Интеллект-карта как средство оценивания качества знаний обучающихся: возможности и ограничения структурно-информационного подхода

Обсуждаются возможности и ограничения использования интеллект-карт как средства оценивания качества знаний обучающихся в рамках структурно-информационного подхода. Интеллект-карта рассматривается, с одной стороны, как логико-смысловая вербально-образная модель учебного материала, отображающая его содержание и структуру, с другой стороны – как модель индивидуальных знаний обучающихся. Для расчета структурных и информационных характеристик интеллект-карты предлагается использовать структурные формулы древовидных графов. Приведен алгоритм расчета структурных и информационных характеристик эталонной интеллект-карты и индивидуальных интеллект-карт, относительного показателя упорядоченности знаний обучающегося

Email for communicating results of diagnostic medical investigations to patients

<p>Background: As medical care becomes more complex and the ability to test for conditions grows, pressure on healthcare providers to convey increasing volumes of test results to patients is driving investigation of alternative technological solutions for their delivery. This review addresses the use of email for communicating results of diagnostic medical investigations to patients.</p> <p>Objectives: To assess the effects of using email for communicating results of diagnostic medical investigations to patients, compared to SMS/ text messaging, telephone communication or usual care, on outcomes, including harms, for health professionals, patients and caregivers, and health services.</p> <p>Search methods: We searched: the Cochrane Consumers and Communication Review Group Specialised Register, Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 1 2010), MEDLINE (OvidSP) (1950 to January 2010), EMBASE (OvidSP) (1980 to January 2010), PsycINFO (OvidSP) (1967 to January 2010), CINAHL (EbscoHOST) (1982 to February 2010), and ERIC (CSA) (1965 to January 2010). We searched grey literature: theses/dissertation repositories, trials registers and Google Scholar (searched July 2010). We used additional search methods: examining reference lists and contacting authors.</p> <p>Selection criteria: Randomised controlled trials, quasi-randomised trials, controlled before and after studies and interrupted time series studies of interventions using email for communicating results of any diagnostic medical investigations to patients, and taking the form of 1) unsecured email 2) secure email or 3) web messaging. All healthcare professionals, patients and caregivers in all settings were considered.</p> <p>Data collection and analysis: Two review authors independently assessed the titles and abstracts of retrieved citations. No studies were identified for inclusion. Consequently, no data collection or analysis was possible.</p> <p>Main results: No studies met the inclusion criteria, therefore there are no results to report on the use of email for communicating results of diagnostic medical investigations to patients.</p> <p>Authors' conclusions: In the absence of included studies, we can draw no conclusions on the effects of using email for communicating results of diagnostic medical investigations to patients, and thus no recommendations for practice can be stipulated. Further well-designed research should be conducted to inform practice and policy for communicating patient results via email, as this is a developing area.</p&gt

Cross-sectional survey of users of internet depression communities

Background: Internet-based depression communities provide a forum for individuals to communicate and share information and ideas. There has been little research into the health status and other characteristics of users of these communities. Methods: Online cross-sectional survey of Internet depression communities to identify depressive morbidity among users of Internet depression communities in six European countries; to investigate whether users were in contact with health services and receiving treatment; and to identify user perceived effects of the communities. Results: Major depression was highly prevalent among respondents (varying by country from 40% to 64%). Forty-nine percent of users meeting criteria for major depression were not receiving treatment, and 35% had no consultation with health services in the previous year. Thirty-six percent of repeat community users who had consulted a health professional in the previous year felt that the Internet community had been an important factor in deciding to seek professional help. Conclusions: There are high levels of untreated and undiagnosed depression in users of Internet depression communities. This group represents a target for intervention. Internet communities can provide information and support for stigmatizing conditions that inhibit more traditional modes of information seeking

Alternatives to the face-to-face consultation in general practice: Focused ethnographic case study

© British Journal of General Practice. Background NHS policy encourages general practices to introduce alternatives to the face-to-face consultation, such as telephone, email, e-consultation systems, or internet video. Most have been slow to adopt these, citing concerns about workload. This project builds on previous research by focusing on the experiences of patients and practitioners who have used one or more of these alternatives. Aim To understand how, under what conditions, for which patients, and in what ways, alternatives to face-to-face consultations present benefits and challenges to patients and practitioners in general practice. Design and setting Focused ethnographic case studies took place in eight UK general practices between June 2015 and March 2016. Method Non-participant observation, informal conversations with staff, and semi-structured interviews with staff and patients were conducted. Practice documents and protocols were reviewed. Data were analysed through charting and the 'one sheet of paper' mind-map method to identify the line of argument in each thematic report. Results Case study practices had different rationales for offering alternatives to the face-to-face consultation. Beliefs varied about which patients and health issues were suitable. Co-workers were often unaware of each other's practice; for example, practice policies for use of e-consultations systems with patients were not known about or followed. Patients reported benefits including convenience and access. Staff and some patients regarded the face-toface consultation as the ideal. Conclusion Experience of implementing alternatives to the face-to-face consultation suggests that changes in patient access and staff workload may be both modest and gradual. Practices planning to implement them should consider carefully their reasons for doing so and involve the whole practice team

Teknologi til fallforbygging – prosjektrapport Falltek.

