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Article

The Interconnected Effects of Financial Constraints, Social Connections, and Health on the Subjective Well-Being of the Unemployed in Abu Dhabi

by
Masood Badri
*,
Mugheer Alkhaili
,
Hamad Aldhaheri
,
Guang Yang
,
Saad Yaaqeib
,
Muna Albahar
and
Asma Alrashdi
Department of Community Development, United Arab Emirates University, Abu Dhabi Department of Community Development, Abu Dhabi 22404, United Arab Emirates
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(20), 14918; https://doi.org/10.3390/su152014918
Submission received: 29 July 2023 / Revised: 18 September 2023 / Accepted: 28 September 2023 / Published: 16 October 2023
(This article belongs to the Section Health, Well-Being and Sustainability)
Browse Figure
Review Reports Versions Notes

Abstract

:
Research consistently highlights the substantially negative effect of unemployment on subjective well-being. This study’s objective is to provide deeper understanding of the complex nature of the associations between happiness and unemployment, which could enrich the duties of social policymakers when designing policy frameworks to improve the well-being of the unemployed. The methodology in this paper employs a path analysis using the Abu Dhabi Quality-of-Life survey (third cycle) data with 4815 unemployed respondents. The present study suggests a comprehensive path model to recognize the most significant associates of the happiness of the unemployed. Key findings indicate that income satisfaction and the ability to make ends meet have the highest effect on the happiness of the unemployed. The model also reveals the strength of different mediation roles played by family connection, quality time with family, and the ability to make ends meet, suggesting that financial difficulties resulting from unemployment can impact social relationships. In addition, the significant differences found between demographic groups based on age, marital status, gender, and educational attainment are also investigated. Policy implications are briefly discussed.

1. Introduction

Growing research attention worldwide has focused on various aspects of the well-being of the unemployed, including economic and material deprivation [1], physical health [2,3], mental health [4], social connections [5], spirituality [6], and emotions [7]. Most research reveals a negative impact of unemployment on those quality-of-life attributes [8].
Subjective well-being has become the most popular measure of quality of life. Life satisfaction and happiness reflect people’s living conditions [9]. On the effect of unemployment on happiness, in particular, several studies indicate that unemployment is correlated with a lower level of happiness [10]. However, inconsistent findings do exist [11]. Analysts have found that unemployment is not necessarily negatively related to subjective well-being [12]. In addition, studies on employment status and various sociodemographic determinants have produced mixed findings [13].
The latest official statistics show that in 2019, the Emirate of Abu Dhabi of the United Arab Emirates (UAE) recorded an unemployment rate of 6.9%, an increase from 5.2% in 2018 [14]. Unemployment in Abu Dhabi has apparent features of youth unemployment and gender differences [15], as the 20–24 age group accounted for 22.0% of total unemployed, and the female unemployment rate reached 14.8% in 2019 [14]. Unemployment and Emiratization challenges in the UAE have been attributed to the structural imbalance of the demand and supply of skills, the availability of low-wage migrant workers, the segmentation of the labor market between public and private sectors, and employee and employer perceptions [16,17,18,19]. Despite continuous and rigorous Emiratization drives by the UAE government, unemployment challenges are likely to continue, as are the negative implications of unemployment for the subjective well-being of the unemployed. Therefore, policymakers need to better understand the differences in subjective well-being between the employed and the unemployed and the significant determinants of happiness of the unemployed in the context of Abu Dhabi to design effective policies for helping the unemployed cope with different facets of their lives.
Therefore, the rationale for conducting this study is to examine the subjective well-being of the unemployed in Abu Dhabi and understand the factors that contribute to their happiness. This study aims to provide a multidimensional perspective on the issue of unemployment and contribute to the existing literature on the negative impact of unemployment on individuals’ psychological and social well-being. By considering economic, social, and health determinants, this study seeks to inform policymakers and support the development of interventions and policies to improve the well-being of the unemployed population.
The present study utilizes the data from the third cycle of the Abu Dhabi Quality-of-Life survey (QoL-3) to develop a path model to analyze the determinants of happiness for the unemployed in Abu Dhabi. In particular, we design and run a comprehensive path model for Abu Dhabi in which subjective health, mental feelings, income satisfaction, ability to make ends meet, and social connections are included and tested. Although subjective well-being has been examined for various groups of the population in the context of Abu Dhabi [20,21,22], including youth [23,24], to our knowledge, this is the first study aimed at unemployed in Abu Dhabi.

