Finding new gaps in a well established theory can be very challenging, traditionally we rely on well-established leaders in the theory to do an review, and point out the directions of future.
Recent development in Meta-analysis provided new possibilities to mathematically examine existing "theoretical system", therefore finding the bridges, this paper provided an example of how-to
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Exploring Unobserved Heterogeneity of Food Safety Behavior: A Meta-Analysis
1. Department of Hospitality Management
College of Human Ecology
Using The Theory Of Planned Behavior To Predict Food Safety Behavioral
Intention: A Meta-analysis
Naiqing Lin Ph.D.; Kevin R. Roberts, Ph.D.
Kansas State University
SSRN: https://ssrn.com/abstract=3104751 or http
://dx.doi.org/10.2139/ssrn.3104751
2. Department of Hospitality Management
College of Human Ecology
Introduction
In 2016, restaurants were still the most commonly reported
location of foodborne diseases outbreaks (469, 52%) and
associated illnesses (4,757, 31%)1.
It has been suggested that 97% of outbreaks traced to non-
manufacturing food businesses involved food handler error or
malpractice2.
To effectively reduce foodborne illnesses, foodservice
managers and food handlers must perform essential food
safety behaviors3.
1. Angelo, Nisler, Hall, Brown, & Gould, 2017; CDC, 2017
2. Howes et al., 1996; Griffith, Livesey, & Clayton, 2010
3. Debess et al., 2009; Green et al., 2007; Green & Selman, 2005
3. Department of Hospitality Management
College of Human Ecology
Problem
Health inspections within the public sector1 and audit reports from
the private sector2 have identified significant degrees of non-
compliance food safety behavior.
Behavioral resistance and failure to comply with proper food safety
practices are both widespread and problematic3.
Using best available antecedents like attitudes, norms, self-
efficacy, perceptions of risk and severity, and personality factors
only explained about 14% to 24% of the variance in behaviors4.
1. CDC, 2016; 2. Egan et al., 2007; Valerie et al., 2008
3. Roberts et al., 2008, 2009; Roberts & Barrett, 2009, 2011)
4. Godin & Kok, 1996; McEachan et al., 2011; Sheeran & Webb, 2016
4. Department of Hospitality Management
College of Human Ecology
Problem
High-quality systematic syntheses are rarely conducted with food
safety behaviors1.
A significant proportion of variance within behavioral intention is
unexplained2, suggesting room for improvement.
Previous review articles focus on summarizing the educational
effectiveness (i.e., improved knowledge) not on food safety
behaviors, thus have considerable limitations2,3.
1. Egan et al., 2007; Ong, Frewer, and Chan, 2017
2. Sheeran, 2002; Sheeran & Webb, 2016
3. Pilling et al., 2008; Sniehotta et al., 2014; York et al., 2009
5. Department of Hospitality Management
College of Human Ecology
Purpose
The purpose of this study is to summarize and evaluate the ability of the
Theory of Planned Behavior (TPB) to predict food safety behavioral
intentions.
6. Department of Hospitality Management
College of Human Ecology
Literature Review
Theoretical Assumption - the Theory of Planned Behavior
(TPB)
Attitude
Subjective Norm
Perceived
Control
Behavioral
Intention
Self-Reported
Behavior
Note. Adapted from Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior: The reasoned
action approach. Taylor & Francis.
Experience
Age
Gender
7. Department of Hospitality Management
College of Human Ecology
Literature Review General Validity and Utility of the TPB
The TPB remains one of the most influential theories of cognitive behavioral change1.
The TPB asserts that it is vital to change intention to perform a behavior in order to
change existing behavior or initiate a new behavior2.
Various correlational studies3 and meta-analysis of meta-analyses3 has supported
the general validity and utility of the TPB4.
Intention offers a superior prediction of behavior in correlational tests compared to
other cognitions including explicit and implicit attitudes, norms, self-efficacy,
perceptions of risk and severity and personality factors4.
