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Increasingly, scholarly articles contain URI references to “web at large” resources including project web sites, scholarly wikis, ontologies, online debates, presentations, blogs, and videos. Authors reference such resources to provide essential context for the research they report on. A reader who visits a web at large resource by following a URI reference in an article, some time after its publication, is led to believe that the resource’s content is representative of what the author originally referenced. However, due to the dynamic nature of the web, that may very well not be the case. We reuse a dataset from a previous study in which several authors of this paper were involved, and investigate to what extent the textual content of web at large resources referenced in a vast collection of Science, Technology, and Medicine (STM) articles published between 1997 and 2012 has remained stable since the publication of the referencing article. We do so in a two-step approach that relies on various well-established similarity measures to compare textual content. In a first step, we use 19 web archives to find snapshots of referenced web at large resources that have textual content that is representative of the state of the resource around the time of publication of the referencing paper. We find that representative snapshots exist for about 30% of all URI references. In a second step, we compare the textual content of representative snapshots with that of their live web counterparts. We find that for over 75% of references the content has drifted away from what it was when referenced. These results raise significant concerns regarding the long term integrity of the web-based scholarly record and call for the deployment of techniques to combat these problems. [ABSTRACT FROM AUTHOR]

The last several decades have witnessed a shift in the way in which news is delivered and consumed by users. With the growth and advancements in mobile technologies, the Internet, and Web 2.0 technologies users are not only consumers of news, but also producers of online content. This has resulted in a novel and highly participatory cyber-physical news awareness ecosystem that fosters digital activism, in which volunteers contribute content to online communities. While studies have examined the various components of this news awareness ecosystem, little is still known about how news media coverage (and in particular digital media) impacts digital activism. In order to address this challenge and develop a greater understanding of it, this paper focuses on a specific form of digital activism, that of the production of digital geographical content through crowdsourcing efforts. Using refugee camps from around the world as a case study, we examine the relationship between news coverage (via Google news), search trends (via Google trends) and user edit contribution patterns in OpenStreetMap, a prominent geospatial data crowdsourcing platform. In addition, we compare and contrast these patterns with user edit patterns in Wikipedia, a well-known non-geospatial crowdsourcing platform. Using Google news and Google trends to derive a measure of thematic public awareness, our findings indicate that digital activism bursts tend to take place during periods of sustained build-up of public awareness deficit or surplus. These findings are in line with two prominent mass communication theories: agenda setting and corrective action, and suggest the emergence of a novel stimulus-awareness-activism framework in today’s participatory digital age. Moreover, these findings further complement existing research examining the motivational factors that drive users to contribute to online collaborative communities. This paper brings us one step closer to understanding the underlying mechanisms that drive digital activism in particular in the geospatial domain. [ABSTRACT FROM AUTHOR]

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user’s credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method. [ABSTRACT FROM AUTHOR]

Miniaturization of computer hardware and the demand for network capable devices has resulted in the emergence of a new class of technology called wearable computing. Wearable devices have many purposes like lifestyle support, health monitoring, fitness monitoring, entertainment, industrial uses, and gaming. Wearable devices are hurriedly being marketed in an attempt to capture an emerging market. Owing to this, some devices do not adequately address the need for security. To enable virtualization and connectivity wearable devices sense and transmit data, therefore it is essential that the device, its data and the user are protected. In this paper the use of novel Integrated Circuit Metric (ICMetric) technology for the provision of security in wearable devices has been suggested. ICMetric technology uses the features of a device to generate an identification which is then used for the provision of cryptographic services. This paper explores how a device ICMetric can be generated by using the accelerometer and gyroscope sensor. Since wearable devices often operate in a group setting the work also focuses on generating a group identification which is then used to deliver services like authentication, confidentiality, secure admission and symmetric key generation. Experiment and simulation results prove that the scheme offers high levels of security without compromising on resource demands. [ABSTRACT FROM AUTHOR]

This paper examined, with a behavioral paradigm, to what extent people choose to view stimuli that portray death, violence or harm. Based on briefly presented visual cues, participants made choices between highly arousing, negative images and positive or negative alternatives. The negative images displayed social scenes that involved death, violence or harm (e.g., war scene), or decontextualized, close-ups of physical harm (e.g., mutilated face) or natural threat (e.g., attacking shark). The results demonstrated that social negative images were chosen significantly more often than other negative categories. Furthermore, participants preferred social negative images over neutral images. Physical harm images and natural threat images were not preferred over neutral images, but were chosen in about thirty-five percent of the trials. These results were replicated across three different studies, including a study that presented verbal descriptions of images as pre-choice cues. Together, these results show that people deliberately subject themselves to negative images. With this, the present paper demonstrates a dynamic relationship between negative information and behavior and advances new insights into the phenomenon of morbid curiosity. [ABSTRACT FROM AUTHOR]

The article discusses rules for considering regarding preprint submission of scientific work in journals. Topics include analysis of published papers undertaken by cell biologist Stephen Royle for estimating the average time from first submission to publication, data mining of the written content for making it better utilizing the knowledge, and encouraging authors to licenses and formats for facilitating reuse while retaining copyright to their work.

The ability to produce timely and accurate flu forecasts in the United States can significantly impact public health. Augmenting forecasts with internet data has shown promise for improving forecast accuracy and timeliness in controlled settings, but results in practice are less convincing, as models augmented with internet data have not consistently outperformed models without internet data. In this paper, we perform a controlled experiment, taking into account data backfill, to improve clarity on the benefits and limitations of augmenting an already good flu forecasting model with internet-based nowcasts. Our results show that a good flu forecasting model can benefit from the augmentation of internet-based nowcasts in practice for all considered public health-relevant forecasting targets. The degree of forecast improvement due to nowcasting, however, is uneven across forecasting targets, with short-term forecasting targets seeing the largest improvements and seasonal targets such as the peak timing and intensity seeing relatively marginal improvements. The uneven forecasting improvements across targets hold even when “perfect” nowcasts are used. These findings suggest that further improvements to flu forecasting, particularly seasonal targets, will need to derive from other, non-nowcasting approaches. [ABSTRACT FROM AUTHOR]

This paper proposes a method to predict fluctuations in the prices of cryptocurrencies, which are increasingly used for online transactions worldwide. Little research has been conducted on predicting fluctuations in the price and number of transactions of a variety of cryptocurrencies. Moreover, the few methods proposed to predict fluctuation in currency prices are inefficient because they fail to take into account the differences in attributes between real currencies and cryptocurrencies. This paper analyzes user comments in online cryptocurrency communities to predict fluctuations in the prices of cryptocurrencies and the number of transactions. By focusing on three cryptocurrencies, each with a large market size and user base, this paper attempts to predict such fluctuations by using a simple and efficient method. [ABSTRACT FROM AUTHOR]