2. Review of the Literature

The social determinants approach has advanced in many fields, such as health [25]. This study’s social determinants of well-being framework examines how social, economic, and cultural factors influence well-being and highlight the socioeconomic systems’ critical role in subjective well-being [26].
Research shows that employment and work status significantly shape individuals’ happiness levels [27]. While several studies on the relationship between employment status and happiness have reported mixed results [13,28], most research reports that the unemployed are less happy than the employed [29]. Such a negative correlation between happiness and unemployment might not necessarily indicate a causal effect [30] and is likely to be influenced by individual and social characteristics [31]. In the following sections, we provide an overview of the relevant literature on the effects of various socio-economic and health factors on the subjective well-being of the unemployed.

2.1. Economic and Financial Constraints

Unemployment usually leads to reduced income and financial hardships, negatively affecting the economic well-being of the unemployed [14,32]. The long-term unemployed, in particular, are more likely to have debt and other financial difficulties [33]. Declining income reduces a household’s ability to make ends meet and economic well-being in general [34]. Income has often been demonstrated to have statistically significant but small effects on subjective well-being [35]. However, ref. [36] found that unemployment did not cause reductions in happiness for individuals whose household income levels substantially exceeded their minimum living requirement.
Apart from instrumental value, income and material resources help individuals cope with stress [37]. Thus, poor financial situations and poverty make the unemployed vulnerable to stress, depression, and other mental health symptoms [4]. Researchers have also established the association between unemployment and unhappiness through insecurity [3].

2.2. Unemployment and Health

Many studies report the relationships between happiness, subjective health, and mental health [38]. Unemployment increases the likelihood of poor physical health [39] and poor mental health [4]. Extensive findings in the literature indicate that psychological distress is a significant outcome of unemployment [40]. Unemployment could also result in certain unhealthy or unsocial behaviors that further deteriorate physical and mental health [41]. Several studies focus on psychological feelings and report that the unemployed reveal significantly worse emotional well-being [7].
Nevertheless, ref. [42] warned that caution should be exerted when estimating the longer-term effects of unemployment due to the nonrandom nature of exits from unemployment and other measurement issues. Addressing the relation between unemployment duration and health, ref. [43] suggested that the most deleterious effects on mental health may occur in the first two months of unemployment, which many studies on unemployment may fail to capture.

2.3. Social Relations and Connections

Unemployment contributes to rising relationship problems with family and friends [43]. The PEW [44] analysis of the US employment data showed how prolonged unemployment could strain personal relationships. Some observed that the unemployed generally feel worse than the employed when engaging with others in the same social activities [5]. In Sweden, ref. [45] examined the impact of adverse economic events because of unemployment on relationship quality and found that women suffered more than men.
Work constitutes the basis for belonging, and loss of work affects a worker’s identity and social life [46]. Social isolation and loneliness are widely recognized as among the most significant issues facing the unemployed [47]. For example, ref. [48] provided evidence from the UK to show that being isolated or lonely is a significant outcome for the young and unemployed. Moreover, some researchers point out that unemployment significantly influences an individual’s motivation to achieve valued life goals [49], which is a significant aspect of both subjective and mental health [50].

2.4. Demographic Factors

Demographic and socioeconomic factors must be factored in when studying employment status and happiness, as unemployment affects people differently [42]. Ref. [51] examined the gender difference in the relationship between health-related quality of life and employment status. Several empirical studies conclude that unemployed men have poorer mental health than women [52], while ref. [53] reported that unemployed female managers encountered substantially greater sources of stress than their male counterparts in all aspects of unemployment.
Some studies showed that the risk of depression increased in older age for females [54]. The study in ref. [55] indicates that unemployed youth show more negative experiences and lower quality of life than the reference group. Many studies focus on youth unemployment, since it has direct economic costs and lasting negative impacts on mental health problems, violence, and social exclusion [56]. Marriage was found to have a more positive influence on the effects of unemployment on health in women than in unemployed men [57]. Higher education usually leads to a more positive impact on happiness [58]. Some focused on the level of education of educated unemployed adults according to age [59]. Unemployed parents and the psychological effects of joblessness on the family are also the subjects of examination [10].

2.5. Regional Issues of Unemployment

The UAE is part of the Gulf Cooperation Council (GCC), which is a collective of countries comprising Bahrain (BHR), Kuwait (KWT), Oman (OMN), Qatar (QAT), Saudi Arabia (SAU), and the United Arab Emirates (UAE). The GCC was formed based on these countries’ shared cultural, political, economic, and social elements [60]. It is worth noting that from a broader perspective, the issues of unemployment seems to affect the broader Arab Gulf region [15]. These issues are not new, as the trend has been documented over the past decade [61]. Therefore, it is essential to situate unemployment issues within the regional context, as they are not limited to the UAE. The majority of studies have focused on the impact of unemployment on GDP [62]; interventions to tackle unemployment, and ineffective education [63]; reform of labor market policies [64]; and developmental and socioeconomic factors related to unemployment [65]. However, research on the negative impact of unemployment on individuals’ psychological and social well-being remains scarce, with a study investigating subjective well-being and work among Emirati youth [24]. Their findings indicate that being employed was a preventive measure against loneliness, sadness, and depression. Considering that the repercussions of unemployment on an individual’s well-being may perpetuate unemployment even further. This study attempts to contribute to the literature in this area for the UAE and GCC region to provide policymakers with a multidimensional perspective on the issue of unemployment.

