This study was conducted to investigate the correlation between frequency of high-caffeine energy drink intake in adolescents and their mental health status using data from the Korean adolescent health behaviors online survey (2014-15). Mental health was classified by the five categories: Perception of stress (PS), Insufficient relief of fatigue after sleep (IRFS), Experience of sadness despair (SD), Suicidal ideation (SI), and Subjective unhappiness (SU). Regarding general characteristics, higher age, height, and body weight of subjects were associated with higher frequency of high-caffeine energy drink (HCED) intake (p< .0001). In the OR analysis, when the lowest group (${\leq}2/wk$) and highest group ($1{\geq}day$) were compared, the highest group showed significantly higher OR in all five categories of mental health. According to gender, males did not show better PS, SD, and SI than females who had a high frequency of HCED (p for trend<.0001). According to school level, middle school students showed a higher risk rate than high school students in PS, IRFS, and SD (p for trend< .0001). Based on the above results, higher frequency of HCED intake among adolescents was associated with more adverse effects on mental health.
Journal of the Korean Academy of Child and Adolescent Psychiatry
/
v.30
no.3
/
pp.109-115
/
2019
Objectives: This study investigates lay beliefs about the etiology and treatments of tic disorder and Tourette's syndrome, as well as identifying sociodemographic and personality variables affecting these beliefs among South Koreans. Methods: In total, 673 participants (mean age $41.77{\pm}12.03$ years) completed an online survey regarding their beliefs about tic disorder and Tourette's syndrome. The factors related to their lay beliefs about the disorders were analyzed, and the correlates were investigated. Results: Results indicated that lay people in South Korea held strong beliefs that the causes of tic disorder and Tourette's syndrome lie within the parenting/psychological and neurological/biological categories, compared to the dietary/environmental one. Among the sociodemographic variables, sex, age, and levels of subjective mental health knowledge were primarily associated with the aforementioned beliefs. Familiarity with tic disorder and Tourette's syndrome was also associated with these beliefs. Among the personality traits investigated, extraversion and conscientiousness had significant influences on the beliefs people had about tic disorder and Tourette's syndrome. Conclusion: The results suggest that both policy makers and mental health service providers should adopt a strategic approach for developing and implementing health education interventions about tic disorder and Tourette's syndrome because individual sociodemographic variables, familiarity with the disorders, and personality traits are all associated with the beliefs about these disorders.
Objectives: The purpose of this study is to analyze factors associated with depression among workers in South Korea by socio-economic factors, health behaviors, and working conditions. Methods: Study subjects include 4,251 adults (19 and older) who are currently working using the data from 2009 National Health and Nutrition Survey. Data were analyzed using frequency test, $X^2$ test, and multiple logistic regression. Results: Multiple logistic regression analysis showed that gender (OR=1.91, p<.001), age (OR=1.53, p=.030), marital status (31-39: OR=1.88, p=.029) were significantly related to depressing among socio-economic factors. Next, among health behaviors factors, perceived health status (Poor: OR=1.76, p=.049; Very poor: OR=3.46, p=.002) was statistically significant. Among characteristics of work environment, trust and respect (OR=1.34, p=.049) and working with hidden emotion (OR=1.88, p<.001) were significantly related to depression. Conclusions: In order to manage and reduce depression among workers, it is important to develop appropriate mental health promotion programs both in work places and in regulations.
This study analyzed the relationship between GPS-based physical activity patterns and mental health using Kaggle Student Life data. Data were collected over a 10-week period from 48 students at Dartmouth College through Android smartphones and included GPS, dark, and phone lock data, and measures such as the Patient Health Questionnaire-9 (PHQ-9), Loneliness Scale, the Positive and Negative Affect Schedule (PANAS), and Perceived Stress Scale. Using latitude and longitude data obtained from GPS measurements, various physical activity indicators were calculated, including the total distance traveled, average distance traveled, average distance traveled in the morning, average distance traveled in the afternoon, average distance traveled in the evening, and average distance traveled in the middle of the night. Pearson's correlation analysis was performed to explore the relationship between GPS-based physical activity patterns and mental health. The study results indicated a significant negative correlation between the average distance traveled in the afternoon and PHQ-9 scores. Results indicated that the higher the afternoon activity, the lower the depressive symptoms. There was a positive correlation be-tween the PANAS-Pos score and the average distance traveled in the evening, indicating that positive emotions tended to increase as evening activities increased. This finding suggests a relationship between physical activity at specific times and mental health.