1. Fishbein & Ajzen, 2011; Sheeran et al., 2016; 2. Rhodes & Dickau, 2012; Webb &
Sheeran, 2006; 3. Armitage & Conner, 2001; McEachan et al., 2011; Sheeran & Webb,
2016; 4. Chiaburu et al., 2011; Sheeran, Harris, & Epton, 2014
8. Department of Hospitality Management
College of Human Ecology
Proposed Research Questions
RQ1: Does attitude, subjective norm, perceived control have a significant random-effect on food
safety behavioral intention among food service workers?
RQ2: What are the unobserved heterogeneity ratios (I2) in observed effects between food safety
attitude, subjective norms, and perceived control to food safety behavioral intention?
9. Department of Hospitality Management
College of Human Ecology
Methods
Boolean phase searches were used in databases and the search
strategy were peer reviewed by two indexing Librarians.
Manual reviews were conducted with the journals with the most food
safety behavior publications from June 1982 to October 2017.
The researchers contacted the corresponding authors of the
selected studies and request any unpublished data or studies.
MIX 2.0 (Englewood NJ: Biostat) were used to manage data.
Meta-Analysis Procedures
10. Department of Hospitality Management
College of Human Ecology
Methods
Studies reporting consumer intentions to adhere to food safety
behaviors were excluded.
Studies using only college students or high school students were
excluded1.
Studies must have at least one direct measure of attitudes,
subjective norm or perceived behavioral control2.
A flow diagram were used to visualize and provide rationale for
exclusion at the screening stage.
Meta-Analysis - Inclusion and Exclusion Criteria
1. Landers & Behrend, 2015
2. Ball, Wilcock, & Aung, 2010
11. Department of Hospitality Management
College of Human Ecology
Methods
Study coding were confirmed to the APA Meta-Analytic Reporting
Standards and PRISMA 2009 standard1.
Aspect of research design were coded as control variables2.
Publication biases were visualized using the Trim and Fill method
(T&F)3 and the significance level (p = 0.05) were tested using
Egger’s Regression of the Intercept Test (ERI)3.
Meta-Analysis – Coding, Reporting and Bias Correction
1. APA, 2011; Liberati et al., 2009
2. Valentine & Cooper, 2008
3. Duval & Tweedie, 2000; Egger et al., 1997
12. Department of Hospitality Management
College of Human Ecology
Methods
• Fisher’s Z were used to calculate
effect sizes, which allows
collective aggregation between
study effects for overall effect size
(𝐸𝑆) based on a random effects
model using weighted average
intra-study correlation1. Forest
plots were used for visualization1.
• The level of data heterogeneity
among the included studies were
calculated using Qz
2 and I2 3.
Meta-Analysis – Statistics
1. Rosenthal, Cooper, & Hedges, 1994; Liberati et al., 2009
2. Borenstein et al., 2009
3. Deeks, Altman, & Bradbum, 2008
16. Department of Hospitality Management
College of Human Ecology
Study Characteristics
Survey Type
Telephone Survey Paper Survey
Place
US UK
Language
English Spanish Chinese
17. Department of Hospitality Management
College of Human Ecology
Sample and Variables
Sample
Food handlers (School/ Care)
Restaurant employees
Food industry workers
Dependent Variable
Hand hygiene
Avoid contamination
Food safety behavior
Training Behavior
18. Department of Hospitality Management
College of Human Ecology
Study Quality
Pilot Study
Yes No
Measurement
7-point Likert type
Bi-polar scale
5-point Likert type scale
TACT
Yes No
19. Department of Hospitality Management
College of Human Ecology
Summary of Study Effects – Main Results
23
• A total of 46 study records
• 19 Attitude to intention correlations:
– 0.271 (95% [Cl] = 0.149 to 0.385, p < 0.01), with a small to medium effect size
• 13 Subjective norms to intention correlations:
– 0.370 (95% [Cl]= 0.190 to 0.455, p < 0.01), with a medium to large effect size
• 14 Perceived behavioral control to intention correlations:
– 0.247 (95% [Cl]= 0.096 to 0.386, p < 0.01), with a small to medium effect size
20. Department of Hospitality Management
College of Human Ecology
Heterogeneity and Explained Variances– Main Results
25
• Results indicate the level of between-study heterogeneity is not
significant (Q = 1.851, df =2, p=0.396).