3. Methods and Design

3.1. The Survey

The Abu Dhabi Quality-of-Life (QoL-3) survey was designed based on several international social surveys and studies, including the OECD’s Better Life Index [66], the Gallup Global Well-being Survey [67], the World Happiness Report [68], and the European Quality-of-Life Survey [69]. It covers various dimensions and factors of well-being, including mental feelings, subjective health, and happiness. The survey was administered online in 2021, following a combination of convenience sampling and random sampling approaches covering all the Emirate of Abu Dhabi’s regions. The random sampling approach was conducted with the cooperation of a team of research assistants from the Statistics Center Abu Dhabi. Sampling weights were introduced to represent the various respondent categories in the achieved sample adequately. For this study, the final sample was composed of 4815 self-reported unemployed persons in Abu Dhabi.

3.2. Variables

The variables selected for the current study adhered to their theoretical relevance, as indicated in the literature review, as well as the statistical significance registered by their partial correlation and path analysis resulting in coefficients. Extensive statistical analysis, including correlation and covariance analysis, multicollinearity analysis, and reliability analysis, helped identify the final list of eight variables to be considered further in the path model for the happiness of the unemployed. The assumed determinants include three main themes. The first theme covered subjective health, mental/psychological or emotional feelings, and isolation. The second theme covered the social-connection-related variables: frequency of meeting with friends, family satisfaction, and quality time with family. The economic well-being theme included the ability to make ends meet and income satisfaction.
Different scaling was used for the items in the survey. The happiness variable was measured on a 0–10 scale. ‘Mental feelings’ was a composite variable reflecting eight signs of mental or psychological issues, such as sadness/depression, worry/anxiety, fear, and boredom, measured on a Likert scale, with one indicating ‘not at all’ and five indicating ‘to a great extent’. The mental feeling variable exhibited a Cronbach Alpha reliability score of 0.913. The remaining variables used in this study were all measured on a 5-point Likert scale. For example, the family satisfaction variable used a 1–5 scale from ‘strongly disagree’ to ‘agree strongly’, responding to the question ‘I am satisfied with my family life’. The response to the question represented the ‘ability to make ends meet’ variable (‘my household can pay for its usual necessary expenses’) using a 1–5 scale from ‘with great difficulty’ to ‘very easily’.

3.3. Statistical Analysis

The analysis started with descriptive statistics for the unemployed category of respondents. The demographic information available in the QoL-3 survey included gender, age, nationality, marital status, education, and region of residence. For the path analysis, we followed a step-by-step process. We introduced one individual variable at every step by checking the fit statistic measures. The analysis considered the happiness variable as the focus variable, and the path analysis aimed to yield a path model and the estimates of associations that can explain the association pattern between happiness and other factors. We considered specific statistics to keep the variable in the model or eliminate it. As recommended, three fundamental statistical values were evaluated: the magnitude of the standardized coefficient, the t-statistics, and the significance level. In addition, variables that did not reflect any significant paths were eliminated from further consideration.
LISREL version 8.8 for Windows was used to adopt the application of path analysis [68,70]. The relationships between the variables of interest were assessed using several statistical criteria of measurement that included Maximum Likelihood Ratio Chi-Square, Root Mean Square Error of Approximation (RMSEA), Normed Fit Index (NFI), Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), Root Mean Square Residual (RMR), Goodness of Fit Index (GFI), and Adjusted Goodness of Fit Index (AGFI), in addition to other indexes.
Before using path analysis, we performed several rounds of multiple linear regressions to examine the association between the independent variables and the assumed dependent variable. Further, we used an analysis of variance (ANOVA) to examine the differences in the happiness of the unemployed between and among different categories according to gender, marital status, age, education attainment, nationality, and region of living. We utilized SPSS version 22 for all the statistical significance tests and analyses [69,71].

