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J Korean Acad Psychiatr Ment Health Nurs > Volume 33(2); 2024 > Article
Park and Kweon: Mediating Effect of Autonomy Support between Exercise Knowledge and Exercise Self-Efficacy of Patients with Severe Mental Illness

Abstract

Purpose

This study aimed to explore how autonomy support mediates the association between exercise knowledge and exercise self-efficacy in patients with severe mental illness.

Methods

A total of 181 individuals were selected through convenience sampling. They completed self-administered surveys measuring exercise knowledge, autonomy support, and exercise self-efficacy. The data analysis was conducted using descriptive statistics, t-tests, one-way analysis of variance, Pearson’s correlation coefficients, and multiple linear regression. To determine the statistical significance of the mediating effect, a bootstrapping test was also conducted.

Results

This research revealed that autonomy support significantly predicted exercise self-efficacy and partially mediated the association between exercise knowledge and exercise self-efficacy (lower limit confidence interval [LLCI]: 2.34; upper limit confidence interval [ULCI]: 5.97). The model incorporating exercise knowledge and autonomy support explained 42.0% of the variance in exercise self-efficacy.

Conclusion

Collaborative endeavors involving mental health practitioners and exercise experts demonstrate notable efficacy in enhancing exercise self-efficacy of individuals with mental illness.

INTRODUCTION

Patients with severe mental illness (SMI) face a significantly reduced life expectancy, shortened by approximately 10~20 years compared to the broader population [1], with cardiovascular diseases as the predominant cause of elevated mortality rates [2]. Contributing factors include lifestyle elements such as inadequate exercise and poor diet, which double the risk of cardiovascular conditions relative to the general population [3]. Moreover, the frequent occurrence of obesity among SMI patients, often exacerbated by metabolic side effects of antipsychotic medications like dyslipidemia, hyperglycemia, and weight gain, further complicates their health scenario [4].
In South Korea, patients with SMI face significant barriers in managing their physical health, resulting in a mortality rate 1.16 times higher than that of the general population, primarily due to cardiovascular issues [5]. A critical gap in the integration between physical health and mental health care services, exacerbated by social stigma, severely limits their participation in physical health activities, thus worsening their risk of adverse health outcomes [6,7].
To address these risks, it is crucial for SMI patients to adopt healthier lifestyle habits, with a particular emphasis on regular exercise to help reduce obesity. The presence of obesity among SMI patients not only leads to a negative body image and decreased medication adherence but also heightens the likelihood of disease relapse [1]. Research indicates that achieving a modest weight loss of 5~10% can yield significant improvements in key health parameters such as cholesterol levels, glucose regulation, and blood pressure [8].
However, acquiring knowledge about the benefits of exercise presents substantial challenges for these patients due to several factors. Healthcare system fragmentation, socioeconomic disadvantages, stigma, cognitive and motivational barriers, and a lack of exercise programs tailored to their needs impede effective patient education and engagement in physical activities [9]. Consequently, these obstacles present significant challenges within the field of mental health nursing, hindering efforts to improve patient outcomes through exercise.
Recognizing the critical role of knowledge in shaping behavior, as posited by social cognitive theory, is essential for addressing these challenges [10]. Knowledge influences beliefs and attitudes and facilitates the formation of complex behavioral patterns, including exercise habits [11]. Knowledge and self-efficacy are pivotal in shaping the behaviors of individuals with SMI, impacting how they manage their health through exercise [10,11].
According to a comprehensive review of the literature on exercise in SMI patients, there is a noticeable gap between exercise self-efficacy and actual exercise behavior [12]. This discrepancy is often linked to a lack of motivation among SMI patients [13]. Therefore, exercise self-efficacy is a crucial mechanism that converts exercise motivation into concrete actions. Enhancing exercise self-efficacy in SMI patients can be effectively achieved through autonomy support, which involves aiding in exercise planning, time management, and monitoring exercise outcomes [14]. Previous research has shown that autonomy support greatly enhances exercise self-efficacy by providing the essential tools and motivation needed to engage in regular exercise [15].
Therefore, the main objective was to investigate the mediating role of autonomy support from mental health professionals in the association between exercise knowledge and exercise self-efficacy among SMI patients. This investigation aims to facilitate consistent and regular exercise among SMI patients as a preventive measure against obesity, with outcomes that could serve as a foundation for developing programs encouraging mental health professionals to actively promote exercise among SMI patients facing obesity challenges.