Research utilizing repeated-measures such as daily assessments with self-report and/or objective measures [e.g., physical activity (PA) monitors] are important in understanding health behaviors and informing practice and policy. However, studies that utilize daily assessment often encounter issues with attrition and non-compliance. The current research yielded high levels of retention and adherence with both self-report and objective daily measures. The purpose of this paper is to highlight and discuss strategies utilized in maximizing retention, minimizing missing data, and some lessons learned from the research experience. Fifty community participants took part in a 4-week study utilizing both daily self-report questionnaires and daily use of PA monitors (Fitbit One™). This study focused on typical daily PA and was not an intervention study (e.g., participants were not randomized nor asked to change their PA behavior). Participants completed the study in two waves (wave 1 n = 10, wave 2 n = 40). The research team utilized several retention strategies including automating the data collection process, a prorated incentive structure, having a dedicated and responsive study staff, and utilizing the 2-wave process to optimize data collection during the 2nd wave. The study had 100% retention and generally positive anonymous feedback post-study. Overall, participants completed the vast majority of daily surveys (97%) and wore their Fitbits (for at least part of the day) on almost all days (99.57%) of the study, although there were individual differences. The strategies discussed and lessons learned may be useful to other researchers using daily measurements for whom adherence and retention are important issues. Future research employing these strategies in different populations, with different measurements, and for longer durations is warranted to determine generalizability. [ABSTRACT FROM AUTHOR]

Ultrasound is an efficacious, versatile and affordable imaging technique in emergencies, but has limited utility without expert interpretation. Telesonography, in which experts may remotely support the use of ultrasound through a telecommunications link, may broaden access to ultrasound and improve patient outcomes, particularly in remote settings. This review assesses the literature regarding telesonography in emergency medicine, focussing on evidence of feasibility, diagnostic accuracy and clinical utility. A systematic search was performed for articles published from 1946 to February 2017 using the Cochrane, Medline, EMBASE, and CINAHL databases. Further searches utilising Scopus, Google Scholar, and citation lists were conducted. 4388 titles were identified and screened against inclusion criteria which resulted in the inclusion of 28 papers. These included feasibility, diagnostic accuracy and clinical pilot studies. Study design, methodology and quality were heterogeneous. There was good evidence of feasibility from multiple studies. Where sufficient bandwidth and high quality components were used, diagnostic accuracy was slightly reduced by image transmission. There was evidence of clinical utility in remote hospitals and low-resource settings, although reliability was infrequently reported. Further exploratory research is required to determine minimum requirements for image quality, bandwidth, frame rate and to assess diagnostic accuracy. Clinical trials in remote settings are justifiable. Telecommunication options will depend on local requirements; no one system conveys universal advantages. The methodological quality of research in this field must improve: studies should be designed to minimise bias, and must include details of their methods to allow replication. Analysis of cost effectiveness and sustainability should be provided. [ABSTRACT FROM AUTHOR]

In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM) framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The novel combination of our proposed adaptive crawler and our stream division/recombination technique provides significant gains in event recall (44.44%) and event precision (9.57%). The addition of these sub-events or pieces, allows us to get closer to solving the event puzzle. [ABSTRACT FROM AUTHOR]

Lately, we see that Internet of things (IoT) is introduced in medical services for global connection among patients, sensors, and all nearby things. The principal purpose of this global connection is to provide context awareness for the purpose of bringing convenience to a patient’s life and more effectively implementing clinical processes. In health care, monitoring of biosignals of a patient has to be continuously performed while the patient moves inside and outside the hospital. Also, to monitor the accurate location and biosignals of the patient, appropriate mobility management is necessary to maintain connection between the patient and the hospital network. In this paper, a binding update scheme on PMIPv6, which reduces signal traffic during location updates by Virtual LMA (VLMA) on the top original Local Mobility Anchor (LMA) Domain, is proposed to reduce the total cost. If a Mobile Node (MN) moves to a Mobile Access Gateway (MAG)-located boundary of an adjacent LMA domain, the MN changes itself into a virtual mode, and this movement will be assumed to be a part of the VLMA domain. In the proposed scheme, MAGs eliminate global binding updates for MNs between LMA domains and significantly reduce the packet loss and latency by eliminating the handoff between LMAs. In conclusion, the performance analysis results show that the proposed scheme improves performance significantly versus PMIPv6 and HMIPv6 in terms of the binding update rate per user and average handoff latency. [ABSTRACT FROM AUTHOR]

Mobile cloud computing, which integrates the cloud computing techniques into the mobile environment, is regarded as one of the enabler technologies for 5G mobile wireless networks. There are many sporadic spare resources distributed within various devices in the networks, which can be used to support mobile cloud applications. However, these devices, with only a few spare resources, cannot support some resource-intensive mobile applications alone. If some of them cooperate with each other and share their resources, then they can support many applications. In this paper, we propose a resource cooperative provision mode referred to as "Crowd-funding", which is designed to aggregate the distributed devices together as the resource provider of mobile applications. Moreover, to facilitate high-efficiency resource management via dynamic resource allocation, different resource providers should be selected to form a stable resource coalition for different requirements. Thus, considering different requirements, we propose two different resource aggregation models for coalition formation. Finally, we may allocate the revenues based on their attributions according to the concept of the "Shapley value" to enable a more impartial revenue share among the cooperators. It is shown that a dynamic and flexible resource-management method can be developed based on the proposed Crowd-funding model, relying on the spare resources in the network. [ABSTRACT FROM AUTHOR]

Biobanks have evolved, and their governance procedures have undergone important transformations. Our paper examines this issue by focusing on the perspective of the professionals working in management or scientific roles in research-based biobanks, who have an important impact on shaping these transformations. In particular, it highlights that recent advances in molecular medicine and genomic research have raised a range of ethical, legal and societal implications (ELSI) related to biobank-based research, impacting directly on regulations and local practices of informed consent (IC), private-public partnerships (PPPs), and engagement of participants. In our study, we investigate the ways that these concerns influence biobanking practices and assess the level of satisfaction of the cross-national biobanking research communities with the ELSI related procedures that are currently in place. We conducted an online survey among biobankers and researchers to investigate secondary use of data, informing and/or re-contacting participants, sharing of data with third parties from industry, participant engagement, and collaboration with industrial partners. Findings highlight the need for a more inclusive and transparent biobanking practice where biobanks are seen in a more active role in providing information and communicating with participants; the need to improve the current IC procedures and the role of biobanks in sharing of samples and data with industry partners and different countries, and the need for practical, tangible and hands-on ethical and legal guidance. [ABSTRACT FROM AUTHOR]

Heterogeneous mobile authentication is a crucial technique to securely retrieve the resource of e-healthcare cloud servers which are commonly implemented in a public key Infrastructure (PKI). Conventionally, a mobile data user can utilize a self-chosen password along with a portable device to request the access privilege of clouds. However, to validate the membership of users, a cloud server usually has to make use of a password table, which not only increases the burden of management, but also raises the possibility of information leakage. In this paper, we propose a secure heterogeneous mobile authentication and key agreement scheme for e-healthcare cloud systems. In our system structure, an e-healthcare cloud server of traditional PKIs does not have to store a password table. A legitimate data user only possesses a security token hardware and keeps an offline updatable password without using any private key. Our scheme is classified into the category of dynamic ID authentication techniques, since a data user is able to preserve his/her anonymity during authentication processes. We formally prove that the proposed mechanism fulfills the essential authenticated key exchange (AKE) security and owns lower computational costs. To further ensure the practical application security, an automatic security validation tool called AVISPA is also adopted to analyze possible attacks and pitfalls of our designed protocol. [ABSTRACT FROM AUTHOR]

