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Emotional Intelligence and Perceived Social Support: Its Relationship with Subjective Well-Being

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31 October 2023

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Abstract
The well-being in the people is a key aspect of the field of psychology. Hence, it is important to an-alyse the variables that are related to life satisfaction and happiness as perceived by individuals and that, therefore, increase their overall well-being. The main objective of this study was to ana-lyse the predictive capacity of emotional intelligence and perceived social support on both the level of life satisfaction and perceived happiness. A total of 380 psychology students completed the Trait Meta Mood Scale, the Multidimensional Scale of Perceived Social Support, the Satisfaction With Life Scale, and the Subjective Happiness Scale. The results show that both emotional intelligence and social support are related to and predictive of subjective happiness and life satisfaction. The importance of developing the components of emotional intelligence and promoting an adequate social network in young people is highlighted.
Keywords: 
Subject: Social Sciences  -   Psychology

1. Introduction

Traditionally, psychology has focused to a greater extent on mental illness and disorder rather than on well-being to alleviate negative effects. The subjective perception of well-being received little attention within the field of psychology until the second half of the 20th century saw an increase in interest in this aspect due to its influence on people’s mental and physical health [1,2]. This boom in the study of psychological well-being arose mainly from positive psychology, a discipline that marked a new paradigm in which well-being began to be analysed from the study of variables related to it, such as happiness and life satisfaction [3]. People’s well-being includes both cognitive (life satisfaction) and affective (emotions such as happiness) aspects [4]. Research with both adolescents and adults shows that subjective well-being is related to the effective functioning of the person in various areas of his or her life and that there is a direct relationship between such well-being and positive personal qualities that favour adaptation [5,6,7,8,9].
Emotional intelligence is a concept that has attracted increasing interest in recent decades. Traditionally, a distinction was made between two types of models of emotional intelligence: ability models and trait models [10]. Ability models understand emotional intelligence as a cognitive ability related to the processing of emotional information [11]. Emotional intelligence in ability models is evaluated using maximum performance tests. Trait models conceptualize emotional intelligence as a set of dispositions hierarchically inferior to personality traits that determine the way in which people deal with their own emotions and the emotions of others [12]. Trait emotional intelligence is typically assessed through self-report tests. Alongside ability models and trait models are the so-called mixed models, which define emotional intelligence as a set of cognitive abilities, emotional competencies, and stable personality traits [13]. Several studies have shown a positive relationship between self-perceived emotional intelligence and personal well-being, both in its cognitive and affective components [14,15,16,17,18,19,20,21]. Likewise, meta-analytic studies have also shown a positive relationship between emotional intelligence and subjective well-being in various populations [22,23,24]. One possible explanation for the positive relationship between emotional intelligence and subjective well-being is that emotional intelligence is also related to prosocial behaviour, a type of behaviour that not only has positive effects on those who receive help but also functions as a protective factor for the mental health and subjective well-being of those who engage in helping behaviours, also contributing to the development of communities [25]. In academia, emotional intelligence has been positively related to variables such as academic performance [26], self-efficacy [27], and academic engagement [28].
Perceived social support has been defined as an individual’s perception that he or she has a social network to turn to in case of need [29]. Empirical evidence has repeatedly shown relationships between perceived social support and well-being and quality of life [14,30,31,32,33,34,35,36,37]. Perceived social support is an essential aspect of the development of well-being because it responds to the needs presented by the individual during his or her development [1]. As in the case of emotional intelligence, perceived social support also has important implications in the educational sphere, being related to higher academic performance [38] and to lower dropout rates [39].
The theoretical framework we have just presented provides us with the foundations on which this research is based which stems from the need to deepen the study of the relationships between emotional and cognitive variables that influence the well-being and happiness of people, and more specifically of young people who are studying for a career and who will soon have to make crucial decisions for their lives.
Along with the positive effects of perceived well-being in the mental health domain [40,41], several studies in the educational domain have found a positive relationship between personal well-being and academic performance [42,43,44,45], an association confirmed in a meta-analysis conducted by Bücker et al. [46]. Likewise, the well-being of university students also shows a negative relationship with burnout [47,48], so studying the possible predictors of students’ well-being can play an important role in developing proposals to improve their performance and educational experience. Although, as we have pointed out above, there is previous research that has studied the relationships between emotional intelligence and social support with perceived student well-being, most of it was conducted by analysing these variables independently, especially in the Spanish population. The study of factors associated with the subjective well-being of university students can provide valuable information to both educators and decision makers in order to develop interventions aimed at promoting well-being in this population. Therefore, the objectives of this study are (1) to analyse the relationships among emotional intelligence and perceived social support, life satisfaction, and subjective happiness in Spanish university students and (2) to analyse the predictive capacity of emotional intelligence and perceived social support on both life satisfaction and subjective happiness in Spanish university students. According to the theoretical framework presented above, emotional intelligence and perceived social support are expected to be positively related and predict part of the variance in the subjective well-being of university students.

