Do intentions predict condom use? Meta-analysis and examination of six moderator variables
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British Journal of Social Psychology (1998),37, 231-250 Printed in Great Britain 231
0 1998 The British Psychological Society
Do intentions predict condom use? Meta-
analysis and examination of six moderator
variables
Paschal Sheeran* and Sheina Orbell
Department of Pyhology, University of Shefield, Shefield S10 ZTN, UK
This study used meta-analysis to quantify the relationship between intentions and
behaviour in prospective studies of condom use. The effects of six moderator
variables were also examined : sexual orientation, gender, sample age, time interval,
intention versus expectation and condom use with ‘steady’ versus ‘casual’
partners. Literature searches revealed 28 hypotheses based on a total sample of 2532
which could be included in the review. Overall, there was a medium to strong
sample-weighted average correlation between intentions and condom use (r+=
.44), and this correlation was similar to the effect sizes obtained in previous reviews.
There were too few studies of gay men to permit meaningful comparison of effect
sizes between homosexual versus heterosexual samples. Gender and measurement
of intention did not moderate the intention-behaviour relationship. However,
shorter time intervals, older samples and condom use with ‘steady’ rather than
‘casual ’ partners were each associated with stronger correlations between intentions
and condom use. Factors which might explain the significant effects of moderator
variables are discussed and implications of the study for future research on
intention-behaviour consistency are outlined.
Unprotected penetrative sex is the primary transmission route for human
immunodeficiency virus (HIV), the agent which causes AIDS (acquired immuno-
deficiency syndrome). Condom use can prevent sexual transmission of HIV and is
more effective than reducing numbers of sexual partners (Reiss & Leik, 1989).
Although time trend analyses show that condom use has increased among both
heterosexuals (e.g. Catania, Stone, Binson & Dolcini, 1995; DeVroome, Paalman,
Dinglestad, Kolker & Sandfort, 1994; Robertson, 1995) and gay men (e.g. Flowers,
Sheeran, Smith & Beail, 1997; Hospers & Kok, 1995; Stall, Coates & Hoff, 1988),
the absolute level of condom use remains low. For example, a nationally
representative survey of people in the UK and France found that 40-60% of the
sexually active sample had never used a condom in the previous 12 months (Bajos e t
al., 1995).
Social psychology can contribute to reducing the spread of HIV/AIDS by
identifying psychological prerequisites of HIV-preventive behaviours such as
condom use (Abraham & Sheeran, 1993, 1994). There have been several applications
* Requests for reprints.232 Paschal Sbeeran and Sbeina Orbell
of social psychological models of behaviour to condom use. These accounts propose
that a person’s intention to use a condom is the most immediate, and important,
predictor of that behaviour. Given the complexity of sexual behaviour, however, it
remains an open question whether intentions do indeed predict future condom use.
The present study uses meta-analysis (e.g. Rosenthal, 1984) to address this question
by quantifying the extent to which behavioural intentions have been associated with
condom use in prospective studies to date.
Social pybological models of condom use
Perhaps the most important social psychological models of behaviour that have been
applied to condom use are the theory of reasoned action (Ajzen & Fishbein, 1980)
and the theory of planned behaviour (Ajzen, 1985, 1991). These models specify
different predictors of intention. According to the theory of reasoned action, people’s
intentions to perform a behaviour are predictable from their attitude towards the
behaviour, their positive or negative evaluation of their performing the behaviour
(e.g. ‘For me, using a condom would be good/bad’), and from their subjective norm,
their beliefs about what significant others think that they should do (e.g. ‘Most
people who are important to me think that I should/should not use a condom’). The
theory of planned behaviour posits an additional variable which influences intention
and which may also directly affect behaviour : perceived behavioural control (Ajzen &
Madden, 1986). Perceived behavioural control refers to the person’s perceptions of
the ease or difficulty of performing the behaviour (e.g. ‘Whether or not I use a
condom is entirely under/outside my control ’) and is closely related to the notion of
self-eflcacy (Bandura, 1992; see, however, Terry & O’Leary, 1995 for a study of the
distinctiveness of the two constructs).
While the theories of reasoned action and planned behaviour differ on the
proposed determinants of intention, both models regard forming an intention (e.g.
‘I intend using a condom the next time I have sex with someone new’) as the
prerequisite of behavioural performance. Behavioural intentions are presumed to
mediate the effects of variables extraneous to the models such as demographic
characteristics as well as attitudes and subjective norms (though not necessarily
perceived behavioural control). The intention construct therefore provides a
summary of the person’s motivational orientation towards performing a behaviour.
Ajzen (1991), for example, states that:
Intentions are assumed to capture the motivational factors that influence a behavior; they are
indicators of how hard people are willing to try, of how much effort they are planning to exert,
in order to perform the behavior (p. 181).