PubMed is a free search engine for biomedical literature accessed by millions of users from around the world each day. With the rapid growth of biomedical literature—about two articles are added every minute on average—finding and retrieving the most relevant papers for a given query is increasingly challenging. We present Best Match, a new relevance search algorithm for PubMed that leverages the intelligence of our users and cutting-edge machine-learning technology as an alternative to the traditional date sort order. The Best Match algorithm is trained with past user searches with dozens of relevance-ranking signals (factors), the most important being the past usage of an article, publication date, relevance score, and type of article. This new algorithm demonstrates state-of-the-art retrieval performance in benchmarking experiments as well as an improved user experience in real-world testing (over 20% increase in user click-through rate). Since its deployment in June 2017, we have observed a significant increase (60%) in PubMed searches with relevance sort order: it now assists millions of PubMed searches each week. In this work, we hope to increase the awareness and transparency of this new relevance sort option for PubMed users, enabling them to retrieve information more effectively. [ABSTRACT FROM AUTHOR]

Background: With widespread use of the internet, lifestyle and dietary data collection can now be facilitated using online questionnaires as opposed to paper versions. We have developed a graphical food frequency assessment app (eNutri), which is able to assess dietary intake using a validated food frequency questionnaire (FFQ) and provide personalised nutrition advice. FFQ user acceptance and evaluation have not been investigated extensively and only a few studies involving user acceptance of nutrition assessment and advice apps by older adults are published. Methods: A formative study with 20 participants (including n = 10 ≥60 years) assessed the suitability of this app for adults and investigated improvements to its usability. The outcomes of this formative study were applied to the final version of the application, which was deployed in an online study (EatWellUK) with 324 participants (including n = 53 ≥60 years) in the UK, using different devices (smartphones, tablets and laptops/desktops). Completion times were based on browser timestamps and usability was measured using the System Usability Scale (SUS), scoring between 0 and 100. Products with a SUS score higher than 70 are considered to be good. Results: In the EatWellUK study, SUS score median (n = 322) was 77.5 (IQR 15.0). Out of the 322 SUS questionnaire completions, 321 device screen sizes were detected by the app. Grouped by device screen size, small (n = 92), medium (n = 38) and large (n = 191) screens received median SUS scores of 77.5 (IQR 15.0), 75.0 (IQR 19.4) and 77.5 (IQR 16.25), respectively. The median SUS scores from younger (n = 268) and older participants (n = 53) were the same. The FFQ contained 157 food items, and the mean completion time was 13.1 minutes (95% CI 12.6–13.7 minutes). Small, medium and large screen devices resulted in completion times of 11.7 minutes (95% CI 10.9–12.6 minutes), 14.4 minutes (95% CI 12.9–15.9 minutes) and 13.6 minutes (95% CI 12.8–14.3 minutes), respectively. Conclusions: The overall median SUS score of 77.5 and overall mean completion time of 13.3 minutes indicate good overall usability, and equally, comparable SUS scores and completion times across small, medium and large screen sizes indicates good usability across devices. This work is a step toward the promotion of wider uptake of online apps that can provide online dietary intake assessment at-scale, with the aim of addressing pressing epidemiological challenges. [ABSTRACT FROM AUTHOR]

The aesthetic quality of the built environment is of paramount importance to the quality of life of an increasingly urbanizing population. However, a lack of data has hindered the development of comprehensive measures of perceived architectural beauty. In this paper, we demonstrate that the local frequency of geotagged photos posted by internet users in two photo-sharing websites strongly predict the beauty ratings of buildings. We conduct an independent beauty survey with respondents rating proprietary stock photos of 1,000 buildings across the United States. Buildings with higher ratings were found more likely to be geotagged with user-uploaded photos in both Google Maps and Flickr. This correlation also holds for the beauty rankings of raters who seldom upload materials to the internet. Objective architectural characteristics that predict higher average beauty ratings of buildings also positively covary with their internet photo frequency. These results validate the use of localized user-generated image uploads in photo-sharing sites to measure the aesthetic appeal of the urban environment in the study of architecture, real estate, urbanism, planning, and environmental psychology. [ABSTRACT FROM AUTHOR]

Education is undergoing profound changes due to permanent technological innovations. This paper reports the results of a pilot study aimed at developing, implementing and evaluating the course, "Applicative Use of Information and Communication Technologies (ICT) in Medicine," upon medical school entry. The Faculty of Medicine, University of Belgrade, introduced a curriculum reform in 2014 that included the implementation of the course, “Applicative Use of ICT in Medicine” for first year medical students. The course was designed using a blended learning format to introduce the concepts of Web-based learning environments. Data regarding student knowledge, use and attitudes towards ICT were prospectively collected for the classes of 2015/16 and 2016/17. The teaching approach was supported by multimedia didactic materials using Moodle LMS. The overall quality of the course was also assessed. The five level Likert scale was used to measure attitudes related to ICT. In total, 1110 students were assessed upon medical school entry. A small number of students (19%) had previous experience with e-learning. Students were largely in agreement that informatics is needed in medical education, and that it is also useful for doctors (4.1±1.0 and 4.1±0.9, respectively). Ability in informatics and use of the Internet in education in the adjusted multivariate regression model were significantly associated with positive student attitudes toward ICT. More than 80% of students stated that they had learned to evaluate medical information and would use the Internet to search medical literature as an additional source for education. The majority of students (77%) agreed that a blended learning approach facilitates access to learning materials and enables time independent learning (72%). Implementing the blended learning course, "Applicative Use of ICT in Medicine," may bridge the gap between medicine and informatics upon medical school entry. Students displayed positive attitudes towards using ICT and gained adequate skills necessary to function effectively in an information-rich environment. [ABSTRACT FROM AUTHOR]

According to advancements in the wireless technologies, study of biometrics-based multi-server authenticated key agreement schemes has acquired a lot of momentum. Recently, Wang et al. presented a three-factor authentication protocol with key agreement and claimed that their scheme was resistant to several prominent attacks. Unfortunately, this paper indicates that their protocol is still vulnerable to the user impersonation attack, privileged insider attack and server spoofing attack. Furthermore, their protocol cannot provide the perfect forward secrecy. As a remedy of these aforementioned problems, we propose a biometrics-based authentication and key agreement scheme for multi-server environments. Compared with various related schemes, our protocol achieves the stronger security and provides more functionality properties. Besides, the proposed protocol shows the satisfactory performances in respect of storage requirement, communication overhead and computational cost. Thus, our protocol is suitable for expert systems and other multi-server architectures. Consequently, the proposed protocol is more appropriate in the distributed networks. [ABSTRACT FROM AUTHOR]

