Exploring the socio-emotional factors associated with subjective well-being in the unemployed

Social support, psychological adjustment and well-being

Social support can be defined as the perception or experience that one is loved and cared for, esteemed, and valued, and part of a social network of communication and mutual assistance (Wills, 1991). A consistent body of research has emerged over recent decades to show that close relations with family, friends, and significant others is a protective factor that helps guard against the deleterious mental and health effects of unemployment (Bjarnason & Sigurdardottir, 2003). Thus, lack of social support is positively related to depressive and anxious symptomatology, both in the general population (Siedlecki et al., 2014) and among the unemployed population (Rey, Extremera & Peláez-Fernández, 2015). Similarly, social support has been found to have a particularly marked effect on how well individuals cope with unemployment, that is, unemployed people cope with the loss of a job more successfully if they have a wide social support network (Bjarnason & Sigurdardottir, 2003; Ślebarska, Moser & Gunnesch-Luca, 2009).

In sum, the adverse impact of unemployment on the psychological adjustment and well-being of unemployed individuals in supportive social contexts might be less than its effect on unemployed individuals living in less supportive contexts (Rey, Extremera & Peláez-Fernández, 2015).

Emotional intelligence, psychological adjustment and well-being

There are currently two predominant models of EI: mixed and ability models (Mayer, Roberts & Barsade, 2008). Mixed models describe EI as a broad conception of intelligence that combines social skills, traits, and dispositional behavior. On the other hand, Mayer & Salovey (1997) ability model of EI involves the ability to carry out accurate reasoning about emotions and the ability to use emotions and emotional knowledge to enhance thought, thus enabling the subject to solve social problems and to adapt effectively to the environment (Mayer, Roberts & Barsade, 2008). In the operational definition of EI, these authors distinguish four specific skills: (1) the ability to identify and express emotions; (2) the ability to use emotions in decision-making; (3) the ability to understand emotions, and; (4) the ability to regulate emotions, both in oneself and in others.

A recent line of research has focused on the unique contributions of EI in explaining the psychological adjustment and well-being of different collectives controlling for classic constructs (Zeidner, Matthews & Roberts, 2012). The results of this research indicate that EI is negatively related to stress and depression (Augusto-Landa et al., 2008; Salguero, Extremera & Fernández-Berrocal, 2012), and positively related to various indicators of well-being (Gallagher & Vella-Brodrick, 2008; Por et al., 2011). All these findings were obtained in samples of the general population, but data on these relationships for unemployed people remain scarce. Prior studies have found that self-regulatory processes may exert influence on both longer-term affective states and on the mental health of individuals who lose their jobs (Wanberg et al., 2012). These results suggest that affective and personal resources are important to subjective well-being and psychological adjustment during unemployment (McKee-Ryan et al., 2005).

In sum, social support and EI might be resources that can help individuals to better cope with stressful situations, such as unemployment, and to increase psychological adjustment and well-being.

Motivation for the present study

Previous literature has confirmed empirical evidence of the relationship between social support and psychological adjustment and subjective well-being in unemployed people. Despite these findings, researchers have not examined the joint contribution of social support and EI dimensions to well-being and psychological adjustment during unemployment. These findings might be significantly useful in the design and development of employment promotion programs and clinical interventions with unemployed people.

Given the aforementioned considerations, the purpose of this study was twofold. The first purpose was to examine the relationships between social support, EI dimensions, stress, depression, and indicators of subjective well-being (life satisfaction and happiness) in a sample of unemployed people. Second, we examined the incremental validity of EI dimensions on stress, depression, and well-being outcomes beyond what is accounted for by the influence of social support. According to the aforementioned studies, higher levels of social support and EI dimensions are expected to be negatively associated with psychological distress and depression and positively associated with well-being outcomes. Thus, our study hypothesized that EI dimensions will explain further additional variance in psychological distress, depression, and well-being outcomes after removing any variance explained by social support.

Participants

The sample was composed of 442 unemployed people (225 males and 217 females) from two southern cities in Spain, who participated voluntarily and anonymously in the study. The mean age was 32.2 years (SD = 9.9). The average duration of unemployment was 20.28 months (SD = 30.7 months). The marital status of the participants was: 59.8% single, 13.5% married, 1.5% divorced, 16.2% widow(er), and 9% cohabiting.

Instruments

Procedure

Participants who were utilizing the national employment office in a province of southern Spain completed a survey about social resources, emotions, psychological adjustment, and well-being. The survey also included measures of social support, Perceived Emotional Intelligence (PEI), stress symptomatology, depressive symptomatology, life satisfaction, and happiness, along with questions related to socio-demographics variables such as age, gender, and period of unemployment. The order in which participants answered the measuring instruments was as follows: first they responded to questions related to socio-demographics variables, this was followed by the scales of social support, PEI, depressive symptomatology and stress symptomatology, life satisfaction, and, finally, they completed the scale that measures the global level of happiness. Data were collected over four consecutive months with the help of a team of research assistants. All subjects were informed that they would be asked to participate in a research study concerned with personality and emotions, and informed consent was obtained. Respondents received no financial compensation for participation in the study.

