key: cord-0800947-dxrdhmyr authors: Owens, Rhea L.; Meierding, Erika E.; Allan, Blake A. title: Service Workers’ Well-Being During COVID-19: A Strengths-Based Inclusive Theory of Work Perspective date: 2022-05-03 journal: J Career Assess DOI: 10.1177/10690727211050898 sha: 67f8aff1bbb4157cf9184bbb2a251b463e54b0fb doc_id: 800947 cord_uid: dxrdhmyr This study tested the Strengths-Based Inclusive Theory of Work (S-BIT of Work), a vocational theory that emphasizes positive psychological and cultural factors, among a sample of service industry workers during COVID-19. Service industry workers (N = 320) were recruited via social media sources across the United States, and structural equation modeling was used to examine the model. This model included privilege and COVID-19 impact as contextual variables; organizational support and workplace dignity as promotive workplace variables; hope, strengths use, adaptability, empowerment, and perceived COVID-19 threat as individual variables; and fulfilling work and psychological distress as outcome variables. Privilege and workplace dignity were identified as particularly important variables; results suggested privilege was positively associated with a promotive work context and negatively related to psychological distress. Additionally, the greater the amount of privilege and dignity the service industry workers experienced, the greater their positive individual characteristics were able to flourish. variables of privilege and the impact of COVID-19 as representative contextual factors we believed were especially relevant among a sample of service industry workers during COVID-19. We also examined the variables of organizational support and workplace dignity as representative factors of a promotive work context. We examined hope, strengths use, career adaptability, and empowerment as the representative positive individual characteristics. We also measured each element of fulfilling work: job satisfaction, workplace positive emotions, meaningful work, and work engagement Owens et al., 2019) . Finally, given the unique circumstances of COVID-19, we also measured COVID-19 threat as an individual characteristic and psychological distress and an outcome variable. (See Figure 1. ) Each variable included in our model is italicized in the review that follows. Service industry workers face a variety of contextual barriers in the pursuit of fulfilling work. The impact of COVID-19 on service industry workers has been a significant contextual stressor. Many industries were shut down for a period of time, including travel, entertainment, and hospitality, and continue to experience challenges (Kniffin et al., 2020) . Millions of Americans have filed for unemployment benefits since the start of COVID-19 (Rugaber, 2020) . For those who have remained employed, work conditions during COVID-19 could result in greater stress, burnout, and mental health concerns than previously seen (Kniffin et al., 2020) . Many low-wage workers, including service industry employees, have experienced greater responsibility and risk during COVID-19 to help maintain work operations (Cubrich, 2020) . Many of these positions tend to be filled by women and racial and ethnic minorities (Centers for Disease Control and Prevention, 2020; Ross & Bateman, 2019) . In addition to low wages, individuals in these positions typically have minimal or insufficient benefits, less access to paid work leave, less support, and economic instability, making them especially vulnerable during COVID-19 (e.g., Cubrich, 2020; Maxwell, 2008) . These inequities have worsened during COVID-19, and safety concerns have heightened because members of racial and ethnic minority groups are less likely to have the ability to work remotely, thus facing greater risk to exposure, as well as already increased risk of COVID-19 fatality associated with lower socioeconomic status, dense living conditions, and preexisting health conditions (Kniffin et al., 2020) . Another contextual variable of particular relevance to service industry workers during this time is privilege. Service workers tend to have fewer resources in comparison to the general population Note. The variables in the rectangles (e.g., privilege) are the constructs selected and measured in this study to represent each broader theoretical proposition of the S-BIT of Work noted in the ovals above each rectangle (e.g., contextual supports and barriers). 1 COVID-19 threat is not viewed as a positive individual characteristic but rather an individual characteristic that was measured due to the circumstances surrounding working during the COVID-19 pandemic. due to lower wages offered (Bureau of Labor Statistics, 2019). Additionally, because service industry work is stigmatized and often viewed as a low status position, service industry workers tend to have less social capital in comparison to those in other occupations (Wildes, 2007) . The low economic power and social power granted by service industry positions may also interfere with employees' perceptions of their work as fulfilling. During COVID-19, many essential worker positions, including the service industry, have been maintained and filled by marginalized groups (Kniffin et al., 2020) , who often experience less privilege in society. Therefore, examining privilege within the context of COVID-19 is an important consideration. The S-BIT of Work focuses on the importance of a promotive work context in the attainment of fulfilling work . Two variables that may be of relevance for service industry workers are perceived organizational support and workplace dignity. Perceived organizational support refers to the extent employees perceive that their organization values their contributions and cares for their well-being (Eisenberger et al., 