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Exploring the relationships of physical activity, emotional intelligence, and mental health among college students.

It is well documented that physical activity (PA) plays a significant role in improving an individual's physical fitness and quality of life. PA aids in an individual's ability for weight management and reduces the risk of morbidity and mortality from various diseases, such as cardiovascular diseases, diabetes, and high blood pressure (Sundblad, Jansson, Renstrom & Engstrom, 2008 instead of Sunblad, Jannson, Renstrom & Engstrom, 2008; Waxman, 2004). PA also has been shown to be associated with determinants of mental health, such as better stress management and a lower risk of depression (Harris, Cronkite, & Moos, 2006; Ruggeberg, Wrosch, & Miller, 2013). Despite these benefits, the World Health Organization (WHO) indicates that physical inactivity is the fourth leading cause for global mortality, contributing to more than 6% of deaths worldwide (WHO, 2009; Dishman et al., 2013). In addition, the WHO also suggests that, with the rising rates of physical inactivity among populations globally, increased risks for chronic diseases likely will follow (WHO, 2010).

The maintenance of adequate levels of physical activity is a critical issue among college students as they learn to cope with a new independent lifestyle. More than half of college students report a decrease in PA after high school graduation even though they generally have access to resources (i.e., equipment and exercise facilities), are well informed about PA, and have a supportive social network (Buckworth & Nigg, 2004; Calfas, Sallis, Lovato, & Campbell, 1994). The decrease in PA is mainly attributed to their newly independent adult life away from their parents, coupled with their demanding work-study schedule. The American College of Sports Medicine (ACSM) recommends individuals participate in 30 minutes of moderate physical activity for 5 or more days per week or 20 minutes of vigorous PA for 3 days or more per week. Moderate PA refers to exercises that are low intensity, such as walking, and do not cause heavy breathing or sweating. Vigorous physical activity refers to exercises that are high intensity, such as running, and cause heavy breathing and sweating (ACHA, 2013). According to the American College Health Association (ACHA), only 48.8% of college students meet this recommendation, and concurrently 34% of American college students have been reported as overweight or obese (ACHA, 2013). In addition among college students, there is a tendency to practice unhealthy weight control habits through compromising food intake by skipping meals, and/or consuming less nutritious/low calorie diets (Megel, Wade, Hawkins, & Norton, 1994).

If not intervened early, these two trends among college students (inadequate physical activity and unhealthy dieting behaviors) have the potential to lead to numerous long-term health problems. Various interventions have been implemented in the past to promote physical activity and its benefits. Efforts by health professionals range from well-established, theory-based interventions to newly-developed, technology-based educational interventions that use social networks and web-based applications (Patrick & Canevello, 2011).

Despite these efforts, additional work is needed to find more effective approaches as most interventions promoting PA in the college and university settings have had limited or moderate success (Keating, Guan, Pinero & Bridges, 2005). This suggests a need for additional research that explores ways to provide a positive influence on physical activity behavior among college students.

Whereas emotions are an essential part of human nature and a motivating factor for most human behavior (Li et al., 2009), only a few studies have evaluated the association between emotional health and physical health. Over the past 25 years, psychoneuroimmunology (PNI), the study of the interactions among immune process, neural and endocrine functions, and behavior, has shed light on the relationship between physical diseases and emotional factors (Ader, 2001). For example, a 13-year prospective study concluded that individuals with major depression had a 4.5 times higher risk of a cardiovascular disease compared with those with no history of depression (Pratt et al., 1996). The concept of Emotional Intelligence (EI) has been developed as a way to evaluate an individual's emotional health and ability. Emotional Intelligence is defined as the ability to identify various forms of emotion, incorporate emotion into the thinking process, and use this ability to manage personal growth (Mayer, Salovey, Caruso, & Sitarenious, 2001). According to Mayer and Salovey's Four Branch Model, EI is described, measured, and tested as an individual's abilities for perceiving emotions (e.g., perceiving non-verbal language of others), utilizing emotions (e.g., positive mood helping in solving problems), regulating emotions (e.g., controlling emotions), and managing emotions (e.g., sharing emotions with other) (Mayer et al., 2001). Whereas previous studies have reported a high degree of association between EI and determinants of mental health (Davis & Humphrey, 2012; Ruiz-Aranda, Castillo, Salguero, Cabello, Fernandez-Berrocal, & Balluerka, 2012), there are few studies documenting the association between EI and determinants of physical health, such as physical activity. Therefore, the primary purpose of this study was to evaluate the predictive nature of EI on physical activity behavior among college students. In addition, mental health status was evaluated, to explore the relatedness of the two concepts, with regards to physical activity. Specifically, study hypotheses included: H1: The four constructs of EI (perceiving emotions, utilizing emotions, regulating emotions, and managing emotions) will independently and significantly predict PA among college students; H2: Global EI (a summative score of perceiving emotions, utilizing emotions, regulating emotions, and managing emotions) will significantly predict PA among college students; H3: Global EI and overall mental health will independently and significantly predict PA among college students.


