Predicting hygienic food handlingbehaviour: modelling the health

action process approachBarbara A. Mullan, Cara L. Wong and Kathleen O’Moore

School of Psychology, University of Sydney, Sydney, Australia

Abstract

Purpose – The purpose of the current paper is to investigate the determinants of hygienic foodhandling behaviour using the health action process approach (HAPA) and to examine if the volitionalcomponents of the model or the addition of past behaviour could explain additional variance inbehaviour.

Design/methodology/approach – A prospective four-week study investigating the predictiveability of HAPA variables and past behaviour was used. At time 1, 109 participants completedself-report questionnaires regarding their action self-efficacy, risk awareness, outcome expectanciesand intentions to hygienically prepare food and past behaviour. At time 2, participants returned afollow-up questionnaire, which measured behaviour, planning, maintenance and recovery self efficacy.Structural equation modelling was used to compare three versions of the HAPA model.

Findings – The first model showed that intention was a significant predictor of behaviour explaining40 per cent of the variance and was the best fit. The second model, which included the volitionalcomponents of the HAPA model, did significantly increase the proportion of behaviour explained. Thethird model, which included past behaviour, increased the variance explained but was not a superiorfit to the previous two models.

Practical implications – The results of this study confirm that aspects of the HAPA may be usefulin determining hygienic food handling behaviour. However, volitional variables do not appear to beimportant in this behaviour. The implications of this for future research and interventions areelucidated.

Originality/value – The current study is one of the first to use the HAPA model to predict hygienicfood handling behaviour.

Keywords Food safety, Food controls, Hygiene, Australia

Paper type Research paper

IntroductionThe number of reported foodborne illnesses in Australia has increased over the pastten years with an estimated 5.4 million cases per year (National Health and MedicalResearch Council, 2003). Other Western populations such as the United States havesimilarly found that approximately a quarter of the population suffer from foodborneillness each year (Mead et al., 1999). Further, many incidents of foodborne illnesses gounreported (Crerar et al., 1996). As a consequence, foodborne diseases pose a significantpublic health problem in Australia and worldwide (Desmarchelier, 1996).

Correct handling of food during all stages of its preparation and storage is vital inreducing the incidence of foodborne illness (NHMRC, 2003). However, between 10 and 20per cent of foodborne illness in Australia and the United Kingdom is estimated to be as aresult of consumer food handling behaviour (Food Authority NSW, 2008; Ryan et al.,1996). A systematic review of food safety studies identified that consumers commonlyimplement unsafe food-handling behaviours during domestic food preparation

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British Food JournalVol. 112 No. 11, 2010pp. 1216-1229q Emerald Group Publishing Limited0007-070XDOI 10.1108/00070701011088205

(Redmond and Griffith, 2003). Observation research has found that infrequent and poorhand-washing techniques are common in Australian food handlers (Jay et al., 1999a) andup to two-thirds of participants did not wash knives and cutting boards after use withraw meat and before reuse of implements (Jay et al., 1999b; Jevsnik et al., 2008).

A large proportion of the research into foodborne illness appears to show adiscrepancy between knowledge of correct food safety behaviours and applying thisknowledge during actual behaviour. For example, a study by Byrd-Bredbenner et al.(2007) found that although 97 per cent of the sample rated their own food safetyknowledge as at least fair, 60 per cent did not implement safe food handling behaviourssuch as washing their hands with soap and water after touching raw poultry. Redmondand Griffith (2003) compared studies into consumer food safety information and foundthat although food safety knowledge was good, participants in other studies generallydid not engage in these food safety behaviours.

Social-cognition models are important to investigate what social influences andcognitive processes motivate health behaviours. However, very few studies haveinvestigated these models to predict safe food handling behaviours (Griffith et al., 1995).

Models used in food hygiene researchThe health belief model (HBM) has been applied in a number of studies of hygienicfood handling behaviours with contradictory results. For instance, the model wassuccessful in predicting behaviour in a study of risk perception (Kuttschreuter, 2006;Roseman and Kurzynske, 2006). However, McArthur et al. (2006) found that the HealthBelief Model was a poor predictor of compliance in food safety recommendations inundergraduate students. Therefore the HBM has been criticized and it has beenproposed that other models may be more successfully applied. One such model is theTheory of Planned Behaviour (TPB), which focuses on intention as the most salientpredictor of future behaviour and has been effectively applied to predict hand hygienepractices (Clayton and Griffith, 2008). A study by Mullan and Wong (2009) found theTPB to predict 66 per cent of the variance in intention and 21 per cent of the variance insafe food handling behaviour. The results of this study indicate that the model is betterat predicting intention than behaviour.

