CDC-Data-2025/attachments/1-s2.0-S0362028X23065018-main_djvu.txt

Journal of Food Protection 86 (2023) 100043 


Contents lists available at ScienceDirect 


Journal of Food Protection 


Mew 


ELSEVIER journal homepage: www.elsevier.com/locate/jfp 


Protecting the Global Food Supply 


Research Paper 


Development of an Empirically Derived Measure of Food Safety Culture in ® 


Check for 


Re staurants | updates 


Adam Kramer '*, E. Rickamer Hoover ', Nicole Hedeen*, Lauren DiPrete *, Joyce Tuttle *, DJ Irving”, 
Brendalee Viveiros°, David Nicholas ”**, Jo Ann Monroy”, Erin Moritz‘, Laura Brown * 


1 National Center for Environmental Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA 30341, USA 

? Minnesota Department of Health, USA 

3 Southern Nevada Health District, Las Vegas, Nevada, USA 

4 California Department of Health, California, USA 

5 Tennessee Department of Health, USA 

© Rhode Island Department of Health, USA 

7 New York State Department of Health, USA 

8 Department of Epidemiology & Biostatistics, School of Public Health, University at Albany (SUNY), Rensselaer, New York. USA 
° Harris County Department of Health, Houston, Texas, USA 


ARTICLE INFO ABSTRACT 


Keywords: 

Food safety culture 

Food safety 

Food worker 

Health knowledge attitudes practice 
Restaurant 


A poor food safety culture has been described as an emerging risk factor for foodborne illness outbreaks, yet 
there has been little research on this topic in the retail food industry. The purpose of this study was to identify 
and validate conceptual domains around food safety culture and develop an assessment tool that can be used to 
assess food workers’ perceptions of their restaurant’s food safety culture. The study, conducted from March 
2018 through March 2019, surveyed restaurant food workers for their level of agreement with 28 statements. 
We received 579 responses from 331 restaurants spread across eight different health department jurisdictions. 
Factor analysis and structural equation modeling supported a model composed of four primary constructs. The 
highest rated construct was Resource Availability (x=4.69, sd=0.57), which assessed the availability of 
resources to maintain good hand hygiene. The second highest rated construct was Employee Commitment 
(x= 4.49, sd=0.62), which assessed workers’ perceptions of their coworkers’ commitment to food safety. 
The last two constructs were related to management. Leadership (x= 4.28, sd=0.69) assessed the existence 
of food safety policies, training, and information sharing. Management Commitment (x= 3.94, sd=1.05) 
assessed whether food safety was a priority in practice. Finally, the model revealed one higher-order construct, 
Worker Beliefs about Food Safety Culture (x = 4.35, sd = 0.53). The findings from this study can support efforts 
by the restaurant industry, food safety researchers, and health departments to examine the influence and 
effects of food safety culture within restaurants. 


The Centers for Disease Control and Prevention (CDC) estimates 
that 48 million cases of domestically acquired foodborne illness occur 
annually in the United States, resulting in 325,000 hospitalizations 
and 3,000 deaths (Scallan, Griffin et al., 2011; Scallan, Hoekstra 
et al., 2011). Most reported foodborne illness outbreaks are attributed 
to restaurants (Dewey-Mattia et al., 2018). Past interventions to reduce 
foodborne illness have focused on addressing commonly identified risk 
factors associated with foodborne illness, such as ensuring food is 
cooked to recommended cooking temperatures and preventing con- 
tamination of the food (Olsen et al., 2000). Despite these important 
interventions, foodborne illnesses continue to occur. To further reduce 


* Corresponding author. 
E-mail address: ank5@cdc.gov (A. Kramer). 


https://doi.org/10.1016/j.jfp.2023.100043 
Received 17 May 2022; Accepted 11 January 2023 
Available online 18 January 2023 


the occurrence of foodborne outbreaks, Griffith et al. (2010b) pro- 
posed examining food safety culture as an emerging risk factor for 
foodborne illness. 

