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Job Insecurity, Financial Threat, and Mental Health in the COVID-19 Context: The Moderating Role of the Support Network

Job Insecurity, Financial Threat, and Mental Health in the COVID-19 Context: The Moderating Role... The aim of this study is two-fold. Firstly, to analyze the relations between the perceptions of job insecurity and financial threat and general mental health during the early stage of the COVID-19 pandemic. And secondly, to identify the potential moderating effect of the support network. We carried out a cross-sectional study on a non-probabilistic sample aimed at a general Chilean adult population to analyze this. The results show that both job insecurity (β = −.183; p < .001) and financial threat (β = −.309; p < .001) are associated with a decline in general mental health. Likewise, the results indicated a positive relationship between support network and general mental health in the two models analyzed (βs = 0.322 and 0.182; ps < 0.001 and = 0.012, respectively), as well as a moderating effect of support network on the relationship between job insecurity and decreased general mental health (β = .232; p < .001). The theoretical and applied scope of these findings are analyzed, and their challenges and limitations are discussed. Keywords job insecurity, financial threat, general mental health, social support, support network, COVID-19 Research conducted in the last two decades, mainly since Introduction the beginning of the Great Recession of 2008, has uncovered The disruptive effects of social distancing, confinement, and the relationship between perceptions of risk in employment quarantine adopted to confront the COVID-19 pandemic and its accompanying financial risk with a myriad of conse- have affected multiple vital areas. Since March 2020, with quences for people’s well-being and health. Job insecurity the rapid expansion of the pandemic throughout the world, (e.g., Burgard et al., 2009; Lübke, 2021) and financial inse- work activities have changed drastically. On the one hand, curity (e.g., Kiely et al., 2015; Rajani et al., 2016) negatively governments and businesses imposed or recommended affect physical, mental, and psychosocial health. Both can working from home or remotely, which affected all activi- directly affect mortality when health is fragile (László et al., ties, except for important sectors and services in which 2010) and can lead to suicidal behaviors (Yip et al., 2007). being present was essential, such as hospitals, primary prod- Insecurity also can affect family and partner relationships uct sourcing, pharmacies, food sales, etc. On the other hand, (Mauno et al., 2017). Concerning the immediate conse- a large number of companies in the industrial and service quences of the COVID-19 pandemic, some studies have sector suddenly suspended their activities, affecting most of detected the negative effects of job insecurity, financial con- the commerce, small services, and hospitality businesses as cerns, and economic hardship on mental health (Dawel et al., well as the industry in activities considered non-essential; this resulted in the loss or temporary layoffs for a large num- ber of workers. The economic implications of the global Universidad Rey Juan Carlos, Madrid, España Universidad de La Frontera, Temuco, Chile pandemic, called “Coronanomics” (Eichengreen, 2020), are Universidad de Concepción, Chile still difficult to estimate in all their macro and micro magni- tude on a worldwide scale and per country (Barua, 2020). All authors are equally contributed. However, the effects on people and their families who lost Corresponding Author: jobs, suffered temporary layoffs, or kept jobs but worried Sergio Salgado, Departamento de Administración y Economía, Universidad about possible loss or deterioration in working conditions de La Frontera, Av. Francisco Salazar 01145, Temuco 4811230, Chile. Email: sergio.salgado@ufrontera.cl must be analyzed. Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open 2020; Ganson et al., 2021; Obrenovic et al., 2021; Wilson affective components related to the emotional reactions to job et al., 2020; Witteveen & Velthorst, 2020). loss or potential job change. The meta-analysis of Jiang and At the same time, previous research has shown the mod- Lavaysse (2018) shows that affective job insecurity was more erating effect of support networks and social support on the strongly related to correlates and outcomes, such as affective negative impact of job insecurity (Näswall et al., 2005; commitment or turnover intention, than cognitive job insecu- Schreurs et al., 2012). Thus, the support received at work rity. However, most research has used the one-dimensional per- can mitigate the negative effect of job insecurity on specific spective of quantitative job insecurity (De Witte, 2000; Sverke work-related outcomes, such as job dissatisfaction and non- & Hellgren, 2002; Vander Elst, De Witte et al., 2014). This is compliant job behaviors. There is also empirical evidence the approach adopted in this study. of the moderating role of instrumental social support in the Extensive prior research has identified three relevant relationship between financial stress and psychological effects of job insecurity. First, meta-analytic studies have well-being and psychosomatic disorders (Åslund et al., shown an overall negative impact of insecurity on general 2014). This effect has also been verified for emotional sup- mental health (Cheng & Chan, 2008; Sverke et al., 2002) on port (Whelan, 1993). specific disorders such as anxiety, depression, as well as on In Chile, where this study was conducted, social distancing decrease in psychological well-being, emotional exhaus- and confinement were adopted in mid-March 2020. This deci- tion, or life dissatisfaction (Llosa et al., 2018). Job insecu- sion meant shutting down and closing multiple productive rity is also associated with increased anxiety, irrational activities with the resulting temporary layoff or suspension of thoughts, and psychological distancing at work. Furthermore, the work contract for a high number of workers. Likewise, the negative effects of job insecurity have also been found on anti-pandemic measures increased the uncertainty about future physical health, including headaches or eyestrain and skin job continuity for many employees in vulnerable work situa- problems (Caroli & Godard, 2016), and incident coronary tions. To analyze the potential negative consequences of these heart disease (Virtanen et al., 2013). experiences, the aims of this study are two-fold. Firstly, to ana- Second, the negative effects of job insecurity on health lyze the relationship between the perceptions of job insecurity indicators and life satisfaction are greater in workers with and financial threat and general mental health during the first low levels of employability or lack of opportunities to find a month of the pandemic in a sample of the Chilean adult popu- new job in case of losing the current one (Caroli & Godard, lation. The second aim was to identify the potential moderat- 2016). These effects are compounded for people over ing effect of the support network on the relationship between 40 years of age (Otterbach & Sousa-Poza, 2016). the two variables. Thus, our goal was to carry out an initial Finally, an indirect effect of job insecurity on health can analysis of how work and economic factors can affect people’s occur when people reduce their investments in health to save mental health in a context of a prolonged health emergency for coping with a possible job loss. Although this potential and the accompanying economic crisis. effect could only be verified in the long term (Caroli & Godard, 2016), it is essential to consider it as a factor that increases the accumulated vulnerability of workers with Theoretical Background and fewer resources since there is evidence that job insecurity Hypothesis also affects negatively daily expenses and some major life decisions (Otterbach & Sousa-Poza, 2016). Consequences of Job Insecurity on Mental Health Specifically, some studies conducted since the beginning and Health Correlates of the COVID-19 pandemic have shown that greater job Job insecurity refers to “the perceived threat of job loss and the insecurity and job loss were related to greater depressive worries related to that threat” (De Witte, 2005, p. 1). It is a symptoms (Wilson et al., 2020; Witteveen & Velthorst, subjective anticipatory perception, the core of which is concern 2020). Additionally, recent or expected employment loss of a and fear regarding the future of one’s current job in the short or nuclear family member was associated with a greater risk of medium term. Such concerns include involuntary loss of one’s poor mental health, measured via four anxiety and depres- job with all the related negative consequences for well-being sion measures (Ganson et al., 2021). Consequently, in this and mental health, job attitudes and behaviors, and quality of pandemic context, this study analyzes the relationship life (Sverke & Hellgren, 2002; Vander Elst, De Witte et al., between job insecurity (and the other variables included in 2014). Further, experiences of job insecurity depend on three this work) with a general mental health screening, operation- threat features: perceived situational control, threat duration, alized through the General Health Questionnaire (Goldberg and volition (Shoss, 2017). Consequently, lower control, lon- & Williams, 1988). ger-term, and lower volition will cause increased distress in Based on these rationales and prior data, we formulate the workers (Shoss, 2017), with detrimental effects on personal following hypothesis: physical and psychological health and work-related well-being (De Cuyper et al., 2019; Lübke, 2021; Shoss, 2017). Finally, H1: In the COVID-19 pandemic context, the perceived other authors (Jiang & Lavaysse, 2018) have proposed differ- job insecurity is negatively related to general mental entiating the cognitive components of job insecurity from the health. Alcover et al. 3 The combination of job insecurity and financial insecurity Consequences of Financial Threat on Mental or risk significantly affects vitality and mental health (Rajani Health and Health Correlates et al., 2016). Also, it has been demonstrated (Lam et al., The financial threat is an emotional state that refers to “self- 2014) that in situations of economic turbulence (such as reported fearful-anxious uncertainty regarding one’s current great crises and recessions, or like the one caused by the and future financial situation” (Fiksenbaum et al., 2017; see COVID-19 pandemic), workers perceive a loss of sense of also Marjanovic et al., 2013). Financial threat perception, or control (Glavin, 2013), so that the adverse effects of job inse- financial distress, is usually associated with people or house- curity on mental health are even higher. Wilson et al. (2020) holds that experience job insecurity when their jobs are less found that greater job insecurity due to COVID-19 was indi- secure and have low protection against unemployment rectly related to greater anxiety symptoms due to greater (Giannetti et al., 2014). Data confirms that the financial financial concern. threat is higher for people who experience many economic Based on these rationales and prior data, we formulate the problems in their everyday life (Marjanovic et al., 2015). following hypothesis: Economic challenges can also become a chronic stress situa- tion in families, which can generate distressing thoughts H2: In the COVID-19 pandemic context, the perceived about paying household expenses and can lead to feelings of financial threat is negatively related to general mental fear, anxiety, and uncertainty regarding one’s ability to main- health. tain the current standard of living (Fiksenbaum et al., 2017; Marjanovic et al., 2013). Support Network as a Moderator in the Prior research has found that economic insecurity is a Relationship Between Job Insecurity, Financial socio-economic determinant of mental health (Kopasker Threat, and General Mental Health et al., 2018). The financial threat preceded or not by debts already incurred is associated with greater psychological dis- Prior research shows a direct association between social rela- tress, characterized by higher levels of depression, anxiety, tionships and mental health (House et al., 1988; Uchino, and fatigue (Fiksenbaum et al., 2017), lower subjective well- 2006). In the study of these associations, social connections being (Netemeyer et al., 2018), greater emotional exhaustion have been conceptualized in terms of a structural perspec- and lower psychological well-being (Marjanovic et al., 2015), tive, namely social networks (with properties such as size and psychological distress and mental health issues and composition); and from a functional perspective or the (Marjanovic et al., 2013). Additionally, it has been shown that social support stance, understood as the subjective feeling of the perception of future financial risk (without future unem- being supported by others (Santini et al., 2015). ployment necessarily occurring) affects mental health more Studies about the role of social networks on mental health negatively than actual volatility, affecting all income levels informed that restricted social networks could turn into social and being more detrimental for men (Kopasker et al., 2018). isolation and negatively impact mental health and life satis- Worry and rumination about financial risk can also exacer- faction (Harasemiw et al., 2019). Also, weak social networks bate negative consequences on mental health, psychological have been associated with higher depressive symptoms well-being, and cognitive functioning (de Bruijn & Antonides, among men and women (Chan et al., 2011). Moreover, stud- 2020). It has also been found that the perception of financial ies on older people have stated the association between risk mediates the relation between economic difficulties and depression and social isolation (Landeiro et al., 2017) and suicidal thoughts, and cognitive confusion/bewilderment loneliness (Tomaka et al., 2006), confirming the protective affects women and men equally (Fiksenbaum et al., 2017). role of social connectedness for mental health. Additionally, Specifically, analyses of representative samples of active there is evidence about the role