Previous meta-analytic reviews have shown that intentions are good predictors of
behaviours in a variety of domains. Across 88 studies, Sheppard, Hartwick &
Warshaw (1988) obtained an average correlation of .53 between intention and
behaviour, while Randall & Wolff’s (1994) review of 98 studies obtained an average
correlation of .45. While these findings are encouraging, there are reasons to suspect
that intentions may not predict condom use as well as intentions predict other
behaviours. Condom use is less an individual than a joint behaviour which requiresIntentions and condom use 233 the cooperation of a sexual partner (Kashima, Gallois & McCamish, 1993). Because sexual partners may have different intentions regarding condom use, intentions obtained from one partner may not be predictive of their joint behaviour. Condom use also requires resources (e.g. having a condom available) and opportunity (e.g. a prospective sexual partner). Both of these factors are thought to attenuate the relationship between intentions and behaviour (Liska, 1984). The first aim of the present study, therefore, is to systematically examine the extent to which behavioural intentions are associated with condom use among heterosexual and gay men using meta-analytical procedures. The second aim is to examine a number of potential moderators of the intentionxondom use relationship. Specifically, sample factors such as sexual orientation, gender and age, and methodological issues such as the time interval between measures of intention and behaviour and the measurement of both intention (intention versus expectation) and condom use (‘casual ’ versus ‘steady ’ partner) could each influence the relationship between intentions and condom use. Sexual orientation Since there are no theoretical grounds for supposing that the correlations between intentions and condom use should differ for gay versus heterosexual samples, no predictions were made regarding the influence of this variable. Gender Several researchers have suggested that men possess greater power in heterosexual relationships than women (Holland, Ramazaglou & Scott, 1990a; Holland, Ramazaglou, Scott, Sharpe & Thomson, 19906; Wight, 1992). This may mean that women are less able to translate their intentions to use a condom into action than men. Consistent with this view, Abraham, Sheeran, Abrams & Spears (1996) found that while intentions were significantly associated with condom use among men in their sample, the correlation between intention and condom use was not significant among women. Researchers have argued that sexual scripts (Gagnon & Simon, 1974) which provide implicit understandings of gender-appropriate roles and behaviours in sexual contexts accord men a more ‘agentic’ role in terms of initiating and coordinating sexual relations (Rose & Frieze, 1989) and that men’s sexual pleasure is privileged in such scripts (Nicolson, 1993). Women may also face emotional and/or physical coercion from men when they try to use a condom. Experiences of frequently being ‘pressured’ to engage in intercourse by men have been reported by women from a wide variety of backgrounds (Biglan, Noel, Ochs, Smolkowski & Metzler, 1995; Holland et al., 19906) and these reports of pressured intercourse are associated with condom non-use (Biglan et al., 1995). A related consideration is women’s self-efficacy to use condoms. Morrison, Rogers Gillmore & Baker (1995) point out that a woman depends more on a male partner’s cooperation than vice versa, since using a condom is a behaviour that he, rather than she, performs. This lack of direct control over the behaviour may have
234 Paschal Sbeeran and Sbeina Orbell
a negative impact upon women’s self-efficacy to use condoms (Kasen, Vaughan &
Walter, 1992). Since self-efficacy or perceived behavioural control can have a direct
impact upon behaviour which is not mediated by intention (Ajzen & Madden, 1986),
this might mean that women are less able to act upon their intentions to use a
condom than men.
Evidence also suggests that adolescents may be less able to translate their intentions
to use condoms into action compared to undergraduate and adult samples (Fisher,
Fisher & Rye, 1995). Two factors might be responsible. First, intentions to use
condoms may be very unstable among this group. For example, Stanton et al. (1996)
found that 58 per cent of their sample of 9-15-year-olds changed their intentions over
a six-month interval. Similarly, Reinecke, Schmidt & Ajzen (1996) found relatively
small correlations (.39 < rs < .46) between measures of intention taken one year
apart among a representative sample of German youth. This temporal inconsistency
is important because unstable intentions have been found to attenuate the relationship
between intentions and behavioural performance (Bagozzi & Yi, 1989; Doll 8c
Ajzen, 1992).
Second, age and sexual experience are positively correlated (Dunne, Donald,
Lucke, Nilsson, Ballard & Raphael, 1994). This means that older samples are likely
to have greater knowledge of sexual scripts and greater condom use self-efficacy and
may be better able to implement their intentions to use a condom. Kashima e t a/.
(1993) have shown that previous experience of condom use increases the consistency
between intentions and subsequent use. In their study, intenders with direct
experience of condom use were more likely to use a condom than intenders who had
no prior experience. Thus, intention stability and lack of direct experience may mean
that adolescents’ intentions are less predictive of condom use than the intentions of
older samples.
Time interval between measurements of intention and behaviour
Ajzen (1985) and Ajzen & Fishbein (1980) have argued that stronger relationships
between intention and behaviour will be obtained when the time interval between the
two measures is shorter than when it is longer. The time interval may influence the
intention-behaviour correlation because intentions may become unstable over time
or because unforeseen obstacles prevent action (Ajzen, 1985; Cote, McCullough &
Reilly, 1985). In a meta-analytic review of this issue, however, Randall & Wolff
(1994) found no significant relationship between the length of delay between
assessment of intention and behaviour and the strength of the intention-behaviour
correlation (r = - .06, n.s.).