4. Results

Table 1 provides a summary of the demographic characteristics of the unemployed respondents in the survey. The sample represents more females (61.7%) and more married respondents (70.1%). Concerning age, the 26–35 and 36–45 age brackets together account for 67.1%. One in three unemployed (33.3%) holds a bachelor’s degree. Emiratis constitute 44.2% of the sample, while non-Emiratis account for 55.8%. Regarding residence location, the majority are from Abu Dhabi (62.7%), followed by Al Ain (33.0%).
A critical goal when using path analysis is to understand the patterns of correlation/covariance among a set of well-being variables and explain their variance with the model envisioned and specified [72]. Table 2 shows the covariances of the variables used in the path analysis. In the path analysis, the Chi-Square test indicates the difference between the expected and observed covariance matrices, with a Chi-Square value of zero indicating little difference between the expected and observed covariance matrices.
The final model generated good fit indicators. As shown in Table 3, the Abu Dhabi model yields a Chi-Square (χ2 = 11.160) with 7 degrees of freedom (p = 0.1318), giving χ2/df = 1.5942. Other statistics are also encouraging (RMSEA = 0.0154, NFI = 0.998, NNFI = 0.996, CFI = 0.999, GFI = 0.999, IFI = 0.999, and RMR = 0.00568). All these statistics indicate the high statistical quality of the path model. Figure 1 shows the final path model. Several model accuracy indicators and parameter values indicated acceptable or strong model structures.
Table 4 shows the standardized path estimates and their associated z-values and t-values for all path model variables. Various direct and indirect determinants impact the happiness of the unemployed. Figure 1 indicates eight significant paths with noticeable direct impacts on the happiness variable. These variables are income satisfaction (0.0250), feeling isolated (0.0239), family satisfaction (0.0220), mental feelings (0.0219), subjective health (0.0194), quality time with family (0.0179), frequency of meeting with friends (0.0153), and ability to make ends meet (0.0132).
Figure 1 also illustrates that some variables mediate in exerting more association with happiness. For example, ‘family satisfaction’ is the mediator between five determinants (subjective health, feeling isolated, quality of time with family, mental feelings, and income satisfaction) and happiness. ‘Ability to make ends meet’ also significantly mediates income satisfaction, feeling isolated, and happiness. Quality time with family mediates happiness and income satisfaction, the ability to make ends meet, and mental feelings. The path model shows that family satisfaction has a significant role in accounting for the happiness of the unemployed directly or through other determinants. A total of seven significant paths are associated with family satisfaction.
Table 5 reveals all the direct and indirect associations between the variables in the final path model. The highest total effect is income satisfaction and making ends meet (0.702). Meanwhile, family satisfaction is significantly influenced by income satisfaction (0.6492).
For happiness, the most significant total effect or association is from income satisfaction (0.5480), feeling isolated (0.2609), and quality time with family (0.2412). Looking at the variable ‘ability to make ends meet,’ income satisfaction exerts a significant total effect (0.702). It is worth noticing also that the mental feeling variable makes itself significantly present when we look at happiness, family satisfaction, and quality time with family.
Additional analyses were conducted. Table 6 provides the mean and standard deviation of the unemployed and the employed regarding their happiness and the other determinants. Such results could assist in understanding the results of the statistical differences test that would follow the path analysis. The variable ‘ability to make ends meet’ had the highest percentage change (25.87%), followed by income satisfaction (21.27%) and feeling isolated (18.23%). For the unemployed, the highest standard deviation is with ‘happiness’ (3.063), ‘frequency of meeting with friends’ (1.365), and ‘quality time with family’ (1.235).
ANOVA was employed to examine the differences in the happiness of the unemployed between and among the subgroups of age, gender, marital status, education attainment, region of living, and being the head of the household. Results reveal significant differences between genders, as females reported a higher level of happiness than males (F = 16.05 with 0.001 significance and mean happiness of 6.785 for males and 7.272 for females). Among the unemployed with different marital statuses, the widowed, separated, and married enjoyed the highest level of happiness of 8.028, 7.774, and 7.231, respectively. On the other hand, the divorced and the single reported the lowest happiness means of 6.412 and 6.664. Looking at the difference by age categories (F = 12.017 and 0.001 significance), those with ages close to college graduation (20 to 24 years) scored the lowest happiness (6.560); those 50 years and above reported relatively higher happiness (7.667).
Interestingly, non-Emiratis enjoyed higher happiness than Emiratis (F = 6.138 and 0.013 significance), as Emiratis scored 6.749, compared with 7.224 for non-Emiratis. In terms of differences in groups by educational attainment (F = 7.54 and 0.003 significance), those who can read/write or have primary education scored the highest on the happiness scales (8.977), and those with college degrees reported the lowest score (6.566). Regarding regions of living (F= 20.030 and significance of 0.001), those unemployed living in the Abu Dhabi region reported the lowest level of happiness (7.002), while those in Al Ain scored the highest (7.200). Those who reported being the head of the household showed significantly lower happiness scores than those who were not the head of the household (6.301 relative to 7.210 with F = 6.607 and (0.008 significance). Finally, the effect of the duration of unemployment on happiness was also investigated. A simple regression of happiness being the dependent variable and the duration of unemployment as the independent variable produced a positive b-score of 0.319 (t = 3.353, with 0.001 significance).

