OBJECTIVES: To identify the prevalence and family and community-level predictors of comorbid speech-language difficulties and socioemotional and behavioral (SEB) difficulties across a population of children at school entry. METHODS: The School Entry Health Questionnaire is a parent survey of children's health and wellbeing, completed by all children starting school in Victoria, Australia (N = 53256). It includes parental report of speech-language difficulties, the Strengths and Difficulties Questionnaire (behavior), and numerous family and community variables. Following univariate analysis, family and community risk characteristics were entered into a multinomial logistic regression model to identify the associated relative risk of comorbid speech/language and SEB needs. The influence of experiencing multiple risk factors was also examined. RESULTS: 20.4% (n = 10,868) began school with either speech-language or SEB difficulties, with 3.1% (n = 1670) experiencing comorbid needs. Five factors predicted comorbidity: the child having witnessed violence; a history of parent mental illness; living in more deprived communities; and the educational attainment of each parent (independently). The relative risk of comorbidity was 6.1 (95% Confidence Interval: 3.9, 9.7) when a child experienced four or more risk factors, compared to those with no risk factors. CONCLUSIONS: The risk of comorbidity in early childhood is associated with a range of family and community factors, and elevated by the presence of multiple factors. Children growing up in families experiencing multiple, complex needs are therefore at heightened risk of the early development of difficulties likely to impact upon schooling. Early identification of these children offers opportunities for appropriate and timely health and education intervention.

Health data have enormous potential to transform healthcare, health service design, research, and individual health management. However, health data collected by institutions tend to remain siloed within those institutions limiting access by other services, individuals or researchers. Further, health data generated outside health services (e.g., from wearable devices) may not be easily accessible or useable by individuals or connected to other parts of the health system. There are ongoing tensions between data protection and the use of data for the public good (e.g., research). Concurrently, there are a number of data platforms that provide ways to disrupt these traditional health data siloes, giving greater control to individuals and communities. Through four case studies, this paper explores platforms providing new ways for health data to be used for personal data sharing, self-health management, research, and clinical care. The case-studies include data platforms: PatientsLikeMe, Open Humans, Health Record Banks, and unforgettable.me. These are explored with regard to what they mean for data access, data control, and data governance. The case studies provide insight into a shift from institutional to individual data stewardship. Looking at emerging data governance models, such as data trusts and data commons, points to collective control over health data as an emerging approach to issues of data control. These shifts pose challenges as to how “traditional” health services make use of data collected on these platforms. Further, it raises broader policy questions regarding how to decide what public good data should be put towards.

Global investment in biomedical research has grown significantly over the last decades, reaching approximately a quarter of a trillion US dollars in 2010. However, not all of this investment is distributed evenly by gender. It follows, arguably, that scarce research resources may not be optimally invested (by either not supporting the best science or by failing to investigate topics that benefit women and men equitably). Women across the world tend to be significantly underrepresented in research both as researchers and research participants, receive less research funding, and appear less frequently than men as authors on research publications. There is also some evidence that women are relatively disadvantaged as the beneficiaries of research, in terms of its health, societal and economic impacts. Historical gender biases may have created a path dependency that means that the research system and the impacts of research are biased towards male researchers and male beneficiaries, making it inherently difficult (though not impossible) to eliminate gender bias. In this commentary, we - a group of scholars and practitioners from Africa, America, Asia and Europe - argue that gender-sensitive research impact assessment could become a force for good in moving science policy and practice towards gender equity. Research impact assessment is the multidisciplinary field of scientific inquiry that examines the research process to maximise scientific, societal and economic returns on investment in research. It encompasses many theoretical and methodological approaches that can be used to investigate gender bias and recommend actions for change to maximise research impact. We offer a set of recommendations to research funders, research institutions and research evaluators who conduct impact assessment on how to include and strengthen analysis of gender equity in research impact assessment and issue a global call for action.

The development community has looked to engineering, social action, planning and evaluation to understand the often inexplicable outcomes of water implementation projects. This paper gives an overview of research that uses Complex Adaptive Systems theory as a framework to investigate the unpredictability of outcomes for community water supply projects. Preliminary interviews and surveys in a remote village in East Timor are used to investigate the viability of social network analysis and system dynamics as tools to make sense of WASH program outcomes.

The importance of journalism to civil society is constantly proclaimed, but empirical evidence on journalism's impact, and how this operates, is surprisingly thin. Indeed, there is confusion even about what is meant by the term “impact”. Meanwhile, the issue of the role of journalism is becoming increasingly urgent as a consequence of the rapid changes engulfing the news media, brought about by technological change and the flow-on effect to the traditional advertising-supported business model. Assessing the impact of journalism has recently been the topic of debate among practitioners and scholars particularly in the United States, where philanthropists have responded to the perceived crisis in investigative journalism by funding not-for-profit newsrooms, with resulting new pressures being placed on journalists and editors to quantify their impact on society. These recent attempts have so far failed to achieve clarity or a satisfactory conclusion, which is not surprising given the complex web of causation within which journalism operates. In this paper, the authors propose a stratified definition of journalistic impact and function. They propose a methodology for studying impact drawing on realistic evaluation—a theory-based approach developed primarily to assess large social programmes occurring in open systems. The authors argue this could allow a conceptual and methodological advance on the question of media impacts, leading to research capable of usefully informing responses at a time of worrying change.

This book shows how the concept of responsible mining is based on five key principles or pillars: holistic assessment; ethical relationships; community-based agreements; appropriate boundaries and good governance.