METHODS

1. Study Design

This study used a descriptive, cross-sectional design with a self-administered survey. The main objective was to investigate the mediating role of autonomy support in the association between exercise knowledge and exercise self-efficacy among individuals with SMI.

2. Participants

Participants were meticulously chosen according to specific criteria to ensure that those involved in the research comprehended the study’s objectives. Each participant was aged 18 or older and had been diagnosed with mental disorders such as schizophrenia, bipolar disorder, or major depressive disorder in accordance with DSM-5 criteria. Additionally, all participants were required to be in a stable condition with no severe residual symptoms, ensuring their capability to communicate effectively. These individuals had been engaged in psychiatric rehabilitation for a minimum of three years. This duration was chosen to ensure that participants had sufficient experience with mental health interventions, which could provide more reliable and informed responses regarding the long-term effects of their treatments [16]. Furthermore, to protect participant well-being, measures were put in place to monitor emotional and mental state before, during, and after the survey administration. Participants were informed that they could withdraw from the study at any time without facing any repercussions. Mental health professionals were also available during the survey process to provide immediate support if any distress or adverse reactions arose as a result of the survey content.
To determine the appropriate sample size, the G*Power program was utilized for regression analysis, with a significance level (⍺) of .05, a power (1-β) of .90, an effect size of 0.15 (medium), and 13 predictor variables. The required sample size was computed to be 162. To account for a 20% dropout rate, 195 surveys were distributed in total. After excluding five participants with insufficient responses and nine participants with missing item responses, the final analysis was conducted based on a sample of 181 participants.

3. Procedure for Data Collection

All procedures of the study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. This study was conducted after obtaining approval from the directors of psychiatric hospitals, mental health welfare centers, and psychosocial rehabilitation facilities located in G City, South Korea. The period for data collection was from May 10th to June 12th, 2021. Due to the ongoing COVID-19 pandemic, special considerations were made to ensure the safety of both the participants and the research team. This included adhering to local health guidelines, such as social distancing and the use of personal protective equipment (such as personal mask and gloves). Access to some facilities was restricted; however, arrangements were made to collect data under stringent safety protocols. The researcher visited each institution directly, providing an explanation of the study’s purpose and content to the treating physician, head of the nursing department, and head nurse in the ward, and requested their cooperation. The surveys were administered by placing the research protocol, informed consent forms, and survey questionnaires into individual envelopes, which were then delivered to the respective department heads or team leaders within the organization. On the designated survey administration date, trained researchers distributed the questionnaires to the participants. The process ensured minimal contact and adhered to the recommended health and safety measures. The research explanation letter detailed the study’s purpose and methods, introduced the researcher, and informed participants that they could withdraw at any time without affecting their treatment. In accordance with Institutional Review Board recommendations to protect participants, all collected data was securely maintained for three years to ensure confidentiality and privacy. The data was used exclusively for this study and maintained anonymously by assigning individual numbers. Upon completing the questionnaire, participants received a 5,000 Korean Won convenience store coupon as compensation.

