Interprofessional collaboration in nursing homes (interprof): A grounded theory study of general practitioner experiences and strategies to perform nursing home visits

Background: Interprofessionalism, considered as collaboration between medical professionals, has gained prominence over recent decades and evidence for its impact has grown. The steadily increasing number of residents in nursing homes will challenge medical care and the interaction across professions, especially nurses and general practitioners (GPS). The nursing home visit, a key element of medical care, has been underrepresented in research. This study explores GP perspectives on interprofessional collaboration with a focus on their visits to nursing homes in order to understand their experiences and expectations. This research represents an aspect of the interprof study, which explores medical care needs as well as the perceived collaboration and communication by nursing home residents, their families, GPS and nurses. This paper focusses on GPS' views, investigating in particular their visits to nursing homes in order to understand their experiences. Methods: Open guideline-interviews covering interprofessional collaboration and the visit process were conducted with 30 GPS in three study centers and analyzed with grounded theory methodology. GPS were recruited via postal request and existing networks of the research partners. Results: Four different types of nursing home visits were found: visits on demand, periodical visits, nursing home rounds and ad-hoc-decision based visits. We identified the core category "productive performance" of home visits in nursing homes which stands for the balance of GPŚ individual efforts and rewards. GPS used different strategies to perform a productive home visit: preparing strategies, on-site strategies and investing strategies. Conclusion: We compiled a theory of GPS home visits in nursing homes in Germany. The findings will be useful for research, and scientific and management purposes to generate a deeper understanding of GP perspectives and thereby improve interprofessional collaboration to ensure a high quality of care.

Techniques for batch reinforcement learning in robotics

This thesis addresses the Batch Reinforcement Learning methods in Robotics. This sub-class of Reinforcement Learning has shown promising results and has been the focus of recent research. Three contributions are proposed that aim to extend the state-of-art methods allowing for a faster and more stable learning process, such as required for learning in Robotics. The Q-learning update-rule is widely applied, since it allows to learn without the presence of a model of the environment. However, this update-rule is transition-based and does not take advantage of the underlying episodic structure of collected batch of interactions. The Q-Batch update-rule is proposed in this thesis, to process experiencies along the trajectories collected in the interaction phase. This allows a faster propagation of obtained rewards and penalties, resulting in faster and more robust learning. Non-parametric function approximations are explored, such as Gaussian Processes. This type of approximators allows to encode prior knowledge about the latent function, in the form of kernels, providing a higher level of exibility and accuracy. The application of Gaussian Processes in Batch Reinforcement Learning presented a higher performance in learning tasks than other function approximations used in the literature. Lastly, in order to extract more information from the experiences collected by the agent, model-learning techniques are incorporated to learn the system dynamics. In this way, it is possible to augment the set of collected experiences with experiences generated through planning using the learned models. Experiments were carried out mainly in simulation, with some tests carried out in a physical robotic platform. The obtained results show that the proposed approaches are able to outperform the classical Fitted Q Iteration.

“Adição ao Jogo online”

Esta dissertação visa compreender a adição ao jogo online, através de duas perspetivas complementares que se congregam num estudo de caso. Analisamos o discurso de um jogador predominantemente de Blackjack online adicto a esta prática (F.) em processo de desabituação, e desenvolvemos a mesma metodologia junto da mãe deste, enquanto fonte complementar de informação, através de entrevistas semi-estruturadas. Desta análise emergiram resultados que clarificam os fatores que funcionam como determinantes da adição, que a mantêm bem como elementos indispensáveis para compreender a decisão de paragem do jogo. Nesta dinâmica conjugamos a perspetiva de F e da sua mãe. A metodologia escolhida para análise dos dados de investigação foi a Grounded Analysis Theory, partindo das vozes dos dois participantes e tendo como objetivo a construção de uma narrativa alternativa e assim contribuir para uma melhor análise de compreensão dos dados obtidos. Através de um processo indutivo de produção de conhecimento organizado e obedecendo a uma sequência que busca uma maior complexidade de integração, tem como objetivo final gerar uma teoria sustentada nos dados recolhidos (Fernandes & Maia, 2001). Enquanto metodologia qualitativa permite-nos aceder aos significados múltiplos que emergiram da experiência destes dois participantes. O jogo online sustentado na sua fácil disponibilidade tem como consequência um maior isolamento do jogador, e uma vez que as recompensas financeiras são uma possibilidade alimenta o ciclo do comportamento aditivo. A observância de problemas físicos e psicológicos percebidos como graves, justificaram uma abordagem de tratamento multidisciplinar, envolvendo ajuda farmacológica, psicológica e social. Os estudos existentes sobre o jogo online são ainda muito escassos, justificandose o estudo qualitativo na construção do conhecimento, pela análise mais detalhada dos fatores que podem contribuir para uma melhor compreensão de todas as especificidades presentes, numa perturbação aditiva ao jogo online.

