828

British Journal of Health Psychology (2011), 16, 828–845C© 2011 The British Psychological Society

TheBritishPsychologicalSociety

www.wileyonlinelibrary.com

Alcohol, conscientiousness and event-levelcondom use

Gareth Hagger-Johnson1∗, Bridgette M. Bewick2, Mark Conner3,Daryl B. O’Connor3 and Darren Shickle2

1Department of Epidemiology and Public Health, University College London, UK2Leeds Institute of Health Sciences, University of Leeds, UK3Institute of Psychological Sciences, University of Leeds, UK

Objectives. Alcohol impairs judgement and could be causally implicated in sexualrisk taking. However, meta-analytic studies do not find an association between alcoholuse and unprotected sexual intercourse at the event level, where both behaviours referto the same point in time. Associations between personality traits and sexual risktaking have been replicated across several studies. Traits may be better conceptualizedas independent risk factors, where alcohol use mediates the association betweenpersonality and condom use. The objective of our study was to determine the directand indirect effects connecting big five personality traits with condom use, potentiallymediated through alcohol use during the most recent sexual encounter.

Design. A sample of community-dwelling adults (N = 190) completed measures ofbig five personality traits and a detailed assessment of event-level sexual behaviour andalcohol use.

Results. In regression model adjusting for known confounding factors, including oralcontraceptive use, partner type, and hazardous drinking patterns, one standard deviationincrease in conscientiousness was associated with a 1.14-fold increase in the odds ofusing a condom with most recent sexual partner (p = .04). Repeating the analysisusing zero-inflated regression for estimated blood alcohol concentration (eBAC) valuesrevealed an association between conscientiousness and eBAC (p = .002). There was noassociation between alcohol and condom use in either analysis.

Conclusions. The results illustrate that personality traits are strong independent riskfactors for sexual risk taking and eBAC values during sexual events, and both shouldbe incorporated into research designs. Future research should evaluate specific facetsof conscientiousness, and whether eBAC mediates the association between personalityand condom use in other samples. The possibility of tailoring interventions to personalitytraits is discussed.

∗Correspondence should be addressed to Gareth Hagger-Johnson, Department of Epidemiology and Public Health, UniversityCollege London, 1–19 Torrington Place, London WC1E 6BT, UK (e-mail: G.Hagger-Johnson@ucl.ac.uk).

DOI:10.1111/j.2044-8287.2011.02019.x

Alcohol, conscientiousness and condom use 829

The public health implications of sexual risk taking are considerable especially giventhe rising cost of treating sexually transmitted infections (STIs) and their consequences(Independent Advisory Group on Sexual Health and HIV, 2008). Researchers have notedrisk factors such as high rates of partner change (Fenton et al., 2005; Johnson et al.,2001; Wellings et al., 2001), low rates of STI testing/screening (Low et al., 2004), andthe existence of concurrent partners outside long-term relationships (Finer, Darroch,& Singh, 1999; Johnson et al., 2001). Many individuals are at increased risk of STIinfection, either from exposure to multiple sexual partners directly or indirectly via apartner’s exposure to other partners (Finer et al., 1999). Sexual risk taking is typicallydefined as having unprotected sexual intercourse with multiple casual partners (Hoyle,Fejfar, & Miller, 2000). In recent years, behavioural research has tended to focus on riskfactors for HIV transmission, but many studies emphasize other STIs and unintendedpregnancies (Hoyle et al., 2000). Condom use is an effective method of preventing manySTIs and unintended pregnancies and this explains why it has been the focus of manyinvestigations (e.g., Hagger-Johnson & Shickle, 2010; Jaccard, McDonald, Wan, Dittus, &Quinlan, 2002; Johnson et al., 2001; Trobst, 2002; Zimmerman et al., 2007). Given thatreducing sexual risk taking necessarily involves changing behaviour, it is important tounderstand the psychosocial determinants of behaviours such as condom use.

Alcohol impairs judgement and decision making (Leigh, 2002; Plant & Plant, 2006)leading researchers and policy makers to suggest that it could be causally implicatedin sexual risk taking (Babor et al., 2003; Department of Health, 2007; Plant & Plant,2006). Many researchers have adopted the ‘event level’ approach, whereby alcoholuse at a specific sexual encounter is recorded, in order to link the two variables atthe same point in time and strengthen the causal interpretation (Leigh & Stall, 1993).Participants are asked about an event, and asked whether alcohol was consumed at thatevent. The ‘event’ can refer to the most recent sexual event with any partner, the mostrecent event with a new partner, or to an event with one’s first ever sexual partner(Leigh, 2002). Some studies have found an association between alcohol and event-levelnon-use of condoms, although this association appears to be moderated by contextualfactors. For example, a recent study in Ireland found that alcohol was associated withnon-use of condoms only after controlling for partner type (main vs. casual; Cousins,McGee, & Layte, 2010). In a recent diary study, alcohol and partner type interactedwith gender. In females, alcohol was positively associated with unprotected sex withcasual partners and negatively associated with unprotected sex with steady partners. Inmen, alcohol was positively correlated with unprotected sex regardless of partner type(Kiene, Barta, Tennen, & Armeli, 2009). However, in two meta-analyses, the alcohol-unprotected sexual intercourse association was not replicated across the totality ofavailable evidence (Halpern Felsher, Millstein, & Ellen, 1996; Leigh, 2002). Alcohol isassociated with a reduction in the odds of condom use at the first sexual event (firstsexual partner; odds ratio (OR) = 0.54; 95% confidence interval (CI) 0.44–0.66), but notfor an individuals’ most recent partner (OR = 1.04; 95% CI 0.89–1.21) or most recentcasual partner (OR = 1.10; 95% CI 0.91–1.32; Leigh, 2002). In one study, a strongerassociation between alcohol and condom use with a first partner was found at higherlevels of age (Leigh, Schafer, & Temple, 1995). This association suggests that there may begenerational differences in the specificity of an effect. In a recent diary study, lower age,oral contraceptive use, partner type, and first partner status were independent predictorsof condom use (Leigh et al., 2008). Partner type replicates strongly across studies as apredictor of condom use (Cousins et al., 2010; Hagger-Johnson & Shickle, 2010), as doesoral contraceptive use (Leigh et al., 2008). It is therefore important to control for age,

