BJSP-Condom Meta-Analysis

Full text

British Journal
of
Social Psychology
(1998),
37,
231-250
0
1998
The British Psychological Society
Printed in Great Britain
231
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
et
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 requires

Intentions 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 (1 996) 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
et
a/.
(1
993) 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
(1
994) 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
et
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
et
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.
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
To
and 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.
There were several inclusion criteria for the review:

Table
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
Abraham, Sheeran,
Abrams
&
Spears
(1
996)
Boldero, Moore
&
Rosenthal
(1992)
Breakwell, Millward
&
Fife-Shaw
(1994)
Bryan, Aiken
&
West
(1996)
de Wit, van
Griensven,
Kok
Sandfort
(1993)
Fisher
(1984)
Random sample of
heterosexual
adolescents
(16-19
years)
Heterosexual
undergraduates
Random sample of
heterosexual
adolescents
(16-20
years)
Heterosexual college
students
Gay men attending
Municipal Health
Clinic in Amsterdam
(mean age
=
41.2
years)
Heterosexual
undergraduates
Intention,
1
item
(‘In
future,
I
intend
to use a condom if
I
have sex with
someone new
’;
5-point scale,
‘
strongly agree
’
to
‘
strongly
disagree’)
Intention“,
1
item (‘Strength of
intention’, 5-point scale, ‘very
determined not to use a condom’ to
‘very determined to use a condom’)
Expectation,
2
items, [‘7-point scale
(‘I
do not expect to have sex’
to
‘I
definitely will do this’ for two
instances of condom use) (always use
condoms/use condoms when not
certain about the other person’s
sexual history)
’1
Expectation,
4
items (e.g. ‘How
likely
is
it that
you
will use a
condom the next time you have
intercourse?
’,
response options not
reported), alpha
=
.77
Intention,
1
item
(‘Do
you intend
to
use a condom when you have
anal intercourse with a casual
partner in the future?’; 5-point
scale; ‘certainty not’
to
‘yes,
certainly
’)
Expectation,
1
item
(‘
unlikely-likely
I
will always use condoms’; number
of points on the scale not specified)
52
‘
New
’
partner Women
81
.15
Men
41 .33
6
Not specified Women
95 .31
Men
49 .40
52
Not specified
I
P
a.
6
Not specified
2:
Women
81 .69
2
26
4
I.
Casual
’
partner
Not
specified
Men
244 .21
Men
44
.55
P;,
CJ
4

N
w
00
Table
1.
(cont.)
Time
interval Respondent
Author(s) Sample Intention versus expectation (weeks) Type of partner sex
N
1
Fisher, Fisher
&
Convenience sample
recruited from gay
organizations
Rye (1995)”
of
gay men
Heterosexual
undergraduates
Heterosexual 9th
grade high school
pupils (adolescents)
Galligan
&
Terry Heterosexual
(1 993) undergraduates
Gallois, Kashima, Predominantly
Terry, McCamish, heterosexual
Timmins
&
convenience sample
Chauvin
(1
992) obtained through
student groups and
social networks
Intention,
1
item (‘If
I
have insertive 8 Not specified Men 29d .59
anal intercourse in the next
two
months, I intend to always use latex
condoms’; 5-point scale, ‘very
likely’
to
‘very unlikely’)
anal intercourse in the next two
Intention, 1 item (‘If I have receptive 8 Not specified
months,
I
intend
to
always use latex
condoms
’
;
5-point scale,
‘
very
likely’
to
‘very unlikely’)
Intention,
1
item (‘If
I
have sex
during the next two months,
I
intend
to
always use latex
condoms’; 5-point scale, ‘very
likely’
to
‘very unlikely’)
Intention,
1
item (‘If
I
have sex
during the next two months, I
intend to always use latex
condoms
’
;
5-point scale,
‘
very
likely’ to ