Mental Health, Workplace Safety, and Vaccine Hesitancy Among Grocery Store Workers During the COVID-19 Pandemic

Brian Mayer
University of Arizona

Sabrina Helm
University of Arizona

Melissa Barnett
University of Arizona

Mona Arora
University of Arizona

Publication Date: 2022

Abstract

This project focuses on the mental health impacts of the COVID-19 pandemic on grocery store workers in Arizona across two waves of survey data collected in July 2020 and January 2021. In particular, we examine how grocery store worker perceptions of workplace safety affected their mental health. We found that workers who perceived their workplace as safe during the pandemic and their employers as providing sufficient protections had lower levels of mental health stress. Key to these risk perceptions were the provision of regular safety trainings regarding workplace policies on COVID-19. We also examined vaccine hesitancy among grocery store workers and found that those workers who had higher confidence in the efficacy of COVID-19 vaccines, along with convenient access to vaccination locations, were less vaccine hesitant. Perceptions of being safe at work however, were not significantly correlated with vaccine hesitancy, while feeling protected by one’s employer reduced vaccine hesitancy. Based on these findings, we conclude more attention is needed to understand the long-term mental health effects of the pandemic along with improved policies and guidelines for protecting frontline workers.


Introduction

Frontline essential workers face elevated risks of exposure to COVID-19 because of the interactive nature of their jobs, which require high levels of interaction with the general public and coworkers (Sim, 20201). A healthy workforce in essential services such as health care, first response, and retail and other services is vital to combating the COVID-19 pandemic. These frontline workers provide necessary access to consumer goods and services and represent a potential source of transmission in their communities (Lan et al., 20212). However, the extant literature on COVID-19 exposure risks and health effects among frontline workers is predominately focused on health care workers and neglects hazards specific to other occupations in the retail and service sectors.

The shift from being a retail worker to an essential worker has not been without its tensions, as Lakoff (20203) observes, “those whose work is categorized as 'essential' are often those whose lives are most precarious.” Grocery store workers are an important example of employees in low-status jobs who experienced transformational shifts in occupational expectations due to the pandemic. According to the Bureau of Labor Statistics (2020), grocery store employees are among the lowest paid jobs, with a national median pay of $11.37 per hour.

The identity and meaning people obtain from their work remains a central issue in contemporary sociology and organizational scholarship (Ramarajan & Reid, 20134; Reid, 20155; Strangleman, 20126). Despite recent debates over the detachment of meaning from the post-Fordist workplace (c.f. Bauman, 19987; Casey, 19958; Sennett, 19989; Strangleman, 2012), studies of the contemporary workforce and management practices continue to confirm the interdependence between employees’ identification with work and their wellbeing and satisfaction with that work (Brown et al., 200710). For most workers, workplace identities develop over time to represent “the goals, values, beliefs, norms, interaction styles and time horizons that are typically associated with a role” (Ashforth, 2001:611). In unsettled times however, workplace identities are likely to come under threat, especially for workers in traditionally less prestigious occupations within the service sector that suddenly gained ‘essential’ status.

Literature Review

Workplace Safety

Retail workers are less likely than health care workers to have had previous experiences with basic infection control procedures or access to personal protective equipment (PPE) (Parks et al., 202012). For many non–health care industries that are deemed essential, the implementation of workplace protections during the COVID-19 pandemic led to substantial transformations of both physical spaces and normative practices. Some workplaces, such as grocery stores, have also become sites of political and cultural dispute and conflict concerning public health practices, such as face mask wearing and social distancing. Recent studies suggest that grocery stores are among several transmission clusters in China (Wang et al., 2020a13) and at least perceived to be so in the United States (Schoeni et al., 202114). The potential stressors associated with the transformation of retail spaces such as grocery stores into epicenters of public health practices such as mask-wearing and social distancing, along with expressions of frustration and anger with these practices, are likely to be consequential for the mental health of this workforce (Kisely et al., 202015).

Emerging literature on the mental health consequences of the COVID-19 pandemic suggests an increasing prevalence of mental health illness. In China, studies found that at least one-third of their study populations had moderate-to-severe mental health distress since the start of the pandemic (Wang et al., 2020b16; Qui et al., 2020). Although studies in the United States have found comparatively lower rates of mental health distress (Holingue et al. 202017), the emerging literature suggests that mental health distress is likely to increase substantially as the pandemic continues (Holingue, Kalb, et al., 202018). Among other frontline worker populations, such as in healthcare, reported rates of depression and anxiety are already significantly higher than the general US population (Lai et al., 202019; Shechter et al., 202020).

Unlike healthcare workers, grocery store workers are far less likely to have had any previous experience with workplace protections related to the management of infectious disease. Nationwide, grocery stores have become transformed spaces—with mask mandates or requests, protective shields separating workers from customers, and new rules governing interactions between customers and workers. Grocery workers have also been asked to enforce these new policies and maintain and clean their workplaces. Based on previous research, these unfamiliar and challenging workplace responsibilities, along with a sense of uncontrollability in the absence of effective workplace protections, have been shown to contribute to deleterious mental health impacts on employees (Kasperson et al., 198821; Slovic, 198722). Workers’ perceptions of occupational risks are often correlated with the presence of effective workplace safety practices (Neal et al., 200023; Ayim et al., 200724). As grocery store workers entered into these transformed workplaces, their employers’ implementation and enforcement of pandemic-specific policies, or lack thereof, are also potential contributors to workers’ risk perceptions and mental health.

Vaccine Hesitancy

The World Health Organization Strategic Advisory Group of Experts (WHO SAGE) working group defines vaccine hesitancy as the “delay of acceptance or refusal of vaccination despite availability of vaccination services” (MacDonald et al., 2015, p. 416325). To better understand the drivers of vaccine hesitancy, the WHO SAGE working group has developed the “Three Cs” model which identifies three central factors involved in vaccine hesitancy: Confidence, Convenience, and Complacency (MacDonald et al., 2015). In this model, confidence refers to the degree of trust in the effectiveness and safety of a vaccine, trust in the system that delivers the vaccine, and the perception of trustworthy agents developing and administering the vaccine. Convenience refers to the availability, affordability, and accessibility of the vaccine. Finally, complacency refers to the risks individuals perceive will be prevented by vaccination.

