Purpose: The purpose of this study was to verify the effectiveness of the model based on the TPB, behavior-related theories, and exercise-related empirical studies in predicting exercise intention and behavior. Methods: The subjects who participated in this study were 152 middle-aged women. The data were analyzed by use of SAS PC program and LISREL 8.12a program. Results: 1) The overall fit of the hypothetical model to the data was acceptable ($\chi^2$ 24.01(p=0.0043), $\chi^2/df$ 2.67, RMSEA 0.11, standardized RMR 0.04, GFI 0.97, AGFI 0.84, NFI 0.95, NNFI 0.85). 2) Affect, subjective norm, perceived behavioral control and habit were significant determinants of the exercise intention. Attitude and facilitating conditions were not significant determinants. These six variables explained 43% of the total variance of the exercise intention. 3) Perceived behavioral control and habit were significant determinants of the exercise behavior. Intention and facilitating conditions were not significant determinants. These four variables explained 95% of the total variance of the exercise behavior. Conclusion: This study shows the model's applicabiltiy in explaining exercise behavior of middle-aged women, and suggests that we should focus on perceived behavioral control and habit rather than intention to improve exercise behavior of middle-aged women.
The purposes of this study were 1) to identify determinants of exercise behavior 2) to determine theoretical frameworks that were used in other research 3) to investigate the limitations of exercise research. seventy six research papers, published between 1984-1999, were selected by searching Medline for this study. Research subjects, determinants of exercise behavior, exercise measurement, the design of studies, statistical method and theoretical background were examined. The results are as follows. 1. On the research subjects, most research papers studied healthy adults. 2. Thirteen variables were identified that were used more than 5 times in various researches were self efficacy, barrier, social support, benefit, physiological characteristics, habit, personality, intention, health status, motivation, subjective norm, attitude, and affect. The most frequently supported determinant was self efficacy, the second one was social support, the third was affect and so on. But few research papers found any significant relationship between subject norms or attitude and exercise. 3. On exercise measurement, only 22.4% of research papers considered intensity, duration, frequency as elements of exercise, and 64.5% of researches were assessed by self-reported questionnaires. 4. In research design, 80.3% of research papers were survey type research. The most frequently used statistcal method was Regression. 5. 44.8% of research papers were done without any theoretical basis. Based on the above findings the following suggestions are made : 1. Research which includes diverse populations with different levels of health status needs to be studied. 2. Determinants of exercise may be dynamic and varing in their influence, therefore, stages of exercise behavior and processes of change need to be studied. 3. In research design, more prospective, longitudinal studies are needed to identify determinants of exercise habits. 4. It is necessary to develop a reliable, valid exercise measurement tool. 5. Studies are needed to develop a theoretical framework for exercise behavior.
The objectives of this study were to verify the effectiveness of the Theory of Planned Behavior in predicting exercise intention and exercise behavior, and to examine the determinants of exercise intention and exercise behavior in the sample of middle-aged women. The subjects who participated in this study were 263 middle-aged women. The instruments used for this study was a survey of general characteristics, attitude (18 items), subjective norm (2 items), perceived behavioral control (19 items), intention (3 items), and exercise behavior (7 items and 23 items for each). Analysis of data was done by use of descriptive statistics and correlation analysis with SAS PC program. The hypothetical model based on the Theory of Planned Behavior was tested by use of LISREL 8.12a program. The results of this study were as follows. 1) The overall fit of the hypothetical model to the data was good(chi-square=11.76, p=0.03, RMSEA=0.07, standardized RMR= 0.03, GFI=0.99, AGFI=0.94, NFI=0.97, NNFI=0.95). 2) Perceived behavioral control, attitude, and subjective norm were significant determinants of exercise intention, and these variables explained 35% of the total variance of exercise intention. 3) Perceived behavioral control, intention, and attitude were significant determinants of exercise behavior. But, subjective norm was not a significant determinants. These four variables explained 69% of the total variance of exercise behavior. In conclusion, this study shows the applicability of the Theory of Planned Behavior in explaining exercise behavior of middle-aged women, and suggests that health care providers should focus on perceived behavioral control and attitude rather than subjective norm to improve exercise behavior of middle-aged women.
Purpose: A dance exercise program was performed to investigate the effects of exercise on exercise intention and exercise-related affect as these are important determinants of exercise behavior. Method: The subjects were overweight (23$\leq$BMI<25) or obese (BMI$\geq$25) postmenopausal women (n=14), who participated in an exercise program from May, 2003 through November, 2003 at one public health center located in Kyong-gi Province. Data was analyzed with an SAS PC program. Result: Exercise intention was significantly increased after the exercise program (t=-2.24, P=0.04). Exercise-related affect was also increased, but there was no statistically significant change (t=1.81, P=0.09). Conclusion: This study suggests that exercise participation can increase the level of future exercise behavior by increasing exercise intention and exercise-related affect.