Researchers (Griffith, Livesey, & Clayton, 2010b; Yiannas, 2008) 
have proposed varying definitions of food safety culture. The Global 
Food Safety Initiative, for example, defines food safety culture as 
“shared values, beliefs and norms that affect mind-set and behavior 
toward food safety in, across and throughout an organization” 
(Global Food, 2018). All the published definitions of food safety cul- 
ture share a common element — that food workers’ shared beliefs influ- 
ence food safety behavior. 


0362-028X/Published by Elsevier Inc. on behalf of International Association for Food Protection. 
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). 


A. Kramer et al. 


Drawing from the organizational and safety culture literature, 
Griffith et al. (2010a) proposed that food safety culture was composed 
of five separate theoretical concepts related to food safety: (1) leader- 
ship, (2) communication, (3) commitment, (4) environment, and (5) 
risk awareness. This conceptualization focused primarily on the orga- 
nizational factors thought to contribute to food safety culture. 

Several studies have surveyed workers in a variety of settings in an 
attempt to develop a food safety culture assessment model. These 
researchers have assessed meat workers (Ball et al., 2010), culinary 
students (Neal et al., 2012), school food service workers (Abidin 
et al., 2014), and workers in a European meat distribution company 
(De Boeck et al., 2015). Taha et al. (2020) examined organizational 
factors and worker beliefs in food manufacturing plants. These studies 
identified anywhere from two to six separate theoretical concepts 
related to food safety culture among these populations. They found 
that beliefs about commitment (management and employee), 
resources (or infrastructure), and work pressures play a role in food 
safety culture. 

Observing that much of the food safety culture research has been 
performed in food manufacturing facilities, the Environmental Health 
Specialists Network (EHS-Net) embarked on a study to develop a food 
worker survey measure that can be used to assess restaurant food 
safety culture at a specific time (sometimes referred to as the food 
safety climate (De Boeck et al., 2015). This paper reports on our devel- 
opment of this measure. EHS-Net is a collaborative network of the 
CDG, the U.S. Food and Drug Administration, the U.S. Department of 
Agriculture’s Food Safety and Inspection Service, and eight health 
departments. A CDC cooperative agreement funded health depart- 
ments in California, Harris County (TX), Minnesota, New York, New 
York City (NY), Rhode Island, the Southern Nevada Health District, 
and Tennessee to participate in EHS-Net and in this study. 


Methods 
Survey development 


We developed a survey for restaurant food workers based on the 
constructs proposed by Griffith et al. (2010a) and previously adminis- 
tered surveys (Ball et al., 2010; De Boeck et al., 2015; Neal et al., 
2012). A workgroup composed of EHS-Net health department staff 
designed the survey to apply to all types of restaurants, rather than 
for a specific company as previous researchers have done (i.e., our sur- 
vey assessed handwashing resources, something that is relevant in all 
restaurants). The survey asked food workers to self-report their level of 
agreement with 28 statements (Table 2) using a Likert-scale ranging 
from 1 (strongly disagree) to 5 (strongly agree). Four of these items 
were reverse-coded (DeVellis, 2003). Table 2 includes the survey 
items, the number of responses, the mean scores (higher scores show 
stronger agreement [or disagreement for reverse-coded items]), and 
standard deviations. We also included questions to assess food work- 
ers’ food safety knowledge and experience working in restaurant 
kitchens. 

To increase restaurant participation in the study and food worker 
honesty in the survey responses, study data collection was anonymous. 
Thus, to ensure we did not collect data that could allow the identifica- 
tion of food workers, we asked limited questions about individual 
demographics. For example, we did not collect data on staff race, eth- 
nicity, or age. 

The instrument was pilot tested with three restaurant food workers 
for comprehension and length of time to complete the survey. The sur- 
vey was translated into Spanish by one native speaker and translated 
back into English by another native speaker to verify the translation. 
A copy of the food worker survey is provided in the Supplementary 
material, and all the study materials are posted at https://www. 
cde.gov/nceh/ehs/ehsnet/study_tools/index.htm. 