Workplace factors are not explicitly included in the list of vaccine hesitance determinants compiled by the WHO SAGE working group (MacDonald et al., 2015) but likely provide context for the “Three Cs” model in terms of affecting workers’ vaccine hesitancy. For example, confidence can be impacted when coworkers or one’s employer recommend, or advise against, vaccination (Lazarus et al, 202026). Convenience may be increased when vaccine distribution sites are offered at the workplace (Graves et al., 201427; Luthy et al., 2016). Complacency may also be increased when work-based perceptions of personal risk of getting infected with COVID-19, or suffering severe effects of the disease, are perceived as low.

Workplace factors beyond increased risk of infection at work may also influence vaccine hesitancy. For example, the occupational categories in the United States with the highest hesitancy, as identified by King et al. (201228), are construction/extraction, installation/maintenance/repair, farming/fishing/forestry, transportation/material moving, and production. Notably, these included categories with multiple workplace COVID-19 outbreaks, such as meat packing plants and agricultural farms (King et al., 2021), underscoring that workplace risk alone does not lead to reduced vaccine hesitancy. Instead, consideration of variation of workers’ perceptions of risks and access to vaccines may help us better understand hesitancy. For instance, access to vaccines may be less convenient for certain occupational groups within certain work settings. As noted with regard to the “Three Cs” model of vaccine hesitancy, convenience is an important factor in increasing vaccine uptake (MacDonald et al., 2015). Fossen et al. (202129) determined that healthcare personnel working in clinical areas with the most convenient access to vaccines were more likely to get vaccinated than other types of healthcare professions (for similar results, see King et al., 2021).

Research Design

Research Questions

This research project is guided by three main research questions. First, we are interested in learning about the potential risks of exposure to COVID-19 as perceived by grocery store workers in Arizona and the efforts being made to protect this vulnerable workforce. Second, we are interested in the mental health and well-being of grocery store workers and how these perceived risks related to the pandemic might impact mental health distress. Finally, we are interested in grocery store workers’ vaccine hesitancy as expressed by the consideration of opting out of receiving a COVID-19 vaccine.

Data, Methods and Procedures

Near the beginning of the COVID-19 pandemic in the spring of 2021, our research team began planning a statewide survey of frontline essential workers in Arizona. To reach this population, we contacted the United Food and Commercial Workers (UFCW) union Local 99, representing approximately 24,000 workers in Arizona, and began a conversation about their membership and concerns with the early impacts of the pandemic. Through this partnership, we developed the Arizona Frontline Worker Survey (AFWS) to be applicable to the experiences of a broad array of workers represented by the UFWC including grocery workers, meatpackers, administrative assistants, and other retail and service sector employees.

Two waves of the AWFS are discussed in this report. The first wave was distributed in July 2020, followed by the second wave six months later in January 2021. The first wave was distributed via email in English and Spanish to the 18,000 potential participants who were over 18 years of age and had both active UFCW membership and an email address on file. Participants were entered into a lottery for forty $50 gift cards. Response time for the first wave was estimated to be fifteen minutes. The second wave repeats the same questions and includes an additional module specifically on vaccine hesitancy and required a slightly longer response time of twenty minutes.

Wave 1 was completed by 3,663 participants in July 2020, 2,028 of whom agreed to be contacted again and were sent a follow-up email in January 2021. Wave 2 was initially distributed both to those 2,028 participants as a direct follow-up to emails provided in response to Wave 1. Two weeks after the initial distribution of Wave 2, a series of invitations were sent again to the overall UFWC Local 99 email list. Follow-up participants were prevented from completing both survey opportunities. Of those potential 2,028 follow-up participants, 841 respondents completed, or partially completed, both waves. For those in the general invitation for the second wave, 1,331 new participants completed the AFWS for the first time. Thus, for analyses sake, we generated two cross-sectional samples of 3,662 participants in Wave 1 and 2,172 participants (follow-up and new participants) for Wave 2, along with a longitudinal dataset of 841 participants with reliable data from both waves. The University of Arizona Institutional Review Board approved all study protocols (IRB# 2006736568).

Health and Well-Being Measures

The AFWS contains two measures of mental health distress, the Patient Health Questionnaire (PHQ-4) and the Perceived Stress Scale (PSS-4), which are highly reliable and validated screening measures of mental health morbidity and have been used to examine mental health outcomes in other populations of workers affected by the COVID-19 pandemic (Tam et al., 202130, Zhang et al., 2020a31, Zhang et al., 2020b32). The PHQ-4 assesses feelings of anxiety and depression using four items which are totaled to produce a generalizable assessment of mental health distress ranging from normal (0-2), mild (3-5), moderate (6-8), to severe (9-12) (Löwe et al., 2010).

The four item Perceived Stress Scale (PSS-4) (Kroenke et al., 200933, Cohen et al., 198334) measures the degree to which life situations are appraised as unpredictable, uncontrollable, and overwhelming and therefore stressful to the participant (Warttig et al., 201335). This measure assesses the frequency of these experiences within the previous month on a five-point Likert scale ranging from “never” (zero) to “very often” (four). Compared to longer perceived stress scales, the PSS-4 exhibits sufficient internal reliability across multiple study populations (Lee, 201236; Mitchell et al., 200837).

We also included self-rated health measure. It was a single-item ordinal measure with five levels ranging from “poor” (one) to “excellent” (five). This measure is a widely used indicator of general health status in epidemiologic and population health research and is generally believed to be highly predictive with subsequent mortality and varied measures of morbidity, disability, and utilization of health services (Zajacova & Dowd, 201138).

