ATURES

Food Safety Educational InterventionPositively Influences College Students'

Food Safety Attitudes^ Beliefs, Knowledge,and Self-Reported Practices

Linda Yarrow, Ph.D., R.D./L.D., CDEValentina iM. Remig, Ph.D., R.D., F.A.D.A.

Mary Meek Higgins, Ph.D., R.D./LD., CDE

Abstract In this study, the authors evaluated college students' foodsafety attitudes, beliefs, knowledge, and self-reported prac-

tices and explored whether these variables were positively influenced by educational inter-vention. Students (n = 59), were mostly seniors, health or non-health majors, and respon-sible for meal preparation. Subjects completed a food safety questionnaire (FSQ) prior toeducational intervention, which consisted of three interactive modules. Subjects complet-ed module pre-, post-, and post-posttests. The FSQ was also administered after exposureto intervention and five weeks later to determine changes in food safety attitudes, beliefs,knowledge, and self-reported practices. Students' FSQ attitude scores increased from 114to 122 (p < .001); FSQ belief and knowledge scores improved from 86 to 98 (p i.OOl) andfrom 11 to 13 (p < .001), respectively. Food safety knowledge was also measured by mod-ule pre- and posttests, and improved significantly after intervention for all students, withhealth majors having the greatest increase. Intervention resulted in improved food safetyself-reported practices for health majors only The educational intervention appeared ef-fective in improving food safety beliefs and knowledge. For health majors, attitudes andsome self-reported practices improved. For all areas, the strongest effects were seen inhealth majors.

IntroductionFoodbornc illness is a major health threat inthe United States, resulting in economic bur-dens for individuals and their employers andin severe cases, even death. Statistics supportthe seriousness of the threat. Each year, food-home illnesses cause an estimated 76 milhonillnesses, 325,000 hospitalisations, and 5,000deaths in the United States (Mead et al., 1999).

Limited research about college studentshas been published describing their risk offoodborne illness. Previous research has pri-marily focused on the general populationand food industry {.Altekruse, Street, Fein, &Levy. 1995; American Dietetic Association,2003; Cody & Hogue, 2003; Food Safet\' andInspection Ser\ice [FSIS], 2002; Redmond& Griffith, 2003). Within the limited data

focusing on college students, food safetyresearchers concluded that undergraduatestudents engage in unsate practices, includ-ing risky food handling and food consump-tion {Li-Cohen & Bruhn, 2002; Morrone &Rathbun, 2003; Unklesbay, Sneed, &r Toma,1998). A search of the scientific literaturefound no studies that provided food safetyeducalion intervention lo improve food safe-ty behaviors of college students.

One purpose of this study was to explorerelationships among food safety attitudes, be-liefs, knowledge, and self-reported practicesof current college students in health and non-health majors. An additional purpose was todetermine whether an educational interven-tion could improve variables of interest.

Methods

SubjectsApproval was obtained from the university'sltistitutional Review Board for Research In-volving Human Subjects before commencingthe research. Seventy-one college students ini-tiated participation with 59 college students,38 females and 21 males aged 21-49 years, vol-untarily completing all required steps. Subjeetswith non-health majors had a higher drop-outrate from the study, with 21 of 32 completingall components of the research compared to 38of 39 health majors. Data were eliminated forthe students who did not view the educationalmodules (i.e., planned inter\-ention). Studentswere recruited by in-class invitations. The stu-

50 Volume 71 • Number A

BLE 1Characteristics of Subjects, Health Majors vs. Non-Health Majors

Characteristics of Subjects p-Value

Held job as a food server such aswaiter or waitressHeld job as a food preparar (cook)

Food safety certification

Average # meals prepared/week

Average # college nutritioncourses completed

Average # college food sciencecourses completedAverage # college microbiologycourses completed

Health Majors(fi=38)

29

24

22

6-10 (n^ 16)

2 or more {n = 36)

1(/i=17)

0(/7=31)

Non-HealthMajors {n = 21)

15

8

6

1-5{n = 13)

0(n=14)

0(/)=18)

0(/J=20)

0.17

3,42

4.66

,68

.064

.031

dents were seniors, plus one graduate student,living in a house or apartment rather than resi-dence halls or Greek housing. Health majorswere enrolled in Human Nutrition 630 (Clini-cal Nutrition) and non-health majors were en-rolled in Mass Communications 645 (PublicRelations Campaigns}.