830 Hagger-Johnson et al.

oral contraceptive use, and partner type. If these factors are related both to alcohol andto condom use, they could confound an association between alcohol and behaviour.Commentators have noted that personality traits and other individual differences areoften neglected factors that should be considered (Shuper et al., 2010; Weinhardt &Carey, 2000). Confounding occurs when a third variable is causally related to the riskfactor and the outcome of interest, but is not controlled for in the statistical model.Confounding can also arise when the risk factor is causally related to the third variable,and both are related to the outcome, yet these relationships are ignored. This lattersituation is more commonly referred to as mediation, which is not distinguishable fromconfounding statistically, but has conceptually distinct causal assumptions (MacKinnon,Krull, & Lockwood, 2000). Given that personality traits predict alcohol use, alcohol useis better conceptualized as a potential mediator, rather than a confounder.

Several associations between personality traits and sexual risk taking have beenreplicated across multiple studies. The most consistent predictor of sexual risk takingis sensation seeking. Sensation seeking is a trait that overlaps considerably withconscientiousness and some elements of extraversion in the comprehensive ‘big five’model of personality (neuroticism, extraversion, openness to experience, agreeableness,and conscientiousness; Bogg & Roberts, 2004; Zuckerman, Kuhlman, Joireman, Teta, &Kraft, 1993). Low conscientiousness shares variance with impulsive sensation seeking,and extraversion overlaps with need for activity and sociability (Zuckerman et al.,1993). Because it was a later addition to the big five, fewer studies have examinedconscientiousness as a risk factor for sexual risk taking. Several recent studies havehowever replicated findings in the expected direction; with lower conscientiousnessscores predicting increased sexual risk taking (Hagger-Johnson & Shickle, 2010; Schmitt,2004; Trobst, 2002). In men who have sex with men (MSM), there is some evidence thatthe association may be mediated by social-cognitive factors, such as perceived controlover HIV (Hagger-Johnson & Shickle, 2010). The contribution from extraversion is fairlyconsistently replicated, with higher extraversion scores associated with increased risk.This effect does however appear more robust in relation to multiple sexual partners perse rather than condom use specifically (Bourdage, Lee, Ashton, & Perry, 2007; Hoyleet al., 2000; Markey & Markey, 2007; Schmitt, 2004; Schmitt & Shackelford, 2008).Conscientiousness is also positively associated with at least 40 other health behaviours(Hagger-Johnson & Whiteman, 2007; Kewley & Vickers, 1994; O’Connor, Conner, Jones,McMillan, & Ferguson, 2009; O’Connor & O’Connor, 2004).

Relationships between personality, alcohol, and event-level sexual risk taking arelikely to be complex. Alcohol use at the event level could mediate relationships betweenpersonality traits and condom use (an indirect effect). Additionally, hazardous alcoholdrinking patterns might predict alcohol use during a sexual encounter. We sought toaddress some of the limitations of previous studies, by collecting detailed informationabout personality traits, hazardous alcohol drinking patterns, alcohol use prior to orduring the event, and the event itself. We used information provided about the number ofstandard drinks consumed, drinking times, and body mass index (BMI) to estimate bloodalcohol concentration (eBAC). Continuous data are more precise than those availablefrom binary-coded variables such as ‘use’ versus ‘non-use’, the latter reducing statisticalpower to detect an effect. It is also important to allow for direct effects that mightconnect traits with condom use, without an indirect or mediated contribution fromalcohol use. For these reasons, we utilized regression modelling with a mediator (eBAC),to test the significance of direct and indirect pathways. This modelling strategy allowsthe influence of risk factors and possible confounders to be controlled and modelled

Alcohol, conscientiousness and condom use 831

explicitly, while also testing putative causal pathways or mediated relationships. Giventhat none of the studies included in the most recent meta-analysis (Leigh, 2002) werebased in the UK, a secondary aim of the study was to provide novel comparative datafor the UK.

