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: [email protected] (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.
References
Abidin, U. Z., Fatimah, U., Arendt, S. W., & Strohbehn, C. H. (2014). Food safety culture
in onsite foodservices: Development and validation of a measurement scale. Journal
of Foodservice Management & Education., 8, 1-10.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A
review and recommended two-step approach. Psychological Bulletin., 103, 411-423.
Ball, B., Wilcock, A. & Colwell, S. (2010). Tool for measuring food safety climate. In J.
Food Prot. (vol. 7) CA: Anaheim (pp. 84-85).
De Boeck, E., Jacxsens, L., Bollaerts, M., & Vlerick, P. (2015). Food safety climate in food
processing organizations: Development and validation of a self-assessment tool.
Trends in Food Science & Technology., 46, 242-251.
DeVellis, R. F. (2003). Scale development : Theory and applications. Thousand Oaks, Calif:
Sage Publications.
Dewey-Mattia, D., Manikonda, K., Hall, A., Wise, M., & Crowe, S. (2018). Surveillance
for Foodborne Disease Outbreaks — United States, 2009-2015. MMWR Surveillance
Summaries, 67, 1-11.
Global Food Safety Initiative (2018). A culture of food safety. Levallois-Perret, France.
Griffith, C. J., Livesey, K. M., & Clayton, D. (2010a). The assessment of food safety
culture. British Food Journal., 112, 439-456.
National Restaurant Association (2014), Economist's Notebook: Hospitality employee
turnover rose slightly in 2013. http://www.restaurant.org/News-Research/News/
Economist-s-Notebook-Hospitality-employee-turnover. Accessed 7/13
Griffith, C. J., Livesey, K. M., & Clayton, D. A. (2010b). Food safety culture: The
evolution of an emerging risk factor? British Food Journal., 112, 426-438.
Neal, J. A., Binkley, M., & Henroid, D. (2012). Assessing factors contributing to food
safety culture in retail food establishments. Food Protection Trends, 32, 468-476.
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). Mcgraw Hill Book Company.
A. Kramer et al.
Olsen, S. J., MacKinnon, L., Goulding, J. S., Bean, N. H., & Slutsker, L. (2000).
Surveillance for foodborne-disease outbreaks—United States, 1993-1997. MMWR
CDC Surveillance Summaries, 49, 1-62.
Scallan, E., Griffin, P. M., Angulo, F. J., Tauxe, R. V., & Hoekstra, R. M. (2011).
Foodborne illness acquired in the United States—unspecified agents. Emerging
Infectious Diseases., 17, 16-22.
Scallan, E., Hoekstra, R. M., Angulo, F. J., Tauxe, R. V., Widdowson, M. A., Roy, S. L., ...
Griffin, P. M. (2011). Foodborne illness acquired in the United States-major
pathogens. Emerging Infectious Diseases, 17, 7-15.
Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting
structural equation modeling and confirmatory factor analysis results: A review. The
Journal of Educational Research, 99, 323-338.
Journal of Food Protection 86 (2023) 100043
Taha, S., Wilkins, S., Juusola, K., & Osaili, T. M. (2020). Food safety performance in food
manufacturing facilities: The influence of management practices on food handler
commitment. Journal of Food Protection, 83, 60-67.
Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or
component analysis: A review and evaluation of alternative procedures for
determining the number of factors or components. In Problems and solutions in
human assessment. Springer (pp. 41-71).
Yiannas, F. (2008). Food safety culture: Creating a behavior-based food safety management
system. Springer Science & Business Media.
Live Music
Archive
Librivox
Free Audio
Metropolitan Museum
Cleveland
Museum of Art
Internet
Arcade
Console Living Room
Open Library
American
Libraries
TV News
Understanding
9/11