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Introduction: Peer review, a cornerstone of academia, promotes rigor and relevance in scientificpublishing. As educators are encouraged to adopt a more scholarly approach to medical education,peer review is becoming increasingly important. Junior educators both receive the reviews of theirpeers, and are also asked to participate as reviewers themselves. As such, it is imperative for juniorclinician educators to be well-versed in the art of peer reviewing their colleagues’ work. In thisarticle, our goal was to identify and summarize key papers that may be helpful for faculty membersinterested in learning more about the peer-review process and how to improve their reviewing skills. Methods: The online discussions of the 2016-17 Academic Life in Emergency Medicine (ALiEM)Faculty Incubator program included a robust discussion about peer review, which highlighted anumber of papers on that topic. We sought to augment this list with further suggestions by guestexperts and by an open call on Twitter for other important papers. Via this process, we created a listof 24 total papers on the topic of peer review. After gathering these papers, our authorship groupengaged in a consensus-building process incorporating Delphi methods to identify the papers thatbest described peer review, and also highlighted important tips for new reviewers. Results: We found and reviewed 24 papers. In our results section, we present our authorshipgroup’s top five most highly rated papers on the topic of peer review. We also summarize thesepapers with respect to their relevance to junior faculty members and to faculty developers. Conclusion: We present five key papers on peer review that can be used for faculty development fornovice writers and reviewers. These papers represent a mix of foundational and explanatory papersthat may provide some basis from which junior faculty members might build upon as they both undergothe peer-review process and act as reviewers in turn.

Scholarly peer review is crucial to science: it not only determines what is published where, but also, indirectly, who is hired, funded and promoted. Yet, virtually every academic has peer review horror stories. Empirical evidence suggests that "peer review is prejudiced, capricious, inefficient, ineffective, and generally unscientific" [1]. An experiment at a major machine learning conference found that peer review was unreliable highlighted that the outcome of peer review can be very noisy [2, 3]. In May 2019, ACM SIGSOFT launched an initiative to improve the quality of research papers and peer reviews at software engineering venues. It has two main components: empirical standards and recommendations for improving review processes.

Papers describing software are an important part of computational fields of scientific research. These “software papers” are unique in a number of ways, and they require special consideration to improve their impact on the scientific community and their efficacy at conveying important information. Here, we discuss 10 specific rules for writing software papers, covering some of the different scenarios and publication types that might be encountered, and important questions from which all computational researchers would benefit by asking along the way., Author summary Computational researchers have a responsibility to ensure that the software they write stands up to the same scientific scrutiny as traditional research studies. These 10 simple rules make doing so easier by enhancing usability, reproducibility, transparency, and other crucial characteristics that aren’t taught in most computer science or research methods curricula.

The evidence suggests that mentoring is one of useful teaching methods in academic medicine but it is not clear for which outcome mentoring is effective. In this study, the authors investigated the number of original research articles that the participants had published in peer-reviewed English-language journals (as a first or a corresponding author) within one year prior to investigation and what characteristics of the participants who published at least one paper would be like compared to those who did not. In March 2015, the authors recruit early- and mid-career Japanese physicians (238 men and 240 women; mean age 40.6 years old) in a web survey. In total, 23.9% of physicians had published at least one original research article as a first author, 10.0% had published as a corresponding author, and 23.4% had a research mentor. A multivariate logistic regression model adjusting for variables selected at p < 0.15 in univariable models showed that even after adjusting for their motivation levels for clinical research, physicians with a research mentor [odds ratio (OR) 6.68; 95% confidence interval (CI), 3.74-11.93], physicians who obtained DMSc, roughly equivalent to PhD in the West (OR, 2.17; 95% CI, 1.26-3.72), and physicians who worked at teaching hospitals (OR 6.39; 95% CI, 2.54-16.04) were more likely to publish an original paper in a peer-reviewed journal. Having a research mentor or DMSc is associated with an experience of successfully publishing original papers in peer-reviewed journals for young and mid-career physician-researchers.

