Art Therapy Using Possible Selves and Digital Media for Individuals with Alcohol Addiction in Korea

The primary purposes of this mixed methods study were to (a) examine whether using an art therapy intervention based on the theory of possible selves enhanced the motivation for change among individuals with alcohol addiction in Korea, and (b) to explore the study participants’ lived experiences of the self as it emerged from the specific art therapy intervention. This study consisted of three distinct theoretical frameworks: the transtheoretical model (TTM); the theory of possible selves; and art therapy—which bridged the two aforementioned theories. A total of seven participants completed five individual sessions each, creating a series of possible future selves through the use of digital media. This convergent parallel mixed methods study included pre and post evaluations using the Korean version of the Stages of Change Readiness and Treatment Eagerness Scale, which measures motivation in three independent subscales (Recognition, Ambivalence, and Taking Steps). Phenomenological research was proceeded simultaneously, which data were collected holistically and creatively throughout the sessions. As a result, qualitative relationships among self-perception, motivation, and creative imagination were revealed in the participants’ movement through the stages of change. These findings also suggested that clients’ artwork of their possible future selves can be powerful predictors to reflect readiness for change, and art therapists are in a unique position to utilize this tool to enhance motivation for change in addiction treatment. However, no statistically significant difference was reported both on a Wilcoxon Signed-ranks Test and a mixed-design ANOVA. Yet considering the small sample size (n = 7), Taking Steps was remarkably found to exceed a large effect size (r = 0.50). Limitations and cultural aspects in this study are also discussed. Continuing research on the topic of possible future selves by using digital media is encouraged for further exploration and application in art therapy

The Impact of Culture on the Demand for Non-Life Insurance

Regression techniques are applied to an unbalanced panel data that includes 68 countries observed over a ten-year period, to explore the factors that affect non-life insurance demand across nations. While previous literature has discovered several significant economic, demographic, and institutional variables, little attention has been devoted to cultural dimensions. We find that non-life insurance consumption is adversely impacted in countries where a large fraction of the population has Islamic beliefs. Also highly significant are three of the cultural scores developed by Hofstede in a celebrated study: Power Distance, Individualism, and Uncertainty Avoidance. An important finding is that culture impacts non-life insurance more in affluent countries, with an adjusted R-square coefficient increasing by 11.7%, than in developing countries where the R-square coefficient increase due to cultural impacts is only 1.2%. These results have implications for multinational insurers seeking to enter a new market. Ceteris Paribus, these insurers should target countries, and population segments within these countries, that exhibit low Power Distance, and high Individualism and Uncertainty Avoidance scores

Differential Aging-In-Place.

This three-essay dissertation explores components of aging–in-place among adults living alone aged 65 and older using nationally representative data from the Health and Retirement Study (HRS). Drawing on the Person-Environment Fit and Person-Centered perspectives, the overall goal is to examine the extent to which three dimensions of aging-in-place, namely the environment, the older individual, and individual agency (efficacy), are inter-related in order to enable independent living among this subgroup of older persons. Together, these three components help to characterize the heterogeneity of the life contexts and personal resources of older adults who live alone and are aging-in-place. The first paper explored to what degree the environment and health subgroups are associated with subjective well-being among older adults living alone. Through clustering analysis, the four health subgroups of sensory-cognitive impaired, physically impaired, frail, and healthy were identified. The intersection of these health subgroups with three environmental contexts that reflect different levels of physical and social support were examined. The frail group was more likely to show depressive symptoms if they lived in a physically average and socially unsupported environment. The sensory-cognitive impaired group was more likely to report depressive symptoms when they lived in a physically-unsupported but socially-supported environment. The second paper asked if changes in depressive symptomatology over time are mediated by changes in perceived control. The findings confirm a stronger negative influence of membership in a vulnerable health subgroup on perceived control, which in turn affects depressive symptoms over time. Among the environmental contexts, only greater social support was associated with a decrease in depressive symptoms over time via perceived control. The third paper extended the empirical examination of proposals drawn from the Person-Environment Fit perspective. I asked how much environments moderate the effects of health profiles and low socioeconomic status on mortality risk. The results show that for individuals in the sensory-cognitive impaired and physically impaired groups, broader social network was associated with an increased risk of death. In addition, the study revealed that older adults living alone with low socioeconomic status who live in a senior housing environment had a reduced risk of death.PhDSocial Work and PsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108765/1/sojupark_1.pd