– a satisfactory degree of homogeneity is achieved.
• The total variance of all TPB studies included in this particular meta-
analysis explained of 22% in true effect total variances (R2 = 0.22).
• A considerable amount of variance is still unexplained (78.4%).
21. Department of Hospitality Management
College of Human Ecology
Quality Control – Publication Bias
26
Egger’s regression
(t44 = 0.676,
p = 0.502).
23. Department of Hospitality Management
College of Human Ecology
Theoretical Implication
Examined prediction and observed variance within food safety behavioral intention1
The weighted average correlation from each independent variable ranged from 0.247 to
0.370, with medium to large effect sizes.
Help solve theoretical conflicts regarding perceived control 2
0.247 (95% [Cl]=0.096 to 0.386, p<0.01).
Theory enhancement by segmentation3, low level of heterogeneity ratio
the TPB model is surprisingly robust in terms of predicting food safety intention with
medium effect sizes indifferent from languages used.
1. Jedidi et al., 1997; Van de Ven, 2007
2. Cooke, Sniehotta, & Schuez, 2007; Lin & Roberts, 2017
3. Creswell 2005; Tashakkori & Teddlie 2003
24. Department of Hospitality Management
College of Human Ecology
Theoretical Implication – Measurement
The results noted that less than half of the studies included in this
study utilized an elicitation study.
Less studies used the TACT elements of the behavioral definition to
improve accessible behavioral outcomes
Bipolar measurement
Future food safety researchers are encouraged to clearly define the
food safety action using the TACT elements
1. Jedidi et al., 1997; Van de Ven, 2007
2. Cooke, Sniehotta, & Schuez, 2007; Lin & Roberts, 2017
3. Creswell 2005; Tashakkori & Teddlie 2003
25. Department of Hospitality Management
College of Human Ecology
Practical Implication
The results indicated that subjective norms tend to be the most
influential construct in TPB model to predicate food safety intention.
Government authorities rely on high-quality systematic
reviews to update policies and best-practice guidelines.
Studies with a large sample tend to have significantly stronger
individual subjective norms.
Correspondent to the group’s culture and identities
Academic researchers use quality synthesis to identify
research gaps within existing literature.
Help identify cost-effective risk prevention strategies and revise
epidemiology practices.
26. Department of Hospitality Management
College of Human Ecology
Limitations
Only included studies published in English
Did not include longitudinal studies
Publication bias
Low combined variance of true effect.
this model has been criticized by many (Ehiri et al., 1997; Griffith, 2000; Pilling et al., 2008; Sniehotta, 2009; Sniehotta, Presseau & Araujo-Soares, 2014; Verplanken & Wood, 2006; York et al., 2009), who argue that individuals who obtain knowledge and skills during training program often fail to act when they return to work (Egan et al. 2007; Griffith, 2000; Roberts & Barrett, 2009, 2011; Sniehotta, 2009; Sniehotta, Presseau & Araujo-Soares, 2014; Verplanken & Wood, 2006)
The long-term objective is to increase food safety behaviors among foodservice workers.
Various correlational studies indicate that intentions predict behavior (Sheeran, 2002).
intention offers a superior prediction of behavior in correlational tests compared to other cognitions, including explicit and implicit attitudes, norms, self-efficacy, perceptions of risk and severity (Sheeran et al., 2014), and personality factors (Chiaburu et al., 2011).
Attitude: refers to the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior
Norm: referring to the perceived social pressure to perform or not to perform a behavior
PBC: refers to the perceived difficulty of performing the behavior
TPB asserts that the most important determinant of behavior is the behavioral intention (BI). The TPB has constructed the behavioral intention as an immediate antecedent of behavior and an indication of an individual’s readiness to perform a given behavior.