Sentiment analysis has been widely explored in many text domains, including product reviews, movie reviews, tweets, and so on. However, there are very few studies trying to perform sentiment analysis in the domain of peer reviews for scholarly papers, which are usually long and introducing both pros and cons of a paper submission. In this paper, we for the first time investigate the task of automatically predicting the overall recommendation/decision (accept, reject, or sometimes borderline) and further identifying the sentences with positive and negative sentiment polarities from a peer review text written by a reviewer for a paper submission. We propose a multiple instance learning network with a novel abstract-based memory mechanism (MILAM) to address this challenging task. Two evaluation datasets are constructed from the ICLR open reviews and evaluation results verified the efficacy of our proposed model. Our model much outperforms a few existing models in different experimental settings. We also find the generally good consistency between the review texts and the recommended decisions, except for the borderline reviews.

Background The internet is being widely used for seeking health information. However, there is no consensus on the association between health information seeking on the internet and the use of health care services. Objective We examined the association between health information seeking via the internet and physician visits. In addition, we investigated the association between online health information seeking and the decisions to visit and not to visit a physician. Methods We used the cross-sectional electronic health (eHealth) data of 18,197 participants from the seventh survey of the Tromsø Study (Tromsø 7). The participants were aged ≥40 years and living in Tromsø, Norway. We used logistic regression models to examine the association between online health information seeking and physician visits, the decision to visit a physician, and the decision not to visit a physician, with adjustment for the demographic status, socioeconomic status, and health status of the participants. Results The use of Web search engines was associated with a physician visit. However, the association was moderated by age, and the OR decreased as age increased. The ORs for the use of Web search engines were 1.99 (95% CI 1.94-2.02) and 1.07 (95% CI 1.03-1.12) at ages 40 and 80 years, respectively. The decision to visit a physician was associated with the use of Web search engines (OR 2.95, 95% CI 2.03-4.46), video search engines (OR 1.43, 95% CI 1.21-1.70), and health apps (OR 1.26, 95% CI 1.13-1.42). The association between social media use and the decision to visit a physician was moderated by gender. Women who used social media had 1.42 (95% CI 1.31-1.55) times higher odds of deciding to visit a physician, whereas the decision to visit a physician was not different between men who used social media and those who did not use social media. Conversely, the decision not to visit a physician was associated with the use of Web search engines (OR 2.78, 95% CI 1.92-4.18), video search engines (OR 1.27, 95% CI 1.07-1.51), social media (OR 1.28, 95% CI 1.10-1.49), and health apps (OR 1.20, 95% CI 1.07-1.35). Conclusions Health information found on the internet was positively associated with both the decision to visit a physician and the decision not to visit a physician. However, the association of health information seeking with the decision to visit a physician was slightly stronger than the association with the decision not to visit a physician. This could imply that the use of eHealth services is associated with a resultant increase in physician visits. In summary, our findings suggest that the internet serves as a supplement to health care services rather than as a replacement.

Many studies demonstrate that peer reviewing provides pedagogical benefits such as inspiration and developing expert vision, and changes classroom culture by encouraging reciprocity. However, much large-scale research in peer assessment has focused on MOOCs, where students have short tenures, and is unable to describe how reciprocity-oriented classroom cultures evolve over time. This short paper presents the first long-term analysis of peer reviewing with 304 students, conducted in three large physical classes in a year-long undergraduate series. Surprisingly, this analysis reveals that when students receive better reviews on their work, they write worse reviews in the future. This suggests that while students believe in the reciprocal nature of peer review, they act anti-reciprocally. Therefore, battling the emergent norm of anti-reciprocity is crucial both for system designers and practitioners who use peer assessment.

Background The electronic health record (EHR) has been fully established in all Norwegian hospitals. Patient-accessible electronic health records (PAEHRs) are available to citizens aged 16 years and older through the national health portal Helsenorge. Objective This study aimed at understanding how patients use PAEHRs. Three research questions were addressed in order to explore (1) characteristics of users, (2) patients’ use of the service, and (3) patient experience with the service. Methods We conducted an online survey of users who had accessed their EHR online at least once through the national health portal. Patients from two of the four health regions in Norway were invited to participate. Quantitative data were supplemented by qualitative information. Results A total of 1037 respondents participated in the survey, most of whom used the PAEHR regularly (305/1037, 29.4%) or when necessary (303/1037, 29.2%). Service utilization was associated with self-reported health, age, gender, education, and health care professional background. Patients found the service useful to look up health information (687/778, 88.3%), keep track of their treatment (684/778, 87.9%), prepare for a hospital appointment (498/778, 64.0%), and share documents with their general practitioner (292/778, 37.5%) or family (194/778, 24.9%). Most users found it easy to access their EHR online (965/1037, 93.1%) and did not encounter technical challenges. The vast majority of respondents (643/755, 85.2%) understood the content, despite over half of them acknowledging some difficulties with medical terms or phrases. The overall satisfaction with the service was very high (700/755, 92.7%). Clinical advantages to the patients included enhanced knowledge of their health condition (565/691, 81.8%), easier control over their health status (685/740, 92.6%), better self-care (571/653, 87.4%), greater empowerment (493/674, 73.1%), easier communication with health care providers (493/618, 79.8%), and increased security (655/730, 89.7%). Patients with complex, long-term or chronic conditions seemed to benefit the most. PAEHRs were described as useful, informative, effective, helpful, easy, practical, and safe. Conclusions PAEHRs in Norway are becoming a mature service and are perceived as useful by patients. Future studies should include experimental designs focused on specific populations or chronic conditions that are more likely to achieve clinically meaningful benefits. Continuous evaluation programs should be conducted to assess implementation and changes of wide-scale routine services over time.

Background: Information from ratings sites are increasingly informing patient decisions related to health care and the selection of physicians. Objective: The current study sought to determine the validity of online patient ratings of physicians through comparison with physician peer review. Methods: We extracted 223,715 reviews of 41,104 physicians from 10 of the largest cities in the United States, including 1142 physicians listed as “America’s Top Doctors” through physician peer review. Differences in mean online patient ratings were tested for physicians who were listed and those who were not. Results: Overall, no differences were found between the online patient ratings based upon physician peer review status. However, statistical differences were found for four specialties (family medicine, allergists, internal medicine, and pediatrics), with online patient ratings significantly higher for those physicians listed as a peer-reviewed “Top Doctor” versus those who were not. Conclusions: The results of this large-scale study indicate that while online patient ratings are consistent with physician peer review for four nonsurgical, primarily in-office specializations, patient ratings were not consistent with physician peer review for specializations like anesthesiology. This result indicates that the validity of patient ratings varies by medical specialization.

Background: Audio and video podcasts have gained popularity in recent years. Increasingly, podcasts are being used in the field of medicine as a tool to disseminate information. This format has multiple advantages including highly accessible creation tools, low distribution costs, and portability for the user. However, despite its ongoing use in medical education, there are no data describing factors associated with the success or quality of podcasts. Objective: The goal of the study was to assess the landscape of anesthesia podcasts in Canada and develop a methodology for evaluating the quality of the podcast. To achieve our objective, we identified the scope of podcasts in anesthesia specifically, constructed an algorithmic model for measuring success, and identified factors linked to both successful podcasts and a peer-review process. Methods: Independent reviewers performed a systematic search of anesthesia-related podcasts on iTunes Canada. Data and metrics recorded for each podcast included podcast’s authorship, number posted, podcast series duration, target audience, topics, and social media presence. Descriptive statistics summarized mined data, and univariate analysis was used to identify factors associated with podcast success and a peer-review process. Results: Twenty-two podcasts related to anesthesia were included in the final analysis. Less than a third (6/22=27%) were still active. The median longevity of the podcasts’ series was just 13 months (interquartile range: 1-39 months). Anesthesiologists were the target audience for 77% of podcast series with clinical topics being most commonly addressed. We defined a novel algorithm for measuring success: Podcast Success Index. Factors associated with a high Podcast Success Index included podcasts targeting fellows (Spearman R=0.434; P=.04), inclusion of professional topics (Spearman R=0.456-0.603; P=.01-.03), and the use of Twitter as a means of social media (Spearman R=0.453;P=.03). In addition, more than two-thirds (16/22=73%) of podcasts demonstrated evidence of peer review with podcasts targeting anesthesiologists most strongly associated with peer-reviewed podcasts (Spearman R=0.886; P=.004) Conclusions: We present the first report on the scope of anesthesia podcasts in Canada. We have developed a novel tool for assessing the success of an anesthesiology podcast series and identified factors linked to this success measure as well as evidence of a peer-review process for a given podcast. To enable advancement in this area of anesthesia e-resources, podcast creators and users should consider factors associated with success when creating podcasts. The lack of these aspects may be associated with the early demise of a podcast series. [JMIR Med Educ 2016;2(2):e14]