Examination of the data employed in Randall & Wolffs (1994) study suggests
caution in accepting their conclusion that time interval does not affect intention-
behaviour relations. Randall & Wolff examined 98 hypotheses which were distributed
across five time intervals (less than one day, less than one week, less than one month,
less than one year, greater than one year) and seven ‘types of behaviour’Intentions and condom use 235 (food/beverage, sexual/reproductive, drug/alcohol, political/voting, leisure/ exercise, school/work/job/career, and ‘other behaviours’). This yields a 5 x 7 matrix of time interval by behaviour type. Inspection of the numbers of behaviours in each cell reveals that there are no data available for 10 of the cells while a further 8 cells contain just one datum. Thus, time interval and behaviour type would seem to be confounded. Randall & Wolff also analysed the impact of time interval within each behaviour type (excluding ‘other behaviours’) and found a significant association between time interval and the intention-behaviour correlation for just one of the six behaviour types-drugs/alcohol behaviours. Even within each behaviour type, however, there is at least one empty time interval cell for each of the six types of behaviour. Since the missing time interval cell varies for different types of behaviour, time interval and behaviour type would again seem to be confounded. We would argue that a stronger test of the effects of temporal contiguity on intention-behaviour relations would be provided by examining the effects of time interval in the context of a single behaviour than in the context of several different behaviours of the same ‘type’. Consistent with Azjen’s (1985) analysis, we hypothesize that longer time intervals will attenuate the strength of the intention-condom use relationship here. Behavioural intention versus behavioural expectation Sheppard et a/. (1988) and Warshaw & Davis (1985) have drawn attention to a distinction between behavioural intentions and behavioural expectations. Whereas intention refers to what one intends or plans to do (e.g. ‘ I intend using a condom the next time I have sexual intercourse 7, behavioural expectation refers to self- predictions about what one is likely to do (e.g. ‘How likely is it that you will use a condom the next time you have sexual intercourse?’). Measures of behavioural expectation are thought to encompass people’s perceptions of factors which may impede performance of a behaviour, such as situational constraints or lack of ability, and may therefore provide better predictors of behaviour than traditional measures of intention (Warshaw & Davis, 1985). Support for this view comes from Sheppard e t al.’s (1988) meta-analysis of the theory of reasoned action. They found that behavioural expectations were more strongly correlated with behaviour than behavioural intentions. Randall & Wolff (1994), on the other hand, found that intention versus expectation did not moderate the relationship between time interval and the intention-behaviour correlation. ‘ Casual’ versus ‘steah ’ partner Sheeran & Abraham (1994) showed that measures of condom use employed in most studies of HIV-preventive behaviour do not specify the type of partner (e.g. ‘new ’, ‘casual’ or ‘steady’ partner) with whom a condom was used. Research suggests, however, that intentions may be better predictors of condom use with ‘steady’ or ‘regular’ partners than condom use with ‘casual’ or ‘new’ partners. Morrison e t a/. (1995) argued that the theory of reasoned action should better predict condom use
236 Paschal Sheeran and Sheina Orbell
among steady partners than casual partners because the beliefs and attitudes of casual
partners are less well known to the actor, leading to ‘greater ambiguity in the
formation of, and follow-through on, intentions to use condoms’ (p. 654). Findings
appear to support this view. Morrison et af. (1995) and Galligan & Terry (1993) both
found that condom use was more predictable for steady partners than for casual
partners.
The present stub
In summary, the present study uses meta-analysis to determine the strength of the
relationship between intentions and condom use among heterosexual and gay
respondents. The effects of six potential moderators of this relationship are also
examined : (i) sexual orientation, (ii) gender, (iii) age, (iv) time interval, (v) intention
versus expectation and (vi) type of partner.
Method
Sample of studies
Several methods were used to generate the sample of studies: (u) computerized searches of social
scientific and medical databases (PsychLit, PsychINFO, Social Science Citation Index (BIDS), Medline,
Index Medicus, AIDSline, Dissertation Abstracts Online and the Conference Papers Index) from the
first report of HIV/AIDS (January 1981) to the time of writing (May 1997), (b) reference lists in each
article identified above were evaluated for inclusion, and (c) the authors of published articles were
contacted and requests were made for unpublished studies and studies in press.
There were several inclusion criteria for the review:
1. Studies had to include a measure of intention and a measure of self-reported condom use. Studies
which did not disaggregate condom use from other measures of HIV-preventive behaviour, such as
abstinence or non-penetrative sex, were excluded. While these studies are informative, as DiClemente
(1992) points out, composite measures of HIV-preventive behaviour mean that the effects of
predictors as they specifically relate to condom use cannot be isolated. Studies which did not
disaggregate condom use from other measures of contraception were also excluded for this reason.
2. A bivariate statistical relationship between intention and condom use had to be retrievable from
studies. Where studies did not include relevant statistics, the authors of the study were contacted and
requests were made for bivariate associations. Almost all authors provided these data (Boldero,
Moore & Rosenthal, 1992; Morrison, 1993; Morrison et ul., 1995; Reinecke etul., 1995; Rye, 1995;
White, Terry & Hogg, 1994).
3. Studies had to measure intention at time Toand measure condom use behaviour at some later time
T,. Studies which reported contemporaneous measures of intentions and behaviour were excluded
because cross-sectional designs do not permit causal inferences (Basen-Engquist, 1992; Basen-
Engquist & Parcel, 1992; Brown, DiClemente & Park, 1992; Cochran, Mays, Ciarletta, Caruso &
Mallon, 1992; Hernandez & DiClemente, 1992; Jemmott & Jemmott, 1991; Macey & Boldero,
1992; Schaalma, Kok & Peters, 1993; Trefie, Juggemann & Ross, 1992).