4. Survey Instruments

Prior to using the study instruments, we secured permission via email from both the original author and the translator. Three self-reported instruments (Exercise Knowledge, Autonomy Support, and Exercise Self-Efficacy) were used to gather the data.
The Exercise Knowledge questionnaire was developed by Lilly Pharmaceutical Company and translated into the Korean version by Lilly Korea [17]. The validity of this tool was confirmed by Ko et al. [18] This questionnaire comprised 8 items, each measured on a true or false scoring scale (0 “false” or 1 “true”). The total scores ranged from 0 to 8, with higher scores indicating a higher level of exercise knowledge. The Kuder-Richardson Formula 20 value was .73 in this study.
The Autonomy Support questionnaire, initially developed by Williams et al. [19], assesses the extent of support provided by healthcare professionals. This tool, specifically designed for patients requiring exercise guidance, is known as the Important Other Climate Questionnaire (IOCQ). It has been adapted and validated for the Korean population by Seo et al. [20]. This questionnaire consisted of 6 items. Each item was assessed using a five-point Likert scale ranging from 1 (“not at all”) to 5 (“always”), with total scores ranging from 6 to 30. Higher scores indicate a higher level of autonomy support. The reliability in this study, Cronbach’s ⍺ was .87.
The Exercise Self-Efficacy questionnaire was originally developed by Bandura et al. [21] This questionnaire was translated and modified to fit the Korean population by Shin et al. [22] The scale consisted of a total of 18 items, each rated on a Likert scale ranging from 0 (“Absolutely cannot do”) to 10 (“Can definitely do”). The total scores ranged from 0 to 180, with higher scores reflecting higher levels of exercise self-efficacy. The reliability, as measured by Cronbach’s ⍺, was .92.

5. Data Analysis

The data analysis was conducted using the IBM SPSS Statistics 24.0 software (SPSS Inc., Chicago, IL, USA). The analysis proceeded through several steps. Firstly, frequency analysis was conducted to examine the demographic characteristics of the participants. Secondly, t-tests or one-way ANOVA were used to evaluate discrepancies in exercise self-efficacy across various demographic variables. Thirdly, descriptive statistics were used to determine the mean, standard deviation, skewness, and kurtosis of the research variables. Fourthly, the study utilized Pearson’s correlation coefficient analysis to investigate the association between the variables. Fifthly, the mediation analysis was utilized to examine whether autonomy support acted as a mediator between exercise knowledge and exercise self-efficacy, following the approach outlined by Baron and Kenny [23]. Lastly, bootstrapping was used with the PROCESS macro (developed by Andrew F. Hayes) to verify the significance of the mediating effect [24]. To determine the significance of the indirect effect, the bootstrapping process involved conducting 5,000 bootstrap iterations and estimating the bootstrap bias-corrected 95% confidence interval.

6. Ethical Considerations

This study obtained approval from the Institutional Review Board at St. John of God Hospital (IRB no. 2021-3) and adhered to the ethical standards set forth in the Declaration of Helsinki. this study has been registered under registration number KCT0008986 with the Clinical Research Information Service (CRiS) of the Republic of Korea. Access to the registration details is available at https://cris.nih.go.kr/cris/index/index.do (accessed on 28 November 2023). The informed consent process included a comprehensive introduction to the study, providing participants with a clear understanding of its objectives, the confidentiality measures in place, the assurance of anonymity, and the potential risks, discomforts, and benefits associated with their involvement. The study adhered to the ethical principles, ensuring the ethical conduct of all research methods employed.

RESULTS

1. Participant Demographics

In this research, the participant demographics are shown in Table 1. The subjects consisted of 52.5% males and 47.5% females. The mean age was 43.38±12.41 years, with the highest proportion of subjects aged 50~59 years (28.7%), followed by 40~49 years (28.2%), <30 years (17.7%), 30~39 years (15.5%), and ≥60 years (9.9%). SMI patients who were unmarried accounted for 74.0% of the subjects, and married and divorced patients accounted for 13.8% and 12.2% of the subjects, respectively. The majority of participants had either graduated from high school (45.3%) or held an undergraduate degree (42.0%), and a smaller percentage of subjects had completed middle school (12.7%). In addition, most of the participants lived with their family (64.6%), followed by alone (22.1%) and in a group home (13.3%). Based on BMI (body mass index) data, most of the participants were in the obesity stage (55.8%), followed by the normal stage (27.1%) and pre-obesity stage (17.1%). The mean age at first psychiatric diagnosis was 25.56±10.40 years. The data on psychiatric diagnosis showed that most of the participants had schizophrenia (69.6%), followed by major depressive disorder (15.5%), bipolar disorder (10.5%), and obsessive-compulsive disorder (4.4%). In this study, no statistically significant differences in the degree of exercise self-efficacy were found based on the participant demographics, at a significance level of .05.