5. Discussions

The study of the happiness of the unemployed should look at the synergistic, more extensive system that involves a wide range of well-being determinants. The meta-analysis of longitudinal studies on the effect of unemployment on well-being suggests the significant role in this relationship of social and economic context, gender, and norms regarding work [8]. In this Abu Dhabi study, the path model offers a broader view that incorporates significant economic, social, and health determinants. Overall, the results of the path model are consistent with similar research that factors in the combining effects of many well-being factors, including physical health, mental health, social connection, and economic well-being [3,4,5].
Firstly, the Abu Dhabi study recognizes the economic well-being effects on the happiness of the unemployed. Both economic well-being variables—income satisfaction and the ability to make ends meet—have the highest effect on happiness. Such conclusions are supported by many other studies worldwide that recognize the financial burdens of unemployment [4]. We offer evidence to support the arguments that associate unemployment with financial difficulties resulting from borrowing more and spending more savings [32]. Moreover, this study reveals many associations between these economic well-being variables and social connection variables, such as family satisfaction, quality time with family, and isolation. Similar findings are provided by [21,73]. In this regard, the UAE recently issued the Unemployment Insurance Scheme as a mandatory program for all Emirati and foreign employees in the public and private sectors to subscribe to from 1 January 2023. This policy offers a buffer of financial protection for the unemployed that was not available before. Furthermore, these findings seem to support the UAE government’s recent aggressive financial initiatives to counter unemployment, with the introduction of the NAFIS federal program to subsidize and incentivize UAE citizens’ salaries in the private sector and offer a range of financially oriented benefits, career counseling, and training [71,74].
Secondly, the significant influence of mental feelings and isolation on happiness is underscored. In most international research dealing with the well-being of the unemployed, issues related to mental health and feelings of isolation and loneliness have received much attention [5,7]. The findings from this study offer an initial glimpse of the well-being of the unemployed in this region. The research findings in Abu Dhabi are consistent with the literature, as unemployment may trigger stress, depression, and unhealthy and unsocial behaviors that negatively affect mental health [4,41]. Abu Dhabi is home to migrant workers of many nationalities. Most unemployed migrants may suffer additional psychological and social isolation from moving to a new place and culture. These findings corroborate an earlier study by [72] that explored determinants of the well-being of migrant workers in Qatar. Being unemployed and looking for work in a new culture may be accompanied by homesickness, emotional deprivation, and isolation [4,50]. The unemployed Emiratis, the majority of whom are youths, are more likely to suffer from lower self-esteem, loss of meaning in life, and depression and anxiety. These findings are significant for Emirati youths, as most federal and local employment initiatives seem to target this segment [15].
More importantly, the path model provides an alarming warning when it reveals that the happiness of the unemployed is characterized by a significant decrease in their social life and connections. While a substantial reduction in contact with family and friends among the unemployed is not uncommon [5], it is worth emphasizing that Emirati and Arab youths tend to define happiness through a collective and social lens shaped by the Arab culture and norms [23]. This further supports social connections as a critical determinant of well-being in Abu Dhabi, confirming that people with more social connections or better social contexts report higher life evaluations [22]. Although the two variables of quality time with family and family satisfaction are associated positively with the happiness of the unemployed, they are negatively affected by mental feelings, which is broadly consistent with the findings of other studies [43,45]. Policymakers should consider such significant interconnections wisely when looking at the happiness of the unemployed in Abu Dhabi. Such evidence helps explain why unemployed Emiratis stated lower happiness than their non-Emirati counterparts. In addition, most migrant workers in Abu Dhabi may have lower prospects in their job hunting back home and are likely to be more optimistic about finding a job in Abu Dhabi than Emiratis.
In Abu Dhabi, unemployed females recorded higher happiness than unemployed males. This result is relatively consistent with other studies that analyze the determinants of happiness, such as subjective health and mental health [51,52], where women recorded more positive scores than men. This may be attributed to the cultural and social norms of the region, where females are supported by their families until they get married [74]. The cultural ‘safety net’ may have contributed to their higher feelings of well-being even when unemployed. The married reported a higher happiness score than the divorced and the single. The same positive influence of marriage on subjective well-being is illustrated by [57]. Also, as expected, unemployed heads of households scored significantly lower happiness scores than those who are not heads of households, which recognizes the burden of parenthood or being the head of a household during unemployment [10]. Those unemployed living in the Abu Dhabi region reported the lowest happiness. This outcome may reflect the higher cost of living in the Abu Dhabi region than in Al Ain or Al Dhafra. Research elsewhere suggests a positive relationship between the level of education and happiness [58]; however, this outcome is not supported by the Abu Dhabi data.