Workplace Risk Perception Measures

We developed several measures of workplace risk perceptions that focused on the changing conditions in the workplace related to COVID-19 to assess the relationship between vaccine hesitancy and workplace conditions for frontline essential workers.

Workplace Safety. To measure workers' perceptions of workplace safety, we asked respondents to answer with the following question: “How safe do you feel at work during the COVID-19 pandemic?” Respondents were allowed to choose between four responses, ranging from one (very unsafe) to four (very safe).

Employer Concern for Employee Health and Safety. To measure workers’ perception of the degree to which their employer prioritized employee health and safety, we asked respondents to show their agreement, ranging from from one (strongly disagree) to four (strongly agree), with the following statement: “My employer is doing enough to keep me safe from COVID-19.”

Customer Compliance. Customer compliance measures workers’ estimations of how many customers follow store policies and public health measures. Respondents were asked about several pandemic-related customer behaviors such as “following posted rules or procedures,” “respecting instructions from employees,” “maintaining social distancing,” and “wearing face coverings or masks.” Respondents were asked to estimate how many customers complied with these behaviors, ranging from one (none) to five (all). We indexed scores for these four questions to produce a scale of perceived customer compliance (α =0.79).

Negative Customer Encounters. Negative Customer Encounters measures workers’ perceptions of the chances they might encounter an angry or frustrated customer while at work. Respondents were asked to estimate the likelihood, ranging from one (“extremely unlikely”) to five (“extremely likely”), that three situations might occur at their workplace: (1) “I could be verbally threatened by a customer”, (2) “I could be physically threatened by a customer,” and (3) “I will have to confront a customer for not following business policies.” Scores were averaged to produce an index ranging from one to five (α = 0.70).

Efficacy of Public Health Practices. Efficacy of Public Health Practices is an index of workers’ perceptions of the efficacy of 14 public health practices related to the COVID-19 pandemic. Respondents were asked, “In your opinion, how effective are the following actions in keeping you safe from COVID-19." The 14 health practices included such things as mask wearing, disinfecting belongings, avoiding crowded spaces, and practicing social distancing. Respondents ranked health practices on a scale ranging from one (not effective) to five (very effective). We indexed all 14 responses to produce a scale of perceived public health practices efficacy (α =0.92).

Vaccine Hesitancy Measures

To assess hesitancy to get the COVID-19 vaccine, the AFWS asked workers: “iIf a vaccine was made available and affordable to you in the near future, how likely would you be personally to get vaccinated?” Responses were recorded on a four-point Likert scale ranging from “very likely” and “somewhat likely” to “not too likely” and “not likely.”

The “Three Cs”. The AFWS also includes questions to measure each aspect of the "Three Cs" model. Confidence was assessed by the question: “How confident are you that currently approved vaccines in the US are safe and effective?” Responses were recorded on a four-point Likert scale ranging from one (“not at all”) to four (“a great deal.”) Convenience was assessed by an index of four questions about aspects of the vaccine distribution that were most important to the respondent, namely: (a) “a vaccine is free to me,” (b) “I do not have to take time off from work,” (c) “I can get the vaccine close to home,” and (d) “I can get the vaccine at work.” Responses for convenience ranged from zero (low) to four (high) in a strongly cohesive scale (α =0.81). Complacency was assessed using an index of three questions asking respondents to rate their level of concern for (a) being infected with the coronavirus, (b) that if infected, they would experience severe or life-threatening symptoms, and (c) that they might potentially transmit the coronavirus to another person. Responses ranged on a scale of one (high chance) to five (low chance), producing an index of degree of complacency regarding COVID-19 (α =0.79).

Demographic Characteristics

To control for variation in our sample of frontline workers, we collected data on our respondents’ sociodemographic characteristics. Specifically, we collected information on biological sex, race and ethnicity, age, educational attainment, marital status, and parental status. We assessed financial well-being with a scale developed by the Consumer Financial Protection Bureau (2015). This abbreviated five-item scale assesses participants’ sense of control over their finances. Scores on the scale ranged from zero (lowest) to 20 (highest) degree of financial well-being.

Results and Discussion

Descriptive statistics for two waves of the AFWS are presented below in Table 1. Our first wave, launched in July 2020 received more responses than Wave 2, which is not unusual for survey work of this nature. There demographic characteristics between the two waves was largely consistent, with the exception of participants in Wave 2 being slightly less racially diverse. However, the racial diversity of the follow-up subpopulation which completed both waves was the same as Wave 1. Lastly, participants in Wave 2 were slightly older on average than Wave 1.

Table 1. Arizona Frontline Worker Survey Descriptive Statistics

Wave 1
n = 3,996
Wave 2
n = 2,172
Waves 1 and 2a
n = 604
Number Percent Number Percent Number Percent
Sex
Male 1,029 31.9 588 27.1 161 28.8
Female 2,180 67.5 1,372 63.2 395 70.7
Race
White 2,365 59.2 1,560 71.8 452 74.8
Non-White 961 28.4 457 21.0 120 19.9
Ethnicity
Hispanic 884 22.1 477 24.2 431 71.4
Non-Hispanic 2,243 56.1 1,464 67.4 125 20.7
Age
18-25 483 15.0 174 8.0 46 7.6
26-55 1,698 52.6 1,067 54.1 313 51.7
≥ 55 1,045 27.1 736 33.9 200 33.1
Education
< High School 170 5.3 104 5.3 21 3.8
High School 1,191 37.0 656 33.2 183 32.7
Some College 1,204 37.4 1,003 40.8 290 48.0
College or Advanced Degree 282 7.1 215 10.8 63 10.5
Income
$25k 1,207 33.5 562 27.1 146 27.4
$25k - $40k 1,118 31.0 657 31.6 185 34.7
$40k - $60k 617 15.4 421 20.3 98 18.4
$60k 664 18.4 433 20.9 104 19.5
Totals may not equal 100% due to missing data.
aThis column refers to the subsample which completed both Waves 1 and 2 of the survey.