MethodsParticipants and procedureThe Wakefield Alcohol and Sexual Health study comprised a community sample of190 adults living in Wakefield, West Yorkshire (postcode WF), a region with very highlevels of socio-economic deprivation (90% of Super Output Areas being within the10% most deprived nationally). Participants were identified on the Prospect LocatorDatabase (www.selectabase.co.uk), comprising a sample of adults having WF postcodesin 2008–2009. The database was targeted to an estimated 18- to 25-year-old age band,having 70%–90% accuracy. We estimated the response rate to lie between 10% and30%, given that the typical response rate for district-wide surveys in Wakefield is 29%–45% (Warren Holroyd, personal communication; QA Research, 2009), which may reflectthe association between deprivation and non-response in postal surveys (Goodman &Gatward, 2008). Several features of the survey were expected to lower the responserate further, such as having no monetary incentive, having a large number of items,having no pre-contact with participants, and asking sensitive questions (Edwardset al., 2002). Low response rates are problematic if the non-responders are atypical inimportant ways (Coggon, Barker, & Rose, 2003). The prevalence of unprotected sexualintercourse (60%), however, was comparable to other studies (e.g., Cousins et al., 2010;Fontes & Roach, 2010; Leigh et al., 2008). Additionally, respondents had similar levelsof educational attainment to their local population, with 83.3% of respondents havingachieved at least five General Certificate of Secondary Education (GCSE) certificatesranging from A∗ to C, compared with the Wakefield average of approximately 70%(Association of Public Health Observatories, 2009). Females were over-represented inthe study, as shown in Table 1. Ethical approval for the study was provided by theNational Health Service (NHS) Leeds Central ethics committee.

Measures

Demographic variables. The questionnaire recorded participants’ age in years, sex,sexual orientation, and ethnic group. Based on frequency counts, sexual orientation wasrecoded into heterosexual (0) and non-heterosexual (1) and ethnic group was not useddue to low numbers of non-white British participants (2.2%). Six participants reportedbeing permanently sick or disabled (see below).

Estimated blood alcohol concentration (eBAC) at the event (mediator variable).Partic-ipants were asked to report the number of standard drinks they had consumed both be-fore and during the last sexual event (recoded separately), under separate headings ‘cansof beer’, ‘bottles of beer’, ‘glasses of wine’, ‘measures of spirits’. The total number of (US)standard drinks consumed was calculated from this information (i.e., 0.5 fl oz ethanol).Participants were asked ‘Over how many hours did you drink this amount? Answer to thenearest hour’, which was used to calculate eBAC using a validated (US) formula that takesinto account gender, weight, and drinking times (Read, Beattie, Chamberlain, & Merrill,

832 Hagger-Johnson et al.

Table 1. Descriptive statistics for variables

N (%) Minimum Maximum Available N∗

Unprotected sexual intercourse(vaginal/anal without condom)

114 (60.0%) 0 1 179

Male 53 (27.9%) 0 1 190Heterosexual orientation 172 (90.5%) 0 1 185Main partner during event 147 (77.4%) 0 1 182Oral contraceptive use 106 (55.8%) 0 1 190Long-term sick/disabled 6 (3.16%) 0 1 190Non-zero eBAC score 28 (14.07%) 0 1 178

Mean (SD)Age in years 23.56 (7.45) 18 78 148Height 169.97 (10.41) 149.86 202.00Weight 72.09 (17.47) 47.17 155.50Body Mass Index 25.29 (5.81) 16.18 53.69AUDIT score 8.38 (6.10) 0 40 187GCSE score (‘best eight’) 35.89 (13.21) 4 64 175NS-SEC occupational social

class2.71 (1.71) 1 5 170

Neuroticism 65.10 (16.91) 28 120 168Extraversion 95.26 (21.27) 33 195 173Openness to experience 88.24 (16.10) 25 156 168Agreeableness 122.18 (24.10) 25 220 172Conscientiousness 148.48 (23.81) 46 246 170Number of drinks

before/during event1.64 (4.16) 0 23 190

Recency of event 4.88 (1.76) 0 6 185eBAC score at event

(g/100 ml).18 (.14) .05 .53 178

∗Participants with available data, before imputation. eBAC = estimated blood alcohol concentration.

2008). This formula has been shown to most closely reflect breath samples (Hustad& Carey, 2005). Self-reported heights and weights were recorded in the questionnaire(Kuczmarski, Kuczmarski, & Najjar, 2001). A total of 28 (14.7%) participants had anon-zero eBAC score, with an additional 12 (6.3%) reported alcohol usage at theevent but missing at least one of the variable required to calculate the eBAC score(total = 40, 21.86%). For the model in which eBAC was recorded into a binarycovariate (see below), score were categorized into zero (coded ‘0’) and greater than zero(coded ‘1’, representing having any eBAC score, including those reporting alcohol usagebut missing). For the model in which eBAC was modelled as a zero-inflated distribution,scores were treated as continuous and modified to convert pounds to kilograms.