2. Materials and Methods

2.1. Participants

To determine the sample size necessary for this study, the criteria of Green [49] were followed; these criteria propose a range of between 15 and 25 subjects for each predictor of the regression model, resulting in a minimum number of between 120 and 200 subjects, since eight variables were introduced in the regression analyses. The sample of this study, selected by incidental nonprobabilistic sampling, was finally 380 students pursuing a Psychology degree at the University of Valencia aged between 18 and 55 years (M = 21.13; SD = 4.95). Of the participants, 316 were female (83.2%), and 64 were male (16.8%).

2.2. Instruments

Trait Meta Mood Scale (TMMS-24; Salovey et al. [50]). This self-perceived emotional intelligence scale measures through the dimensions of attention to feelings, which represents the degree to which people believe they pay attention to their own emotional states; emotional clarity, defined as the perceived ability to correctly identify and understand one’s own emotions; and emotion repair, or subjective ability to eliminate negative emotions and prolong positive ones. The Spanish adaptation [51], which has 24 items that are assessed on a five-point Likert scale, presents reliability coefficients of α = 0.86 for the emotional attention and emotion repair scales and α = 0.90 for the emotional clarity scale.
Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al. [52]). This scale evaluates the subjective perception that people have of the social support they receive in three dimensions: family, friends, and significant others. This scale is composed of 12 items that are answered on a seven-point Likert scale. The Spanish adaptation [53] of this scale showed a reliability of α = 0.85.
Satisfaction With Life Scale (SWLS; Diener et al. [54]). This scale evaluates general satisfaction with life by means of five items assessed by a seven-point Likert scale. The Spanish adaptation of this scale [55] showed a reliability of α = 0.85.
Subjective Happiness Scale (SHS; Lyubomirsky and Lepper [56]). This scale evaluates the subject’s degree of perceived happiness through four items with a seven-point Likert-type response scale. The Spanish adaptation of this scale [57] presented a reliability of α = 0.81.

2.3. Procedure

All students participated voluntarily and anonymously after being informed of the scope and objectives of the study. The tests were administered, after the participants provided informed consent, following the corresponding instructions for each test in the classroom during the students’ academic schedule by one of the research authors in a single session with no time limit. No incentives were offered to the students in exchange for their participation.

Ethical Considerations

This study is a part of a research project (HIM/2015/017/SSA.1207, “Effects of mindfulness training on psychological distress and quality of life of the family caregiver”) approved by the Research, Ethics, and Biosafety Commissions of the Hospital Infantil de México Federico Gómez National Institute of Health in Mexico City. While conducting this study, the ethical rules and considerations for research with human subjects currently enforced in Mexico [58] and those outlined by the American Psychological Association [59] were followed. All parents were informed of the objectives and scope of the research and their rights according to the Declaration of Helsinki [60]. The parents who agreed to participate in the study signed an informed consent form. Participation in this study was voluntary and did not involve payment.