Qucslionnaire Administration andScoring

A food safety questionnaire (FSQ) previouslyused by ihis research team to conduct a tele-phone survey with older adults was adaptedfor use with college students. The majority ofquestions were taken from a preexisting vali-dated scale developed hy Medeiros and co-authors (Medeiros, Kendall, Hillers, Chen. &DiMascoia, 2001). The university survey sys-tem, an online platform for conducting sur-veys, was used to administer the FSQ. Studyparticipants completed the FSQ three times:pretntervention (prior to viewing education-al food safety modules), postintervention (upto one week after module completion), andposi-postintervention (five weeks after mod-ule completion).

The survey questions were grouped by theevaluated dependent variables: food safetyattitudes, beliefs, and knowledge, and self-reported practices to include high-risk foodintake. Index scales were developed to deter-mine a score for each of the variables. Indexscore ranges were: attitudes (21-147), beliefs(17-119), knowledge (0-14), three-pointself-reported practices scale (9-27), andhigh-risk food intake (13-39).

InterventiotiInteractive instructional materials were de-veloped and pilot tested. A lesson-buildingprogram that lets the user create engaging,interactive Web lessons was used (Softch-alk, 2002). The three educational modulesincluded food safety instruction with clipart, animated graphics, flash card activities,quizzes, word seek activities, crosswordpuzzles, drag-n-drop activities, audio clips,and links to the World Wide Web. Eachmodule was designed to require 30-60 min-utes lor completion, followed by a posttestlasting 10-15 minutes. Delivering instruc-tion in an online format gave students flex-ibility in when and where tbey completedthe modules. Previous focused food safetydiscussions held with other junior- andsenior-level college students contributedto decisions about which food safety topicswere included and emphasized in the educa-tional modules.

Module One provided a food safety over-view with incidence and prevalence of food-borne illnesses in the United States, emergingand common pathogens, and recommendedfood handling guidelines. Module Two pre-sented a briel review of food safety literatureand information on common food safetybeliefs, knowledge, and food handling prac-tices. The use of food thermometers, popularattitudes about food safety, and informationabout industry requirements and standardswere also included. Module Three focusedon older adults' foodborne illness risks andpreferred food safety handling practices.

Pre-, post-, and post-postmodule tests as-sessed food safety knowledge, using multiplechoice, true/false, or rank option questions.Students completed a pretest (active onlinefor two days) prior to viewing each onlinemodule, which was active for one week. Dur-ing the last two days that the module wasavailable for viewing, a posttest was activatedvia the survey system. Additional post- andpost-postmodule questions assisted research-ers in evaluaiing students" self-reported be-haviors. Students answered behavior changequestions during the postmodule test and asecond time with the post-postquestionnairefive weeks after completion of modules,

Statistical AnalysesThe majority of FSQ response options wereseven-point Likert scales with assigned values.When Likert scales included a response of notapplicable, those responses were not used inanalysis. Some response scales included don'tknow as an option. Since a response of don'tknow on the consumption of high-risk foodsscale indicated some risk (e.g., students mighteat rare hamburger, which may put them un-knowingly at foodborne illness risk), this re-sponse was scored to represent risk,

FSQ responses were analyzed for each ad-ministration: Time 1 (preintervention), Time2 (postiniervention), and Time 3 (five weekpost-postintervention). Results oí the interven-tion pre-, post-, and post-postmodule tests werealso analyzed. Response frequencies resultedin nonnormal distributions. The small samplesize, nonnormal distributions, and high pre-dominance of ordinal information supportedthe use of nonparametric testing. Statislicalanalyses used Wilcoxin Signed Rank, Fried-man. Mann-Whitney Ü. McNemar, Cochran Q,Chi-square, and Speannans rho tests. To test in-ternal consistency reliability of the FSQ, Cron-bach's alpha was performed for each index.