Journal of Food Protection 86 (2023) 100043 
Sample 


The study sample consisted of randomly selected restaurants in 
each of the eight EHS-Net health department’s jurisdictions. Restau- 
rants were defined as establishments that prepare and serve food or 
beverages to customers but are not institutions, food carts, mobile food 
units, temporary food stands, supermarkets, restaurants in supermar- 
kets, or caterers. In each EHS-Net jurisdiction, staff chose a geographic 
area in which to recruit restaurants for study participation, based on a 
reasonable travel distance (mean = 88.1 min, range = 30 min to 4 h). 
One jurisdiction was urban; the other seven were a combination of 
urban, suburban, and rural areas. The staff then sent a list of restau- 
rants within that area to CDC, which selected a random sample of 
restaurants for each jurisdiction. Staff in each jurisdiction requested 
voluntary study participation from managers in a random sample of 
restaurants and scheduled a data collection visit through telephone 
calls or visits to the participating restaurants. Within each restaurant, 
food workers were requested to voluntarily participate in the study. No 
incentives were provided to participate in this study. 


Data collection 


Data collection took place from March 2018 to March 2019. Data 
were collected by EHS-Net staff. All data collectors participated in 
training designed to promote data collection consistency. At each 
restaurant, data collectors, EHS-Net staff, interviewed a manager 
(someone who had authority over the restaurant) about restaurant 
characteristics, asked food workers (staff members who prepare food 
in the restaurant) to complete a survey, and conducted an observation 
of food preparation and storage practices in the kitchen area. This 
paper presents data from the food worker survey on food workers’ 
beliefs about food safety. 

Food workers completed a self-administered survey about their 
beliefs around food safety in their restaurant. The survey was provided 
in English and Spanish using the SurveyMonkey (Momentive, San 
Mateo, CA, USA) online survey platform. Food workers could either 
complete the survey online using the online application (at their con- 
venience) or complete a paper version of the survey during the data 
collection visit. Any surveys completed on paper forms were entered 
into SurveyMonkey later by the data collectors. We did not record 
whether a food worker completed an electronic or paper-based survey. 

A study identifier was used to link worker survey data to the match- 
ing restaurant; however, we did not collect data that could identify 
individual restaurants, managers, or workers. Each EHS-Net jurisdic- 
tion’s institutional review board approved the study protocol. 


Analysis 


We randomly split the completed survey responses into two groups 
(n = 248 per group) for analysis. One group was used for model build- 
ing, and the other group was used for validation of the statistical 
model. We examined the model fit of the theoretical model of food 
safety culture based on the constructs proposed by Griffith et al. 
(2010a) using confirmatory factor analysis. To assess fit, we examined 
the overall concordance of multiple indices; these included the chi- 
square (not statistically significant indicated a better fit), the standard- 
ized root mean square residual (SRMR < 0.08 indicates a better fit), 
the comparative fit index (CFI > 0.95 indicates a better fit), and root 
mean square error of approximation (RMSEA < 0.06 indicates a better 
fit) (Schreiber et al., 2006). However, the data that we collected did 
not support this model structure. Therefore, we then conducted an 
exploratory factor analysis to identify the factors that were empirically 
supported. We retained items that loaded onto unique common fac- 
tors, had a primary factor loading of 0.4 or above, and did not load 
onto another factor at 0.3 or above. We then examined whether the 
data would benefit from a data reduction method using Bartlett’s test 


A. Kramer et al. 


of sphericity, where a significant value supports further data reduc- 
tion. We then examined the number of factors that would be supported 
by the model using a scree test and minimum average partials test 
(Velicer et al., 2000). Once we identified the four factors and their 
associated items, we assessed scale reliability using Cronbach’s alpha 
with an alpha coefficient of 0.65 or higher considered acceptable. 
After that, we conducted structural equation modeling to identify an 
appropriate model structure and to determine if the data would sup- 
port further generalization to a higher-order factor. Finally, we created 
a composite measure for each factor in the model, based on the struc- 
tural equation model, where the sum of the Likert-scaled questions for 
each factor was calculated. Negatively phrased questions were recoded 
so that higher scores would equate to positive agreement (e.g., strong 
disagreement with a negatively phrased item was recoded as strong 
agreement for analysis). We then divided the sum by the number of 
questions associated with the factor to provide a standardized score 
for each factor. We used SAS version 9.4 (SAS Institute, Cary, NC, 
USA) to analyze the data. 


