24 research outputs found
Effectiveness of advice from physician and nurse on smoking cessation stage in Taiwanese male smokers attending a community-based integrated screening program
Gender differences in smoking behavior trajectory patterns and related factors among older adults in Taiwan
Sex differences in smoking behavior trajectory patterns and related factors among older adults in Taiwan
Gender differences in smoking behavior trajectory patterns and related factors among older adults in Taiwan
HEALTH BEHAVIORS AMONG HIGH SCHOOL STUDENTS
針對臺北市某國民中學七十六學年度入學之512名學生進行連續三年追蹤調查,目 的在瞭解學生們於國中階段之健康行為 (包括常吃早餐、不常失眼、固定運動、目前沒有吸 菸及目前沒有喝酒等六項行為 ) 及三年間的變化情形。結果發現,常吃早餐 (≧ 5 次╱週 ) 和不常失眠 (1 次╱週 ) 之比率在三年間皆約為 80 %; 固定運動的比率在一、二年級 時各約佔 30 %,三年級時降為 7 %; 目前沒有吸菸者 (包括「從不吸菸」及「過去曾吸 但現已不吸 ) 所佔的比率逐年稍有降低 (三個年度各為 99 %,98 %, 和 96 % ) 目前 沒有喝酒者 (包括「從不喝酒」及「過去曾喝但現已不喝」所佔比率三個年度皆在 80-90 %之間。健康行為在三年間的變化方面:第一、二年間有 12.9 %的男生由較常失眠變為不 常失眠 (由「每週兩次及以上」改為「每週一次及以下」及 12.4 %的女生由不喝酒變為有 喝酒;第二、三年間有 12.9 %的男生由常吃早餐變為不常吃早餐,有 16.7 %的男生由不 常失眠變為較常失眠,33.3 %的男生及 24.2 %的女生由固定運動變為不固定運動。 至於 吸菸之發生率,在國中的第一年至第二年間為 6 %,第二年至第三年間為 20 %; 飲酒之 發生率則分別為 9 %及 22 %。 根據本研究結果,建議學校為學生提供營養早餐,並鼓勵 學生於課外養成自行運動的習慣,另於適當時機教導學生菸害知識及拒菸技巧,使學生於國 中階段養成有益健康的行為方式
Factors Related to Non-Response Trajectories of Children and Adolescents in a Long Term Follow-Up Study
目標:兒童與青少年行為之長期發展研究(簡稱CABLE計畫)因面臨研究樣本隨教育階段改變(國小、國中、高中、大學)而調整資料收集方法,本研究目的為描述兒童與青少年長期追蹤未回應之趨勢及原因,並分析其相關社會人口學因素。方法:CABLE計畫自2001年起針對台北及新竹國小一年級(世代一)和四年級學童(世代二)進行追蹤,以獲有父母同意書之學童為研究樣本(分別為2,852、2,663人)。未回應係指每年追蹤調查的應施測名單中未能回收問卷者。以世代分層Group-based Trajectory Model探討未回應趨勢及相關社會人口學因素。結果:經軌跡分析,世代一、二均呈現四個未回應軌跡:持續回應(世代一、二之百分比分別為73.4%、76.0%)、後期未回應(11.2%、5.4%)、漸增持續未回應(9.3%、8.2%)、及早期未回應後期回應(6.1%、9.7%)。相對於持續回應者,居住於台北、父母教育為高中及以下、父母婚姻為非結婚者,分別有較高之機會屬於不同狀況之未回應軌跡。結論:以CABLE持續追蹤資料進行推論時宜處理未回應之社會人口學差異。Objectives: The Child and Adolescent Behaviors in Long-term Evolution (abbreviated as CABLE) project had to change data collection methods for these subjects as they advanced to higher level schools including elementary school, junior high school, senior high school, and college or university. The purpose of this study was to describe the trajectories of non-response during the 9 year follow-up and to analyze the socio-demographic factors related to those trajectories. Methods: CABLE commenced in 2001 and subjects were followed every year. They were 1st and 4th grade students (sample sizes were 2853 and 2663 respectively) with parental consent in Taipei City and Hsin-Chu County. Non-response was defined as not responding to a questionnaire every year. We used the Group-based Trajectory Model to find non-response trajectories and related factors as stratified by cohorts. Results: Both cohorts showed four trajectories: continuing response (percentages in cohort 1 and cohort 2 were 73.4% and 76.0%, respectively), late non-response (11.2% and 5.4%), increasing non-response (9.3% and 8.2%), and early non-response but late response (6.1% and 9.7%). With continuing response as the reference group, those who lived in Taipei City, those whose parental education was lower than senior high school, and those whose parents were not married were more likely to be non-responsive. Conclusions: Using CABLE long term data to make implication should consider these socio-demographic differences with non-response trajectories
Defending behaviors, bullying roles, and their associations with mental health in junior high school students: a population-based study
Abstract Background Students should be encouraged to help prevent or stop bullying. However, defending victims of bullying can impact on mental health. It is not only bystanders who may defend victims, but bullies, victims and bully-victims can also have defending behaviors. Nevertheless, most studies of defending behaviors have been limited to an examination of the reactions of bystanders or those not involved in bullying and have ignored the other players. The aim of this study is to investigate the associations between defending behaviors and mental health among bullies, victims, bully-victims and bystanders. Methods Associations among defending behaviors, mental health (including depressive symptoms and social anxiety), and bullying experiences were cross-sectionally examined in 3441 students (13–15 years old.) from 20 randomly selected junior high schools in Taiwan using a self-report questionnaire. SAS 9.3 Survey Analysis procedures were used to conduct descriptive analysis and multiple regression models. Results Defending behaviors were associated with bullying roles and were higher in victims than in bullies or bystanders. Defending behaviors were positively associated with social anxiety and depressive symptoms. After stratifying by bullying roles, defending behaviors were positively associated with social anxiety in bystanders, and were positively associated with depressive symptoms in victims and bystanders. However, defending behaviors were not significantly associated with mental health indicators in bullies. Conclusions The associations between defending behaviors and mental health varied according to bullying roles. The results suggest that bystanders and victims experience more mental health effects than bullies. Intervention programs aimed at preventing bullying should focus on strategies that minimize social anxiety and depression in victims and bystanders, and urge students to help vulnerable peers during bullying events
Comparison of the social contact patterns among school-age children in specific seasons, locations, and times
Social contact patterns among school-age children play an important role in the epidemiology of infectious disease. This study explored how people interact in specific seasons (flu season and non-flu season), environmental settings (city and county), and times (weekend and weekday). We conducted a survey of junior high school students (grades 7–8) using an established questionnaire during May–June 2013 and December 2013. The sample size with pair-wise comparisons for the times (weekday/weekend) and stratification by location and seasons were 75, 87, 105 and 106, respectively. The sample size with pair-wise comparisons for the seasons (flu/non-flu) and stratification by location were 54 and 83, respectively. Conversation and skin-to-skin contact behaviors were surveyed through diary-based questionnaires, of which 665 valid questionnaires were returned. There was no difference in the number of contacts during the flu and non-flu seasons, with averages of 16.3 (S.D. = 12.9) and 14.6 (S.D. = 9.5) people, respectively. However, statistical analysis showed that the average number of contacts in Taichung City and Yilan County were significantly different (p < 0.001). Weekdays were associated with 23–28% more contacts than weekend days during both the non-flu and flu seasons (p < 0.001) (Wilcoxon signed-rank test). Our work has important implications for the dynamic modeling of infectious diseases and performance analysis of human contact numbers and contact characteristics for schoolchildren in specific seasons, places, and times