Suchergebnisse

From a theoretical point of view, older adults may not necessarily face a greater of risk becoming lonely than middle-aged adults but are more likely at disadvantage at fighting loneliness. Therefore, in this study we differentiate between the risk of becoming lonely and the risk of remaining lonely. A large longitudinal data set representative for the German non-institutionalized population from 40 to 90 years of age (N = 15,408; 49% female) was used in the analysis. Lagged logistic regression models were estimated to investigate the effect of earlier experiences of severe loneliness on the risk of being lonely after three years across middle age and late adulthood. Individual differences in health, views on aging, and social activities were taken into account to explore their role in age differences in the risk of remaining lonely. The analysis revealed marginal age differences in the risk of becoming lonely but a marked age gradient regarding the risk of remaining lonely. Lonely older adults who were older than 75 years of age were more likely to remain lonely after three years than lonely middle-aged adults. Controlling for individual differences in health, views on aging as social loss and social activities accounted for this age difference.Interventions against loneliness may prioritize older age groups because losses in capacities, shifts in motivations and a degraded opportunity structure render it increasingly less likely that older adults leave a state of loneliness on their own accord.

The aim of this study is to compare the levels of volunteering by German baby boomers, who are currently in their fifties and sixties, to cohorts born earlier. Using data from the German Aging Survey (DEAS), logistic and negative binomial regressions were employed to analyze the prevalence and time contributions that baby boomers invest in volunteering. The study indicates a higher prevalence of volunteering by baby boomers compared with earlier-born cohorts and suggests that the large size of this cohort will imply high levels of volunteering that could increase even further as the cohort approaches retirement. Moreover, our findings suggest stability in voluntary time contributions by baby boomers compared with earlier-born cohorts; this contrasts with the existing research showing decreased overall time contributions to volunteering. The study underscores the importance of considering cohort-specific differences in voluntary engagement behavior to gain a deeper understanding of the dynamics of volunteering.

Digitalization alters working processes, contents, and skill demands for workers. Common age stereotypes attribute lower digital competences and abilities to adapt to technological changes to older workers. Thus far, it is unclear how workers' self-perceptions of aging (SPA) are affected by the emergence of digital skill demands at work. Therefore, this study investigates if and how digital skill demands in occupations are associated with the level of and changes in older workers' SPA. To shed light on this question, data from the German Ageing Survey (2014 and 2017) is used. In latent change score models, the level and change of workers' SPA in the domains of physical and social losses, ongoing development, and self-knowledge are investigated. Level and change of digitalization in workers' occupations are used as predictors of change and are based on digital skill demands in occupations that are determined via job ads data. Interindividual differences in the baseline levels and interindividual differences in changes in all domains of SPA are found. When controlling for digitalization in occupations, sociodemographic and job-related characteristics, higher digitalization levels (DLs) in occupations are associated with improvements in SPA in the domains of ongoing development and self-knowledge. No significant associations with older workers' SPA are found for changes in the DL. Our results suggest that compassionate ageism that intends to protect older workers from digital demands is inappropriate, since indications of empowering effects in some domains of SPA have been found.

Abstract
The context of retirement has changed over the last decades, but there is little knowledge on whether the quality of retirement adjustment has changed as well. Changes in retirement regulations and historical differences in resources may affect the quality of adjustment and increase inequalities between different socioeconomic groups. In the present study, we investigated historical differences in retirement adjustment by comparing cross-sectional samples of retirees from 1996, 2002, 2008, and 2014, based on the population-based German Ageing Survey. Adjustment was measured with three different indicators (perceived change in life after retirement, retirement satisfaction, adjustment difficulties). Retirement satisfaction was higher in later samples, but for the other two outcomes, there was no evidence for systematic increases or decreases in levels of retirement adjustment with historical time over the studied period. White-collar workers reported better adjustment than blue-collar workers did, and for two of three outcomes, this effect was stable over time. The white-collar workers' advantage concerning retirement satisfaction, however, increased. We conclude that in Germany, at least for those who retire within the usual time window, adjustment quality has not changed systematically over the examined 18-year period. We only found mixed evidence for a growing social inequality in the retirement adjustment. However, as individual agency in choosing one's retirement timing and pathway is increasingly restricted, social inequalities in well-being before retirement may increase.

