Despite the growing interest in studying factors affecting subjective well-being of older adults, little research has been conducted on vast territory of Siberia (Russia) with large population. To address this lack of evidence, we explored the relationship between subjective well-being and social aspects (social and emotional support, social network, and social activities), living conditions (standards of living and residence area), self-reported health, and demographic characteristics in older adults living in Tomsk Region, Siberia. Subjective well-being was measured by life satisfaction and happiness (each measured with one 11-point question). Sample included 489 community-dwelling respondents, aged 65 or older. We found that mean life satisfaction and happiness reported by our respondents were lower than those of European countries. Higher quality of social interaction, better standards of living, and being satisfied with own health were associated with higher life satisfaction and happiness. This study provides original data on a region barely investigated and suggests that Siberian older adults receive strong benefits from social support and from social network and that similar factors are related to subjective well-being both in Siberian and Eastern European older adults. Future studies should further explore the relationship between different kinds of social support (e.g., psychological vs. material support) and subjective well-being in different Siberian ethnic groups or regions.

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ObjectiveIn this paper we study if and under what conditions crowdsourcing can be used as a reliable method for collecting high-quality emotion labels on pictures. To this end, we run a set of crowdsourcing experiments on the widely used IAPS dataset, using the Self-Assessment Manikin (SAM) emotion collection instrument, in order to rate pictures on valence, arousal and dominance, and explore the consistency of crowdsourced results across multiple runs (reliability) and the level of agreement with the gold labels (quality). In doing so, we explored the impact of targeting populations of different level of reputation (and cost) and collecting varying numbers of ratings per picture.ResultsThe results tell us that crowdsourcing can be a reliable method, reaching excellent levels of reliability and agreement with only 3 ratings per picture for valence and 8 per arousal, with only marginal difference between target populations. Results for dominance were very poor, echoing previous studies on the data collection instrument used. We also observed that specific types of content generate diverging opinions in participants (leading to higher variability or multimodal distributions), which remain consistent across pictures of the same theme. These can inform the data collection and exploitation of crowdsourced emotion datasets.

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