The U.S. Newspaper Industry in Transition

[Excerpt] The U.S. newspaper industry is suffering through what could be its worst financial crisis since the Great Depression. Advertising revenues are plummeting due to the severe economic downturn, while readership habits are changing as consumers turn to the Internet for free news and information. Some major newspaper chains are burdened by heavy debt loads. In the past year, seven major newspaper chains have declared bankruptcy, several big city papers have shut down, and many have laid off reporters and editors, imposed pay reductions, cut the size of the physical newspaper, or turned to Web-only publication. As the problems intensify, there are growing concerns that the rapid decline of the newspaper industry will impact civic and social life. Already there are fewer newspaper reporters covering state capitols and city halls, while the number of states with newspapers covering Congress full-time has dwindled to 23 from the most recent peak of 35 in 1985. As old-style, print newspapers decline, new journalism startups are developing around the country, aided by low entry costs on the Internet. The emerging ventures hold promise but do not have the experience, resources, and reach of shrinking mainstream newspapers. Congress has begun debating whether the financial problems in the newspaper industry pose a public policy issue that warrants federal action. Whether a congressional response to the current turmoil is justified may depend on the current causes of the crisis. If the causes are related to significant technological shifts (the Internet, smart phones and electronic readers) or societal changes that are disruptive to established business models and means of news dissemination, the policy options may be quite limited, especially if new models of reporting (and, equally important, advertising) are beginning to emerge. Governmental policy actions to bolster existing businesses could stall or retard such a shift. In this case, policymakers might stand back and allow the market to realign news gathering and delivery, as it has many times in the past. If, on the other hand, the current crisis is related to the struggle of some major newspapers to survive the current recession, possible policy options to ensure the continuing availability of in-depth local and national news coverage by newspapers might include providing tax breaks, relaxing antitrust policy, tightening copyright law, providing general support for the practice of journalism by increasing funding for the Corporation for Public Broadcasting (CPB) or similar public programs, or helping newspapers reorganize as nonprofit organizations. Policymakers may also determine that some set of measures could ease the combination of social and technological transition and the recession-related financial distress of the industry

The Use of Dining Data to Increase Retention and Academic Success in Residential First-Year Students

Higher education leaders have been conducting research over the last 50 years to pinpoint why students enroll in college and then end up leaving. Research shows that there is not a single factor that influences a student’s decision, but it is a variety of factors. Influential factors include class attendance, a sense of belonging, motivation, academic rigor and performance, finances, and more. A student’s physical wellness and mental state can also impact their academic success and life while in college. First-year students often experience depression, anxiety, and loneliness as they try to successfully transition to college. Most of these influential factors are quantified and measured by institutions in real-time through predictive analytics to identify students at risk of leaving. One data point that has not been thoroughly researched is dining data. This non-experimental, causal-comparison study investigated the relationship between dining data and academic success and retention. Analysis of the data showed that dining data can predict academic success and retention, however, the strongest correlation existed between a significant change in dining habits predicting persistence into the next semester. The findings indicate that dining data should be collected by institutions and integrated into predictive analytics to identify at-risk students. Further research should be conducted to generalize the use of dining data in predictive analytics as well as investigate how dining data can be paired with other data points to further identify students in need of assistance

Behavioral Economics and Developmental Science: A New Framework to Support Early Childhood Interventions

Public policies have actively responded to an emergent social and neuroscientific evidence base documenting the benefits of targeting services to children during the earliest period of their development. But problems of low utilization, inconsistent participation, and low retention continue to present themselves as challenges. Although most interventions recognize and address structural and psycho-social barriers to parent’s engagement, few take seriously the decision making roles of parents. Using insights from the behavioral sciences, we revisit assumptions about the presumed behavior of parents in a developmental context. We then describe ways in which this framework informs features of interventions that can be designed to augment the intended impacts of early development, education and care initiatives by improving parent engagement

Employing Environmental Data and Machine Learning to Improve Mobile Health Receptivity

Behavioral intervention strategies can be enhanced by recognizing human activities using eHealth technologies. As we find after a thorough literature review, activity spotting and added insights may be used to detect daily routines inferring receptivity for mobile notifications similar to just-in-time support. Towards this end, this work develops a model, using machine learning, to analyze the motivation of digital mental health users that answer self-assessment questions in their everyday lives through an intelligent mobile application. A uniform and extensible sequence prediction model combining environmental data with everyday activities has been created and validated for proof of concept through an experiment. We find that the reported receptivity is not sequentially predictable on its own, the mean error and standard deviation are only slightly below by-chance comparison. Nevertheless, predicting the upcoming activity shows to cover about 39% of the day (up to 58% in the best case) and can be linked to user individual intervention preferences to indirectly find an opportune moment of receptivity. Therefore, we introduce an application comprising the influences of sensor data on activities and intervention thresholds, as well as allowing for preferred events on a weekly basis. As a result of combining those multiple approaches, promising avenues for innovative behavioral assessments are possible. Identifying and segmenting the appropriate set of activities is key. Consequently, deliberate and thoughtful design lays the foundation for further development within research projects by extending the activity weighting process or introducing a model reinforcement.BMBF, 13GW0157A, Verbundprojekt: Self-administered Psycho-TherApy-SystemS (SELFPASS) - Teilvorhaben: Data Analytics and Prescription for SELFPASSTU Berlin, Open-Access-Mittel - 201