2. Descriptive Statistics for Research Variables

In this research, the descriptive statistics are shown in Table 2. The average scores were as follows: 4.83 points for exercise knowledge, 21.01 points for autonomy support, and 74.14 points for exercise self-efficacy. All variables in this study demonstrated univariate normality, as none exceeded an absolute skewness of 3.00 or an absolute kurtosis of 10.00.

3. Correlations between Research Variables

In this research, the correlation between research variables are shown in Table 3. The participants’ exercise self-efficacy showed a significant correlation with research variables. The exercise self-efficacy was a positive correlation with exercise knowledge (r=.38, p<.01) and autonomy support (r=.63, p<.001). Furthermore, exercise knowledge was positively correlated with autonomy support (r=.38, p<.01).

4. Mediating Effects of Autonomy Support

The analysis of the mediating effect of autonomy support on the relationship between exercise knowledge and exercise self-efficacy in SMI patients is detailed in Table 4. In regression analysis, the Durbin-Watson statistic was close to the ideal value of 2. This indicates that the assumption of independence of residuals is met. Additionally, the variance inflation factor (VIF) was less than 10, confirming the absence of multicollinearity. To analyze the mediating effect, we employed a three-step method. In the first step, we examined the impact of exercise knowledge on exercise self-efficacy as the dependent variable, finding that exercise knowledge significantly influenced exercise self-efficacy (β=.38, p<.001). In the second step, we evaluated the impact of exercise knowledge on autonomy support as the mediator, confirming a significant impact of exercise knowledge on autonomy support (β=.38, p<.001). In the final step, we included autonomy support as an independent variable alongside exercise knowledge and analyzed their combined effect on exercise self-efficacy as the dependent variable. The analysis showed that exercise knowledge significantly impacted exercise self-efficacy (β=.17, p<.01), while autonomy support also had a notable effect on exercise self-efficacy (β=.56, p<.001). These findings indicate that autonomy support may partially mediate the association between exercise knowledge and exercise self-efficacy. Exercise knowledge alone accounted for 14.0% of the variance in exercise self-efficacy. When both exercise knowledge and autonomy support were included in the model, they explained 42.0% of the variance in exercise self-efficacy.
To verify the mediating effect, we employed bootstrapping with the PROCESS macro. The indirect, direct, and total effects of the mediating variable are presented in Table 5. A total of 5,000 bootstrap samples were re-extracted, and the indirect effect coefficient was analyzed with a 95.0% confidence interval. The results indicated that the indirect effect coefficient was 4.05, accounting for 42.0% of the total effect. The mediating effect test showed that the confidence interval for the effect of autonomy support on the association between exercise knowledge and exercise self-efficacy did not include zero, with a lower limit of 2.34 and an upper limit of 5.97. Thus, the mediating effect was statistically significant.