Research Design and Study Sample

This study utilized a cross-sectional research design. A convenience sample of 438 college students (female=335, male=103), 1830 years of age, and attending the University of Oklahoma participated in this study. For recruitment, a mass email was sent to 20,100 undergraduate students requesting them to participate in an online survey that contained the Schutte Self-Report Emotional Intelligence Test (SSEIT), the International Physical Activity Questionnaire (IPAQ) long form, the Kessler Psychological Distress Scale K6, and a demographic questionnaire. Details of all three instruments and their respective reliability and validity statistics are provided in the following section. Institutional Review Board (IRB) approval was obtained from the University of Oklahoma before data were collected (IRB#3752).

Instrumentation/Measurement Protocols

Schutte Self-Report Emotional Intelligence Test (SSEIT). Emotional Intelligence was evaluated by the SSEIT, which consists of 33 items, each of which is measured on a five-level Likert scale with "1" representing "strongly agree," and "5" representing "strongly disagree." The SSEIT has been deemed both a valid and reliable scale [(Cronbach's M = 0.90) (Schutte et al., 1998); (test-retest reliability of 0.78) (Schutte et al., 1998); (reliability of M = .93) (Brackett & Mayer, 2003)]. This instrument provided a global measure of EI and can be scaled additionally into four sub-scores based on the four modalities of EI: perceiving emotions, utilizing emotions, regulating emotions, and managing emotions. The perceiving emotions scale contained 10 items, with scores ranging from 10 to 50; and an example item included 'I am aware of nonverbal messages I send to others.' The utilizing emotions scale contained 6 items, with scores ranging from 6 to 30; and an example item included 'Emotions are some of things that make my life worth living.' The regulating emotions scale contained 9 items, with scores ranging from 9 to 45; and an example item included 'when I experience a positive emotion, I know how to make it last.' Finally, the managing emotions scale contained 8 items, with scores ranging from 8 to 40; and an example item included 'I present myself in a way that makes a good impression on others.' The global measure of EI was computed by summating the four sub-scores of EI, and had a possible range of 33 to 165 with higher scores indicating an overall higher level of EI.

International Physical Activity Questionnaires (IPAQ). Physical activity was evaluated using the long-form IPAQ Self-administered Questionnaire. The IPAQ is available in more than 18 languages and is widely used in multiple countries to assess self-reported PA (Craig et al., 2003). The long-form IPAQ evaluates PA in 4 domains. Part one (Items 1-7) evaluated job-related physical activities. Part two (Items 8-13) evaluated PA for transportation purposes. Part three (Items 14-19) evaluated PA related to home maintenance or while enjoying family time. Part four (Items 20-25) evaluated PA for recreation and sport purposes. Data for each activity obtained from participants was converted to units of energy utilized (MET-minutes/week) as outlined in the manual Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ). For the purpose of analysis, participants were categorized into three groups based on reported MET-minutes/week: (1) High PA group: more than 1500 MET-minutes/week; (2) Moderate PA group: more than 600 but less than 1500 MET-minutes/week, and; (3) Low PA group: less than 600 MET-minutes/week.