Although the AFWS was designed to be applicable to the broad range of occupational categories represented by the UFCW, by far the most common type of worker to respond to the survey were grocery workers, comprising 84% of Wave 1 and 87% of Wave 2 respondents. Table 2 reports the frequency of job type by survey respondent for Waves 1 and 2. All respondents in the subsample who particpated in both Waves 1 and 2 were grocery store workers. In the remaining analyses, including the comparisons of Waves 1 and 2, we limit our discussion to grocery store workers.

Table 2. Arizona Frontline Worker Survey Occupational Categories

Wave 1
n = 3,996
Wave 2
n = 2,172
Number Percent Number Percent
Grocery Worker 3,344 83.7 1,881 86.6
Food 82 2.1 34 1.6
Medical Office Worker 58 1.5 137 6.1
Custodial Worker 32 0.8 19 0.9
Parking Attendant 7 0.2 2 0.1
Other 340 8.5 457 4.7

Given the importance of public health surveillance during COVID-19, we included a set of questions about potential exposure to the coronavirus. We asked respondents both if they had tested positive at any point prior to completing the survey and if they believed they had been infected with the coronavirus regardless of any testing. Overall, we observed relatively low rates of COVID-19 infections as defined solely by the receipt of a positive test. For Wave 1, administered in July of 2020, only 1.4% of our grocery store worker sampled reported testing positive at any point prior to completing the survey (see Table 3). July 2020 marked the peak of the first wave of the pandemic in Arizona, where some 3,600 new cases were being observed each day (New York Times, 202239). However, a much higher rate of believed infections was reported (7.8%) and more closely approximates statewide trends. Wave 2, administered in January 2021, corresponded with the pandemic’s second wave in Arizona which peaked close to 10,000 new cases each day. Yet again, we observed comparatively low rates of COVID-19 infection with only 0.5% of Wave 2 respondents reporting testing positive and 2.3% believing that had been infected with the coronavirus between July 2020 and January 2021.

Table 3. Rates of COVID-19 Infection Among Grocery Workers

Wave 1
n = 3,996
Wave 2
n = 2,172
Number Percent Number Percent
Tested Positive 45 1.4 10 0.5
Believed Infected 261 7.8 50 2.3

Workplace Safety

One of our main research questions was the degree to which workers felt their employers provided protection from exposure to COVID-19. To assess this topic, we designed the two survey measures of workplace safety mentioned above, and, we also asked workers about their access to personal protective equipment (PPE) at work and the administrative safety controls (e.g., workplace redesigns, signage, policies) that their employers had implemented. Responses did not vary much between Wave 1 and Wave 2. We assume this consistency in employer actions as likely the result of most major changes being made in the immediate aftermath of the pandemic’s outbreak dyring Spring 2020 with little to no modifications being made subsequently.

Table 4, below, shows the odds ratios from a logistic regression model with various types of PPE potentially available to workers and training on their use and the bivariate measure of participants’ sense of being safe (one) or not safe at work (zero). By far the strongest predictor of feeling safe was having access to safety trainings. Indeed, according to our results, grocery workers who had access to safety training were at least twice as likely to feel safe in their workplace as those who did not have access to training.

Table 4. Personal Protective Equipment and Perceived Safety at Work

Workplace Characteristics Wave 1
Odds Ratio (95% CI)
Wave 2
Odds Ratio (95% CI)

Personal Protective Equipment and Trainings
Safety training 2.03 (1.60-2.57)* 2.49 (1.46-4.25)***
Hand sanitizer 1.93 (1.56-2.38)* 1.12(0.68-1.87)*
Face masks 1.49 (1.06-2.10)** 0.90 (0.37-2.18)
Hand washing stations 1.40 (1.18-1.66)** 2.28 (1.53-3.39)***
Face shields 1.23 (1.01-1.51)*** 1.31 (0.84-2.05)
Gloves 1.10 (0.92-1.32) 0.95 (0.64-1.52)
Temperature screening 0.82 (0.77-0.86) ---
Employment status
Part-time 1.14 (0.98-1.33) 1.20 (0.78-1.61)
Job tenure
1 year 1.35 (1.11-1.65)** 1.15 (0.69-1.92)
*** Significant at P < .001; ** Significant at P = .01, * Significant at P = .05; determined by 2-tailed test of significance.

Of the various PPE we asked participants to evaluate, the provision of gloves and temperature screenings were insignificantly correlated with feeling safe at work in Wave 1. For Wave 2, we eliminated the temperature screening question. By January 2021, being provide both face masks and face shields were also no longer significant.

At the outset of our study we assumed workers would place the most importance on their employers providing physical safety measures such as face masks, gloves, and hand sanitizer. Our survey results, however, were surprising in this regard. On the one hand, the AFWS did show that workers perceived several physical safety measures—including hand sanitizer, hand washing stations, and masks or face shields—as valuable. On the other hand, their relatively lower predictive size shows that workers valued access to safety training more, especially in Wave 2. For the most part, PPE and training remained equally important across the two waves, though being provided face masks in Wave 2 was no longer a significant predictor.

Table 5 examines how other controls and modifications employers made during the pandemic affected workers' sense of safety and being protected at work. In this case, workers most valued employers who required social distancing in the workplace. Those workers who indicated that their employers required customers to adhere to social distancing guidelines were more than twice as likely to feel both safe and protected compared to workers in locations lacking social distancing requirements.