DISCUSSION

Given the higher prevalence of obesity among individuals with SMI, largely attributed to antipsychotic medication use and unhealthy lifestyle choices, this cross-sectional study was designed to explore the potential mediating role of autonomy support in the nexus between exercise knowledge and exercise self-efficacy in this population. The ensuing discussion is predicated on the empirical findings of our research.
First of all, despite the importance of exercise knowledge and self-efficacy for SMI, the results of this study show that both are below moderate levels, highlighting a significant gap in current interventions. According to social cognitive theory, knowledge profoundly influences individual decision-making processes and the formation of complex behavioral patterns [10,11]. Therefore, there is a pressing need for enhanced educational programs that provide comprehensive information on exercise and nutrition specifically tailored to address the unique challenges faced by SMI patients [25]. The findings also indicate that intrinsic motivation for exercise, or exercise self-efficacy, is similarly low [26]. This underscores the necessity for targeted strategies aimed at boosting this motivation to engage SMI patients effectively in physical activities. Educational interventions within psychosocial rehabilitation must include detailed information on the benefits, methods, and importance of exercise to improve patients’ ability to engage in and benefit from physical activities. Additionally, collaborations between mental health professionals and exercise specialists can make these educational efforts more practical and customized, thereby enhancing their effectiveness. Moreover, the study suggests that while cognitive-behavioral strategies are potentially effective at modifying behavior, they are not being applied effectively in interventions for the SMI population. This gap further reinforces the need for programs that are well-adapted to the specific needs of these patients, helping them understand and manage their conditions better. By providing actionable information and fostering a supportive environment through professional collaboration, these programs can promote sustained behavior change and significantly improve the mental and physical health outcomes for individuals with SMI.
Second, our study found a strong positive correlation among exercise knowledge, autonomy support, and exercise self-efficacy in SMI patients. This correlation supports previous findings that illustrate a significant association between exercise knowledge and self-efficacy across various patient groups, such as those with osteoarthritis, pregnancy, and ankylosing spondylitis [25-27]. Furthermore, our findings indicate that autonomy support positively correlates with both exercise knowledge and self-efficacy in SMI patients, suggesting that increased exercise knowledge enhances autonomy support, which in turn boosts self-efficacy. These findings emphasize the importance of autonomy support from healthcare providers in elevating exercise self-efficacy, a relationship that is supported by earlier studies showing that enhanced autonomy support positively influences the individual, thereby increasing exercise self-efficacy [28]. According to self-determination theory, effective autonomy support involves behaviors that encourage an individual’s initiative, offer choices, provide relevant information, and minimize pressure—factors crucial to fostering self-regulation behavior [29]. Williams et al. suggest that autonomy support should be tailored to the context, indicating that healthcare providers who are familiar with a patient’s specific symptoms and exercise capacity are more likely to offer effective support [18]. This necessitates collaborative efforts between mental health providers and exercise specialists to deliver well-informed and appropriately tailored autonomy support that meets the unique needs of SMI patients. Consequently, our findings suggest that interventions aimed at increasing exercise self-efficacy should not only focus on improving exercise knowledge but also on strengthening autonomy support. However, our study does not identify which types of healthcare providers are most effective at delivering this support. Future research should therefore explore the dynamics of how different providers implement autonomy support, considering the specific symptoms and exercise levels of SMI patients. Understanding these dynamics is essential for designing interventions that effectively utilize autonomy support to improve exercise outcomes for SMI patients. Such studies will be crucial in ensuring that each patient receives the most beneficial form of support to enhance their exercise outcomes and overall well-being.
Lastly, this study has demonstrated that exercise knowledge significantly influences exercise self-efficacy in SMI patients through the mediating role of autonomy support. We found that exercise knowledge directly affects exercise self-efficacy, while autonomy support serves as an important indirect enhancer. Specifically, exercise knowledge explained 14.2% of the variance in exercise self-efficacy, and when combined with autonomy support in our model, the explained variance increased to 42.0%. This finding underscores the complex interaction between knowledge and support in influencing SMI patients’ self-efficacy, highlighting the critical role of autonomy support in this relationship. Our results indicate that autonomy support not only enhances the impact of exercise knowledge on exercise self-efficacy but also has varying effectiveness based on the provider. Autonomy support, which includes behaviors that encourage patient initiative, provide relevant information, and offer choices, can significantly boost self-efficacy if it is contextually tailored. According to Yeom and Lee, autonomy support effectively increases the extent of self-efficacy, emphasizing the need for healthcare providers to be well-acquainted with the patient’s specific symptoms and exercise levels to deliver effective support [30]. However, our study identifies a gap in specifying which types of healthcare providers are most effective at providing this support, suggesting a need for further research to explore the dynamics between different providers and their capacity to implement autonomy support, considering the specific symptoms and exercise levels of SMI patients. Additionally, the variability in the effectiveness of autonomy support based on educational and socio-demographic backgrounds points to the necessity for more nuanced research. Future studies should examine how different socio-demographic and clinical characteristics of SMI patients affect the efficacy of autonomy support. This deeper understanding is crucial for designing interventions that effectively utilize autonomy support to improve exercise outcomes for SMI patients.
In summary, our findings highlight the importance of integrating autonomy support into therapeutic settings to bolster SMI patients’ confidence in their ability to engage in exercise. By enhancing exercise knowledge and strategically using autonomy support, we can significantly improve the physical health and overall well-being of SMI patients. Future study should focus on tailoring educational content and support mechanisms to the unique needs of SMI patients, ultimately enhancing their quality of life.
A limitation of this research is its cross-sectional design, which only allows for the identification of association between variables at a single point in time and does not establish causal relationships. To achieve a deeper understanding of the exercise self-efficacy of SMI patients, future research should utilize longitudinal designs. Additionally, this study focused solely on the effect of autonomy support on the relationships between exercise knowledge and exercise self-efficacy in SMI patients. Other factors, such as autonomous self-regulation, perceived exercise performance, and self-determination, may also have a significant impact. Future studies should consider including these additional factors when examining the exercise behaviors of SMI patients in a psychiatric mental health setting.