Using these inclusion criteria, a total of 28 tests of the association between intention and condom use
could be used in the review. Of these, just two hypotheses came from samples of gay men. The remainder
involved exclusively or predominantly heterosexual samples. The 18 studies which yielded the 28 effect
sizes are preceded by an asterisk in the reference list. These 18 studies include 2 unpublished papers
(yielding three hypotheses: Morrison, 1993; Rye, 1995).
Study characteristics were coded independently by the authors. Reliabilities were uniformly high,
ranging from 94 to 100 per cent. Disagreements were jointly resolved. Table 1 presents the
characteristics and effect sizes obtained from each study.1. Studies of the relationship between behavioural intentions and heterosexual condom use
Time
interval Respondent
Author(s) Sample Intention versus expectation (weeks) Type of partner sex N r
m, Sheeran, Random sample of Intention, 1 item (‘In future, I intend 52 ‘New ’ partner Women 81 .15
s & Spears heterosexual to use a condom if I have sex with Men 41 .33
adolescents (16-19 someone new ’; 5-point scale,
years) ‘strongly agree ’ to ‘strongly
disagree’)
, Moore & Heterosexual Intention“, 1 item (‘Strength of 6 Not specified Women 95 .31
thal (1992) undergraduates intention’, 5-point scale, ‘very Men 49 .40
determined not to use a condom’ to
‘very determined to use a condom’)
ell, Millward Random sample of Expectation, 2 items, [‘7-point scale 52 Not specified
e-Shaw (1994) heterosexual (‘I do not expect to have sex’ to ‘I
I
adolescents (16-20 definitely will do this’ for two P
years) instances of condom use) (always use a.
condoms/use condoms when not
certain about the other person’s
sexual history) ’1
2:
Aiken & Heterosexual college Expectation, 4 items (e.g. ‘How 6 Not specified Women 81 .69 2
(1996) students likely is it that you will use a
condom the next time you have
intercourse? ’, response options not
reported), alpha = .77
van Gay men attending Intention, 1 item (‘Do you intend 26 I. Casual ’ partner Men 244 .21
ven, Kok Municipal Health to use a condom when you have
rt (1993) Clinic in Amsterdam anal intercourse with a casual
(mean age = 41.2 partner in the future?’; 5-point
years) scale; ‘certainty not’ to ‘yes,
certainly ’)
1984) Heterosexual Expectation, 1 item (‘unlikely-likely 4 Not specified Men 44 .55
undergraduates I will always use condoms’; number P;,
CJ
of points on the scale not specified) 41. (cont.) N
w
00
Time
interval Respondent
uthor(s) Sample Intention versus expectation (weeks) Type of partner sex N 1
Fisher & Convenience sample Intention, 1 item (‘If I have insertive 8 Not specified Men 29d .59
995)” of gay men anal intercourse in the next two
recruited from gay months, I intend to always use latex
organizations condoms’; 5-point scale, ‘very
likely’ to ‘very unlikely’)
Intention, 1 item (‘If I have receptive 8 Not specified
anal intercourse in the next two
months, I intend to always use latex
condoms ’; 5-point scale, ‘very
likely’ to ‘very unlikely’)
Heterosexual Intention, 1 item (‘If I have sex 8 Not specified
undergraduates during the next two months, I
intend to always use latex
condoms’; 5-point scale, ‘very
likely’ to ‘very unlikely’)
Heterosexual 9th Intention, 1 item (‘If I have sex 4 Notspecified
grade high school during the next two months, I Men 29 .ll 0
pupils (adolescents) intend to always use latex PP
condoms ’; 5-point scale, ‘very
likely’ to ‘very unlikely’)
n & Terry Heterosexual Expectation, 1 item (‘Over the next 12 ‘Regular’ partnersc Mixed 50 .63
undergraduates three months I will definitely use 12 ‘Casual/new’ Mixed 27 .38
condoms with regular (casual/new) partners
partners’; 7-point scale, ‘very
unlikely’ to ‘very likely’)
, Kashima, Predominantly Intention, 1 item (‘Whether they 8 Notspecified Mixed 144 .49
McCamish, heterosexual intended to use a condom during
ins & convenience sample their next sexual encounter’; 7-point
in (1992) obtained through scale, ‘definitely not intend’ to
student groups and ‘definitely intend ’)
social networkss, Terry, Heterosexual Intention, 1 item (‘Whether they 8 Not specified Women 91 .60
ins, Kashima undergraduates intended to perform their sexual Men 70 .53
cCamish (1994) activities with themselves or their
partner using a condom on their
next sexual encounter’; 7-point
scale, ‘definitely do not intend’ to
‘definitely intend ’)
on (1993) Heterosexual teenagers Expectation, 1 item (‘How likely are 12 Casual partner Women” 43 .18
at sexually you to use condoms with your Steady partner Women 140 .49
transmitted diseases steady/casual partner(s) over the Casual partner Men 32 .32
(STD) clinics and next 3 months?’, ‘very unlikely’ to Steady partner Men 77 .45
juvenile detention ‘very likely’)
centres
on, Rogers Heterosexual adult Expectation, 1 item (‘How likely are 12 Casual partner Women 38 .28
ore & Baker STD clinic attenders you to use condoms with your Steady partner Women 163 .31
) (mean age = 27.7 steady/casual partner(s) over the Casual partner Men 52 .26
years) next 3 months?’; ‘very unlikely’ to Steady partner Men 105 .49
‘very likely’)
ke, Schmidt Random household Intention, 3 items (‘I insist on using 52 ‘New’ partners Mixed 172 .22 1.24,
ten (1996) survey of adolescents a condom with new sexual partners .20, .22]’
(predominantly even if my partner does not want
heterosexual) to’; 3-point scale, ‘yes, true’, ‘don’t
know’, ‘no, false’)
995) Predominantly Intention, no details 8 Not specified Women 56 .55 [.50,
heterosexual .60]’
undergraduates
son & Predominantly Expectation, 2 items (e.g. ‘How 12 Not specified Mixed 85 .66
ott (1996) heterosexual likely is it that you will use
undergraduates condoms if you decide to have sex
in the next 3 months?’; 5-point
scale, ‘very unlikely ’ to ‘very
likely’), alpha = .721. (cont.)