Health behaviours are performed inconsistently regardless of intentions (Sniehottaet al., 2005) leaving what is commonly referred to as the “intention-behaviour gap”. Asa consequence of this research the TPB has been criticised as an incomplete model(Ajzen, 1991) and the health action process approach (HAPA) has been developed inattempt to bridge this gap.

The HAPA is a social-cognition model of health behaviour, which contends thathealth behaviour change is a process, which consists of a motivational and a volitionalphase (Schwarzer et al., 2003). In the motivational phase the individual forms anintention to either adopt a behaviour or change a risk behaviour. Three components ofrisk awareness, outcome expectancies, and perceived action self-efficacy lead to theformation of an intention. Risk awareness is an important component as a perceivedthreat or concern must exist before an individual considers the benefits of possibleactions and behaviours and reflects on their ability to actually perform them(Schwarzer et al., 2003). Outcome expectancies are then balanced based on positive andnegative evaluations of the behaviour. This leads to behaviour change if the outcomesare perceived to be more beneficial than not taking action. Self-efficacy is the belief

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about one’s capability to accomplish a behaviour even if barriers exist and is seen asthe most influential motivational factor and the strongest predictor of behaviouralintentions (Schwarzer, 2008). Once an intention to change a behaviour is formed, thechange must be planned, initiated, and maintained, and relapses have to be managed.These constructs form the subsequent volitional stage of the model, which involvesimplementing intentions into actual behaviours, and includes three variables:

(1) planning;

(2) maintenance self-efficacy; and

(3) recovery self-efficacy (Schwarzer et al., 2003).

Schwarzer and Fuchs (1996) explored the interplay between self-efficacy, outcomeexpectancies, risk perception, and healthy eating behaviour over a six-month period.Their study showed that the model accounted for 21 per cent of the variance in healthyeating behaviour at follow-up in men and 20 per cent of the variance in women, withintentions to act and self-efficacy being the only significant predictors. A further studyfound self efficacy and intention predicted 33 per cent of high-fibre diet behaviour and48 per cent of low-fat diet behaviour (Schwarzer and Renner, 2000). The importance ofplanning is also highlighted in recent research with planning and self efficacypredicting 73 per cent of dietary behaviour (Schwarzer et al., 2007). Thesedevelopments are promising for utilising the HAPA variables to enhanceunderstanding of food related behaviour.

In addition to these volitional variables, another variable that may be important infood related behaviour is that of past behaviour or habit. Brennan et al. (2007) foundthat in relation to food handling behaviours past experience was an importantpredictor of future behaviour. Ouellette and Wood (1998) contend that behaviours thatare performed consistently in stable conditions eventually become habitual. It is likelythe safe food handling practices will become a habit when performed consistently. Forthat reason the influence of past behaviour is also investigated in the present study.

Although the HAPA has been applied to a large number of food and nutritionrelated behaviours including improving fruit and vegetable consumption(Luszczynska, Tryburcy and Schwarzer, 2007), reducing fat intake (Luszczynska,Scholz and Sutton, 2007), weight reduction (Luszczynska, Sobczyk and Abraham,2007) and consumption of low fat food (Renner et al., 2000), the model has not beenapplied to food hygiene behaviours. However, individual food handling practices arelikely to be habitual, and the HAPA has been successfully applied to other habitualbehaviours such as dental flossing and seat-belt use (Schwarzer et al., 2007), as well asbreakfast consumption (Mullan et al., 2008).

Therefore the main aim of this study is to consider whether motivational HAPAcomponents predict food hygiene intention and whether the addition of volitionalHAPA variables (maintenance, recovery self efficacy and planning) predict more ofhygienic food handling behaviour than intention alone.

It is hypothesized that motivational variables of outcome expectancies, riskperception, and action self-efficacy will predict intention and that theintention-behaviour relationship will be moderated by action planning and recoveryand maintenance self efficacy. As food hygiene behaviour may be habitual, it is furtherhypothesized that the addition of past behaviour will significantly increase thevariance explained.