Results 
Demographics 


We contacted 1,496 restaurants to participate in the study, of 
which 506 were excluded (restaurants were no longer in business, 
were not a restaurant [e.g., a grocery store], the manager was unable 
to communicate with the study recruiting staff in English). Of the 
remaining 990 restaurants, we had participation from 331 restaurants. 
We received 579 food worker survey responses from those 331 differ- 
ent restaurants. Manager interview data indicated that the study 
restaurants were largely independently owned (57.1%). Food worker 
survey data showed that the largest group of food workers had 1-5 
years of experience (39.9%), 1-5 years of tenure in their current estab- 
lishment (46.6%), and worked primarily in the kitchen (55.4%). Most 
respondents had a current Certified Food Protection Manager creden- 
tial (56.7%); however, only 9.5% were in a supervisory role. Food 
workers reported primarily speaking English (72.5%) and Spanish 
(18%). Most of the food workers had completed high school 
(32.5%), had at least some college education (49.1%), and were male 
(50.6%) (Table 1). 


Data screening 


Of the 579 responses, 44 (7.6%) were completed in Spanish. All 
Likert-scaled items were initially tested for multicollinearity, deviation 
from linearity, consistency with similar items, and if all items were 
answered. This screening led us to drop item 5 (Table 2) from further 
analyses because it did not consistently correlate with other similar 
questions. This lack of correlation is likely due to the influence of var- 
ied glove use requirements across the jurisdictions. 


Theoretical model 


An initial theoretical model based on Griffith et al. (2010a) work 
was constructed where we associated each of the items to one of five 
constructs: Commitment; Communication; Leadership; Resources; and 
Risk Awareness. We then assessed this model for fit. However, our data 


did not support this model. None of the fit indices — 
7-(485) = 2,039.45, p < 0.0001; SRMR = 0.10; CFI = 0.68; and 
RMSEA = 0.11 (0.12, 0.11) — indicated an adequate fit between 


the data and the model. 


Journal of Food Protection 86 (2023) 100043 


Table 1 
Respondent demographics 
Demographic characteristic N Percentage 
Restaurant ownership 
Independently owned 189 57.1 
Chain owned 138 41.7 
Not reported 4 1.2 
Years of experience in food service 
<1 54 9.3 
1-5 231 39.9 
6-10 110 19 
11-15 60 10.4 
>15 103 17.8 
Not reported 21 3.6 
Years’ tenure in the current restaurant 
<1 191 33 
1-5 270 46.6 
6-10 65 11.2 
11-15 22 3.8 
>15 22 3.8 
Not reported 9 1.6 
Certified food protection manager 
Currently certified 328 56.7 
Previously certified 54 9.3 
Not certified 182 31.4 
Not Reported 15 2.6 
Primary area of the restaurant that they work in 
Kitchen/food preparation 321 55.4 
Food service/bar 155 26.8 
Management 55 9.5 
Other 35 6.1 
Not reported 13 2.3 
Sex 
Male 293 50.6 
Female 260 44.9 
Not reported 26 4.5 
Self-reported primary language 
English 420 72.5 
Spanish 104 18 
Chinese 16 2.8 
Other 26 4.5 
Not reported 13 2.3 
Level of formal education 
Less than High school graduate 73 12.6 
High school graduate 188 32.5 
Post high school 284 49.1 
Not reported 34 5.9 


Exploratory factor analysis 


We initially included 27 items in a factor analysis. Sixteen ques- 
tions were retained in the model. The principal factor analysis used 
squared multiple correlations with all other items, unweighted least 
squares factors, and a promax (oblique) rotation. The remaining 11 
items did not load onto common factors or meet the above criteria 
for retention in further analyses. 

A significant Bartlett’s test of sphericity (7[62] = 133.92, 
Pp < 0.0001) indicated that the data could be reduced into factors. 
Results of a scree test and a minimum average partials test suggested 
four factors would be sufficient to explain the variance (Velicer 
et al., 2000). 