Background: Decision aids can support informed choice in mammography screening, but for the German mammography screening programme no systematically evaluated decision aid exists to date. We developed a decision aid for women invited to this programme for the first time based on the criteria of the International Patient Decision Aids Standards Collaboration. Objective: To determine whether a decision aid increases informed choice about mammography screening programme participation. Methods: A representative sample of 7,400 women aged 50 was drawn from registration offices in Westphalia-Lippe, Germany. Women were randomised to receive usual care (i.e., the standard information brochure sent with the programme’s invitation letter) or the decision aid. Data were collected online at baseline, post-intervention, and 3 months follow-up. The primary outcome was informed choice. Secondary outcomes were the constituents of informed choice (knowledge, attitude, intention/uptake), decisional conflict, decision regret, and decision stage. Outcomes were analysed using latent structural equation models and χ2-tests. Results: 1,206 women participated (response rate of 16.3%). The decision aid increased informed choice. Women in the control group had lower odds to make an informed choice at post-intervention (OR 0.26, 95% CI 0.18-0.37) and at follow-up (OR 0.66, 95% CI 0.46-0.94); informed choices remained constant at 30%. This was also reflected in lower knowledge and more decisional conflict. Post-intervention, the uptake intention was higher in the control group, whereas the uptake rate at follow-up was similar. Women in the control group had a more positive attitude at follow-up than women receiving the decision aid. Decision regret and decision stage were not influenced by the intervention. Conclusion: This paper describes the first systematic evaluation of a newly developed decision aid for the German mammography screening programme in a randomised controlled trial. Our decision aid proved to be an effective tool to enhance the rate of informed choice and was made accessible to the public. Trial registration: German Clinical Trials Register . [ABSTRACT FROM AUTHOR]

Introduction: A broad range of self-tests (testing for e.g. HIV, cancer, hepatitis B/C) have become available and can be conducted by lay consumers without the help of a health professional. The aims of this study were to (a) investigate the prevalence of self-testing, (b) identify the most frequently used self-tests, and (c) explore the associations between socio-demographic, health-related and individual factors with self-testing. Methods: A face-to-face plus paper-pencil cross-sectional survey was conducted. The sample consisted of 2.527 respondents who were representative of the German population in terms of the age, sex, and residence. Basic descriptive statistics and univariate logistic regression analyses were performed. Results: 8.5% of the participants reported having used one or more self-tests in the past, totalling 363 self-tests, with a mean of 1.7 (min. = 1, max. = 6). The three self-tests most frequently indicated were for detecting diabetes, bowel cancer, and allergies. Self-testers were older (Nagelkerke R2 = .006, p < .01), had a higher BMI (Nagelkerke R2 = .013, p < .001) and displayed more physical and mental fatigue (Nagelkerke R2 = .031, p < .001) than non-testers. Self-testers also reported higher global life satisfaction values (Nagelkerke R2 = .008, p < .01) and a higher educational level (Nagelkerke R2 = .015, p < .01). Conclusions: Self-testing is fairly prevalent in Germany Given the current shortage of physicians in Germany, especially in rural areas, and recent studies on the use of self-medication, the topic of self-testing has a great practical and socio-political relevance. Future studies should investigate further predictors of self-testing (e.g. contextual, situational and individual factors) as well as the emotional consequences of testing as a layperson without the attendance of a health professional. [ABSTRACT FROM AUTHOR]

Introduction: Electronic health (eHealth) strategies are evolving making it important to have valid scales to assess eHealth and health literacy. Item response theory methods, such as the Rasch measurement model, are increasingly used for the psychometric evaluation of scales. This paper aims to examine the internal construct validity of an eHealth and health literacy scale using Rasch analysis in a population with moderate to high cardiovascular disease risk. Methods: The first 397 participants of the CONNECT study completed the electronic health Literacy Scale (eHEALS) and the Health Literacy Questionnaire (HLQ). Overall Rasch model fit as well as five key psychometric properties were analysed: unidimensionality, response thresholds, targeting, differential item functioning and internal consistency. Results: The eHEALS had good overall model fit (χ2 = 54.8, p = 0.06), ordered response thresholds, reasonable targeting and good internal consistency (person separation index (PSI) 0.90). It did, however, appear to measure two constructs of eHealth literacy. The HLQ subscales (except subscale 5) did not fit the Rasch model (χ2: 18.18–60.60, p: 0.00–0.58) and had suboptimal targeting for most subscales. Subscales 6 to 9 displayed disordered thresholds indicating participants had difficulty distinguishing between response options. All subscales did, nonetheless, demonstrate moderate to good internal consistency (PSI: 0.62–0.82). Conclusion: Rasch analyses demonstrated that the eHEALS has good measures of internal construct validity although it appears to capture different aspects of eHealth literacy (e.g. using eHealth and understanding eHealth). Whilst further studies are required to confirm this finding, it may be necessary for these constructs of the eHEALS to be scored separately. The nine HLQ subscales were shown to measure a single construct of health literacy. However, participants’ scores may not represent their actual level of ability, as distinction between response categories was unclear for the last four subscales. Reducing the response categories of these subscales may improve the ability of the HLQ to distinguish between different levels of health literacy. [ABSTRACT FROM AUTHOR]

The extraction of information from social media is an essential yet complicated step for data analysis in multiple domains. In this paper, we present Vigi4Med Scraper, a generic open source framework for extracting structured data from web forums. Our framework is highly configurable; using a configuration file, the user can freely choose the data to extract from any web forum. The extracted data are anonymized and represented in a semantic structure using Resource Description Framework (RDF) graphs. This representation enables efficient manipulation by data analysis algorithms and allows the collected data to be directly linked to any existing semantic resource. To avoid server overload, an integrated proxy with caching functionality imposes a minimal delay between sequential requests. Vigi4Med Scraper represents the first step of Vigi4Med, a project to detect adverse drug reactions (ADRs) from social networks founded by the French drug safety agency Agence Nationale de Sécurité du Médicament (ANSM). Vigi4Med Scraper has successfully extracted greater than 200 gigabytes of data from the web forums of over 20 different websites. [ABSTRACT FROM AUTHOR]

This paper describes a new computer virus spreading model which takes into account the possibility of a virus outbreak on a network with limited anti-virus ability. Then, the model is investigated for the existence of equilibria and their stabilities are proved and illustrated. Moreover, it is found that these two factors are not only relative to the threshold value determining whether the virus becomes extinct or not, but that they are also relative to the virus epidemic levels. Theoretical and experimental results indicate that, in some ways, it would be practically possible to eradicate the virus or suppress its prevalence below a suitable level. Consequently, some suggestions are proposed that may help eradicate or suppress virus propagation over a real computer network. [ABSTRACT FROM AUTHOR]

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder. [ABSTRACT FROM AUTHOR]

As the enterprise of the “Internet of Things” is rapidly gaining widespread acceptance, sensors are being deployed in an unrestrained manner around the world to make efficient use of this new technological evolution. A recent survey has shown that sensor deployments over the past decade have increased significantly and has predicted an upsurge in the future growth rate. In health-care services, for instance, sensors are used as a key technology to enable Internet of Things oriented health-care monitoring systems. In this paper, we have proposed a two-stage fundamental approach to facilitate the implementation of such a system. In the first stage, sensors promptly gather together the particle measurements of an android application. Then, in the second stage, the collected data are sent over a Femto-LTE network following a new scheduling technique. The proposed scheduling strategy is used to send the data according to the application’s priority. The efficiency of the proposed technique is demonstrated by comparing it with that of well-known algorithms, namely, proportional fairness and exponential proportional fairness. [ABSTRACT FROM AUTHOR]