Die Variablendokumentation dient der Übersicht aller Variablen in Deutsch und in Englisch, die bisher in den vier Befragungswellen des Deutschen Alterssuryveys (DEAS) von 1996 bis 2011 erhoben wurden. Anhand einer Zuordnung der einzelnen Variablen in verschiedene Themenblöcke wird so eine übersichtliche Dokumentation der bisher verwendeten Variablen erreicht. Die Variablendokumentation soll dem DEAS-Datennutzer als Übersicht über alle abgefragten Variablen und Skalen der verschiedenen Wellen dienen. Damit soll der Zugang und der Vergleich von Variablen im Längsschnitt und mit anderen Datensätzen vereinfacht werden.Als Grundlage für die Erstellung dienten die einzelnen Fragebogen, wobei die dritte Welle im Jahr 2008 als Referenz genutzt wurde. Folgende Informationen werden in der Variablendokumentation abgebildet: Alle Items der Variablen werden in Deutsch und in Englisch aufgelistet, die jeweilige Codierung dieser sowie die dazugehörigen Variablennamen und die Information, wo sich diese Variable befindet (CAPI/Drop-off und Welle) werden in einer Tabelle ersichtlich. Items einer Skala, die umkodiert wurden, um der Richtung der Skala zu entsprechen, wurden mit einem (*) gekennzeichnet. Zudem sind Referenzen für die eingesetzten Skalen aufgelistet.Im zweiten Kapitel der Variablendokumentation befindet sich eine Übersicht über alle eingesetzten Skalen des DEAS. Neben Kurzinformationen zu der jeweiligen Skala wird weiterhin die Welle aufgeführt, in der sie Verwendung findet.Weiterhin befindet sich in Kapitel drei der Variablendokumentation eine Übersicht über die generierten Konstrukte. Die Konstrukte sind Variablen, die nicht direkt dem DEAS-Fragebogen entnommen sind, aber mit Hilfe abgefragter Variablen gebildet werden, um dem Nutzer bei bestimmten thematischen Fragestellungen die Datenarbeit zu erleichtern. Zudem gibt es Konstrukte, die dem DEAS aus anderen Datenquellen hinzu gespielt werden, um für bestimmte Fragestellungen eine tiefergehende Analyse zu ermöglichen. Die tabellarische Darstellung der Konstrukte basiert auf der Welle 2011 und enthält eine Beschreibung des Konstrukts sowie die dazugehörige Codierung. In der Kurzbeschreibung zu jeder Welle werden die Konstrukte und die benutzten Variablen genauer beschrieben. Diese können – ebenso wie die Codebücher – über die Webseite des Forschungsdatenzentrums des Deutschen Zentrums für Altersfragen heruntergeladen werden: https://www.dza.de/fdz.html ; This documentation of variables serves as an overview of all variables, which have been collected in the German Ageing Survey (DEAS) from 1996 to 2011, given in German and English. All variables are documented by assigning them to different thematic fields. This documentation provides a thorough overview over all collected variables and scales of the different waves.The single questionnaires served as basis for the compilation of this documentation, the third wave of the year 2008, however, has been used as reference. The following information can be found in this documentation: All items of the variables are listed in German and English. Their coding, the name of the variable and the information from which wave or in which instrument (CAPI or drop-off) the variable has been collected, is listed in a table. Items of scales which have been recoded to match the direction of the scale are marked with (*). Additionally, references for appliedscales are given at the bottom of the respective table.An overview over all scales used in the DEAS questionnaires can be found in the second chapter. Next to short information, the wave in which it has been used is given.Chapter three contains a summary of all derived variables that were generated to make analyses for specific thematic problems or questions easier. Some of these variables were generated from questions that had been used in the DEAS questionnaire. Other derived variables were added to the data from other sources in order to facilitate in-depth analyses in specific thematic fields. The short description of every wave of the DEAS describes all derived variables more closely. These – as well as the codebooks – can be downloaded from the website of the Research Data Centre of the German Centre of Gerontology at: https://www.dza.de/en/fdz.html