ResultsCharacteristics of the subjects are presentedin Table 1, The number of participants whoheld food safety certification was significant-ly different according lo their major. Fifty-eight percent of health majors were certifiedcompared to just 29% of the non-health stu-dents (p = .03). These differences were notsurprising since for ihe health majors, foodsafety certification was required in one oftheir previous classes.

Index scores for the total group were ana-lyzed for comparison over time, before andafter food safety educational intervention.

jaiui<ir\'/Febmdr\' 2009 • journal ol Environmcnial Hcdilh 3 1

As a group, students' food safety attitudesimproved from 114.5 to 122.2 out of 147 pos-sible (p < .001) from pretest to post-posttest.The reported changes can be attributed toimprovements in health majors' FSQ attitudescores, which increased (p < .001) from prc-intervention to post-postintcrvention, whilenon-health majors did not show improve-ment. Attitude questions were also examinedindividually The most significant changesoccurred between pre- and postintenxntion.Students from both groups became more con-cerned about eating eggs tbat did not havefirm yolks (p < .001), drinking unpasteurizedapple juice (p ^ .001), eating alfalfa sprouts(p 5 .001), eating hotdogs right out of thepackage (p s .001), thawing perishable foodson tbe counter (p = .001), and not refrigerat-ing foods such as rice and beans {p = ,007).

Students' FSQ belief index scores increasedfrom85.8to97.6ofll9(ps.001) from Time1 to Time 3, representing more positive foodsafety beliefs after intervention. When beliefquestions were examined individually, threebeliefs had the strongest change. Students'mean rating of the statement, "If 1 followsafe food handling practices, my cbances ofsickness would decrease," increased from 1.4(strongly disagree) to 6.7 (strongly agree)(p £ .001). After intervention, students alsoindicated belief tbat they were more likelyto get sick if they did not wash their bandsprior to cooking (p <, .001) and if tbey leftcooked food out of the refrigerator for morethan two hours (p = .005), Students exhibitedincreased belief that eating or handling raw-sprouts (p£ .001), raw vegetables (p< .001),raw beef (p = ,011), raw chicken (p = .035),and raw shellfish (p = .049) could be harm-ful to beaitb. Students became less concernedwith risks associated with raw fruits (p =.004). Students also increased in the beliefthat it was common for people in the UnitedStates to become sick because of tbe way thatfood is prepared or handled in the home (p =.001) and that contamination of food by mi-croorganisms was a greater problem than pre-viously recognized (p < .001). As subgroups,both health majors {p£ .001) and non-healthmajors (p = .018) increased in behef scores.Noivhealtb majors significantly increased (p£ .001) in the belief tbat the home was a pri-mary source of foodbome illness.

Immediately after intervention, students'FSQ score for total knowledge increased(p< .001), with scores changing from 11.2 to12.6 out of H possible points. The most sig-nificant changes were found in responses to