The Opaqueness of Structured Bonds: Evidence from the U.S. Insurance Industry

It has been argued that the opaqueness of structured bonds, such as mortgage-backed securities, asset-backed securities and collateral debt obligations, was one of the major causes of the recent financial crisis that started in late 2007. We analyse the evolving nature of information asymmetry inherent in various types of structured bonds by examining the U.S. insurers’ assets. We show that, prior to 2004, structured bonds were not associated with greater information asymmetry; however, holding more multi-class structured bonds, especially privately placed bonds, increased the information asymmetry when evaluating insurers’ assets post-2004. The effect of information asymmetry was more significant with life insurers than with non-life insurers. In addition, by investigating the rating grades of such structured bonds, we find that the market views higher-grade, privately placed, multi-class structured bonds as having the highest information asymmetry among all types of structured bonds post 2004, an effect which is, again, more significant with life insurers. This result shows that structuring complexities and unreliable ratings make structured bonds more opaque than just securitisation itself

Long-term employment outcomes among female cancer survivors

Advances in early detection and treatment have led to a growing population of female cancer survivors, many of whom are of working age. We examined the relationship between cancer and long-term (\u3e5 years) employment outcomes in a nationally representative sample of working-age women in the United States. Data from nine waves of the Health and Retirement Study were used to examine employment status and weekly hours worked among cancer survivors

The Relationship Between the Working Environment and Quality of Life Among Home Health Aides: Focusing on the Mediation Role of Burnout

As South Korea’s population rapidly ages, there is an increasing demand for home aides. However, little is known about how the caregiving environment affects HHAs. Guided by the environment comfort model, we examined the association between care recipients’ home environment and HHA’s quality of life, focusing on how burnout mediates this relationship. Our data came from a national survey of home health aides in 2020 (N = 786). We conducted an exploratory factor analysis to identify six factors related to the care environment in three dimensions: physical (1. space; 2. indoor/outdoor conditions), functional (3. home appliances; 4. heating/air conditioning), and psychological (5. satisfaction with the home environment; 6. relationships with care recipients and their families). We then used a path analysis to examine the relationship between these factors, burnout, and quality of life. Our findings show that safe indoor/outdoor conditions and positive relationships with care recipients and their families are associated with lower levels of burnout, leading to a higher quality of life (p \u3c .05). This highlights the importance of considering both physical and psychological aspects of the caregiving environment to prevent burnout and improve the quality of life for HHAs, ultimately contributing to high-quality services for care recipients

Genome-wide target specificities of CRISPR-Cas9 nucleases revealed by multiplex Digenome-seq

We present multiplex Digenome-seq to profile genome-wide specificities of up to 11 CRISPR-Cas9 nucleases simultaneously, saving time and reducing cost. Cell-free human genomic DNA was digested using multiple sgRNAs combined with the Cas9 protein and then subjected to whole-genome sequencing. In vitro cleavage patterns, characteristic of on- and off-target sites, were computationally identified across the genome using a new DNA cleavage scoring system. We found that many false positive, bulge-type off-target sites were cleaved by sgRNAs transcribed from an oligonucleotide duplex but not by those transcribed from a plasmid template. Multiplex Digenome-seq captured many bona fide off-target sites, missed by other genome-wide methods, at which indels were induced at frequencies <0.1%. After analyzing 964 sites cleaved in vitro by these sgRNAs and measuring indel frequencies at hundreds of off-target sites in cells, we propose a guideline for the choice of target sites for minimizing CRISPR-Cas9 off-target effects in the human genome.

Long-Term Health Effects of Work Trajectories Among Middle-Aged and Older Adults: The Mediating Role of Work, Material, and Social Environments

Using data from 14 waves (2003–2016) of the Korean Labor and Income Panel Study (KLIPS) (N = 1,627 individuals aged 45–64; 22778 observations), in this study, we conducted sequence analysis and a multi-categorical variable mediation analysis (1) to examine to what extent long-term work histories exhibit varying degrees of de-standardization and precariousness using sequence analysis (2) to explore the potential mediating effects of work, material, and social environments in the association between multiple work sequences and self-rated health. We found the coexistence of a relatively stable long-term employment pattern and a high prevalence of precariousness. The health and economic risks of precarious work fall disproportionately on older workers. Future researchers should continue to analyze whether the COVID-19 pandemic will lead to long-term changes in the workforce to improve our understanding of and response to working in later life and its health effects

Self-Supervised Pre-Training for Precipitation Post-Processor

Obtaining a sufficient forecast lead time for local precipitation is essential in preventing hazardous weather events. Global warming-induced climate change increases the challenge of accurately predicting severe precipitation events, such as heavy rainfall. In this paper, we propose a deep learning-based precipitation post-processor for numerical weather prediction (NWP) models. The precipitation post-processor consists of (i) employing self-supervised pre-training, where the parameters of the encoder are pre-trained on the reconstruction of the masked variables of the atmospheric physics domain; and (ii) conducting transfer learning on precipitation segmentation tasks (the target domain) from the pre-trained encoder. In addition, we introduced a heuristic labeling approach to effectively train class-imbalanced datasets. Our experiments on precipitation correction for regional NWP show that the proposed method outperforms other approaches.Comment: 7 pages, 3 figures, 1 table, accepted to NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning at [this http URL](https://www.climatechange.ai/papers/neurips2023/18