of social networks on job members of the labor force of six European countries indi- insecurity. Studies stated the negative relationship between cated a positive relationship between immediate economic solid ties and job insecurity (Mehreen et al., 2019) and the hardships during the COVID-19 lockdown and indicators of moderating effect of social networks on the financial strain mental health deterioration, such as feelings of depression and depression (Sicotte et al., 2008). and health anxiety (Witteveen & Velthorst, 2020). This asso- From the social support view, the protective effect of the ciation between financial hardship and poor mental health is perceived social support on mental health and wellbeing has more pronounced when workers have a lower occupational a long trajectory in psychosocial research (Thoits, 2011). In status. In a similar vein, Wilson et al. (2020) found that greater their classic study, Cohen and Wills (1985) found support for financial concern due to COVID-19 was related to greater the moderating model when social support refers to the per- anxiety symptoms in a sample of employed U.S. individuals, ceived availability of interpersonal resources that respond and Dawel et al. (2020) found that financial distress due to the directly to people who are experiencing stressful events. pandemic consequences was a key correlate of poorer mental Given that both job insecurity and financial threats constitute health in Australian population measured via anxiety, depres- powerful work-related stressors (De Witte, 2005; Fiksenbaum sion, and psychological well-being measures. et al., 2017; Marjanovic et al., 2013; Sverke & Hellgren, 4 SAGE Open 2002), identifying the potential moderating effect of social H5: In the COVID-19 pandemic context, support network support from a person’s social network is of great relevance moderates the relationship between financial threat and to offsetting their negative consequences for health. general mental health. Theoretical models (Greenhalgh & Rosenblatt, 1984) and previous studies have demonstrated that social support Materials and Methods moderates the negative effects of job insecurity on work outcomes, such as job satisfaction and vigor (Cheng et al., A cross-sectional correlational study was conducted on a 2014), and on well-being and mental health (Lim, 1996; non-probabilistic sample of the general Chilean adult popu- Näswall et al., 2005). It has also been found that women lation. The project underwent assessment by an Ethics and use social support more often and efficiently than men Bioethics Committee (# 650-2020, March 2020). (Matud, 2004). These results were confirmed in a recent study that showed that when women actively access their Sampling Strategy social support network, this acts as a buffer for the nega- tive consequences of job insecurity (Menéndez-Espina The Government of Chile began to decree social distancing et al., 2019). These conclusions agree with Cohen and and confinement measures on March 16, 2020, and they pro- Wills (1985) that the effectiveness of this interpersonal- gressively increased restrictions on productive, commercial, social resource depends on it serving specifically to man- and consumption activities as different regions detected con- age the stressful situation. However, another recent study tagions and deaths. The data were collected via an online (Giunchi et al., 2019) clarified previous results that sup- questionnaire (Questionpro) between March 24 and April 23. ported the moderating effect of the perception of social The recruitment strategy combined professional networks, support, as they showed that the negative relationship social networks, professional associations, undergraduate between job insecurity and psychological well-being is and graduate students, and personal contacts who were reduced when the perception of job insecurity is low, but invited to participate and disseminate this invitation among not when it is high. their network of contacts (snowball strategy). Before begin- There is also empirical evidence of the moderating role ning the study, the participants read and signed informed of instrumental social support in the relationship between consent. Participants took an average of 27 minutes to com- financial stress and psychological well-being and psycho- plete all the instruments. When necessary, they could save somatic disorders (Åslund et al., 2014) and in the relation- their progress and take it up again when convenient. The bat- ship between financial stress and alcohol-related behaviors, tery of questionnaires included other instruments not consid- including drinking to deal with problems, excessive con- ered in this study that corresponds to a complementary line sumption of alcohol and problems with alcohol (Peirce of research aimed at exploring several personal and social et al., 1996). The moderating effect has been verified for factors that could affect people’s well-being and health in the instrumental and emotional social support (Whelan, 1993). context of the COVID-19 pandemic. These last results lead to the assumption that instrumental A total of 591 participants completed the study (592 full support can serve as a strategy centered on confronting the responses to the online questionnaire were obtained, of problem. In contrast, emotional support can be used as a which a duplicate case identified through the informed e-mail strategy centered on negative emotional responses. These was eliminated). All the participants resided in Chile. relations may be important in designing interventions to reduce the negative effects of insecurity and financial Instruments threats. Although social network and social support are separated Job insecurity. Job Insecurity Scale (De Witte, 2000) variables, both are closely related and provide a comprehen- was used, adapted, and validated in Spanish (Vander Elst, sive view of the role of social relationships as sources of cop- De Witte et al., 2014). It includes four items (e.g., “I fear ing with environmental and work stressors. To combine that I might lose my job”) scored on a 6-point Likert scale social network and social support perspectives, we adopt the (1 = Strongly disagree to 6 = Strongly agree). This measure notion of support network: the number of close bonds or inti- has shown acceptable reliability and validity in the literature mate relationships that provide support. (Cronbach’s alphas generally above 0.80; e.g., Vander Elst, Based on these rationales and prior data, we formulate the De Witte et al., 2014). following hypothesis: Financial threat. The Financial Threat Scale adapted to H3: In the COVID-19 pandemic context, the support net- Spanish (Marjanovic et al., 2015) was used to measure this work is positively related to general mental health. construct. The instrument contains six items (e.g., “How H4: In the COVID-19 pandemic context, support network much do you feel threatened by your financial situation?”) moderates the relationship between perceived job insecu- that are evaluated on a 5-point Likert scale (1 = Not at all; rity and general mental health. 5 = A great deal). The scale has shown acceptable reliability Alcover et al. 5 and validity in the literature (Cronbach’s alphas generally it is recommended a critical ratio of multivariate kurtosis above .80; e.g., Marjanovic et al., 2015). lower than 5 (Bentler, 2005; Byrne, 2010). The internal con- sistency reliability was examined using Cronbach’s alpha General mental health. To measure the perception of gen- (α), McDonald’s omega (⍵), and composite reliability eral mental health, the 12-item version of the General Health (C.R.), for which values above .80 are considered acceptable Questionnaire (Goldberg & Williams, 1988) was used in (Hair et al., 2014; Lance et al., 2006). Convergent validity its version previously applied in Chile (Garmendia, 2010; was tested through the average variance extracted (AVE), for Rivas-Diez & Sánchez-López, 2014). This instrument is which values greater than 0.50 are considered acceptable widely used for mental health screening (Gnambs & Staufen- (Hair et al., 2014). biel, 2018). It contains 12 questions (e.g., “Are you able to As this is a cross-sectional study, it is important to control concentrate on what you do?,” “Have you felt constantly the effect of the common method variance (CMV) and to ana- under strain?,” “Have you felt unhappy or depressed”) lyze the discriminant validity of the measures. Strategies for answered on a 4-point Likert scale (1 = Never; 4 = Always). CMV were used a priori and post hoc. Regarding the a priori Although more than one underlying factor has been detected strategy, instruments with different scale formats were used in in the literature, the instrument’s structure is recognized as this study, which helps to prevent CMV (Podsakoff et al., essentially one-dimensional. This way it is used in the pres- 2012). Regarding the post hoc strategy, the Harman single fac- ent study as recommended (Gnambs & Staufenbiel, 2018). tor test was carried out via exploratory factor analyses (Chang Literature has reported reliability and validity for this instru- et al., 2010). This is the most widely used method to examine ment (Cronbach’s alphas above .85; e.g., Garmendia, 2010; the pernicious presence of CMV (Podsakoff et al., 2003; Rivas-Diez & Sánchez-López, 2014). Tehseen et al., 2017). The assumption is that if CMV exists, the first not rotated factor (eigenvalue >1) on a principal com- Support network. The support network was measured by a ponents analysis that includes all the involved items account single item about the size of the family/friends support net- for more than 50% of the variance. work (i.e., Approximately, how many close friends or rela- Discriminant validity was analyzed in two ways. First, we tives do you have? (people with whom you get along and test if the correlation between constructs is lower than the can talk to about everything happening). This measure is square root of the AVE for any single latent construct. included in the Medical Outcome Study (MOS) social sup- Second, the scales’ confirmatory factor analysis (CFA) was port survey (Sherbourne & Stewart, 1991). The use of single performed in two steps. The first step analyzes the fit of a items in general, and social support measures, in particular, model in which the items of the different scales are collapsed has already been widely discussed and accepted as appropri- in a single-latent variable. Then, the fit of the theoretical ate in the field of occupational health (Fisher et al., 2016), model is analyzed. The discriminant validity of the con- and previous research has shown that it is a good predictor of structs is sustained when the fit of the single-latent model is health outcomes (e.g., Janevic et al., 2004). not satisfactory and the theoretical model shows an accept- able level of fit (Anderson & Gerbing, 1988). Control variables. The variables gender, age, and educa- To test the hypotheses, structural equation modeling tional level were included in this study as control variables. (SEM) was performed. The latent moderator variable was The decision to include these control variables is based on included by multiplying the items pairs of the corresponding those employed in previous studies in this research field variables as the observed values (Schumacker, 2002). (e.g., Bentley et al., 2019; Hellgren & Sverke, 2003; Wat- Both CFA and SEM used the diagonal weighted least son & Osberg, 2017) and in particular, in studies conducted squares method (DWLS; Muthén, 1993) with robust estima- during pandemic-induced confinement (see specifically, e.g., tion of errors. This method is recommended for models Dawel et al., 2020; Ganson et al., 2021; Wilson et al., 2020; including continuous and categorical variables (Kline, 2016). Witteveen & Velthorst, 2020). It is also effective for small samples and variables that are not normally distributed (Rhemtulla et al., 2012). The evalu- ation of the models fit considered the following criteria to be Data Analysis considered acceptable: χ /df ratio <3, root mean square error First, we analyzed univariate and multivariate normality. of approximation (RMSEA) ≤0.06, standardized root mean There is no consensus regarding an acceptable degree of uni- square residual (SRMR) ≤0.08, comparative fit index (CFI), variate non-normality, but cut-off values are often +/3 and and Tucker-Lewis index (TLI) ≥0.95 (Hu & Bentler, 1999). ±7 for skewness and kurtosis, respectively (Curran et al., Z-scores for all the observed variables were used in the anal- 1996; DeCarlo, 1997). Multivariate normality was tested ysis. For processing data, JASP, an open-source software, using Mardia’s coefficient. In this regard, two criteria are and Lavaan were used (JASP Team, 2021; Rosseel, 2012). considered: (a) it is recommended a critical ratio of multi- The analyzes related to the financial threat variable are car- variate kurtosis lower than ±1.96 (p > .05); (b) taking into ried out on the total sample (n = 591). The analyses involving account that the p-value could be affected by the sample size, job insecurity measures are carried out on the subsample that 6 SAGE Open Table 1. Demographic Information of the Participants. being so restless or agitated that you have been moving from one place to another more than usual”) in which the responses Parameters were accumulated to a greater extent in the central scores of Total sample, n 591 the scale. On the other hand, the variable support network Gender, n (%) showed skewness and kurtosis outside the range that would Female 449 (76) indicate a normal distribution (4.418 with a critical ratio >43; Male 140 (23.7) and 33.360 with a critical ratio >160, respectively) which is Other 2 (0.3) consistent with previous research where this variable has Mean age in years, M (SD) 37.63 (12.85) been freely reported as a continuous measure (e.g., Bruine de Mean children, M (SD) 1.28 (9.74) Bruin et al., 2020; Fung et al., 2001). This occurs because Occupational status, n (%) most people have a small support network, and very few have Full-time job 269 (45.5) a large one, which was an expected distribution. Part-time job 43 (7.3) Regarding multivariate normality, Mardia’s coefficients Independent worker 82 (13.9) do not support this assumption (kurtosis >100; critical ratio Student 79 (13.4) >37; p < .001). Unemployed 55 (9.3) Retired 