1986) . Perceived organizational support has been found to mediate the relationship between organizational support and job satisfaction and negatively influence turnover intentions among service industry employees (Allen et al., 2003) . Additionally, another study found that among retail employees that those who engaged in high levels of emotional labor and had high levels of perceived organizational support expressed the highest levels of job satisfaction of the sample (Duke et al., 2009) . Workplace dignity is defined as "the self-recognized and other-recognized worth acquired from (or injured by) engaging in work activity" (Lucas, 2017 (Lucas, , p. 2549 . Workplace dignity involves both inherent and earned dignity through job contributions (Hodson, 2001) . Common forms of violations of worker dignity include mismanagement and abuse, forced participation, overwork, and infringement on autonomy (Hodson, 2001) . Despite its importance for worker well-being, little empirical research has been conducted on the topic. Prior research on worker dignity was examined through a combination of other proxy workplace variables (see Lucas, 2017) . Existing research suggests worker dignity is promoted by subjective factors, such as autonomy, respect, and meaningful work, as well as objective factors, such as equality, safe and healthy work conditions, job security, and financial benefits (Bolton, 2007) . Thus, workplace dignity appears especially relevant to service industry workers during COVID-19. Positive individual characteristics are traits and skills that individuals possess, which enable them to cope and thrive in work environments . For the purpose of this study, the positive individual characteristics of hope, strengths, adaptability, and empowerment were examined because these variables are well supported in the literature as beneficial for a diverse array of communities (see Owens et al., 2019) . Hope is a positive individual characteristic that is readily studied in the vocational literature (e.g., Juntunen & Wettersten, 2006; Reichard et al., 2013; Wandeler et al., 2017) . Hope is defined as the ability to generate multiple paths to achieve one's goals (i.e., pathways) and the motivation (i.e., agency) to use the identified pathways to reach one's goals (Snyder, 1994 (Snyder, , 2000 . In general, hope is positively related with work well-being, job satisfaction, work engagement, job performance, and career adaptability (e.g., Reichard et al., 2013; Wandeler et al., 2017) . In the service industry, hope is significantly and positively associated with performance outcomes, including commission and supervisor ratings (Combs et al., 2010) . In a study of frontline hotel employees, hope on job performance, service recovery performance, and extra role customer service was fully mediated by work engagement (Karatepe, 2014) . Another positive individual characteristic that may be important for service workers is strengths. For the purpose of this study, strengths are conceptualized as "positive traits or skills that promote optimal functioning" (Owens et al., 2018) . In the work context, strengths are often examined through their use. The positive relation between strengths use and well-being is well documented (e.g., Forest et al., 2012; Govindji & Linley, 2007; Proctor et al., 2011) , including in the work setting (e.g., Keenan & Mostert, 2013; van Woerkom et al., 2016) . However, there is currently no known research about the impact of strengths use in the service industry. Career adaptability is arguably another relevant positive individual characteristic, particularly during COVID-19 (Kniffin et al., 2020) . Career adaptability refers to an individual's ability to respond flexibly and cope with their work context, including both current and future work pursuits, particularly in unpredictable or novel situations (e.g., Krieshok et al., 2009; Savickas, 1997) . Generally, adaptability is positively associated with autonomy and support from supervisors in the workplace (Ito & Brotheridge, 2005) . Research also suggests that career adaptability partially mediated the effect of work conditions on well-being (Maggiori et al., 2013) . In the service industry, adaptability has been found to be positively related to promotability (i.e., the likelihood of an employee's advancement; Greenhaus et al., 1990) and career satisfaction (Chan et al., 2016) . In a qualitative study examining adaptability among service industry workers, participants were found to fit into three groups: those who were "getting by" (remaining in their current position), those who were "getting on" (planning to move into more "highly skilled" employment), and those who were "going nowhere" (did not perceive themselves to have career advancement prospects; Brown, 2016) . Based on the themes identified, the researcher asserted that the service workers who were in the "getting by" and "going nowhere" categories had underdeveloped career adaptability (Brown, 2016) . Empowerment is another positive individual characteristic, which is composed of the following elements: meaning, self-efficacy, self-determination, and personal control (Fulford & Enz, 1995) . Empowerment is positively associated with job satisfaction, organizational commitment, selfesteem, and job security (Kirkman & Rosen, 1999; Liden et al., 2000; Spreitzer, 2007) . Research suggests empowerment is beneficial for service industry employees, because empowerment positively influences job satisfaction, positive attitudes, and customers' perception of service quality in the service industry (Fulford & Enz, 1995; Gazzoli et al., 2010) . The primary goal of the current study was to test the full S-BIT of Work among a sample of service industry workers during COVID-19, with particular attention to variables