Evaluation of the Wellspring Model for Improving Nursing Home Quality

Examines how successfully the Wellspring model improved the quality of care for residents of eleven nonprofit nursing homes in Wisconsin. Looks at staff turnover, and evaluates the impact on facilities, employees, residents, and cost

A Bibliometric Study on Learning Analytics

Learning analytics tools and techniques are continually developed and published in scholarly discourse. This study aims at examining the intellectual structure of the Learning Analytics domain by collecting and analyzing empirical articles on Learning Analytics for the period of 2004-2018. First, bibliometric analysis and citation analyses of 2730 documents from Scopus identified the top authors, key research affiliations, leading publication sources (journals and conferences), and research themes of the learning analytics domain. Second, Domain Analysis (DA) techniques were used to investigate the intellectual structures of learning analytics research, publication, organization, and communication (Hjørland & Bourdieu 2014). The software of VOSviewer is used to analyze the relationship by publication: historical and institutional; author and institutional relationships and the dissemination of Learning Analytics knowledge. The results of this study showed that Learning Analytics had captured the attention of the global community. The United States, Spain, and the United Kingdom are among the leading countries contributing to the dissemination of learning analytics knowledge. The leading publication sources are ACM International Conference Proceeding Series, and Lecture Notes in Computer Science. The intellectual structures of the learning analytics domain are presented in this study the LA research taxonomy can be re-used by teachers, administrators, and other stakeholders to support the teaching and learning environments in a higher education institution

Intellectual evolution of social innovation: a bibliometric analysis and avenues for future research trends

Despite the fact that the concept of social innovation is extensively employed by scholars and practitioners, yet the conceptualisation and the research structure remained fragmented and scattered, because no rigorous attempt has been made to understand the core concept of social innovation. The notion of social innovation is multi-faceted and multi-disciplinary fluctuating from public-policy to environmental sustainability; which makes an investigation of the concept essential for business-to-business practitioners and scholars. By processing 370 publications from a sample of 125 journals and books with a total of 2941 citations, the authors unpack/unfold the intellectual foundation of social innovation in business and management domains by performing four bibliometric analyses and they evaluate the research domain qualitatively (1970-2019). By using co-citation, network visualisation through co-occurrence data, multi-dimensional scaling, and hierarchical cluster analysis, this research sheds light to the intellectual structure of social innovation including social value, economic value, societal impact, and bifocal innovations. This research reveals the key research clusters embodied by social innovation foundation. The present study identifies four important components for the future avenues of social innovation (i.e. opportunity, innovation practice, opportunity exploiter, value), and proposes a potential research framework to the researchers and practitioners, hoping to provide insights on social innovation

Beyond the horizon of measurement: Festschrift in honor of Ingwer Borg

"Modesty and academic excellence paired with trustfulness and truthfulness, these are the descriptions we would choose, if asked to describe Ingwer Borg in a nutshell. A glance at his oevre reveals a multi-talented, innovative, and cross-disciplinary scientist, who, by all means, could fill his walls with eminent names, topics, positions, and publications. This is in contrast to the frugality of his office, a scientific workbench, not a celebrity's showroom. In addition to his academic pursues he likes to venture into real life, too. This volume is organized in two parts. The first part deals with measurement issues including the application of multidimensional scaling to substantive issues but where the method is center-stage. The second part in substantive in focus and deals with questions of the organization of firms and employee attitudes." (author's abstract). Contents: Peter Ph. Mohler: Sampling from a universe of items and the De-Machiavellization of questionnaire design (9-14); Hubert Feger: Some analytical foundations of multidimensional scaling for ordinal data (15-40); Patrick J.F. Groenen, Ivo A. van der Lans: Multidimensional scaling with regional restrictions for facet theory: an application to Levy's political protest data (41-64); Arie Cohen: A comparison between factor analysis and smallest space analysis of the comprehensive scoring system of the Rorschach (65-72); Wolfgang Bilsky: On the structure of motives: beyond the 'big three' (73-84); Shlomit Levy, Dov Elizur: Values of veteran Israelis and new immigrants from the former Soviet Union: a facet analysis (85-104); Simon L. Dolan, Christian Acosta-Flamma: Values and propensity to adopt new HRM web-based technologies as determinants of HR efficiency and effectiveness: a firm level resource-based analysis (105-124); Sanjay T. Menon: Non-hierarchical emergent structure: a case study in alternative management (125-138); Christiane Spitzmüller, Dana M. Glenn: Organizational survey response: previous findings and an integrative framework (139-162); Thomas Staufenbiel, Maren Kroll, Cornelius J. König: Could job insecurity (also) be a motivator? (163-174); Michael Braun, Miriam Baumgärtner: The effects of work values and job characteristics on job satisfaction (175-188)

