Predictors of Cigarette Smoking Behavior Among Military University Students in Taiwan. Wang, Kwua-Yun; Yang, Chia-Chen

Similar documents
Text-based Document. Psychometric Evaluation of the Diabetes Self-Management Instrument-Short Form (DSMI-20) Lin, Chiu-Chu; Lee, Chia-Lun

Predictors of Depression Among Midlife Women in South Korea. Ham, Ok-kyung; Im, Eun-Ok. Downloaded 8-Apr :24:06

Survey of Smoking, Drinking and Drug Use (SDD) among young people in England, Andrew Bryant

Text-based Document. Predicting Factors of Body Fat of Metabolic Syndrome Persons. Downloaded 13-May :51:47.

Text-based Document. Gaston-Johansson, Fannie. Downloaded 25-Jul :44:24.

Fall Prevention Algorithm for the Older Adult Population: A DNP Project Utilizing Evidence-Based Practice and Translational Research

Initiation of Smoking and Other Addictive Behaviors: Understanding the Process

Development and Evaluation of a Senior-Tailored Elastic Band Exercise Program

Text-based Document. Pain Management and Palliative Care: A Program of Research. Huijer, Huda Abu-Saad. Downloaded 9-May :53:16

Attitudes and Beliefs of Adolescent Experimental Smokers: A Smoking Prevention Perspective

Smart Nutrition and Conditioning for Kids (SNACK): An Interprofessional Approach to Nutrition and Physical Education

Text-based Document. Could Music Group Therapy Improve Negative Symptoms of Schizophrenia? Downloaded 28-Jun :19:09

Registered Nurses and Influenza Vaccination: Changing Mindsets and Improving Compliance to Foster Global Health

Diabetes-Related Knowledge, Attitude(s) and Practices of Health Workers Working With Diabetes in the Free State

Methodology Introduction of the study Statement of Problem Objective Hypothesis Method

FACTORS RELATED TO SMOKING HABITS OF MALE SECONDARY SCHOOL TEACHERS

Text-based Document. The Relationship between Vitamin D Levels in Pregnancy and Blood Glucose at the Gestational Diabetes Screening

Preventing Child and Adolescent Smoking

Impact of UNC Health Care s Tobacco-Free Hospital Campus Policy on Hospital Employees

Text-based Document. Increasing Physical Activity in Post Liver Transplant Patients. Serotta, Jennifer. Downloaded 14-May :39:26

diagnosis and initial treatment at one of the 27 collaborating CCSS institutions;

SMOKING STAGES OF CHANGE KEY MESSAGES

A RCT of the Effects of Medication Adherence Therapy for People with Schizophrenia Specturm Disorders. Chien, Wai Tong; Mui, Jolene; Cheung, Eric

The study was cross-sectional, conducted during the academic year 2004/05.

Εvaluation of a health education programme for the prevention of smoking in secondary education students

Text-based Document. Authors Goossens, Peter J. J.; Engelbertink, Monique M. J. Downloaded 29-Jun :22:10.

Evaluation of Workplace-based Quit Smoking Programs. Check-in Survey for Employers

Spirituality and Religiosity as an Approach to Coping for Adolescents Living with Sickle Cell Disease: A Review of the Literature

Engaging Youth in Mental Health Promotion: Mental Health and Addictions Champions

Real-World Data for Enhancement of a National Smoking Cessation Intervention

Development and Prediction of Hyperactive Behaviour from 2 to 7 Years in a National Population Sample

Title: The Theory of Planned Behavior (TPB) and Texting While Driving Behavior in College Students MS # Manuscript ID GCPI

Despite substantial declines over the past decade,

Successful Cessation: Exploring Quit Attempts at Lehigh Valley Hopital's Tabacco Treatment Program.

FACTORS INFLUENCING SMOKING BEHAVIOURS AMONG MALE ADOLESCENTS IN KUANTAN DISTRICT

Guidelines to Manage Aggression and Facilitate the Mental Health of Educators in the Workplace. Authors Poggenpoel, Marie; Myburgh, Chris P. H.