Time
interval Respondent
Author(s) Sample Intention versus expectation (weeks) Type of partner sex N f
~ ~~ ~ ~~ ~
, Li, Black, Heterosexual young Expectation, 1 item (‘How likely is it 24 Not specified Mixed 24 .05
o, Galbraith, people aged 9-15 that you will use a condom the next
lman & Kaljee years in public time you have sex?’; %point scale,
housing ‘likely’, ‘uncertain’, ‘unlikely’)
developments
r Velde, Heterosexual STD Intention, 1 item (Intend to use 16 ‘Private’ partners* Mixed 100 .35 \
kaas & clinic attenders (age condoms with private/prostitution 16 ‘Prostitution ’ Mixed 147 .42 3
er Pligt > 17 years) contacts; 5-point scale, ‘definitely partners 2
no’ to ‘definitely yes’) a\a
Terry & Heterosexual Intention, 3 items (e.g. ‘I intend to 4 Not specified Mixed 164 .80 P
(1994) university students use a condom every time I have sex 5
during the next month’; 7-point s
scale, extremely unlikely’ to
’ 2.
‘extremely likely’), alpha = .96 3
0
0 e t ul. (1992) employed two measures of intention to use a condom: a ‘prior intention’ measure and a measure of ‘intention in action’. The latter measure refers
ndents’ perceptions of their intentions immediately prior to intercourse. Bccause intention in action was measured at the same time as condom use, only the prior
n measure is included here.
es a mixed sex sample. Data were not disaggregated for men and women.
independent samples were studied.
ndents having insertive or receptive anal intercourse are not independent. In order to compute the overall intention-condom use effect size, the average-weighted
ion for the two measures was employed and the largest N in the analysis (cf. Gerrard, Gibbons & Bushman, 1996).
dents with ‘casual’and ‘steady’ partners are not independent. In order to compute the overall intention-condom use effect size, the average weighted correlation
two measures was employed and the largest N in the analysis (cf. Gerrard et uJ., 1996).
measures of condom use were employed.
easures of intention were employed.
e’ partners refer to respondents who only had private partners. Samples for private and prostitution partners are therefore independent.Intentions and condom use 241
Meta-anahtic strateg))
The effect size estimate employed here was a weighted average of the sample correlations, r+. r+
describes the direction and strength of the relationship between two variables with a range of - 1.0 to
+ 1.O. Computing the weighted average effect size requires a transformation of the correlation from
each relevant hypothesis into Fisher’s Z. The following formula is then employed :
Average Z value = J(N, x r z o
JN,
where rzt = the Fisher’s Z transformation of the correlation from each study i, N , = number of persons
in study i.
In this way correlations based on larger samples receive greater weight than those from smaller
samples. The average Z value is then backtransformed to give r+ (see Hedges & Olkin, 1985; Hunter,
Schmidt & Jackson, 1982).
Homogeneity analyses were conducted using the chi-square statistic (Hunter et a/., 1982) to determine
whether variation among the correlations was greater than chance. The degrees of freedom for the chi-
square test is A- 1, where k is the number of independent correlations. If chi-square is non-significant,
then the correlations are homogeneous and the average weighted effect size, r+s can be said to represent
the population effect size.
Transformations of other statistics (e.g. t , contingency tables) to statistic r and computation of
weighted average effect size and homogeneity statistics were conducted using Schwarzer’s (1988) Meta
computer program.
Multiple samples and multiple measures. Where studies included more than one sample and reported
separate statistical tests for each sample, then the correlation from each sample was used as the unit of
analysis. Where studies included more than one measure of condom use (e.g. condom use with ‘casual’
versus ‘steady’ partners) (Morrison, 1993; Morrison et a/., 1995), then the weighted average correlation
was computed within each independent sample of that study. The largest N in that sample was then
employed in computing the overall effect size (cf. Gerrard, Gibbons & Bushman, 1996). These
procedures retain the richness of the data without violating the independence assumption which
underlies the validity of meta-analytic procedures.