CONCLUSION

Compared to the general population, patients with SMI have a higher prevalence of obesity due to the use of antipsychotic drugs and unhealthy lifestyles. Through an examination of the interconnections between exercise knowledge, exercise self-efficacy, and autonomy support in SMI patients, as well as the mediating role of autonomy support in the association between exercise knowledge and self-efficacy, valuable insights have been gained for the development of strategies aimed at enhancing exercise self-efficacy in this population. Based on the results, it is recommended that mental health professionals and exercise specialists collaborate to provide autonomy support to SMI patients. This collaborative approach can significantly contribute to improving exercise self-efficacy and, consequently, promote better health outcomes for individuals with SMI. Furthermore, it is essential to pursue longitudinal research to understand the long-term effects of autonomy support on exercise self-efficacy, obesity rates, and overall health outcomes in individuals with SMI. Intervention programs should be developed to specifically target autonomy support in relation to exercise for SMI patients, promoting autonomy and self-determination in their exercise endeavors. Evaluating the effectiveness of these interventions in enhancing exercise self-efficacy, reducing obesity, and improving overall well-being is crucial for refining and customizing interventions to better serve the needs of SMI patients in their pursuit of improved health and well-being.

Acknowledgments

We extend their heartfelt appreciation to all the participants for their involvement and cooperation in this study.

CONFLICTS OF INTEREST

The authors declare that there are no conflicts of interest related to this study.

Notes

AUTHOR CONTRIBUTIONS
Conceptualization or/and Methodology: Park, J & Kweon, Y-R
Data curation or/and Analysis: Kweon, Y-R
Funding acquisition: Park, J
Investigation: Park, J & Kweon, Y-R
Project administration or/and Supervision: Kweon, Y-R
Resources or/and Software: Park, J & Kweon, Y-R
Validation: Park, J & Kweon, Y-R
Visualization: Park, J & Kweon, Y-R
Writing: original draft or/and review & editing: Park, J & Kweon, Y-R

