%) and the remaining percentage is the contribution of the other GCC countries.

ContextThe power of open source software peer review lies in the involvement of virtual communities, especially users who typically do not have a formal role in the development process. As communities grow to a certain extent, how to organize and support the peer review process becomes increasingly challenging. A universal solution is likely to fail for communities with varying characteristics. ObjectiveThis paper investigates differences of peer review practices across different open source software communities, especially the ones engage distinct types of users, in order to offer contextualized guidance for developing open source software projects. MethodComparative case studies were conducted in two well-established large open source communities, Mozilla and Python, which engage extremely different types of users. Bug reports from their bug tracking systems were examined primarily, complemented by secondary sources such as meeting notes, blog posts, messages from mailing lists, and online documentations. ResultsThe two communities differ in the key activities of peer review processes, including different characteristics with respect to bug reporting, design decision making, to patch development and review. Their variances also involve the designs of supporting technology. The results highlight the emerging role of triagers, who bridge the core and peripheral contributors and facilitate the peer review process. The two communities demonstrate alternative designs of open source software peer review and their tradeoffs were discussed. ConclusionIt is concluded that contextualized designs of social and technological solutions to open source software peer review practices are important. The two cases can serve as learning resources for open source software projects, or other types of large software projects in general, to cope with challenges of leveraging enormous contributions and coordinating core developers. It is also important to improve support for triagers, who have not received much research effort yet.

The Scaled Agile Framework (SAFe) has been adopted by a large number of organizations to scale agile to large enterprises that develop software. At the moment, SAFe seems to be the most predominant agile scaling framework. Despite the current popularity of SAFe in the software intensive industry, there exists surprisingly little research on the adoption and usage of SAFe. To study what is known about SAFe with respect to benefits and challenges of its usage, we conducted a multivocal literature review. The preliminary version of the results are presented in this poster version of paper. We identified 48 unique adoption cases in 46 organizations from both peer reviewed and non peer reviewed (grey literature) sources.

Enterprise software needs to be customizable, and the customization needs from a customer are often beyond what the software vendor can predict in advance. In the on-premises era, customers do deep customizations beyond vendor's prediction by directly modifying the vendor's source code and then build and operate it on their own premises. When enterprise software is moving to cloud-based multi-tenant SaaS (Software as a Service), it is no longer possible for customers to directly modify the vendor's source code, because the same instance of code is shared by multiple customers at runtime. Therefore, the question is whether it is still possible to do deep customization on multi-tenant SaaS. In this paper, we give an answer to this question with a novel architecture style to realize deep customization of SaaS using intrusive microservices. We evaluate the approach on an open source online commercial system, and discuss the further research questions to make deep customization applicable in practice. Deep customization of multi-tenant SaaS using intrusive microservices

The subject of this study was the product development project creating a new innovative proof-of-concept (POC) prototype device that could control a connected industrial overhead crane in order to perform automatic or semi-automatic high precision lifts within a limited time frame. The development work focused on innovating a new measuring concept, which was parallel to finding suitable sensors for the application. Furthermore, the project resulted in a closed loop control system with Industrial Internet connected sensors and a user interface for factory workers. The prototyping journey is depicted to illustrate the decisions made during the product development project to contribute to both the pragmatic and the process discussion in the field of Industrial Internet. The purpose of this research was to explore and generate hypotheses for how new applications should be developed for heavy industry connected devices. The research question is: what are the implications of applying agile product development methods, such as Wayfaring, to heavy industrial machinery and Industrial Internet -based problems? The methodologies used in this paper, in addition to developing the device, are case study research and hypotheses generated from case studies. The hypotheses generated include that it is also possible to prototype large size connected machinery with low-cost and in a short time, and investment decisions for heavy Industrial Internet products become easier with concrete data from proof-of-concept prototypes by creating knowledge about the investment risk and the value proposition.

This is the peer reviewed version of the following article: “ Domènech, B., Ferrer, L. and Pastor, R. (201o) Comparison of various approaches to design wind-PV rural electrification projects in remote areas of developing countries. Wiley Interdisciplinary Reviews-Energy and Environment, Desember which has been published in final form at [doi: 10.1002/wene.332]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving." Nowadays, around 1.1 billion people in rural and remote areas of developing countries remain without electricity. Stand-alone projects that combine the wind and photovoltaic generation technologies as well as microgrids and individual supplies for the distribution network are an adequate strategy to reach such isolated regions. However, the design of electrification projects is complex, having to define the best combination of generation and distribution technologies, under a challenging social context and tight technoeconomic resources. In order to ease decision-making, several tools have been developed in the literature and are here reviewed, grouped into three main categories: optimization processes, aiming to minimize project costs subject to technical constraints, through exact or heuristic algorithms; multicriteria processes, using different methods to select the best among a set of predefined scenarios according to economic, technical, social, and environmental criteria; and systematized tools, that have been developed to provide user-friendly interface for their larger dissemination in different regions and contexts. Hence, this paper aims to provide researchers and practitioners an analysis of the advantages and limitations of approaches used over the last decade when addressing the designing of wind and/or photovoltaic electrification projects for extremely poor and isolated areas in developing countries, as well as some areas for further research.

