Développement de plaintes somatiques chez les adolescents et jeunes adultes en Suisse

In this study we explored the development of somatic complaints among adolescents and young adults aged 16 to 30 years in Switzerland. Using data from the Transitions from Education to Employment (TREE) study, we applied a hidden Markovian model with covariates to cluster trajectories representing the sum of eight somatic complaints. The resulting groups differed mainly in terms of gender, reading literacy, and substance use. The trajectories of somatic complaints were also related to the number of critical events experienced by the respondents.Der Beitrag untersucht, wie sich in der Schweiz somatische Beschwerden bei Jugendlichen bzw. jungen Erwachsenen im Alter zwischen 16 und 30 Jahren entwickeln. Mit den Daten der TREE-Studie wurde ein verstecktes Markov-Modell mit Kovariaten gerechnet, um Verläufe von acht somatischen Beschwerden zu clustern. Die so gebildeten Gruppen unterscheiden sich signifikant bezüglich Geschlecht, kognitiven Fertigkeiten und Substanzkonsum. In den untersuchten Verläufen zeigen sich auch Zusammenhänge mit kritischen Lebensereignissen der Befragten.Nous avons exploré le développement de plaintes somatiques chez les adolescents et jeunes adultes âgés de 16 à 30 ans vivant en Suisse. Sur la base de données de l’enquête TREE (Transitions from Education to Employment), nous avons appliqué un modèle markovien caché avec covariables afin de classifier des trajectoires représentant la somme de huit plaintes somatiques. Les groupes obtenus diffèrent en termes de genre, de niveau de lecture et de consommation de substances. Les trajectoires de plaintes somatiques sont aussi liées au nombre d’événements de vie critiques dont les personnes interrogées ont fait l’expérience

Sequence analysis: its past, present, and future

This article marks the occasion of Social Science Research’s 50th anniversary by reflecting on the progress of sequence analysis (SA) since its introduction into the social sciences four decades ago, with focuses on the developments of SA thus far in the social sciences and on its potential future directions. The application of SA in the social sciences, especially in life course research, has mushroomed in the last decade and a half. Using a life course analogy, we examined the birth of SA in the social sciences and its childhood (the first wave), its adolescence and young adulthood (the second wave), and its future mature adulthood in the paper. The paper provides a summary of (1) the important SA research and the historical contexts in which SA was developed by Andrew Abbott, (2) a thorough review of the many methodological developments in visualization, complexity measures, dissimilarity measures, group analysis of dissimilarities, cluster analysis of dissimilarities, multidomain/multichannel SA, dyadic/polyadic SA, Markov chain SA, sequence life course analysis, sequence network analysis, SA in other social science research, and software for SA, and (3) reflections on some future directions of SA including how SA can benefit and inform theory-making in the social sciences, the methods currently being developed, and some remaining challenges facing SA for which we do not yet have any solutions. It is our hope that the reader will take up the challenges and help us improve and grow SA into maturity

Sequence analysis: Its past, present, and future

This article marks the occasion of Social Science Research's 50th anniversary by reflecting on the progress of sequence analysis (SA) since its introduction into the social sciences four decades ago, with focuses on the developments of SA thus far in the social sciences and on its potential future directions. The application of SA in the social sciences, especially in life course research, has mushroomed in the last decade and a half. Using a life course analogy, we examined the birth of SA in the social sciences and its childhood (the first wave), its adolescence and young adulthood (the second wave), and its future mature adulthood in the paper. The paper provides a summary of (1) the important SA research and the historical contexts in which SA was developed by Andrew Abbott, (2) a thorough review of the many methodological developments in visualization, complexity measures, dissimilarity measures, group analysis of dissimilarities, cluster analysis of dissimilarities, multidomain/multichannel SA, dyadic/polyadic SA, Markov chain SA, sequence life course analysis, sequence network analysis, SA in other social science research, and software for SA, and (3) reflections on some future directions of SA including how SA can benefit and inform theory-making in the social sciences, the methods currently being developed, and some remaining challenges facing SA for which we do not yet have any solutions. It is our hope that the reader will take up the challenges and help us improve and grow SA into maturity.</p