ComparisonScores for S

Variable

Attitude

Health

Non-health

Beliefs

Health

Non-health

Knowledge

Health

Non-healtti

SRP° 3 pt. scale

Health

Non-health

High-risk foodintake

Health

Non-health

2of Health and Non-Health Students' FoodVariables for Time 1, Time 2, Time 3̂

Mean

Timel

120.3 ±11.4

104.0 ±13.8

87.9 ±10.5

82.1 ± 7.4

11.8 ±1.9

10.2 ±1.7

20.2 ± 3.0

18.0 ±2.5

33.4 ± 3.8

31.9 ±4.5

Index Scores

± Standard Deviation

Time 2

128.7 ±14,9

108.8 ±16.5

100.3 ±9.3

88.7 ±15.8

13.1 ±1.0

11.6 ±2.3

21.9 ±2.7

18,1 ±3,3

34.2 ± 3.9

32.6 ± 4.0

Time 3 Timel

S.001

130.8 ±9.0

106,6 ±21,9

100.8 ±9.9

92,0 ±11.8

13,1 ±0.9

11.7 ±1.6

22.9 ± 2.7

14,62 ±3.2

34.5 ± 3,7

33,0 ±3,7

.030

,001

.001

.146

Safety Index

p-Vatue

Time 2 Time 3

<.OO1

.004

,002

s,001

.086

<,001

,003

5.001

á.OO1

,101

Note. AÍ = 38 health and 21 non-health majors.^Tinie 1 = preintervention, Time 2 = postintervention, and Time 3 - post-postintervention."SRP - Self-reporteä practices, including thermometef use.

four questions. More students became awaretbat they should not prepare food for othersif they bave diarrhea (correct responses in-creased from 49% to 88%). Students learnedthat hamburger patties should be cooked toan internal temperature of 16O''F (correctresponses increased from 39% to 64%), Stu-dents also increased in knowledge tbat cook-ing egg yolks and whites until firm killedharmful organisms (61% correct increased to81%). Finally, students learned tbat nonpinkhamburger meat does not guarantee safenessto eat (75% correct increased to 93%). Assubgroups, both bcalth and non-health ma-jors had increased FSQ knowledge scores (p< .001) for each group from preinterventionto post-postintervention.

Self-reported safe food practices becamemore frequent. Scores increased from 19 to21 of 27 possible points {p= .001). Specifical-

ly, students became less likely to prepare foodfor otbers if they had diarrhea ( p i .001), andmore hkely to use food thermometers (p =,01), The reponed changes can be attributedto the health majors' improvement in notpreparing food for otbers if they bad diarrhea(p = .002), thermometer use (p = .006), andnot leaving cooked items out for use later inthe day (p = .046) sucb as at a buffet or party.As a subgroup, non-health majors did notimprove in self-reported practices. As a totalgroup and subgroups, no significant changesoccurred among the students' self-reportedpractices for food sanitation, hygiene, stor-age, thawing, or high-risk food intake.

Index scores were compared betweengroups. Health majors scored higher thannon-bealth majors for all indices for each timeperiod (Table 2) except for high-risk food in-take. The strongest differences were for food

52 Volume 71 • Numher 6

BLE 5Comparison of Health Majors' and Non-Health Majors' AverageModule Knowledge Test Score

Modules Health Non-Health p-Value

Mean ± Standard Deviation

Module 1 average score

Time!

Time 2

Time 3

39.7 ±13.5

77.4 ±18.2

55.5 ±14.9

40.8 ±12.9

46.9 ±17.5

40.9 ±13.7

.854

S.001

<.OO1

Module 2 average score

Timel

Time 2

Time 3

44.3 ±12.6

82.5 ±14.5

55.9 i 13.6

35.0 ± 9.1

46.8 ± 19.0

38.1 ± 13.8

.025

s.OOl

.001

Module 3 average score

Timel

Time 2

Time 3

55.0 ±12.3

78.0 ±10.7

64.4 ±13.6

49.9 ±16.9

62.1 s 44.3

52.8 ±14.8

.587

.021

.009

/Vote A I -38 health, 21 non-healfli majors; Time 1 - preintervention, Time 2 = postintervention, and Time 3 = post-postintervention.

safety attitudes and self-reported food safetypractices, with heallh majors scoring muchhigher at all ihrce time periods (pS .001).

The strongest relationships amortg the in-dices of attitudes, beliefs, knowledge, andself-reported practices were between Time 2and Time 3 for food safety attitudes and he-liefs. Those students who had more positivefood safety beliefs also had tnore positive foodsafety attitudes immediately after educationalintervention (r 139] = .63, p < .001). The ef-fect size is larger to much larger than typical(per Cohen's [1988] guidelines). Forty-threepercent of the variance in food safety beliefs atTime 2 was predicted by food safety attitudes.For Time 3, the correlation direction wasagain positive (r 142] = .74, p s .001), with ef-fect size being mtich larger ihan typical. Foodsafety attitudes predicted 55% of the variancein food safety beliefs at Time 3.

