Initial medication adherence-review and recommendations for good practices in outcomes research: an ISPOR medication adherence and persistence special interest group report

Background: Positive associations between medication adherence and beneficial outcomes primarily come from studying filling/consumption behaviors after therapy initiation. Few studies have focused on what happens before initiation, the point from prescribing to dispensing of an initial prescription. Objective: Our objective was to provide guidance and encourage high-quality research on the relationship between beneficial outcomes and initial medication adherence (IMA), the rate initially prescribed medication is dispensed. Methods: Using generic adherence terms, an international research panel identified IMA publications from 1966 to 2014. Their data sources were classified as to whether the primary source reflected the perspective of a prescriber, patient, or pharmacist or a combined perspective. Terminology and methodological differences were documented among core (essential elements of presented and unpresented prescribing events and claimed and unclaimed dispensing events regardless of setting), supplemental (refined for accuracy), and contextual (setting-specific) design parameters. Recommendations were made to encourage and guide future research. Results: The 45 IMA studies identified used multiple terms for IMA and operationalized measurements differently. Primary data sources reflecting a prescriber's and pharmacist's perspective potentially misclassified core parameters more often with shorter/nonexistent pre- and postperiods (1-14 days) than did a combined perspective. Only a few studies addressed supplemental issues, and minimal contextual information was provided. Conclusions: General recommendations are to use IMA as the standard nomenclature, rigorously identify all data sources, and delineate all design parameters. Specific methodological recommendations include providing convincing evidence that initial prescribing and dispensing events are identified, supplemental parameters incorporating perspective and substitution biases are addressed, and contextual parameters are included.

A privacy-preserving location tracking system for smartphones based on cloud storage

With the widespread use of smartphones, the loss of a device is a critical problem, which results both in disrupting daily communications and losing valuable property. As a result, tracking systems have been developed to track mobile devices. Previous tracking systems focus on recovering the device's locations after it goes missing, with security methods implemented on the clients. However, users' locations are stored in untrusted third-party services, which may be attacked or eavesdropped. In this paper, we propose a system, named Android Cloud Tracker, to provide a privacy-preserving tracking client and safe storing of user's locations. We use cloud storage controlled by users themselves as storage facilities, and they do not need to worry about any untrusted third party. We implement Android Cloud Tracker prototype on Android phones, and the evaluation shows that it is both practical and lightweight: it generates a small amount of data flow and its distributed architecture provides strong guarantees of location privacy while preserving the ability to efficiently track missing devices.

A differentially private algorithm for location data release

The rise of mobile technologies in recent years has led to large volumes of location information, which are valuable resources for knowledge discovery such as travel patterns mining and traffic analysis. However, location dataset has been confronted with serious privacy concerns because adversaries may re-identify a user and his/her sensitivity information from these datasets with only a little background knowledge. Recently, several privacy-preserving techniques have been proposed to address the problem, but most of them lack a strict privacy notion and can hardly resist the number of possible attacks. This paper proposes a private release algorithm to randomize location dataset in a strict privacy notion, differential privacy, with the goal of preserving users’ identities and sensitive information. The algorithm aims to mask the exact locations of each user as well as the frequency that the user visits the locations with a given privacy budget. It includes three privacy-preserving operations: private location clustering shrinks the randomized domain and cluster weight perturbation hides the weights of locations, while private location selection hides the exact locations of a user. Theoretical analysis on privacy and utility confirms an improved trade-off between privacy and utility of released location data. Extensive experiments have been carried out on four real-world datasets, GeoLife, Flickr, Div400 and Instagram. The experimental results further suggest that this private release algorithm can successfully retain the utility of the datasets while preserving users’ privacy.

Teacher knowledge, child interest and parent expectation: Factors influencing multicultural programs in an early childhood setting

© 2015, Early Childhood Australia Inc. All rights reserved. MULTICULTURAL CURRICULA/PROGRAMS assume an important role within a cultural approach to learning and teaching in early childhood education in New Zealand. Te Whariki, the national early childhood curriculum framework of New Zealand, is an emancipatory and socially constructive document that emphasises equity, social justice and the important position of culture in children's learning and development. In practice this means developing early childhood programs that are sensitive and responsive to the needs and interests of children and families of minority cultures. Drawing on a critical social constructivist framework, this study of one early childhood centre in New Zealand identifies the features of its multicultural curriculum. The paper argues that a devotion to supporting children of minority cultures has persisted in the curriculum, but there is a reliance on mainstream pedagogy focused on children's learning within the centre environment and teachers' subjective knowledge about children's needs.