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MethodologyStudy sampleThe participants were 109 first year psychology students (85 female, 24 males), with amean age of 19.5 years (range 17 to 35, SD ¼ 2:43). Over half of the participantsclassified themselves as Australian – Caucasian ethnicity (53.2 per cent, n ¼ 58), 26.6per cent (n ¼ 29) Asian, 12 per cent (n ¼ 13) European, and 8.4 per cent (n ¼ 9)classified themselves as “other”. Ethical approval was obtained from the UniversityHuman Ethics Committee where the research was conducted.

DesignA total 109 participants completed two online questionnaires spaced four weeks apart.

ProcedureAt time one, students completed questions related to demographic variables, riskawareness, outcome expectancies, task self-efficacy, intention and past behaviour ofhygienic food handling behaviour. At time 2, participants reported their food hygienebehaviour over the experimental timeframe, and completed measures of planning,maintenance self-efficacy and recovery self-efficacy.

MaterialsIn the study that follows food hygiene was defined as “action taken to ensure that foodis handled, stored, prepared and served in such a way, and under such conditions, as toprevent the contamination of the food” (Donaldson, 1991 p. 22).

The HAPA questionnaire was designed according to the guidelines outlined bySchwarzer et al. (2003). The questionnaire was electronically administered anddesigned using an online tool called Quask FormArtist Software. Participants couldcomplete the study from university or at home.

Risk awareness was measured with three risk components:

(1) relative risk;

(2) absolute risk; and

(3) risk severity.

Absolute risk was measured with three items (if you don’t prepare food hygienicallyevery meal, how do you estimate the likelihood that you will ever: suffer from foodpoisoning/will feel less healthy/will not eat your food). This was measured on aseven-point Likert scale from very low to very high. A Cronbach’s alpha coefficient of0.819 (M ¼ 13:39, SD ¼ 3:98) was reported. Relative risk was measured by askingparticipants, compared to other people of your age and sex, if you don’t prepare foodhygienically every meal how do you estimate the likelihood that you will ever: sufferfrom food poisoning/will feel less healthy/will not eat your food. An alpha coefficient of0.829 (M ¼ 13:98, SD ¼ 4:39) was reported. The third component measured was riskseverity (How severe would the following health related problems be for you, to sufferfrom food poisoning/to feel less healthy/to be unable to eat your food). An alphacoefficient of 0.699 (M ¼ 12:82, SD ¼ 3:23) was reported. Due to the low internalconsistency of risk severity, only absolute and relative risks were examined. Thecombined effect of absolute and relative risk had a lower internal consistency than eachalone (Cronbach’s alpha ¼ 0.774), therefore the two were kept as separate constructs.

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Outcome expectancies were measured as the mean of three, seven-point (1 to 7)items (If I start to prepare food hygienically I will: avoid food poisoning/eat my food/behealthier). An alpha coefficient of 0.850 (M ¼ 17:14, SD ¼ 3:39) was reported.

Action self-efficacy was measured as the mean of three, seven-point (1 to 7) items (Iam confident that I am able to prepare food hygienically every meal even if I have to:make a detailed plan to have appropriate materials/rethink my behaviours andopinions regarding food hygiene/overcome my usual habit of not preparing foodhygienically). An alpha coefficient of 0.899 (M ¼ 16:74, SD ¼ 0:358) was reported.

Behavioural intention was assessed with the item, (I intend to prepare foodhygienically every meal for the next four weeks) measured on a seven-point scale(M ¼ 5:80, SD ¼ 1:36).

Past behaviour was measured by asking participants how often during the previousfour weeks, they had prepared food hygienically, measured from never to daily.

At time two participants reported on their food behaviours over the past four weeksas well as answering items related to HAPA variables including:

. Behaviour was measured by asking participants how many days over the pastfour weeks (28 days) they had prepared food hygienically (M ¼ 22:23,SD ¼ 7:84, range 4-28).

. Coping/maintenance self efficacy was measured as the mean of three items askinghow confident participants were that they could maintain preparing foodhygienically every meal even if they had to: make a detailed plan to haveappropriate materials/rethink their behaviours and opinions regarding foodhygiene/overcome their usual habit of not preparing food hygienically. Items werescored 1 to 7. An alpha coefficient of 0.894 (M ¼ 16:40, SD ¼ 5:04) was reported.