Theoretical Contributions

A review of the literature suggests that currently, there is no overarching theory that explains both unemployment and well-being [75,76]. However, there are several theories that explain the relationship between unemployment and well-being.
Structural unemployment theory is a longer-lasting form of unemployment caused by fundamental shifts in an economy and exacerbated by extraneous factors such as technology, competition, and government policy [77]. Structural unemployment occurs because contextual factors prevent employment. Jobs are available, but there is a serious mismatch between what companies need and what workers can offer. This is evident in the recent efforts of Emiratization in the UAE [18,19]; there seems to be structural barriers to employment within the UAE context for both Emiratis and expats. The findings of this study provide support for the Structural Employment Theory. This study recognizes the significant role of social and economic context, gender, nationality, and norms regarding unemployment. These findings suggest that the structural factors related to employment play a crucial role in determining the well-being of the unemployed.
In another strain, Cole [78] combined elements from five theories (skills atrophy model; social-psychological model of hysteresis; agency restriction theory; latent deprivation theory; and reverse causation theory) to propose the Integrated Model of Unemployment Effects. The integrated theory proposes that unemployment (or underemployment) deprives people of important latent and manifest benefits (LAMB’s) associated with employment, which in turn negatively impacts well-being (e.g., depression, anxiety, fear, stress, etc.). Poorer well-being adversely affects a person’s motivation to engage in job-search activity or the acquisition of human capital skills that facilitate re-employment. Potential employers also avoid hiring individuals with poor well-being, because they perceive them as less productive. Such individuals are therefore likely to remain unemployed for longer periods of time, which in turn further negatively affects their LAMB’s and well-being (a scarring effect). A vicious downward cycle may develop, creating the risk of long-term unemployment.
This study’s findings support Cole’s integrated model, as they reveal associations between economic well-being variables and social connection variables, such as family satisfaction, quality time with family, and isolation. These findings suggest that unemployed individuals’ well-being is influenced by their ability to find employment and maintain social connections. The aforementioned Unemployment Insurance Scheme in the UAE, which is a policy initiative providing financial protection for the unemployed, further aligns with the principles of Cole’s Integrated Model of Unemployment Effects, as it aims to support individuals during their job search and mitigate the negative effects of unemployment.

6. Conclusions

In this study, we explored a path model for the happiness of the unemployed in Abu Dhabi to understand the significant associations between their happiness and subjective health, mental feelings, social connections, and economic well-being. The results of the path model provide a clear view of the most significant factors that play essential roles in the subjective well-being of the unemployed.
For Abu Dhabi and the broader Arab Gulf region, these findings offer an initial glimpse of unemployment’s psychological and social consequences on the individual level. They may serve as a justification for more holistic intervention policies tackling unemployment. Unemployment is a negative experience that reduces happiness and imposes various economic, social, and health risks. The resulting evidence of this study produces valuable insights for setting a set of policy-relevant moderators that consider the multidimensional connections between various well-being factors such as health, income, and social connections. Social policymakers in Abu Dhabi should remain vigilant given the evidence that unemployment leads to adverse mental health changes, strained family relations, and loss of contact with close friends. A better understanding of the underlying associates of subjective well-being from the findings of this study could also promote the awareness and earlier identification of mental stress among the unemployed and the implementation of appropriate preventive policy interventions to facilitate their better adjustment. Policymakers should also consider further economic reforms to improve welfare and social safety nets for the unemployed.
Despite the strong evidence of specific determinants of happiness for the unemployed, the complexity of the associations between and among happiness and the determinants must be stressed, especially when demographic and socioeconomic elements are also considered. This may explain some of the mixed findings in the literature and justifies indigenous approaches to the study of the subjective well-being of the unemployed.