Table 5. Workplace Controls and Perceived Safety at Work for Wave 1

Workplace Characteristics Safety at Work
Odds Ratio (95% CI)
Protected at Work
Odds Ratio (95% CI)

Workplace controls
Social distancing 2.55 (2.15-3.02)*** 2.36 (2.36-3.31) ***
Free face masks or gloves for customers 1.65 (1.40-1.94)*** 1.40 (1.37-1.89) ***
Improved cleaning 1.59 (1.34-1.89) *** 1.75 (1.47-2.10) ***
Limited customers 1.45 (1.20-1.75) *** 1.70 (1.42-2.04) ***
Employee face mask requirement 1.04 (0.68-1.59) 1.13 (0.73-1.75)
Visible signage 1.05 (0.86-1.29) 1.06 (0.87-1.30)
Floor markings 1.00 (0.79-1.26) 0.80 (0.63-1.01)
Sneeze guards 0.76 (0.58-0.98)** 0.70 (0.52-0.88)***
Employment status
Part-time 1.14 (0.97-1.33) 1.10 (0.94-1.28)
Full-time 1 [Reference] 1 [Reference]
Job Tenure
<1 year 1.15 (1.15-1.70) 1.73 (1.42-2.10)
≥1 year 1 [Reference] 1 [Reference]
*** Significant at P < .001; ** Significant at P = .01; determined by 2-tailed test of significance.

Other customer-oriented measures were also significantly correlated with feeling safe and protected, including: providing free masks or gloves to customers, limiting the number of customers allowed in a workplace at a given time, and requiring improved cleaning measures.

Mental Health

The second major research question we sought to explore through the AFWS was the mental health state of frontline workers during the pandemic. In particular, we utilized the two short assessments of mental health distress mentioned above: The PHQ-4, which assesses symptoms of anxiety and depression, and the PSS-4, which assesses symptoms of stress.

For both Wave 1 and Wave 2, we observed high levels of anxiety and distress with close to 17% of our study population exhibiting symptoms of severe distress on the PHQ-4 scale (See Table 6 below). Nationally, anxiety and depression increased in the general U.S. population during the pandemic, however, the observed levels of severe symptoms as measured by the PHQ-4 have been closer to 10% (Khubchandani et al., 202140). There was very little change in this measure between waves.

Table 6. Mental Health Distress on the Patient Health Questionnaire (PHQ-4) for Waves 1 and 2

Wave 1
n = 3,996
Wave 2
n = 2,172
Number Percent Number Percent
Normal 1,162 35 757 36.9
Mild 931 28 580 28.3
Moderate 569 17.1 372 18.1
Severe 660 16.5 318 16.9

On the PSS-4 measure of perceived stress, respondents scored an average of 6.95 in Wave 1 and 6.96 in Wave 2. Unlike the PHQ-4, there are no official cutoff points on the PSS-4 which establish normal, mild, moderate, or severe levels of stress. However, many studies set a benchmark of problematic stress as greater than or equal to a score of seven. Just over half of our study sample approaches that benchmark in both waves. However, the PSS-4 is not a diagnostic tool for stress-related behavioral health issues and instead is used to approximate potentially problematic patterns. Combined with the PHQ-4 scores, we find more than half of our sample to have problematic scores indicative of high levels of mental health distress.

Based on these observations, we next combined our measures of workplace safety and mental health distress to explore our third research question, which asks whether hazardous workplace conditions contribute to increases in mental health distress. To answer this question, we restricted our analysis to the subsample of respondents which participated in both survey waves. Then, we examined changes in their mental health distress scores from Wave 1 to Wave 2 using an ordinary least squares regression model. The independent variables for this model measuring perceptions of workplace safety and protections are measured at January 2021. Therefore, interpretations of this model are based on the assumption that increases or decreases in mental health distress measured in January 2021 are functions of perceptions of risk assessed also in January. As such, any changes in mental health distress measures are the difference between Wave 1 and Wave 2 scoring where negative correlations signify a decrease in mental health distress and positive correlations as increases.

Table 7. Workplace Safety and Grocery Worker Mental Health Distress Related to COVID-19

Independent Variables Effect on Worker Anxiety and Depressiona
(PHQ-4 Measure)
Effect on Worker Perceived Stressb
(PSS-4 Measure)
Safety at Work
Safe -1.79 (0.36)*** -0.55 (0.31)
Not Safe 1 [Reference] 1 [Reference]
Protected at Work
Protected -0.15 (0.35) -0.12 (0.35)
Not Protected 1 [Reference] 1 [Reference]
Contracted COVID-19 0.03 (0.35) -0.12 (0.30)
Sex
Female 1.09 (0.33)*** 0.55 (0.30)**
Male 1 [Reference] 1 [Reference]
Race/Ethnicity
Hispanic -0.29 (0.36) -0.22 (0.30)
Non-Hispanic White 1 [Reference] 1 [Reference]
Age Group
18-25 1 [Reference 1 [Reference]
26-34 -1.67 (0.66) -1.45 (0.57)**
35-54 -2.60 (0.59)*** -1.95 (0.50)***
≥55 -2.84 (0.60)*** -2.58 (0.51)***
Marital Status
Single 1 [Reference] 1 [Reference]
Married or Cohabitating 0.86 (0.33)** 0.33 (0.27)
Educational Attainment
<High school 1 [Reference] 1 [Reference]
High school 1.54 (0.80)*** -0.47 (0.67)
College 1.69 (0.78) -0.08 (0.66)
Other
Financial Well-Being -1.35 (0.02)*** -1.57 (0.01)***
Constant 12.99 (0.43) 17.36 (0.78)
r2 0.30 0.35
Results from ordinary least squares regression model. Sample restricted to subset of respondents which participated in both Wave 1 and Wave 2 of the survey (n = 604).
aThis column reports the B (SE) or the effect of the independent variable on the change in respondent PHQ-4 scores between Wave 1 and Wave 2 of the survey.
bThis column reports the B (SE) or the effect of the independent variable on the change in respondent PSS-4 scores between Wave 1 and Wave 2 of the survey.
*** Significant at P < .001; determined by 2-tailed test of significance, ** Significant at P = .01; determined by 2-tailed test of significance.