Energy efficient measures to reduce electrical energy use in commercial buildings in New York City

GEA Consulting Engineers, acting as the design engineers, was hired by the owner, East Village 207 Residential LLC2 for energy modeling for compliance with LEED NC V3 -- This report details the results of the energy simulation done with the 100% construction documents -- This report only refers to entities within the LEED3 project boundary -- The project consists of a new eight-story high-end residential condominium building with 81 units, as shown in illustration 1, and approximately 117,905 GSF, equivalent to 10,953.73 m2, is located at 211 E 13th Street in New York, NY -- The residential portion of the building will function 24-7 -- The design goal is to utilize energy efficient measures to reduce electrical energy use and aims to achieve LEED certification -- LEED EA Credit 14 requires a building to demonstrate a percentage improvement in the proposed building performance compared with the baseline building -- The Credit rewards 1 point for achieving 12% reduction in energy costs -- Additionally, the Credit rewards another point for each subsequent reduction of 2% in the building’s energy cost

Anatomy in the Library: Anatomical Models on Course Reserves

In Fall 2015, the Engineering and Physical Science Library (EPSL) began lending anatomical models as part of its course reserves program. EPSL received a partial skeleton and two muscle model figures from instructors of BSCI105. These models circulate for 4 hours at a time and are generally used by small, collaborative groups of students in the library. This poster will look at the challenges and rewards for adding these items to EPSL’s course reserves.

Avaliação da Liderança, Motivação e Recompensa

O ambiente organizacional no mundo globalizado actual é altamente instável, como consequência quer a gestão estratégica quer a sua implementação operacional, são solicitadas constantemente a adaptar-se a novos modelos de gestão e suscitam problemas às organizações que fazem sentir os seus efeitos transversalmente, uma das áreas que faz ressonância destas constantes mudanças são os Recursos Humanos. O presente trabalho centra-se no segmento restrito dessa realidade que se focaliza na liderança, motivação e recompensa. O objecto da investigação é uma instituição bancária em Luanda (Angola), como instrumento de investigação foi usado um inquérito, cujas questões decorreram do acervo conceptual patente na literatura. Concluiu-se que a avaliação da liderança é simétrica à avaliação da recompensa e que a motivação apresenta um perfil aproximado à média geral, analisados os dados em função das categorias das variáveis sociodemográficas, foi possível concluir que em múltiplas instâncias, elas condicionam e sobre determinam os resultados globais.

Síndromes de polinização ocorrentes em uma área de Mata Atlântica, Paraíba, Brasil

ARAUJO, Afranio Cesar de et al. Síndromes de polinização ocorrentes em uma área de Mata Atlântica, Paraíba, Brasil. Biotemas, Florianopolis, v. 4, n. 22, p.83-94, dez. 2009. Disponível em: . Acesso em: 04 out. 2010.

Modelagem em programação linear para resolução de jogos fuzzy intervalares

A teoria de jogos modela estratégias entre agentes (jogadores), os quais possuem recompensas ao fim do jogo conforme suas ações. O melhor par de estratégias para os jogadores constitui uma solução de equilíbrio. Porém, nem sempre se consegue estimar os dados do problema. Diante disso, os parâmetros incertos presentes em modelos de jogos são formalizados pela teoria fuzzy. Assim, a teoria fuzzy auxilia a teoria de jogos, formando jogos fuzzy. Dessa forma, parâmetros, como as recompensas, tornam-se números fuzzy. Mais ainda, quando há incerteza na representação desses números fuzzy utilizam-se os números fuzzy intervalares. Então, neste trabalho modelos de jogos fuzzy intervalares são analisados e métodos computacionais são desenvolvidos para a resolução desses jogos. Por fim, realizam-se simulações de programação linear para observar melhor a aplicação das teorias estudadas e avaliar a proposta.

ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

A rewarding experience? Exploring how crowdfunding is affecting music industry business models.

This paper provides an exploratory study of how rewards-based crowdfunding affects business model development for music industry artists, labels and live sector companies. The empirical methodology incorporated a qualitative, semi-structured, three-stage interview design with fifty seven senior executives from industry crowdfunding platforms and three stakeholder groups. The results and analysis cover new research ground and provide conceptual models to develop theoretical foundations for further research in this field. The findings indicate that the financial model benefits of crowdfunding for independent artists are dependent on fan base demographic variables relating to age group and genre due to sustained apprehension from younger audiences. Furthermore, major labels are now considering a more user-centric financial model as an innovation strategy, and the impact of crowdfunding on their marketing model may already be initiating its development in terms of creativity, strength and artist relations.