. Recovery self efficacy was measured as the mean of three, seven-point (1 to 7)items asking participants to report on their confidence in being able to return topreparing food hygienically even if they happened to give it up for threemonths/give it up for six months/give it up for 12 months. An alpha coefficient of0.955 ðM ¼ 16:40, SD ¼ 4:84) was reported.

. Planning was measured as the mean of five items, on a seven point scale, askingif participants had a plan for when, where, how, with whom and how often theywill prepare food hygienically. An alpha coefficient of 0.955 (M ¼ 21:66,SD ¼ 9:70) was reported.

Data analysisStructural equational modelling with Amos 6.0 using the maximum likelihood estimationwas used to test the HAPA models. Each model was evaluated by examining thecomparative fit index (CFI), the Tucker-Lewis index (TLI), the root-mean-square-error ofapproximation (RMSEA) and x2 divided by degrees of freedom (x2/df). A good model fitwas indicated by a high CFI or TLI (.0.90), a low RMSEA (,0.08) and a x2/df between 1and 2 (Kline, 2005). Three models were examined in the present study.

Model 1In the hypothesized model, action self efficacy, outcome expectancies, relative andabsolute risk were entered as predictors of intention, and intention as a predictor offood handling behaviour at time 2.

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Model 2The second model added the HAPA variables of planning, maintenance and recoveryself efficacy as predictors of behaviour. A path was also specified from intention toplanning as according to Schwarzer et al. (2003), planning can mediate the intention -behaviour link. In addition action self efficacy was entered as a predictor ofmaintenance and recovery self efficacy.

Model 3The last model investigated the effect of past behaviour, with past behaviour enteredas a predictor of both intention and behaviour.

ResultsIn this sample, 48.6 per cent of participants claimed they had prepared foodhygienically everyday for the last four weeks, 21.1 per cent reported five to six times aweek, 21.1 per cent reported three to four times a week, and 9.3 per cent reported thatthey rarely or never prepared food hygienically over the last four weeks. There were nodrop-outs in the present study probably due to the incentive of course credit tocomplete both questionnaires at time 1 and 2. Table I presents the intercorrelationsbetween motivational HAPA variables, intention at Time 1 and volitional HAPAvariables and behaviour at Time 2.

Model 1: prediction of intention and behaviourThe first model tested the prediction of intention using the motivational variables ofthe HAPA, as well as the prediction of behaviour by intention. The model was areasonable fit for the data (see Table II). The x2/df ratio was 2.0 and the overallsignificance was p ¼ 0:059 indicating that the fit of the model was correct (Kline, 2005).Action self-efficacy, outcome expectancies and risk awareness were significantpredictors of intention, however, relative risk was not. The HAPA variables explained30 per cent of the variance in intention. In turn, intention predicted 36 per cent of thevariance in behaviour at time 2 (Figure 1).

1 2 3 4 5 6 7 8 9

1. Risk awareness 1.002. Action self efficacy 0.31 * * 1.003. Outcome expectancies 0.40 * * 0.42 * * 1.004. Intention 0.27 * * 0.49 * * 0.42 * * 1.005. Recovery 0.29 * * 0.25 * * 0.42 * * 0.45 * * 1.006. Maintenance 0.29 * * 0.51 * * 0.41 * * 0.33 * * 0.57 * * 1.007. Planning 0.22 * 0.28 * * 0.48 * * 0.39 * * 0.42 * * 0.53 * * 1.008. Behaviour 0.136 0.24 * 0.26 * * 0.61 * * 0.38 * * 0.39 * * 0.35 * * 1.009. Past behaviour 0.17 0.26 * * 0.33 * * 0.63 * * 0.45 * * 0.42 * * 0.30 * * 0.62 * * 1.00

Notes: * p , 0.05; * * p , 0.01

Table I.Pearson’s product

correlations ofHAPA variables

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Model 2: prediction of intention and behaviour with planning and maintenance andrecovery self efficacyThe second model investigated the volitional components of the HAPA modelincluding planning, maintenance self-efficacy and recovery self-efficacy. Model 2 didnot fit the data as well as Model 1 (see Table II) and most of the fit statistics fell out ofthe range for an adequate fit. As seen in Figure 2, intention was a significant predictorof planning, however, planning was not a significant predictor of behaviour. Thereforeplanning did not mediate the effect between intention and behaviour. Neithermaintenance nor recovery self efficacy were significant predictors of behaviour.Intention and the three HAPA variables of planning, maintenance and recoveryself-efficacy accounted for 39 per cent of the variance in behaviour, an additional 4 percent compared to model 1.