The big five personality traits. The ‘big five’ personality traits were measured using80 bipolar adjective pairs (e.g., ‘Retiring . . . . . . . . . Sociable’; McCrae & Costa, 1985)asking participants to indicate how strongly they identified with each adjective (on ascale from 1 to 9). Internal consistencies were high in the current study, for all fivescales (neuroticism � = .87, extraversion � = .87, openness to experience � = .82,agreeableness � = .93, conscientiousness � = .92). Personality traits were scored to

Alcohol, conscientiousness and condom use 833

have zero mean and unit standard deviation (SD) (z scores). The reliability and validityof the big five adjectives has been reported previously (e.g., McCrae & Costa, 1987).

Alcohol Usage Disorders Identification Test (Babor, Higgins-Biddle, Saunders, &Monteiro, 2001). The Alcohol Usage Disorders Identification Test (AUDIT) is a screeningtool for identification of hazardous drinking patterns. The AUDIT can also help identifyalcohol dependence and consequences of harmful alcohol use (Allen, Litten, Fertig, &Babor, 1997). In the current study, total AUDIT scores were used and these had highinternal consistency (� = .78). Previous studies have shown good 6-week test–reteststability of total AUDIT scores (e.g., at .88; Daeppen, Yersin, Landry, Pecoud, & Decrey,2000).

Socio-economic status (SES). Educational attainment was measured by taking the ‘besteight’ GCSE scores reported by each participant, ranging from grade U (coded 0) tograde A∗ (coded 8), or missing (Deary, Strand, Smith, & Fernandes, 2007). In the UK,GCSEs are typically sat at the age of 16, corresponding to US Grade 10. Occupationalsocial class was calculated using the National Statistics Socio-economic Classification (NS-SEC) self-coded method, derived from employment status information matched to theStandard Occupational Classification 2000 (SOC2000; Rose, Pevalin, & O’Reilly, 2005).Recoded scores were: semi-routine and routine occupations (1), lower supervisory andtechnical occupations (2), small employers and own account workers (3), intermediateoccupations (4), and managerial or professional occupations (5).

Unprotected intercourse (UI) with last partner (outcome variable). Participants wereasked ‘What happened during your last sexual encounter’ and were asked to tick any offour behavioural items (kissing, oral sex, vaginal sex, anal sex). Three response optionswere available for each behaviour (‘no’, ‘yes, with condom’, ‘yes, without condom’). Non-use of condoms for vaginal or anal sex was recoded into the event-level outcome variable,where ‘1’ indicates unprotected intercourse (UI) and ‘0’ indicates no UI. To control forthe recency of the event, a 6-point scale was provided that allowed participants to specifywhen the event occurred: ‘Never’ (coded ‘0’), ‘in the last 7 days’ (coded ‘1’) to ‘longerthan 5 years ago’ (coded ‘6’). It was important to allow participants to report when eventswere not consensual. Therefore, an additional item evaluated whether participants ‘hadto be persuaded’ (N = 10) or ‘were forced’ (N = 2, excluded from the analyses reportedbelow). Where values were discrepant across vaginal and anal intercourse, the highestvalue was taken. The item, ‘Did you use any form of contraception other than a condom?’was recoded into oral contraceptive use (‘1’) and non-use (‘0’).

ResultsDescriptive statistics for the variables included in the models described below are shownin Table 1. The zero-order correlation between event-level condom use and having a non-zero eBAC score was non-significant (r = −.05, p = .51), as was the correlation betweenevent-level condom use and eBAC scores (r = .12, p = .54). Multivariate analyseswere performed using Mplus version 6.1 (Muthen & Muthen, 1998–2010) using theweighted least squares with mean and variance adjustment (WLSMV) estimator, whichis appropriate for categorical mediators and outcome variables. With the exception of

834 Hagger-Johnson et al.

event level unprotected sexual

intercourse

eBAC > 0

AUDIT score

main partner

conscientiousness

oral contraceptive use

OR = 0.878 (95% CI .773 to .997)

OR = 1.12 (95% CI 1.05 to 1.21)

OR = 5.66 (95% CI 1.31 to 23.51)

OR = 0.17 (95% CI 0.07 to 0.42)

Figure 1. Path diagram illustrating regression of event-level unprotected intercourse (outcomevariable), having an estimated blood alcohol concentration (eBAC) > 0 (mediator); on personalitytraits and other covariates.Note. Coefficients from Table 2 have been converted into odds ratios and 95% confidence intervals.The very wide confidence interval for oral contraceptive use may have arisen because very few (N =7) participants not reporting usage had a non-zero eBAC score.