Peer reviewing is a central component in the scientific publishing process. We present the first public dataset of scientific peer reviews available for research purposes (PeerRead v1),1 providing an opportunity to study this important artifact. The dataset consists of 14.7K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR. The dataset also includes 10.7K textual peer reviews written by experts for a subset of the papers. We describe the data collection process and report interesting observed phenomena in the peer reviews. We also propose two novel NLP tasks based on this dataset and provide simple baseline models. In the first task, we show that simple models can predict whether a paper is accepted with up to 21% error reduction compared to the majority baseline. In the second task, we predict the numerical scores of review aspects and show that simple models can outperform the mean baseline for aspects with high variance such as ‘originality’ and ‘impact’.

Peer reviews form an essential part of scientific communications. Research papers and proposals are reviewed by several peers before they are finally accepted or rejected for publication and funding, respectively. With the steady increase in the number of research domains, scholarly venues (journal and/or conference), researchers, and papers, managing the peer review process is becoming a daunting task. Application of recommender systems to assist peer reviewing is, therefore, being explored and becoming an emerging research area. In this paper, we present a deep learning network based Meta-Review Generation considering peer review prediction of the scholarly article (MRGen). MRGen is able to provide solutions for: (i) Peer review prediction (Task 1) and (ii) Meta-review generation (Task 2). First, the system takes the peer reviews as input and produces a draft meta-review. Then it employs an integrated framework of convolution layer, long short-term memory (LSTM) model, Bi-LSTM model, and attention mechanism to predict the final decision (accept/reject) of the scholarly article. Based on the final decision, the proposed model MRGen incorporates Pointer Generator Network-based abstractive summarization to generate the final meta-review. The focus of our approach is to give a concise meta-review that maximizes information coverage, coherence, readability and also reduces redundancy. Extensive experiments conducted on the PeerRead dataset demonstrate good consistency between the recommended decisions and original decisions. We also compare the performance of MRGen with some of the existing state-ofthe- art multi-document summarization methods. The system also outperforms a few existing models based on accuracy, Rouge scores, readability, non-redundancy, and cohesion.

Replicability tests of scientific papers show that the majority of papers fail replication. Moreover, failed papers circulate through the literature as quickly as replicating papers. This dynamic weakens the literature, raises research costs, and demonstrates the need for new approaches for estimating a study’s replicability. Here, we trained an artificial intelligence model to estimate a paper’s replicability using ground truth data on studies that had passed or failed manual replication tests, and then tested the model’s generalizability on an extensive set of out-of-sample studies. The model predicts replicability better than the base rate of reviewers and comparably as well as prediction markets, the best present-day method for predicting replicability. In out-of-sample tests on manually replicated papers from diverse disciplines and methods, the model had strong accuracy levels of 0.65 to 0.78. Exploring the reasons behind the model’s predictions, we found no evidence for bias based on topics, journals, disciplines, base rates of failure, persuasion words, or novelty words like “remarkable” or “unexpected.” We did find that the model’s accuracy is higher when trained on a paper’s text rather than its reported statistics and that n-grams, higher order word combinations that humans have difficulty processing, correlate with replication. We discuss how combining human and machine intelligence can raise confidence in research, provide research self-assessment techniques, and create methods that are scalable and efficient enough to review the ever-growing numbers of publications—a task that entails extensive human resources to accomplish with prediction markets and manual replication alone.