This is a report on the ninth edition of the Conference and Labs of the Evaluation Forum (CLEF 2018), held in early September 2018, in Avignon, France. CLEF was a four day event combining a Conference and an Evaluation Forum. The Conference featured keynotes by Nicholas Belkin, Julio Gonzalo, and Gabriella Pasi, and presentation of 29 peer reviewed research papers covering a wide range of topics in addition to many posters. The Evaluation Forum consisted to ten Labs: CENTRE, CheckThat, DynSe, eRisk, eHealth, ImageCLEF, LifeCLEF, Cultural Microblog Contextualization, PAN, and PIR-CLEF, addressing a wide range of tasks, media, languages, and ways to go beyond standard test collections.

Health care information systems play an important role for communication across the organizational borders of health care services. The electronic health record represents the main entity in the management, exchange and storage of medical information. Health care organizations must adopt strategies for security and privacy risks associated with access to health care information systems, but on the other hand, the information needs to be accessible and readable for authorized health care professionals carrying out patient treatment. This paper presents a literature review on security management in health care information systems. The aim was to analyze descriptions and definitions of information security policy, access control management and the usability of security solutions.

Health care services are facing challenges with a growing ageing population prone to chronic conditions and multi-morbidities. Telemedicine applications have the potential to enhance patient’s safety at home by monitoring of chronic diseases, promoting coping and independence. The research project Patients and Professionals in Productive Teams aims to study patient-centered teamwork across organizational borders, supported by technology. This paper describes the research agenda for a study on how telemedicine follow-up impacts on chronic obstructive pulmonary disease patients’ quality of life and possible effects on patient empowerment, in the health region of Southern Norway. The outcome is expected to describe how telemedicine can be carried out and implemented in daily routines together with a patient-centred health care team with the aim to increase patient safety.

This paper engages with social justice in engineering education based on pedagogical tools aimed at improving analytical reading, writing and critical reflection in course activities. The authors conceptualizes analytical thinking, critical reflection, and web-based peer review as tools for transformation of student learning, and apply these tools as instructions to engineering students studying city planning in Stockholm, Sweden. Students were asked to use the tools to critically analyze the role of national identities, social vis-à-vis technological engineering, and what politics have shaped Swedish society. In studying these aspects of city planning, the authors argue for a shift in attention toward the practices of engineers’ work around issues of social justice, an argument reinforced by the results of textual analysis of student essay reflections on social justice in city planning. The results are a wide range of themes of critical reflection made by students arising from course activities. These included balancing social and environmental justice, like suburban segregation, planning ideals and, in some cases, challenges for the planning profession. We argue that these are valuable lessons for engineers, which can be achieved by combining practical experiences of planning practices with tools for advancing critical and analytical skills of engineering students. By analyzing engineering students’ views on solutions and challenges of addressing social justice in practice, we can improve our understanding of the engineering skills required to work with social justice. In this way, the study complements discussion and critiques of the relationships between society and engineering outlined in the rhetoric of engineering grand challenges, and contributes by discussing new roles for engineers in facing day-to-day challenges working with social justice.

The Wireless Body Area Network (WBAN) has gained popularity as a new technology for e-Health, and is considered as one of the key research areas in computer science and healthcare applications. WBAN collects patients’ data, monitors constantly their physiological parameters, using small implantable or wearable sensors, and communicates these data using wireless communication techniques in short range. WBAN is playing a huge role in improving the quality of healthcare. Still, due to sensitive and concurrent nature of e-Heath systems, current research has showed that designers must take into considerations the security and privacy protection of the data collected by a WBAN to safeguard patients from different exploits or malicious attacks, since e-Health technologies are increasingly connected to the Internet via wireless communications. In this paper we outline the most important security requirements for WBANs. Furthermore, we discuss key security threats to avoid. Finally, we conclude with a summary of security mechanisms to follow that address security and privacy concerns of WBANs, and need to be explored in an increasingly connected healthcare world. This Article is brought to you for free and open access by the Publication and Journals at UBT Knowledge Center.

Human-Computer Interaction (HCI) is dynamic and interdisciplinary. Diverse areas of knowledge contribute to form and advance the state of the art, but also bring different views about how to do research in HCI. In this paper we aim at promoting discussion and increased awareness on different kinds of research by comparing the three HCI waves with concepts of Philosophy of Science and general research paradigms. We believe this awareness can play an important role in improving the fairness of the peer review process and support researchers in positioning themselves and their investigations.