A mixed-methods framework for analyzing text data: Integrating computational techniques with qualitative methods in demography

Demography as a Field: Where We Came From and Where We Are Headed

This essay provides a series of reflections on the current state of demography as seen by four early-career researchers who are actively engaged in aspects of the discipline as varied as research, teaching, mentorship, data collection efforts, policy making, and policy advising. Despite some claims that the discipline is weakening, we showcase the great potential of the field and outline promising pathways and novel directions for the future. In so doing, we critically assess recent innovations in data quality and availability, stressing the need to "revolutionize" the way that demographic methods are taught by adopting a viewpoint that more closely reflects the rapidly changing, or "fast," nature of global social phenomena such as conflict-related displacements, environmental disasters, migration streams, pandemics, and evolving population policies. We conclude by discussing the relevance of careful demographic analyses for policy making, stressing three main points: (i) the need to make demography more visible and understandable to the public eye; (ii) the importance of engaging and co-creating with local communities to "break" the academic bubble; and (iii) the urge to counteract the spread of misinformation-a phenomenon that has become even more visible in the aftermath of the COVID-19 outbreak.

Does Machine Learning Offer Added Value Vis-à-Vis Traditional Statistics? An Exploratory Study on Retirement Decisions Using Data from the Survey of Health, Ageing, and Retirement in Europe (SHARE)

Do machine learning algorithms perform better than statistical survival analysis when predicting retirement decisions? This exploratory article addresses the question by constructing a pseudo-panel with retirement data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The analysis consists of two methodological steps prompted by the nature of the data. First, a discrete Cox survival model of transitions to retirement with time-dependent covariates is compared to a Cox model without time-dependent covariates and a survival random forest. Second, the best performing model (Cox with time-dependent covariates) is compared to random forests adapted to time-dependent covariates by means of simulations. The results from the analysis do not clearly favor a single method; whereas machine learning algorithms have a stronger predictive power, the variables they use in their predictions do not necessarily display causal relationships with the outcome variable. Therefore, the two methods should be seen as complements rather than substitutes. In addition, simulations shed a new light on the role of some variables—such as education and health—in retirement decisions. This amounts to both substantive and methodological contributions to the literature on the modeling of retirement.

The asymmetries of the biopsychosocial model of depression in lay discourses - Topic modelling online depression forums

BACKGROUND

One of the most comprehensive approaches to depression is the biopsychosocial model. From this wider perspective, social sciences have criticized the reductionist biomedical discourse, which has been dominating expert discourses for a long time. As these discourses determine the horizon of attributions and interventions, their lay interpretation plays a central role in the coping with depression.

METHODS

In order to map these patterns, online depression forums are analyzed with natural language processing methods, where computational tools are complemented with a qualitative approach. Latent Dirichlet Allocation topic model of depression-related posts from the most popular English-speaking online health discussion forums (N = ~70 000) reveals the monolog (attributions and self-disclosures) and interactive (consultations and quasi-therapeutic interactions) patterns.

RESULTS

Following the evaluation of various models 18 topics were differentiated: attributions referring to health, family, partnership and work issues; self-disclosures referring to contemplations, introducing the experience of suffering and well-being, along with diaries of everyday activities and hardships; consultations about psychotherapies, classifications, drugs and the experience; and quasi-therapeutic interactions relying on unconditional positive regards, recovery helpers experience or spirituality. These topics were evaluated from the perspective of the biopsychosocial model: the weight of each dimension was measured along with the discursive function.

CONCLUSIONS

Biomedical discourse is underrepresented in lay discussions, while psychological discourse plays an overall dominant role. Even if actors are initially aware of the social mechanisms contributing to depression, they neglect these factors when it comes to considering the countermeasures.

Protocol for a systematic review of living labs in healthcare

INTRODUCTION

Healthcare is increasingly challenged to meet the demands of user involvement and knowledge mobilisation required by the 21st-century patient-centred and knowledge-based economies. Innovations are needed to reduce problematic barriers to knowledge exchange and improve collaborative problem solving. Living labs, as open knowledge systems, have the potential to address these gaps but are underexplored in healthcare.

METHODS AND ANALYSIS

We will conduct the first systematic review of living labs across healthcare contexts. We will comprehensively search the following online databases from inception to 31 December 2020: Scopus, the Cochrane Library (Wiley), Medline (OVID), Embase (OVID), Web of Science, PsycINFO (OVID) and EBSCOhost databases including Academic Search Complete, Business Source Premier, Canadian Reference Centre, CINAHL, MasterFILE Premier, SPORTDiscus, Library & Information Science Source, Library, Information Science & Technology Abstracts, AgeLine, EconLit, Art Full Text, Women's Studies International and Social Work Abstracts. We will search for grey literature using Google advanced techniques and books/book chapters through scholarly and bibliographical databases. We will use a dual-reviewer, two-step selection process with pre-established inclusion criteria and limit to English language publications. Empirical studies of any design examining living lab development, implementation or evaluation in health or healthcare will be included. We will use the Mixed Methods Appraisal Tool (MMAT) for methodological quality appraisal and Covidence software for review management, and we will extract data on pre-established variables such as lab context and technological platforms. We will create evidence tables and analyse across variables such as focal aim and achievement of living lab principles, such as the use of cocreation and multimethod approaches. We will tabulate data for descriptive reporting and narrative synthesis to identify current applications, approaches and promising areas for living lab development across health contexts.

ETHICS AND DISSEMINATION

Ethical approval was not required for this review. This review will inform research into living labs in health environments, including guidance for a living lab in paediatric rehabilitation. Academic publications shared through collaborative networks and social media channels will provide substantive knowledge to the growing tech-health development sector and to researchers, practitioners and organisations seeking enhanced patient/stakeholder engagement and innovations in knowledge translation and evidence-based practice.

PROSPERO REGISTRATION NUMBER

CRD42020175275.

Computational Social Science and Sociology

The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: (a) social network analysis and group formation; (b) collective behavior and political sociology; (c) the sociology of knowledge; (d) cultural sociology, social psychology, and emotions; (e) the production of culture; (f) economic sociology and organizations; and (g) demography and population studies. Our review reveals that sociologists are not only at the center of cutting-edge research that addresses longstanding questions about human behavior but also developing new lines of inquiry about digital spaces as well. We conclude by discussing challenging new obstacles in the field, calling for increased attention to sociological theory, and identifying new areas where computational social science might be further integrated into mainstream sociology.

A Systematic Review of Coastal Vulnerability Mapping

Coastal areas worldwide represent an aggregation of population and assets of growing economic, geopolitical, and sociocultural significance, yet their functions are increasingly challenged by worsening coastal hazards. Vulnerability assessments have been recognized as one way we can better understand which geographic areas and segments of society are more susceptible to adverse impacts from different stressors or hazards. The aims of this paper are to evaluate the state of coastal vulnerability assessment mapping efforts and to identify opportunities for advancement and refinement that will lead to more cohesive, impactful, and policy-relevant coastal vulnerability studies. We conducted a systematic review of the literature that addresses physical and social vulnerability to coastal hazards and contains corresponding mapping products. The content was analyzed for the scale of analysis, location, disciplinary focus, conceptual framework, metrics used, methodological approach, data sources, mapping output, and policy relevance. Results showed that most Coastal Vulnerability Mapping Assessments (CVMAs) are conducted at the local level using a range of methodologies, often with limited inclusion of social considerations and limited discussion of policy relevance. Based on our analysis, we provide seven recommendations for the advancement of this field that would improve CVMAs’ methodological rigor, policy relevance, and alignment with other vulnerability assessment paradigms.