2.4. Data Analysis

Data analysis was performed using the IBM SPSS Statistics v.24 statistical package. First, descriptive statistics and correlational analysis of the variables under study were calculated. Then, to determine the predicted variance in both life satisfaction and subjective happiness by emotional intelligence and perceived social support, two hierarchical regression analyses were performed. The order in which the variables were entered was the same in both cases. In the first step, the sociodemographic variables sex and age were entered; in the second step, the three scales of perceived social support (significant others, family, and friends) were entered simultaneously; and in the third step, the emotional intelligence scales (attention, clarity, and repair) were included.

3. Results

Means, standard deviations and Spearman correlations for the variables studied are presented in Table 1. As shown in this table, the TMMS-24 variables emotional clarity and emotion repair maintain a positive correlation with both life satisfaction and subjective happiness. The variables of perceived social support (significant others, family and friends) also correlate positively with life satisfaction and subjective happiness. Additionally, the TMMS-24 variables show positive correlations with the three variables of perceived social support.
Two multiple hierarchical regression analyses were carried out, one for each of the dependent variables: life satisfaction (Table 2) and subjective happiness (Table 3). The results show that for both life satisfaction and subjective happiness, the models are significant when the variables of perceived social support and emotional intelligence are entered in the second and third steps, respectively. The variables sex and age explain virtually no percentage of the variance in either life satisfaction (SWLS) or subjective happiness (SHS). In step 2, the introduction of the perceived social support variables explained 24.1% of the variance in SWLS (R = 0.491, R2 = 0.241; F(5.374) = 23.794, p < 0.001) and 17.4% of the variance in SHS (R = 0.417, R2 = 0.174; F(5.371) = 15.749, p < 0.001), with perceived support from family and friends being statistically significant predictors for both dependent variables. In the last step of the regression analysis, the introduction of the three emotional intelligence variables causes the explained percentage of SWLS to increase to 40.4% (R = 0.635, R2 = 0.404; F(8.371) = 31.413, p < 0.001) and that of SHS to increase to 46.4% (R = 0.681, R2 = 0.464; F(8.371) = 40.135, p < 0.001), with the predictor variables being statistically significant for the three components of emotional intelligence for both life satisfaction and subjective happiness, attention to feelings negatively, emotional clarity, and emotion repair positively.
To rule out multicollinearity, variance inflation values and tolerance indices were calculated and found to be within the recommended ranges, with variance inflation values below 10 and tolerance indices above 0.10.