Continuous discovery of co-location contexts from Bluetooth data

The discovery of contexts is important for context-aware applications in pervasive computing. This is a challenging problem because of the stream nature of data, the complexity and changing nature of contexts. We propose a Bayesian nonparametric model for the detection of co-location contexts from Bluetooth signals. By using an Indian buffet process as the prior distribution, the model can discover the number of contexts automatically. We introduce a novel fixed-lag particle filter that processes data incrementally. This sampling scheme is especially suitable for pervasive computing as the computational requirements remain constant in spite of growing data. We examine our model on a synthetic dataset and two real world datasets. To verify the discovered contexts, we compare them to the communities detected by the Louvain method, showing a strong correlation between the results of the two methods. Fixed-lag particle filter is compared with Gibbs sampling in terms of the normalized factorization error that shows a close performance between the two inference methods. As fixed-lag particle filter processes a small chunk of data when it comes and does not need to be restarted, its execution time is significantly shorter than that of Gibbs sampling.

The introduction of an undergraduate interventional radiology (IR) curriculum: impact on medical student knowledge and interest in IR

INTRODUCTION: Interventional radiology (IR) plays a vital role in modern medicine, with increasing demand for services, but with a shortage of experienced interventionalists. The aim of this study was to determine the impact of a recently introduced IR curriculum on perception, knowledge, and interest of medical students regarding various aspects of IR. METHODS: In 2014, an anonymous web-based questionnaire was sent to 309 4th year medical students in a single institution within an EU country, both before and after delivery of a 10-h IR teaching curriculum. RESULTS: Seventy-six percent (236/309) of the respondents participated in the pre-IR module survey, while 50 % (157/309) responded to the post-IR module survey. While 62 % (147/236) of the respondents reported poor or no knowledge of IR compared to other medical disciplines in the pre-IR module survey, this decreased to 17 % (27/157) in the post-IR module survey. The correct responses regarding knowledge of selected IR procedures improved from 70 to 94 % for venous access, 78 to 99 % for uterine fibroid embolization, 75 to 97 % for GI bleeding embolization, 60 to 92 % for trauma embolization, 71 to 92 % for tumor ablation, and 81 to 94 % for angioplasty and stenting in peripheral arterial disease. With regard to knowledge of IR clinical roles, responses improved from 42 to 59 % for outpatient clinic review of patients and having inpatient beds, 63-76 % for direct patient consultation, and 43-60 % for having regular ward rounds. The number of students who would consider a career in IR increased from 60 to 73 %. CONCLUSION: Delivering an undergraduate IR curriculum increased the knowledge and understanding of various aspects of IR and also the general enthusiasm for pursuing this specialty as a future career choice.

A framework for classifying online mental health related communities with an interest in depression

Mental illness has a deep impact on individuals, families, and by extension, society as a whole. Social networks allow individuals with mental disorders to communicate with others sufferers via online communities, providing an invaluable resource for studies on textual signs of psychological health problems. Mental disorders often occur in combinations, e.g., a patient with an anxiety disorder may also develop depression. This co-occurring mental health condition provides the focus for our work on classifying online communities with an interest in depression. For this, we have crawled a large body of 620,000 posts made by 80,000 users in 247 online communities. We have extracted the topics and psycho-linguistic features expressed in the posts, using these as inputs to our model. Following a machine learning technique, we have formulated a joint modelling framework in order to classify mental health-related co-occurring online communities from these features. Finally, we performed empirical validation of the model on the crawled dataset where our model outperforms recent state-of-the-art baselines.

DoSTra: Discovering common behaviors of objects using the duration of staying on each location of trajectories

Since semantic trajectories can discover more semantic meanings of a user's interests without geographic restrictions, research on semantic trajectories has attracted a lot of attentions in recent years. Most existing work discover the similar behavior of moving objects through analysis of their semantic trajectory pattern, that is, sequences of locations. However, this kind of trajectories without considering the duration of staying on a location limits wild applications. For example, Tom and Anne have a common pattern of Home→Restaurant → Company → Restaurant, but they are not similar, since Tom works at Restaurant, sends snack to someone at Company and return to Restaurant while Anne has breakfast at Restaurant, works at Company and has lunch at Restaurant. If we consider duration of staying on each location we can easily to differentiate their behaviors. In this paper, we propose a novel approach for discovering common behaviors by considering the duration of staying on each location of trajectories (DoSTra). Our approach can be used to detect the group that has similar lifestyle, habit or behavior patterns and predict the future locations of moving objects. We evaluate the experiment based on synthetic dataset, which demonstrates the high effectiveness and efficiency of the proposed method.