Results
The overall intention-condom use relationship
The sample size-weighted average correlation between intention and condom use
was r+ = .44 (95 per cent confidence interval = .41-.47, A = 28, N = 2532). In order
to ensure that this statistic was not biased by the preponderance of published studies,
the effect sizes for published versus unpublished studies were compared. The average
correlations for published studies (r+ = .44,k = 25, N = 2259) and unpublished
studies (r+ = .44, A = 3, N = 273) were identical. To determine the robustness of the
average correlation obtained here, we estimated the number of unpublished studies
containing null results which would be required to invalidate this study’s conclusion
that intention and condom use are significantly related ( p < .05). The ‘Fail-safe N’
(Rosenthal, 1984) was 217. Since there are unlikely to be so many unpublished studies
with null results which we were unable to locate, the r+ obtained can confidently be
viewed as significantly different from zero. While the average correlation is robust,
the homogeneity statistic shows considerable variation in the correlations reported
in previous studies (x2(21) = 161.65, p < .OOl). This heterogeneity encourages a
search for moderators.242 Paschal Sheeran and Sheina Orbell
Effects of moderator variables on the intention-condom use relationship
The first moderator variable we had hoped to examine was sexual orientation.
Unfortunately, since there were only two hypotheses involving gay men with a
combined sample size of N = 273, meaningful comparison of the effect sizes from
gay versus heterosexual samples was not possible. This view is supported by findings
showing that the Fail-safe N for the average correlation between intentions and
behaviour for gay men was 8. This value is considerably less than Rosenthal’s (1984)
+
guidelines for regarding a correlation as ‘robust’ (5k 10, or 20 studies in the present
case). More studies of gay men are required in order to determine whether sexual
orientation moderates the intention-condom use relationship.
We adopted two strategies to examine the effects of other moderators (Hunter &
Schmidt, 1990). First, correlations between r+ and each of the moderator variables,
gender, sample age, time interval and intention versus expectation were computed
(see Table 2). Second, we treated each moderator as a categorical variable. We
computed the effect size for each level of the moderator and used Fisher’s Z test for
the comparison of independent correlations to test the significance of the difference
between effect sizes. Table 3 presents the separate effect sizes obtained for men and
women, adolescents and older samples, shorter and longer time intervals, and
behavioural intention and behavioural expectation (analyses for condom use with a
‘steady’ versus a ‘casual’ partner were more complex and are described later).
Gender. We hypothesized that there would be a stronger correlation between
intention and condom use for (heterosexual) men than for (heterosexual) women.
However, the average effect sizes for men (r+ = .45) and women (r+ = .44)did not
differ significantly (Z = 0.22, n.s.) and gender and effect size were not associated
( r = .02, n.s.). Thus, men and women do not appear to differ in their capacity to
implement their intentions to use condoms.
Sample age. There was a significant correlation between sample age and the strength
of the intention-condom use relationship ( r = - .69, p < .OOl). Consistent with our
hypothesis, the effect size for adolescents (r+= .25) was significantly smaller than the
effect size for older samples (r+ = .50, Z = 6.48, p < .OOl). Adolescents were less
able to implement their intentions to use condoms than undergraduate and adult
samples.
Time interval. The correlation between the logarithmic transformation of time
interval and strength of the intention-condom use relationship was also significant
(r = - .59, p < .OOl). Longer delays between the assessment of intention and the
assessment of condom use were associated with attenuation of the intention-
behaviour correlation. Dividing time interval at the sample median (Mdn = 10 weeks),
the average correlation for ‘short’ intervals (r+ = .59) was significantly bigger than
the correlation for ‘long’ intervals (r+ = .33; Z = 8.28, p < .OOl).
It should be noted that sample age and time interval were negatively correlated
( r = - .58, p < .OOl), indicating that studies of adolescent samples have generally
employed longer time intervals while studies of undergraduates and adults haveIntentions and condom use 243
Table 2. Correlations between intention-condom use effect size and moderator
variables
1 2 3 4 5
1. Gender' 1.oo - .08 - .06 - .08 .02
2. Sample ageb 1.oo - .58* .13 .69*
3. T i m e interval' 1 .oo .02 - .59*
4. BI vs. BEd 1.oo .05
5. Intention-condom use r+ 1.oo
* p < .001.
Gender was coded men = 0, women = 1. Analyses for gender d o not include data for gay men. For
correlations involving gender, N = 1310. N = 2532 for all other correlations.
* Sample age was coded adolescents = 0, other = 1.
Time interval was computed as a logarithmic transformation (base 10 log) of the delay in assessment
between intention and condom use (in weeks). As Cohen & Cohen (1983) and Randall & Wolff (1994)
point out, a logarithmic transformation of time is more Likely than an untransformed variable to be
linearly related to the dependent variable.
Behavioural expectation (BE) was coded = 0, behavioural intention (BI) was coded = 1.
Table 3. Intention-condom use effect sizes obtained for each moderator variable
Moderator k' Nb r+c 95% CId Chi-square'
Women 9 825 .44 .38-.50 41.76*
Men 8 485 .45 .37-.52 11.55
Adolescents 9 661 .25 .17-.32 15.41
O l d e r samples 19 1871 .50 .46-.53 119.23*
' Short' time interval 14 1040 .59 .54-.62 91.77*
'Long' time interval 14 1492 .33 .2&.37 42.92*
Intention 18 1700 .44 .40-.48 111.12*
Expectation 10 832 .43 .37-.48 50.68*
* p < .001.