strength of each behavioral belief (bbi) is multiplied by the evaluation of its consequence
each important individual believes to the person (nbi) multiplied by his/her motivation to comply with the behavior (mci)
perceived behavioral control, each control belief (cbi) or self-efficacy (sei) is multiplied by the perceived power of the control factor (ppi)
BI immediate antecedent of behavior and an indication of an individual’s readiness to perform a given behavior
TPB accounted for 27% and 39% of the variance in behavior and intention
R2 = .31 and .21, Self reported behavior or Observed behavior respectively; Armitage & Conner, 2001
Sheeran et al. (2017) found that experience can produce a quadratic relationship between intentions and behavior,
Experience could make one’s intentions to perform that behavior more stable or accessible (Doll & Ajzen, 1992). With greater experience, workers should have stronger intention to perform the food safety behaviors. On the other hand, greater experience is associated with increased automatization of behavioral performance. The more often one has performed a behavior in the past, the more likely it is that the action sequence becomes a habit, and consequently, there is less need for a conscious intent to guide behaviors (Wood & Neal, 2007). However, this habitual behavioral performance and the moderator information remains unknown within the foodservice literature (Sheeran & Webb, 2016; Sniehotta, 2009; Sniehotta et al., 2014; Verplanken & Wood, 2006).
Konecnik & Gartner, 2007
Konecnik & Gartner, 2007
post considerable threat to external validity
Thus, review papers and studies that investigate only background factors will be excluded
post considerable threat to external validity
Thus, review papers and studies that investigate only background factors will be excluded
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
post considerable threat to external validity
Thus, review papers and studies that investigate only background factors will be excluded
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
either a poor predictor (Lin & Roberts, 2017) or strong indicator of intended food safety behavior (Campell et al., 1998; Egan et al. 2007; McEachan et al., 2011).
Segmentation provides a mechanism to facilitate abduction by surfacing anomalies, which must then be confronted and resolved theoretically.
Anomalies = not normal
Abduction = Charles Sanders Peirce
either a poor predictor (Lin & Roberts, 2017) or strong indicator of intended food safety behavior (Campell et al., 1998; Egan et al. 2007; McEachan et al., 2011).
Segmentation provides a mechanism to facilitate abduction by surfacing anomalies, which must then be confronted and resolved theoretically.
Anomalies = not normal
Abduction = Charles Sanders Peirce
All of the studies reported internal validity using Cronbach’s alpha, and most of the studies established construct validity by matching the assessment of the attitude, subjective norms, and perceived behavioral control with the intended food safety behavior
Overall, is 0.282 (95% [Cl]=0.205 to 0.356, p<0.001).
either a poor predictor (Lin & Roberts, 2017) or strong indicator of intended food safety behavior (Campell et al., 1998; Egan et al. 2007; McEachan et al., 2011).
Segmentation provides a mechanism to facilitate abduction by surfacing anomalies, which must then be confronted and resolved theoretically.
Anomalies = not normal
Abduction = Charles Sanders Peirce
either a poor predictor (Lin & Roberts, 2017) or strong indicator of intended food safety behavior (Campell et al., 1998; Egan et al. 2007; McEachan et al., 2011).
Segmentation provides a mechanism to facilitate abduction by surfacing anomalies, which must then be confronted and resolved theoretically.
Anomalies = not normal
Abduction = Charles Sanders Peirce
If publication bias is present, the funnel plot will become less asymmetry. A clustering of larger or more significant studies emmerged slightly toward the top of the plot and clustered around the mean effect size. The base of the plot had fewer results, indicating a smaller number of negative-result studies were included in the analysis (Glasziou, Irwig, Bain, & Colditz, 2001). The funnel plot in this study is well balanced, show there is no apparent nor significant level of heterogeneity being observed.
either a poor predictor (Lin & Roberts, 2017) or strong indicator of intended food safety behavior (Campell et al., 1998; Egan et al. 2007; McEachan et al., 2011).
Segmentation provides a mechanism to facilitate abduction by surfacing anomalies, which must then be confronted and resolved theoretically.
Anomalies = not normal
Abduction = Charles Sanders Peirce
Descriptive Norms
And Group Norms
E.Gs of epidemiology practices incl. revise current ethical principle (autonomy: respect for individual rights), informed consent
Future researchers are encouraged to examine the heterogeneous nature of tourists using group-level measurement with data collected other than English-language survey.
Use more studies with stronger measurements, which can, in turn, help with analytical precision and reducing bias.