The Journal of Korean Society for School & Community Health Education
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v.23
no.1
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pp.1-16
/
2022
Background & Objectives: Self-rated health has been widely used to evaluate health status and accepted as a subjective measurement of quality of life. This study aimed to analyze the associations between self-rated health, health promotion behaviors, and mental health factors and suggest the approaches to improve health status among university students. Methods: Two thousand six hundred seventy-seven students who had stayed at dormitories on campus participated in the DU health survey by self-reported questionnaire from April 10 to 14, 2017. Multivariate logistic regression analysis was performed to estimate the odds ratios and 95% confidence intervals of association of self-rated health with health-related factors among male and female students. Results: 38.6% of the respondents reported good self-rated health. Male and first-year students were more likely to report good self-rated health than female and third-year students. There were significant differences in sex, grade, health problems, BMI, sleeping hours, eating breakfast, consumption of fruits and vegetables, physical activity (regular walking, strength exercise, moderate exercise, vigorous exercise), perceived stress, depression, and suicide thought (p<0.05). Conclusion: Although health promotion programs for university students are essential to support their adaptation to campus life and academic achievement, evidence-based health programs to encourage their participation are still insufficient. Therefore, it should establish a campus-based health policy and develop health promotion programs to increase self-rated health levels and prevent mental health problems for university students.
Objectives: The purpose of the study was to investigate the relationship between internet addiction and health in dental hygiene students. Methods: A self-reported questionnaire was completed by 216 dental hygiene students in Daegu from June 9 to 13, 2014. Data were analyzed by descriptive statistics, t-test, and ANOVA using SAS 9.2 program. The instruments included Korean internet addiction scale(K scale) and Korean version of the general health questionnaire. General characteristics consisted of grade, religion, residential types, economic condition, place of internet use, duration, purpose, and time of use. Physical characteristics consisted of subjective physical condition, smoking, alcohol drinking, exercise above twice per week, musculoskeletal disease, and location of physical symptoms. Psychiatric scale and 6 questions of physical characteristics were consulted by the statistician of preventive medicine department. Results: Internet users over 4 hours manifested the poor mental health, while those who uses internet under 2 hours showed good mental health(F = 1.41, p < 0.01). The students having good physical condition showed better mental health than those with poor physical condition(t = -2.81, p < 0.01). The students exercising at least twice a week showed better mental health than those who do not exercise(t = -3.10, p < 0.01). Those who having musculoskeletal symptoms showed higher index of internet addiction score than those who do not(t = 4.21, p < 0.01). Those who have no musculoskeletal symptoms tended to have better mental health than those who have musculoskeletal symptoms(t = 2.28, p < 0.05). The variables correlated to mental health were internet addiction, subjective physical condition, and exercise at least twice a week. The severity level of internet addiction leads to poor mental health(r = 0.26, p < 0.001). Conclusions: Internet addiction is closely related to mental health. So the students must know the danger of internet addiction. Proper health education is necessary for the prevention of addiction symptoms.
