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The onset of a chronic physical health condition (CHC) can highly impact individuals' well-being and mental health. Social support has been shown to help people rebound after the onset of a CHC. Nonetheless, little is known about the longitudinal pattern of social support and its reciprocal association with mental health in CHC. This study aimed to illustrate the longitudinal pattern of perceived social support and to examine the reciprocal association between perceived social support and psychological distress across 6 years. Two random intercept cross-lagged panel models were conducted, one for emotional and one for practical support, using yearly assessments of 582 Swiss Household Panel's participants reporting a CHC. A reciprocal association was found, with psychological distress 1 year after the onset being linked to less emotional support in the following year and vice versa, more emotional support being linked to less psychological distress the following year. A unidirectional association was found for practical support, with more psychological distress 1 year before the CHC onset being linked to more practical support at the onset year. This study underlines the importance of involving the social environment of individuals living with a CHC, especially around the first year after the onset. &nbsp

Our study investigates the impact of social media on survey outcomes, particularly focusing on how the general public’s perception of issue importance is influenced by Twitter. To accomplish this, we propose two case studies in Swiss politics focusing on social media’s effect on opinion change during elections and the similarities in arguments on social media and in survey data during direct democracy votes. This study relies on a two-year longitudinal data collection of tweets (from January 2019 to December 2020) sent by more than 50.000 identified Swiss seed users and their most active followers. We find that the content of tweets surrounding popular votes reflects similar arguments as those expressed by a representative survey sample. Cases without congruence can be explained by the groups of users dominating social media discussions about the votes but also by the complexity and variety of arguments surrounding the votes. Furthermore, our findings demonstrate that the salience of policy issues on social media has no systematic effect on public opinion change regarding the perceived importance of similar issues, as social media’s impact strongly depends on the content and on the tweet’s author. These results provide valuable insights for researchers, helping them understand the circumstances in which social media data are most likely to be available and present a useful complement to surveys for understanding the dynamics of public opinion.

Although daily hassles have been of interest since the 1980s, only a few tools have been developed to assess them. Most of them are checklists or open-ended questions that are demanding for participants in panel surveys. Therefore, to facilitate daily hassles integration into large surveys, the aim of this study was to present a new tool assessing daily hassles, the LIVES–Daily Hassles Scale (LIVES-DHS), and to examine its relation to life satisfaction, in a sample of 1,170 French- and German-speaking adults living in Switzerland. In a first random subsample, we conducted a principal axis factor analysis, and the results suggested a five-factor solution. Furthermore, we conducted a confirmatory factor analysis on a second random subsample, and it supported the hierarchical factor structure of the scale. The LIVES-DHS consists of 18 items represented by five factors that describe five sources of daily hassles: financial, physical, relational, environmental, and professional. The bivariate correlations showed that the LIVES-DHS could differentiate the concept of daily hassles from associated concepts. Finally, the hierarchical regression showed that daily hassles negatively predicted life satisfaction and added a significant incremental variance beyond that accounted for by age, gender, household income, education level, and personality traits.