Purpose: The purpose of this study was to identify factors influencing exercise behaviors of the male manual workers and office workers based on health promotion model by examining the relationships among them, and then to provide basic information for developing exercise program. Methods: The 97 laborers and 99 officiers were collected from two worksites. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients and multiple regression. Results: Male laborers' exercise behavior was significantly influenced by exercise self-efficacy, exercise social support and exercise experience over 3 months, and these factors explained 50.2% of the total variance. Male officiers' exercise behavior was significantly influenced by exercise self-efficacy, subjective health status, perceived exercise barriers and exercise social support, and they explained 47.3% of the total variance. Conclusions: Based on the findings that exercise self-efficacy and exercise social support commonly influence exercise behavior of male laborers and officiers, there is a need to develop an exercise program to improve exercise self-efficacy and exercise social support.
Purpose: The purpose of this study was to identify the factors influencing self-identity and menopausal symptoms their influence on level of depression in middle-aged woman. Methods: Participants were 135 middle-aged women who were living in city B, were 45-60 years old, informed of study purpose, and agreed to participate. Data were collected from December, 2012 to January, 2013 using scales measuring depression, self-identity, and menopausal symptoms. Data were analyzed using t-test, ANOVA, Scheff$\acute{e}$ test, Pearson Correlation Coefficients, and Multiple Stepwise Regression. Results: Level of depression was low, self-identity was slightly high, and menopausal symptoms were relatively low in these middle-aged women. There were significant differences in depression by perceived health status and perceived economic status. Depression had a moderate negative correlation with self-identity (r=-.49, p<.001) and a moderate positive correlation with menopausal symptoms (r=.57, p<.001). Menopausal psychological symptoms were the factor most affecting depression and explained 37% of the variance in depression. A total of 51% of variance in depression was explained by menopausal symptoms (psychological and physical), self-identity, and perceived economic status. Conclusion: Thus, an effort to improve self-identity, especially a plan to attenuate menopausal psychological symptoms is needed to reduce depression.
Purpose: The purpose of this study was to identify effects of parenting stress in North Korean refugee fathers on their parenting behavior. Methods: A descriptive study design was used. Data were collected during 2014 and 2015 in a settlement support center for North Korean refugees and 99 North Korean refugee fathers participated. Data were analyzed using SPSS 21.0. Results: Warmth encouragement parenting behavior received the highest score. The score for parenting stress was 81.98 out of 180, and 32.3% of participants were found to need professional help (${\geq}PSI\;90$). There were significant negative correlations between warmth encouragement parenting behavior and parenting stress. There were also significant positive correlations between rejection neglect parenting behavior and parenting stress. Predictors of warmth encouragement behavior were parent-child dysfunctional interaction which explained 10.1% of the variance. Predictors of rejection neglect behavior were parent-child dysfunctional interaction, number of children and wife's education level which explained 33.4% of the variance. Conclusion: Findings show that North Korean refugee fathers' parenting stress significantly influenced warmth encouragement and rejection neglect parenting behavior indicating a need to identify ways to decrease parenting stress. Parenting education can guide North Korean refugee fathers to strengthen parent-child positive interactions and therefore promote their children's growth and development.
This paper attempts to identify the occupational stress-related factors among the workers at the manufacturing industry and to provide the basic data concerning development of stress management program focused on the manufacturing industry. The subjects exhibit significantly highest level of 'the characteristics of task and participation in decision making factor'. And the mean score of 'the avoid coping strategies' was higher than 'the control coping strategies'. The main factor that affected the occupational stress responses was 'the physio-environmental factor' and it was explained 15.6% out of the total variance of the stress responses. Also, it would be explained 29% out of the total variance of the stress responses with 'the characteristics of task/participation in decision making factor', sex, social support, and 'extra-organizational stressor'. In conclusion. For developing the stress management program in workplace, 'the physical environmental factor' and 'the characteristics of task and participation in decision making factor' should be considered. Also, It should be identified the direct and indirect paths among factors that significantly related factors to the occupational stress of workers further more.
During the last two decades, many industrial complexes for heavy and chemical industries have been established along the Korean coastline, thereby increasing the pollution materials burden on the coastal environment of seawater. Masan Bay is one of the most polluted coastal areas in Korea and the main soures of pollutants are domestic and industrial wastewater from Masan, Changwon. This study was aimed to evaluate relationships among the physicochemical parameters in the bottom water of Masan bay and to examine environmental factors affecting to pollutions of seawater by factor analysis. 'rife factor loading, 1 is showed higher increasing inclination after 1989 year in station 1. The variance of pollutant materials is showed 43.7% in which the coastal inflow water is indicated external loadings(factor 1 : NO3--N, TN, factor 4 : SiO2-Si) corresponded to domestic sewage, industrial wastewater, and earth-sands in the bottom water of Masan bay And the internal loadings(factor 2 : SS, salinity, factor 3 . W.T., DO) are explained 33.8%'corresponded the phenomena of sedimentary layer and oxygen concentration. Therefore, The external loadings are explained by the higher factor pollutantal variance in Masan bay.