Kessler Psychological Distress Scale K6. The Kessler Psychological Distress Scale K6 was developed to assess incidence of serious mental illness (SMI) (Kessler, 2003). This scale is included in national health tracking surveys such as CDC surveillance systems, and the SAMHSA National Household Survey on Drug Use and Health, and as a result, nearly 500,000 people complete this survey each year (Kessler et al., 2010). This instrument is considered to be valid [mean = 5.3 [+ or -] 3.8], (p = 0.0008)] and reliable (Cronbach's M = 0.78) (Baggaley et al., 2007). This scale contained 6 items assessing how an individual felt during the past 30 days (nervous, hopeless, restless or fidgety, sad or depressed, that everything was an effort, and no good or worthless), measured in a five-level Likert scale with "1" representing "all of the time," and "5" representing "none of the time." Scores ranged from 6 to 30, with lower scores indicating higher risk for SMI. In addition to the preceding scales, demographic information, such as age, sex, ethnicity, class rank, and approximate Grade Point Average (GPA) score on a 4.0 scale, was collected.

Data Collection and Analysis

All survey materials were programmed into an online service (Qualtrics), for which the Web link was sent out on a listserv of all undergraduate students attending the University of Oklahoma. Students were informed that no personal data would be collected to ensure confidentiality. Given the nature of this study (an online survey collecting non-sensitive information, with no identifying information) it was reviewed by the sponsoring university and declared 'Exempt' from requiring informed consent from participants; however, participants were asked to read an information sheet outlining the study purpose, study design, measurement procedures, length of participation, expected risks and benefits, voluntary nature of the study, confidentiality of collected information, and contact information for the researcher before starting the survey. A survey link was sent to 20,100 students, of which 471 (2.34%) students participated. Of the remaining 471 responses 33 were discarded due to incomplete surveys. All data were analyzed using SPSS version 19.0. Two separate methods of data analysis were conducted for this study. A one-way ANOVA was used to determine the mean difference in EI scores and mental health scores among participants in different levels of PA (High, Moderate and Low). Second, three regression models were conducted to test each hypothesis. The level of significance was set at 0.05 for all statistical analyses.


A majority of participants were female (335, 76.5%), and white (329, 75.1%). The average age of participants was 20.1 years ([+ or -] 2.388), and the class rank was mixed with freshmen (n = 151; 34.5), sophomore (n = 100; 22.8%), juniors (n = 92, 21%), and seniors (n = 84, 19.2%). Descriptive statistics for study variables are presented in Table 1. In this study, the mean score of Global EI was 102.94 (SD=12.63), whereas perceiving emotions reported a mean of 25.25 [+ or -] 4.21, utilizing emotions reported a mean of 18.54 [+ or -] 2.79, regulating emotions reported a mean of 29.76 [+ or -] 4.58, and managing emotions reported a mean of 29.38 [+ or -] 4.47. Of the 438 participants, 19.2% were categorized into High PA group (n = 84), 37.6% into the Moderate PA group (n = 165), and 43.2% into the Low PA group (n = 189). The total MET-minutes/ week reported a mean of 912.29 [+ or -] 758.23. For total mental health, mean scores were reported as 19.88 [+ or -] 3.11.

Cronbach's alpha was calculated to evaluate the internal consistency reliability for each scale, and a value of 0.70 or above was considered acceptable. All constructs of the SSEIT, with the exception of utilizing emotions met this criterion; however, the score was close (alpha = 0.68) to cut off value; therefore, no changes were made to the scale. Similarly, the Kessler Psychological Distress Scale K6 reported a Cronbach's alpha of 0.825.

The univariate F ratios (one-way ANOVA) comparing the three PA groups with regard to Global EI and four constructs of EI (perceiving emotions, utilizing emotions, regulating emotions, and managing emotions), and mental health are presented in Table 2. There was significant differences (p < 0.05) in the three PA groups for the regulating emotions, Global EI, mental health, and Total MET-minutes/week, but there were no significant differences in the other three variables of EI (perceiving emotions, utilizing emotions, and managing emotions). Post hoc tests were also conducted using the Least Significant Difference (LSD) test to determine which groups were different from one another. The mean subscale scores for regulating emotions, Global EI, and mental health of the High PA group were significantly higher (p < 0.05) than the Low PA group, but no other pairwise differences were found (Table 2).

