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Rationale, Aims, and Objectives: This article aims to examine global population ageing and to evaluate the likely risks and dilemmas of demographic ageing within the context of the health and well-being of individuals., Methods: This paper is based on the author's research in the field of social gerontology, demography, and public health. In addition, a literature review has been carried out focused on the objectives of the research., Results: The study has identified potential risks and dilemmas that the older people may face in the globalized world. There are four main aspects that contribute to an unequal distribution of risks in later life: (a) burden of disease in epidemiological transition, (b) financial security in retirement, (c) familial resources for older peoples' care, and (d) availability of workforce for older peoples' care. Whilst population ageing is a global trend, its impact is not equal across the world, and this is highlighted in this research. There are some important dilemmas which are identified in this paper that may also fuel the potential risks and challenges facing ageing societies., Conclusions: It is apparent that older people will face numerous risks in later life and those in developing countries are likely to face more challenges than those in developed countries. The findings may be useful to policymakers for formulating future plans and policy implementation. Further research is required to identify the number of health care workers needed to tackle the challenges of an ageing societies across the globe., (© 2018 John Wiley & Sons, Ltd.)

Context: The study of discourses (i.e. verbal interactions or written accounts) is increasingly used in social sciences to gain insight into issues connected to discourse, such as meanings, behaviours and actions. This paper situates discourse analysis in medical education, based on a framework developed in organisational discourse analysis and widely deployed in other social science disciplines., Objectives: This paper aims to examine the constructs of 'discourse' and 'discourse analysis', and how various understandings of discourse and discourse analysis may play out in empirical and analytical settings, with a particular focus on the field of medical education., Methods: The study is based on a literature analysis of discourse analysis approaches published in Medical Education., Results: Findings suggest that empirical studies through discourse analysis can be heuristically understood in terms of the links between text, practices and meaning., Conclusions: Discourse analysis provides a more strongly supported argument when it is possible to defend claims on three levels: practice, using observational data; meaning, using ethnographic data, and text, using conversational and textual data., (© 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.)

Like any discipline, bioethics is a developing field of academic inquiry; and recent trends in scholarship have been towards more engagement with empirical research. This 'empirical turn' has provoked extensive debate over how such 'descriptive' research carried out in the social sciences contributes to the distinctively normative aspect of bioethics. This paper will address this issue by developing a practical research methodology for the inclusion of data from social science studies into ethical deliberation. This methodology will be based on a naturalistic conception of ethical theory that sees practice as informing theory just as theory informs practice - the two are symbiotically related. From this engagement with practice, the ways that such theories need to be extended and developed can be determined. This is a practical methodology for integrating theory and practice that can be used in empirical studies, one that uses ethical theory both to explore the data and to draw normative conclusions., (© 2010 Blackwell Publishing Ltd.)

'Behavioural medicine' is poised to contribute to the quality of health to the benefit of patients and physicians. There is a need for medical students and residents to better understand the field of behavioural medicine, and for practising physicians to incorporate it in medical education and clinical practice. This paper seeks to correct an erroneous conceptualization of behavioural medicine as being limited to psychosocial and mental health adjustments, and to provide examples of selected applications for medical conditions, including those that are not primarily regarded as requiring changes in lifestyle or psychotherapy. In fact, there are dramatic treatment and intervention protocols available that employ behavioural procedures that can provide relief for patients in all medical and dental specialties and that deserve to be considered along with conventional treatment protocols., (© 2010 Blackwell Publishing Ltd.)

Aims: The purpose of this paper is to introduce the social science alcohol and drug research undertaken by the Centre for Alcohol and Drug Research (CRF) and at the same time offer an insight into the development in Danish alcohol and drug research throughout the past 15-20 years., Method: A review of articles, books and reports published by researcher from CRF from the mid-1990s until today and an analysis of the policy-making in the Danish substance use and misuse area., Results: CRF is a result of the discussions surrounding social, health and allocation policy questions since the mid-1980s. Among other things, these discussions led to the formal establishment of the Centre in 1991 under the Aarhus University, the Faculty of Social Science. Since 2001 the Centre has received a permanent basic allocation, which has made it possible to appoint tenured senior researchers; to work under a more long-term research strategy; to function as a milieu for educating PhD students; and to diversify from commissioned research tasks to initiating projects involving more fundamental research. Research at the Centre is today pivoted around four core areas: consumption, policy, prevention and treatment., Conclusion: The emergence, continuation, financing and character of the research taking place at CRF can be linked closely to the specific Danish drug and alcohol discourse and to the division of the responsibility for alcohol and drug research into separate Ministries., (© 2010 The Authors, Addiction © 2010 Society for the Study of Addiction.)