IntroductionPrevious reviews of mobile messaging for individuals with musculoskeletal pain have shown positive effects on pain and disability. However, the configuration of digital content, method of presentation and interaction, dose and frequency needed for optimal results remain unclear. Patient preferences concerning such systems are also unclear. Addressing these knowledge gaps, incorporating evidence from both experimental and observational studies, may be useful to understand the extent of the relevant literature, and to influence the design and outcomes of future messaging systems. We aim to map information that could be influential in the design of future mobile messaging systems for individuals with musculoskeletal pain conditions, and to summarise the findings of efficacy, effectiveness, and economics derived from both experimental and observational studies.Methods and analysisWe will include studies describing the development and/or use of mobile messaging to support adults (≥18 years) with acute or chronic musculoskeletal pain. We will exclude digital health studies that lack a mobile messaging component, or those targeted at other health conditions unrelated to the bones, muscles and connective tissues, or involving surgical or patients with cancer, or studies involving solely healthy individuals. Our sources of information will be online databases and reference lists of relevant papers. We will include papers published in English in the last 10 years. Two pairs of independent reviewers will screen, select and extract the data, with any disagreements mediated by a third reviewer. We will report the results according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews checklist. We will synthesise the findings in a tabular format and provide a descriptive summary.Ethics and disseminationFormal ethical approval is not required. We will disseminate the findings through publication in a peer-reviewed journal, relevant conferences, and relevant consumer forums.Trial registrationOpen Science Framework https://osf.io/8mzya; DOI: 10.17605/OSF.IO/8MZYA.

This paper investigates the possible benefits as well as the overall impact on the behaviour of students within a learning environment, which is based on double-blinding reviewing of freely selected peer works. Fifty-six sophomore students majoring in Informatics and Telecommunications Engi-neering volunteered to participate in the study. The experiment was conducted in a controlled environment, according to which students were divided into three groups of different conditions: control, usage data, usage and ranking data. No additional information was made available to students in the control condition. The students that participated in the other two conditions were provided with their usage information (logins, peer work viewed/reviewed, etc.), while members of the last group could also have access to ranking information about their positioning in their group, based on their usage data. According to our findings, students’ performance between the groups were comparable, however, the Ranking group revealed differences in the resulted behavior among its members. Specifically, awareness of ranking information mostly benefited students which were relatively in favor of ranking, motivating them to further engage and perform better than the rest of the group members.

Introduction Writing a thesis or dissertation during a postgraduate medical or surgical training is a part of curriculum, which is considered a major component of training during residency. We aimed to analyze and find out the fate of thesis of our residents, their outcome, and impact. We have also evaluated the reasons for not publishing the thesis in a peer-reviewed paper. Methods This study was conducted at a neurosurgical department of a premier training institute. PubMed and Google Scholar were searched for the topics of thesis and names of residents to find out whether any paper was published similar to topic of thesis. The faculties and residents were also personally contacted to evaluate the publication status of their thesis. A questionnaire was sent to the students who did not publish their thesis to find out the reasons for not submitting for publication. Results Total 56 residents submitted 85 thesis. The conversion rate to peer-reviewed publication was 32.5%. There was decreasing trend of conversion to publication over 10 years. The most common reasons for not publishing was a bad design of study, or deemed worthless for publication. Conclusion Conversion rate of thesis to paper is poor. In addition to writing thesis, candidates should be encouraged to have publications in indexed journal as full-length articles. Such publications carry more significance in long-term career of a resident.