Basic assumptions were tested for the multiple linear regression analysis. The histogram of the regression standardized scores formed a normal curve therefore the assumptions of linearity and homogeneity of variance for multiple regression were met. Also, the validity and reliability of instruments were established before regression 0.065. The adjusted [R.sup.2] indicates that only 1% of the variability in the dependent variable of the Total MET-minutes/week was predicted by the four independent variables in the regression model. None of the predictors were found to be independently significant.

Relationship of Global Emotional Intelligence subscales to Physical Activity and the Addition of Mental Health to Global Emotional Intelligence towards Physical Activity

Two models of regression were performed with the dependent variable, Total MET-minutes/week, in order to explore the relationship between Global EI (Model 1), and Global EI, when mental health is added (Model 2). For Model 1, the R value for regression was significantly different than zero F(1,431) = 8.204, p = 0.004 with [R.sub.2] of 0.019 (0.016 adjusted) and 95% confidence interval ranging from 0.004 to 0.021. The adjusted [R.sup.2] indicates that only analyses were conducted. Correlations were conducted between all variables to explore whether any of the constructs of EI was correlated with each other. Pearson correlation ranged from 0.346 to 0.555 and all correlations were found to be statistically significant (p < 0.05).

Relationship of Emotional Intelligence Subscales to Physical Activity

Simultaneous multiple regressions were performed with the dependent variable, as total MET-minutes/week and the independent variables perceiving emotions, utilizing emotions, regulating emotions, and managing emotions (Table 3). The R value for regression was not significantly different than zero F(4,428)=2.060, p = 0.0785 with [R.sup.2] of .019 (.010 adjusted) and 95% confidence interval ranging from -0.030 to 1.6% of the variability in the dependent variable, Total MET-minutes/week was predicted by Global EI. In this case, Global EI was found to be a significant predictor of Total-MET-minutes/ week (p = 0.004). The unstandardized coefficient for Global EI was 0.013, which indicates that for each 1-unit increase in the value of Global EI, the value of Total MET-minutes/week will increase by 0.013. For Model 2, a hierarchical regression model was conducted to determine whether mental health status could mediate the relationship between Global EI and Total MET-minutes/week. Results indicated that by adding mental health status, the amount of variance of total MET-minutes/week significantly increased from 1.6% to 2.9% (p = 0.011); however, the relative importance of EI changed. Whereas in the first model EI was a significant predictor of Total MET-minutes/week (p = 0.004), in the second model Global EI was no longer significant (p = 0.080) and mental health status was statistically significant (p = 0.011).


Emotions are integral part of being human. Popular media have even claimed that EI can be more important than IQ for predicting success in various areas of life (Goleman, 1995). Studies have reported that emotions provide the principal currency as the motivational force leading toward our best or worst behaviors (Dolan, 1992). The result of this study supports the importance of EI and mental health in predicting PA among college students. The reported parameters estimates suggested moderate predictability factor of Global EI and mental health in predicting PA among college students. This finding is in line with those of Li et al. (2009) and Omar et al. (2012). Li et al. (2009) suggested that PA was the best predictor for EI when compared to mental health, gender, general mood, and general health. Similarly, a study by Omar et al. (2012) found significant differences (p < 0.05) in three PA groups of males for the subscales of regulating and utilizing emotion. Both of these studies suggested that a relationship between EI and PA exists; PA was found to be a significant predictor for EI. Also, individuals who are emotionally healthy are theoretically in better control of their behaviors. Being emotionally healthy is a protective factor from depression, anxiety, or other psychological issues. In addition, emotional health may refer to the presence of positive moods, which is very important for an individual's motivation to participate in PA.