Factors Influencing Smoking Behavior Among Adolescents

Patient-perceived barriers for cancer pain management between Western and Asian cultures-a systematic review by meta-analysis

Smoking Behavior of Thai Youths Thailand Dr. Choochai Supawongse et al, Results of the study 1. Situation of minors smoking.

11/1/2013. Depression affects approximately 350 million people worldwide, and is the leading cause of disability globally (WHO, 2012)

Social and Behavioral Sciences for Tobacco Use

Treatment Outcomes of a Tailored Smoking Cessation Programme for Individuals Accessing Addiction Treatment Services

Asthma and Tobacco: Double Trouble for Wisconsin Adolescents

Tobacco Use among Year Old Students in the Philippines, Authors. Nathan R. Jones CDC Office on Smoking and Health

Hae Won KIM. KIM Reproductive Health (2015) 12:91 DOI /s x

The Experience of Dysmenorrhea and Its Related Self-Care Behaviors Among Adolescent Girls. Wong, Cho Lee; Lam, Lai Wah; Ip, Wan Yim

Stigma in Sickle Cell Disease Scale Development: A Pilot Study in Adults and Family/Caregivers in the U.S. and Nigeria

Smoking Status and Body Mass Index in the United States:

A Survey of Greek Elementary School Students smoking habits and attitudes

Self-Management Among Adults with Type 2 Diabetes in Vietnam. Authors Dao, Hanh T. T.; Anderson, Debra Jane; Chang, Anne M.

Rewards for reading: their effects on reading motivation

Characteristics Associated With Awareness, Perceptions, and Use of Electronic Nicotine Delivery Systems Among Young US Midwestern Adults

Predictors of smoking cessation among Chinese parents of young children followed up for 6 months

SMOKING RELAPSE ONE YEAR AFTER DELIVERY AMONG WOMEN WHO QUIT SMOKING DURING PREGNANCY

ATTUD APPLICATION FORM FOR WEBSITE LISTING (PHASE 1): TOBACCO TREATMENT SPECIALIST (TTS) TRAINING PROGRAM PROGRAM INFORMATION & OVERVIEW

Outcomes of an Intensive Smoking Cessation Program for Individuals with Substance Use Disorders

Text-based Document. Using Guided Imagery to Reduce Pain and Anxiety. Authors Cole, Linda C. Downloaded 3-May :29:51

Population level Distribution of NRT: Means and Effectiveness from an Ontario wide Study Involving over 25,000 Participants

Optimizing Smoking Cessation within HUD s Proposed Smoke-Free Rule

XYZ County Schools LifeSkills Training (LST) Program Student Survey Results for the School Year

REPORT ON GLOBAL YOUTH TOBACCO SURVEY SWAZILAND

IUPUI Campus Smoking Survey Methods and Preliminary Findings January, 2004

Michele Clements-Thompson and Robert C. Klesges University of Memphis Prevention Center. Harry Lando University of Minnesota

Turnbull, T. (Triece); van Schaik, P. (Paul); van Wersch, A. (Anna)

Cancer Patients Interest and Preferences for an Inpatient Smoking Cessation Program (SCP)

The Effectiveness of Exercise Program for Aerobic Fitness in Adults With Systemic Lupus Erythematosus: A Systematic Review and Meta-Analysis

Northern Tobacco Use Monitoring Survey Northwest Territories Report. Health and Social Services

Psychosocial Correlates of Youth Smoking in Mississippi

Supplementary materials: Predictors of response to pegylated interferon in chronic hepatitis B: a

Increases in waterpipe tobacco smoking prevalence on a U.S. college campus 4

Indepen dent Study On Program Effective ness

Electronic Cigarette Use and Respiratory Symptoms in Chinese Adolescents in Hong Kong. Title. Wang, MP; Ho, DSY; Leung, LT; Lam, TH

Text-based Document. Women are Different!: Gender Specific Protocols for Treatment of Hypertension. Authors Whiffen, Rebecca J.