that both align with the theory and are relevant to service industry workers. Therefore, in addition to S-BIT of Work variables that are largely generalizable (e.g., privilege and strength use), we also included variables that align with the theoretical propositions of the S-BIT of Work that are relevant to COVID-19, including contextual (COVID-19 impact) and individual (perceived COVID-19 threat and psychological distress) factors. We collected a diverse sample of service industry workers from the United States and used structural equation modeling to examine the theoretical model. This model included the contextual factors of COVID-19 impact and privilege predicting the promotive work context variables of organizational support and workplace dignity. In turn, the promotive work context variables of organizational support and workplace dignity predicted the individual characteristics of hope, strengths use, adaptability, empowerment, and perceived COVID-19 threat, which subsequently predicted the outcome variables of fulfilling work and psychological distress (see Figure 1 ). We also included the impact of COVID-19 as a general criterion that predicted the promotive work context variables, perceived COVID-19 threat, and the outcome variables. We tested this full mediation model against an incremental validity model that allowed direct effects from privilege and the work context variables to the outcome variables. The primary hypothesis of this study was that the full mediation model would have the best fit to the data, supporting the overall theory. Specific, secondary hypotheses examining individual relations were generated as well. It was hypothesized that COVID-19 impact would negatively relate to organizational support, workplace dignity, and fulfilling work, and positively relate to psychological distress. It was hypothesized that privilege would positively relate to organizational support, workplace dignity, and fulfilling work, and negatively relate to psychological distress. It was also hypothesized that organizational support and workplace dignity would positively relate to hope, strengths use, adaptability, and empowerment, and negatively relate to perceived COVID-19 threat. It was hypothesized that hope, strengths use, adaptability, and empowerment would positively relate to fulfilling work and negatively relate to psychological distress, and COVID-19 threat would negatively relate to fulfilling work and positively relate to psychological distress. It was hypothesized there would be significant indirect effects from COVID-19 impact and privilege to the individual characteristics (i.e., hope, strengths use, adaptability, empowerment, and COVID-19 threat) via organizational support and workplace dignity. Finally, it was hypothesized there would be significant indirect effects from organizational support and workplace dignity to fulfilling work and psychological distress via the individual positive characteristics. For a full a list of all individual hypotheses, see the Appendix in the online Supplemental Material. A total of 420 service workers from the United States participated in this study. Inclusion criteria for this study included that participants were at least 18 years of age and were working in the service industry (e.g., barista, waitstaff, hotel staff, and transportation driver) at the time of the study. Of these participants, 67 failed two out of the three attention check items and 33 only completed the demographic questions; therefore, they were excluded from the analyses. The resulting sample consisted of 320 service industry workers who were included in the analyses. The mean age was 28.55 years (SD = 8.87) and ranged from 18 to 58 years old. Participants identified as 62.2% (n = 199) women, 32.8% (n = 105) men, 4.4% (n = 14) as "other," and 0.6% (n = 2) did not disclose. Additionally, participants identified as 84.7% (n = 271) White, 5.9% (n = 19) Latina/ o/x, 3.1% (n = 10) Multiracial, 2.5% (n = 8) Asian American, 3.3% (n = 11) other races and ethnicities, and 0.3% (n = 1) did not disclose. Regarding the jobs represented, 48.1% (n = 154) were retail workers, 9.7% (n = 31) were restaurant servers, 5% (n = 16) were restaurant managers, 5% (n = 16) were delivery drivers, 4.7% (n = 15) were chefs/cooks, 3.4% (n = 11) were baristas, 1.9% (n = 6) were bartenders, 1.9% (n = 6) worked in fast food, 10.9% (n = 35) were other jobs, and 9.4% (n = 30) were not reported. At the beginning of the survey, participants completed a screener question that asked them whether or not they were a service industry worker, which included several example service industry jobs. Participants who indicated they were not service industry workers were automatically removed from the survey. Privilege. Privilege was measured using the Distance from Privilege Scale (DFP; Kerr et al., 2012) . The scale measures participants' perceptions of their level of privilege across various domains (geography, gender, race/ethnicity, ability/disability status, citizenship status, intelligence, sexual orientation, religion, social class, and attractiveness; Kerr et al., 2012) . The scale includes 10 items, where participants are asked to rank themselves on a scale of 1-10, with 10 being the most ideal, accepted, and valued level of privilege, and 1 representing the least ideal, accepted, and valued level of privilege for each category (Kerr et al., 2012) . A sum score was used. An example item is "Think of this ladder as representing where people stand in our society. At the top of the ladder are the people whose gender is the most accepted and valued in our society. At the bottom of the ladder are the people whose gender is the least accepted and valued in our society. The higher up you are on this ladder, the closer you are to the