Christina Athanasopoulou

Exploring Design Requirements for Repurposing Dental Virtual Patients From the Web to Second Life: A Focus Group Study

Background Since their inception, virtual patients have provided health care educators with a way to engage learners in an experience simulating the clinician’s environment without danger to learners and patients. This has led this learning modality to be accepted as an essential component of medical education. With the advent of the visually and audio-rich 3-dimensional multi-user virtual environment (MUVE), a new deployment platform has emerged for educational content. Immersive, highly interactive, multimedia-rich, MUVEs that seamlessly foster collaboration provide a new hotbed for the deployment of medical education content. Objective This work aims to assess the suitability of the Second Life MUVE as a virtual patient deployment platform for undergraduate dental education, and to explore the requirements and specifications needed to meaningfully repurpose Web-based virtual patients in MUVEs. Methods Through the scripting capabilities and available art assets in Second Life, we repurposed an existing Web-based periodontology virtual patient into Second Life. Through a series of point-and-click interactions and multiple-choice queries, the user experienced a specific periodontology case and was asked to provide the optimal responses for each of the challenges of the case. A focus group of 9 undergraduate dentistry students experienced both the Web-based and the Second Life version of this virtual patient. The group convened 3 times and discussed relevant issues such as the group’s computer literacy, the assessment of Second Life as a virtual patient deployment platform, and compared the Web-based and MUVE-deployed virtual patients. Results A comparison between the Web-based and the Second Life virtual patient revealed the inherent advantages of the more experiential and immersive Second Life virtual environment. However, several challenges for the successful repurposing of virtual patients from the Web to the MUVE were identified. The identified challenges for repurposing of Web virtual patients to the MUVE platform from the focus group study were (1) increased case complexity to facilitate the user’s gaming preconception in a MUVE, (2) necessity to decrease textual narration and provide the pertinent information in a more immersive sensory way, and (3) requirement to allow the user to actuate the solutions of problems instead of describing them through narration. Conclusions For a successful systematic repurposing effort of virtual patients to MUVEs such as Second Life, the best practices of experiential and immersive game design should be organically incorporated in the repurposing workflow (automated or not). These findings are pivotal in an era in which open educational content is transferred to and shared among users, learners, and educators of various open repositories/environments.

Effectiveness of Social Media Interventions for People With Schizophrenia: A Systematic Review and Meta-Analysis

Background Recent studies have shown that people with serious mental disorders spend time online for the purposes of disclosure, information gathering, or gaming. However, coherent information on the effects of social media on treatment for people with schizophrenia is still lacking. Objective Our aim was to determine the effects of social media interventions for supporting mental health and well-being among people with schizophrenia. Methods A systematic review and meta-analysis were undertaken to determine the effects of social media interventions for supporting mental health and well-being among people with schizophrenia. Ten databases were searched, while search parameters included English-only manuscripts published prior to June 25, 2015. Study appraisals were made independently by 2 reviewers, and qualitative and quantitative syntheses of data were conducted. Results Out of 1043 identified records, only two randomized studies of moderate quality (three records, total N=331, duration 12 months) met the inclusion criteria. Participants were people with schizophrenia spectrum or an affective disorder. Social media was used as part of Web-based psychoeducation, or as online peer support (listserv and bulletin board). Outcome measures included perceived stress, social support, and disease-related distress. At 3 months, participants with schizophrenia in the intervention group reported lower perceived stress levels ( P=.04) and showed a trend for a higher perceived level of social support ( P=.06). However, those who reported more positive experiences with the peer support group also reported higher levels of psychological distress ( P=.01). Conclusions Despite using comprehensive searches from 10 databases, we found only two studies, whereas numerous reports have been published citing the benefits of social media in mental health. Findings suggest the effects of social media interventions are largely unknown. More research is needed to understand the effects of social media, for users with and without mental illness, in order to determine the impact on mental well-being ofsocial media use as well as its risks.

Intelligent system for identification and replacement of faulty sensor measurements in Thermal Power Plants (IPPAMAS: Part 1)

This paper describes a procedure of identifying sensor faults and reconstructing the erroneous measurements. Knowledge discovery in databases is successfully applied for deriving models that estimate the value of one variable based on correlated others. The estimated values can then be used instead of the recorded ones of a measuring instrument with false reading. The aim is to reassure the correctness of data entered to an optimization software application that was developed for the Thermal Power Plants of Western Macedonia, Greece. The architecture of the application follows the Multi-Agent System approach in order to cope with its complexity and distributed nature. The application was tested on a case study and proved to be efficient.