GLOBAL YOUTH TOBACCO SURVEY

Trait anxiety and nicotine dependence in adolescents A report from the DANDY study

Excellence in Prevention descriptions of the prevention

Appendix 1 This appendix was part of the submitted manuscript and has been peer reviewed. It is posted as supplied by the authors.

MacKenzie Phillips, MPH Program Coordinator

Rates and Predictors of Renewed Quitting After Relapse During a One-Year Follow-Up Among Primary Care Patients

VOICES OF THE HIDDEN

PUBLIC HEALTH RESEARCH

Smokers & Their Workplaces

Welcome Pioneers for Smoking Cessation

T obacco use is the leading cause of premature mortality in

Validity and reliability of physical education teachers' beliefs and intentions toward teaching students with disabilities (TBITSD) questionnaire

O riginal Article. Prevalence of smoking among male secondary school students in Jeddah, Saudi Arabia INTRODUCTION ABSTRACT

Depression and social support trajectories during 1 year postpartum among marriagebased immigrant mothers in Taiwan

Schroeder Institute + Mayo Clinic

Developing Genetic Education for Smoking Cessation. Julia F. Houfek, PhD, APRN-CNS, BC Associate Professor UNMC College of Nursing

Treatment Outcomes from the TDC: A Look at Smoking Cessation Among Patients with Co- Occurring Disorders

NATIONAL CERTIFICATE IN TOBACCO TREATMENT PRACTICE (NCTTP) TEST EXEMPTION OFFER APPLICATION VALID: OCTOBER 15, APRIL 15, 2018

HTH Page 1

NATIONAL CERTIFICATE IN TOBACCO TREATMENT PRACTICE (NCTTP) APPLICATION

Feng-Yi Lai, RN, MSN, Instructor Department of Nursing, Shu-Zen College of Medicine and Management, Asphodel Yang, RN, PhD, Associate Professor

Theory of Planned Behavior and how they predict Lebanese medical students behavioral intention to advise patients to quit smoking

Perceived relative harm of e cigarettes and attitudes towards their availability, advertising and use: A longitudinal survey

Potential Consequences of E-Cigarette Use: Is Youth Health Going Up in Smoke? October 11, 2016

Leveraging Social Networks to Promote Cancer Prevention Health Behaviors

Transcription:

The Henderson Repository is a free resource of the Honor Society of Nursing, Sigma Theta Tau International. It is dedicated to the dissemination of nursing research, researchrelated, and evidence-based nursing materials. Take credit for all your work, not just books and journal articles. To learn more, visit www.nursingrepository.org Item type Format Title Authors Presentation Text-based Document Predictors of Cigarette Smoking Behavior Among Military University Students in Taiwan Wang, Kwua-Yun; Yang, Chia-Chen Downloaded 8-Apr-2018 20:50:46 Link to item http://hdl.handle.net/10755/243203

Predictors of Cigarette Smoking Behavior Among Military University Students in Taiwan Kwua-Yun Wang, Chia-Chen Yang *, Nain-Feng Chu **, Der-Min Wu *** RN, PhD, Deputy Director, Department of Nursing, Taipei Veterans General Hospital, & Adjunct Professor, School of Nursing, National Defense Medical Center * RN, MS, Instructor, School of Nursing, National Defense Medical Center, & Doctoral Candidate, The Graduate Institute of Clinical Medical Sciences, Chang Gung University **MD, PhD, Superintendent, DOH Taitung Hospital, Adjunct Professor, School of Public Health, National Defense Medical Center ***MS, Associate Professor

Significance

The smoking rate among Taiwanese adolescents remains high. In any age group, smoking behavior can be influenced by personal, social, and familial factors. In adolescents, many factors, including psychological, physical, emotional, interpersonal relationship, social and familial, interact to influence smoking behavior. At present, no data are available on smoking behavior in military students in Taiwan. Understanding the factors that influence smoking behavior is a critical element in smoking cessation programs.

