No abstract

Retirement is a major life-course transition for which some people plan more than others. Given that planning positively affects retirement adjustment, it is important to investigate the heterogeneity in retirement planning and its antecedents. While financial preparation has been thoroughly investigated, little is known about the activities older workers plan to do in retirement. We hypothesize that older workers' plans for retirement activities can be categorized into 3 domains: bridge employment, selfdevelopmental leisure, and social leisure. Moreover, we expect these plans to be affected by workers' opportunities for continuity, spousal support, and perception of time. We test these hypotheses using data from the first wave of the Netherlands Interdisciplinary Demographic Institute Pension Panel Study (NPPS). The study consists of a sample of almost 6,800 Dutch older workers who were asked about their plans to engage in 10 different activities in retirement. Where relevant, spouses of older workers were also surveyed, providing multiactor data for these couples (N ϭ 4,052). Our results support the classification of retirement activity plans into 3 domains. Moreover, the results of structural equation models confirm that the activities for which older workers plan are related to their opportunity structure (i.e., occupational status, number of preretirement leisure activities, number of social roles), spousal support to engage in these activities, and older workers' perception of time (i.e., future time perspective, perceived life expectancy). Our findings can help identify older workers who might face a more difficult retirement transition, because they have fewer plans to address the various psychosocial aspects of retirement.

A growing number of studies have tried to assess the effects of social media on adolescents, who are among the most avid social media users. To establish the effects of social media use, we need accurate and valid instruments to measure adolescents’ time spent with these media. The aim of this preregistered study was to examine the accuracy and validity of retrospective surveys and experience sampling methods (ESM), by comparing adolescents’ responses to these self-report measures with their digital trace data. The sample consisted of 131 adolescents (48% girls; Mage = 14.1) with Android smartphones. In both retrospective surveys and ESM, adolescents overestimated their time spent on social media, but they more accurately estimated their time spent on platforms that are used in a less fragmented way (Instagram) than on platforms that are used in a more fragmented way (Snapchat). The between-person validity of adolescents’ time spent estimates according to retrospective surveys and ESM was sufficient (r ranged from .51 to .55). The accuracy of retrospective surveys increased over time (i.e., learning effect), while both the accuracy and validity of ESM decreased over time (i.e. fatigue effect).

Research agrees that self-reported measures of time spent with social media (TSM) show poor convergent validity, because they correlate modestly with equivalent objective digital trace measures. This experience sampling study among 159 adolescents (12,617 self-reports) extends this work by examining the comparative predictive validity of self-reported and digital trace measures of TSM, that is, the extent to which self-reported and digital trace measures of TSM correspond in their effects on self-esteem, well-being, and friendship closeness. Using an N = 1 method of analysis, we investigated the correspondence on a between-person, within-person, and person-specific level. Although our results confirmed the poor convergent validity of self-reported TSM reported earlier, we found that self-reports of TSM had comparable predictive validity to digital trace measures on all three levels. Because comparative predictive validity of self-reported TSM is crucial for investigating social media effects, our results have important implications for future research using self-reported TSM.

Longitudinal studies allow researchers to investigate the reciprocal associations between media use and well-being. But surprisingly little work has conceptualized the role of time in these associations. The aim of our study was to fill this important void in the literature. In a three-week experience sampling study among 300 adolescents into social media use (SMU) and well-being, we compared social media effects (SMU → well-being) and social media selection effects (well-being → SMU) at hourly, daily, and weekly time intervals. Both social media effects and social media selection effects were consistent across the three different time intervals. Moreover, social media effects and social media selection effects were symmetrical processes, in that they occurred at the same time intervals. We suggest several avenues for future research to enhance our understanding of how (social) media effects and media selection effects evolve at short-term, mid-term, and long-term time intervals.

Existing research agrees that subjective, self-reported measures of time spent with social media (TSM) show poor convergent validity, because they correlate only modestly with equivalent objective digital trace measures. This experience sampling study among 159 adolescents (12,617 self-reports) extends this work by examining the predictive validity of self-reported TSM, that is, the extent to which self-reported and digital trace measures of TSM correspond in their effects on self-esteem, well-being, and friendship closeness. Using an advanced N=1 method of analysis, we investigated the predictive validity on a between-person, within-person, and person-specific level. Although our results confirmed the poor convergent validity of self-reported TSM reported in earlier work, we found high predictive validity of self-reported TSM for all three outcomes and all three levels. Because a high predictive validity of self-reported TSM is crucial for investigating the effects of social media, our results have important implications for future research using self-reported TSM.

No abstract

We investigated the expressions of happiness and sadness in adolescents’ direct messages (DMs) on Instagram. Using neural topic modelling (BERTopic), we analyzed 211,778 DMs belonging to 96 adolescents, who donated data from 110 Instagram accounts. Results showed that (1) expressions of happiness were more than four times more prevalent than expressions of sadness; (2) the number of DMs containing expressions of happiness and sadness were highly correlated; (3) there are temporal trends in the expression of happiness and sadness in adolescents’ DMs and there are individual differences in these trends, and (4) there is no significant between- or within-person relationship between the number of messages containing expressions of happiness and sadness and adolescents’ well-being.