Elsewhere, we reported that grocery workers who perceived being safe at work during the first wave of the COVID-19 pandemic were less likely to experience mental health distress (Mayer et al., 202141). Here in Table 7, we include these same independent variables and test whether they also predict any potential changes in mental health distress later in the pandemic. Similar to our earlier findings, the results showed that workers who perceived feeling safe at work in January 2021 were strongly correlated to reductions in their mental health distress (PHQ-4) from July 2020 to January 2021. (This result was only statistically significant for the PHQ-4 measure, not the PSS-4 measure.) Interestingly, however, workers' perceptions that their employer was doing enough to protect them from COVID-19 were not statistically significant indicators of any changes in mental health distress.

These are interesting findings, as the pandemic has been quite cyclical in terms of new variants causing multiple spikes in transmission, as well as the introduction to the COVID-19 vaccines in the spring of 2021. Whereas feeling safe and protected in the workplace at the start of the pandemic helped to protect workers against potential mental health problems, the feeling of being safe is also associated with a reduction in mental health distress over a six-month period but the perception that one’s employer is doing enough to mitigate COVID-19 risks is not. This finding is likely suggestive that the management of workplace risks is interpreted very much as an individual function and is potentially not perceived as dependent on one’s employer. Multiple demographic characteristics are also statistically significant predictors of changes in mental health, including sex and age. Women were significantly more likely than men to have experienced an increase in mental health distress during Wave 2 while respondents over age 25 were more likely to have experienced a decrease. Financial well-being was also a significant predictor of reductions in mental health distress over time.

Vaccine Hesitancy

Table 8 shows the results for our ordinary least squares model predicting workers' vaccine hesitancy at Wave 2. Of the “Three Cs,” two components were statistically significant predictors of vaccine hesitancy among grocery workers: Confidence and Convenience. Confidence in the safety and efficacy of COVID-19 vaccines is the strongest predictor of workers being more receptive toward the vaccines (B=-.80, p=<.001). Convenience was also statistically significant and associated with lower hesitancy (B=-.15, p=<.001). However, our measure of complacency was not correlated with vaccine hesitancy at Wave 2 at a statistically significant level.

Table 8. Factors Affecting Vaccine Hesitancy Among Grocery Workers

Predictor Effect on Vaccine Hesitancya Standard Errorb
The Three Cs
Confidence -0.80*** 0.04
Convenience -0.15*** 0.04
Complacency 0.01 0.01
Workplace Risks
Perceived Safety
at Work
0.01 0.07
Perceived Employer
Protection
0.23*** 0.07
Customer Compliance
with Safety
-0.12 0.05
Belief in Public Health -0.12*** 0.07
Demographic Variables
Sex (Female) 0.12 0.07
Race (Nonwhite) -0.17 0.12
Ethnicity (Hispanic) 0.08 0.13
Age (55+) -0.03 0.06
Education
Some College -0.08 0.07
College -0.09 0.07
Other
Financial Wellbeing -0.00 0.10
Constant 4.90 0.227
Results from ordinary least squares regression model. Sample restricted to subset of respondents which participated in both Wave 1 and Wave 2 of the survey (n = 604).
aThis column reports the the unstandardized beta (B).
bThis column reports the standard error for the unstandardized beta (SE B).
*** Significant at P < .001; ** Significant at P = .01; determined by 2-tailed test of significance.

Of the workplace risk perceptions, respondents who perceived that their employer was taking sufficient precautions to protect employees expressed higher vaccine hesitancy than workers who did not think their employers did so (B=.23, p=.002). Interestingly, neither perceptions of being safe at work (p=.914) nor perceptions that store customers were generally compliant with safety protocols (p=.214) predicted vaccine hesitancy. Unlike our findings for mental health distress being linked to individual perceptions of being safe, vaccine hesitancy appears to be more a function of one’s trust in their employer. If a worker believes that their employer is doing enough to protect them from exposure to COVID-19, they were more likely to be more vaccine hesitant.

Participants holding more favorable views about the effectiveness of public health measures to prevent the spread of COVID-19 (e.g., washing hands, avoiding crowds, social distancing, etc.) were also less vaccine hesitant than respondents with less favorable views (B=-.12, p=<.001). This finding is more expected than the positive correlation between employer protections and vaccine hesitancy, as less trust in other public health measures are likely correlated with less trust in COVID-19 vaccines.

Conclusions

Overall, we find significantly high levels of mental health distress within Arizona’s grocery store workforce, well above the U.S. national average (Holingue et al., 2021, Khubchandani et al., 2021). Approximately 17% of our sample reported severe levels of mental health distress on the PHQ-4 as well as generally high levels of stress on the PSS-4 across both waves, with relatively little change between July 2020 and January 2021. Our findings suggest that grocery store workers are exposed to multiple workplace stressors and a perceived lack of effective safety training is a major contributor to their mental health distress.

Being an essential worker increases one’s risks of exposure, and this core vulnerability is heightened by demographics of precarious occupations like grocery workers. Our results indicate that being female, younger, or reporting financial insecurity are correlated with mental health distress. This pattern is consistent with research on mental health effects of the pandemic across the general population (e.g., Holingue et al., 2020; Wilson et al., 202042). Low-wage workers have been identified as most taxed by increased home care duties during the pandemic (Russell et al., 202043), pointing at the dual pandemic-related stress for those essential workers who perceive increased workplace risk and stress, as well as rising individual stress levels. From a management perspective, temporarily reducing work-related demands when individual demands are high could provide an opportunity to demonstrate concern for the psychosocial well-being of these vulnerable employees (Janetzke and Ertel, 201744). Furthermore, management should be providing access to mental health services during the pandemic and ensuring that employees are aware of its availability and potential coverage through health insurance plans.

Grocery store workers’ decision-making about COVID-19 vaccination is also a critical topic. Their frequent interactions with members of the public, although often brief, place frontline workers in grocery stores at high risk of exposure. Vaccination is critical in these spaces. We find substantial evidence that elements of the “Three Cs” model for vaccine hesitancy are important factors affecting how receptive workers are to vaccination. Confidence in the efficacy of the vaccine seems to be the strongest predictor of hesitancy, such that workers with more confidence that vaccines are effective were less hesitant. We also find some support for the significance of workplace risk perceptions in influencing how these workers make decisions about getting vaccinated, although in an unexpected manner. Our findings suggest that workers’ perception that their employer was doing enough to protect them from COVID-19 was a strong predictor of higher levels of vaccine hesitancy. One interpretation of this finding is that if workers do indeed feel that their workplace is safe, getting the vaccine is less important to them. However, our measure of workers’ general sense of safety in the workplace was not significant.