Research Purpose

The purpose of this study was to investigate the prevalence and predictors of smoking behaviors among military university students in Taiwan.

Material and Methods

Study Design Cross-sectional, descriptive and correlation design. Subjects were recruited from seven military universities nationwide in 2004.

Subjects Eligibility criteria for this study included: age 18 or higher and male. A total of 2,477 usable questionnaires were available for the data analysis. Participation proportions were computed in terms of the number of questionnaires collected divided by total number of students in each school. Proportion ranges for each school ranged from 82.0% to 100%.

Definition of Terms Non-smokers: Non-smokers defined as never-smokers or ex-smokers. Never-smokers referred to participants who either have never smoked a cigarette or not smoked regularly and, over the course of their lifetime, have not smoked more than 100 cigarettes. Ex-smokers referred to participants who, over their lifetime, smoked more than 100 cigarettes or previously smoked on a daily basis but have since quit cigarette smoking and, at present, do not smoke cigarettes at all.

Smokers: Smokers defined as over their lifetime, have smoked over 100 cigarettes and at present smoke cigarettes on a regular basis (at least one cigarette a day) or semi-regular basis (continuing occasional smoker).

Demographics age, Study tools parents education level, family environment (including parents/sibling smoking behaviors), school environment (including teachers, best friends smoking behaviors and schools policy of smoking).

Cigarette smoking history frequency of smoking, amount of smoking, reasons for smoking, age of first smoke, progression to regular cigarette use, continuation of smoking, motivation for cessation.

Cigarette smoking attitude questionnaire Consists of 15 questions and measures attitudes toward smoking with regard to health effects, perceived impression of smoking, effects of smoking on emotional condition, and smoking prohibition policies. Each of the questions were answered on a 5-point Likert-type scale, from 1 (strongly agree) to 5 (strongly disagree). Content validity index (CVI) values was.96; Cronbach s alpha coefficients was.83.

Self-Efficacy Refusing to Smoke questionnaire Developed by Liao (1994) was used to measure a respondent s confidence to not smoke when faced with the following situations: stress, nervousness, boredom, depression, and being in smoke-free public spaces. The questionnaire consists of 10 questions, with each question answered on a 5-point Likert-type scale ranging from 1 ( have no confidence at all) to 5 (have full confidence). Content validity index (CVI) value was.86; Cronbach s alpha coefficients was.98.

Cigarette smoking behavior Measured by frequency and duration of cigarette smoking from the past through the present; Classified respondents into two types: nonsmokers and smokers.

Data Collection and Processing Data collection was carried out in a classroom at each school. Data collectors were introduced to the study purposes and instructed on how administer the questionnaire to subjects. Questionnaires were checked and verified for completeness when the subjects handed them in.

A standardized decoding register was compiled and all data were computerized with the help of a card reader. Afterwards, all computerized data were compared and rectified against actual questionnaire data in order to eliminate inconsistencies. A frequency distribution was computed to check for any abnormal or outlying values.

Ethical considerations Before starting this study, researchers obtained approvals from the administrative departments of all targeted universities. Participants signed a written consent form, and confidentiality of responses was assured.

Statistical Analysis Data were analyzed using the SAS 8.1 statistical software package (SAS Institute, Inc., Cary, NC). Descriptive statistical analysis described the distribution of different variables of the study. Inferential statistical analysis, including a Student s t-test and logistic regression analysis, was used to predict factors underlying cigarette smoking behaviors. Statistical significance was defined as p <.05.

Results

Distribution of Demographics Of the 2,477 students, mean age was 20.9 years (SD = 2.1 years). The educational level of students parents was primarily college and university (37.6%) for fathers and junior high school or lower (34.8%) for mothers. With regard to family environment, 15.7% of students fathers and 3.2% of students mothers reported smoking cigarettes. Approximately 13% of siblings also smoked. As to school environment, 62.2% students reported smoking by their teachers and/or officers, and 36.4% of their best friends smoked. More than half of the students indicated that their schools had a no-smoking policy in place ( Table 1).