30 (5.1) Internal Consistency Reliability and Convergent Household work 24 (4.1) Other 9 (1.5) Validity Completed educational level, n (%) Cronbach’s alpha (α), MacDonald’s omega (⍵), composite Graduate studies 222 (37.6) reliability (C.R.), and the average variance extracted (AVE), Undergraduate studies 256 (43.3) together with means, standard deviations, and latent variable Technical/professional studies 49 (8.3) correlations are shown in Table 2. Results show acceptable High school 63 (10.7) internal consistency levels when observing the Cronbach’s Elementary school 1 (0.2) alpha, McDonald’s omega, and composite reliability (>.8). Urban or rural place of residence, n (%) Urban area 550 (93.1) Regarding convergent validity, AVE values show acceptable Rural area 41 (6.9) levels (>0.5), except for general mental health, which is Region of residence in Chile (the most represented are lower than the benchmark. However, we can accept its AVE shown), n (%) value of 0.4 in combination with composite reliability higher Bio-Bio 213 (36) than 0.6 (Fornell & Larcker, 1981), and having in mind that Metropolitan area of Santiago 137 (23.2) it is a widely used measure, so keeping all the items allows La Araucanía 121 (20.5) better comparability of the results. Valparaiso 36 (6.1) Los Lagos 17 (2.9) Common Method Variance (CMV) and Discriminant Validity includes full-time, part-time, and independent workers Harman’s test showed that the first not rotated factor (eigen- (n = 394). Z-scores for the analyzes were calculated into the value >1) explains 26.83% of the variance; thus, CMV does corresponding sample. not affect covariance among variables. Regarding discrimi- nant validity, the diagonal of Table 2 presents the square root of AVE, showing in all cases values higher than the latent Results variable correlations, which support the discriminant validity The demographic information of the participants is presented of the variables. in Table 1. It is observed that females and people with higher education are more represented. The latter may be because Confirmatory Factor Analyzes the snowball technique used to obtain the sample started from networks and contacts close to the university context. The factorial structure of the scales was analyzed in two CFAs. Model 1 included the measures of job insecurity and general mental health in the subsample of workers (n = 394). Univariate and Multivariate Normality Model 2 included the financial threat and general mental Regarding skewness and kurtosis, the items of both financial health measures in the general sample (n = 591). As seen in threat and job insecurity scales showed values within the Tables 3 and 4, these analyses were carried out in two steps. acceptable range, except for one item of the general mental First, it was tested whether a single-factor model fit the data, health scale that showed a kurtosis over 4 (“Moving or speak- and then the hypothesized theoretical model was analyzed. ing so slowly that others may have noticed. Or the opposite: The results supported the discriminant validity, and the Alcover et al. 7 Table 2. Mean, Standards Deviation, Cronbach’s Alpha, McDonald’s Omega, Composite Reliability, Average Variance Extracted and Latent Variable Correlations. Variable Mean SD α ⍵ C.R. AVE 1 2 3 4 1. JI 3.040 1.478 .886 0.895 0.888 0.669 (0.818) 0.617** −0.092 −0.226** 2. FT 3.102 1.067 .918 0.917 0.918 0.653 (0.808) −0.117 −0.373** 3. SN 8.140 8.246 — — — — — 0.211** 4. GMH 2.897 0.543 .885 0.887 0.887 0.400 (0.632) Note. n = 591, except those results involving job insecurity, where n = 394. C.R. = composite reliability; AVE = average variance extracted; (___) = square root of AVE; JI = job insecurity; FT = financial threat; SN = support network; GMH = General Mental Health. **p < .01. Table 3. CFA Fit Indices for the Model 1, that Includes the Job Insecurity and General Mental Health Measures. 2 2 Model 1 χ df p χ /df ratio SRMR RMSEA [90% CI] CFI TLI Single-factor model 1140.784 104 <.001 10.969 0.146 0.159 [0.151–0.169] 0.731 0.689 Two-factor model 196.807 103 <.001 1.911 0.068 0.048 [0.038–058] 0.976 0.972 Note. N = 394. χ = chi square; df = degrees of freedom; SRMR = standardized root mean residual; RMSEA = root mean square error of approximation; CFI = comparative fit index; TLI = Tucker-Lewis index. Table 4. CFA Fit Indices for Model 2, that Includes the Financial Threat and General Mental Health Measures. 2 2 Model χ df p χ /df ratio SRMR RMSEA [90% CI] CFI TLI Single-factor model 2159.055 135 <.001 15.993 0.153 0.160 [0.154–166] 0.805 0.779 Two-factor model 322.799 134 <.001 2.408 0.061 0.049 [0.042–056] 0.982 0.979 Note: N = 591. χ = chi square; df = degrees of freedom; SRMR = standardized root mean residual; RMSEA = root mean square error of approximation; CFI = comparative fit index; TLI = Tucker-Lewis index. theoretical structure of the instruments since the level of fit significant effect of the interaction between the support net- leads to rejecting the single-factor model. In contrast, the fit work and job insecurity on general mental health (β = .232; for the theoretical model (two-factors) is acceptable. p < .001), that is, the greater the support network, the lower Loadings factors are presented in Tables 5 and 6. the negative effect of job insecurity on general mental health. Only age showed a positive and significant effect on general mental health (β = .099; p = .043). Structural Equation Modeling The second model (Figure 2) was performed in the gen- To analyze the hypotheses, two SEMs were carried out. The eral sample, including financial threat, support network, and first model (Figure 1) was performed in the subsample of its interaction as antecedents of general mental health, con- workers, including job insecurity, support network, and its trolling for age, educational level, and gender (two people interaction as antecedents of general mental health, control- who were self-categorized as “other” were excluded from the ling for age, educational level, and gender (one person who analysis because it is not enough quantity to draw conclu- was self-categorized as “other” was excluded from the analy- sions; n = 589). In this model, Hypotheses 2, 3, and 5 were sis because it is not enough quantity to draw conclusions; analyzed. This measurement model has acceptable fit levels n = 393). In this model, Hypotheses 1, 3, and 4 were ana- (x /df = 1.288; SRMR = 0.052; RMSEA = 0.028 [0.022– lyzed. This measurement model has acceptable fit levels 0.033]; CFI = 0.986; TLI = 0.985) explaining 23.5% of the (x /df = 1.395; SRMR = 0.079; RMSEA = 0.032 [0.023– variance of general mental health. Hypothesis 2 was con- 0.040]; CFI = 0.977; TLI = 0.973) explaining 15.9% of the firmed since financial threat showed a direct significant neg- variance of general mental health. Regarding Hypothesis 1, ative effect on general mental health (β = −.309; p < .001). job insecurity showed a direct negative and significant effect The support network was positively and significantly related on general mental health (β = −.183; p < .001), and for to general mental health (β = .182; p = .012), confirming hypothesis 3, the support network was positively and signifi- Hypothesis 3. Regarding Hypothesis 5, the support network cantly related to general mental health (β = .322; p < .001). did not moderate the relationship between financial threat Regarding Hypothesis 4, the analysis shows a positive and and general mental health (β = .093; p = .199). Age (β = .205; 8 SAGE Open Table 5. CFA Factor Loadings for the Job Insecurity-General Mental Health Model. 95% Confidence interval Factor Indicator Estimate Std. Error z-value p Lower Upper GMH GMH_1 0.459 0.046 9.896 <.001 0.368 0.550 GMH_2 0.456 0.052 8.860 <.001 0.355 0.557 GMH_3 0.436 0.047 9.178 <.001 0.343 0.529 GMH_4 0.573 0.048 11.942 <.001 0.479 0.667 GMH_5 0.623 0.045 13.745 <.001 0.535 0.712 GMH_6 0.639 0.051 12.627 <.001 0.540 0.739 GMH_7 0.598 0.043 13.888 <.001 0.513 0.682 GMH_8 0.528 0.048 11.048 <.001 0.434 0.622 GMH_9 0.671 0.046 14.720 <.001 0.582 0.760 GMH_10 0.568 0.057 10.040 <.001 0.457 0.679 GMH_11 0.467 0.073 6.408 <.001 0.324 0.609 GMH_12 0.687 0.041 16.956 <.001 0.608 0.767 JI JI_1 0.856 0.034 25.156 <.001 0.789 0.922 JI_2 0.642 0.053 12.150 <.001 0.539 0.746 JI_3 0.827 0.034 24.240 <.001 0.760 0.894 JI_4 0.922 0.030 30.708 <.001 0.863 0.981 Note. GMH = General Mental Health; JI = job insecurity. Table 6. CFA Factor Loadings for the Financial Threat-General Mental Health model. 95% Confidence interval Factor Indicator Estimate Std. error z-value p Lower Upper GMH GMH_1 0.550 0.042 13.046 <.001 0.467 0.632 GMH_2 0.490 0.042 11.635 <.001 0.408 0.573 GMH_3 0.487 0.040 12.129 <.001 0.408 0.565 GMH_4 0.608 0.037 16.262 <.001 0.535 0.681 GMH_5 0.682 0.036 18.795 <.001 0.610 0.753 GMH_6 0.684 0.041 16.611 <.001 0.603 0.764 GMH_7 0.652 0.036 18.000 <.001 0.581 0.723 GMH_8 0.646 0.038 17.099 <.001 0.572 0.720 GMH_9 0.719 0.037 19.201 <.001 0.646 0.792 GMH_10 0.689 0.045 15.308 <.001 0.601 0.777 GMH_11 0.600 0.057 10.601 <.001 0.489 0.710 GMH_12 0.720 0.031 23.535 <.001 0.660 0.780 FT FT_1 0.817 0.033 25.120 <.001 0.754 0.881 FT_2 0.897 0.025 35.329 <.001 0.847 0.947 FT_3 0.891 0.025 35.434 <.001 0.842 0.941 FT_4 0.751 0.033 22.429 <.001 0.685 0.817 FT_5 0.764 0.033 23.201 <.001 0.699 0.828 FT_6 0.710 0.036 19.944 <.001 0.641 0.780 Note. GMH = General Mental Health; FT = financial threat. negative relationship between financial threat and general p < .001) and educational level (β = .082; p = .049) was posi- mental health and the moderating effect of the support net- tively related to general mental health. work on this relationship because having more children at home implies greater sensitive expenses and the need for a Complementary Analysis support network. We found that for those who have three or more children (n = 64; eliminating a participant that commit Bearing in mind that hypothesis 5 was not supported, we a typing error [children = 236]), the model explains a higher explored whether the number of children could deepen the Alcover et al. 9 Figure 1. This model tested hypotheses 1, 3, and 4 in the subsample of workers, including job insecurity, support network, and its interaction as antecedents of general mental health, controlling for age, educational level, and gender. The latent moderator variable (interaction) was included by multiplying the items pairs of job insecurity and support network as the observed values. percentage of the variance of the general mental health H4, a moderating effect of the support network was found in (38.6%), showing a significant direct effect of financial the relationship between job insecurity and general mental threat (β = −.491; p < .001), the support network (β = .289; health; but this moderation was not significant in the rela- p = .012), as well as their interaction (β = .177; p = .048). This, tionship between financial threat and general mental health, on the other hand, does not occur for the group of people who so H5 wasn’t confirmed. We discuss these findings below. report two children or less (n = 524), in which the model Job insecurity is perceived as a threat in Chile in the con- explains only 21.2% of the variance of the general mental text of the COVID-19 pandemic. However, job insecurity health, with a significant direct effect of financial threat scores are not extreme, which suggests that the sample’s edu- (β = −.292; p < .001), but neither the support network directly cation level, and therefore its perceived employability, might nor its moderating effect on the relationship between finan- play a protective role on the perception of job insecurity and cial threat and general mental health showed a significant its negative psychological consequences (De Cuyper et al., level (β = .164 and .090; p = .097 and .327, respectively). 2012; Green, 2011). Notwithstanding the above, some stud- ies have not identified a moderating effect of employability on the positive relationship between job insecurity and Discussion decreased psychological well-being (Cheng & Chan, 2008; Our results indicate, in line with H1 and H2, that people Kirves et al., 2011; Llosa et al., 2018). already perceived the impact of the COVID-19 pandemic The results show a statistically significant relationship during the first stage of the lockdown through job insecurity between job insecurity and mental health, agreeing with the and financial threat and that these perceptions related nega- evidence obtained in other socioeconomic contexts (Cheng tively to their general mental health. Likewise, confirming & Chan, 2008; Llosa et al., 2018; Sverke et al., 2002). The H3, a relationship between the support network and general current situation brought by COVID-19 fulfills some of the mental health was observed. Additionally, consistent with conditions that characterize job insecurity according to Shoss 10 SAGE Open Figure 2. This model tested hypotheses 2, 3, and 5 in the general sample, including financial threat, support network, and its interaction as antecedents of general mental health, controlling for age, educational level, and gender. The latent moderator variable (interaction) was included by multiplying the items pairs of financial threat and support network as the observed values. (2017)—lower control and lower volition—since the impact distribution, with an identical effect of psychological distress generated by the pandemic has been sudden and uncontrol- (e.g., Kopasker et al., 2018). lable for governments and organizations, and workers alike. In previous crises brought about by epidemics and pan- Although the long-terms effects are still unknown (Shoss, demics, the effects of financial threats are present during the 2017), it must be remembered that Chile had undergone a quarantine period, especially, in the medium and long term “social uprising” in October and November 2019 with con- (Brooks et al., 2020; Jeong et al., 2016). Thus, given that our sequential social and economic effects, that could also con- study was completed during the earliest stage of the COVID- tribute to increasing the perception of job insecurity. 