The study was carried out in accordance with the Declaration of Helsinki and the ethical guidelines of the American Psychological Association. The study protocol was approved by the Research Ethics Committee of the University of Jaén.

Statistical analysis

Preliminary analyses were carried out to compute descriptive statistics and internal consistency, as well as to detect correlations among social support, PEI dimensions, depressive symptomatology, stress symptomatology, and subjective well-being indicators (life satisfaction and happiness). To check whether PEI dimensions are related to depressive symptomatology, stress symptomatology, and subjective well-being indicators (even after controlling for the influence of social support), we conducted a three-step hierarchical regression in which socio-demographic variables were entered first (as control variables), followed by social support, and, finally, PEI dimensions (self-emotion appraisal, other-emotion appraisal, use of emotion, and regulation of emotion).

These analyses were carried out using the SPSS package (version 20.0; IBM, Chicago, IL, USA).

Descriptive analyses

Pearson correlations, means, standard deviations, and reliability of the different subscales used for the present sample are presented in Table 1. As expected, social support and all PEI dimensions were found to be significant and negatively related to depressive symptomatology and stress symptomatology. Similarly, social support and emotional dimensions were also found to be significant and positively associated to life satisfaction and happiness (see Table 1).

Hierarchical regression analyses

To examine and evaluate the separate contribution of socio-demographic variables, social support, self-emotion appraisal, other-emotion appraisal, use of emotion, and regulation of emotion for the prediction of depressive symptomatology, stress symptomatology, life satisfaction, and happiness, our study conducted a set of hierarchical regression analyses. For the first step, gender, age, and duration of unemployed were entered as control variables. Second, we entered social support: the well-known and classic dimension that is traditionally associated with psychological adjustment and the psychological well-being of the unemployed. Finally, PEI dimensions were entered into the regression. To examine whether predictors accounted for a small, medium, or large amount of the variance in psychological adjustment and well-being indicators, we used Cohen (1988) convention for small (f² = 0.02), medium (f² = 0.15), and large (f² = 0.35) effects. The results of these analyses are presented in Tables 2 and 3.

As Table 2 shows, a total of 20% of the variance was accounted for with respect to depressive symptomatology (R² = 0.20; F (7, 442) = 12.63, p < 0.001). In the first step, sex (β = −0.04, p > 0.05) did not predict the depression level. However, age (β = 0.23, p < 0.001) and time of unemployment (β = 0.10, p < 0.05) reached statistical significance in predicting the depression scores. In the next step, the classic dimension associated with depressive symptomatology (social support) did not predict the depression level (β = −0.06, p > 0.05). In the final step, use of emotions and regulation of emotions had a regression coefficient that reached statistical significance: (β = −0.25, p < 0.01) and (β = −0.14, p < 0.05), respectively, explaining a small but significant amount of variance (f² = 0.123) in the prediction of depression (ΔR² = 0.11).

A total of 15% of the variance was accounted for with respect to stress symptomatology (R² = 0.15; F (7, 442) = 9.13, p < 0.001). In the first step, sex (β = 0.00, p > 0.05) did not predict the stress level. However, age (β = 0.21, p < 0.001) and period of unemployment (β = 0.10, p < 0.05) reached statistical significance for predicting the stress scores. In the next step, the classic dimension associated with stress symptomatology—social support—did not predict the stress level (β = 0.12, p > 0.05). In the final step, regulation of emotions was the only factor that had a regression coefficient that reached statistical significance (β = −0.31, p < 0.001), explaining a small but significant amount of variance (f² = 0.111) in the prediction of stress (ΔR² = 0.10) (see Table 2).

As Table 3 shows, in terms of life satisfaction, a total of 20% of the variance of life satisfaction was accounted for (R² = 0.20; F (7, 442) = 12.97, p < 0.001). In step one, sex (β = −0.116, p > 0.05) and period of unemployment (β = 0.042, p > 0.05) did not predict life satisfaction. Age was the only socio-demographic variable that had a regression coefficient that reached statistical significance (β = −0.09, p < 0.05). In the next steps, social support was associated with life satisfaction for the unemployed (β = 0.22, p < 0.001). In the final step, the use of emotions was the unique predictor that had a regression coefficient that reached statistical significance (β = 0.26, p < 0.001), explaining a small but significant amount of variance (f² = 0.086) in the prediction of life satisfaction (ΔR² = 0.08).

Finally, with regard to subjective happiness, a total of 25% of the variance was accounted for (R² = 0.25; F (7, 442) = 17.17, p < 0.001). In step one, the socio-demographic variables did not predict happiness: age (β = −0.07, p > 0.05), sex (β = 0.07, p > 0.05), and period of unemployment (β = 0.07, p > 0.05). In the second step, social support was associated with the happiness of the unemployed (β = 0.24, p < 0.001). In the final step, self-emotion appraisal and use of emotions had a regression coefficient that reached statistical significance: (β = 0.13, p < 0.05) and (β = 0.22, p < 0.001), respectively, explaining a small but significant amount of variance (f² = 0.123) in the prediction of happiness (ΔR² = 0.11) (see Table 3).