Table 1. Subject Demographics (N=2,477) Variables n % Age (years old) 18 138 5.6 19 423 17.1 20 593 23.9 21 576 23.3 22 717 28.9 Not Recorded 30 1.2 Father s Education Level Junior high 648 26.2 High school 725 29.3 College/University 931 37.6 Graduated 104 4.2 Not Recorded 69 2.7 Mother s Education Level Junior high 862 34.8 High school 856 34.6 College/University 653 26.4 Graduated 40 1.6 Not Recorded 66 2.6 Father Smoking Status Yes 966 15.7 No 1121 45.3 Not record 390 39.0 Mother Smoking Status Yes 80 3.2 No 2013 81.3 Not record 384 15.5 Sibling Smoking Status Yes 313 12.6 No 1779 71.8 Not record 385 15.6 Teacher Smoking Status Yes 1540 62.2 No 471 19.0 Not record 466 18.8 Best friend smoking status Yes 901 36.4 No 1155 46.6 Not recorded 421 17.0 School non-smoking policy Have 1372 55.4 No 881 35.6 Unknown 224 9.0

Prevalence and Cigarette Smoking History The prevalence of cigarette smoking was 5.7%. Subjects who were non-smokers accounted for 94.3% of the total (Table 2). Smokers (Table 3) More than half of the students (53.9%) who smoked cigarettes consumed an average of fewer than five cigarettes per day. Around 45% smoked cigarettes every day of the week. More than one-third (34.8%) reported having smoked for 3-4 years. Around 13% of students reported that they started smoking after enrollment in school, and 33.3% progressed to become regular smokers.

Forty-four percent of students reported curiosity as the main reason behind their first cigarette smoking experience, followed by low mood (12.1%), and relief from stress (11.3%). Continuation of smoking was mainly due to relief from stress (52.5%), difficulties in smoking cessation (38.3%), and boredom (28.4%). In terms of cessation intent, most (83.0%) indicated a desire to quit the smoking habit.

Table 2. Prevalence of Cigarette Smoking Behavior Among Participants (N=2,477) Variables n % Non-smoker 2336 94.3 Smoker 141 5.7

Table 3. Cigarette Smoking Characteristics Among Smokers (N=141) Variables n % Variables n % Average Quantity (per day) Form a Regular Smoking Habit < 5 pcs. 76 53.9 Before enrollment in school 84 59.6 6-10 pcs. 45 11-15 pcs. 16-20 pcs. 3 2.1 > 20 pcs. 2 1.4 Not recorded 5 31.9 After enrollment in school 47 33.3 10 7.1 Unknown 10 7.1 3.6 Reasons for Continuing to Smoke (multiple answers allowed) Have smoking around mate Relief from stress 16 11.4 74 52.5 Average Days (per week) Interpersonal relationship 7 5.0 1-2 days 40 28.4 Difficulties of smoke cessation 54 38.3 3-4 days 25 5-6 days 10 17.7 7.1 boredom Stimulating effect 40 28.4 35 24.8 Every day 63 44.7 Other 6 4.3 Not recorded 3 2.1 Would You Like to Quit Habit? Smoking Duration No 20 14.2 <1 year 10 7.1 Yes 117 83.0 1-2 year 28 19.9 Not recorded 4 2.8 3-4 year 49 34.8 5-9 year 42 29.8 >10 year 10 7.1 Not recorded 2 1.3 First Smoking Experience Before in military school 118 83.7 While in military school 18 12.8 Not recorded 5 3.5 Reasons for Starting to Smoke (multiple answers allowed) Curiosity 62 44.0 Boredom 12 8.5 Stimulating effect 3 2.1 Friends instigate 10 7.1 Imitating family/ friends 3 2.1 Expression of smart and cool 3 2.1 Relief from stress 16 11.3 Peer pressure 6 4.3 Other 9 6.4