As the pandemic continues to unfold, coordinated, equity-based policies and worker safety initiatives that prioritize the health and safety of the employee are needed. Both safety trainings and administrative controls are likely to increase employees’ perceptions of their employer’s commitment to their safety, which can motivate them to follow safety protocols and reduce transmission risks in the workplace. These findings further indicate the need for employer-initiated efforts and policies to ensure accessibility to the COVID vaccine, as this presents a form of assurance to employees in enhancing workplace safety.

References


  1. Sim, MR. (2020). The COVID-19 pandemic: major risks to healthcare and other workers on the front line. BMJ Publishing Group Ltd

  2. Lan, F. Y., Suharlim, C., Kales, S. N., & Yang, J. (2021). Association between SARS-CoV-2 infection, exposure risk and mental health among a cohort of essential retail workers in the USA. Occupational and environmental medicine, 78(4), 237-243. 

  3. Lakoff, A. (2020). The Supply Chain Must Continue: Becoming Essential in the Pandemic Emergency. Items: Insights from the Social Sciences. https://items.ssrc.org/covid-19-and-the-social-sciences/disaster-studies/the-supply-chain-must-continue-becoming-essential-in-the-pandemic-emergency/ 

  4. Ramarajan, L., & Reid, E. (2013). Shattering the myth of separate worlds: Negotiating nonwork identities at work. Academy of Management Review, 38(4), 621-644. 

  5. Reid, E. (2015). Embracing, passing, revealing, and the ideal worker image: How people navigate expected and experienced professional identities. Organization Science, 26(4), 997-1017. 

  6. Strangleman, T. (2012). Work identity in crisis? Rethinking the problem of attachment and loss at work. Sociology, 46(3), 411-425. 

  7. Bauman, Z. (1998). Globalization: The human consequences: Columbia University Press. 

  8. Casey, C. (1995). Work, self, and society: After industrialism: Psychology Press. 

  9. Sennett, R. (1998). The corrosion of character: The personal consequences of work in the new capitalism: WW Norton & Company. 

  10. Brown, A., Kirpal, S. R., & Rauner, F. (2007). Identities at work, 5: Springer Science & Business Media. 

  11. Ashforth, B. E. (2001). The handbook of emotional intelligence: Theory, development, assessment, and application at home, school, and in the workplace. Personnel Psychology, 54(3), 721. 

  12. Parks, C. A., Nugent, N. B., Fleischhacker, S. E., & Yaroch, A. L. (2020). Food system workers are the unexpected but under protected COVID heroes. The Journal of Nutrition, 150(8), 2006-2008. 

  13. Wang, L., Duan, Y., Zhang, W., Liang, J., Xu, J., Zhang, Y., ... & Li, H. (2020). Epidemiologic and clinical characteristics of 26 cases of COVID-19 arising from patient-to-patient transmission in Liaocheng, China. Clinical epidemiology, 12, 387. 

  14. Schoeni, R. F., Wiemers, E. E., Seltzer, J. A., & Langa, K. M. (2021). Association Between Risk Factors for Complications From COVID-19, Perceived Chances of Infection and Complications, and Protective Behavior in the US. JAMA network open, 4(3), e213984. https://doi.org/10.1001/jamanetworkopen.2021.3984 

  15. Kisely, S., Warren, N., McMahon, L., Dalais, C., Henry, I., & Siskind, D. (2020). Occurrence, prevention, and management of the psychological effects of emerging virus outbreaks on healthcare workers: rapid review and meta-analysis. bmj, 369

  16. Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020). Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. International journal of environmental research and public health, 17(5), 1729. 

  17. Holingue, C., Badillo-Goicoechea, E., Riehm, K. E., Veldhuis, C. B., Thrul, J., Johnson, R. M., ... & Kalb, L. G. (2020). Mental distress during the COVID-19 pandemic among US adults without a pre-existing mental health condition: findings from American trend panel survey. Preventive medicine, 139, 106231. 

  18. Holingue, C., Kalb, L. G., Riehm, K. E., Bennett, D., Kapteyn, A., Veldhuis, C. B., ... & Thrul, J. (2020). Mental distress in the United States at the beginning of the COVID-19 pandemic. American Journal of Public Health, 110(11), 1628-1634. 

  19. Lai, J., Ma, S., Wang, Y., Cai, Z., Hu, J., Wei, N., ... & Hu, S. (2020). Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA network open, 3(3), e203976-e203976. 

  20. Shechter, A., Diaz, F., Moise, N., Anstey, D. E., Ye, S., Agarwal, S., ... & Abdalla, M. (2020). Psychological distress, coping behaviors, and preferences for support among New York healthcare workers during the COVID-19 pandemic. General hospital psychiatry, 66, 1-8. 

  21. Kasperson, R. E., Renn, O., Slovic, P., Brown, H. S., Emel, J., Goble, R., ... & Ratick, S. (1988). The social amplification of risk: A conceptual framework. Risk analysis, 8(2), 177-187. 

  22. Slovic, P. (1987). Perception of risk. Science, 236(4799), 280-285. 

  23. Neal, A., Griffin, M. A., & Hart, P. M. (2000). The impact of organizational climate on safety climate and individual behavior. Safety science, 34(1-3), 99-109. 

  24. Ayim Gyekye, S., & Salminen, S. (2007). Workplace safety perceptions and perceived organizational support: Do supportive perceptions influence safety perceptions?. International Journal of Occupational Safety and Ergonomics, 13(2), 189-200. 