19 pandemic, it is foreseeable that the economic stressors Parallel to this, results show a perception of financial will increase as the current situation endures. Prior research threat at values slightly above scale’s midpoint. The rela- is consistent in showing that the negative and adverse effects tively rapid measure approved by the Chilean Senate and of repeated financial threats (Watson & Osberg, 2017), asso- Congress to make unemployment insurance more flexible ciated with both job insecurity and unemployment, are mul- due to the COVID-19 emergency (March 31), which tiple and severe for people and their personal and social extended coverage for the most vulnerable sectors, could environments—affecting in particular social relations and control the perception of immediate financial risk. The find- family functioning (Klehe et al., 2012; Probst, 2005); there- ing that perceived financial threat is correlated with general fore, the outcomes obtained in this study can serve to warn of mental health is consistent with previous findings after the the foreseeable consequences for mental health in an employ- effects of large economic recessions (Fiksenbaum et al., ment and economic situation that may continue over time. 2017; Marjanovic et al., 2013, 2015; Netemeyer et al., 2018). The results show that the perceptions of job insecurity There is an increasing body of evidence that economic inse- and financial threat are significantly related to each other curity is experienced the same regardless of the income which agrees with what has been found in previous studies Alcover et al. 11 in situations of recent large-scale economic crises (Lam obtained concerning the lack of effect of the support network et al., 2014; Rajani et al., 2016). In addition, both are asso- with financial threat may be due to the perception that eco- ciated with a decline in perceived mental health, which is nomic insecurity has a generalized impact, not limited to also consistent with prior results (e.g., Klehe et al., 2012; one’s situation. Consequently, there is no expectation of Kopasker et al., 2018; Rajani et al., 2016), thus agreeing in receiving help from the support network to deal with eco- part with the prior evidence (Greenhalgh & Rosenblatt, nomic problems. 1984), but not with the results obtained by Rajani et al. Although the debate on what is the average size of peo- (2016) in the context of the Great Recession of 2008 in ple’s support network (around 150; Hill & Dunbar, 2003) is European countries, which conclude that job insecurity and currently still open, when distinguishing between the size of financial worries affected mental health in the same way. the close support group (family and friends), the sympathy Nor are they in line with those obtained in Sweden by group, and the rest of the support network, the size of the Richter et al. (2014), who confirmed that job dependency former is usually the smallest, ranging from 5 to 20 members due to economic issues did not mitigate the relation between (Pollet et al., 2011; Wrzus et al., 2013). However, this num- job insecurity and psychological well-being. These discrep- ber also varies across age groups and may also be sensitive to ancies with some prior research may be because in Chile, national culture (Wrzus et al., 2013). In our study, the sup- social protection systems are much less robust than those port network of the participants can be considered medium generally available in European Union countries with wel- size (mean of 8.13); what seems important is the perceived fare states (Rajani et al., 2016), and in particular in Sweden effectiveness of this network to manage job insecurity and (Richter et al., 2014), and they are close to those that pre- financial threat. Given that the response on the support net- dominate in the US (Greenhalgh & Rosenblatt, 1984). work includes family members and close friends, it can be Thus, in Chile, where the population generally carries high inferred that the perception of social support in case of need debt levels and a fragile unemployment insurance system, has a reasonable level of certainty. This perception of pri- people who view their financial situation with concern mary, reliable, and robust bonds directly affects the reception react more negatively to the threat, which is reflected in of various types of social support (Thoits, 2011). The partici- their mental health. In this sense, we argue that the moder- pants seem to perceive that the support network is a powerful ating effect of the support network will be higher if the per- resource to cope with financial stress and job insecurity. In son is responsible for a larger number of children, which addition to this direct influence, the perception of the support generates a considerable difference in terms of financial network may also expand through the experience of trust, expenses in this country. In line with the previous reason- where its members increase their social capital through their ing, the complementary analysis provided in the results sec- contacts. tion shows that when comparing those who report three or Finally, although more than 2 years have passed since the more children with those who have two or fewer, the results pandemic started and several studies have been published showed that the direct effect of the support network and its about the effect of variables related to financial stress, job interaction with financial threat is only related to a low insecurity or social support, between others, and mental decrease to general mental health in the group of up to three health (e.g., de Miquel et al., 2022; Göktaş & Özdinç, 2022; children. Additionally, the percentage of variance explained Mousa & Samara, 2022; Said et al., 2022; Yao & Wu, 2022) by these models is greater in this group, which is why these the results obtained are still timely and relevant. The psycho- variables, to a large extent, explain the worsening of gen- logical reaction in a situation of abrupt limitation of social eral mental health in the group with more dependents. Prior routines, such as the beginning of the lockdown, is not results (Kopasker et al., 2018) also show that the negative exhausted in this event, and it can be extrapolated to other effects of economic insecurity are greater in men, who, due hard and inadvertent situations. Thus, these findings help to to socioeconomic and cultural reasons, continue to be the better understand and to be prepared for other public health main providers in families, as can also occur in Chile. crises, natural disasters, and armed conflicts, among other Finally, the study results indicate a medium moderating situations, that can profoundly affect people’s lives. effect of the support network since it moderates the associa- tion of job insecurity with the decline in perceived mental Practical Implications health. In contrast, this moderating effect is not found for financial threat in the general sample, and it is only observed First, the outcomes obtained have direct practical implica- among those who have three or more children. These results tions related to the need to implement psychological support are similar to those obtained in previous studies about both measures for workers and the unemployed to equip them constructs (Cheng et al., 2014; Näswall et al., 2005; Whelan, with coping strategies to manage uncertainty and stress. 1993), although we have not found differences between men These psychosocial supports should be available in organiza- and women in terms of the moderating effect of perceived tions, and primary care centers to be accessible and have an social support, as other studies have found concerning job ongoing positive effect on mental health in the medium and insecurity (Menéndez-Espina et al., 2019). The result long term (Pfefferbaum & North, 2020). 12 SAGE Open Second, the conclusions drawn here should serve as an Additionally, and fifth, occupational health, job insecu- alert to the risk that the double perception of job insecurity rity, and job precariousness are three of the 10 critical areas and financial threat can generate by increasing psychological for research and practice in WOP due to the impact on them self-pressures of productivity and the over-commitment to by COVID-19 as identified by experts (Rudolph et al., the job, one of the first consequences that have already been 2021); thus, this study makes an important contribution to detected since the pandemic began (Mukhtar, 2020; Stanhope knowledge in this context, but it must be broadened or & Weinstein, 2021; Zhang et al., 2021). The COVID-19 cri- complemented. sis place explicit or implicit demands that are responded to by people with work overload, increasing working days (in Limitations and Future Research person or remotely), reducing or giving up days off or vaca- First, the cross-sectional nature of the design only allows us to tion days, or accepting abusive working conditions that can identify relations between the variables. However, the impor- also increase the perception of qualitative job insecurity tance of having preliminary data on the disruptive impact (Hellgren et al., 1999), lower perceived control and the caused by the scale and speed of the global pandemic in Chile resulting negative effects on mental and physical health justifies the urgency of obtaining an initial approach to the con- (Vander Elst, Richter et al., 2014; Zhang et al., 2021). sequences for the mental health of work-related variables. Therefore, it seems urgent to regulate and monitor working Second, the participants in our study did not form part of a conditions compliance during the COVID-19 crisis and the probabilistic sample, at the outcomes cannot be generalized so-called “new normal” in the post-pandemic period. In this to the Chilean population. Also, in this case, future studies sense, it is necessary to guarantee the workers’ and unem- should include representative samples or concentrate groups ployed labor rights so that their job insecurity (subjective and of workers, specific people or contexts (concrete professions, objective) does not increase. In a similar vein, it is advisable young or older workers or vulnerable groups, etc.) to most to ensure that the new work arrangements (e.g., teleworking accurately identify the differential effects of “Coronanomics” or hybrid work) do not have negative psychosocial conse- in each setting. quences, such as work-family conflict. These measures can Third, our measure of support network calls for quantity favor the maintenance of appropriate well-being and physi- and lacks assessment of the quality of the social network. cal and mental health levels. Further studies should include an additional measure of close- Third, the results also have important implications for ness/frequency of connections, abusive/negative relationships, designing strategies and psychosocial interventions that can symmetrical/asymmetrical relationships, and so on. strengthen support networks and potential social support. Fourth, the influence of gender on the results was con- Given the strong connections between social relations, sup- trolled in both models analyzed. Despite this, the sample port, and mental health (House et al., 1988; Uchino, 2006), imbalance in this variable can be considered a possible actions aimed at reinforcing interpersonal ties and support study’s weakness. networks through, for example, support groups, community Finally, and fifth, this study has only considered the vari- initiatives, or networks of people who share similar charac- ables mentioned as moderating antecedents and consequents, teristics (studies, profession, etc.) (Cohen et al., 2000) can be but we are aware that in the experiences people are living highly effective at equipping those who experience financial during this economic and health crisis, other personal, fam- threat and job insecurity with social coping and resilience ily, organizational and social variables are involved that resources that increase personal resources. Despite being interact in a complex way, which is reflected in the rather subjective perceptions, financial and job insecurity have low percentage of variance explained by the contrasted mod- objective components, such as contractual status, the volume els. The inclusion of variables such as gender, contract sta- of layoffs in a productive sector or level of unemployment in tus, work-family conflict or cultural differences, among a region (Ellonen & Nätti, 2015; Helbling & Kanji, 2018) others (Kniffin et al., 2021), in future studies will be needed and, consequently, are not an individual but a collective to understand the real impacts and to design strategies and problem; therefore, the possible tools to confront them will interventions that can prevent, reduce or alleviate the effects also need to be collective and social. In this regard, organiza- for the well-being, health, and safety of people and their fam- tional measures that can be beneficial in preventing negative ilies as well as for the functioning and effectiveness of mental health consequences are those aimed at reducing organizations. financial threat levels. Thus, employers may, for example, offer advice, counseling, or training on financial and debt Acknowledgments management and planning for health care, mortgage, or col- lege costs, as well as subsidizing employee lunches and We are grateful for the support of Matías Arriaga in the data analy- transportation costs. In terms of government measures, regu- sis process of this study. lations and laws aimed at increasing coverage for temporary Data Availability Statement and long-term unemployment and those aimed at avoiding gender discrimination, especially in the case of female work- The data corresponding to this study is available on Open Science ers with family responsibilities, would also be beneficial. Framework (OSF) website (https://osf.io/p7xdf/; Salgado, 2020). Alcover et al. 13 Declaration of Conflicting Interests Caroli, E., & Godard, M. (2016). Does job insecurity deterio- rate health? Health Economics, 25(2), 131–147. https://doi. The author(s) declared no potential conflicts of interest with respect org/10.1002/hec.3122 to the research, authorship, and/or publication of this article. Chan, A., Malhotra, C., Malhotra, R., & Ostbye, T. (2011). Living arrangements, social networks and depressive symptoms Funding among older men and women in Singapore. 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Job Insecurity, Financial Threat, and Mental Health in the COVID-19 Context: The Moderating Role of the Support Network

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SAGE
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© The Author(s) 2022