An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering

This paper proposes a new memetic evolutionary algorithm to achieve explicit learning in rule-based nurse rostering, which involves applying a set of heuristic rules for each nurse's assignment. The main framework of the algorithm is an estimation of distribution algorithm, in which an ant-miner methodology improves the individual solutions produced in each generation. Unlike our previous work (where learning is implicit), the learning in the memetic estimation of distribution algorithm is explicit, i.e. we are able to identify building blocks directly. The overall approach learns by building a probabilistic model, i.e. an estimation of the probability distribution of individual nurse-rule pairs that are used to construct schedules. The local search processor (i.e. the ant-miner) reinforces nurse-rule pairs that receive higher rewards. A challenging real world nurse rostering problem is used as the test problem. Computational results show that the proposed approach outperforms most existing approaches. It is suggested that the learning methodologies suggested in this paper may be applied to other scheduling problems where schedules are built systematically according to specific rules.

The Relation between Substance Use and Medication Adherence among HIV Positive Substance Users in Residential Treatment

Poor medication adherence is problematic among HIV positive, low-income African-American substance users. Substance use has been shown to be associated with poor medication adherence, though we do not know the mechanism that underlies this relationship. Lack of positive environmental rewards and the propensity to discount delayed rewards may be possible mechanisms to explain this relationship. Using baseline data from a randomized controlled trial, we examined the relationships between substance use and medication adherence, testing both environmental rewards and delay discounting as independent mediators. There was a main effect of substance use on adherence, such that high frequency of substance use predicted poor adherence. There was also a main effect of environmental rewards on adherence, such that a lack of environmental reinforcement predicted poor adherence. This study shed light on the processes that contribute to low adherence, namely substance use and lack of environmental contingencies, and suggests important targets for intervention.

Género, idade e antiguidade na empresa : Uma análise comparativa de contracto psicológico.

Poucos são os estudos que relacionam variáveis de nível individual como o género, idade e antiguidade na empresa, com a percepção de contracto psicológico, no entanto para além destas variáveis moldarem o conteúdo do contracto psicológico (Guest, 2004), parecem também determinar diferentes valores e interesses de trabalho (Elizur, 1994; Bal, Lange, Jansen e Velde, 2008). Tais evidências chamam a atenção das organizações para o facto de diferentes grupos de trabalhadores apresentarem diferentes percepções de contracto psicológico, podendo consequentemente responder de diferente forma às mesmas políticas organizacionais (Freese & Schalk, 1996). O presente estudo procurou perceber se diferentes grupos de trabalhadores, de diferentes géneros, idades e antiguidades apresentam diferentes percepções de contracto psicológico, procurando posteriormente aceder às causas percebidas de quebra de contracto (Renegação, Disrupção, Incongruência e Anulação), mencionadas na literatura por Rousseau (1995) e Morrinson e Robinson (1997). Foi utilizada uma amostra, recolhida por conveniência, de 83 participantes pertencentes a uma empresa do sector alimentar, constituída por 57,8% de mulheres e 42,2% de homens. Em média possuem 37 anos de idade e 9 anos de antiguidade na empresa. Foi aplicado um questionário, desenvolvido por Lester, Turnley, Bloodgood e Bolino (2002) constituído por diferentes dimensões (Compensação, Recompensas com base na performance, Características da Função, Progressão e Desenvolvimento, Recursos e Relação Laboral) que constituem o contracto psicológico, assim como pelas diferentes causas percebidas de incumprimento da promessa. Após uma análise factorial, foram extraídos 5 factores (Características da Função, Relação Laboral, Compensação, Recursos e Progressão e Recompensas com base na performance). Os resultados demonstraram que os trabalhadores mais velhos percepcionam que a sua empresa lhes proporciona menos do que o prometido relativamente à Compensação, resultados igualmente obtidos para os trabalhadores com mais antiguidade na empresa. Uma posterior análise correlacional demonstrou que a idade está associada com a antiguidade dos trabalhadores. Quanto à causa percebida de incumprimento, os resultados evidenciaram que a maioria dos trabalhadores atribui o incumprimento das promessas à Renegação. Por outras palavras, os trabalhadores entendem que a sua organização não cumpriu as promessas que lhes fez, simplesmente porque assim o quis.

An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering

This paper proposes a new memetic evolutionary algorithm to achieve explicit learning in rule-based nurse rostering, which involves applying a set of heuristic rules for each nurse's assignment. The main framework of the algorithm is an estimation of distribution algorithm, in which an ant-miner methodology improves the individual solutions produced in each generation. Unlike our previous work (where learning is implicit), the learning in the memetic estimation of distribution algorithm is explicit, i.e. we are able to identify building blocks directly. The overall approach learns by building a probabilistic model, i.e. an estimation of the probability distribution of individual nurse-rule pairs that are used to construct schedules. The local search processor (i.e. the ant-miner) reinforces nurse-rule pairs that receive higher rewards. A challenging real world nurse rostering problem is used as the test problem. Computational results show that the proposed approach outperforms most existing approaches. It is suggested that the learning methodologies suggested in this paper may be applied to other scheduling problems where schedules are built systematically according to specific rules.

Art, Archives and Accessions

Presentation from the MARAC conference in Boston, MA on March 18-21, 2015. S3 - Museum Institutional Records: Stewardship and Advocacy, Challenges and Rewards