Purpose: This study was conducted to find out interrelation of health behavior and related variables to provide basic data for an effective health promotion for the taxi-divers. Methods: 293 male taxi-drivers from 2 cities in Korea participated in this study. The data were collected using questionnaires from April 17th to Jun 3rd, 2006, and analyzed by descriptive statistics, t-test, ANOVA, Pearson correlation, and multiple regression. Results: There were statistically significant differences according to monthly income, past illness or surgery, current disease or medication, frequency of fright on daily driving (FFDD), driving fatigue, working style, social support in health status; current disease or medication, FFDD, driving fatigue, duty shift, social support in health perception; body mass index (BMI), FFDD, driving fatigue, intention of changing job, social support in health behavior. Social support, health status, health perception, and health behavior were significantly correlated with one another. The multiple regression analysis showed that health perception (17.8%), BMI (6.8%), intention of changing job (5.7%), and driving fatigue (4.2%) explained the 34.5% variance of health behavior. And the 22.6% of variance of health perception was explained by social support (12.2%), health status (6.9%), and duty shift (3.2%). Conclusions: To promote the taxi-drivers' health, nursing intervention strategies unique for them should consider health behavior and affecting factors.
Purpose: The purpose of this study was to examine potential factors related to the management of cancer pain, that is, hospital institutional factors as well as personal aspects of nurses. Methods: This study was a descriptive research study in which 229 RNs working in 2 tertiary medical institutions in Seoul and 4 secondary medical institutions in Seoul, Incheon and Gyeonggi were surveyed. Results: It was found that nurses' knowledge about pain intervention, their working division and their knowledge about the use of analgesics had different effects on their pharmacologic interventions. These 3 variables explained 14.5% of the variance regarding pharmacologic interventions. On the other hand, nurses' knowledge about pain interventions and nursing organization were variables affecting non-pharmacologic interventions by the nurses. These two variables explained 22.1% of the variance regarding non-pharmacologic interventions by the nurses. Conclusion: The findings indicate that nursing organization, one of hospital institutional factors, had significant effects on non-pharmacologic interventions. Therefore, to increase effective pain management by nurses, an organizational system should be established such as placement of nurse practitioners, improvement of nurses' autonomy in pain management, and development and distribution of standardized guidelines.
Purpose: The purpose of study was to assess the health promoting lifestyle among hospital nurses and to investigate the relationships between the health promoting lifestyle, resourcefulness, and perceived health status. Methods: The subjects were 400 nurses working at three university hospitals. The data were collected by self-administered questionnaires from September 1st to September 30th, 2008. Results: The range of Health Promoting Lifestyle Profile (HPLP) was 71-185, the average score was 112.50, and the item mean was 2.16 (total 4). The range of resourcefulness was 9-50, and the average score was 16.56. The range of perceived health status was 4-13, and the averae score was 9.52. Health promoting lifestyle was showed significantly positive correlations with resourcefulness (r=.473, p<.001), and with perceived health status (r=.176, p<.001). The independent variables including resourcefulness, religion, working shift, sleeping hours, and exercise explained 58.6% of the variance of health promoting lifestyle. Especially, resourcefulness explained 53.2% of the variance of health promoting lifestyle. Conclusion: Resourcefulness was identified as the most important variable contributing to the performance of health promoting lifestyle.
Haddadi, P.;Yazdi-Samadi, B.;Naghavi, M.R.;Kalantari, A.;Maury, P.;Sarrafi, A.
Plant Biotechnology Reports
/
제5권2호
/
pp.135-146
/
2011
The objective of the present research was to map QTLs associated with agronomic traits such as days from sowing to flowering, plant height, yield and leaf-related traits in a population of recombinant inbred lines (RILs) of sunflower (Helianthus annuus). Two field experiments were conducted with well-irrigated and partially irrigated conditions in randomized complete block design with three replications. A map with 304 AFLP and 191 SSR markers with a mean density of 1 marker per 3.7 cM was used to identify QTLs related to the studied traits. The difference among RILs was significant for all studied traits in both conditions. Three to seven QTLs were found for each studied trait in both conditions. The percentage of phenotypic variance ($R^2$) explained by QTLs ranged from 4 to 49%. Three to six QTLs were found for each yield-related trait in both conditions. The most important QTL for grain yield per plant on linkage group 13 (GYP-P-13-1) under partial-irrigated condition controls 49% of phenotypic variance ($R^2$). The most important QTL for 1,000-grain weight (TGW-P-11-1) was identified on linkage group 11. Favorable alleles for this QTL come from RHA266. The major QTL for days from sowing to flowering (DSF-P-14-1) were observed on linkage group 14 and explained 38% of the phenotypic variance. The positive alleles for this QTL come from RHA266. The major QTL for HD (HD-P-13-1) was also identified on linkage group 13 and explained 37% of the phenotypic variance. Both parents (PAC2 and RHA266) contributed to QTLs controlling leaf-related traits in both conditions. Common QTL for leaf area at flowering (LAF-P-12-1, LAF-W-12-1) was detected in linkage group 12. The results emphasise the importance of the role of linkage groups 2, 10 and 13 for studied traits. Genomic regions on the linkage groups 9 and 12 are specific for QTLs of leaf-related traits in sunflower.
Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.
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