  25. MacDonald, N. E. (2015). Vaccine hesitancy: Definition, scope and determinants. Vaccine, 33(34), 4161-4163 

  26. Lazarus, J. V., Wyka, K., Rauh, L., Rabin, K., Ratzan, S., Gostin, L. O., ... & El-Mohandes, A. (2020). Hesitant or not? The association of age, gender, and education with potential acceptance of a COVID-19 vaccine: A country-level analysis. Journal of Health Communication, 25(10), 799-807. 

  27. Graves, M. A., Harris, J. R., Hannon, P. A., Hammerback, K., Ahmed, F., & Zhou, C. (2014). Workplace-based influenza vaccination promotion practices among large employers in the United States. Journal of occupational and environmental medicine, 56(4), 397-402. 

  28. King, R.P., Anderson, M., DiGiacomo, G., Mulla, D., & Wallinga, D. (2012). State Level Food System Indicators. Healthy Foods, Healthy Lives Institute University of Minnesota. 

  29. Fossen, M. C., Bethany, M. D., Modak, S. R., Parris, S. M., & Modak, R. M. (2021). Who’s vaccinated? A closer look at healthcare workers’ coronavirus disease 2019 (COVID-19) COVID-19 vaccine hesitancy and demographics. Infection Control & Hospital Epidemiology, 1-2. 

  30. Tam, C. C., Sun, S., Yang, X., Li, X., Zhou, Y. and Shen, Z. (2021) 'Psychological distress among HIV healthcare providers during the COVID-19 pandemic in China: mediating roles of institutional support and resilience', AIDS and Behavior, 25(1), pp. 9- 17. 

  31. Zhang, S. X., Liu, J., Jahanshahi, A. A., Nawaser, K., Yousefi, A., Li, J. and Sun, S. (2020a) 'At the height of the storm: Healthcare staff’s health conditions and job satisfaction and their associated predictors during the epidemic peak of COVID-19', Brain, behavior, and immunity, 87, pp. 144-146. 

  32. Zhang, W.-r., Wang, K., Yin, L., Zhao, W.-f., Xue, Q., Peng, M., Min, B.-q., Tian, Q., Leng, H.-x. and Du, J.-l. (2020b) 'Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China', Psychotherapy and Psychosomatics, 89(4), pp. 242-250. 

  33. Kroenke, K., Spitzer, R. L., Williams, J. B. and Löwe, B. (2009) 'An ultra-brief screening scale for anxiety and depression: the PHQ–4', Psychosomatics, 50(6), pp. 613-621. 

  34. Cohen, S., T. Kamarck and R. Mermelstein (1983). A global measure of perceived stress." Journal of health and social behavior: 385-396. 

  35. Warttig, S. L., Forshaw, M. J., South, J. and White, A. K. (2013) 'New, normative, English-sample data for the short form perceived stress scale (PSS-4)', Journal of Health Psychology, 18(12), pp. 1617-1628. 

  36. Lee, E.-H. (2012) 'Review of the psychometric evidence of the perceived stress scale', Asian nursing research, 6(4), pp. 121-127. Löwe et al., 2010 

  37. Mitchell, A. M., Crane, P. A. and Kim, Y. (2008) 'Perceived stress in survivors of suicide: psychometric properties of the Perceived Stress Scale', Research in Nursing & Health, 31(6), pp. 576-585. 

  38. Zajacova, A., & Dowd, J. B. (2011). Reliability of self-rated health in US adults. American journal of epidemiology, 174(8), 977-983. 

  39. New York Times. (2022). "Tracking Coronavirus in Arizona: Latest Map and Case Count." https://www.nytimes.com/interactive/2021/us/arizona-covid-cases.html. Last accessed February 21, 2022. 

  40. Khubchandani, J., Sharma, S., Webb, F. J., Wiblishauser, M. J., & Bowman, S. L. (2021). Post-lockdown depression and anxiety in the USA during the COVID-19 pandemic. Journal of Public Health, 43(2), 246-253. 

  41. Mayer, B., Arora, M., Helm, S., & Barnett, M. (2021). Essential but Ill-Prepared: How the COVID-19 Pandemic Affects the Mental Health of the Grocery Store Workforce. Public Health Reports, 00333549211045817. 

  42. Wilson, J. M., Lee, J., Fitzgerald, H. N., Oosterhoff, B., Sevi, B., & Shook, N. J. (2020). 'Job insecurity and financial concern during the COVID-19 pandemic are associated with worse mental health. Journal of Occupational and Environmental Medicine, 62(9), 686-691. 

  43. Russell, B. S., Hutchison, M., Tambling, R., Tomkunas, A. J., & Horton, A. L. (2020). 'Initial challenges of caregiving during COVID-19: Caregiver burden, mental health, and the parent–child relationship'. Child Psychiatry & Human Development, 51(5), 671-682. 

  44. Janetzke, H., & Ertel, M. (2017). Psychosocial risk management in more and less favourable workplace conditions. International Journal of Workplace Health Management

Suggested Citation:

Mayer, B., Helm, S., Barnett, M., & Arora, M. (2022). Mental Health, Workplace Safety, and Vaccine Hesitancy Among Grocery Store Workers During the COVID-19 Pandemic (Natural Hazards Center Quick Response Research Report Series, Report 339). Natural Hazards Center, University of Colorado Boulder. https://hazards.colorado.edu/quick-response-report/mental-health-workplace-safety-and-vaccine-hesitancy-among-grocery-store-workers-during-the-covid-19-pandemic

Mayer, B., Helm, S., Barnett, M., & Arora, M. (2022). Mental Health, Workplace Safety, and Vaccine Hesitancy Among Grocery Store Workers During the COVID-19 Pandemic (Natural Hazards Center Quick Response Research Report Series, Report 339). Natural Hazards Center, University of Colorado Boulder. https://hazards.colorado.edu/quick-response-report/mental-health-workplace-safety-and-vaccine-hesitancy-among-grocery-store-workers-during-the-covid-19-pandemic