‘years of age’ (21.3% missing), no variables had more than 10.4% missing data (Table 1).Logistic regression analysis suggested that participants with higher levels of educationalattainment at GCSE were slightly less likely to withhold their age (OR = 0.946; 95% CI0.898–0.996). To reduce bias associated with case-wise deletion and because the datawere not missing completely at random (MCAR), multiple imputation across 10 datasetswas employed. The path diagram for the model is shown in Figure 1, where circles referto latent variables, squares refer to observed variables, significant pathways are shownwith solid arrows, and unstandardized beta weights describe the effect sizes for eachsignificant pathway. Personality traits and SES were centred to have zero mean and unitSD. Seven participants were excluded from the analysis, either because they reportedbeing permanently sick/disabled (none reported alcohol use and unprotected sexualintercourse with their most recent partner) or because consent was not provided. Theresults below are presented in three parts: (1) the regression of the binary outcomevariable (event-level unprotected sexual intercourse) on the hypothesized mediator(having any eBAC score greater than zero), latent class variable, and the predictorvariables; (2) a regression of the hypothesized mediator on the predictor variables; (3) asensitivity analysis, checking whether treating eBAC as a censored continuous variablechanges the results. Models were tested sequentially, beginning with a demographicsonly model (Model 1), a model containing personality traits and AUDIT score (Model 2),adjustment for socio-economic variables (Model 3), additional adjustment for event-levelvariables (Model 4), and a final version in which non-significant pathways were removed(Model 5). Parameter estimates, standard errors (SE), and p-values for each model areshown in Table 2 and the results for Model 4 correspond to the OR and 95% CI shownin Figure 1. OR are used to describe the association between predictor variables andmediators or outcomes, because eBAC and event-level UI are categorical variables.

1. Regression of the binary outcome variable (event-level unprotected sexualintercourse) on predictor variables and the hypothesized mediatorIn the demographics only model (Model 1), having an eBAC score greater than zero,age, gender, and sexual orientation were not associated with the outcome variable.Personality traits and AUDIT score were not associated with the outcome in Model2, and did not change the lack of association observed for demographic variables. Anon-significant trend towards conscientiousness being associated with the outcome

Alcohol, conscientiousness and condom use 835

Tabl

e2.

Res

ults

from

the

regr

essi

onof

even

t-le

velu

npro

tect

edse

xual

inte

rcou

rse

(cat

egor

ical

outc

ome

vari

able

)an

des

timat

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ood

alco

holc

once

ntra

tion

bein

ggr

eate

rth

anze

ro(c

ateg

oric

alm

edia

tor

vari

able

)on

pred

icto

rva

riab

les

N=

183a

Mod

el1:

Mod

el2:

Mod

el3:

Mod

el4:

Mod

el5:

Dem

ogra

phic

son

lyPe

rson

ality

trai

tsC

ontr

ollin

gfo

rso

cio-

Con

trol

ling

for

even

t-N

on-s

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tm

odel

and

AU

DIT

econ

omic

vari

able

sle

velv

aria

bles

path

way

sre

mov

edR2

=.0

5R2

=.1

3R2

=.1

4R2

=.1

7R2

=.1

3

Para

met

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timat

esB

SEp

BSE

pB

SEp

BSE

pB

SEp

Reg

ress

ion

ofev

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cted

sexu

alin

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ours

eon

med

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ran

dpr

edic

tor

vari

able

sA

nyeB

AC

(yes

)−.

02.0

6.7

0−.

02.0

5.7

1−.

02.0

5.6

5−.

02.0

4.6

8A

ge.0

1.0

1.4

3.0

1.0

1.2

3.0

1.0

1.4

3.0

1.0

1.4

0M

ale

(yes

)−.

09.1

2.4

8−.

08.1

0.4

2−.

08.1

0.4

2.0

0.1

0.9

9H

eter

osex

ualo

rien

tatio

n(y

es)

.21

.26

.41

.24

.18

.19

.24

.18

.18

.14

.15

.34

Neu

rotic

ism

−.05

.05

.25

−.06

.05

.22

−.07

.04

.14

Extr

aver

sion

.09

.05

.10

.08

.05

.14

.05

.05

.31

Ope

nnes

sto

expe

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ce.0

0.0

5.9

3.0

2.0

5.6

9.0

4.0

5.4

4A

gree

able

ness

.06

.05

.27

.04

.05

.37

.06

.05

.22

Con

scie

ntio

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15.0

8.0

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13.0

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14.0

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.33

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.25

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.03

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.36

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.26

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Rec

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.03

.58

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es)

.13

.12

.31

Con

tinue

d

836 Hagger-Johnson et al.

Tabl

e2.

Con

tinue

d

N=

183a

Mod

el1:

Mod

el2:

Mod

el3:

Mod

el4:

Mod

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bles

path

way

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=.0

7R2

=.2

6R2

=.2

2R2

=.6

8R2

=.6

4

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met

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timat

esB

SEp

BSE

pB

SEp

BSE

pB

SEp

Reg

ress

ion

ofm

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tor

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pred

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Age

−.03

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.32

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.41

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exua

lori

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tion

(yes

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9.5

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21.

07.9

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euro

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5.1

4.7

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−.10

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(yes

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hold

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for

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.26

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.26

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ldfo

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Alcohol, conscientiousness and condom use 837