Estimated Number and Location of Future Moose-Vehicle Collisions (MVC) in Maine

Moose (Alces alces) are a keystone herbivore in Maine. Because of the large number of rural roads in Maine, there is a high rate of moose-vehicle collisions (MVCs), which is increasing. On-road encounters with animals resulted in 231 fatalities in the United States in 1999. Because of the fatality of MVCs, it is important to know where they are most likely to occur. I used GIS analysis to estimate where future MVCs would occur, factoring in the variables of land cover suitability for moose, distance from water bodies, locations of past MVCs, and speed limits on the roads. I ran four different analyses, each one weighting the variables equally. I also ran a regression to determine if increasing road speed was associated with the increase in the number of MVCs per length of road. There was not a strong positive relationship between the number of MVCs per length of road and the speed limit, but it was interesting to note that there were more MVCs per length of road on 35mph and 40mph roads than on 45, 50, 55 or 65mph roads. Future research on MVCs would benefit from the inclusion of include moose population density and road traffic data.

Volunteered Geographic Information For Water Management: A Prototype Architecture

Driven by Web 2.0 technology and the almost ubiquitous presence of mobile devices, Volunteered Geographic Information (VGI) is knowing an unprecedented growth. These notable technological advancements have opened fruitful perspectives also in the field of water management and protection, raising the demand for a reconsideration of policies which also takes into account the emerging trend of VGI. This research investigates the opportunity of leveraging such technology to involve citizens equipped with common mobile devices (e.g. tablets and smartphones) in a campaign of report of water-related phenomena. The work is carried out in collaboration with ADBPO - Autorità di bacino del fiume Po (Po river basin Authority), i.e. the entity responsible for the environmental planning and protection of the basin of river Po. This is the longest Italian river, spreading over eight among the twenty Italian Regions and characterized by complex environmental issues. To enrich ADBPO official database with user-generated contents, a FOSS (Free and Open Source Software) architecture was designed which allows not only user field-data collection, but also data Web publication through standard protocols. Open Data Kit suite allows users to collect georeferenced multimedia information using mobile devices equipped with location sensors (e.g. the GPS). Users can report a number of environmental emergencies, problems or simple points of interest related to the Po river basin, taking pictures of them and providing other contextual information. Field-registered data is sent to a server and stored into a PostgreSQL database with PostGIS spatial extension. GeoServer provides then data dissemination on the Web, while specific OpenLayers-based viewers were built to optimize data access on both desktop computers and mobile devices. Besides proving the suitability of FOSS in the frame of VGI, the system represents a successful prototype for the exploitation of user local, real-time information aimed at managing and protecting water resources.

An ordering of measures of the welfare cost of inflation in economies with interest-bearing deposits

This paper builds on Lucas (2000) and on Cysne (2003) to derive and order six alternative measures of the welfare costs of inflation (five of which already existing in the literature) for any vector of opportunity costs. The ordering of the functions is carried out for economies with or without interestbearing deposits. We provide examples and closed-form solutions for the log-log money demand both in the unidimensional and in the multidimensional setting (when interest-bearing monies are present). An estimate of the maximum relative error a researcher can incur when using any particular measure is also provided.

Cyclical Interest Payments on Inside Money

Rio de Janeiro

Trade or investment? location decisions under regional integration

This paper studies the production and trade patterns that may arise between two different countries if plant location is introduced as a first step in the producers' decision making. A three-stage game is used: the first deals with location and the next two with capacity and final sales decisions. Demand and cost structures differ by country, and the latter contain specific elements related to the foreign operation. The structure of possible Nash-equilibria is examined and an analysis of the changes in the solution, if the countries engage in an integration process, is made. As in previous models, though global welfare gains may not be very high, single country ones may be considerable, due to changes in the location of the plants. However, even if full integration takes place, global Marshallian welfare may decrease. Conditions which determine a tendency towards multinationalisation are obtained. Assuming a move toward integration, conditions are also provided to characterize when exporting will be preferred to local production. The fact that producers may retain a certain discriminating power, notwithstanding the elimination of barriers to arbitrage, creates a tendency to locate production in the country where prices are higher. This explains why welfare gains may not be obvious. An empirical illustration, with real data from two MERCOSUL countries (Brazil and Argentina) illustrates the possible outcomes.