Report of the Working Group on Fishery Systems

Contributors: Poul Degnbol, Jon G. Sutinen, Kjellrun Hiis Hauge, Holder Hovgaard, Eskild Kirkegaard, Knut Korsbrekke, Paul Marchal, Sigbjørn Mehl, Jesper Raakjær Nielsen, Carl O'Brien, Martin Pastoors, Per Sparre, Robert Stephenson, Sigurd Tjelmelan

CONNECT for quality: protocol of a cluster randomized controlled trial to improve fall prevention in nursing homes

<p>Abstract</p> <p>Background</p> <p>Quality improvement (QI) programs focused on mastery of content by individual staff members are the current standard to improve resident outcomes in nursing homes. However, complexity science suggests that learning is a social process that occurs within the context of relationships and interactions among individuals. Thus, QI programs will not result in optimal changes in staff behavior unless the context for social learning is present. Accordingly, we developed CONNECT, an intervention to foster systematic use of management practices, which we propose will enhance effectiveness of a nursing home Falls QI program by strengthening the staff-to-staff interactions necessary for clinical problem-solving about complex problems such as falls. The study aims are to compare the impact of the CONNECT intervention, plus a falls reduction QI intervention (CONNECT + FALLS), to the falls reduction QI intervention alone (FALLS), on fall-related process measures, fall rates, and staff interaction measures.</p> <p>Methods/design</p> <p>Sixteen nursing homes will be randomized to one of two study arms, CONNECT + FALLS or FALLS alone. Subjects (staff and residents) are clustered within nursing homes because the intervention addresses social processes and thus must be delivered within the social context, rather than to individuals. Nursing homes randomized to CONNECT + FALLS will receive three months of CONNECT first, followed by three months of FALLS. Nursing homes randomized to FALLS alone receive three months of FALLs QI and are offered CONNECT after data collection is completed. Complexity science measures, which reflect staff perceptions of communication, safety climate, and care quality, will be collected from staff at baseline, three months after, and six months after baseline to evaluate immediate and sustained impacts. FALLS measures including quality indicators (process measures) and fall rates will be collected for the six months prior to baseline and the six months after the end of the intervention. Analysis will use a three-level mixed model.</p> <p>Discussion</p> <p>By focusing on improving local interactions, CONNECT is expected to maximize staff's ability to implement content learned in a falls QI program and integrate it into knowledge and action. Our previous pilot work shows that CONNECT is feasible, acceptable and appropriate.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00636675">NCT00636675</a></p

Multi-Source Data Fusion for Cyberattack Detection in Power Systems

Cyberattacks can cause a severe impact on power systems unless detected early. However, accurate and timely detection in critical infrastructure systems presents challenges, e.g., due to zero-day vulnerability exploitations and the cyber-physical nature of the system coupled with the need for high reliability and resilience of the physical system. Conventional rule-based and anomaly-based intrusion detection system (IDS) tools are insufficient for detecting zero-day cyber intrusions in the industrial control system (ICS) networks. Hence, in this work, we show that fusing information from multiple data sources can help identify cyber-induced incidents and reduce false positives. Specifically, we present how to recognize and address the barriers that can prevent the accurate use of multiple data sources for fusion-based detection. We perform multi-source data fusion for training IDS in a cyber-physical power system testbed where we collect cyber and physical side data from multiple sensors emulating real-world data sources that would be found in a utility and synthesizes these into features for algorithms to detect intrusions. Results are presented using the proposed data fusion application to infer False Data and Command injection-based Man-in- The-Middle (MiTM) attacks. Post collection, the data fusion application uses time-synchronized merge and extracts features followed by pre-processing such as imputation and encoding before training supervised, semi-supervised, and unsupervised learning models to evaluate the performance of the IDS. A major finding is the improvement of detection accuracy by fusion of features from cyber, security, and physical domains. Additionally, we observed the co-training technique performs at par with supervised learning methods when fed with our features

Feasibility study on dietary recommendations for older adults in the European Union

Despite mounting scientific evidence to support healthy and balanced diet in promoting active and healthy ageing, targeted, age-specific, and up-to-date dietary recommendations for older adults in Europe are not easy to find. On the 23-24 October 2014, the JRC organised an expert workshop "Feasibility study on dietary recommendations for older adults in the European Union" to discuss the need for dietary recommendations targeting older adults in Europe, and to identify strategies to promote better diet to prevent malnutrition in the older population. Twenty four experts from multiple disciplines related to nutrition and ageing from various European countries participated in the one and half day workshop. The overall consensus was that older adults, who are healthy may not need additional specific dietary recommendations as the current general adult population recommendations are likely to be sufficient, although some argued that even in healthy older adults, attention should still be paid to vitamin D and protein intakes. Participants identified and developed points for action for three main strategies/ working areas to promote better diet and reduce malnutrition in older adults. The strategies were 1) to develop targeted dietary guidelines for specific groups of older adults, 2) to implement general screening with a multi-disciplinary approach, and 3) to carry out additional research in a number of areas related to diet and ageing.JRC.I.2-Public Health Policy Suppor