scholarly journals Association between Cross-Cultural Social Adaptation and Overseas Life Satisfaction among Chinese Medical Aid Team Members (CMATMs) in Africa

2019 ◽  
Vol 16 (9) ◽  
pp. 1572 ◽  
Author(s):  
Xiaochang Chen ◽  
Xiaojun Liu ◽  
Wei Yu ◽  
Anran Tan ◽  
Chang Fu ◽  
...  
Keyword(s):  
Life Satisfaction ◽  
Regression Models ◽  
Cross Cultural ◽  
Social Adaptation ◽  
Linear Regression Models ◽  
Team Members ◽  
Medical Aid ◽  
Electronic Questionnaires ◽  
The Relationship ◽  
Overall Life Satisfaction

This study evaluated the relationship between cross-cultural social adaptation and overseas life satisfaction among Chinese medical aid team members (CMATMs) in Africa. A revised Chinese version of the Sociocultural Adaptation Scale (CSCAS) was used to measure participants’ cross-cultural social adaptation. The self-designed survey of the CMATMs’ overseas life satisfaction includes the following five aspects: food, housing, transportation, entertainment, and security. Electronic questionnaires were distributed non-randomly. Linear regression models were established to explore the association between cross-cultural social adaptation and all dimensions of overseas life satisfaction. After adjusting all the confounders, compared with moderate adaptation, poor adaptation was negatively correlated with all dimensions of overseas life satisfaction (B for food = −0.71, B for housing = −0.76, B for transportation = −0.70, B for entertainment = −0.53, B for security = −0.81, B for overall satisfaction = −0.71, all p < 0.001), whereas good adaptation was positively associated with all dimensions of overseas life satisfaction (B for food = 1.23, B for housing = 1.00, B for transportation = 0.84, B for entertainment = 0.84, B for security = 0.76, B for overall life satisfaction = 0.94, all p < 0.001). This study shows that a better cross-cultural social adaptation was positively connected to a higher level of overseas life satisfaction in general, and more specifically to higher levels of satisfaction with food, housing, transportation, entertainment, and security. This knowledge can be utilized in promoting cross-cultural social adaptation and overseas life satisfaction among CMATMs in Africa.

Relationship Between Mental Health, Resilience, and Physical Activity in Older Adults: A 2-Year Longitudinal Study

2021 ◽  
pp. 1-9
Author(s):  
Maria Priscila Wermelinger Ávila ◽  
Jimilly Caputo Corrêa ◽  
Alessandra Lamas Granero Lucchetti ◽  
Giancarlo Lucchetti
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Older Adults ◽  
Regression Models ◽  
Linear Regression Models ◽  
Physically Active ◽  
Effective Interventions ◽  
Self Sufficiency ◽  
The Relationship

The aim of this study was to longitudinally investigate the association between resilience and mental health in older adults and to determine the influence of physical activity on this relationship. A total of 291 older adults were included in a 2-year follow-up study. Adjusted linear regression models evaluated the association between resilience at baseline and mental health after 2 years in sufficiently and insufficiently physically active older adults. A negative correlation was found between resilience at baseline and depression, anxiety, and stress after 2 years for the overall sample. This association changed after stratifying the group. Sufficiently physically active individuals made greater use of the resilience components “Self-Sufficiency” and “Perseverance,” whereas insufficiently physically active individuals made greater use of “Meaning of Life” and “Existential Singularity.” Physical activity can influence the relationship between resilience and mental health. These results can help guide the devising of more effective interventions for this age group.

Expanding the Happiness Paradox: Ethnoracial Disparities in Life Satisfaction Among Older Immigrants in the United States

2017 ◽  
Vol 31 (2) ◽  
pp. 231-255
Author(s):  
Rocío Calvo ◽  
Dawn C. Carr ◽  
Christina Matz-Costa
Keyword(s):  
United States ◽  
Life Satisfaction ◽  
Regression Models ◽  
The United States ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Older Immigrants ◽  
Happiness Paradox ◽  
Retirement Study ◽  
Lower Life Satisfaction

Objective: This study investigated nativity disparities in life satisfaction among ethnoracial groups of older adults in the United States and the factors associated with such disparities. Method: Cross-sectional data from 7,348 respondents aged 60 and older from the 2012/2014 waves of the Health and Retirement Study (HRS) were used to estimate linear regression models. Results: Older immigrants experienced higher levels of life satisfaction than comparable native-born individuals. This “happiness advantage” was particularly salient for Hispanic immigrants, who reported the highest levels of life satisfaction of all groups included in the study. With increasing education, life satisfaction increased for White and “Other Race” groups, regardless of nativity. However, for both Black groups and native-born Hispanics, higher levels of education were associated with lower life satisfaction. Discussion: Findings suggest that the “happiness paradox” may not only be a matter of Hispanic ethnicity, but that it may also extend to immigrants from other ethnoracial backgrounds.