Table 3 shows the survey items and factor loadings. The EHS-Net 
working group reviewed the items that formed each of the four factors 
to provide their perceptions of the constructs measured by each factor. 
The working group labeled those factors as Leadership, Management 
Commitment, Employee Commitment, and Resource Availability. 
Leadership included six items, Employee Commitment included four 
items, and Resource Availability and Management Commitment 
included three items each. 

Scale reliability for each factor was assessed using Cronbach’s 
alpha; each factor had acceptable reliability (Leadership = 0.88, 
Employee Commitment = 0.87, Resource Availability = 0.72, Man- 


A. Kramer et al. 


Table 2 
Descriptive data on the Food Safety Culture Tool items 


Item N° Mean? SD 


Hb 


. Employees follow food safety rules, even when no one is 578 4.45 0.74 


looking 

2. Employees encourage each other to follow food safety 578 4.43 0.79 
rules 

3. Employees take responsibility for food safety in their 578 4.51 0.70 
areas 

4. Employees wash their hands when they are supposed to 576 4.56 0.69 


on 


. Employees touch food that will not be cooked with their 571 2.09 1.37 
bare hands (Reverse coded)* 

6. Employees do not work while they are sick with vomiting 577 4.38 1.12 
or diarrhea 

7. There are enough gloves or utensils to use to avoid 577 4.57 0.96 
touching the food with my bare hands 

8. Sinks are nearby and are easy to get to for handwashing 576 4.74 0.57 

9. Sinks for handwashing have hot water, soap, and paper 578 4.77 0.56 
towels or another way to dry my hands 

10. Equipment is well maintained and operates properly 578 4.45 0.81 

11. There is enough staff to cover when the restaurant is 576 4.12 1.00 
busy 

12. There is enough staff to cover when an employee does 577 3.89 1.08 
not come into work 

13. Employees have to cut corners because there is too 573 3.89 1.22 
much work to do (Reverse coded) 

14. Managers encourage employees to follow food safety 576 4.64 0.71 
rules 

15. When the restaurant is busy, managers prioritize serving 570 3.67 1.48 
food over following food safety rules (Reverse coded) 

16. Managers encourage employees to report food safety 577 4.44 0.83 


problems 
17. Managers ignore when employees are not following 576 4.22 1.20 
food safety rules (Reverse coded) 
18. Managers are aware of the food safety rules 573 4.64 0.71 
19. Managers strive to improve food safety practices 563 4.51 0.71 


20. If food safety rules are not followed a customer may 575 4.62 0.73 
become sick 

21. The restaurant provides sufficient food safety training 578 4.43 0.82 
for me to do my job 


22. I know what the food safety rules are for my job 575 4.65 0.61 

23. Food safety is stressed with signs, posters, or in-shift 571 4.22 1.00 
meetings 

24. Employees are positively recognized for following food 574 4.00 1.04 
safety rules 

25. Managers get feedback from employees to improve food 574 4.02 1.00 
safety 

26. Employees know the restaurant’s food safety 574 4.47 0.68 
expectations 

27. My manager explains what is expected of me 575 4.53 0.69 


28. It is easy to talk with my manager about any problems 576 4.45 0.89 


* Respondents were not required to answer every question resulting in 
varying response rates. 

> Scores can range from 1 (strongly disagree) to 5 (strongly agree). Higher 
scores indicate stronger agreement with the statement or disagreement for 
reverse-coded items. 

© Question 5 was dropped from the analysis because it was not consistently 
correlated with other similar questions. 


agement Commitment = 0.73) (Nunnally, 1978). External validity 
was assessed using the reserved half of the dataset; the results were 
similar to those obtained from the first half of the data. 


Structural equation modeling 


Structural equation modeling was used to identify the relationships 
among the factors and to determine if the data would support a higher- 
order factor (Anderson and Gerbing, 1988). In other words, this mod- 
eling was to determine if the identified factors are stand-alone factors, 
are inter-related, and if they can be further generalized to a higher- 
order factor (an overarching factor that is explained by these primary 
factors, similar to how individual questions explain the primary 
factors). 