Model 3: prediction of intention and behaviour with past behaviourIn the third model, past behaviour was also entered as a predictor of both intention andbehaviour. Past behaviour was the strongest predictor of both intention and behaviour.After inclusion of past behaviour, only action self-efficacy remained a significant

Fit indices Model 1 Model 2 Model 3

TLI 0.878 0.719 0.685CFI 0.965 0.888 0.885RMSEA 0.097 0.136 0.144x2; df 12.1; 6; 54.0; 18; .000 65.3; 20x2/df 2.02 3.00 3.27p 0.059 0.000 0.000

Notes: CFI ¼ comparative fit index; TLI ¼ Tucker-Lewis index; RMSEA ¼ root-mean-square-errorof approximation; x2/df ¼ x2 divided by degrees of freedom

Table II.Summary of model fitindices for each HAPAmodel

Figure 1.Model 1 – HAPAmotivational variables andintention predictingfour-week behaviour

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predictor of intention. Past behaviour was also a significant predictor of futurebehaviour but intention remained the strongest predictor. The model did not fit thedata as well as the previous two models (see Table II and Figure 3).

DiscussionThe results of the present study indicate that the HAPA is a useful model forpredicting safe food handling intention, but less useful for predicting behaviour. Thefirst hypothesis was supported in that the motivational HAPA variables of outcomeexpectancy, risk awareness and self-efficacy predicted 30 per cent of intention toprepare food hygienically. The analysis showed that action self-efficacy was thestrongest predictor of intention. Outcome expectancies and absolute risk were also

Figure 2.Model 2 – HAPAmotivational and

volitional variablespredicting four-week

behaviour

Figure 3.Model 3 – HAPAmotivational and

volitional variables andpast behaviour predicting

four-week behaviour

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significant, but relative risk was not. This compares with other research using theHAPA model where outcome expectancies and self efficacy but not risk perceptionpredicted intention in a longitudinal study of women’s breast self examination(Luszczynska and Schwarzer, 2003). In the current study absolute risk and relative riskwere considered separately because of the low correlation between these two factorsand risk severity was excluded. This may explain why most other studies have notfound risk to be predictive of intention and future research needs to consider thesecomponents separately. It may be that in the case of food handling, individuals maynot consider themselves at risk of getting food poisoning as they incorrectly believethey are already performing the correct behaviours. For instance a study by Jay et al.(1999a) using video surveillance in 40 home kitchens in Melbourne, found a significantdiscrepancy between the stated hygienic handling practices and the observed ones.Therefore relative risk may not have been a significant predictor in the current studyas individuals incorrectly assumed that they already practiced hygienic food handling.

Research in the USA (Roseman and Kurzynske, 2006) has found a relationshipbetween risk perception and safe food handling behaviours. This study showed thatindividuals with lower perceived risk practiced less healthy behaviours. This hasimplications for any interventions to change food handling behaviours with the aimbeing to increase people’s relative risk awareness through education on the saferalternatives to their existing food handling behaviour.

Research into hand hygiene practices by Clayton and Griffith (2008) found that byusing the TPB, 19 per cent of the variance in intention was explained. However incomparison a similar study on general food hygiene found that the TPB explained 66per cent of the variance in intention (Mullan and Wong, 2009), a much higherproportion than the current study using HAPA. It may be that this discrepancy relatesto the efficacy of the HAPA compared to the TPB. The HAPA does not include anormative component, which was found to be a significant predictor of intention toprepare food hygienically (Mullan and Wong, 2009). However, outcome expectancieswithin the HAPA are not dissimilar to the attitude component of the TPB (whichconsist of outcome expectancies £ behavioural evaluation) (Ajzen and Fishbein,1969); and the self efficacy component has been found to be comparable to externalperceived behavioural control (Ajzen, 2002a). In addition, Clayton and Griffith (2008)only looked at hand washing in a work setting whereas in the current study, foodhygiene behaviours were more inclusive. Future research comparing models is neededto clarify this finding.