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

BAYESIAN IDENTIFICATION OF OUTLIERS AND CHANGE-POINTS IN MEASUREMENT ERROR MODELS

2005 ◽  
Vol 08 (04) ◽  
pp. 433-449 ◽  
Author(s):  
FERNANDO A. QUINTANA ◽  
PILAR L. IGLESIAS ◽  
HELENO BOLFARINE
Keyword(s):  
Linear Regression ◽  
Outlier Detection ◽  
Change Point ◽  
Regression Models ◽  
Point Problem ◽  
Linear Regression Models ◽  
Outlier Identification ◽  
Change Point Problem ◽  
Error In Variables ◽  
The Relationship

The problem of outlier and change-point identification has received considerable attention in traditional linear regression models from both, classical and Bayesian standpoints. In contrast, for the case of regression models with measurement errors, also known as error-in-variables models, the corresponding literature is scarce and largely focused on classical solutions for the normal case. The main object of this paper is to propose clustering algorithms for outlier detection and change-point identification in scale mixture of error-in-variables models. We propose an approach based on product partition models (PPMs) which allows one to study clustering for the models under consideration. This includes the change-point problem and outlier detection as special cases. The outlier identification problem is approached by adapting the algorithms developed by Quintana and Iglesias [32] for simple linear regression models. A special algorithm is developed for the change-point problem which can be applied in a more general setup. The methods are illustrated with two applications: (i) outlier identification in a problem involving the relationship between two methods for measuring serum kanamycin in blood samples from babies, and (ii) change-point identification in the relationship between the monthly dollar volume of sales on the Boston Stock Exchange and the combined monthly dollar volumes for the New York and American Stock Exchanges.

Amendment of traditional assessment measures for the negative symptoms of schizophrenia

2018 ◽  
Vol 49 ◽  
pp. 50-55 ◽  
Author(s):  
Aida Farreny ◽  
Judith Usall ◽  
Jorge Cuevas-Esteban ◽  
Susana Ochoa ◽  
Gildas Brébion
Keyword(s):  
Verbal Memory ◽  
Regression Models ◽  
Negative Symptoms ◽  
Linear Regression Models ◽  
Illness Duration ◽  
Traditional Assessment ◽  
Syndrome Scale ◽  
Assessment Measures ◽  
Negative Syndrome ◽  
The Relationship

AbstractSchizophrenia research based on traditional assessment measures for negative symptoms appears to be, to some extent, unreliable. The limitations of the Positive and Negative Syndrome Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS) have been extensively acknowledged and should be taken into account. The aim of this study is to show how the PANSS and the SANS conflate negative symptoms and cognition and to offer alternatives for the limitations found.MethodsA sample of 117 participants with schizophrenia from two independent studies was retrospectively investigated. Linear regression models were computed to explore the effect of negative symptoms and illness duration as predictors of cognitive performance.ResultsFor the PANSS, the item “abstract thinking” accounted for the association between negative symptoms and cognition. For the SANS, the “attention” subscale predicted the performance in verbal memory, but illness duration emerged as a stronger predictor than negative symptoms for outcomes of processing speed, verbal and working memory.ConclusionUtilizing alternative models to the traditional PANSS and SANS formats, and accounting for illness duration, provide more precise evidence on the relationship between negative symptoms and cognition. Since these measures are still extensively utilized, we recommend adopting more rigorous approaches to avoid misleading results.

scholarly journals Loneliness and COVID-19 preventive behaviours among Japanese adults

2020 ◽  
Author(s):  
Andrew Stickley ◽  
Tetsuya Matsubayashi ◽  
Michiko Ueda
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Odds Ratio ◽  
Regression Models ◽  
Online Survey ◽  
Health Behaviours ◽  
Regression Analyses ◽  
Linear Regression Models ◽  
Japanese Adults ◽  
The Relationship