Introduction: Nurses may play an important role in the delivery of medical services based on the use of ehealth tools. Nevertheless, their taking an active role in an ehealth environment depends on their possessing the appropriate skills and mindset. The main objective of this paper was to assess nurses’ opinions and to analyze the predictors of their acceptance of ehealth features relevant to patient empowerment with a strong focus on chronic care. Methods: A survey was conducted among nurses from hospital centers of south-eastern Poland based on a questionnaire designed to assess their attitudes toward the ehealth domain. The predictors of the nurses’ acceptance of ehealth usage within specific contexts were assessed with uni- and multivariate logistic regression. Results: An analysis was performed on data from 648 questionnaires retained after a quality check. The duration of Internet use was consistently related to higher acceptance of ehealth applications and more certainty regarding the reliability of health-related information available on the Internet. Nurses from urban medical centers were more skeptical about the use of specific ehealth solutions. Conclusion: Previous experience in using information technologies is the main factor influencing the acceptance of specific ehealth solutions relevant for care provided to patients suffering from chronic conditions. [ABSTRACT FROM AUTHOR]

This paper presents data from the Program for the International Assessment of Adult Competencies with a focus on the interrelationships among health information seeking behavior (HISB), and health status or use of preventive health measures for U.S. adults both with and without a high school diploma. Key results of ordinal and binary logistic regression analyses indicated that, after controlling for demographic factors, (1) adults with a high school diploma use more text-based health information sources while adults without a high school diploma use more oral sources, (2) using the Internet as a source of health information is more strongly related to reporting excellent/very good health status than having a high school diploma, (3) those without a high school diploma who use the Internet report the largest increase in health status over any other health information source, and (4) for those with learning disability or vision problem, a high facility in reading English is an important predictor of whether the Internet is used as a health information source. The Internet appears to play a key role in both enhancing health status and enabling use of preventive measures for those with and without a high school diploma; although, individuals without a high school diploma who use the Internet for health information derive substantial benefit in health status. [ABSTRACT FROM AUTHOR]

We introduce a rapid deterministic algorithm for identification of the most critical links which are capable of causing network disruptions. The algorithm is based on searching for the shortest cycles in the network and provides a significant time improvement compared with a common brute-force algorithm which scans the entire network. We used a simple measure, based on standard deviation, as a vulnerability measure. It takes into account the importance of nodes in particular network components. We demonstrate this approach on a real network with 734 nodes and 990 links. We found the worst scenarios for the cases with and without people living in the nodes. The evaluation of all network breakups can provide transportation planners and administrators with plenty of data for further statistical analyses. The presented approach provides an alternative approach to the recent research assessing the impacts of simultaneous interruptions of multiple links. [ABSTRACT FROM AUTHOR]

Situated in southeastern Sierra Leone, Kenema Government Hospital (KGH) maintains one of the world’s only Lassa fever isolation wards and was a strategic Ebola virus disease (EVD) treatment facility during the 2014 EVD outbreak. Since 2006, the Viral Hemorrhagic Fever Consortium (VHFC) has carried out research activities at KGH, capturing clinical and laboratory data for suspected cases of Lassa fever. Here we describe the approach, progress, and challenges in designing and maintaining a data capture and management system (DCMS) at KGH to assist infectious disease researchers in building and sustaining DCMS in low-resource environments. Results on screening patterns and case-fatality rates are provided to illustrate the context and scope of the DCMS covered in this study. A medical records system and DCMS was designed and implemented between 2010 and 2016 linking historical and prospective Lassa fever data sources across KGH Lassa fever units and its peripheral health units. Data were captured using a case report form (CRF) system, enzyme-linked immunosorbent assay (ELISA) plate readers, polymerase chain reaction (PCR) machines, blood chemistry analyzers, and data auditing procedures. Between 2008 and 2016, blood samples for 4,229 suspected Lassa fever cases were screened at KGH, ranging from 219 samples in 2008 to a peak of 760 samples in 2011. Lassa fever case-fatality rates before and following the Ebola outbreak were 65.5% (148/226) and 89.5% (17/19), respectively, suggesting that fewer, but more seriously ill subjects with Lassa fever presented to KGH following the 2014 EVD outbreak (p = .040). DCMS challenges included weak specificity of the Lassa fever suspected case definition, limited capture of patient survival outcome data, internet costs, lapses in internet connectivity, low bandwidth, equipment and software maintenance, lack of computer teaching laboratories, and workload fluctuations due to variable screening activity. DCMS are the backbone of international research efforts and additional literature is needed on the topic for establishing benchmarks and driving goal-based approaches for its advancement in developing countries. [ABSTRACT FROM AUTHOR]

Today’s students have increased expectations for flexible learning options and evidence-based practice resources to be available to support curricular activities. We investigated: (i) the suitability of a static website for teaching ocular anatomy and physiology and an interactive version of the website with quiz and self-assessment activities and (ii) the usefulness of a blended online and in-lab environment to teach in Optometry. We administered a survey to compare responses of optometry students who had access to the interactive website, with those from students from a previous year who used the static version. We examined learning preferences of students in a focus group. Students were positive about the value of the website for their learning and the clarity of the website content. Nevertheless, objective comparison of pass rates for students using the static and interactive websites did not show significant changes. The majority of students commenting on the static website felt they did not get sufficient feedback via the website (67%) compared with only 22% from students who used self-assessments in the interactive website. Interestingly, users of the static website commented that it was perceived as just another resource while users of the interactive website commented on the usefulness of the material to review knowledge before laboratories. In the focus group, students reported they preferred a blended learning over the website alone even by students using the interactive website as they felt the need to revise content with the educator before the test. We conclude that there is acceptance of online learning methods due to the technologically ‘savvy’ environment of students in the first year of the Optometry programme but there is still dependence on the educator as the main administrator of their learning. [ABSTRACT FROM AUTHOR]

Objective: The recent 2014 Ebola Virus Disease (EVD) outbreaks rang the bell to call upon global efforts to assist resource-constrained countries to strengthen public health surveillance system for early response. Malawi adopted the Integrated Disease Surveillance and Response (IDSR) strategy to develop its national surveillance system since 2002 and revised its guideline to fulfill the International Health Regulation (IHR) requirements in 2014. This study aimed to understand the state of IDSR implementation and differences between guideline and practice for future disease surveillance system strengthening. Methods: This was a mixed-method research study. Quantitative data were to analyze completeness and timeliness of surveillance system performance from national District Health Information System 2 (DHIS2) during October 2014 to September 2016. Qualitative data were collected through interviews with 29 frontline health service providers from the selected district and 7 key informants of the IDSR system implementation and administration at district and national levels. Findings: The current IDSR system showed relatively good completeness (73.1%) but poor timeliness (40.2%) of total expected monthly reports nationwide and zero weekly reports during the study period. Major implementation gaps were lack of weekly report and trainings. The challenges of IDSR implementation revealed through qualitative data included case identification, compiling reports for timely submission and inadequate resources. Conclusions: The differences between IDSR technical guideline and actual practice were huge. The developing information technology infrastructure in Malawi and emerging mobile health (mHealth) technology can be opportunities for the country to overcome these challenges and improve surveillance system to have better timeliness for the outbreaks and unusual events detection. [ABSTRACT FROM AUTHOR]