Distribution of smoking attitudes and self-efficacy Due to missing data on a number of the submitted questionnaires, the number of respondents used in data analysis was 2,025 and 2,059, respectively. Student s t-test showed significantly different attitudes toward smoking and levels of self-efficacy between smokers and nonsmokers (p <.001) (Table 4). With regard to attitude toward smoking, non-smokers scored significantly higher than smokers (63.0 ± 8.8 vs. 52.2 ± 6.7), which indicated that non-smokers in universities showed less acceptance of smoking behaviors.

Smokers scored significantly lower than non-smokers in terms of self-efficacy (26.1 ± 6.4 vs. 46.4 ± 6.6), which indicated that smokers in universities were not confident or assertive enough to resist cigarettes.

Table 4. Difference in Smoking Attitudes and Self-Efficacy Among Participants(N=2025 & 2059) Variables Smoking Attitude Non-smoker Smoker N M SD t value p value 1920 105 63.0 52.2 8.8 6.7 15.8 <.001 Self-Efficacy Non-smoker Smoker 1955 104 46.4 26.1 6.6 6.4 30.9 <.001

Prediction Model for Cigarette Smoking Behaviors Model 1 used univariate logistic regression to analyze smoking factors of influence. Results revealed that age, family environment, school environment, attitudes toward smoking and self-efficacy were related to cigarette smoking behaviors (Table 5). Model 2 used multivariate logistic regression to analyze smoking behaviors. Results showed age, peer influence and self-efficacy were the significant predictors of cigarette smoking behaviors (Table 5).

Table 5. Predictive Models Related to Cigarette Smoking Behavior Among Participants (N=2477) Variables Model 1 Model 2 OR 95% C.I. OR 95% C.I. Age 1.35*** 1.16-1.56 1.40* 1.04-1.88 Father smoking status (Yes / No) 1.90** 1.27-2.84 1.28 0.66-2.47 Mother smoking status (Yes / No) 0.65 0.28-1.54 0.41 0.10-1.70 Sibling smoking status (Yes / No) 3.32*** 2.19-5.05 1.44 0.70-2.96 Teacher smoking status (Yes / No) 3.34*** 1.67-6.67 1.10 0.40-3.04 Best friend smoking status (Yes / No) 9.38*** 5.31-16.57 3.61** 1.53-8.54 School non-smoking policy (Yes / No) 1.50*** 1.25-1.79 1.09 0.79-1.51 Smoking attitude 0.87*** 0.85-0.89 1.03 0.98-1.08 Self-efficacy 0.78*** 0.75-0.81 0.76*** 0.72-0.80 Note. 1 Univariate analysis with the crude odd ratio. 2 Multivariate analysis after adjusting for other variables in the model. For example, the adjusted OR of cigarette smoking for age were after further adjusting for father smoke status, mother smoke status, sibling smoke status, teacher smoke status, best friend smoke status, smoking attitude and self-efficacy; study subject as a smoker. *p <.05. **p<.01. ***p <.001.

Conclusion

Age, best friends smoking/peer influence, and self efficacy were significant predictors of smoking behaviors among military university students in Taiwan. Peer influence should be taken into account when planning tobacco control strategies. It may be beneficial to promote the formation of student smoking cessation groups in order to reinforce positive group norms. Collaborative work with the Ministry of Health and other agencies are warranted at different levels. Student smokers could benefit from professional counseling and motivational interviews as well as pharmacological interventions.

It is clear that the National Defense Department wants to maintain optimal military readiness, Smoking cessation is one of the most cost-effective methods of achieving this.

Implications for Future Research

To explore interrelationships between variables as there are many other factors that affect smoking behaviors. This baseline dataset can be a benchmark for National Defense tobacco control administrators planning the next steps for a longitudinal follow-up.

Thank You for Your Attention!!! Questions and Comments