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2158-2440
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2158-2440
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10.1177/21582440221121048
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Abstract

The aim of this study is two-fold. Firstly, to analyze the relations between the perceptions of job insecurity and financial threat and general mental health during the early stage of the COVID-19 pandemic. And secondly, to identify the potential moderating effect of the support network. We carried out a cross-sectional study on a non-probabilistic sample aimed at a general Chilean adult population to analyze this. The results show that both job insecurity (β = −.183; p < .001) and financial threat (β = −.309; p < .001) are associated with a decline in general mental health. Likewise, the results indicated a positive relationship between support network and general mental health in the two models analyzed (βs = 0.322 and 0.182; ps < 0.001 and = 0.012, respectively), as well as a moderating effect of support network on the relationship between job insecurity and decreased general mental health (β = .232; p < .001). The theoretical and applied scope of these findings are analyzed, and their challenges and limitations are discussed. Keywords job insecurity, financial threat, general mental health, social support, support network, COVID-19 Research conducted in the last two decades, mainly since Introduction the beginning of the Great Recession of 2008, has uncovered The disruptive effects of social distancing, confinement, and the relationship between perceptions of risk in employment quarantine adopted to confront the COVID-19 pandemic and its accompanying financial risk with a myriad of conse- have affected multiple vital areas. Since March 2020, with quences for people’s well-being and health. Job insecurity the rapid expansion of the pandemic throughout the world, (e.g., Burgard et al., 2009; Lübke, 2021) and financial inse- work activities have changed drastically. On the one hand, curity (e.g., Kiely et al., 2015; Rajani et al., 2016) negatively governments and businesses imposed or recommended affect physical, mental, and psychosocial health. Both can working from home or remotely, which affected all activi- directly affect mortality when health is fragile (László et al., ties, except for important sectors and services in which 2010) and can lead to suicidal behaviors (Yip et al., 2007). being present was essential, such as hospitals, primary prod- Insecurity also can affect family and partner relationships uct sourcing, pharmacies, food sales, etc. On the other hand, (Mauno et al., 2017). Concerning the immediate conse- a large number of companies in the industrial and service quences of the COVID-19 pandemic, some studies have sector suddenly suspended their activities, affecting most of detected the negative effects of job insecurity, financial con- the commerce, small services, and hospitality businesses as cerns, and economic hardship on mental health (Dawel et al., well as the industry in activities considered non-essential; this resulted in the loss or temporary layoffs for a large num- ber of workers. The economic implications of the global Universidad Rey Juan Carlos, Madrid, España Universidad de La Frontera, Temuco, Chile pandemic, called “Coronanomics” (Eichengreen, 2020), are Universidad de Concepción, Chile still difficult to estimate in all their macro and micro magni- tude on a worldwide scale and per country (Barua, 2020). All authors are equally contributed. However, the effects on people and their families who lost Corresponding Author: jobs, suffered temporary layoffs, or kept jobs but worried Sergio Salgado, Departamento de Administración y Economía, Universidad about possible loss or deterioration in working conditions de La Frontera, Av. Francisco Salazar 01145, Temuco 4811230, Chile. Email: sergio.salgado@ufrontera.cl must be analyzed. Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open 2020; Ganson et al., 2021; Obrenovic et al., 2021; Wilson affective components related to the emotional reactions to job et al., 2020; Witteveen & Velthorst, 2020). loss or potential job change. The meta-analysis of Jiang and At the same time, previous research has shown the mod- Lavaysse (2018) shows that affective job insecurity was more erating effect of support networks and social support on the strongly related to correlates and outcomes, such as affective negative impact of job insecurity (Näswall et al., 2005; commitment or turnover intention, than cognitive job insecu- Schreurs et al., 2012). Thus, the support received at work rity. However, most research has used the one-dimensional per- can mitigate the negative effect of job insecurity on specific spective of quantitative job insecurity (De Witte, 2000; Sverke work-related outcomes, such as job dissatisfaction and non- & Hellgren, 2002; Vander Elst, De Witte et al., 2014). This is compliant job behaviors. There is also empirical evidence the approach adopted in this study. of the moderating role of instrumental social support in the Extensive prior research has identified three relevant relationship between financial stress and psychological effects of job insecurity. First, meta-analytic studies have well-being and psychosomatic disorders (Åslund et al., shown an overall negative impact of insecurity on general 2014). This effect has also been verified for emotional sup- mental health (Cheng & Chan, 2008; Sverke et al., 2002) on port (Whelan, 1993). specific disorders such as anxiety, depression, as well as on In Chile, where this study was conducted, social distancing decrease in psychological well-being, emotional exhaus- and confinement were adopted in mid-March 2020. This deci- tion, or life dissatisfaction (Llosa et al., 2018). Job insecu- sion meant shutting down and closing multiple productive rity is also associated with increased anxiety, irrational activities with the resulting temporary layoff or suspension of thoughts, and psychological distancing at work. Furthermore, the work contract for a high number of workers. Likewise, the negative effects of job insecurity have also been found on anti-pandemic measures increased the uncertainty about future physical health, including headaches or eyestrain and skin job continuity for many employees in vulnerable work situa- problems (Caroli & Godard, 2016), and incident coronary tions. To analyze the potential negative consequences of these heart disease (Virtanen et al., 2013). experiences, the aims of this study are two-fold. Firstly, to ana- Second, the negative effects of job insecurity on health lyze the relationship between the perceptions of job insecurity indicators and life satisfaction are greater in workers with and financial threat and general mental health during the first low levels of employability or lack of opportunities to find a month of the pandemic in a sample of the Chilean adult popu- new job in case of losing the current one (Caroli & Godard, lation. The second aim was to identify the potential moderat- 2016). These effects are compounded for people over ing effect of the support network on the relationship between 40 years of age (Otterbach & Sousa-Poza, 2016). the two variables. Thus, our goal was to carry out an initial Finally, an indirect effect of job insecurity on health can analysis of how work and economic factors can affect people’s occur when people reduce their investments in health to save mental health in a context of a prolonged health emergency for coping with a possible job loss. Although this potential and the accompanying economic crisis. effect could only be verified in the long term (Caroli & Godard, 2016), it is essential to consider it as a factor that increases the accumulated vulnerability of workers with Theoretical Background and fewer resources since there is evidence that job insecurity Hypothesis also affects negatively daily expenses and some major life decisions (Otterbach & Sousa-Poza, 2016). Consequences of Job Insecurity on Mental Health Specifically, some studies conducted since the beginning and Health Correlates of the COVID-19 pandemic have shown that greater job Job insecurity refers to “the perceived threat of job loss and the insecurity and job loss were related to greater depressive worries related to that threat” (De Witte, 2005, p. 1). It is a symptoms (Wilson et al., 2020; Witteveen & Velthorst, subjective anticipatory perception, the core of which is concern 2020). Additionally, recent or expected employment loss of a and fear regarding the future of one’s current job in the short or nuclear family member was associated with a greater risk of medium term. Such concerns include involuntary loss of one’s poor mental health, measured via four anxiety and depres- job with all the related negative consequences for well-being sion measures (Ganson et al., 2021). Consequently, in this and mental health, job attitudes and behaviors, and quality of pandemic context, this study analyzes the relationship life (Sverke & Hellgren, 2002; Vander Elst, De Witte et al., between job insecurity (and the other variables included in 2014). Further, experiences of job insecurity depend on three this work) with a general mental health screening, operation- threat features: perceived situational control, threat duration, alized through the General Health Questionnaire (Goldberg and volition (Shoss, 2017). Consequently, lower control, lon- & Williams, 1988). ger-term, and lower volition will cause increased distress in Based on these rationales and prior data, we formulate the workers (Shoss, 2017), with detrimental effects on personal following hypothesis: physical and psychological health and work-related well-being (De Cuyper et al., 2019; Lübke, 2021; Shoss, 2017). Finally, H1: In the COVID-19 pandemic context, the perceived other authors (Jiang & Lavaysse, 2018) have proposed differ- job insecurity is negatively related to general mental entiating the cognitive components of job insecurity from the health. Alcover et al. 3 The combination of job insecurity and financial insecurity Consequences of Financial Threat on Mental or risk significantly affects vitality and mental health (Rajani Health and Health Correlates et al., 2016). Also, it has been demonstrated (Lam et al., The financial threat is an emotional state that refers to “self- 2014) that in situations of economic turbulence (such as reported fearful-anxious uncertainty regarding one’s current great crises and recessions, or like the one caused by the and future financial situation” (Fiksenbaum et al., 2017; see COVID-19 pandemic), workers perceive a loss of sense of also Marjanovic et al., 2013). Financial threat perception, or control (Glavin, 2013), so that the adverse effects of job inse- financial distress, is usually associated with people or house- curity on mental health are even higher. Wilson et al. (2020) holds that experience job insecurity when their jobs are less found that greater job insecurity due to COVID-19 was indi- secure and have low protection against unemployment rectly related to greater anxiety symptoms due to greater (Giannetti et al., 2014). Data confirms that the financial financial concern. threat is higher for people who experience many economic Based on these rationales and prior data, we formulate the problems in their everyday life (Marjanovic et al., 2015). following hypothesis: Economic challenges can also become a chronic stress situa- tion in families, which can generate distressing thoughts H2: In the COVID-19 pandemic context, the perceived about paying household expenses and can lead to feelings of financial threat is negatively related to general mental fear, anxiety, and uncertainty regarding one’s ability to main- health. tain the current standard of living (Fiksenbaum et al., 2017; Marjanovic et al., 2013). Support Network as a Moderator in the Prior research has found that economic insecurity is a Relationship Between Job Insecurity, Financial socio-economic determinant of mental health (Kopasker Threat, and General Mental Health et al., 2018). The financial threat preceded or not by debts already incurred is associated with greater psychological dis- Prior research shows a direct association between social rela- tress, characterized by higher levels of depression, anxiety, tionships and mental health (House et al., 1988; Uchino, and fatigue (Fiksenbaum et al., 2017), lower subjective well- 2006). In the study of these associations, social connections being (Netemeyer et al., 2018), greater emotional exhaustion have been conceptualized in terms of a structural perspec- and lower psychological well-being (Marjanovic et al., 2015), tive, namely social networks (with properties such as size and psychological distress and mental health issues and composition); and from a functional perspective or the (Marjanovic et al., 2013). Additionally, it has been shown that social support stance, understood as the subjective feeling of the perception of future financial risk (without future unem- being supported by others (Santini et al., 2015). ployment necessarily occurring) affects mental health more Studies about the role of social networks on mental health negatively than actual volatility, affecting all income levels informed that restricted social networks could turn into social and being more detrimental for men (Kopasker et al., 2018). isolation and negatively impact mental health and life satis- Worry and rumination about financial risk can also exacer- faction (Harasemiw et al., 2019). Also, weak social networks bate negative consequences on mental health, psychological have been associated with higher depressive symptoms well-being, and cognitive functioning (de Bruijn & Antonides, among men and women (Chan et al., 2011). Moreover, stud- 2020). It has also been found that the perception of financial ies on older people have stated the association between risk mediates the relation between economic difficulties and depression and social isolation (Landeiro et al., 2017) and suicidal thoughts, and cognitive confusion/bewilderment loneliness (Tomaka et al., 2006), confirming the protective affects women and men equally (Fiksenbaum et al., 2017). role of social connectedness for mental health. Additionally, Specifically, analyses of representative samples of active there is