In view of the fact that the current online virtual network embedding algorithms do not consider the fragment resources generated in the embedding process deeply enough, resulting in the problem that the acceptance ratio and the revenue to cost ratio are both low, a mathematical model for virtual network reconfiguration is constructed and a heuristic algorithm for fragment-aware virtual network reconfiguration (FA-VNR) is proposed. The FA-VNR algorithm selects the set of virtual nodes to be migrated according to the fragment degrees of the physical nodes, and selects the best virtual node migration scheme according to the reduction of the fragment degrees of the physical nodes as well as the reduction of the embedding cost of the embedded virtual networks. Extensive simulation results show that the proposed FA-VNR algorithm not only can obviously improve the acceptance ratio and the revenue to cost ratio of the current online virtual network embedding algorithm, but also has better optimization effect than the existing virtual network reconfiguration algorithm. [ABSTRACT FROM AUTHOR]

Background: AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Internet, the ‘big data’ aggregated from Internet search engines, which contain users’ information on the concern or reality of their health status, provide a new opportunity for AIDS surveillance. This paper uses search engine data to monitor and forecast AIDS in China. Methods: A machine learning method, artificial neural networks (ANNs), is used to forecast AIDS incidences and deaths. Search trend data related to AIDS from the largest Chinese search engine, Baidu.com, are collected and selected as the input variables of ANNs, and officially reported actual AIDS incidences and deaths are used as the output variable. Three criteria, the mean absolute percentage error, the root mean squared percentage error, and the index of agreement, are used to test the forecasting performance of the ANN method. Results: Based on the monthly time series data from January 2011 to June 2017, this article finds that, under the three criteria, the ANN method can lead to satisfactory forecasting of AIDS incidences and deaths, regardless of the change in the number of search queries. Conclusions: Despite the inability to self-detect HIV/AIDS through online searching, Internet-based data should be adopted as a timely, cost-effective complement to a traditional AIDS surveillance system. [ABSTRACT FROM AUTHOR]

Objectives: To synthesise results of population surveys assessing knowledge and attitudes about prevention and treatment of dementia. Methods: MEDLINE, EMBASE, PsycINFO, and grey literature were searched for English language entries published between 2012 and May 2017. Survey questions were grouped using an inductive approach and responses were pooled. Results: Thirty-four eligible studies and four grey literature items were identified. Surveys were conducted in Europe, the US, Eastern Asia, Israel, and Australia. Nearly half of respondents agreed that dementia is a normal and non-preventable part of ageing, but belief in the potential for prevention may be improving over time. The role of cardiovascular risk factors was poorly understood overall. Less than half of respondents reported belief in the availability of a cure for dementia. The value of seeking treatment was highly endorsed. Conclusions: Results suggest that knowledge about the potential for dementia prevention and treatment remains poor but may be improving over time. Knowledge among those living in low- and middle-income countries are largely unknown, presenting challenges for the development of National action plans consistent with World Health Organization directives. [ABSTRACT FROM AUTHOR]

Temporal contact networks are studied to understand dynamic spreading phenomena such as communicable diseases or information dissemination. To establish how spatiotemporal dynamics of nodes impact spreading potential in colocation contact networks, we propose “inducement-shuffling” null models which break one or more correlations between times, locations and nodes. By reconfiguring the time and/or location of each node’s presence in the network, these models induce alternative sets of colocation events giving rise to contact networks with varying spreading potential. This enables second-order causal reasoning about how correlations in nodes’ spatiotemporal preferences not only lead to a given contact network but ultimately influence the network’s spreading potential. We find the correlation between nodes and times to be the greatest impediment to spreading, while the correlation between times and locations slightly catalyzes spreading. Under each of the presented null models we measure both the number of contacts and infection prevalence as a function of time, with the surprising finding that the two have no direct causality. [ABSTRACT FROM AUTHOR]

The ability to ascertain the extent of product sale fluctuations for each store and locality is indispensable to inventory management. This study analyzed POS data from 158 convenience stores in Kawasaki City, Kanagawa Prefecture, Japan and found a power scaling law between the mean and standard deviation of product sales quantities for several product categories. For the statistical domains of low sales quantities, the power index was 1/2; for large sales quantities, the power index was 1, so called Taylor’s law holds. The value of sales quantities with changing power indixes differed according to product category. We derived a Poissonian compound distribution model taking into account fluctuations in customer numbers to show that the scaling law could be explained theoretically for most of items. We also examined why the scaling law did not hold in some exceptional cases. [ABSTRACT FROM AUTHOR]

Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response. The current state of the art is to gather this knowledge using in-person patient contact. While accurate, this is time-consuming and expensive. This has motivated inquiry into new approaches using internet activity traces, based on the theory that lay observations of health status lead to informative features in internet data. These approaches risk being deceived by activity traces having a coincidental, rather than informative, relationship to disease incidence; to our knowledge, this risk has not yet been quantitatively explored. We evaluated both simulated and real activity traces of varying deceptiveness for influenza incidence estimation using linear regression. We found that deceptiveness knowledge does reduce error in such estimates, that it may help automatically-selected features perform as well or better than features that require human curation, and that a semantic distance measure derived from the Wikipedia article category tree serves as a useful proxy for deceptiveness. This suggests that disease incidence estimation models should incorporate not only data about how internet features map to incidence but also additional data to estimate feature deceptiveness. By doing so, we may gain one more step along the path to accurate, reliable disease incidence estimation using internet data. This capability would improve public health by decreasing the cost and increasing the timeliness of such estimates. [ABSTRACT FROM AUTHOR]

Background: Alcohol use disorder (AUD) is known to co-occur with other addictions, as well as with mental health problems. However, the effects of other addictions co-occurring with AUD on mental health problems were rarely studied and not considering them may bias estimates of the association between AUD and mental health problems. This study investigated which role co-occurring addictions play for the cross-sectional associations between self-reported AUD and mental health problems. Method: Participants were 5516 young Swiss men (73.0% of those that gave written informed consent) who completed a self-report questionnaire. Using short screening questionnaires, we assessed three substance use disorders (alcohol, cannabis and tobacco), seven behavioural addictions (internet, gaming, smartphone, internet sex, gambling, work, exercise) and four mental health problems (major depression, bipolar disorder, attention deficit hyperactivity disorder (ADHD) and social anxiety disorder). Differences in the proportions of mental health problems were tested using logistic regressions between (1) participants with no AUD and AUD, (2) participants with no AUD and AUD alone and (3) participants with no AUD and AUD plus at least one co-occurring addiction. Results: Overall, (1) participants with AUD had higher proportions of major depression (Odds ratio (OR [95% confidence interval]) = 3.51 [2.73, 4.52]; ADHD (OR = 3.12 [2.41, 4.03]); bipolar disorder (OR = 4.94 [3.38, 7.21]) and social anxiety (OR = 2.21 [1.79, 2.73])) compared to participants with no AUD. Considering only participants with AUD alone compared to participants with no AUD (2), differences in proportions were no longer significant for major depression (OR = 0.83 [0.42, 1.64]), bipolar disorder (OR = 1.69 [0.67, 4.22]), social anxiety (OR = 1.15 [0.77, 1.73]) and ADHD (OR = 1.65 [1.00, 2.72]) compared to participants with no AUD. In contrast, (3) proportions of mental health problems were considerably higher for participants with AUD plus at least one other addiction when compared to participants with no AUD, with OR’s ranging from 2.90 [2.27, 3.70] for social anxiety, 4.03 [3.02, 5.38] for ADHD, 5.29 [4.02, 6.97] for major depression to 6.64 [4.44, 9.94] for bipolar disorder. Conclusions: AUD was associated with all four measured mental health problems. However, these associations were mainly due to the high proportions of these mental health problems in participants with AUD plus at least one co-occurring addiction and only to a lesser degree due to participants with AUD alone (i.e. without any other co-occurring addictions). Hence, estimates of the association between AUD and mental health problems that do not consider other addictions may be biased (i.e. overestimated). These findings imply that considering addictions co-occurring with AUD, including behavioural addictions, is important when investigating associations between AUD and mental health problems, and for the treatment of AUD and co-morbid disorders. [ABSTRACT FROM AUTHOR]