people at the very top and the lower you are, the closer you are to the bottom. Where would you put yourself on the ladder? Please indicate the rung where you think you stand." The DFP has adequate internal consistency (α = .70; Kerr et al., 2012) and good test-retest reliability (r =.82; Kerr et al., 2012) . The internal consistency for this study was .72. COVID-19 Impact. The Coronavirus Impacts Questionnaire measures the degree to which COVID-19 has impacted people's lives (Conway et al., 2020) . This measure includes nine items and three subscales-financial, resources, and psychological. It uses a 7-point Likert-type scale ranging from 1 (Not True of Me at All) to 7 (Very True of Me), and a sum score was used. An example question is "I have lost job-related income due to the Coronavirus (COVID-19)." The Coronavirus Impacts Questionnaire has demonstrated strong internal consistency (α = .81-.86). The internal consistency for this study was .84. Organizational Support. Organizational support was measured using the eight-item version of the Survey of Perceived Organizational Support (SPOS; Eisenberger et al., 1986; Rhoades & Eisenberger, 2002) . This scale measures the extent to which employees perceive that their organization values their contributions and cares about their well-being (Eisenberger et al., 1986) . The inventory uses a 7-point Likert-type scale (0 = Strongly Disagree to 6 = Strongly Agree; Rhoades & Eisenberger, 2002) , and a sum score was used. An example question includes "The organization takes pride in my accomplishments at work." The short version of the SPOS is unidimensional and has previously demonstrated high internal consistency (α = .92) and validity with perceived supervisory support and organizational dependability (Hutchison, 1997) . The internal consistency for this study was .95. Workplace Dignity. Workplace dignity was measured with the Workplace Dignity Scale, which assesses the extent to which employees perceive experiencing dignity in their workplace (Thomas & Lucas, 2019) . This scale is comprised of 18 items and six subscales: respectful interaction, competence-contribution, equality, inherent value, general dignity, and indignity. The measure uses a 7-point Likert-type scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree), and a sum score was used. An example item is "People at work communicate with me respectfully." The Workplace Dignity Scale previously demonstrated strong internal consistency (α = .96) and validity with interpersonal justice, competence, status, employee engagement, burnout, and turnover intentions (Thomas & Lucas, 2019) . The internal consistency for this study was .97. Hope. Hope was measured with the Trait Hope Scale (Snyder et al., 1991) . The scale consists of two subscales-pathways and agency-and an overall hope score. Pathways involves the ability to think of multiple routes to reach one's goals, whereas agency involves the motivation to reach one's goals. Overall hope is the combined score of both pathways and agency. The Trait Hope Scale includes 12 items and uses an 8-point Likert-type scale (1 = Definitely False to 8 = Definitely True), and a sum score was used. An example item is "I energetically pursue my goals." The Trait Hope Scale has adequate internal consistency (total scale α = .74-.84; agency subscale α = .71-.76; pathways subscale α = .63-.80; Snyder et al., 1991) . Test-retest reliability is also adequate for this scale (r = .73-.82; Snyder et al., 1991) . The Trait Hope Scale demonstrated good convergent validity with the State Hope Scale (Snyder et al., 1996) . The internal consistency for this study was .86. Strengths. The Strengths Use Scale measures the degree people use their strengths in daily life (SUS; Govindji & Linley, 2007) . The Strengths Use Scale includes 14 items and uses a 7-point Likert-type scale (1 = Strongly Disagree to 7 = Strongly Agree; Govindji & Linley, 2007) . A sum score was used, and an example item is "I am regularly able to do what I do best." The SUS has excellent internal consistency (α = .94-.97; Govindji & Linley, 2007; Wood et al., 2011) and high test-retest reliability (r icc = .85; Wood et al., 2011) . The internal consistency for this study was .93. Adaptability. Adaptability was measured using the Career Adaptability subscale from the Career Futures Inventory (Rottinghaus et al., 2005) . This subscale measures the perceived ability to cope and adjust with change, work responsibilities, and unexpected events related to career plans (Rottinghaus et al., 2005) . It includes 11 items on a 5-point Likert-type scale (1 = Strongly Disagree to 5 = Strongly Agree), and a sum score was used. An example item includes "I can overcome potential barriers that may exist in my career." The Career Adaptability subscale has demonstrated adequate internal consistency (α = .85) and test-retest reliability (r = .63). The Career Futures Inventory has also demonstrated convergent and discriminant validity with Big Five personality traits, optimism, positive and negative affect, problem-solving styles, and selfefficacy (Rottinghaus et al., 2005) . The internal consistency for this study was .83. Empowerment. Empowerment was measured using Fulford and Enz's (1995) adapted version of Spretizer's (1992) Psychological Empowerment Scale for use in the service industry. This adapted version of the scale has been previously used to examine empowerment in the service industry context (e.g., Fulford & Enz, 1995; Gazzoli et al., 2010) . The modified, 12-item scale uses a 7point Likert-type scale (1 = Strongly Disagree to 7 = Strongly Agree; Fulford & Enz, 1995) , and a sum score was used. The scale includes three subscales: meaning, self-efficacy, and influence (Fulford & Enz, 1995) . Meaning is defined as the alignment