evidence about the role of social networks on job members of the labor force of six European countries indi- insecurity. Studies stated the negative relationship between cated a positive relationship between immediate economic solid ties and job insecurity (Mehreen et al., 2019) and the hardships during the COVID-19 lockdown and indicators of moderating effect of social networks on the financial strain mental health deterioration, such as feelings of depression and depression (Sicotte et al., 2008). and health anxiety (Witteveen & Velthorst, 2020). This asso- From the social support view, the protective effect of the ciation between financial hardship and poor mental health is perceived social support on mental health and wellbeing has more pronounced when workers have a lower occupational a long trajectory in psychosocial research (Thoits, 2011). In status. In a similar vein, Wilson et al. (2020) found that greater their classic study, Cohen and Wills (1985) found support for financial concern due to COVID-19 was related to greater the moderating model when social support refers to the per- anxiety symptoms in a sample of employed U.S. individuals, ceived availability of interpersonal resources that respond and Dawel et al. (2020) found that financial distress due to the directly to people who are experiencing stressful events. pandemic consequences was a key correlate of poorer mental Given that both job insecurity and financial threats constitute health in Australian population measured via anxiety, depres- powerful work-related stressors (De Witte, 2005; Fiksenbaum sion, and psychological well-being measures. et al., 2017; Marjanovic et al., 2013; Sverke & Hellgren, 4 SAGE Open 2002), identifying the potential moderating effect of social H5: In the COVID-19 pandemic context, support network support from a person’s social network is of great relevance moderates the relationship between financial threat and to offsetting their negative consequences for health. general mental health. Theoretical models (Greenhalgh & Rosenblatt, 1984) and previous studies have demonstrated that social support Materials and Methods moderates the negative effects of job insecurity on work outcomes, such as job satisfaction and vigor (Cheng et al., A cross-sectional correlational study was conducted on a 2014), and on well-being and mental health (Lim, 1996; non-probabilistic sample of the general Chilean adult popu- Näswall et al., 2005). It has also been found that women lation. The project underwent assessment by an Ethics and use social support more often and efficiently than men Bioethics Committee (# 650-2020, March 2020). (Matud, 2004). These results were confirmed in a recent study that showed that when women actively access their Sampling Strategy social support network, this acts as a buffer for the nega- tive consequences of job insecurity (Menéndez-Espina The Government of Chile began to decree social distancing et al., 2019). These conclusions agree with Cohen and and confinement measures on March 16, 2020, and they pro- Wills (1985) that the effectiveness of this interpersonal- gressively increased restrictions on productive, commercial, social resource depends on it serving specifically to man- and consumption activities as different regions detected con- age the stressful situation. However, another recent study tagions and deaths. The data were collected via an online (Giunchi et al., 2019) clarified previous results that sup- questionnaire (Questionpro) between March 24 and April 23. ported the moderating effect of the perception of social The recruitment strategy combined professional networks, support, as they showed that the negative relationship social networks, professional associations, undergraduate between job insecurity and psychological well-being is and graduate students, and personal contacts who were reduced when the perception of job insecurity is low, but invited to participate and disseminate this invitation among not when it is high. their network of contacts (snowball strategy). Before begin- There is also empirical evidence of the moderating role ning the study, the participants read and signed informed of instrumental social support in the relationship between consent. Participants took an average of 27 minutes to com- financial stress and psychological well-being and psycho- plete all the instruments. When necessary, they could save somatic disorders (Åslund et al., 2014) and in the relation- their progress and take it up again when convenient. The bat- ship between financial stress and alcohol-related behaviors, tery of questionnaires included other instruments not consid- including drinking to deal with problems, excessive con- ered in this study that corresponds to a complementary line sumption of alcohol and problems with alcohol (Peirce of research aimed at exploring several personal and social et al., 1996). The moderating effect has been verified for factors that could affect people’s well-being and health in the instrumental and emotional social support (Whelan, 1993). context of the COVID-19 pandemic. These last results lead to the assumption that instrumental A total of 591 participants completed the study (592 full support can serve as a strategy centered on confronting the responses to the online questionnaire were obtained, of problem. In contrast, emotional support can be used as a which a duplicate case identified through the informed e-mail strategy centered on negative emotional responses. These was eliminated). All the participants resided in Chile. relations may be important in designing interventions to reduce the negative effects of insecurity and financial Instruments threats. Although social network and social support are separated Job insecurity. Job Insecurity Scale (De Witte, 2000) variables, both are closely related and provide a comprehen- was used, adapted, and validated in Spanish (Vander Elst, sive view of the role of social relationships as sources of cop- De Witte et al., 2014). It includes four items (e.g., “I fear ing with environmental and work stressors. To combine that I might lose my job”) scored on a 6-point Likert scale social network and social support perspectives, we adopt the (1 = Strongly disagree to 6 = Strongly agree). This measure notion of support network: the number of close bonds or inti- has shown acceptable reliability and validity in the literature mate relationships that provide support. (Cronbach’s alphas generally above 0.80; e.g., Vander Elst, Based on these rationales and prior data, we formulate the De Witte et al., 2014). following hypothesis: Financial threat. The Financial Threat Scale adapted to H3: In the COVID-19 pandemic context, the support net- Spanish (Marjanovic et al., 2015) was used to measure this work is positively related to general mental health. construct. The instrument contains six items (e.g., “How H4: In the COVID-19 pandemic context, support network much do you feel threatened by your financial situation?”) moderates the relationship between perceived job insecu- that are evaluated on a 5-point Likert scale (1 = Not at all; rity and general mental health. 5 = A great deal). The scale has shown acceptable reliability Alcover et al. 5 and validity in the literature (Cronbach’s alphas generally it is recommended a critical ratio of multivariate kurtosis above .80; e.g., Marjanovic et al., 2015). lower than 5 (Bentler, 2005; Byrne, 2010). The internal con- sistency reliability was examined using Cronbach’s alpha General mental health. To measure the perception of gen- (α), McDonald’s omega (⍵), and composite reliability eral mental health, the 12-item version of the General Health (C.R.), for which values above .80 are considered acceptable Questionnaire (Goldberg & Williams, 1988) was used in (Hair et al., 2014; Lance et al., 2006). Convergent validity its version previously applied in Chile (Garmendia, 2010; was tested through the average variance extracted (AVE), for Rivas-Diez & Sánchez-López, 2014). This instrument is which values greater than 0.50 are considered acceptable widely used for mental health screening (Gnambs & Staufen- (Hair et al., 2014). biel, 2018). It contains 12 questions (e.g., “Are you able to As this is a cross-sectional study, it is important to control concentrate on what you do?,” “Have you felt constantly the effect of the common method variance (CMV) and to ana- under strain?,” “Have you felt unhappy or depressed”) lyze the discriminant validity of the measures. Strategies for answered on a 4-point Likert scale (1 = Never; 4 = Always). CMV were used a priori and post hoc. Regarding the a priori Although more than one underlying factor has been detected strategy, instruments with different scale formats were used in in the literature, the instrument’s structure is recognized as this study, which helps to prevent CMV (Podsakoff et al., essentially one-dimensional. This way it is used in the pres- 2012). Regarding the post hoc strategy, the Harman single fac- ent study as recommended (Gnambs & Staufenbiel, 2018). tor test was carried out via exploratory factor analyses (Chang Literature has reported reliability and validity for this instru- et al., 2010). This is the most widely used method to examine ment (Cronbach’s alphas above .85; e.g., Garmendia, 2010; the pernicious presence of CMV (Podsakoff et al., 2003; Rivas-Diez & Sánchez-López, 2014). Tehseen et al., 2017). The assumption is that if CMV exists, the first not rotated factor (eigenvalue >1) on a principal com- Support network. The support network was measured by a ponents analysis that includes all the involved items account single item about the size of the family/friends support net- for more than 50% of the variance. work (i.e., Approximately, how many close friends or rela- Discriminant validity was analyzed in two ways. First, we tives do you have? (people with whom you get along and test if the correlation between constructs is lower than the can talk to about everything happening). This measure is square root of the AVE for any single latent construct. included in the Medical Outcome Study (MOS) social sup- Second, the scales’ confirmatory factor analysis (CFA) was port survey (Sherbourne & Stewart, 1991). The use of single performed in two steps. The first step analyzes the fit of a items in general, and social support measures, in particular, model in which the items of the different scales are collapsed has already been widely discussed and accepted as appropri- in a single-latent variable. Then, the fit of the theoretical ate in the field of occupational health (Fisher et al., 2016), model is analyzed. The discriminant validity of the con- and previous research has shown that it is a good predictor of structs is sustained when the fit of the single-latent model is health outcomes (e.g., Janevic et al., 2004). not satisfactory and the theoretical model shows an accept- able level of fit (Anderson & Gerbing, 1988). Control variables. The variables gender, age, and educa- To test the hypotheses, structural equation modeling tional level were included in this study as control variables. (SEM) was performed. The latent moderator variable was The decision to include these control variables is based on included by multiplying the items pairs of the corresponding those employed in previous studies in this research field variables as the observed values (Schumacker, 2002). (e.g., Bentley et al., 2019; Hellgren & Sverke, 2003; Wat- Both CFA and SEM used the diagonal weighted least son & Osberg, 2017) and in particular, in studies conducted squares method (DWLS; Muthén, 1993) with robust estima- during pandemic-induced confinement (see specifically, e.g., tion of errors. This method is recommended for models Dawel et al., 2020; Ganson et al., 2021; Wilson et al., 2020; including continuous and categorical variables (Kline, 2016). Witteveen & Velthorst, 2020). It is also effective for small samples and variables that are not normally distributed (Rhemtulla et al., 2012). The evalu- ation of the models fit considered the following criteria to be Data Analysis considered acceptable: χ /df ratio <3, root mean square error First, we analyzed univariate and multivariate normality. of approximation (RMSEA) ≤0.06, standardized root mean There is no consensus regarding an acceptable degree of uni- square residual (SRMR) ≤0.08, comparative fit index (CFI), variate non-normality, but cut-off values are often +/3 and and Tucker-Lewis index (TLI) ≥0.95 (Hu & Bentler, 1999). ±7 for skewness and kurtosis, respectively (Curran et al., Z-scores for all the observed variables were used in the anal- 1996; DeCarlo, 1997). Multivariate normality was tested ysis. For processing data, JASP, an open-source software, using Mardia’s coefficient. In this regard, two criteria are and Lavaan were used (JASP Team, 2021; Rosseel, 2012). considered: (a) it is recommended a critical ratio of multi- The analyzes related to the financial threat variable are car- variate kurtosis lower than ±1.96 (p > .05); (b) taking into ried out on the total sample (n = 591). The analyses involving account that the p-value could be affected by the sample size, job insecurity measures are carried out on the subsample that 6 SAGE Open Table 1. Demographic Information of the Participants. being so restless or agitated that you have been moving from one place to another more than usual”) in which the responses Parameters were accumulated to a greater extent in the central scores of Total sample, n 591 the scale. On the other hand, the variable support network Gender, n (%) showed skewness and kurtosis outside the range that would Female 449 (76) indicate a normal distribution (4.418 with a critical ratio >43; Male 140 (23.7) and 33.360 with a critical ratio >160, respectively) which is Other 2 (0.3) consistent with previous research where this variable has Mean age in years, M (SD) 37.63 (12.85) been freely reported as a continuous measure (e.g., Bruine de Mean children, M (SD) 1.28 (9.74) Bruin et al., 2020; Fung et al., 2001). This occurs because Occupational status, n (%) most people have a small support network, and very few have Full-time job 269 (45.5) a large one, which was an expected distribution. Part-time job 43 (7.3) Regarding multivariate normality, Mardia’s coefficients Independent worker 82 (13.9) do not support this assumption (kurtosis >100; critical ratio Student 79 (13.4) >37; p < .001). Unemployed 