The current findings do not support the second hypothesis that the volitionalcomponents of the HAPA model moderated the relationship between intention andbehaviour. When it came to predicting behaviour, intention was found to explain 36 percent of the variance in behaviour at the four week follow-up. The volitional variablesonly predicted an additional 3 per cent of variance in behaviour and their inclusiondecreased the overall model-data fit. There are a number of reasons why this may bethe case. In contrast to previous research using the HAPA, planning did not mediatethe relationship between intention and behaviour, or directly predict safe food handlingbehaviour. It has been argued that plans specifying when, where and how to performthe intended action, facilitates behaviour by activating automatization processes(Gollwitzer, 1999), and these have been found to be a strong predictor of breast selfexamination (Luszczynska and Schwarzer, 2003) and exercise behaviour (Sniehotta

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et al., 2005). In the present study, however, planning may not have been important as itis probable that most participants did not want to change or increase behaviours. Themajority of participants indicated that they believed that they were already preparedfood hygienically most days of the week, therefore they would have no intention tochange, nor need to create specific plans to initiate behaviour that they believed theywere already performing. Future research into the facilitating effects of planning in thisbehaviour may need to use a sample of individuals who wish to change. In addition,individuals may need to be aware of correct hygienic handling procedures to be able tomake detailed plans about behaviour.

Maintenance and recovery self efficacy were not significant predictors of behaviour,however, this may be due to the relatively short time-frame used in this study.Research using shorter time periods have found that maintenance and recovery haveless of an impact on behaviour as it is less likely that performance of regularbehaviours will lapse (Luszczynska, Mazurkiewicz, Ziegelmann and Schwarzer, 2007).A review investigating the volitional HAPA variables in seven different health studies(Schwarzer, 2008) which used longer timeframes (four to seven months) found thatplanning and recovery self efficacy mediated the relationship between intention andbehaviour for exercise, breast self examination and dental hygiene. Future studies mayneed to use a longer prospective time frame to assess if these components become moresalient in predicting food handling behaviour.

Therefore it appears that in this particular behaviour, personal motivation orintention has the strongest influence over future behaviour. This supports moretraditional social-cognition models such as the TPB, which claim that intention is themost immediate and important predictor of behaviour (Ajzen, 1991; Ajzen andFishbein, 1969).

Past behaviour was found to be a strong significant predictor of both intention andbehaviour. Frequency of past behaviour is often used as a measure of habit as when abehaviour is frequently performed in a stable context it becomes automatic (Ouelletteand Wood, 1998). Past behaviour has been found to be the most significant predictor ofbehaviour in a number of health behaviours including breakfast eating (Wong andMullan, 2009) and exercise (Rhodes and Courneya, 2003). The findings strengthens thenotion that hygienic food handling practices may be habitual and could also accountfor why the HAPA volitional variables were not significant. If a behaviour isperformed habitually, it does not need to be planned, maintained or recovered.Nevertheless, other researchers argue that past behaviour should not be equated tohabit, as just because a behaviour is performed frequently does not necessarily mean itis a habit (Ajzen, 2002b). In addition, other habitual behaviours have been successfullypredicted by the HAPA in previous studies. Schwarzer et al. (2007) found that planningand recovery self-efficacy accounted for 36 per cent of dental flossing and 42 per cent ofseat belt use. Therefore it cannot be the case that all habitual behaviours do not rely onthese post-intentional variables. Unlike the other behaviours, food preparation isunavoidable for most people; therefore participants may have found the measures ofvolitional variables irrelevant. Future research in determining the qualitativedifferences between habitual and non-habitual behaviours may be useful forbehavioural interventions.

It was examined if the inclusion of past behaviour improved the overall fit of thedata, however, the model including past behaviour fit the data less well than the

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previous two models. This may be due to the fact that past behaviour tends to maskthe effect of social cognitive variables as it encompasses a number of components (pastbehaviour can influence expectancies, self-efficacy, intentions, habit) so other measuresof habit may be more productively utilised in future research.