Number of correlations.
Sample size upon which sample-weighted average correlation is based.
Sample-weighted average correlation between intentions and condom use.
95 % confidence interval.
Chi-square test for homogeneity of sample correlations.
employed shorter intervals. To ensure that the effects of time interval were
independent of the effects of sample age, we compared the correlations between time
interval and r+ within the adolescent and older samples. There remained a significant
difference between longer and shorter time intervals for adolescents (r+ = .16 and
.36, respectively, Z = 2.72, p < .Ol) and for older samples (r+ = .37 and .60
respectively, Z = 6.57, p < .OOl).
In order to ensure that the effects of sample age were independent of the effects of
time interval, the effect sizes for sample age were compared within each level of time
interval. There was a significant difference between the effect sizes for adolescents244 Paschal Sbeeran and Sbeina Orbell
(r+ = .25) and older samples (r+ = .37) for time intervals greater than 10 weeks (Z =
2.51, p < .Ol). There was also a significant difference between adolescents and older
samples for shorter time intervals (r+ = .18 and .60, respectively, Z = 3 . 8 4 , ~< .Ol).
Longer time intervals and younger age, therefore, both attenuate the strength of the
correlation between behavioural intention and condom use.
Bebavioural intention versus behavioural expectation. The correlation between intention
versus expectation and r+ was not significant ( r = .05, n.s.) and when the effect sizes
for intention (r+ = .44)and expectation (r+ = .43) were compared, the difference was
not significant (Z = 0.29, n.s.). Measures of behavioural intention versus behavioural
expectation appeared to have similar average correlations with condom use.
‘ Casual’ versus ‘steah’ partner. Galligan & Terry (1993), Morrison (1993) and
Morrison et al. (1995) present intention-condom use correlations separately for
‘casual’ and ‘steady’ partners (see Table 1). We therefore computed separate effect
sizes for the two types of partner. Consistent with our hypothesis, the correlation
between intention and condom use with ‘steady’ partners seemed to be stronger
(r+ = .45, k = 5, N = 535, 95 % CI = .38-.51, x2 = 9.42, n.s.) than the correlation
with ‘casual’ partners (r+ = .27, k = 5, N = 192,95% CI = .13-.40, xa = 0.91, n.s.).
We cannot statistically compare these effect sizes because these ‘casual ’ and ‘steady ’
samples are not independent and because the Ns differ for the two correlations.
In a second analysis we combined the effect sizes for ‘steady’ partners from
Morrison (1993), Morrison et al. (1995) and Galligan & Terry (1993) and compared
the result with the combined effect sizes for ‘casual’/‘new’ partners from Abraham
et al. (1996), de Wit et al. (1993) and Reinecke e t al. (1996). The average correlation
between intention and condom use with ‘steady’ partners (r+ = .45) was significantly
bigger than the average correlation for ‘casual’ partners (r+ = .21, k = 4, N = 538,
95% CI = .13-.29, x2 = 0.99, n.s., Z = 4.44,p < .OOl).
Discussion
A sample size-weighted average correlation coefficient of .44was obtained between
intentions and condom use. Because condom use requires the cooperation of a sexual
partner, we had anticipated that the intention-behaviour effect size here would be
lower than that obtained in previous reviews. Contrary to expectations, r+ = .44is
very similar to the average correlations obtained by Randall & Wolff (1994) (r+ =
.45) and Sheppard e t al. (1988) (r+ = .53) in their meta-analyses of the theory of
reasoned action. Condom use is not, it seems, less predictable from intentions than
are other behaviours.
Literature searches revealed just two longitudinal studies of intentions and
condom use among gay men. This small sample precluded meaningful comparison
of effect sizes for gay versus heterosexual samples. It is, perhaps, worrying that
despite the large number of longitudinal studies of gay men (see Flowers e t al., 1997,
for review), the most proximate predictor of condom use-intentions to use
one-has rarely been measured. Clearly, this is a serious omission in studies to date,
which needs to be rectified in future research.
Our expectation was that gender would influence the intention-condom useIntentions and condom use 245
relationship. Previous research showed that men have greater power in heterosexual
relationships (Holland e t al., 1990a, b), which suggested that men might be better
able to implement their intentions to use condoms than women. We found that the
strength of the intention-condom use correlation did not differ for men and women,
however. Future research will need to examine whether variables characterized by
substantive gender differences in previous research such as sex roles, experiences of
sexual coercion, or condom use self-efficacy might directly influence the enactment
of intentions to use condoms.
We hypothesized that the intention-condom use relationship would be weaker
among adolescent samples compared to older samples based on research suggesting
that intentions to use condoms are very unstable among adolescents (Reinecke e t al.,
1996; Stanton e t al., 1996). This hypothesis was supported both by the overall
analyses and by analyses which controlled for the confounding effect for time
interval. The effect of sample age upon the intention-behaviour correlation does not
appear to have been examined in previous research. However, despite the significant
effect obtained here, it remains unclear why age moderated the relationship between
intentions and condom use. We have suggested that intention stability (Bagozzi &
Yi, 1989; Doll & Ajzen, 1992) or lack of direct experience with the behaviour
(Kashima e t al., 1993) might be responsible. Future research should directly address
these hypotheses taking account of the need to increase adolescents’ capacity to enact
their intentions to practise safer sex.