Limitations and Future Directions

The data collected for this study relied on self-reported measures, which may be subject to recall bias or social desirability bias. This could affect the accuracy and reliability of the responses provided by the participants. Furthermore, the authors acknowledge the limitation of including only one model and relying on online panel data. This limitation may affect the generalizability and reliability of the findings. Replicating the results in another study would strengthen the validity of the hypotheses and provide more robust evidence.
While this study considered several variables related to economic, social, and health dimensions, there may be other important factors that were not included in the analysis. These additional variables could potentially influence the happiness of the unemployed.
This study focused specifically on the context of Abu Dhabi and the Gulf Cooperation Council (GCC) region. Therefore, the findings may not be applicable to other regions or countries with different sociocultural and economic contexts.
Common method bias in this study was investigated by observing the HTMT and VIF. However, there have been developments in the field of method bias, and more rigorous methods were introduced, such as using a post hoc method to test if common method bias [79,80,81] is an issue in the analysis of the study findings, for example, the unmeasured latent method constructs (ULMC), which may be utilized in follow-up studies. Furthermore, considering that variables were measured by multiple indicators, a confirmatory factor analysis may be beneficial to test the measurement model fit (e.g., Chi-Square, TLI, CFI, SRMR) in order to reach more robust results.
Looking at the complex interplay of these variables, a longitudinal study design might offer another angle of the social issue related to unemployment and well-being. Additional insights may be reached by tracking people’s experiences in unemployment over time and exploring the duration of the effectiveness of mediating factors.

Author Contributions

M.B., H.A., S.Y. and M.A. (Mugheer Alkhaili) participated in the conceptualization; M.A. (Mugheer Alkhaili), G.Y., S.Y. and M.A. (Muna Albahar) participated in the methodology; M.B. and A.A. participated in using the software; M.A. (Muna Albahar), M.B., M.A. (Mugheer Alkhaili), S.Y. and G.Y. participated in the validation; M.B., M.A. (Muna Albahar) and G.Y. participated in the formal analysis; M.B. and G.Y. participated in a formal investigation; A.A. participated in data curation; M.A. (Mugheer Alkhaili) and M.A. (Muna Albahar) participated in writing—original draft preparation; M.A. (Mugheer Alkhaili), G.Y. and M.A. (Muna Albahar) participated in writing—review and editing; M.B., S.Y., M.A. (Muna Albahar) and A.A. participated in visualization. M.A. (Mugheer Alkhaili) and H.A. participated in supervision; G.Y., H.A. and A.A. participated in project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This work has been conducted and supported by research offices in the Department of Community Development and Statistics Center Abu Dhabi. There was no funding provided to conduct this research.

Institutional Review Board Statement

Does not apply.

Informed Consent Statement

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

Data Availability Statement

Data available on request from the authors.

Acknowledgments

The authors thank the cooperation of all Abu Dhabi government departments and communities for assisting in the distribution of the survey.

Conflicts of Interest

The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest, or non-financial interest in the subject matter or materials discussed in this manuscript.