55 (9.3) Retired 30 (5.1) Internal Consistency Reliability and Convergent Household work 24 (4.1) Other 9 (1.5) Validity Completed educational level, n (%) Cronbach’s alpha (α), MacDonald’s omega (⍵), composite Graduate studies 222 (37.6) reliability (C.R.), and the average variance extracted (AVE), Undergraduate studies 256 (43.3) together with means, standard deviations, and latent variable Technical/professional studies 49 (8.3) correlations are shown in Table 2. Results show acceptable High school 63 (10.7) internal consistency levels when observing the Cronbach’s Elementary school 1 (0.2) alpha, McDonald’s omega, and composite reliability (>.8). Urban or rural place of residence, n (%) Urban area 550 (93.1) Regarding convergent validity, AVE values show acceptable Rural area 41 (6.9) levels (>0.5), except for general mental health, which is Region of residence in Chile (the most represented are lower than the benchmark. However, we can accept its AVE shown), n (%) value of 0.4 in combination with composite reliability higher Bio-Bio 213 (36) than 0.6 (Fornell & Larcker, 1981), and having in mind that Metropolitan area of Santiago 137 (23.2) it is a widely used measure, so keeping all the items allows La Araucanía 121 (20.5) better comparability of the results. Valparaiso 36 (6.1) Los Lagos 17 (2.9) Common Method Variance (CMV) and Discriminant Validity includes full-time, part-time, and independent workers Harman’s test showed that the first not rotated factor (eigen- (n = 394). Z-scores for the analyzes were calculated into the value >1) explains 26.83% of the variance; thus, CMV does corresponding sample. not affect covariance among variables. Regarding discrimi- nant validity, the diagonal of Table 2 presents the square root of AVE, showing in all cases values higher than the latent Results variable correlations, which support the discriminant validity The demographic information of the participants is presented of the variables. in Table 1. It is observed that females and people with higher education are more represented. The latter may be because Confirmatory Factor Analyzes the snowball technique used to obtain the sample started from networks and contacts close to the university context. The factorial structure of the scales was analyzed in two CFAs. Model 1 included the measures of job insecurity and general mental health in the subsample of workers (n = 394). Univariate and Multivariate Normality Model 2 included the financial threat and general mental Regarding skewness and kurtosis, the items of both financial health measures in the general sample (n = 591). As seen in threat and job insecurity scales showed values within the Tables 3 and 4, these analyses were carried out in two steps. acceptable range, except for one item of the general mental First, it was tested whether a single-factor model fit the data, health scale that showed a kurtosis over 4 (“Moving or speak- and then the hypothesized theoretical model was analyzed. ing so slowly that others may have noticed. Or the opposite: The results supported the discriminant validity, and the Alcover et al. 7 Table 2. Mean, Standards Deviation, Cronbach’s Alpha, McDonald’s Omega, Composite Reliability, Average Variance Extracted and Latent Variable Correlations. Variable Mean SD α ⍵ C.R. AVE 1 2 3 4 1. JI 3.040 1.478 .886 0.895 0.888 0.669 (0.818) 0.617** −0.092 −0.226** 2. FT 3.102 1.067 .918 0.917 0.918 0.653 (0.808) −0.117 −0.373** 3. SN 8.140 8.246 — — — — — 0.211** 4. GMH 2.897 0.543 .885 0.887 0.887 0.400 (0.632) Note. n = 591, except those results involving job insecurity, where n = 394. C.R. = composite reliability; AVE = average variance extracted; (___) = square root of AVE; JI = job insecurity; FT = financial threat; SN = support network; GMH = General Mental Health. **p < .01. Table 3. CFA Fit Indices for the Model 1, that Includes the Job Insecurity and General Mental Health Measures. 2 2 Model 1 χ df p χ /df ratio SRMR RMSEA [90% CI] CFI TLI Single-factor model 1140.784 104 <.001 10.969 0.146 0.159 [0.151–0.169] 0.731 0.689 Two-factor model 196.807 103 <.001 1.911 0.068 0.048 [0.038–058] 0.976 0.972 Note. N = 394. χ = chi square; df = degrees of freedom; SRMR = standardized root mean residual; RMSEA = root mean square error of approximation; CFI = comparative fit index; TLI = Tucker-Lewis index. Table 4. CFA Fit Indices for Model 2, that Includes the Financial Threat and General Mental Health Measures. 2 2 Model χ df p χ /df ratio SRMR RMSEA [90% CI] CFI TLI Single-factor model 2159.055 135 <.001 15.993 0.153 0.160 [0.154–166] 0.805 0.779 Two-factor model 322.799 134 <.001 2.408 0.061 0.049 [0.042–056] 0.982 0.979 Note: N = 591. χ = chi square; df = degrees of freedom; SRMR = standardized root mean residual; RMSEA = root mean square error of approximation; CFI = comparative fit index; TLI = Tucker-Lewis index. theoretical structure of the instruments since the level of fit significant effect of the interaction between the support net- leads to rejecting the single-factor model. In contrast, the fit work and job insecurity on general mental health (β = .232; for the theoretical model (two-factors) is acceptable. p < .001), that is, the greater the support network, the lower Loadings factors are presented in Tables 5 and 6. the negative effect of job insecurity on general mental health. Only age showed a positive and significant effect on general mental health (β = .099; p = .043). Structural Equation Modeling The second model (Figure 2) was performed in the gen- To analyze the hypotheses, two SEMs were carried out. The eral sample, including financial threat, support network, and first model (Figure 1) was performed in the subsample of its interaction as antecedents of general mental health, con- workers, including job insecurity, support network, and its trolling for age, educational level, and gender (two people interaction as antecedents of general mental health, control- who were self-categorized as “other” were excluded from the ling for age, educational level, and gender (one person who analysis because it is not enough quantity to draw conclu- was self-categorized as “other” was excluded from the analy- sions; n = 589). In this model, Hypotheses 2, 3, and 5 were sis because it is not enough quantity to draw conclusions; analyzed. This measurement model has acceptable fit levels n = 393). In this model, Hypotheses 1, 3, and 4 were ana- (x /df = 1.288; SRMR = 0.052; RMSEA = 0.028 [0.022– lyzed. This measurement model has acceptable fit levels 0.033]; CFI = 0.986; TLI = 0.985) explaining 23.5% of the (x /df = 1.395; SRMR = 0.079; RMSEA = 0.032 [0.023– variance of general mental health. Hypothesis 2 was con- 0.040]; CFI = 0.977; TLI = 0.973) explaining 15.9% of the firmed since financial threat showed a direct significant neg- variance of general mental health. Regarding Hypothesis 1, ative effect on general mental health (β = −.309; p < .001). job insecurity showed a direct negative and significant effect The support network was positively and significantly related on general mental health (β = −.183; p < .001), and for to general mental health (β = .182; p = .012), confirming hypothesis 3, the support network was positively and signifi- Hypothesis 3. Regarding Hypothesis 5, the support network cantly related to general mental health (β = .322; p < .001). did not moderate the relationship between financial threat Regarding Hypothesis 4, the analysis shows a positive and and general mental health (β = .093; p = .199). Age (β = .205; 8 SAGE Open Table 5. CFA Factor Loadings for the Job Insecurity-General Mental Health Model. 95% Confidence interval Factor Indicator Estimate Std. Error z-value p Lower Upper GMH GMH_1 0.459 0.046 9.896 <.001 0.368 0.550 GMH_2 0.456 0.052 8.860 <.001 0.355 0.557 GMH_3 0.436 0.047 9.178 <.001 0.343 0.529 GMH_4 0.573 0.048 11.942 <.001 0.479 0.667 GMH_5 0.623 0.045 13.745 <.001 0.535 0.712 GMH_6 0.639 0.051 12.627 <.001 0.540 0.739 GMH_7 0.598 0.043 13.888 <.001 0.513 0.682 GMH_8 0.528 0.048 11.048 <.001 0.434 0.622 GMH_9 0.671 0.046 14.720 <.001 0.582 0.760 GMH_10 0.568 0.057 10.040 <.001 0.457 0.679 GMH_11 0.467 0.073 6.408 <.001 0.324 0.609 GMH_12 0.687 0.041 16.956 <.001 0.608 0.767 JI JI_1 0.856 0.034 25.156 <.001 0.789 0.922 JI_2 0.642 0.053 12.150 <.001 0.539 0.746 JI_3 0.827 0.034 24.240 <.001 0.760 0.894 JI_4 0.922 0.030 30.708 <.001 0.863 0.981 Note. GMH = General Mental Health; JI = job insecurity. Table 6. CFA Factor Loadings for the Financial Threat-General Mental Health model. 95% Confidence interval Factor Indicator Estimate Std. error z-value p Lower Upper GMH GMH_1 0.550 0.042 13.046 <.001 0.467 0.632 GMH_2 0.490 0.042 11.635 <.001 0.408 0.573 GMH_3 0.487 0.040 12.129 <.001 0.408 0.565 GMH_4 0.608 0.037 16.262 <.001 0.535 0.681 GMH_5 0.682 0.036 18.795 <.001 0.610 0.753 GMH_6 0.684 0.041 16.611 <.001 0.603 0.764 GMH_7 0.652 0.036 18.000 <.001 0.581 0.723 GMH_8 0.646 0.038 17.099 <.001 0.572 0.720 GMH_9 0.719 0.037 19.201 <.001 0.646 0.792 GMH_10 0.689 0.045 15.308 <.001 0.601 0.777 GMH_11 0.600 0.057 10.601 <.001 0.489 0.710 GMH_12 0.720 0.031 23.535 <.001 0.660 0.780 FT FT_1 0.817 0.033 25.120 <.001 0.754 0.881 FT_2 0.897 0.025 35.329 <.001 0.847 0.947 FT_3 0.891 0.025 35.434 <.001 0.842 0.941 FT_4 0.751 0.033 22.429 <.001 0.685 0.817 FT_5 0.764 0.033 23.201 <.001 0.699 0.828 FT_6 0.710 0.036 19.944 <.001 0.641 0.780 Note. GMH = General Mental Health; FT = financial threat. negative relationship between financial threat and general p < .001) and educational level (β = .082; p = .049) was posi- mental health and the moderating effect of the support net- tively related to general mental health. work on this relationship because having more children at home implies greater sensitive expenses and the need for a Complementary Analysis support network. We found that for those who have three or more children (n = 64; eliminating a participant that commit Bearing in mind that hypothesis 5 was not supported, we a typing error [children = 236]), the model explains a higher explored whether the number of children could deepen the Alcover et al. 9 Figure 1. This model tested hypotheses 1, 3, and 4 in the subsample of workers, including job insecurity, support network, and its interaction as antecedents of general mental health, controlling for age, educational level, and gender. The latent moderator variable (interaction) was included by multiplying the items pairs of job insecurity and support network as the observed values. percentage of the variance of the general mental health H4, a moderating effect of the support network was found in (38.6%), showing a significant direct effect of financial the relationship between job insecurity and general mental threat (β = −.491; p < .001), the support network (β = .289; health; but this moderation was not significant in the rela- p = .012), as well as their interaction (β = .177; p = .048). This, tionship between financial threat and general mental health, on the other hand, does not occur for the group of people who so H5 wasn’t confirmed. We discuss these findings below. report two children or less (n = 524), in which the model Job insecurity is perceived as a threat in Chile in the con- explains only 21.2% of the variance of the general mental text of the COVID-19 pandemic. However, job insecurity health, with a significant direct effect of financial threat scores are not extreme, which suggests that the sample’s edu- (β = −.292; p < .001), but neither the support network directly cation level, and therefore its perceived employability, might nor its moderating effect on the relationship between finan- play a protective role on the perception of job insecurity and cial threat and general mental health showed a significant its negative psychological consequences (De Cuyper et al., level (β = .164 and .090; p = .097 and .327, respectively). 2012; Green, 2011). Notwithstanding the above, some stud- ies have not identified a moderating effect of employability on the positive relationship between job insecurity and Discussion decreased psychological well-being (Cheng & Chan, 2008; Our results indicate, in line with H1 and H2, that people Kirves et al., 2011; Llosa et al., 2018). already perceived the impact of the COVID-19 pandemic The results show a statistically significant relationship during the first stage of the lockdown through job insecurity between job insecurity and mental health, agreeing with the and financial threat and that these perceptions related nega- evidence obtained in other socioeconomic contexts (Cheng tively to their general mental health. Likewise, confirming & Chan, 2008; Llosa et al., 2018; Sverke et al., 2002). The H3, a relationship between the support network and general current situation brought by COVID-19 fulfills some of the mental health was observed. Additionally, consistent with conditions that characterize job insecurity according to Shoss 10 SAGE Open Figure 2. This model tested hypotheses 2, 3, and 5 in the general sample, including financial threat, support network, and its interaction as antecedents of general mental health, controlling for age, educational level, and gender. The latent moderator variable (interaction) was included by multiplying the items pairs of financial threat and support network as the observed values. (2017)—lower control and lower volition—since the impact distribution, with an identical effect of psychological distress generated by the pandemic has been sudden and uncontrol- (e.g., Kopasker et al., 2018). lable for governments and organizations, and workers alike. In previous crises brought about by epidemics and pan- Although the long-terms effects are still unknown (Shoss, demics, the effects of financial threats are present during the 2017), it must be remembered that Chile had undergone a quarantine period, especially, in the medium and long term “social uprising” in October and November 2019 with con- (Brooks et al., 2020; Jeong et al., 2016). Thus, given that our sequential social and economic effects, that could also con- study was completed during the earliest stage of the COVID- tribute to increasing the perception of job insecurity. 