A previous meta-analysis of the effects of time interval on the intention-behaviour
correlation (Randall & Wolf€, 1994) concluded that the strength of the intention-
behaviour relationship does not diminish as the delay between the assessment of
intention and behaviour increases. We argued that there were insufficient data in
Randall & Wolff s (1994) meta-analysis to appropriately address this hypothesis and
that a stronger test would be afforded by determining the effects of time interval in
the context of a single behaviour. Time interval had a significant negative
relationship with the intention-condom use correlation in the present study, and this
effect remained significant even when sample age was controlled.
This finding supports the position repeatedly stressed by Fishbein and Ajzen (e.g.
Ajzen, 1985; Ajzen & Fishbein, 1980; Ajzen & Madden, 1986) that the measure of
intention should be as close as possible to the performance of the behaviour. This is
not to suggest that intentions are necessarily very poor predictors of behaviour over
longer time periods. Cohen (1992) suggests that a weighted average correlation of .10
should be characterized as ‘small’, a value of .30 as ‘medium’, and a value of .50 as
‘large ’. Our findings therefore indicate that the average correlation between
intention and behaviour over longer time intervals is ‘medium’ rather than small
(r+ = .32), while the average correlation over shorter time intervals is ‘large’ (r+ = .56).
We also examined whether a ‘measureof behavioural intention versus behavioural
expectation influenced the intention-condom use correlation. Contrary to Sheppard
e t al.’s (1988) meta-analysis, but consistent with Randall & Wolff s (1994) findings,
we found no difference between the average correlations between expectations and
condom use versus intentions and condom use. Our data indicate that the type of
measure of behavioural intention does not influence the predictive validity of that
measure.246 Paschal Sheeran and Sheina Orbell The final moderator of intention-condom use consistency examined here was condom use with ‘casual’l‘new ’ partners versus condom use with ‘steady’ partners. We hypothesized that the intention-condom use correlation would be stronger for ‘steady’ sexual partners than for ‘casual’ partners because the beliefs and attitudes of these partners are better known to actors and communication about contraceptive behaviour is more likely (Morrison et al., 1995). Although relatively few studies specified the type of partner with whom a condom was used, our predictions were supported. Condom use with a ‘steady’ partner was better predicted by intention than was condom use with a ‘casual’ partner. This finding underlines the need to specify type of sexual partner in future psychosocial studies of condom use (Sheeran & Abraham, 1994). Specifying the type of partner with whom a condom is used would contribute to research in this area by enabling researchers to identify the unique determinants of condom use in different types of relationship. This would enable more careful targeting of psychological variables in AIDS education campaigns. Possible criticisms of our meta-analysis should be addressed. The present research is based upon a relatively small number of hypotheses (k = 28) compared to previous reviews (Randall & WoH, 1994; Sheppard et aL, 1988). Mullen (1984) points out that the validity of meta-analysis does not depend upon the number of studies included in a review, but depends upon the extent to which the studies which have been included are representative of the population of studies on that topic. Since the present study involved an exhaustive literature search (including unpublished research), we believe that the findings obtained here are valid. Moreover, since the present study focused upon a single behaviour, inferences about the effects of moderator variables can be made with confidence. Our meta-analysis also has the difficulty that the measurement of condom use relies upon self-reports. Randall & Wolff (1994) have shown that there are stronger intention-behaviour correlations when self-report measures of behaviour are employed compared to more objective behaviour measures. This is a difficulty for research on sexual behaviour and for other behaviours which are sensitive, private or illegal. Catania, Gibson, Chitwood & Coates (1990) point out that there is no ‘gold standard’ for the measurement of condom use and that the employment of self- reports of behaviour is unavoidable. This does not represent a serious problem for our research, however, because test-retest reliability analyses and validation of self- reports against reports of sexual partners indicate that self-report measures of condom use do have satisfactory reliability and validity (Blake, Sharp & Temoshok, 1992; Catania et al., 1990; Sheeran & Abraham, 1994). In conclusion, this review finds that there is a medium to strong correlation between intentions to use condoms and condom use. The weighted average correlation obtained here does not differ substantively from the correlations found in previous meta-analyses of intention-behaviour relationships. While gender and measures of intention versus expectation did not moderate the intention-condom use relationship, shorter time intervals, older samples and condom use with a ‘steady’ rather than a ‘casual’ sexual partner were each associated with stronger correlations between intention and behaviour. Future research will need to examine variables such as intention stability and condom communication which may mediate the effects
Intentions and condom use 247
of time interval, age and types of sexual partner on the intention-condom use
relationship.
Acknowledgements
The authors would like to thank Jennifer Boldero, Diane Morrison, Jost Reinecke, Barbara J. Rye,
Catherine A. Sanderson and Katy White for their cooperation in providing additional data. We are
particularly grateful to Jennifer Boldero, Diane Morrison and Barbara J. Rye for providing unpublished
data. We would also like to thank Christine Galloway, Olivia Rickerby and Janette Watson of the
Department of Information Studies, University of Sheffield for conducting the computerized literature
search. We thank Penny Ditchburn for production of the tables.
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