Improvements in educational modtileknowledge scores after intervention werelound for all three food safety modules(Table 3). On a scale of 1-100, Module Onemean scores increased from 40.1 to 66.5 (p< .001). For Module Two, mean scores in-creased from 41.0 to 69.8 (p < .001). ForModule Three, mean scores increased from53.2 to 72.3 (p<.001).

Health majors had significantly highermodule test scores than non-health majors,except for Module One pretest and ModuleThree pretest. While all mean scores droppedfrom the postintervention to the post-postint-ervention measurement, they remained high-er than the preintervention scores (p <.OO1).This result can be attributed to health majors'knowledge scores, which at post-postinter-vention dropped but were still higher thanpreintervention scores. Knowledge scores fornon-health majors dropped at post-postinter-vention, with no scores higher ihan preinter-vention scores, indicating they did not retainthe newly acquired information.

A notable distinction between the groupswas the amount of time students spent com-pleting the modules. Approximately three-fourths of non-health majors spent 30 min-utes or less on each educational module,white all health majors spent 30 minutes totwo hours. Health majors also referred backto the educational materials while complet-ing posttests, unlike non-health majors. Bothgroups had equal access to materials duringposttests. Health majors strongly indicatedthat the module information was importantto their future profession (74%) compared tonon-health majors (9.5%).

Effectiveness of educational content wassupported when students indicated theycould likely achieve most of the module ob-jectives. Students also reported that the in-teractive educational programs and varielyof learning activities enhanced their learningand understanding. Students indicated theWeb-based delivery was convenient and ihatthey would recommend this lype of coursematerial presentation to other students.

DiscussionRelationships among attitudes, beliefs,knowledge, and self-reported practices ofcollege students before and after food safe-ty education intervention were exploredin a nonrepresentative small sample of col-lege students. A review of literature foundone other study that focused specifically onfood safety knowledge of college students(Unklesbay, Sneed, & Toma, 1998). In ihatstudy, health majors scored higher than non-health majors, a finding that was supportedin this research.

The educational intervention led the col-lege health majors to have more positiveattitudes concerning food safety practices.Measuring food safety attitudes is important,since, according to the Theory of PlannedBehavior (Aizen, 2006), people act in accor-dance with their intentions, and intentionsare influenced by attitudes. Thus, improvingcollege students' attitudes about food safetymay be a first step towards influencing theirfood safely behaviors. Indeed, two of theirself-reported food practices did improve forthis group. Health majors reported decreasedconsumption of some high-risk foods andreported increased usage of thermometers,both of which are important practices to pre-vent foodborne illness (FSIS, 2007).

The educational modules had a positiveitnpact on food safety knowledge, as all scoresincreased immediately after intervention. Atpost-postintervention, however, non-healthmajors' food safety knowledge showed noimprovement, indicating they did not retainnewly acquired information five weeks af-ter intervention. Regarding how individualslearn, the Constructivism Theory states thatthe learner constructs or builds new ideasor concepts based upon past knowledge andpast experiences (Bush, 2006). In this case,non-health students had the least food safetyexposure and training prior to educationalintervention, which may have limited theirability to learn food safety concepts. Simi-larly although health majors had received

Januär\'/Fcbruar\' 2009 • journal of Environmcnlal Health 3 3

food safety information in previous collegecourses, FSQ and premodule test scores in-dicated that much of this lype of inlormaUonwas not retained. Our results indicate thatconsideration should be given to providing areview of food safety information in upper-level courses for health majors.