Abstract Background There is some evidence that loneliness may be linked to poorer health behaviours. Despite this, there has been little research to date on the relationship between loneliness and COVID-19 preventive behaviours. We studied these associations in a sample of the Japanese population. Methods Data were analysed from an online survey of 2000 adults undertaken in April and May 2020. Loneliness was assessed with the Three-Item Loneliness Scale. Information was also collected on 13 COVID-19 preventive behaviours. Regression analyses were used to examine associations. Results In linear regression models adjusted for demographic and mental health variables, both dichotomous and continuous loneliness measures were negatively associated with engaging in COVID-19 preventive behaviours. Logistic regression analyses further showed that loneliness was also associated with reduced odds for a variety of individual preventive behaviours including wearing a mask (odds ratio [OR]: 0.77, 95% confidence interval [CI]: 0.62–0.95), disinfecting hands (OR: 0.80, 95% CI: 0.67–0.94) and social distancing when outdoors (OR: 0.75, 95% CI: 0.61–0.92). Conclusions Loneliness is associated with lower engagement in COVID-19 preventive behaviours. Interventions to prevent or ameliorate loneliness during the ongoing pandemic may be important in combating the spread of the coronavirus.

scholarly journals Temporal-Spatial Analysis of Traffic Congestion Based on Modified CTM

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Chenglong Chu ◽  
Na Xie ◽  
Xiqun Chen ◽  
Yuxin Wu ◽  
Xiaoxiao Sun
Keyword(s):  
Traffic Congestion ◽  
Regression Models ◽  
Piecewise Linear ◽  
Transmission Model ◽  
Spatial Evolution ◽  
Cell Transmission Model ◽  
Linear Regression Models ◽  
Piecewise Linear Regression ◽  
Relationship Of ◽  
The Relationship

A modified cell transmission model (CTM) is proposed to depict the temporal-spatial evolution of traffic congestion on urban freeways. Specifically, drivers’ adaptive behaviors and the corresponding influence on traffic flows are emphasized. Two piecewise linear regression models are proposed to describe the relationship of flow and density (occupancy). Several types of cellular connections are designed to depict urban rapid roads with on/off-ramps and junctions. Based on the data collected on freeway of Queen Elizabeth, Ontario, Canada, we show that the new model provides a relatively higher accuracy of temporal-spatial evolution of traffic congestions.

GENDER DIFFERENCES IN CONSUMPTION ASPIRATIONS: A CROSS-CULTURAL APPRAISAL

1991 ◽  
Vol 19 (4) ◽  
pp. 237-253 ◽  
Author(s):  
Wendy Bryce ◽  
T. T. Olney
Keyword(s):  
Gender Differences ◽  
Life Satisfaction ◽  
Content Analysis ◽  
Cultural Differences ◽  
Good Life ◽  
Cross Cultural ◽  
The Good Life ◽  
Relative Importance ◽  
Satisfaction Measures ◽  
The Relationship

This study explores the possibility of gender and cultural differences in consumption aspirations using two different approaches. The first approach is designed to elicit stereotypes with regard to consumption dreams or the “good life”: “What do you believe most Americans (New Zealanders) wish for or want to achieve in their lives?”. The second approach probes for individuals' actual aspirations: “Three years after graduation, how do you want your life to be in terms of …”. Specific consumption categories examined in both approaches allow an assessment of individuals' relative emphasis on Having, Doing and Being (Sartre, 1956). Priority rankings of these categories provide information regarding the relative importance of each class of possessions/experiences. In addition, materialism and life satisfaction measures are included to assess the relationship between these two constructs and consumption aspirations and dream stereotypes. Content analysis of the data indicates that (1) significant gender differences in consumption aspirations and dream stereotypes do exist, although the form of these differences varies as a function of culture, and (2) culture has a more significant effect on aspirations and dreams than does gender. Findings are discussed in terms of gender theory and cultural differences between the two countries.

scholarly journals Factors associated with parasite dominance in fishes from Brazil

2016 ◽  
Vol 25 (2) ◽  
pp. 225-230
Author(s):  
Cristina Fernandes do Amarante ◽  
Wagner de Souza Tassinari ◽  
Jose Luis Luque ◽  
Maria Julia Salim Pereira
Keyword(s):  
Linear Regression ◽  
Body Length ◽  
Regression Models ◽  
Mixed Model ◽  
Multiple Linear Regression Model ◽  
Mixed Effects ◽  
The Body ◽  
Linear Regression Models ◽  
Biological Aspects ◽  
The Relationship

Abstract The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

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