4. Discussion

The objectives of this research were to analyse the relationships among emotional intelligence, perceived social support, subjective happiness, and life satisfaction, as well as the predictive capacity of the first two on happiness and satisfaction.
On the one hand, correlation analyses have shown the existence of strong and positive statistically significant relationships of the emotional clarity and emotion repair components of emotional intelligence with both subjective happiness and life satisfaction, results consistent with the previous findings of studies that also used the TMMS-24 test [15,18,20]. Therefore, we can say that those students who identify and understand their own emotions and who are able to manage them effectively, prolonging the positive ones and reducing the negative ones, can feel happier and more satisfied. We also found statistically significant relationships of a positive nature, although generally more moderate, of the three valued components of perceived social support (family, friends, and significant others) with perceived happiness and life satisfaction, similar to what has been found in other research papers [1,31,61,62]. Thus, there is a connection between feeling happy and satisfied and the support received from the social network formed by people in the family environment, friends, and other circles that are important to the person.
Along with the above, and although it is not the main objective of the study, statistically significant relationships were also found between all the components of emotional intelligence and the components of perceived social support, a result similar to that found in previous research [14,63,64]. This result was expected since greater emotional intelligence can help increase people’s social competence and, consequently, improve their relationships and social support networks [65].
On the other hand, and consistent with previous findings [18,19,20,66,67,68], regression analyses demonstrate the importance of emotional intelligence in predicting both life satisfaction and subjective happiness: positively, the components of emotional clarity and emotion repair, and negatively, attention to feelings. Thus, students who correctly identify their emotions and are able to manage them effectively perceive themselves as happier and more satisfied. These results are consistent with previous findings that emotional clarity is a key component in predicting people’s well-being [19,69]. However, emotional mindfulness is a negative predictor of both life satisfaction and happiness. Therefore, although a certain level of emotional attention may be adaptive, an excess of attention to one’s emotions accompanied by the inability to regulate them adequately may cause a greater presence of negative states [70]. Emotional intelligence has been related to an increase in social relationships and a higher frequency of prosocial behaviours [25,71], variables that have also been associated with subjective well-being, given that maintaining frequent social relationships is a crucial aspect in the life satisfaction and happiness of the people who form part of a community.
Perceived social support, both from friends and family, is also shown to be a significant variable in predicting life satisfaction and subjective happiness. The results from previous research are congruent with this fact, although they generally relate perceived family support more strongly to personal well-being [71,72,73]. In addition to being associated with both good mental and physical health [74,75], receiving social support from multiple sources also helps people cope adaptively with life difficulties [76,77,78], so it does not seem strange that this variable functions as a predictor of personal well-being.
Despite these findings, it is necessary to consider certain limitations of this study that should be kept in mind in future research. The main limitation is that the nonprobabilistic sampling coupled with the homogeneity of the sample, composed of mostly female university students, limits the generalizability of the results obtained. Furthermore, the wide age range of this study’s participants could also be considered a limitation, although the standard deviation of the age of the subjects is not high and most of them are in the same age group. Another limitation of this study is its cross-sectional design, since a longitudinal investigation could provide information that would help better understand the influence of emotional intelligence and social support on perceived well-being. Finally, emotional intelligence was measured with a self-report test, so it would be useful to complement this type of measure with others of maximum performance.
Despite the above limitations, this study provides valuable information on the effects and predictive capacity of emotional intelligence and perceived social support on life satisfaction and subjective happiness that can be used for the design of intervention programs in various settings (school, university, family, etc.). Bearing in mind that it is possible to increase emotional intelligence with appropriate instructional programs [79,80,81], it can be concluded, therefore, that fostering emotional intelligence and reinforcing social support networks is an appropriate strategy to increase the well-being of university students, both at a general level and in specific fields of studies.

Author Contributions

Conceptualization, S.H.-F., I.M.-Á., and M.J.S.-B.; methodology, C.M.-S., M.M.-V., and F.T.-T.; software, S.H.-F. and I.M.-Á.; validation, I.M.-Á. and M.J.S.-B.; formal analysis, S.H.-F., I.M.-Á., and M.J.S.-B.; investigation, M.M.-V., C.M.-S., and F.T.-T.; resources, F.T.-T.; data curation, C.M.-S. and F.T.-T. writing—original draft preparation, S.H.-F., I.M.-Á., and M.J.S.-B.; writing—review and editing, S.H.-F., I.M.-Á., and F.T.-T.; data visualization, M.M.-V., C.M.-S., and F.T.-T.; supervision, M.M.-V. and F.T.-T.; project administration, S.H.-F. and F.T.-T.; funding acquisition, F.T.-T. All authors have read and agreed to the published version of the manuscript.

Funding

Hospital Infantil de México Federico Gómez National Institute of Health, research project HIM/2015/017/SSA.1207, “Effects of mindfulness training on psychological distress and quality of life of the family caregiver”, with the main researcher Filiberto Toledano-Toledano. The source of federal funds did not control the study design, data collection, analysis, interpretations, or decisions regarding publication.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Commissions of Research, Ethics and Biosafety at the Hospital Infantil de México Federico Gómez, National Institute of Health. Approval Code: HIM/2015/017/SSA.1207, “Effects of mindfulness training on psychological distress and quality of life of the family caregiver”; Approval Date: This study is part of “Research Project HIM/2013/019/SSA.1141 Measurement and assessment of resilience in pediatric chronic disease,” which was approved on 16 December 2013, by the Research, Ethics and Biosafety Commissions of the Hospital Infantil de México Federico Gómez.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors without undue reservation.