Teaching introductory programming courses is not an easy task. Instructors of introductory programming courses are facing many challenges related to the nature of programming, the students’ characteristics and the traditional teaching methods that they are using. Blended learning seems to be a promising approach to address these challenges. Many studies concluded that blended learning can be more effective than traditional teaching and can improve students’ learning experience. However, the current state of knowledge and practice in applying blended learning to introductory programming courses is limited. In an attempt to begin remedying this gap, this review synthesizes the different blended learning approaches that have been applied in introductory programming courses. It classifies them into five models then discusses the impact of each of these models on the learning experience of novice programmers. It concludes by providing some recommendations for instructors who want to blend their courses as well as some implications for future research. [ABSTRACT FROM AUTHOR]

Background: In response to a physician shortage in Ethiopia, the number of medical students admitted to public universities was rapidly increased through a “flooding” policy. Objectives: To assess medical student perceptions on the impact of the “flooding” policy on medical education and e-learning initiatives, as well as plans for future emigration. Design: A cross-sectional survey of medical students at AAU was implemented in 2014. Attitude and practice items were assessed using a Likert scale. Logistic regression analysis was performed to identify characteristics associated with an interest in future emigration. Results: 673 (99.6%) of 676 students approached completed the survey, representing 39.5% of all 1705 medical students enrolled at AAU in 2014. Most students felt the “flooding” policy had a negative impact on their medical education and >90% felt there was not adequate infrastructure to support the increased student body. E-learning activities to accommodate increased class size included distribution of electronic tablets, but at the time of the survey only 34.8% of students still had a working tablet and 82.3% reported problems with internet connectivity. Most preclinical students (85.1%) who had attended live-streamed lectures preferred traditional classroom lectures. Half of the students (49.5%) intended to practice medicine in Ethiopia. Independent risk factors for planning to emigrate included age <21 years (aOR = 1.30, 95% CI 1.04, 1.97); having applied to medical school for reasons other than “wanting to be a physician” (aOR = 1.55, 95% CI 1.14, 2.20), and not believing that “flooding” policy would increase the number of physicians working in Ethiopia (aOR = 1.87, 95% CI 1.33, 2.58). Conclusions: The “flooding” policy lead to significant educational challenges that were not fully alleviated by e-learning initiatives. Concomitant increases in resources for infrastructure development and faculty expansion are needed to maintain quality medical education. Additional research is needed on factors that influence medical graduates decision to emigrate. [ABSTRACT FROM AUTHOR]

Background: Patient feedback after contact with a hospital is regarded as an important source of information for the improvement of local healthcare services. Routine patient surveys are in widespread use to obtain such feedback. While general principles for the composition of this kind of surveys have been described in the literature, it is unknown which method of contact and topics of feedback are important to patients in postcontact healthcare surveys. Material and methods: We invited 2931 consecutive patients who had in- or outpatient contact with the Department of Orthopaedics and Traumatology at the University Hospital Basel to an anonymous survey. They were asked whether they were generally in favor of feedback surveys. They also had the opportunity to state their preferred form of contact (text message, app, email, online or letter) and provide up to three topics that they regarded as specifically important in patient surveys. Results: A total of 745 patients participated in the survey (25.4%), of these 61.9% expressed the preference to be surveyed, and 69.1% selected `letter’ as one of the preferred forms of contact. Favoring only `letter’ contact increased substantially with age. Overall 54.6% of patients stated at least one topic that they wished to give feedback on. The most frequent topics were related to treatment and rather general aspects regarding staff and overall impression. The wish to include suggestions for improvements was rarely mentioned as specific topic. Conclusions: The majority of patients seem to be rather indifferent to the existence and content of patient surveys. They mention a wide range of topics from general to specific ones, but do not express interest in the opportunity to suggest changes. There is a need to effectively engage patients in healthcare planning using new approaches to obtain valuable feedback on patients’ hospital stay and contact experiences. These new approaches should ideally be more informative and cost-effective than the current practice. [ABSTRACT FROM AUTHOR]

Relative to the large investments in mobile health (mHealth) strategies for mental illnesses such as anxiety and depression, the development of technology to facilitate illness self-management for people with schizophrenia spectrum illnesses is limited. This situation falls out of step with the opportunity mHealth represents for providing inexpensive and accessible self-care resources and the routine use of mobile technologies by people with schizophrenia. Accordingly, the focus of this study was upon the feasibility of a schizophrenia-focused mobile application: App4Independence (A4i). A4i is a multi-feature app that uses feed, scheduling, and text-based functions co-designed with service users to enhance illness self-management. This study was completed in a large urban Canadian centre and employed pre-post assessments over a 1-month period that examined medication adherence, personal recovery, and psychiatric symptomatology. App use metrics were assessed as was qualitative feedback through semi-structured interview. Findings are reported in line with the World Health Organization mHealth Evidence and Assessment (mERA) checklist. Among the 38 individuals with a primary psychosis who participated, there was no research attrition and classic retention on the app was 52.5%. Significant improvement was observed in some psychiatric symptom domains with small-medium effects. Significant change in recovery engagement and medication adherence were not observed after controlling for multiple comparisons. Those who interacted with the app more frequently were more depressed and had higher hostility and interpersonal sensitivity at baseline. Satisfaction with the app was high and qualitative feedback provided insights regarding feature enhancements. This research suggested that A4i is feasible in terms of outcome and process indicators and is a technology that is ready to move on to clinical trial and validation testing. This study contributes to the small but emergent body of work investigating digital health approaches in severe mental illness populations. [ABSTRACT FROM AUTHOR]