The social aspect of sustainable and ‘clean’ production/manufacturing technologies is researched and understood by means of Social Life Cycle Assessment (SLCA), a Life Cycle Sustainability Assessment (LCSA) tool, which is still in its infancy. In this paper, a search for all peer-reviewed publications on applied Social LCA, which have appeared in scientific journals, between O’Brien et al (1996) and the latest one at the time of writing (April 2018), was carried out, using Scopus as the repository and using “S-LCA” OR “SLCA” OR “Social LCA” OR “Social Life Cycle Assessment” as search-phrases in title, abstract and keywords of publications, separately. Overall, 213 publications were unearthed, and the trend shows that there has been a near-exponential increase over time. A little over 55% of these publications – 121 to be precise - were applications of S-LCA – often in combination with environmental-LCA and life cycle costing analysis, in an LCSA. This paper discusses the contributions of a selected subset of these 121 publications to the body of S-LCA knowledge, with the focus being restricted to applications in developing and transition economies of the world, on the premise that there is a more urgent need to understand social aspects of production and manufacturing in these parts of the world. A SWOT analysis of S-LCA has been carried out towards the end. There is a consensus among many researchers that while LCC and E-LCA have matured a lot over time, S-LCA, the newest of the trio, is evolving slowly to become a harmonised tool which can serve as an effective complement to the aforesaid two, in life cycle sustainability assessments of products and processes in industry.

Scientific papers are complex and understanding the usefulness of these papers requires prior knowledge. Peer reviews are comments on a paper provided by designated experts on that field and hold a substantial amount of information, not only for the editors and chairs to make the final decision, but also to judge the potential impact of the paper. In this paper, we propose to use aspect-based sentiment analysis of scientific reviews to be able to extract useful information, which correlates well with the accept/reject decision. While working on a dataset of close to 8k reviews from ICLR, one of the top conferences in the field of machine learning, we use an active learning framework to build a training dataset for aspect prediction, which is further used to obtain the aspects and sentiments for the entire dataset. We show that the distribution of aspect-based sentiments obtained from a review is significantly different for accepted and rejected papers. We use the aspect sentiments from these reviews to make an intriguing observation, certain aspects present in a paper and discussed in the review strongly determine the final recommendation. As a second objective, we quantify the extent of disagreement among the reviewers refereeing a paper. We also investigate the extent of disagreement between the reviewers and the chair and find that the inter-reviewer disagreement may have a link to the disagreement with the chair. One of the most interesting observations from this study is that reviews, where the reviewer score and the aspect sentiments extracted from the review text written by the reviewer are consistent, are also more likely to be concurrent with the chair's decision., Comment: Accepted in JCDL'20

Background Productive faculty are key to generating new knowledge and advancing pharmacy practice. The work environments of academic pharmacists are critical to their vitality, commitment, and longevity. Objectives To (1) identify correlates of faculty scholarly productivity and teaching effectiveness, considering personal and environmental characteristics; (2) determine the relationship between a faculty's perception of organizational citizenship behaviors they witness with the organizational culture of their employing college/school of pharmacy; and (3) describe the relationship between organizational climate, job satisfaction, and commitment of academic pharmacists. Methods A self-administered survey was disseminated to a random sample of U.S. academic pharmacists acquired from AACP list-servs. The survey measured perceptions of their organization's culture, the organizational citizenship behaviors they witness at their institution, their job satisfaction, teaching load and productivity, and scholarly productivity based upon peer-reviewed scholarly papers accepted. Both bivariate and multivariate (regression) procedures were employed to identify factors most responsible for explaining academic pharmacist's work environment. Results Responses were received from 177 of 600 survey recipients. Faculty reported having had accepted 10.9 ± 13.6 papers in peer-reviewed journals during the previous 5 years, with most of those in journals with relatively low Impact Factor scores. Faculty productivity was related to type of academic institution employed, teaching effectiveness, job satisfaction, and other factors. Organizational citizenship behaviors and organizational culture was seen similarly by faculty of varied ranks and experience levels. Commitment to remain at the current college/school of pharmacy was highly associated with culture, climate, and job satisfaction conditions. Conclusions The results provided evidence for a strong connection or nexus between teaching and research effectiveness. Organizational culture of academic pharmacy programs is highly important for faculty vitality and commitment. The findings should be helpful for academic leaders in devising programs for mentoring, development, and retention of faculty.

Despite compelling evidence of its potential effectiveness, uptake of self and peer assessment in higher education has been slower than expected. As with other assessment practices, self and peer assessment is ultimately enabled, or inhibited, by the actions of individual academics. This paper explores what academics see as the benefits and challenges of implementing self and peer assessment, through the analysis of interviews with 13 Australian academics. Thematic analysis of our qualitative data identified seven themes of benefits and five challenges. Our academics showed strong belief in the power of self and peer assessment as formative assessment, contrary to past literature which has focussed on the accuracy of students’ marking. This paper therefore brings insights as to not only what academics value about self and peer assessment but also identifies potential inhibitors in practice. Recommendations are made about improving the design and implementation of self and peer assessment in higher...