between one's values and the goals or objectives of one's work activities (Fulford & Enz, 1995) . Self-efficacy is the belief that one can successfully perform assigned tasks (Fulford & Enz, 1995) . Finally, influence relates to an individual's belief that they can influence outcomes and decisions in their organization (Fulford & Enz, 1995) . An example item includes "I have freedom in determining how to do my job." The Psychological Empowerment Scale has high reliability (meaning subscale α = .80; self-efficacy subscale α = .70; influence subscale α = .83; Fulford & Enz, 1995) . The internal consistency for this study was .90. COVID-19 Threat. The Perceived Coronavirus Threat questionnaire measures how threatened or worried people are about COVID-19 (Conway et al., 2020) . It is comprised of 6 items, using a 7point Likert-type scale, ranging from 1 (Not True of Me at All) to 7 (Very True of Me), and a sum score was used. An example item is "I am afraid of the coronavirus (COVID-19) ." The Perceived Coronavirus Threat questionnaire previously demonstrated strong internal consistency (α = .88). The internal consistency for this study was .89. Fulfilling Work. Fulfilling work was measured as a latent variable with job satisfaction, meaningful work, work engagement, and workplace positive affect as indicators (Allan et al., 2021) . Job Satisfaction. Job Satisfaction was measured using the Judge et al. (1998) adapted version of the Brayfield and Rothe's (1951) measure of job satisfaction. The modified, 5-item scale uses a 10point Likert-type scale (0 = Strongly Disagree to 10 = Strongly Agree; Judge et al., 1998) , and a sum score was used. An example item is "I find real enjoyment in my work." This scale has demonstrated high reliability (α = .88; Judge et al., 1998) . It also has high convergent validity with the Job Descriptive Index (Judge et al., 1998; Smith et al., 1969) . The internal consistency for this study was .90. Meaningful Work. Meaningful work was measured using the Psychological Meaningfulness Scale (May et al., 2004) . This scale was designed to measure meaning employees find in workrelated activities. The 6-item measure uses a 5-point Likert-type scale (1 = Strongly Disagree to 5 = Strongly Agree), and a sum score was used. An example item includes "The work I do on this job is meaningful to me." This measure has demonstrated high internal consistency (α = .90; May et al., 2004) . The internal consistency for this study was .96. Engagement. Work Engagement was measured using the 6-item absorption subscale from the Utrecht Work Engagement Scale (UWES; Schaufeli et al., 2002) . The measure uses a 7-point Likerttype scale (0 = Never to 6 = Always), and a sum score was used. An example item is "Time flies when I'm working." The absorption subscale demonstrated adequate internal consistency (α = .73 with students and α = .72 with employees) and divergent validity with burnout (Schaufeli et al., 2002) . The internal consistency for this study was .79. Positive Emotions. State positive emotions was measured using the positive affect subscale from the PANAS (Watson et al., 1988) . The positive affect subscale consists of 10 items in which emotion words are rated, such as "excited" and "inspired," using a 5-point Likert-type scale (1 = Very Slightly or Not at All to 5 = Extremely; Watson et al., 1988) . A sum score was used. The instructions "Indicate to what extent you feel this way in your workplace on a daily basis" were used so it was clear emotions experienced at work were of interest. The PANAS has demonstrated high internal consistency (α = .86-.90) and adequate test-retest reliability for the positive affect subscale (r =.47-.68; Watson et al., 1988) . It has also demonstrated convergent validity with other brief measures of affect and divergent validity with distress and psychopathology (Watson et al., 1988) . The internal consistency for this study was .90. Psychological Distress. Psychological distress was measured using the Depression, Anxiety, and Stress Scale-21 Items (DASS-21) scale (Lovibond & Lovibond, 1995) . The DASS-21 is comprised of three subscales-depression, anxiety, and stress-as well as a total score. Participants were asked to rate how often they have experienced symptoms over the past week from 0 (did not apply to me) to 3 (applied to me very much or most of the time), and a sum score was used. An example item includes "I found it difficult to relax." The DASS-21 has demonstrated adequate reliability for each subscale and the total score (.82-.93; Henry & Crawford, 2005; Lovibond & Lovibond, 1995) . It has also demonstrated validity with external anxiety and depression scales and positive and negative emotions (Henry & Crawford, 2005; Lovibond & Lovibond, 1995) . Once the study was approved by the Institutional Review Board, participants were recruited using social media (Reddit, Facebook, and Instagram) and rolling recruitment from the middle of November 2020 through the first week in December 2020. A brief description of the study and the study survey link were posted on the social media sources. If desired, individuals could share the social media post about the study with others. The participants consented to the study and completed the online, anonymous questionnaires discussed in the Measures section one time. For those interested, participants could enter a drawing for four $25 pre-paid debit cards. To evaluate the models, we used structural equation modeling with robust maximum likelihood (MLR) in Mplus 8.4 (Muthen & Muthen, 1998 . To evaluate the fit of the models, we used the chi-square test (χ 2 ), the comparative fit index (CFI), the root mean square error of approximation (RMSEA), and the standardized root-mean-residual (SRMR; Hu & Bentler, 1999) . A significant