Socio-economic inequalities in health in Catalonia

In this paper we measure the degree of income related inequality in mental health as measured by the GHQ instrument and general health as measured by the EQOL-5D instrument for the Catalan population. We find that income is the main contributor to inequality, although the share of inequality in mental health that can be explained by income is much greater than the corresponding share of inequality in general health. We also find that the variation in demographic structure reduces income related inequality in mental health but increases income related inequality in general health. The regional variations in both instruments for health are striking, with the Barcelona districts faring relatively bad with respect to the rest of geographical areas and Lleida being the health region where, all else held equal, the population reports the greatest level of health. A big share of inequality in the two health measures, but specially mental health, is due to the favourable position in both health and income of those who enjoy an indefinite contract with respect to the rest of individuals. We also find that risky working conditions affect both health measures and are able to explain an important share of socio-economic inequality.Health inequalities, decomposition analysis, Spain

Surveillance, big data and democracy: lessons for Australia from the US and UK

This article argues that current laws are ill-equipped to deal with the multifaceted threats to individual privacy by governments, corporations and our own need to participate in the information society. Introduction In the era of big data, where people find themselves surveilled in ever more finely granulated aspects of their lives, and where the data profiles built from an accumulation of data gathered about themselves and others are used to predict as well as shape their behaviours, the question of privacy protection arises constantly. In this article we interrogate whether the discourse of privacy is sufficient to address this new paradigm of information flow and control. What we confront in this area is a set of practices concerning the collection, aggregation, sharing, interrogation and uses of data on a scale that crosses private and public boundaries, jurisdictional boundaries, and importantly, the boundaries between reality and simulation. The consequences of these practices are emerging as sometimes useful and sometimes damaging to governments, citizens and commercial organisations. Understanding how to regulate this sphere of activity to address the harms, to create an infrastructure of accountability, and to bring more transparency to the practices mentioned, is a challenge of some complexity. Using privacy frameworks may not provide the solutions or protections that ultimately are being sought. This article is concerned with data gathering and surveillance practices, by business and government, and the implications for individual privacy in the face of widespread collection and use of big data. We will firstly outline the practices around data and the issues that arise from such practices. We then consider how courts in the United Kingdom (‘UK’) and the United States (‘US’) are attempting to frame these issues using current legal frameworks, and finish by considering the Australian context. Notably the discourse around privacy protection differs significantly across these jurisdictions, encompassing elements of constitutional rights and freedoms, specific legislative schemes, data protection, anti-terrorist and criminal laws, tort and equity. This lack of a common understanding of what is or what should be encompassed within privacy makes it a very fragile creature indeed. On the basis of the exploration of these issues, we conclude that current laws are ill-equipped to deal with the multifaceted threats to individual privacy by governments, corporations and our own need to participate in the information society

A Program for the Comprehensive Cognitive Training of Excess Weight (TRAINEP): The Study Protocol for A Randomized, Controlled Trial

Background: The available treatments for people with excess weight have shown small effects. Cognitive training has shown promising results, but most of the research focused on normalweight university students and reported immediate results after a single training session. This parallel group, randomized, controlled trial aims to study the efficacy of a program for the comprehensive cognitive treatment of excess weight. Methods and Analysis: Participants will be 150 people with excess weight recruited through social media, who will be randomized into three groups: cognitive intervention, sham cognitive intervention, and treatment as usual. All assessment and intervention sessions will be online in groups of 5–6 participants. The three groups will attend a motivational interviewing session, and they will receive individualized diet and physical exercise guidelines throughout the program. The cognitive training will consist of four weekly sessions of approximately 60–90 min, each based on approach–avoidance bias training, inhibitory control training, implementation of intentions, and episodic future thinking, respectively. The main outcome measure will be a change in Body Mass Index (kg/m2). Secondary outcomes include changes in cognitive measures, eating and physical exercise behaviors, and anthropometric measures. Assessments will be conducted up to 6 months after the end of the program. In addition, data on the use of the health system will be collected to analyze the cost-effectiveness and the cost-utility of training. Linear mixed models will be used for statistical analysis. Findings of this study will expand the available evidence on cognitive interventions to reduce excess weight.Spanish Ministry of Science, Innovation, and Universities MCIN/AEIEuropean Regional Development Fund "ERDF A way of making Europe" RTI2018-098771-B-I0

Stories of Impact from the Social Innovation Fund

The Social Innovation Fund is an initiative of the federal government's Corporation for National and Community Service intended to improve the lives of people in low-income communities. It does so by mobilizing public and private resources to grow promising and innovative community-based solutions that have evidence of compelling impact in three areas of priority need: economic opportunity, healthy futures and youth development.The Social Innovation Fund promotes an approach to giving that includes many of the fundamentals that members of the GEO community helped pioneer and have long advocated for, and the fund is aligned with GEO's own mission to promote grantmaking strategies and practices that contribute to grantee success. GEO, through the Scaling What Works initiative, and the Corporation for National and Community Service collected stories that showcase the work of Social Innovation Fund grantees in their communities. These stories feature individuals and families who have benefited from the programs and services of nonprofits receiving support through the Social Innovation Fund and its private philanthropic partners, and they show the ways in which these high-performing organizations are growing their impact within communities across the nation