Acknowledgments

The authors thank Hospital Infantil de México Federico Gómez Instituto Nacional de Salud, for providing their facilities.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Descriptive analysis and bivariate correlations.
Table 1. Descriptive analysis and bivariate correlations.
Mean(SD) Skewness Kurtosis 1 2 3 4 5 6 7 8
TMMS-Attention 29.40(5.89) −0.53 −0.04 -
TMMS-Clarity 25.94(6.27) −0.02 −0.42 0.230 ** -
TMMS-Repair 25.95(6.18) −0.05 −0.65 0.044 0.425 ** -
MSPSS-Significant others 24.63(4.42) −1.75 2.83 0.105 * 0.215 ** 0.160 ** -
MSPSS-Family 23.15(5.29) −1.35 1.31 0.135 ** 0.220 ** 0.250 ** 0.439 ** -
MSPSS-Friends 24.56(4.09) −1.66 3.37 0.109 * 0.147 ** 0.279 ** 0.477 ** 0.389 ** -
SWLS 25.63(5.80) −0.73 0.47 0.029 0.403 ** 0.479 ** 0.365 ** 0.395 ** 0.417 ** -
SHS 4.80(1.22) −0.55 −0.23 −0.023 0.398 ** 0.609 ** 0.239 ** 0.307 ** 0.342 ** 0.639 ** -
Notes: TMMS: Trait Meta Mood Scale; MSPSS: Multidimensional Scale of Perceived Social Support. SWLS: Satisfaction With Life Scale; SHS: Subjective Happiness Scale; * p < 0.05. ** p < 0.01.
Table 2. Hierarchical multiple regression predicting life satisfaction.
Table 2. Hierarchical multiple regression predicting life satisfaction.
R2 F B SE β p
Step 1 0.003 0.654 0.520
Age 0.007 0.060 0.006 0.914
Gender 0.914 0.799 0.059 0.253
Step 2—MSPSS 0.241 23.794 <0.001
Significant others 0.053 0.069 0.041 0.440
Family 0.330 0.056 0.301 <0.001
Friends 0.385 0.073 0.271 <0.001
Step 3—TMMS 0.404 31.413 <0.001
Attention −0.105 0.042 −0.106 0.013
Clarity 0.207 0.044 0.224 <0.001
Repair 0.277 0.044 0.295 <0.001
Notes: TMMS: Trait Meta Mood Scale; MSPSS: Multidimensional Scale of Perceived Social Support. First step: R2 = 0.003; second step: ∆R2 = 0.238; third step: ∆R2 = 0.162.
Table 3. Hierarchical multiple regression predicting subjective happiness.
Table 3. Hierarchical multiple regression predicting subjective happiness.
R2 F B SE β p
Step 1 0.009 1.724 0.180
Age 0.023 0.013 0.096 0.064
Gender 0.025 0.167 0.008 0.883
Step 2—MSPSS 0.174 15.749 <0.001
Significant others 0.003 0.015 0.012 0.823
Family 0.048 0.012 0.210 <0.001
Friends 0.083 0.016 0.278 <0.001
Step 3—TMMS 0.464 40.135 <0.001
Attention −0.025 0.008 −0.123 0.003
Clarity 0.037 0.009 0.189 <0.001
Repair 0.094 0.009 0.478 <0.001
Notes: TMMS: Trait Meta Mood Scale; MSPSS: Multidimensional Scale of Perceived Social Support First step: R2 = 0.009; second step: ∆R2 = 0.165; third step: ∆R2 = 0.290.
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