χ 2 can indicate a poor fitting model, but this test is not reliable in larger samples (Tabachnick & Fidell, 2013) . Criteria for the CFI and RMSEA have ranged from less conservative (CFI ≥ .90; RMSEA ≤ .10, SRMR ≤ .10) to more conservative (CFI ≥ .95; RMSEA ≤ .08; SRMR ≤ .06; Hu & Bentler, 1999; Weston & Gore, 2006) , but researchers should be cautious when using strict cut-offs and should consider sample size and model complexity when judging fit (Weston & Gore, 2006 ). In the current study, we had a complex model with less than 500 participants, so we primarily used the less stringent criteria (Weston & Gore, 2006) . We tested differences in model fit with the scaled chi-square test (Muthen & Muthen, 1998 . When conducting structural equation models with latent variables, using parcels as compared to item level data has many advantages, such as more precise parameter estimates, better model fit, less bias in estimates, increased reliability, and reduced levels of skewness and kurtosis (e.g., Little et al., 2002) . Therefore, for latent constructs comprised of measures with six items or less (perceived COVID-19 threat and empowerment), we used each of the items as an indicator for its corresponding latent variable. For constructs with subscales, we used the subscales as indicators (workplace dignity, COVID-19 impact, hope, psychological distress, and fulfilling work). For constructs without subscales (privilege, organizational support, strengths use, and adaptability), we conducted an exploratory factor analysis and assigned items to parcels in countervailing order according to the size of the factor loading (Weston & Gore, 2006) . This resulted in 41 observed variables in the models. We tested four models in total. First, we tested a measurement model to ensure latent constructs were measured adequately by items and parcels. Second, we tested a full mediation model in which the predictors (i.e., privilege and the work context variables) have no incremental validity beyond the intervening variables (i.e., work context variables and individual characteristics) in the prediction of the outcomes (i.e., fulfilling work and psychological distress). In other words, the full mediation model only included the contextual variables (i.e., privilege and COVID-19 impact) predicting the promotive work context variables (i.e., organizational support and workplace dignity) that predicted the individual characteristics (i.e., hope, strengths use, adaptability, empowerment, and COVID-19 threat), which in turn predicted fulfilling work and psychological distress. Third, we tested the incremental validity model, in which we allowed relations from the predictors (i.e., privilege and the work context variables) to the outcomes. This model tested whether the predictors had incremental validity in the prediction of the outcomes, over and above the intervening variables (i.e., promotive work context variables and individual characteristics). In addition, we allowed COVID-19 impact to predict COVID-19 threat and the outcome variables for the incremental validity model. Fourth, we removed any non-significant paths to find the most parsimonious model and tested a final trimmed model. For all models, we allowed variables within levels (e.g., the individual characteristics) to correlate. Most participants had no missing data (55.9%). Of those with missing data, 91.5% were missing 10 items or less. To assess whether missing data were missing at random, we conducted Little's missing completely at random test on all study items. This test was not significant, χ 2 (16,166) = 16,402.32, p = .095, suggesting that data were missing completely at random. Therefore, we used full information maximum likelihood to calculate estimates, which outperforms other methods of handling missing data, such as listwise deletion, and maintains power without biasing estimates (Tabachnick & Fidell, 2013) . All variables had absolute values of skew and kurtosis within acceptable ranges (Weston & Gore, 2006) . We also examined variance inflation factors and observed no scores less than one or greater than four. The measurement model had acceptable fit to the data, χ 2 (724) = 1461.78, p < .001, CFI = .913, RMSEA = .06, 90% CI [.05, .06], and SRMR = .06, and all indicators loaded onto their respective factors at values of .38 or higher (Wang & Wang, 2012) . Table 1 depicts the correlations among latent factors from the measurement model. All the S-BIT of Work variables correlated with one another as expected. However, COVID-19 impact did not significantly correlate with hope and adaptability, and COVID-19 threat did not significantly correlate with hope, strengths use, and adaptability. The full mediation model had acceptable fit to the data, χ 2 (739) = 1534.14, p < .001, CFI = .906, RMSEA = .06, 90% CI [.05, .06], and SRMR = .07. The incremental validity model represented a significant improvement, χ 2 (733) = 1478.05, p < .001, CFI = .912, RMSEA = .06, 90% CI [.05, .06], SRMR = .07, χ 2 (6) = 79.53, p < .001, but of the additional paths, only privilege significantly predicted psychological distress (β = À.20, p = .016) and only organizational support (β = .28, p < .001) and workplace dignity (β = .19, p = .040) significantly predicted fulfilling work. To find the most parsimonious model, we removed these nonsignificant paths as well as other non-significant paths from the structural model. While the new model represented a slight decline in fit from the previous model, χ 2 (745) = 1502.03, p < .001, CFI = .911, RMSEA = .06, 90% CI [.05, .06], SRMR = .08, χ 2 (12) = 23.98, p = .006, we retained it as the most parsimonious model. As seen in Figure 2 , all paths in the final model were significant. Table 2 includes the estimates, standard errors, and p-values for