19 pandemic, it is foreseeable that the economic stressors Parallel to this, results show a perception of financial will increase as the current situation endures. Prior research threat at values slightly above scale’s midpoint. The rela- is consistent in showing that the negative and adverse effects tively rapid measure approved by the Chilean Senate and of repeated financial threats (Watson & Osberg, 2017), asso- Congress to make unemployment insurance more flexible ciated with both job insecurity and unemployment, are mul- due to the COVID-19 emergency (March 31), which tiple and severe for people and their personal and social extended coverage for the most vulnerable sectors, could environments—affecting in particular social relations and control the perception of immediate financial risk. The find- family functioning (Klehe et al., 2012; Probst, 2005); there- ing that perceived financial threat is correlated with general fore, the outcomes obtained in this study can serve to warn of mental health is consistent with previous findings after the the foreseeable consequences for mental health in an employ- effects of large economic recessions (Fiksenbaum et al., ment and economic situation that may continue over time. 2017; Marjanovic et al., 2013, 2015; Netemeyer et al., 2018). The results show that the perceptions of job insecurity There is an increasing body of evidence that economic inse- and financial threat are significantly related to each other curity is experienced the same regardless of the income which agrees with what has been found in previous studies Alcover et al. 11 in situations of recent large-scale economic crises (Lam obtained concerning the lack of effect of the support network et al., 2014; Rajani et al., 2016). In addition, both are asso- with financial threat may be due to the perception that eco- ciated with a decline in perceived mental health, which is nomic insecurity has a generalized impact, not limited to also consistent with prior results (e.g., Klehe et al., 2012; one’s situation. Consequently, there is no expectation of Kopasker et al., 2018; Rajani et al., 2016), thus agreeing in receiving help from the support network to deal with eco- part with the prior evidence (Greenhalgh & Rosenblatt, nomic problems. 1984), but not with the results obtained by Rajani et al. Although the debate on what is the average size of peo- (2016) in the context of the Great Recession of 2008 in ple’s support network (around 150; Hill & Dunbar, 2003) is European countries, which conclude that job insecurity and currently still open, when distinguishing between the size of financial worries affected mental health in the same way. the close support group (family and friends), the sympathy Nor are they in line with those obtained in Sweden by group, and the rest of the support network, the size of the Richter et al. (2014), who confirmed that job dependency former is usually the smallest, ranging from 5 to 20 members due to economic issues did not mitigate the relation between (Pollet et al., 2011; Wrzus et al., 2013). However, this num- job insecurity and psychological well-being. These discrep- ber also varies across age groups and may also be sensitive to ancies with some prior research may be because in Chile, national culture (Wrzus et al., 2013). In our study, the sup- social protection systems are much less robust than those port network of the participants can be considered medium generally available in European Union countries with wel- size (mean of 8.13); what seems important is the perceived fare states (Rajani et al., 2016), and in particular in Sweden effectiveness of this network to manage job insecurity and (Richter et al., 2014), and they are close to those that pre- financial threat. Given that the response on the support net- dominate in the US (Greenhalgh & Rosenblatt, 1984). work includes family members and close friends, it can be Thus, in Chile, where the population generally carries high inferred that the perception of social support in case of need debt levels and a fragile unemployment insurance system, has a reasonable level of certainty. This perception of pri- people who view their financial situation with concern mary, reliable, and robust bonds directly affects the reception react more negatively to the threat, which is reflected in of various types of social support (Thoits, 2011). The partici- their mental health. In this sense, we argue that the moder- pants seem to perceive that the support network is a powerful ating effect of the support network will be higher if the per- resource to cope with financial stress and job insecurity. In son is responsible for a larger number of children, which addition to this direct influence, the perception of the support generates a considerable difference in terms of financial network may also expand through the experience of trust, expenses in this country. In line with the previous reason- where its members increase their social capital through their ing, the complementary analysis provided in the results sec- contacts. tion shows that when comparing those who report three or Finally, although more than 2 years have passed since the more children with those who have two or fewer, the results pandemic started and several studies have been published showed that the direct effect of the support network and its about the effect of variables related to financial stress, job interaction with financial threat is only related to a low insecurity or social support, between others, and mental decrease to general mental health in the group of up to three health (e.g., de Miquel et al., 2022; Göktaş & Özdinç, 2022; children. Additionally, the percentage of variance explained Mousa & Samara, 2022; Said et al., 2022; Yao & Wu, 2022) by these models is greater in this group, which is why these the results obtained are still timely and relevant. The psycho- variables, to a large extent, explain the worsening of gen- logical reaction in a situation of abrupt limitation of social eral mental health in the group with more dependents. Prior routines, such as the beginning of the lockdown, is not results (Kopasker et al., 2018) also show that the negative exhausted in this event, and it can be extrapolated to other effects of economic insecurity are greater in men, who, due hard and inadvertent situations. Thus, these findings help to to socioeconomic and cultural reasons, continue to be the better understand and to be prepared for other public health main providers in families, as can also occur in Chile. crises, natural disasters, and armed conflicts, among other Finally, the study results indicate a medium moderating situations, that can profoundly affect people’s lives. effect of the support network since it moderates the associa- tion of job insecurity with the decline in perceived mental Practical Implications health. In contrast, this moderating effect is not found for financial threat in the general sample, and it is only observed First, the outcomes obtained have direct practical implica- among those who have three or more children. These results tions related to the need to implement psychological support are similar to those obtained in previous studies about both measures for workers and the unemployed to equip them constructs (Cheng et al., 2014; Näswall et al., 2005; Whelan, with coping strategies to manage uncertainty and stress. 1993), although we have not found differences between men These psychosocial supports should be available in organiza- and women in terms of the moderating effect of perceived tions, and primary care centers to be accessible and have an social support, as other studies have found concerning job ongoing positive effect on mental health in the medium and insecurity (Menéndez-Espina et al., 2019). The result long term (Pfefferbaum & North, 2020). 12 SAGE Open Second, the conclusions drawn here should serve as an Additionally, and fifth, occupational health, job insecu- alert to the risk that the double perception of job insecurity rity, and job precariousness are three of the 10 critical areas and financial threat can generate by increasing psychological for research and practice in WOP due to the impact on them self-pressures of productivity and the over-commitment to by COVID-19 as identified by experts (Rudolph et al., the job, one of the first consequences that have already been 2021); thus, this study makes an important contribution to detected since the pandemic began (Mukhtar, 2020; Stanhope knowledge in this context, but it must be broadened or & Weinstein, 2021; Zhang et al., 2021). The COVID-19 cri- complemented. sis place explicit or implicit demands that are responded to by people with work overload, increasing working days (in Limitations and Future Research person or remotely), reducing or giving up days off or vaca- First, the cross-sectional nature of the design only allows us to tion days, or accepting abusive working conditions that can identify relations between the variables. However, the impor- also increase the perception of qualitative job insecurity tance of having preliminary data on the disruptive impact (Hellgren et al., 1999), lower perceived control and the caused by the scale and speed of the global pandemic in Chile resulting negative effects on mental and physical health justifies the urgency of obtaining an initial approach to the con- (Vander Elst, Richter et al., 2014; Zhang et al., 2021). sequences for the mental health of work-related variables. Therefore, it seems urgent to regulate and monitor working Second, the participants in our study did not form part of a conditions compliance during the COVID-19 crisis and the probabilistic sample, at the outcomes cannot be generalized so-called “new normal” in the post-pandemic period. In this to the Chilean population. Also, in this case, future studies sense, it is necessary to guarantee the workers’ and unem- should include representative samples or concentrate groups ployed labor rights so that their job insecurity (subjective and of workers, specific people or contexts (concrete professions, objective) does not increase. In a similar vein, it is advisable young or older workers or vulnerable groups, etc.) to most to ensure that the new work arrangements (e.g., teleworking accurately identify the differential effects of “Coronanomics” or hybrid work) do not have negative psychosocial conse- in each setting. quences, such as work-family conflict. These measures can Third, our measure of support network calls for quantity favor the maintenance of appropriate well-being and physi- and lacks assessment of the quality of the social network. cal and mental health levels. Further studies should include an additional measure of close- Third, the results also have important implications for ness/frequency of connections, abusive/negative relationships, designing strategies and psychosocial interventions that can symmetrical/asymmetrical relationships, and so on. strengthen support networks and potential social support. Fourth, the influence of gender on the results was con- Given the strong connections between social relations, sup- trolled in both models analyzed. Despite this, the sample port, and mental health (House et al., 1988; Uchino, 2006), imbalance in this variable can be considered a possible actions aimed at reinforcing interpersonal ties and support study’s weakness. networks through, for example, support groups, community Finally, and fifth, this study has only considered the vari- initiatives, or networks of people who share similar charac- ables mentioned as moderating antecedents and consequents, teristics (studies, profession, etc.) (Cohen et al., 2000) can be but we are aware that in the experiences people are living highly effective at equipping those who experience financial during this economic and health crisis, other personal, fam- threat and job insecurity with social coping and resilience ily, organizational and social variables are involved that resources that increase personal resources. Despite being interact in a complex way, which is reflected in the rather subjective perceptions, financial and job insecurity have low percentage of variance explained by the contrasted mod- objective components, such as contractual status, the volume els. The inclusion of variables such as gender, contract sta- of layoffs in a productive sector or level of unemployment in tus, work-family conflict or cultural differences, among a region (Ellonen & Nätti, 2015; Helbling & Kanji, 2018) others (Kniffin et al., 2021), in future studies will be needed and, consequently, are not an individual but a collective to understand the real impacts and to design strategies and problem; therefore, the possible tools to confront them will interventions that can prevent, reduce or alleviate the effects also need to be collective and social. In this regard, organiza- for the well-being, health, and safety of people and their fam- tional measures that can be beneficial in preventing negative ilies as well as for the functioning and effectiveness of mental health consequences are those aimed at reducing organizations. financial threat levels. Thus, employers may, for example, offer advice, counseling, or training on financial and debt Acknowledgments management and planning for health care, mortgage, or col- lege costs, as well as subsidizing employee lunches and We are grateful for the support of Matías Arriaga in the data analy- transportation costs. In terms of government measures, regu- sis process of this study. lations and laws aimed at increasing coverage for temporary Data Availability Statement and long-term unemployment and those aimed at avoiding gender discrimination, especially in the case of female work- The data corresponding to this study is available on Open Science ers with family responsibilities, would also be beneficial. Framework (OSF) website (https://osf.io/p7xdf/; Salgado, 2020). Alcover et al. 13 Declaration of Conflicting Interests Caroli, E., & Godard, M. (2016). Does job insecurity deterio- rate health? Health Economics, 25(2), 131–147. https://doi. The author(s) declared no potential conflicts of interest with respect org/10.1002/hec.3122 to the research, authorship, and/or publication of this article. Chan, A., Malhotra, C., Malhotra, R., & Ostbye, T. (2011). Living arrangements, social networks and depressive symptoms Funding among older men and women in Singapore. 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SAGE OpenSAGE

Published: Sep 15, 2022

Keywords: job insecurity; financial threat; general mental health; social support; support network; COVID-19

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