The health benefits of regular PA have been established, however the challenging part for health educators is to promote PA to college students and help them integrate it into their daily lives. Reports from ACHA (2013) suggest more than 50% of students do not meet recommended amount of PA. In the past, the emotional domain of PA has been overlooked, as there have only been a few studies that have explored the relationship among EI and PA (Li et al., 2009). Slaski, et al. (2003) suggested that EI can be taught, and may be useful in improving health, well-being, reducing stress and enhancing overall performance. The purpose of this study was to emphasize the emotional aspect of participating in PA and to suggest emotional aspects can be enhanced to promote PA. The recommendation from this study might be helpful for health educators to integrate EI and mental health components in future PA interventions among college students. This research also may be helpful in creating and promoting interventions that support changes in various mental health aspects such as self-esteem, attitudes, self-motivation, and social relationships, which may ultimately lead to positive changes in PA behavior. In this context, where the neurobiological substrates of human emotion are now attracting increasing interest in various areas (Dolan, 2002), studies such as this one are important in establishing strong empirical support.

One limitation of this study is the use of self-reported questionnaires in assessing PA, EI, and mental health. There is a possibility of substantially overlapping optimism and general positivity that is inherited with all self-report measures. Another important limitation of this study is its cross-sectional research design. This prevented the establishment of directionality and causality. A positive relationship was found between EI and PA, but cannot establish that higher EI will result in higher PA, because it is equally possible that people with higher PA have higher EI, as people with higher PA have higher self-confidence and are more socially active. Future research should clarify this issue. The final limitation was related to the low response rate we received (2.34% of respondents). This may have created a sampling bias, and limit our ability to generalize this study to other college populations.

In conclusion, college students with a higher Global EI score were more likely to be physically active than their lower Global EI counterparts. Furthermore, college students in the High PA group reported better mental health compared to the moderate and low PA groups. The current study supports that PA enhances health and managing EI may be an effective way to improve PA behavior among college students. Future research should aim at determining the causal relationship between PA and EI. In addition, future studies should focus on research that includes training to enhance EI among college students, which could lead to improvements in overall health.


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Amir Bhochhibhoya MS, MBA

Paul Branscum PhD, RD

E. Laurette Taylor PhD

Craig Hofford PhD

Send correspondence to Amir Bhochhibhoya MS, MBA, Graduate Assistant, Department of Health and Exercise Science, University of Oklahoma, 1401 Asp Avenue, Norman, Oklahoma 73019; Paul Branscum PhD, RD, is an Assistant Professor in the Department of Health and Exercise Science, University of Oklahoma, Norman, OK, 73019; E. Laurette Taylor PhD, is an Associate Professor in the Department of Health and Exercise Science, University of Oklahoma, Norman, OK, 73019; Craig Hofford PhD, is an Associate Professor in the Department of Health and Exercise Science, University of Oklahoma, Norman, OK, 73019.
Table 1. Descriptive Statistics of Constructs of EI Assessed
by SSEIT, Major PA Measurements Assessed by IPAQ, and Global
Mental Health Status Assessed by Kessler Psychological
Distress Scale K6 (n = 438)

Measure          Possible   Oberseved      Mean (SD)      Cronbach's
                  range       range                         Alpha

Global EI         33-165     33-138     102.94 (12.63)      0.888
Perceiving        10-50       11-35      25.25 (4.21)       0.781
Utilizing          6-30       6-25       18.54 (2.79)       0.680
Regulating         9-45       9-40       29.76 (4.58)       0.782
Managing           8-40       8-40       29.38 (4.47)       0.751
Total Mental       6-30       6-24       19.88 (3.11)       0.825
Total MET-        0-3572     0-3572     912.29 (758.23)      N/A

Table 2. Emotional Intelligence, Mental Health and
Total MET-minutes/week in the Three Levels of
Physical Activity (PA) Groups (n = 438)