Previous research has Indicated thaiknowledge does not always correspond toimproved food safety behaviors {Redmond& Griffith, 2003). This finding was sup-ported in the current study. Even after theirfood safety beliefs and knowledge improvedwith exposure to the study's educational In-tervention (which emphasized importance ofchecking end-point temperatures of leftoversand meat items in particular), non-healthmajors were not more inclined to use ther-mometers or decrease consumption of riskyloods. The Behaviorism Theoiy states that be-haviors will increase or decrease based uponpositive or negative reinforcement (Bush,2006). If students do not recognize positivereinforcements associated with proper foodhandling techniques, such as good health,or do not recognize negative reinforcements,such as diarrhea or vomiting related to food-borne illness, tben they may not be motivat-ed to change.

Several theoretical frameworks address-ing relationships between attitudes and be-haviors have been described (Ajzen, 2001;Crano, 2005; Petty, 1997). Resistance to be-havioral change is likely related to attitudestrength or attitude ambivalence or bolh.Wbile food safety attitudes became more

positive in this study, they may not have be-come strong enough to facilitate more be-havior change. Even when attitudes change,the new attitude overrides but may notreplace the old attitude, which is habitual(Ajzen, 2001).

Potential weaknesses of the current studyinclude internal validity threats related totesting and mortality (drop-out rate). Stu-dents may have become sensitized to foodsafety issues due to repeated multiple test-ing (although both groups had the sameexposures), and the non-health majors hada higher drop-out rate. Possible externalvalidity threats include interaction of test-ing and treatment (intervention). All sub-jects received intervention in the same or-der but performance from earlier treattnentcould have affected test performance fromlater treatment, Reactivity could also posea threat because incentive tn complete allrequired steps may have differed betweenhealth and non-heallh majors. Other possi-ble validity threats were assessed and foundto not be a concern. No significant out-breaks of foodborne illness were reportednationally or locally during the study, andno major local news articles discussed foodsafety issues. The subjects did not matureat different rates and were not tested differ-ently (Jones, 1996J.

ConclusionThis research has demonstrated that aninteractive food safety education inter-vention resulted in improved food safety

knowledge and beliefs for college students.The strongesl effects were seen in studentswbo described that food safety principleswere important to their future professions,i.e., health majors. Educational interven-tion resulted in health majors" improve-ment in food safety attitudes and in theself-reported practices of thermometer useand consumption of some high-risk foods,and not preparing food for others whendiarrhea was present. The Interactive edu-cational modules were received positivelyby both groups of students and this typeof educational program can be considereda valuable tool for food safety education ofcollege students.

Because college students' behaviors placethem at increased risk for foodborne ill-ness, educational interventions, such as theone developed for this study, are needed.Many college students are preparing mealsfor themselves and others for the first time.Additionally, many students represent futurepracticing professionals responsible for de-livery of food safety education to the pubhc.College students will benefit from exposuresto safe food handling instruction and effectivepractices fur preventing foodborne illnesses.Additional research is needed to better exam-ine specific barriers to changing food safetybehaviors of college students. y$(

Corresponding Author: Linda Yarrow, Instruc-tor, Kansas State University, Dept. of HumanNutrition, 255 Justin Hall, Manhattan, KS66506-1407. E-mail: lyarrow@ksu.edu.

FËEERENCESAizen, I, (n.d.) Theory of planned Jjt'liavioi: Retrieved January 25,

2006, from http://www-unix.oit.umass.edu/~aizen/tpb.diag.htm!Ajzen, 1. (2001). Nature and operation of attitudes. Annual Review of

Psychology. 52, 27-58.Altekruse, S.F, Street, D.A., Fein, S.B., & Lev); A.S. (1995). Con-

sumer knowledge of foodbome microbial hazards and food-han-dling practices. Jounuii of Food Protection, 59(3), 287-294.

American Dietetic Association. (2003). Food and water safety, jinj/-nal of the American Dietetic Association. IO3{9). 1203-1218.

Bush, G. (2006). Learning about learning: From theories to trends.Teacher Librarian, 34(2), 14.