This paper develops a ridge procedure for structural equation modelling (SEM) with ordinal and continuous data by modelling the polychoric/polyserial/product-moment correlation matrix R. Rather than directly fitting R, the procedure fits a structural model to R(a) =R+aI by minimizing the normal distribution-based discrepancy function, where a > 0. Statistical properties of the parameter estimates are obtained. Four statistics for overall model evaluation are proposed. Empirical results indicate that the ridge procedure for SEM with ordinal data has better convergence rate, smaller bias, smaller mean square error, and better overall model evaluation than the widely used maximum likelihood procedure.

Structural equation models (SEMs) have become widely used to determine the interrelationships between latent and observed variables in social, psychological, and behavioural sciences. As heterogeneous data are very common in practical research in these fields, the analysis of mixture models has received a lot of attention in the literature. An important issue in the analysis of mixture SEMs is the presence of missing data, in particular of data missing with a non-ignorable mechanism. However, only a limited amount of work has been done in analysing mixture SEMs with non-ignorable missing data. The main objective of this paper is to develop a Bayesian approach for analysing mixture SEMs with an unknown number of components and non-ignorable missing data. A simulation study shows that Bayesian estimates obtained by the proposed Markov chain Monte Carlo methods are accurate and the Bayes factor computed via a path sampling procedure is useful for identifying the correct number of components, selecting an appropriate missingness mechanism, and investigating various effects of latent variables in the mixture SEMs. A real data set on a study of job satisfaction is used to demonstrate the methodology.

With the advance of web search and navigation technology, enormous amount of information, non-information, and misinformation may be obtained in milliseconds in response to questions about 'what works' in social sciences. Today, policy makers in non-medical public service arenas are under increasing pressure to make sound decisions based on scientific evidence. Some of these decisions are a matter of legal requirement. This paper shows how such movements are closely aligned with the evolution of organizations that develop and apply evidence standards and evidence grading schemes within the social science communities. The current state of evidence-based practice in social sciences is examined by reviewing the latest development of randomized trials and evidence grading schemes in the fields of education, criminal justice, and social welfare. Studies conducted under the auspices of the Campbell Collaboration and What Works Clearinghouse are used to illustrate ingredients of evidence grading schemes, graphic display of results of systematic reviews, and discrepancies of evidence derived from randomized trials and non-experimental trials. Furthermore, it is argued that the use of evidence on 'what works' depends on the potential users' awareness, understanding of the evidence, as well as their capacity and willingness to use it. Awareness and understanding depends on the world wide web and its augmentations, while capacity and willingness depends more on incentives to use good evidence and on political and ethical values. Implications for the future development of evidence grading organizations are discussed., (© 2008 Blackwell Publishing Asia Pty Ltd and Chinese Cochrane Center, West China Hospital of Sichuan University.)

Many variables that are used in social and behavioural science research are ordinal categorical or polytomous variables. When more than one polytomous variable is involved in an analysis, observations are classified in a contingency table, and a commonly used statistic for describing the association between two variables is the polychoric correlation. This paper investigates the estimation of the polychoric correlation when the data set consists of misclassified observations. Two approaches for estimating the polychoric correlation have been developed. One assumes that the probabilities in relation to misclassification are known, and the other uses a double sampling scheme to obtain information on misclassification. A parameter estimation procedure is developed, and statistical properties for the estimates are discussed. The practicability and applicability of the proposed approaches are illustrated by analysing data sets that are based on real and generated data. Excel programmes with visual basic for application (VBA) have been developed to compute the estimate of the polychoric correlation and its standard error. The use of the structural equation modelling programme Mx to find parameter estimates in the double sampling scheme is discussed.

In the social and behavioural sciences, structural equation modelling has been widely used to test a substantive theory or causal relationship among latent constructs. Cross-validation (CV) is a valuable tool for selecting the best model among competing structural models. Influential cases or outliers are often present in practical data. Therefore, even the correct model for the majority of the data may not cross-validate well. This paper discusses various drawbacks of CV based on sample covariance matrices, and develops a procedure for using robust covariance matrices in the model calibration and validation stages. Examples illustrate that the CV index based on sample covariance matrices is very sensitive to influential cases, and even a single outlier can cause the CV index to support a wrong model. The CV index based on robust covariance matrices is much less sensitive to influential cases and thus leads to a more valid conclusion about the practical value of a model structure.