Journal of Food Protection 86 (2023) 100043 


We examined various structural forms of the factors identified in 
the exploratory factor analysis; a model with one higher-order factor 
(Worker beliefs about food safety culture) was found to be optimal. 
The fit indices for this model showed an overall good fit — 
7100) = 210.78, p < 0.0001; SRMR = 0.05; CFI = 0.95; and 
RMSEA = 0.07 (0.08,0.05) (Figure 1). 

Reliability estimates were generally acceptable (Table 4). Item reli- 
ability was generally above 0.5, except for item 7 (0.27). We chose to 
retain this item because of its contextual similarity to other items and 
to maintain factor reliability. The four primary factors exhibited 
acceptable overall composite reliability (Leadership = 0.91, Employee 
Commitment = 0.89, Resource Availability = 0.79, and Management 
Commitment = 0.78). Relationships between individual items and 
their associated factor were examined; all pathways were significant. 
Similarly, the relationships between each of the primary factors were 
significantly associated with the higher-order factor (Table 4). The 
finding that the t-values are significant for these path coefficients sug- 
gests that the items are measuring the same construct. 


Scale measures 


All constructs had composite scores spanning the entire range, from 
1 (strongly disagree) to 5 (strongly agree). In general, food workers 
viewed each of the factors positively (composite score >3), although 
individual workers in some restaurants reported lower scores. Food 
workers viewed Resource Availability highest (mean = 4.69, 
SD = 0.57), followed by Employee Commitment (mean = 4.49, 
SD = 0.62), Leadership (mean = 4.28, SD = 0.69), and Management 
Commitment (mean = 3.94, SD = 1.05). The overall belief in food 
safety culture had a mean score of 4.35 (SD = 0.53) (Table 4). 


Discussion 


Our intent for this study was to provide convergent validity in sup- 
port of existing food safety culture models within restaurant food 
workers. Because our data did not support the application of any of 
the existing published models of food safety culture, we created a 
new model. Our model is not wholly unique and does share some com- 
mon factors with previously published models. Similar to other mod- 
els, we identified a Leadership factor (Abidin, Fatimah, Arendt, & 
Strohbehn, 2014; De Boeck, Jacxsens, Bollaerts, & Vlerick, 2015; 
Griffith, Livesey, & Clayton, 2010a; Taha, Wilkins, Juusola, & Osaili, 
2020) and Resources factor (Abidin et al., 2014; De Boeck et al., 
2015). However, while some researchers have identified a single con- 
struct of commitment (Abidin, Fatimah, Arendt, & Strohbehn, 2014; 
De Boeck, Jacxsens, Bollaerts, & Vlerick, 2015; Griffith, Livesey, & 
Clayton, 2010a), we found two commitment-related constructs — one 
for managers and one for workers (Ball et al., 2010; Neal et al., 
2012; Taha et al., 2020). Additionally, other researchers have identi- 
fied constructs which our data did not support, such as risk awareness 
(Abidin, Fatimah, Arendt, & Strohbehn, 2014; De Boeck, Jacxsens, 
Bollaerts, & Vlerick, 2015; Griffith, Livesey, & Clayton, 2010a). Differ- 
ences between our model and others may be because food safety cul- 
ture constructs differ across settings (Abidin et al., 2014; Ball et al., 
2010; De Boeck et al., 2015; Neal et al., 2012; Taha et al., 2020). 
Our findings might also be the result of our sample being comprised 
of a large and heterogenous (331 restaurants spread across eight differ- 
ent jurisdictions) sample compared with the limited sampling frames 
available to other researchers. 

The items making up Resource Availability, the construct with the 
highest rated composite score of the four, assess the availability of 
resources needed to maintain good hand hygiene. This high score 
was not unexpected; hand hygiene resources are a basic component 
of food safety and are assessed during inspections. 