was observed (p = .08) at this stage. Controlling for event-level variables (oral con-traceptive use, recency of the event, and partner type) resulted in the associationbetween conscientiousness and condom use becoming significant (Model 4). Oralcontraceptive use and casual partner type were also associated with non-zero eBACscores. Model 5 involved removing non-significant pathways from Model 4, one at atime starting with the lowest t-value. This produced a more parsimonious yet well-fitting model. In this final model, conscientiousness was significantly associated withunprotected sexual intercourse, OR = 0.878 (95% CI 0.773–0.997). Higher scores onconscientiousness were associated with a reduction in the odds of unprotected sex. AnOR of 0.88 corresponds to its inverse OR of 1.14 for using a condom per SD increasein conscientiousness. Therefore, controlling for other variables in the model, one SDincrease in conscientiousness was associated with a 1.14-fold increase in the odds of usinga condom with the most recent sexual partner. Having any eBAC score greater than zerowas not associated with event-level unprotected sex. The fit of this final model was excel-lent by several criteria (� 2 = 23.32, d.f. = 8, Comparative Fit Index (CFI) = .96, TuckerLewis Index (TLI) = 1.05, Weighted Root Mean Square Residual (WRMR) = .85, RootMean Square Error of Approximation (RMSEA) = .01) and is illustrated visually in Figure 1,where the coefficients from Table 2 have been converted into OR and 95% CI for ease ofinterpretation.

2. Regression of the hypothesized mediator (having an eBAC score greater thanzero) on predictor variablesHigher AUDIT scores were associated with having a non-zero eBAC score at the mostrecent event (OR = 1.12; 95% CI 1.05–1.21), consistent with hazardous drinking patternsincreasing the odds of drinking alcohol prior to or during a sexual encounter. Oralcontraceptive use was also significantly associated with eBAC status (OR = 5.66; 95% CI1.31–23.51). This suggests that participants or their partners who use oral contraceptivesare more likely to drink alcohol at the most recent sexual event. The wide confidenceintervals surrounding this estimate, however, may reflect the relatively small numbersof respondents reporting no oral contraceptive usage and having an eBAC score of zero(N = 7). If the event-level encounter was with a main partner, this greatly reduced theodds of having a non-zero eBAC score (OR = 0.17; 95% CI 0.07–0.42) suggesting thatalcohol is more likely to be present for event-level encounters with casual partners. AnOR of 0.17 corresponds to an OR of 5.88 for casual partner type, a large effect size,suggesting more than a five-fold increase in the odds of alcohol being used prior tocasual sexual encounters than with main partners. Finally, we tested for indirect effectsconnecting personality traits and AUDIT score to condom use, via the mediator (non-zero eBAC vs. zero eBAC). Testing for indirect effects is preferred over the traditionalapproach to testing for mediation sequentially, which can increase the probability of asignificant result by chance (MacKinnon, Fairchild, & Fritz, 2007). No indirect effectswere significant for any of the 10 datasets (all ps > .05), as expected, given that eBACstatus was not significantly associated with condom use.

3. Censored regression approach to eBAC scoresTreating eBAC as a categorical variable may result in loss of information and statisticalpower (Babyak, 2004), potentially missing significant associations involving alcohol usein the models described above. An alternative approach to modelling eBAC scores is

838 Hagger-Johnson et al.

event level unprotected sexual

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OR = 1.25 (95% CI 1.20 to 1.30)

OR = 0.73 (95% CI .55 to .98)

OR = 0.027 (95% CI .001 to .713)

Figure 2. Path diagram illustrating regression of event-level unprotected intercourse (outcomevariable), on eBAC values, treated as having a zero-inflated distribution, on personality traits andother covariates.Note. Coefficients for categorical outcome variables have been converted into odds ratios and 95%confidence intervals. Coefficients for continuous variables (eBAC score) are unstandardized betaweights. The very wide confidence interval for oral contraceptive is likely to have arisen becausevery few (N = 7) participants not reporting usage had a non-zero eBAC score.

zero-inflated regression modelling (McCarthy, Lynch, & Pedersen, 2007; Pedersen &McCarthy, 2008; Rotheram-Boris et al., 2009). This approach separates the distributionof eBAC scores into two parts: (1) having a zero eBAC score (coded ‘1’) versus havinga non-zero eBAC score (coded ‘0’); (2) eBAC scores treated as continuous, as part of anunderlying latent response variable. It is then possible to predict the odds of having a zeroeBAC score, alongside predicting eBAC scores for those participants who have a non-zero score. A zero-inflated regression model was therefore tested, including personalitytraits, AUDIT score, and event-level variables as predictor variables (Figure 2). Thesevariables were allowed to predict eBAC score, treated as continuous, at the same timeas predicting zero versus non-zero eBAC score.

The results from the zero-inflated regression approach (Table 3) produced a verysimilar association between conscientiousness and unprotected sex (OR = 0.86;95% CI 0.80–0.93), and between oral contraceptive use and unprotected sex (OR= 1.25; 95% CI 1.20–1.30). Among those with non-zero eBAC scores, extraversionwas associated with an increase in eBAC score, openness to experience and con-scientiousness with a decrease. These pathways were not apparent when eBACwas treated as a categorical variable in the models described above. Higher AUDITscores were associated with a reduction in the odds of having a zero eBAC score(OR = 0.73; 95% CI 0.55–0.98). Oral contraceptive use was also associated withzero eBAC status, the wide confidence interval likely reflecting the small number(N = 7) of people with zero eBAC scores not reporting oral contraceptive usage. The

Alcohol, conscientiousness and condom use 839

Table 3. Results from the regression of event-level unprotected sexual intercourse (categoricaloutcome variable) and estimated blood alcohol concentration (zero inflated) on predictor variables