Attitudes towards schizophrenia on YouTube: A content analysis of Finnish and Greek videos

Objective: To investigate attitudes towards schizophrenia and people with schizophrenia presented in YouTube videos. Methods: We searched YouTube using the search terms “schizophrenia” and “psychosis” in Finnish and Greek language on April 3rd, 2013. The first 20 videos from each search (N = 80) were retrieved. Deductive content analysis was first applied for coding and data interpretation and it was followed by descriptive statistical analysis. Results: A total of 52 videos were analyzed (65%). The majority of the videos were in the “Music” category (50%, n = 26). Most of the videos (83%, n = 43) tended to present schizophrenia in a negative way, while less than a fifth (17%, n = 9) presented schizophrenia in a positive or neutral way. Specifically, the most common negative attitude towards schizophrenia was dangerousness (29%, n = 15), while the most often identified positive attitude was objective, medically appropriate beliefs (21%, n = 11). All attitudes identified were similarly present in the Finnish and Greek videos, without any statistically significant difference. Conclusions: Negative presentations of schizophrenia are most likely to be accessed when searching YouTube for schizophrenia in Finnish and Greek language. More research is needed to investigate to what extent, if any, YouTube viewers’ attitudes are affected by the videos they watch.

An analysis of online health information on schizophrenia or related conditions: a cross-sectional survey

BackgroundAround 20% of those who seek health information online, search specifically for mental health. However, little is known about the nature of the online health information offered by two European countries, Finland and Greece, which are characterized by markedly differing levels of Internet access and online health information seeking. This study aims to assess, describe and compare websites, written in two European, non-English languages (Finnish and Greek) that appear first after performing an online search concerning schizophrenia or related conditions.MethodsThe first 20 results from four search terms (searched in Finnish and Greek) in the Web search engine ‘Google’ were screened. A total of 160 websites were retrieved (80 Finnish, 80 Greek) and evaluated using a preformulated coding system which consisted of websites’ indicators, such as: types, characteristics, accountability, interactivity, aesthetics and content. Differences between websites were evaluated with Chi-Square or Fisher’s Exact tests for categorical data and independent t-tests for parametric data.ResultsTwenty-four Finnish and thirty-four Greek websites (36% in total) were included. Almost two-thirds (62%, n=36) were owned by an organization, compared to 17% (n=10) by an individual. In both countries, aesthetics had the highest score (possible range 0–4, mean = 2.6, SD = .62), while interactivity the lowest (range 0–5, mean = 1.79, SD = .87). There were no statistically significant differences among the accountability, interactivity and aesthetics scores of the Finnish and Greek websites.ConclusionsAll assessed indicators suggest there is a need to improve Finnish and Greek online information about schizophrenia or related conditions. The poor website interactivity is of particular concern given the challenges faced by the target group. The findings can be used to guide the development and dissemination of online mental health information aimed at Finnish and Greek online health-seekers.

An Agent Based Prototype for Optimizing Power Plant Operation

Mobile networks in compared to wired networks have unique characteristics. In mobile networks, frequent network topology changes may bring about by node mobility, which are rare in wired networks. In contrast to the stable link capacity of wired networks, wireless link capacity continually varies because of the impacts from transmission power, receiver sensitivity, noise, fading and interference. Moreover, wireless mobile networks have a high error rate, power restrictions and bandwidth limitations.

Connectivity to computers and the Internet among patients with schizophrenia spectrum disorders: a cross-sectional study

Purpose Information and communication technologies have been developed for a variety of health care applications and user groups in the field of health care. This study examined the connectivity to computers and the Internet among patients with schizophrenia spectrum disorders (SSDs). Patients and methods A cross-sectional survey design was used to study 311 adults with SSDs from the inpatient units of two psychiatric hospitals in Finland. The data collection lasted for 20 months and was done through patients’ medical records and a self-reported, structured questionnaire. Data analysis included descriptive statistics. Results In total, 297 patients were included in this study (response rate =96%). More than half of them (n=156; 55%) had a computer and less than half of them (n=127; 44%) had the Internet at home. Of those who generally had access to computers and the Internet, more than one-fourth (n=85; 29%) used computers daily, and >30% (n=96; 33%) never accessed the Internet. In total, approximately one-fourth of them (n=134; 25%) learned to use computers, and less than one-third of them (n=143; 31%) were known to use the Internet by themselves. Older people (aged 45–65 years) and those with less years of education (primary school) tended not to use the computers and the Internet at all (P<0.001), and younger people and those with higher education were associated with more active use. Conclusion Patients had quite good access to use computers and the Internet, and they mainly used the Internet to seek information. Social, occupational, and psychological functioning (which were evaluated with Global Assessment of Functioning) were not associated with access to and frequency of computer and the Internet use. The results support the use of computers and the Internet as part of clinical work in mental health care.

Enhancing Agent Intelligence through Data Mining: A Power Plant Case Study

In this paper, the methodology for an intelligent assistant for power plants is presented. Multiagent systems technology and data mining techniques are combined to enhance the intelligence of the proposed application, mainly in two aspects: increase the reliability of input data (sensor validation and false measurement replacement) and generate new control monitoring rules. Various classification algorithms are compared. The performance of the application, as tested via simulation experiments, is discussed.

Utilizing data mining algorithms for identification and reconstruction of sensor faults: a Thermal Power Plant case study

This paper describes a procedure of identifying sensor faults and reconstructing the erroneous measurements. Data mining algorithms are successfully applied for deriving models that estimate the value of one variable based on correlated others. The estimated values can then be used instead of the recorded ones of a measuring instrument with false reading. The aim is to reassure the correctness of data entered to an optimization software application under development for the Thermal Power Plants of Western Macedonia, Greece.