Background: Online health information, if evidence-based and unbiased, can improve patients’ and caregivers’ health knowledge and assist them in disease management and health care decision-making. Objective: To identify standards for the development of health information resources on the internet for patients. Methods: We searched in MEDLINE, CINAHL, Scopus, Web of Science, and Google Scholar for publications describing evaluation instruments for websites providing health information. Eligible instruments were identified by three independent reviewers and disagreements resolved by consensus. Items reported were extracted and categorized into seven domains (accuracy, completeness and comprehensiveness, technical elements, design and aesthetics, usability, accessibility, and readability) that were previously thought to be a minimum requirement for websites. Results: One hundred eleven articles met inclusion criteria, reporting 92 evaluation instruments (1609 items). We found 74 unique items that we grouped into the seven domains. For the accuracy domain, one item evaluated information provided in concordance with current guidelines. For completeness and comprehensiveness, 18 items described the disease with respect to various topics such as etiology or therapy, among others. For technical elements, 27 items evaluated disclosure of authorship, sponsorship, affiliation, editorial process, feedback process, privacy, and data protection. For design and aesthetics, 10 items evaluated consistent layout and relevant graphics and images. For usability, 10 items evaluated ease of navigation and functionality of internal search engines. For accessibility, five items evaluated the availability of websites to people with audiovisual disabilities. For readability, three items evaluated conversational writing style and use of a readability tool to determine the reading level of the text. Conclusion: We identified standards for the development of online patient health information. This proposed instrument can serve as a guideline to develop and improve how health information is presented on the internet. [ABSTRACT FROM AUTHOR]

Doubt is subjective uncertainty about one’s perceptions and recall. It can impair decision-making and is a prominent feature of obsessive-compulsive disorder (OCD). We propose that evaluation of doubt during decision-making provides a useful endophenotype with which to study the underlying pathophysiology of OCD and potentially other psychopathologies. For the current study, we developed a new instrument, the Doubt Questionnaire, to clinically assess doubt. The random dot motion task was used to measure reaction time and subjective certainty, at varying levels of perceptual difficulty, in individuals who scored high and low on doubt, and in individuals with and without OCD. We found that doubt scores were significantly higher in OCD cases than controls. Drift diffusion modeling revealed that high doubt scores predicted slower evidence accumulation than did low doubt scores; and OCD diagnosis lower than controls. At higher levels of dot coherence, OCD participants exhibited significantly slower drift rates than did controls (q<0.05 for 30%, and 45% coherence; q<0.01 for 70% coherence). In addition, at higher levels of coherence, high doubt subjects exhibited even slower drift rates and reaction times than low doubt subjects (q<0.01 for 70% coherence). Moreover, under high coherence conditions, individuals with high doubt scores reported lower certainty in their decisions than did those with low doubt scores. We conclude that the Doubt Questionnaire is a useful instrument for measuring doubt. Compared to those with low doubt, those with high doubt accumulate evidence more slowly and report lower certainty when making decisions under conditions of low uncertainty. High doubt may affect the decision-making process in individuals with OCD. The dimensional doubt measure is a useful endophenotype for OCD research and could enable computationally rigorous and neurally valid understanding of decision-making and its pathological expression in OCD and other disorders. [ABSTRACT FROM AUTHOR]

Film clips, music, and self-referential statements (termed Velten, after their originator) have been successfully used to temporarily induce sadness and happiness. However, there is little research on the effectiveness of these procedures combined, particularly in internet-based settings, and whether Velten statements contribute to alter mood beyond the effect of simple instructions to close one's eyes and enter the targeted mood. In Study 1 (N = 106) we examined the effectiveness 80 Velten statements (positive, negative, neutral-self, neutral-facts) to create brief and effective sets that might be used in future research. In Study 2 (N = 445) we examined the effect size of 8-min combined mood induction procedures, which presented video clips in the first half and music excerpts with Velten statements or closed eyes instructions in the second half. Participants answered questionnaires on social desirability, joviality, and sadness before being randomly assigned to 1 of 7 groups varying in Valence (positive, negative, neutral) and Velten (closed eyes control, self-referential Velten, and, in the case of neutral condition, factual statements). Subsequently, participants completed the joviality and sadness scales a second time. Compared to the neutral conditions, the positive mood inductions increased joviality (Hedges G = 1.35, 95% CI [1.07, 1.63]), whereas the negative mood inductions increased sadness (Hedges G = 1.28, 95% CI [1.01, 1.55]). We did not observe any significant difference between Velten and closed eyes instructions in inducing joviality or sadness, nor did we observe any significant difference between neutral Velten statements referring to self and facts. Although social desirability bias was associated with reports of greater joviality and lower sadness, it could not account for the effects of the positive and negative mood induction procedures. We conclude that these combined mood induction procedures can be used in online research to study happy and sad mood. [ABSTRACT FROM AUTHOR]

Background: Evidence highlights a global shortage of wheelchair service provision education and training that results in inappropriate wheelchair provision with associated health and economic consequences. Two learning methodologies, a hybrid and an in-person course, based on the World Health Organization Wheelchair Service Training Package Basic Level, currently are available to train wheelchair service providers worldwide. The effectiveness of the in-person methodology, used as the standard of practice, has never been tested. Meanwhile, the Hybrid Course, which combines online and in-person training, was developed to reduce training costs and to scale training interventions and has shown potential effectiveness in increasing basic level wheelchair service provision knowledge. The objective of this study was to compare the effectiveness of both learning methodologies based on knowledge and satisfaction among a group of wheelchair service providers in India and Mexico. Methods: We conducted a controlled quasi-experimental study to evaluate changes in basic wheelchair knowledge and levels of satisfaction between Hybrid and In-person course learners in India and Mexico. A convenience sampling method guided by local stakeholders’ input was used to recruit participants. Outcomes were assessed using self-administered online surveys, the International Society of Wheelchair Professionals Wheelchair Service Provision Basic Test (primary outcome) completed pre- and post- the learning intervention and an anonymous Satisfaction Survey (secondary outcome) completed post- intervention. Baseline characteristics were compared among groups using hypothesis tests based on their assumptions. The primary analysis was intention-to-treat. To address missing values and lost to follow-up, multiple chained imputations were conducted. The primary outcome was analyzed using linear mixed models. The secondary outcome was analyzed using a two-tailed two independent samples t-test. Results: A total of 81 participants, 43 (53.1%) in the In-person group and 38 (46.9%) in the Hybrid group, participated in the study. Mean baseline knowledge scores were below the passing cutoff of the test (53 points) in both groups. Both study groups experienced statistically significant improvements in the primary outcome when comparing pre- and post-test scores (p<0.0001) with total mean scores above the passing cutoff of the test. The in-person group experienced, on average, larger effects on the primary outcome. The difference in mean change from post-test to pre-tests between In-person groups and Hybrid was 3.6 (95% Confidence Interval: 1.7;5.4), Cohen’s d = 0.36, with a small effect size favoring the In-person training. With regards to satisfaction, the difference between the two interventions was 0.23±0.07 in favor of the In-person group (p = 0.0021). Conclusions: Both learning methodologies had a statistically significant effect in increasing wheelchair service knowledge with overall high levels of satisfaction. However, the In-person group reported overall larger effects when compared with the Hybrid methodology. This study provided recommendations on how organizations can improve blended learning interventions to enhance participants’ learning experiences and reduce potential barriers and limitations. [ABSTRACT FROM AUTHOR]