Fallforebygging er høyt prioritert i kommunene og Falltek (www.falltek.no) hadde som mål å utvikle og bruke motiverende teknologi til fallforebyggende trening. Gjennom å kombinere følgeforskning og utvikling av teknologi kan vi • Bedre fange opp brukerbehov • Støtte innovative prosesser i kommunene og • Tilpasse teknologiutviklingen til brukerbehov og kommunens organiserin

Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse.

BACKGROUND: Social media has become an established platform for individuals to discuss and debate various subjects, including vaccination. With growing conversations on the web and less than desired maternal vaccination uptake rates, these conversations could provide useful insights to inform future interventions. However, owing to the volume of web-based posts, manual annotation and analysis are difficult and time consuming. Automated processes for this type of analysis, such as natural language processing, have faced challenges in extracting complex stances such as attitudes toward vaccination from large amounts of text. OBJECTIVE: The aim of this study is to build upon recent advances in transposer-based machine learning methods and test whether transformer-based machine learning could be used as a tool to assess the stance expressed in social media posts toward vaccination during pregnancy. METHODS: A total of 16,604 tweets posted between November 1, 2018, and April 30, 2019, were selected using keyword searches related to maternal vaccination. After excluding irrelevant tweets, the remaining tweets were coded by 3 individual researchers into the categories Promotional, Discouraging, Ambiguous, and Neutral or No Stance. After creating a final data set of 2722 unique tweets, multiple machine learning techniques were trained on a part of this data set and then tested and compared with the human annotators. RESULTS: We found the accuracy of the machine learning techniques to be 81.8% (F score=0.78) compared with the agreed score among the 3 annotators. For comparison, the accuracies of the individual annotators compared with the final score were 83.3%, 77.9%, and 77.5%. CONCLUSIONS: This study demonstrates that we are able to achieve close to the same accuracy in categorizing tweets using our machine learning models as could be expected from a single human coder. The potential to use this automated process, which is reliable and accurate, could free valuable time and resources for conducting this analysis, in addition to informing potentially effective and necessary interventions

Assessment of the quality and content of website health information about herbal remedies for menopausal symptoms

Objective: To assess quality, readability and coverage of website information about herbal remedies for menopausal symptoms. Study design: A purposive sample of commercial and non-commercial websites was assessed for quality (DISCERN), readability (SMOG) and information coverage. Main outcome measures: Non-parametric and parametric tests were used to explain variability of these factors across types of websites and to assess associations between website quality and information coverage. Results: 39 sites were assessed. Median quality and information coverage scores were 44/80 and 11/30 respectively. The median readability score was 18.7, similar to UK broadsheets. Commercial websites scored significantly lower on quality (p=0.014), but there were no statistical differences for information coverage or readability. There was a significant positive correlation between information quality and coverage scores irrespective of website provider (r=0.69, p<0.001, n=39). Conclusion: Overall website quality and information coverage is poor and the required reading level high

Mental Disorder Recovery Correlated with Centralities and Interactions on an Online Social Network

Recent research has established both a theoretical basis and strong empirical evidence that effective social behavior plays a beneficial role in the maintenance of physical and psychological well-being of people. To test whether social behavior and well-being are also associated in online communities, we studied the correlations between the recovery of patients with mental disorders and their behaviors in online social media. As the source of the data related to the social behavior and progress of mental recovery, we used PatientsLikeMe (PLM), the world's first open-participation research platform for the development of patient-centered health outcome measures. We first constructed an online social network structure based on patient-to-patient ties among 200 patients obtained from PLM. We then characterized patients' online social activities by measuring the numbers of "posts and views" and "helpful marks" each patient obtained. The patients' recovery data were obtained from their self-reported status information that was also available on PLM. We found that some node properties (in-degree, eigenvector centrality and PageRank) and the two online social activity measures were significantly correlated with patients' recovery. Furthermore, we re-collected the patients' recovery data two months after the first data collection. We found significant correlations between the patients' social behaviors and the second recovery data, which were collected two months apart. Our results indicated that social interactions in online communities such as PLM were significantly associated with the current and future recoveries of patients with mental disorders.Comment: 20 pages, 5 figures, 5 tables; accepted for publication in Peer

Language complexity in on-line health information retrieval

The number of people searching for on-line health information has been steadily growing over the years so it is crucial to understand their specific requirements in order to help them finding easily and quickly the specific in-formation they are looking for. Although generic search engines are typically used by health information seekers as the starting point for searching information, they have been shown to be limited and unsatisfactory because they make generic searches, often overloading the user with the provided amount of results. Moreover, they are not able to provide specific information to different types of users. At the same time, specific search engines mostly work on medical literature and provide extracts from medical journals that are mainly useful for medical researchers and experts but not for non-experts. A question then arises: Is it possible to facilitate the search of on-line health/medical information based on specific user requirements? In this pa-per, after analysing the main characteristics and requirements of on-line health seeking, we provide a first answer to this question by exploiting the Web structured data for the health domain and presenting a system that allows different types of users, i.e., non-medical experts and medical experts, to retrieve Web pages with language complexity levels suitable to their expertise. Furthermore, we apply our methodology to the results of a generic search engine, such as Google, in order to re-rank them and provide different users with the proper health/medical Web pages in terms of language complexity