Background: This paper explores telemonitoring/mhealth approaches as a promising real time and contextual strategy in overhauling HIV and TB interventions quality access and uptake, retention,adherence and coverage impact in endemic and prone-epidemic prevention and control in sub-Sahara Africa. Methods: The scoping review method was applied in acknowledged journals indexing platforms including Medline, Embase, Global Health, PubMed, MeSH PsycInfo, Scopus and Google Scholar to identify relevant articles pertaining to telemonitoring as a proxy surrogate method in reinforcing sustainability of HIV/TB prevention/treatment interventions in sub-Saharan Africa. Full papers were assessed and those selected that fosters evidence on telemonitoring/mhealth diagnosis, treatment approaches and strategies in HIV and TB prevention and control were synthesized and analyzed. Results: We found telemonitoring/mhealth approach as a more efficient and sustained proxy in HIV and TB risk reduction strategies for early diagnosis and prompt quality clinical outcomes. It can significantly contribute to decreasing health systems/patients cost, long waiting time in clinics, hospital visits, travels and time off/on from work. Improved integrated HIV and TB telemonitoring systems sustainability hold great promise in health systems strengthening including patient centered early diagnosis and care delivery systems, uptake and retention to medications/services and improving patients’ survival and quality of life. Conclusion: Telemonitoring/mhealth (electronic phone text/video/materials messaging)acceptability, access and uptake are crucial in monitoring and improving uptake, retention,adherence and coverage in both local and national integrated HIV and TB programs and interventions. Moreover, telemonitoring is crucial in patient-providers-health professional partnership, real-time quality care and service delivery, antiretroviral and anti-tuberculous drugs improvement, susceptibility monitoring and prescription choice, reinforcing cost effective HIV and TB integrated therapy model and survival rate.

Writing in these pages, Noland and colleagues recently proposed a methodology for cost-benefit analysis of ‘Road Diets’ (re-design of the cross-section of a four-lane arterial). On the basis of the proposed procedures, the authors conclude that a Road Diet of an empirical case study (in New Brunswick, New Jersey, USA) would provide ‘overwhelming’ benefits. The study team has employed similarly unambiguous language in statements in other public fora. In this paper, I do not take a view of whether Road Diets are in general desirable or not (which will depend heavily on local context). Rather, I demonstrate here that the specification of benefits and costs in the proposed methodology is systematically biased (upwards in the case of ‘benefits’ and downwards in the case of ‘costs’). I also show that the authors mis-interpret public opinion regarding the proposed Road Diet; general public opinion cannot be known on the basis of the evidence that is presented to readers. Finally, it has been previously shown that transportation planners tend to, on average, systematically under-estimate costs and over-estimate benefits. While the authors’ motivations during the study at issue cannot be known, the systematic bias in specifying costs and benefits is consistent with Flyvbjerg’s ‘political-economic hypothesis’, in which it is theorized that planners strategically misrepresent costs and benefits in order to increase the likelihood of a politically-preferred project being advanced. Flyvbjerg suggests making independent peer reviews publicly available as part of a strategy to encourage accountability through transparency; this is the spirit in which the present paper is disseminated.

Source at http://www.jocet.org/. As the challenges associated with sustainability, urbanization, life quality and demography become more imminent, companies are adapting to the changing requirements by means of revised strategic approaches. Thus, enterprises are increasingly deviating from the traditionally absolute priority of maximizing total return for shareholders. While this priority is still important, businesses are also looking at the total societal impact (TSI), which represents a collection of measures and assessments that incorporate the economic, social and environmental impacts of their products and services [1]. This paper focuses on the compound influence that TSI may have within the energy domain. In particular, the business opportunities resulting from the Horizon 2020 funded project INVADE are being discussed but seen from the perspective of a socially responsible corporate strategy. Referring to discussions, analyses and undertaken initiatives this paper concludes that business models which incorporate environmentally friendly, local and social and fair energy are capable of accelerating business growth for the concerned companies.