There are a number of limitations to the current study. The first relates to thedefinition of food handling behaviour, which was very broad so as to encompass themain areas of import in safe food handling: personal hygiene, avoidance ofcross-contamination, adequate cooking of foods, food storage, and avoidance of foodfrom unsafe sources (Medeiros et al., 2001). Therefore the definition used in the currentstudy did not look at any specific behaviour it covered all the general aspects of safefood handling. Future research may wish to consider each of these aspects separately.Second the use of a homogenous population of university undergraduates may makethe findings difficult to generalise. However, this group of people prepare foodregularly and research has shown that they are at high risk of food poisoning(Byrd-Bredbenner et al., 2007), and so are an important population to study. In additionthere was a lack of correspondence between the measures used. The measurement forHAPA variables and intention asked participants to think about their hygienic foodhandling at every meal, whereas past behaviour and behaviour only asked how manytimes per week or which days they prepared food hygienically. The assumption wasthat the majority of participants would make reference to their evening meals in theirresponses. In addition, HAPA only uses a single item measures for intention, and pastbehaviour was measured similarly, which could have lead to the high correlationbetween these variables and behaviour. Future research needs to consider which mealsare being investigated, and whether all food handling behaviours need to beconsidered. The questionnaire constructs were designed based on the generalguidelines by Schwarzer et al. (2003) and appeared to have fairly good reliability (asshown by the high internal consistency), however the validity of particularly thevolitional constructs could be questioned. For example, the measure of recoveryself-efficacy asked if they could recover if they happened to give up preparing foodhygienically. While people may occasionally stop preparing food due to holidays orillness, for example, it is unlikely that most people give up preparing food completely.However, many people will use shortcuts in food hygiene practices due to timeshortages or lack of cleaning products so it is likely people will have periods wherethey give up preparing food hygienically. However future research could consideralternative wordings of these questions to improve validity.

Finally, the reliance on self report may have affected the accuracy of the results. Asmentioned, some researchers have found that not all observed food handling behaviourcorrelates with self report ( Jay et al., 1999a). However, these discrepancies may be moreapparent than real. In an observational study by Clayton and Griffith (2008), there wasvery little relationship between participant’s self report of hand-washing and theiractual hand-washing behaviour but this relates to the definition they used in the studyof what hand-washing was i.e. 10 seconds with soap under hot running water.Participants may have been washing their hands, but not doing so appropriately.Therefore, there needs to be much clearer definitions used when comparingobservation with self report. For this reason and as the majority of research using theHAPA has used self report successfully, self report was determined to be appropriatein the current study (Schwarzer et al., 2007).

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One implication of the current research is that future interventions need to targetparticipant’s understanding of safe food handling behaviour. For example, withhand-washing, future research could target correct hand washing procedures ratherthan just general hand-washing. Further, until such a time as people considerthemselves at risk as a consequence of food hygiene behaviour, interventions to changethis behaviour will remain problematic. Participants in this study did not considerthemselves at risk compared to others and this could be the target of futureinterventions. The HAPA does not contain any reference to social norms as comparedto the TPB. Future studies could include elements of social comparison and socialnorms as research has found that behaviours that are performed publicly or for othersoften are influenced strongly by social norms (Quine and Rubin, 1997). Planning wasnot a significant predictor of behaviour in the current study, but past behaviour was.Future research could consider the interaction of habitual behaviour andimplementation intentions to investigate this further.

Interestingly, the present study contrasts with most of the research published usingthe HAPA (e.g. Schwarzer, 2008). The results demonstrate the utility of the HAPA inpredicting intention and behaviour, but the best model fit was the model that used themost sparing number of constructs. Although the addition of the volitional variables inmodel 2 slightly increased the proportion of variance explained in behaviour, the fitwas less than model 1 that used intention alone to predict behaviour. The volitionalHAPA variables were not found to moderate the relationship between intention andbehaviour either. Therefore at least in the case of food handling behaviour, increasingintentions to perform safe food handling may be sufficient to produce behaviouralchange.

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Byrd-Bredbenner, C., Maurer, J., Wheatley, V., Schaffner, D., Bruhn, C. and Blalock, L. (2007),“Food safety self-reported behaviors and cognitions of young adults: results of a nationalstudy”, Journal of Food Protection, Vol. 70 No. 8, pp. 1917-26.

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Corresponding authorBarbara.A. Mullan can be contacted at: Barbara@psych.usyd.edu.au

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