A. Kramer et al. 


Journal of Food Protection 86 (2023) 100043 


Table 3 
Factor loadings and communalities based on factor analysis with promax rotation for 16 items from the Food Safety Culture Survey Tool (n = 248) 
Item Factor 1 - Factor 2 - Employee Factor 3 - Factor 4 - Management Communality 
Leadership Commitment Resources Commitment 

21. The restaurant provides sufficient food safety training forme todomy 0.82 0.72 
job 

25. Managers get feedback from employees to improve food safety 0.79 0.65 

23. Food safety is stressed with signs, posters, or in-shift meetings 0.76 0.55 

24. Employees are positively recognized for following food safety rules 0.73 0.58 

27. My manager explains what is expected of me 0.60 0.66 

26. Employees know the restaurant’s food safety expectations 0.58 0.64 

3. Employees take responsibility for food safety in their areas 0.82 0.78 

2. Employees encourage each other to follow food safety rules 0.80 0.70 

1. Employees follow food safety rules, even when no one is looking 0.71 0.69 

4. Employees wash their hands when they are supposed to 0.55 0.53 

8. Sinks are nearby and are easy to get to for handwashing 0.85 0.75 

9. Sinks for handwashing have hot water, soap, and paper towels or another 0.77 0.64 
way to dry my hands 

7. There are enough gloves or utensils to use to avoid touching the food with 0.56 0.29 
my bare hands 

15. When the restaurant is busy, managers prioritize serving food over 0.81 0.62 
following food safety rules (Reverse coded) 

13. Employees have to cut corners because there is too much work to do 0.72 0.56 
(Reverse coded) 

17. Managers ignore when employees are not following food safety rules 0.68 0.49 


(Reverse coded) 


Note: Factor loadings <0.3 are suppressed. 


The items making up Employee Commitment assess workers’ per- 
ceptions of their coworkers’ commitment to food safety (e.g., employ- 
ees follow food safety rules even when no one is looking). This 
construct was relatively highly rated, suggesting that workers in our 
study believed their coworkers were committed to food safety. 
Employee commitment to food safety likely leads to social norms that 
are supportive of food safety behavior; social norms can be important 
predictors of behavior (Yiannas, 2008). 


Leadership 


Employee 
Commit ment 


Worker Beliefs 
- FS Gulture 


Resources 


Figure 1. Path diagram of food safety culture model. 


Two of the unique constructs directly tied to management: Leader- 
ship and Management Commitment. Leadership deals primarily with 
stated food safety policies, training, and information sharing (ques- 
tions such as: The restaurant provides sufficient food safety training 
for me to do my job). Management Commitment covers prioritizing 
food safety practice (with questions such as: When the restaurant is 
busy, managers prioritize serving food over following food safety 
rules). These constructs had the lowest overall scores and highest vari- 
ation in scores. This dichotomy might result from the difference 
between the stated practices (Leadership) and their implementation 
(Management Commitment). We take this to mean that restaurants 
might have good practices in place, but the pragmatic realities of oper- 
ating a restaurant might result in lapses in the application of those 
practices. 

We were able to further generalize the results of this study to a 
higher-order construct composed of the results of the four primary 
constructs. This higher-order construct provides a high-level view of 
the overall food safety culture in a restaurant. This finding also indi- 
cates that food safety culture may be a part of the larger organizational 
culture in the restaurant. 

We also assessed risk awareness (e.g., If food safety rules are not 
followed, a customer might become sick). However, these questions 
did not load onto a unique factor, suggesting that restaurant food 
workers might have highly variable views of the risk posed by food. 
This finding suggests that perceptions of risk may be less important 
to food safety culture than manager and worker commitment to speci- 
fic food safety behaviors. 

This study has at least six limitations. First, the survey was self- 
administered, which would require the food worker to be able to read. 
Second, the survey was provided only in English and Spanish, which 
required the food worker to comprehend one of these languages to 
complete the survey. The potential universe of primary languages used 
by food workers is likely much greater than these two languages. 
Third, because the survey responses were self-reported, responses 
are subject to social desirability bias, which might have resulted in 
overreporting of socially desirable responses, such as positive views 
of food safety. Fourth, since limited information was collected about 
the food workers’ individual characteristics, we are unsure of the com- 
parability of our sample to all food workers. Fifth, responses were from 
voluntarily participating restaurants. Responses from restaurants that 