More than 40% of the world’s population still relies on traditional biomass for their cooking needs. A shift to advanced cookstoves can bring significant health and environmental benefits, but only with near exclusive use which requires significant changes in users’ behaviours. Since the emergence of the Global Alliance for Clean Cookstoves (now the Clean Cooking Alliance) in 2011, more attention has been directed to consumer and demand side factors in clean cookstove adoption and efforts to better understand individuals’ behaviours, household dynamics and decision making around the adoption of clean cookstoves and fuels have increased. This paper presents a review of the academic literature (2013–2020) and aims to identify the most successful interventions of behaviour change techniques in the adoption of improved cookstoves as well as the most common barriers to success cited in the literature. The study sourced 40 peer reviewed published academic papers from spring 2013 to summer 2020, and identified the following most commonly used behaviour change techniques in the adoption of improved cookstoves: Shaping Knowledge (n = 19), Reward & Threat (n = 13), Social Support (n = 9), Comparisons (n = 4), Identity/Self-Belief (n = 4), Regulation (n = 0), Change in the Physical Environment (n = 2), Goals & Planning (n = 6). Based on these results, we present gaps in the literature and provide policy recommendations to promote the adoption and continued use of improved cookstoves.

Publication and researcher bias is common in software engineering experiments.Our model shows how these biases lead to a high proportion of incorrect results.Increased statistical power is a key factor to improve the trustworthiness. ContextThe trustworthiness of research results is a growing concern in many empirical disciplines. AimThe goals of this paper are to assess how much the trustworthiness of results reported in software engineering experiments is affected by researcher and publication bias, given typical statistical power and significance levels, and to suggest improved research practices. MethodFirst, we conducted a small-scale survey to document the presence of researcher and publication biases in software engineering experiments. Then, we built a model that estimates the proportion of correct results for different levels of researcher and publication bias. A review of 150 randomly selected software engineering experiments published in the period 20022013 was conducted to provide input to the model. ResultsThe survey indicates that researcher and publication bias is quite common. This finding is supported by the observation that the actual proportion of statistically significant results reported in the reviewed papers was about twice as high as the one expected assuming no researcher and publication bias. Our models suggest a high proportion of incorrect results even with quite conservative assumptions. ConclusionResearch practices must improve to increase the trustworthiness of software engineering experiments. A key to this improvement is to avoid conducting studies with unsatisfactory low statistical power.

This paper explores the application of learning designs featuring formalised and structured technology enhanced peer learning. These include student produced learning elements, peer review discussions and peer assessment in the BSc/MSc level summer course Restoration of European Ecosystems and Freshwaters (REEF), the Master thesis preparation seminars for the Master of Public Health (MPH) and the MOOC course Global Environmental Management (GEM). The application of student produced learning elements and peer review discussions is investigated by analyzing quotes from course evaluations and performing focus group interviews. The application of peer assessment is investigated by analyzing the agreement of peer assessment between students assessing the same assignment. Our analyses confirm previous research on the value of peer learning and peer assessment and we argue that there could also be a huge benefit from developing learning design patterns that facilitate informal peer learning and reinforce knowledge sharing practices. This paper explores the application of learning designs featuring formalised and structured technology enhanced peer learning. These include student produced learning elements, peer review discussions and peer assessment in the BSc/MSc level summer course Restoration of European Ecosystems and Freshwaters (REEF), the Master thesis preparation seminars for the Master of Public Health (MPH) and the MOOC course Global Environmental Management (GEM). The application of student produced learning elements and peer review discussions is investigated by analyzing quotes from course evaluations and performing focus group interviews. The application of peer assessment is investigated by analyzing the agreement of peer assessment between students assessing the same assignment. Our analyses confirm previous research on the value of peer learning and peer assessment and we argue that there could also be a huge benefit from developing learning design patterns that facilitate informal peer learning and reinforce knowledge sharing practices.

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.

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.

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.

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?

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 ...

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.

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.

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