Table 1.
Differences in Exercise Self-efficacy according to the Characteristics of Participants (N=181)
Characteristics Categories n (%) or M±SD M±SD t or F p
Gender Man 95 (52.5) 72.20±32.06 -0.91 .366
Woman 86 (47.5) 76.29±28.23
Age (year) < 30 32 (17.7) 72.18±34.99 0.79 .532
30~39 28 (15.5) 83.32±25.63
40~49 51 (28.2) 73.19±29.26
50~59 52 (28.7) 72.71±32.71
≥ 60 18 (9.9) 70.16±23.00
43.38±12.41
Education ≤ Middle school 23 (12.7) 65.26±33.39 2.01 .137
High school 82 (45.3) 72.40±32.33
≥ College 76 (42.0) 78.71±26.38
Marital status Married 25 (13.8) 77.20±32.47 0.23 .799
Unmarried 134 (74.0) 74.04±29.80
Divorced 22 (12.2) 71.27±31.80
Religion Christianity 70 (38.7) 73.00±31.57 0.76 .520
Catholicism 26 (14.4) 70.73±29.37
Buddhism 14 (7.7) 85.14±30.40
Others 71 (39.2) 74.35±29.42
Residence status Family 117 (64.6) 74.24±28.12 0.03 .971
Alone 40 (22.1) 73.27±35.36
Group home 24 (13.3) 75.12±32.66
Body mass index (BMI) Normal 49 (27.1) 72.55±31.61 0.49 .612
Pre-obesity 31 (17.1) 79.00±29.33
Obesity 101 (55.8) 73.42±25.32
Diagnosis Schizophrenia 126 (69.6) 73.00±31.57 0.76 .520
Major depression 28 (15.5) 70.73±29.37
Bipolar 19 (10.5) 85.14±30.40
OCD 8 (4.4) 74.35±29.42
Age at first psychiatric diagnosis (year) 25.56±10.40

F=ANOVA value; OCD=obsessive-compulsive disorder; M=mean; SD=standard deviation; t=t-test values

Table 2.
Descriptive Statistics of Research Variables (N=181)
Variables Min Max M±SD Skewness Kurtosis
Exercise knowledge 1.00 8.00 4.83±1.59 -0.07 -0.60
Autonomy support 6.00 30.00 21.01±4.68 -0.13 -0.03
Exercise self-efficacy 0.00 162.00 74.14±30.28 0.01 0.24

M=mean; Min=minimum; Max=maximum; SD=standard deviation.

Table 3.
Correlation between Research Variables (N=181)
Variables Exercise knowledge
Autonomy support
Exercise self-efficacy
r r r
Exercise knowledge 1.00
Autonomy support .38* 1.00
Exercise self-efficacy .38* .63** 1.00

r=Pearson’s correlation coefficient;

* p< .01,

** p<.001.

Table 4.
The Mediating Effect of Autonomy Support on the relationship between Exercise Knowledge and Exercise Self-efficacy (N=181)
Step Pathway B SE β t Adj. R2 F
1 Exercise knowledge → Exercise self-efficacy 7.27 1.31 .38 5.54** .14 30.73**
2 Exercise knowledge → Autonomy support 1.11 0.20 .38 5.48** .14 30.08**
3 Exercise knowledge → Exercise self-efficacy 3.22 1.18 .17 2.74* .42 63.62**
Autonomy support → Exercise self-efficacy 3.64 0.40 .56 9.08**

Adj. R2=adjusted R-squared; B=unstandardized regression coefficient; β=standardized regression coefficient; F=ANOVA values; SE=standard error; t= t-test values;

* p<.01,

** p<.001.

Table 5.
Verification of the Bootstrapping Mediation Effect (N=181)
Variables B SE Bootstrap 95% CI
Indirect effect 4.05 0.91 2.34~5.97
Direct effect 3.22 1.18 0.90~5.54
Total effect 7.27 1.31 4.68~9.86

B=unstandardized regression coefficient; CI=confidence interval; SE=standard error.

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