The objectives of this study were to verify the determinants of regular exercise behavior in female workers by applying a modified Theory of Planned Behavior. The variables investigated for this study were health status, health concern, health habit, attitude (7 items), subjective norm (3 items), and perceived behavioral control(5 items). Data was collected from 204 female workers using a self-administered questionnaire. The results of this study were as follows. 1) Regular exercise behavior was significantly influenced by perceived behavior control for time, pleasurable attitude, and the subjective norm of their colleagues. 2) A modified Theory of Planned Behavior is particularly useful in explaining exercise behavior of female workers. We suggest that health care providers should focus on not only attitude and social norms but also perceived behavioral control in order to improve the exercise behavior of female workers.
본 연구는 고령자들의 운동지속 행동에 영향을 미치는 사회심리적 결정요인들을 분석하는데 목적을 두었다. 계획된 행동이론을 바탕으로 본 연구는 고령자들의 건강에 대한 위험지각, 역경의 상황에서도 운동을 실천할 수 있다는 믿음(자기효능감), 운동결과에 대한 기대와 평가(태도), 운동에 대한 주위 사람들의 의사를 따르려는 생각(집단동조)과 같은 사회인지적 요인들이 고령자들의 운동지속 행동(의도성, 실행력, 지속성)에 영향을 미치는 결정요인이라고 예상했다. 연구 대상자들은 서울시에 위치한 노인복지관과 노인대학 등에서 선정된 65세 이상의 남녀 노인 453명(남: 171명, 여: 282명)이었다. 이들의 사회인지적 요인들과 운동지속 행동 요인들은 일련의 질문지를 사용하여 측정됐다. 위계적 중다회귀분석 결과는 본 연구에서 제안된 사회인지적 요인들(자기효능감, 운동태도, 집단동조, 건강위험지각)이 운동의도에 영향을 미치는 결정요인이라는 사실을 제시해 주고 있다. 그러나 운동의도에 대한 집단동조와 건강위험지각의 예측력은 매우 미약하게 나타났다. 또한 운동의도는 초기 운동실행의 가장 강력한 결정요인으로 나타났으며, 초기 운동실행은 지속적인 운동행동을 가장 강력하게 예측해 주었다. 이러한 결과들은 고령자 운동지속 행동에 영향을 미치는 사회심리적 결정요인들이 시간의 경과에 따라 역동적으로 변화할 수 있다는 가능성을 시사해 주고 있다.
The purpose of this study was to explain the relationship between health promoting behavior and self-esteem, and the relationship between health promoting behavior and self-efficacy. The instrument of this study was a structured questionnaire included health promoting lifestyle, self-esteem and self-efficacy. The data were collected from August 24 to September 3, 1999 and analyzed by Cronbach alpha, descriptive statistics, t-test, ANOVA, Scheffe's test, Pearson's correlation coefficient and stepwise multiple regression by using SPSS/PC+ program. The results of research were as follows : 1. The average score of performance in the health promoting behavior variables was 2.61. The variable with the highest degree of performance was the sanitary life(3.14), whereas the one with the lowest degree was the professional health maintenance(1.50). The average score of self-esteem was 2.89, and self-efficacy was 6.60. 2. There was significant difference according to the demographic variables. The total health promoting behavior was predicted by age, religion, monthly income. personality, perceived health status and frequency of exercise. Self-esteem was predicted by religion, monthly income and personality. Self-efficacy was predicted by age, religion and personality. 3. There was a significant correlation between health promoting behavior and self-esteem, self-efficacy. 4. Self-efficacy was the highest factor (variable) predicting health promoting behavior. A total of 44.7% of the variance was explained in the total health promoting behavior by the self-efficacy, frequency of exercise, self-esteem, perceived health status and personality. In conclusion, this study revealed that self-efficacy, self-esteem may be important factors that can improve health promoting behavior. Therefore the findings of this study may provide significant basic data for health promoting program development.