Cody M.M., &r Hogue, M.A, (2003). Results of the home foodsafety—it's in your hands 2002 survey: Comparisons to the1999 benchmark survey and healthy people 2010 food safetybehavior objectives. Journal of the American Dietetic Associa-tion. 103(9). 1115-1125.

Cohen, J. ( 1988). Statistical power analysis for the behavioral sciences(2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.

Crano, W.D. (2005). Attitudes and persuasion. Annual Review of Psy-chology. 57, 345-374.

Food Safety and Inspection Service, U.S. Department of Agriculture,(n.d., updated March 16, 2007). Kitchen thennometers. RetrievedMay 17, 2007, from http://www.fsis.usda.gov/Eact_Sheels/Kitch-en_Thermometers/index.asp

Food Safety and Inspection Service, U.S. Department of Agriculture.(2002). PR/HACCP rule evaluation report: Changes in consumerknowledge, behavior, and confidence since the 1996 PR/HACCP finalnde. Retrieved March 15th, 2006, from http://www.fsis.usda.gov/oa/researcli/behaviur_haccp.btm

Jones, K.A. (1996). Research methods in the social and behavioral sci-ences (2nd ed.). Sunderland, MA: Sinauer Associates.

54 Vültitnc 71 • Number 6

WEERENCESLi-Coben, A.E., & Bruhn, CM. (2002). Safety of consumer handling of

fresh produce from the time of purchase to the plate: A comprehen-sive consumer survey Journal ofEood Protection. 65(8), 1287-1296.

Mead, P, Slutsker, L., Dietz, V, McCaig, L., Bresee, J., Shapiro, C ,Griffin, P, & Tauxe. R. (1999). Food-related illness and death inthe United States. Emerging infectious Disease, 5, 607-625.

Medeiros, L.C., Kendall, P, Hillers, V., Chen, G., & DiMascola, S,(2001). Identification and classification of consumer food han-dling behaviors for food safety education. Jmirnaí of the AmeritanDietetic Association, ¡OJ(ll). 1326-1339,

Morrone. M., & Rathbun, A. (2003). Health education and foodsafety behavior in the university setting. Jounuil of EnvironmentalHealth, 65(7), 9-15.

Petty, R.E. (1997). Attitudes and attitude change. Annual Revit'w ofPsychology, 48. 609-647.

Redmond, E.C., & Griffith, CJ. (2003). Consumer food handling inthe home: A review of food safety studies. Journal of Food Protec-tion. 66(1) A30-161.

Softchalk, L. (2002). Lesson builder. Retrieved Januar>' 10th, 2005,from http://www.softchalk.com/

Unklesbay, N., Sneed, J., & Toma, R. (1998). College students' at-titudes, practices, and knowledge of food safety Journal of FoodProtection. 61(9). 1175-1180.

Did YOUKnow

NEHA e-Learning has just added 18 new courses from presentationsmade at the 2008 AEC in Tucson! The tracks taped this year werein food safety, general environmental health, sustainability andvector control. Remember, NEHA members get free continuingeducation credits for completing the courses and quizzes which canbe used toward your credential requirements! Visit www.neha.org/elearning for information on these and all of the NEHA e-Learningopportunities!

N O M I N A T I O N S N O W A C C E P T E O

The Walter S. Mangold Award, which recognizes ex-

traordinary achievement in environmental health, has

been presented since 1956 to the brightest and best

in this profession. Nominations for this award may be

made by an affiliate or by any five NEHA members,

regardless of their affiliation.

cSi m i ̂ g^ CO) 1 cdl

Although the Mangold—NEHA's most prestigious award

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profession for its skill, knowledge, and commitment to

public heaith. Nominations are due in the NEHA office by

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For information, please visit www.neha.org/about/awardinfo.html. Members can obtain nomination

forms by calling (303) 756-9090, extension 302, or by sending an e-mail to gpfeufer@neha.org.

Jdnudr)'/February 2009 • Journal of Environmenlal Health 3 5