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Sustainability 15 14918 g001
Figure 1. The final path model of happiness of the unemployed.
Figure 1. The final path model of happiness of the unemployed.
Sustainability 15 14918 g001
Table 1. The unemployed profile.
Table 1. The unemployed profile.
NPercent
Gender
Male1.84538.3%
Female2.97061.7%
Marital status
Married337470.1%
Single87718.2%
Divorced3928.1%
Separated551.1%
Widow1172.4%
Education
Read and write1710.036
Primary school1723.6%
Secondary school3587.4%
Prep. school140329.1%
Post high school2144.4%
College diploma4699.7%
Bachelor’s degree160333.3%
Master’s degree3827.9%
Doctoral degree430.9%
Age
25 and less4709.8%
26–35157532.7%
36–45165734.4%
46–5563013.1%
56–653266.8%
More than 651573.3%
Nationality
Emirati213044.2%
Non-Emirati268555.8%
Regions of living
Abu Dhabi302062.7%
Al Ain158833.0%
Al Dhafra3266.7%
Table 2. The covariance matrix.
Table 2. The covariance matrix.
X1X2X3X4X5X6X7X8X9
Ability to make ends meet (X1)0.838
Quality time with family (X2)0.1120.808
Family satisfaction (X3)0.1100.4060.699
Happiness (X4)0.1502680.2990.634
Income satisfaction (X5)0.3800.0490.2420.2480.518
Subjective health (X6)0.1070.0360.1450.1120.1280.448
Mental feelings (X7)−0.127−0.210−0.251−0.170−0.124−0.0830.048
Frequency of meeting with friends (X8)0.0700.0610.0900.0280.0630.025−0.1380.750
Feeling Isolated (X9)−0.137−0.078−0.145−0.137−0.065−0.0700.162−0.1060.368
Table 3. Final path model fit statistics.
Table 3. Final path model fit statistics.
Degrees of Freedom for 7
Maximum Likelihood Ratio Chi-Square11.160 (p = 0.1318)
Root Mean Square Error of Approximation (RMSEA)0.0154
Expected Cross-Validation Index (ECVI)0.0348
ECVI for Saturated Model0.0359
Normed Fit Index (NFI)0.998
Non-Normed Fit Index (NNFI)0.996
Comparative Fit Index (CFI)0.999
Incremental Fit Index (IFI)0.999
Root Mean Square Residual (RMR)0.00568
Goodness of Fit Index (GFI)0.999
Adjusted Goodness of Fit Index (AGFI)0.994
Parsimony Goodness of Fit Index (PGFI)0.155
Table 4. Structural equation maximum likelihood estimates.
Table 4. Structural equation maximum likelihood estimates.
Variables (TO)Significant Variables (FROM)Standardized EstimateZ-ValueSig.
Ability to make ends meetIncome Satisfaction0.020634.1590.001
Feeling isolated from others0.0244−10.1150.001
Quality time with familyAbility to make ends meet0.02264.7690.001
Income satisfaction0.0291−2.9600.003
Mental feelings0.0250−16.980.001
Family satisfactionAbility to make ends meet0.0159−14.0890.001
Quality time with family0.013831.5020.001
Income satisfaction0.020424.0420.001
Subjective health0.01757.3820.001
Mental feelings0.0194−9.0020.001
Feeling isolated0.0210−9.3210.001
HappinessAbility to make ends meet0.0132−6.5500001
Quality time with family0.017912.9770.001
Family satisfaction0.02203.7500.001
Income satisfaction0.025018.3040.001
Subjective health0.01942.9780.001
Mental feelings0.0219−2.2620.001
Frequency of meeting with friends0.0153−4.0890.001
Feeling isolated0.0239−10.0090.001
Table 5. Direct, indirect, and total associations.
Table 5. Direct, indirect, and total associations.
FromToDirectIndirectTotal
Subjective healthHappiness0.0640.01180.0758
Mental feelingsHappiness−0.0580.01530.0733
Feeling isolatedHappiness−0.2430.01790.2609
Income satisfactionHappiness0.4610.08700.5480
Quality time with familyHappiness0.2340.00720.2412
Family satisfactionHappiness0.0880.01150.0995
Frequency of meeting with friendsHappiness−0.062-0.062
Ability to make ends meetHappiness−0.1730.02750.2005
Feeling isolatedAbility to make ends meet−0.255-−0.255
Income satisfactionAbility to make ends meet0.702-0.702
Quality time with familyFamily satisfaction0.434-0.434
Feeling isolatedFamily satisfaction−0.2030.05710.2601
Subjective healthFamily satisfaction0.134-0.134
Income satisfactionFamily satisfaction0.4920.15720.6492
Mental feelingsFamily satisfaction−0.174-−0.174
Ability to make ends meetFamily satisfaction−0.2240.04690.2709
Income satisfactionQuality time with family0.0930.07580.1688
Mental feelingsQuality time with family−0.119-−0.119
Table 6. Summary of variables in the path model for the employed and the unemployed.
Table 6. Summary of variables in the path model for the employed and the unemployed.
VariablesEmployedUnemployed% Mean Change
MeanSt. DeviationMeanSt. Deviation
Happiness7.5772.3987.0203.0637.35%
Subjective health3.6431.0063.4151.1556.26%
Mental feelings2.2681.0612.6511.119−16.89%
Feeling isolated2.2111.0872.6141.218−18.23%
Income satisfaction3.0041.1302.3651.16721.27%
Ability to make ends meet2.6631.1301.9741.05125.87%
Family satisfaction3.9941.0783.8911.1762.28%
Quality time with family3.0781.2593.5471.23515.24%
Frequency of meeting with friends3.1631.3233.0751.3652.69%
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Badri, M.; Alkhaili, M.; Aldhaheri, H.; Yang, G.; Yaaqeib, S.; Albahar, M.; Alrashdi, A. The Interconnected Effects of Financial Constraints, Social Connections, and Health on the Subjective Well-Being of the Unemployed in Abu Dhabi. Sustainability 2023, 15, 14918. https://doi.org/10.3390/su152014918

AMA Style

Badri M, Alkhaili M, Aldhaheri H, Yang G, Yaaqeib S, Albahar M, Alrashdi A. The Interconnected Effects of Financial Constraints, Social Connections, and Health on the Subjective Well-Being of the Unemployed in Abu Dhabi. Sustainability. 2023; 15(20):14918. https://doi.org/10.3390/su152014918

Chicago/Turabian Style

Badri, Masood, Mugheer Alkhaili, Hamad Aldhaheri, Guang Yang, Saad Yaaqeib, Muna Albahar, and Asma Alrashdi. 2023. "The Interconnected Effects of Financial Constraints, Social Connections, and Health on the Subjective Well-Being of the Unemployed in Abu Dhabi" Sustainability 15, no. 20: 14918. https://doi.org/10.3390/su152014918

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