The purpose of this study was to identify the major factors affecting performance in health promoting behavior. The subjects for this study were 414 workers employed in one transportation manufacturing plant in Pusan and were obtained by a convenience sample. Data were collected from November 11th to December 21th, 1996 by structured questionnaires. Collected data were analyzed by SPSS PC. The results of this study are as follows. 1. The average score of performance in the health promoting behavior was 2.42 ; the range of the score was from 1.44 to 3.71. The variable with the highest degree of performance was self-actualization, whereas the one with the lowest degree was exercise. 2. In the relationships between demographic variables and performance in the health promoting behavior, only the shift system showed statistically significant differences in the total of health promoting behavior ; especially the group of no shift operation was higher in the performance of subscale such as exercise, nutrition, interpersonal support than that of the shift operation. Some demographic variables showed significant differences in the subscale of the health promoting behavior ; age, worker's career and marital status. 3. Performance in the health promoting behavior was significantly correlated with perceived health status, health conception, self-efficacy, perceived benefits and perceived barriers. 4. The most important factor that affects performance in the health promoting behavior was self-efficacy. The combination of self-efficacy, perceived benefits, perceived health status, perceived barriers, shift system and department of work accounted for 31.05% of the variance in health promoting behavior.
Background: In this study we investigated factors influencing cancer screening intention and behavior to develop measures to increase the rate of cancer screening in the Korean elderly. Materials and Methods: Participants included 425 elderly subjects 65 years of age or older from D city, South Korea. The health behavior characteristics and cancer screening-related and theory of planned behavior (TPB) factors influencing the participant attitudes on cancer screening were examined to identify determinants significantly affecting cancer screening intentions and behavior. Results: Predictive factors influencing cancer screening behavior included smoking, exercise, cancer concerns, preference for the type of cancer screening, prior experience with the National Cancer Screening Program, perception of the National Cancer Screening Program, behavioral control with respect to cancer screening and cancer screening intentions. The factors influencing cancer screening behavior were different from those for cancer screening intentions. Conclusions: Increasing the cancer screening intentions of the elderly is necessary to raise the rates of cancer screening. Additionally, identifying the inhibitory factors that serve as obstacles to cancer screening in the elderly and changing screening intentions into actual screening behavior is necessary. This study provides a reference for developing and applying policy measures and intervention strategies to increase the cancer screening rates of the elderly in Korea.
Introduction. Despite the fact that half of premature deaths are caused by unhealthy lifestyles such as smoking tobacco, sedentary lifestyle, alcohol and drug abuse and poor nutrition, there are no theoretical models which accurately explain these health promotion related behaviors. This study tests a new model of health behavior called the Model of Health Promotion Behavior. This model draws on elements and frameworks suggested by the Health Belief Model, Social Cognitive Theory, the Theory of Planned Action and the Health Promotion Model. This model is intended as a general model of behavior but this first test of the model uses amount of exercise as the outcome behavior. Design. This study utilized a cross sectional mail-out, mail-back survey design to determine the elements within the model that best explained intentions to exercise and those that best explained amount of exercise. A follow-up questionnaire was mailed to all respondents to the first questionnaire about 10 months after the initial survey. A pretest was conducted to refine the questionnaire and a pilot study to test the protocols and assumptions used to calculate the required sample size. Sample. The sample was drawn from 2000 eligible participants at two blue collar (utility company and part of a hospital) and two white collar (bank and pharmaceutical) companies located in Southeastern Michigan. Both white collar site had employee fitness centers and all four sites offered health promotion programs. In the first survey, 982 responses were received (49.1%) after two mailings to non-respondents and one additional mailing to secure answers to missing data, with 845 usable cases for the analyzing current intentions and 918 usable cases for the explaining of amount of current exercise analysis. In the follow-up survey, questionnaires were mailed to the 982 employees who responded to the initial survey. After one follow-up mailing to non-respondents, and one mailing to secure answers to missing data, 697 (71.0%) responses were received, with 627 (63.8%) usable cases to predict intentions and 673 (68.5%) usable cases to predict amount of exercise. Measures. The questionnaire in the initial survey had 15 scales and 134 items; these scales measured each of the variables in the model. Thirteen of the scales were drawn from the literature, all had Cronbach's alpha scores above .74 and all but three had scores above .80. The questionnaire in the second mailing had only 10 items, and measured only outcome variables. Analysis. The analysis included calculation of scale scores, Cronbach's alpha, zero order correlations, and factor analysis, ordinary least square analysis, hierarchical tests of interaction terms and path analysis, and comparisons of results based on a random split of the data and splits based on gender and employer site. The power of the regression analysis was .99 at the .01 significance level for the model as a whole. Results. Self efficacy and Non-Health Benefits emerged as the most powerful predictors of Intentions to exercise, together explaining approximately 19% of the variance in future Intentions. Intentions, and the interaction of Intentions with Barriers, with Support of Friends, and with Self Efficacy were the most consistent predictors of amount of future exercise, together explaining 38% of the variance. With the inclusion of Prior Exercise History the model explained 52% of the variance in amount of exercise 10 months later. There were very few differences in the variables that emerged as important predictors of intentions or exercise in the different employer sites or between males and females. Discussion. This new model is viable in predicting intentions to exercise and amount of exercise, both in absolute terms and when compared to existing models.
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