Measure                 Mean [+ or -] SD       F

Perceiving emotions                          1.747
High (n = 84)          26.0 [+ or -] 4.20
Moderate (n = 165)     25.2 [+ or -] 4.39
Low (n = 189)         24.97 [+ or -] 4.02
Utilizing emotions                           1.730
High (n = 84)         18.84 [+ or -] 2.68
Moderate (n = 165)    18.71 [+ or -] 2.68
Low (n = 189)         18.27 [+ or -] 2.93
Regulating emotions                          3.195
High (n = 84)         30.36 [+ or -] 4.02
Moderate (n = 165)     30.17 [+ or -] 4.7
Low (n = 189)          29.13 [+ or -] 4.6
Managing emotions                            2.596
High (n = 84)         30.03 [+ or -] 4.02
Moderate (n = 165)    29.67 [+ or -] 4.54
Low (n = 189)         28.84 [+ or -] 4.55
Global EI                                    3.514
High (n = 84)         105.24 [+ or -] 11.5
Moderate (n = 165)    103.76 [+ or -] 12.9
Mental Health                                3.044
High (n = 84)          20.46 [+ or -] 3.0
Moderate (n = 165)     20.02 [+ or -] 2.8
Low (n = 189)          19.50 [+ or -] 3.4
Low (n = 189)         101.23 [+ or -] 12.7

Measure                  P            LSD

Perceiving emotions    0.176      Hi = Mo = Lo
High (n = 84)
Moderate (n = 165)
Low (n = 189)
Utilizing emotions     0.179      Hi = Mo = Lo
High (n = 84)
Moderate (n = 165)
Low (n = 189)
Regulating emotions   0.042 *   Hi > Lo, Hi > Mo
High (n = 84)
Moderate (n = 165)
Low (n = 189)
Managing emotions      0.076      Hi = Mo = Lo
High (n = 84)
Moderate (n = 165)
Low (n = 189)
Global EI             0.031 *     Hi > Lo = Mo
High (n = 84)
Moderate (n = 165)
Mental Health         0.049 *     Hi > Lo = Mo
High (n = 84)
Moderate (n = 165)
Low (n = 189)
Low (n = 189)

* p < 0.05, Hi = High PA group, Mo = Moderate PA
Group, Lo = Low PA group Predictor variables of PA

Table 3. Parameters Estimates from the Multiple Regressions
for Total MET-minutes/week as Predicted by Perceiving
Emotions, Utilizing Emotions, Regulating Emotions, and
Managing Emotions. (n = 438)

Variable              Unstandardized       Unstandardized
                      Coefficients          Coefficients

                        B     Std. Error        Beta

Perceiving Emotions   0.010     0.015          0.037
Utilizing Emotions    0.018     0.024          0.043
Regulating Emotions   0.014     0.015          0.054
Managing Emotions     0.011     0.017          0.044

Variable                t     Unstandardized

                        T          Sig.

Perceiving Emotions   0.647       0.518
Utilizing Emotions    0.734       0.464
Regulating Emotions   0.897       0.370
Managing Emotions     0.670       0.503

F = 2.060, [R.sup.2] = 0.019, Adjusted [R.sup.2] = 0.010

Table 4. Parameter Estimates from the Hierarchical
Multiple Regressions Model for Total MET-Minutes/Week
as Predicted by Global EI in First Model and Global
EI and Mental Health Status in Second Model (n = 438)

Predictors     R     [R.sup.2]      Adj

Model 1      0.137     0.019       0.016

Global EI

Model 2      0.183     0.033       0.029

Global EI

Predictors   [R.sup.2]   Unstandardized
              change     Coefficient

                         B       SE B

Model 1

(Constant)               5.062   .460
Global EI                0.013   0.004

Model 2       0.015 *

(Constant)               4.552   .499
Global EI                0.008   0.005
Mental                   0.048   0.019

Predictors   Standardized     t      Sig.


Model 1

(Constant)                  10.99    0.000
Global EI       0.137       2.864   0.004 *

Model 2

(Constant)                  9.13     0.000
Global EI       0.089       1.754    0.080
Mental          0.131       2.565   0.011 *

* p < 0.05
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Author:Bhochhibhoya, Amir; Branscum, Paul; Taylor, E. Laurette; Hofford, Craig
Publication:American Journal of Health Studies
Date:Mar 22, 2014
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