Background: While attention has been paid to physical risks in the work environment and the promotion of individual employee health, mental health protection and promotion have received much less focus. Psychosocial risk management has not yet been fully incorporated in such efforts. This paper presents good practices in promoting mental health in the workplace in line with World Health Organization (WHO) guidance by identifying barriers, opportunities, and the way forward in this area. Methods: Semistructured interviews were conducted with 17 experts who were selected on the basis of their knowledge and expertise in relation to good practice identified tools. Interviewees were asked to evaluate the approaches on the basis of the WHO model for healthy workplaces. Results: The examples of good practice for Workplace Mental Health Promotion (WMHP) are in line with the principles and the five keys of the WHO model. They support the third objective of the WHO comprehensive mental health action plan 2013-2020 for multisectoral implementation of WMHP strategies. Examples of good practice include the engagement of all stakeholders and representatives, science-driven practice, dissemination of good practice, continual improvement, and evaluation. Actions to inform policies/legislation, promote education on psychosocial risks, and provide better evidence were suggested for higher WMHP success. Conclusion: The study identified commonalities in good practice approaches in different countries and stressed the importance of a strong policy and enforcement framework as well as organizational responsibility for WMHP. For progress to be achieved in this area, a holistic and multidisciplinary approach was unanimously suggested as a way to successful implementation.
This study surveyed 57,303 teenagers using the 15th (2019) online Juvenile Health Behavior survey data to understand the relationship between oral health behavior, mental health, and smoking. The results of analyzing the factors affecting smoking experience are as follows: The smoking rate was higher in men (p<0.001), in a lower academic ability (p<0.001), and in moderate economic status was moderate (p<0.001). The smoking rate was higher in 2 or less brushing frequency (p<0.001), in no brushing before going to bed (p<0.001), in no brushing aftger lunch (p<0.001), in no experience of oral health education (p<0.001), and when the subjests felt unhealty in oral health (p<0.001). The smoking rate was significantly higher in those who experienced a lot of stress (p<0.001) and feelings of depression (p<0.001). The odds ratio for smoking was 1.44 when not brushing teeth before bedtime, 0.76 in experience of oral health education, and 1.29 in unhealthy subjective oral health. The odds ratio for smoking was 0.91 in no stress and 1.85 in depression. Since oral behavior and mental health affect smoking, intervening with these factors is necessary to quit smoking.
Purpose: The aim of this study was to determine the perceived needs and confidence of school nurses in health education at middle and high schools in Seoul, Korea. Methods: A descriptive survey questionnaire was developed by a research team to investigate the perceived needs and confidence across eight health education areas. A total of 329 school nurses at secondary schools in the metropolitan areas of Seoul participated. Descriptive statistics, the t-test, and ANOVA were conducted to analyze the data. Results: Generally high means in perceived education needs(Mean: 3.8~4.7/5) and health education confidence (Mean 3.3~4.5/5) were reported. However, there were significantly low means of health education confidence related to perceived needs in health education for all areas of health education. While injury prevention and emergency care education were the highest perceived educational needs and were also areas with high confidence of school nurses, mental health, social health, and sexual health were areas where nurses showed a significantly lower confidence. In general, nurses with a longer clinical experience and educational career had a higher confidence in injury prevention, emergency care, and mental health. Conclusions: Multi-level support, including the continuing education and proactive in-service training, for the school nurses needs to be developed to improve their teaching competency.
This study was designed to identify the relation between Self-care Agency and mental health in vocational high school students of a rural area. The subjects for this study were 210 students living in Chonnam province: the breakdown of first, second and third grade students were 74, 78 and 58 respectively. The data were collected from April 1 to 4, 1997. The instruments used in this study were the Self-Care Agency Questionnaire developed by Deneys (1981) and the simplified SCL-90 developed by Lee, H. K. (1986) for measuring Mental Health. The data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation using the SAS $PC^+$ Program. The results were as follows: 1. The mean score of the Self-care Agency was 2.43. 2. The mean score of Mental Health was 2.11. 3. There were significant differences in sex (t=6.13, p= .014), religion (t=4.65, p= .032), the educational level of the father (F=3.62, p= .032), economic status (F=5.90, p= .003), and school performance (F=5.94, p= .003) with respect to selfeare agenecy. 4. There were significant differences in dwelling place (t=3.18, p= .025), economic status (F=4.55, p= .012), school performance (F=6.72, p= .002) and health problems (t= 5.41, p= .021) with respect to mental health. 5. The relationship between self care agency and mental health revealed a significant correlation (r=- .24, p= .005). The results showed that a low level of self care agency has an effect on mental health. We need an effective health education program to promote mental health.
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