A. Kramer et al. 


Journal of Food Protection 86 (2023) 100043 


Table 4 
Properties of the Food Safety Culture Structural Equation Model 
Constructs and Items Standardized e Reliability Variance extracted Mean Standard 
loading estimate Deviation 
Leadership 0.91" 0.38 4.28 0.69 
21. The restaurant provides sufficient food safety training for me to do my job 0.83 35.98 0.69 
23. Food safety is stressed with signs, posters, or in-shift meetings 0.73 22.11 0.53 
24. Employees are positively recognized for following food safety rules 0.75 23.58 0.55 
25. Managers get feedback from employees to improve food safety 0.77 26.12 0.59 
26. Employees know the restaurant’s food safety expectations 0.81 31.72 0.65 
27. My manager explains what is expected of me 0.81 32.17 0.66 
Employee commitment 0.89" 0.37 449 0.62 
1. Employees follow food safety rules, even when no one is looking 0.84 35.46 0.70 
2. Employees encourage each other to follow food safety rules 0.82 32.86 0.67 
3. Employees take responsibility for food safety in their areas 0.88 44.02 0.77 
4. Employees wash their hands when they are supposed to 0.73 21.89 0.53 
Resources 0.79" 0.32 4.69 0.57 
7. There are enough gloves or utensils to use to avoid touching the food with my bare 0.52 9.95 0.27 
hands 
8. Sinks are nearby and are easy to get to for handwashing 0.88 26.88 0.77 
9. Sinks for handwashing have hot water, soap, and paper towels or another way to dry 0.80 22.89 0.64 
my hands 
Management commitment 0.78" 0.32 3.94 1.05 
13. Employees have to cut corners because there is too much work to do (Reverse 0.76 18.02 0.58 
coded) 
15. When the restaurant is busy, managers prioritize serving food over following food 0.74 16.95 0.55 
safety rules (Reverse coded) 
17. Managers ignore when employees are not following food safety rules (Reverse 0.71 15.72 0.51 
coded) 
Workers’ beliefs about food safety culture 4.35 0.53 


* t tests assessed the pathways between all items and the constructs. All t tests were significant at p < 0.0001. 


> Denotes composite reliability. 


did not participate might have differed, leading to a potential selection 
bias. Finally, because turnover is high in the restaurant industry 
(National Restaurant Association, 2014), worker beliefs about food 
safety culture captured at the time of our study might not be represen- 
tative of worker beliefs in restaurants over time. 

We have provided a new, empirically derived model for assessing 
worker’s beliefs about food safety culture. This model is based on 
restaurant workers’ level of agreement with statements about the food 
safety within their restaurant. Restaurants can use this tool to obtain a 
benchmark of their workers’ views of food safety. The tool can also be 
used to assess changes in perceptions of food safety over time and the 
effect of interventions designed to improve the food safety culture. 

This model could be further refined. Eleven of the questions we 
asked did not load onto any constructs. This might be because of addi- 
tional constructs that we did not ask about (such as work pressures or 
worker burnout). We recommend further evaluation and refinement of 
the questions to determine if there are food safety culture factors our 
study did not assess. Further, we recommend developing additional 
questions around the existing factors that we identified. This will serve 
to strengthen the factors (from a statistical standpoint) and allow 
researchers to more narrowly define what the constructs are 
measuring. 


Declaration of Competing Interests 


The authors declare that they have no known competing financial 
interests or personal relationships that could have appeared to influ- 
ence the work reported in this paper. 


Acknowledgments 


We thank the restaurant managers and employees that participated 
in this study and the EHS-Net data collectors. Without their participa- 
tion, this study would not have been possible. This publication is based 
on data collected and provided by the CDC EHS-Net, which is sup- 


ported by a CDC grant funded under CDC-RFA-EH-15-001. The find- 
ings and conclusions in this report are those of the authors and do 
not necessarily represent the views of CDC or the Agency for Toxic 
Substances and Disease Registry. Use of trade names and commercial 
sources is for identification only and does not imply endorsement by 
the U.S. Department of Health and Human Services. 


Appendix A. Supplementary material 


Supplementary data to this article can be found online at 
https://doi.org/10.1016/j.jfp.2023.100043. 


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