these paths. The final model explained 52% of the variance in psychological distress and 64% of the variance in fulfilling work. We tested the 13 indirect effects in the final trimmed model with robust confidence intervals from MLR. Table 3 shows the results of these tests. All indirect effects were significant, except for privilege and COVID-19 impact to empowerment via organizational support. This study examined the S-BIT of Work with a sample of service industry workers during the COVID-19 pandemic. We tested the relations from the contextual (COVID-19 impact and privilege), promotive work context (organizational support and workplace dignity), and individual characteristics (hope, strengths use, adaptability, empowerment, and COVID-19 threat) variables to the outcome variables of fulfilling work and psychological distress. Overall, the incremental validity model and the final trimmed model, which only included the significant paths, demonstrated acceptable fit. This result generally supported the propositions of the S-BIT of Work. The Appendix in the online supplemental material includes a detailed list of which secondary hypotheses were supported and not supported. Several variables and relations appeared especially salient for service workers and will be highlighted in the discussion that follows. Regarding the contextual variables, privilege appeared to be a key factor in the model. As expected, privilege was significantly and positively related to both promotive work context variables-organizational support and workplace dignity. Counter to expectations, privilege did not significantly predict fulfilling work. However, privilege indirectly predicted fulfilling work via organizational support and workplace dignity. Thus, the greater the workplace supported service industry workers and promoted dignity, the greater the degree of fulfilling work they experienced. This aligns with past research, suggesting that organizational support and workplace dignity promotes worker well-being (Allen et al., 2003; Bolton, 2007; Duke et al., 2009) . As expected, privilege was also significantly and negatively related to psychological distress. Previous research has shown marginalized populations are negatively affected by economic instability, discrimination, and systemic inequities, and have been disproportionally affected by COVID-19 (e.g., Fassinger, 2008; Kniffin et al., 2020) , all factors that could contribute to greater distress. Additionally, privilege indirectly predicted the individual positive characteristics of strengths use, adaptability, and empowerment through workplace dignity. In other words, the greater the amount of privilege and dignity the service industry workers experienced, the greater their positive individual characteristics were able to flourish. This suggests both broader contextual factors-in this case privilege-and the more immediate environment-in this case a work setting that facilitates dignity-might influence the expression of internal characteristics, aligning with the theoretical propositions of the S-BIT of Work . Thus, the more privileged a person is, the more likely they are to experience dignity in the workplace, and the more likely they can use beneficial characteristics (e.g., strengths and adaptability) to their advantage. Unexpectedly, apart from empowerment, the indirect relationships between privilege and each of the individual characteristics (hope, strengths use, adaptability, and COVID-19 threat) via organizational support were non-significant, contrary to the S-BIT of Work's theoretical propositions and a body of literature supporting the relevance of workplace support (see Owens et al., 2019) . Privilege indirectly predicted empowerment through organizational support. During COVID-19, workplace dignity may be more important than workplace support for service industry workers, especially when considering social distancing guidelines may limit social interactions. The contextual variable of COVID-19 impact significantly and positively predicted psychological distress. COVID-19 impact also negatively predicted organizational support and workplace dignity. Thus, it appears COVID-19 is detrimental to the functioning of the workplace. Perhaps the safety concerns, social distancing parameters, and the overall additional stress of COVID-19 has put a strain on both work settings and workers. In addition, COVID-19 impact did not directly predict fulfilling work. However, COVID-19 impact indirectly predicted fulfilling work via organizational support and workplace dignity. Therefore, results suggest COVID-19 negatively related to the employees' well-being in the workplace, regardless of the extent to which their workplace was promotive. COVID-19 impact indirectly predicted strengths use, adaptability, and empowerment via workplace dignity. COVID-19 impact also indirectly predicted empowerment via organizational support. Additional research following COVID-19 will be helpful to examine these factors further in less acute situations. When examining the promotive work context variables-organizational support and workplace dignity-workplace dignity appeared to be more instrumental. In addition to the relations previously mentioned, workplace dignity also indirectly predicted fulfilling work via strengths use. However, both workplace dignity and organizational support directly predicted fulfilling work, but not psychological distress. Therefore, it seems that a promotive work context is more predictive of greater well-being in the work context than protecting against or decreasing psychological distress. Moreover, of the individual characteristics in the model, strengths use was most related to fulfilling work. Past research supports the role of strengths use in promoting wellbeing in