B SE p

Regression of event-level unprotected sexual intercourse on mediator and predictor variableseBAC .03 .10 .79Neuroticism −.07 .04 .06Extraversion .03 .06 .62Openness to experience .02 .05 .66Agreeableness .08 .05 .11Conscientiousness −.13 .04 .00AUDIT −.01 .01 .13Oral contraceptive use .23 .07 .00Recency of event −.02 .02 .43Main partner (yes) .15 .11 .17

Regression of mediator (eBAC) on predictor variables, where eBAC values are non-zeroNeuroticism .08 .15 .61Extraversion .61 .25 .01Openness to experience −.43 .16 .01Agreeableness .12 .26 .65Conscientiousness −.69 .22 .00AUDIT .00 .03 .90Oral contraceptive use .13 .34 .71Recency of event −.09 .16 .59Main partner (yes) −.54 .42 .20

Regression of having zero eBAC values versus non-zero (reference category) on predictor variablesNeuroticism .05 .64 .94Extraversion 1.40 1.26 .27Openness to experience −1.66 1.33 .21Agreeableness .45 1.30 .73Conscientiousness −.76 1.31 .56AUDIT −.31 .15 .05Oral contraceptive use −3.61 1.67 .03Recency of event −.10 .47 .84Main partner (yes) 2.97 1.52 .05

Residual variancesEvent .19 .01 .00eBAC .35 .17 .05

results from zero-inflated regression suggest that treated eBAC scores as continuousdata may reveal significant associations between personality traits and eBAC that mightotherwise have been missed, if eBAC is categorized into zero and non-zero. Crucially,conscientiousness was associated both with eBAC score and with condom use. Althoughit is not possible to test for indirect effects for zero-inflated mediator variables inMplus, we tested whether eBAC might mediate the association observed betweenconscientiousness and event-level UI, among participants with a non-zero eBAC score(N = 40). The indirect effect was not statistically significant in any imputed dataset (allps > .05), which is unsurprising given that eBAC was not associated with condomuse. In summary, conscientiousness was independently associated with low eBAC

840 Hagger-Johnson et al.

and with condom use. Participants’ eBAC scores were not associated with condomuse, whether categorized or treated as continuous in zero-inflated regression. Thezero-inflated regression approach does not imply that the categorization approachto alcohol data is redundant, merely that there is more than one modelling strategyavailable.

DiscussionIn a sample of community-dwelling adults, event-level alcohol use was not associatedwith event-level unprotected sexual intercourse. Higher scores on the personality-traitconscientiousness were associated with a significant increase in the odds of usinga condom with the most recent sexual partner. Alcohol use did not mediate therelationship between personality traits and condom use. Although several variables wereassociated with alcohol drinking at the event (AUDIT score, oral contraceptive use, andcasual partner type), only low conscientiousness was a risk factor for unprotected sexin this study. Event-level alcohol use neither predicted unprotected sex, nor mediatedthe association from other psychosocial risk factors.

Strengths of the study include the level of detail collected on the substantivelyimportant variables. Data on the number of standard drinks consumed, drinking times,and BMI were available, permitting the calculation of eBAC, using validated formulae.Big five trait measures were available, which were internally consistent and previouslyvalidated. By adding personality traits into the model, we addressed one of the principallimitations of much alcohol and sexual behaviour research – the failure to control forconfounding by personality and individual differences (Weinhardt & Carey, 2000).We also adjusted for socio-economic status (SES), using two important indicators(educational attainment and occupational social class). Given the strong evidence thatpersonality traits and SES are associated with health behaviours and health outcomes,it is important that studies of alcohol and sexual risk taking consider them. Finally, thequestionnaires were fully anonymous, which is likely to increase reliability compared toalternatives such as face-to-face and telephone interviews (Schroder, Carey, & Vanable,2003). Diary methods represent a popular alternative or complement to questionnaires( Jaccard et al., 2002).

Diary methods have been useful in understanding how conscientiousness influencesother kinds of health behaviours (O’Connor et al., 2009). Given that studies havesuccessfully utilized diaries in studies of alcohol and condom use (Leigh et al., 2008);our approach taken here could be extended to include a sexual and alcohol-drinkingdiary recording multiple events and eBAC scores during those events. Other limitationsof the present study include the modest sample size available for the model (N =183), which reduces the statistical power to detect smaller effect sizes. The associationbetween conscientiousness and condom use was detected, although we clearly cannotrule out the possibility that a smaller association between eBAC and unprotected sexwould be detected in a larger study. The size and significance of the association betweenconscientiousness and UI is noteworthy. The non-significant association between alcoholand event-level condom use is consistent with meta-analytic summaries of the availableevidence base (e.g., Leigh, 2002). If there is an association between alcohol andunprotected sex at the event level, it is likely to be small. A second limitation isthat participants in the study may differ from those choosing not to participate onimportant characteristics, such as sexual experience, sexual attitudes and behaviours,and personality traits (Fenton, Johnson, McManus, & Erens, 2001). We found, however,