the workplace (e.g., Keenan & Mostert, 2013; Littman-Ovadia & Steger, 2010) . Unexpectedly, the predicted direct and indirect relationships involving the positive individual characteristic of hope were not supported. Generally, hope is perceived as a trait that helps individuals overcome challenges (Owens et al., 2018; Snyder et al., 1991) and relevant to the world of work (e.g., Reichard et al., 2013; Wandeler, et al., 2017) . Therefore, when facing a challenge such as working during COVID-19, hope would be expected to be beneficial. Perhaps strengths use, adaptability, and empowerment are more relevant during COVID-19 and collectively overshadowed hope's contribution. Hope can also be conceptualized as an individual strength; therefore, statistically, it may have had redundancy with the more global construct of strengths use. It is also possible that because trait hope was measured instead of state hope, the variable was not as pertinent to the current situation. Additional research examining the role of hope in the S-BIT of Work and with service industry workers and other samples is needed. As previously noted, privilege seems to be an important contextual variable to consider not only in light of a pandemic, but also among service industry workers, positions commonly filled by marginalized groups. Both recognizing and addressing the importance of privilege during these times, but also once the pandemic has resolved, will be important to enhance worker well-being. Work settings could aim to broaden their recruitment strategies to recruit diverse pools of applicants as well as create greater access to positions for those with less privilege. Places of employment could also work to implement policies designed to create greater equity in the workplace and reduce barriers for those with less privilege through intentional activities, such as mentorship programs and leadership trainings. In addition, work settings could provide supervisor and worker trainings related to equity, diversity, and inclusivity, as well as biases and discrimination, to provide greater knowledge and awareness related to privilege. Relatedly, workplace dignity also played a salient role in the model. Finding ways to acknowledge and promote the dignity of essential workers seems especially timely during these challenging times and would also be advantageous beyond working during COVID-19. Workplaces could strive to find ways to actively seek out the input and voices of their employees and gather their ideas for improvement. For instance, employees could be involved in committees to address employee concerns and regular town halls could be conducted to brainstorm and gather feedback from a large group. Employers and work settings could also implement company-wide mechanisms to recognize and celebrate their employees through awards, recognition, and/or incentives. Overall, finding ways to promote employees' strengths and positive characteristics appears advantageous. This study is not without limitations. First, recruitment took place during a brief period during COVID-19. Since the time of the outbreak through today, many things have changed, greater knowledge has become available, and in some cases there are less restrictions in the workplace. Thus, findings must be interpreted with those considerations in mind and not too heavily generalized. Additionally, 9% of the sample did not report their current job role, which can make generalizing the results more challenging. However, our greatest interest was in the overall experience of service industry workers, not specific jobs. The screener question used in the survey provides confidence that goal was achieved. Moreover, given the focus of the S-BIT of Work, the sample would also benefit from greater diversity across all demographics assessed. Given the recruitment method, self-selection bias must also be considered. It is possible employees invested in their jobs or frustrated by the circumstances were more inclined to complete the questionnaires. Future research could attempt different recruitment strategies and seek samples from diverse communities to address these limitations. Another limitation was the cross-sectional data. This limited the ability to determine any casual inferences about the results as well as the direction of the relations between variables. In future studies, longitudinal data could be collected to address these limitations, as well as examine reciprocal relations between the positive individual characteristics and contextual supports and barriers and the work context, as originally proposed by Owens et al. (2019) . Given this was the first empirical examination of the S-BIT of Work, there are many future areas to explore. Different worker and student populations could be examined both during and after COVID-19. Additionally, service industry workers' experience after COVID-19 could be examined. Finally, additional contextual, promotive work context, and individual positive characteristics variables could be examined. As noted previously, it would be worthwhile to further examine the construct of hope both with the same and different samples. Specifically, there was a high correlation between hope and strengths use in the current study, which was surprising. These constructs may overlap to such a degree that they are redundant within the S-BIT of Work model. Future studies may operationalize or measure hope and strengths use differently or modify the S-BIT of Work appropriately. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The first author received financial support from the University of Minnesota Duluth's new faculty start-up funds that supported conducting this study. Are work well-being variables distinct? 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