Alcohol, conscientiousness and condom use 841

that the prevalence of unprotected sex was similar to other studies. Bias resulting fromparticipants with higher levels of educational attainment, being more likely to participatein research, is often cited as being problematic (Nishiwaki, Clark, Morton, & Leon, 2005).We were able to demonstrate only slightly higher levels of educational attainment in ourstudy than would be expected in the population (a slightly higher mean, but with similarvariance). Although females were over-represented in our study, previous research hasshown that gender composition of samples does not influence the association betweenalcohol and condom use (Leigh, 2002). Third, the choice of mediator could haveproduced differences in results. The mediator was chosen on substantive theoreticalgrounds, but it would be feasible to hypothesize other mediating variables or moderatorsthat might connect personality traits with UI, or modify the risk associated with them.Different approaches to the condom variable might also produce differences in results.For example, condom use can be modelled using censored regression (Hershberger,Fisher, & Reynolds, 2005), multilevel modelling (Leigh et al., 2008), or as a latent traitrepresenting general propensity to have unprotected sex (Hagger-Johnson & Shickle,2010). A priority for future research is to see if findings are replicated, in larger and morerepresentative samples of the population.

There are important similarities and differences between our results and previousstudies. Our findings are consistent with the meta-analysis (Leigh, 2002), comprisingstudies from the United States, Norway, Canada, and France, where alcohol was notpredictive of sexual risk taking, other than with first partner. Our results are thereforesimilar to those observed elsewhere (c.f. Cousins et al., 2010). Our data add to thegrowing evidence base that low conscientiousness is a risk factor for sexual risk taking.The association between conscientiousness and condom use has now been replicatedseveral times (Hagger-Johnson & Shickle, 2010; Schmitt, 2004; Trobst, 2002), as hassensation seeking, a trait that shares variance with conscientiousness (Hoyle et al.,2000; Zimmerman et al., 2007). Similarly, several principal personality traits (particularlyneuroticism, extraversion, and low conscientiousness) are associated with alcohol use(Malouff, Thorsteinsson, Rooke, & Schutte, 2007), highlighting the need for mutualadjustment in multivariate models that attempt to predict condom use. The pattern ofresults we observed here was consistent with these prior reports, although there is aclear need to replicate the findings in a future study.

The predictors of alcohol use and eBAC concentrations provide important clues aboutwhich variables to study in future research. For example, AUDIT scores appear to predictthe decision to have a drink of any kind, but not the quantity and speed of drinking atthe event. This may be worth investigating in greater detail. The role of personality traitsagreeableness, openness to experience, and conscientiousness as predictors of alcoholuse during sex should be investigated. These traits did not predict having a non-zeroeBAC score, but were associated with the quantity and speed of drinking alcohol amongthose who did drink. This may suggest that personality traits, have differential effectson engaging and sustaining alcohol drinking during a specific sexual event; a hypothesisthat could be tested in future research.

Conscientiousness facets may be differentially related to health behaviours, includingsexual risk taking. Recent work by Roberts et al. (2005) has explored the underly-ing structure of trait conscientiousness. These authors conducted a factor analysisof conscientiousness-related scales drawn from seven major personality inventoriesand revealed six underlying factors: industriousness (e.g., achievement striving, self-efficacy, self-discipline), order (orderliness, organized, perfectionism), self-control (e.g.,cautiousness; impulse control), responsibility (e.g., responsibility; achievement via

842 Hagger-Johnson et al.

conformance, avoids trouble), traditionalism (e.g., comply with rules, customs, norms,etc.), and virtue (e.g., honesty, morality). Moreover, in their related meta-analysis of theleading behavioural contributors to the conscientiousness–mortality relationship, Boggand Roberts (2004) have made the case that the facets of responsibility and self-controlare the most important in relation to health behaviours with traditionalism being one ofthe best predictors of risky health behaviours (e.g., risky driving, drug use, violence).Therefore, future research might usefully examine how the facets of conscientiousnessmay differentially influence sexual risk taking. This will allow researchers to designmore effective, targeted, and tailored behaviour change interventions (e.g., Conrod,Castellanos, & Mackie, 2010).

Personality and individual differences are risk factors for unhealthy behaviours, andmay distort an apparent association between alcohol and sexual risk taking. Alcoholuse during a sexual event may be better conceptualized as a mediating variable, withpersonality traits and hazardous drinking patterns as predictor variables. This studydemonstrates that personality and individual differences are important determinantsof both sexual health behaviours and alcohol use prior to and during sexual events.Therefore, they are important variables that should be included explicitly in models thatdescribe how multiple health behaviours are connected. In addition to demographicvariables and personality traits, reviews have shown that constructs developed inthe social-cognitive tradition such as attitudes, behavioural intentions, and perceivedbehavioural control, can enhance predictive power for condom use (Albarracın, Johnson,Fishbein, & Muellerleile, 2001; Sheeran, Abraham, & Orbell, 1999). It is possible tocombine personality traits with social-cognitive variables, such as perceived control,within the same model (Conner & Abraham, 2001; Hagger-Johnson & Shickle, 2010).Understanding how dispositional and social-cognitive factors influence alcohol andsexual behaviour will further attempts to improve sexual health behaviours and mitigatenegative public health outcomes.

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Received 4 October 2010; revised version received 24 February 2011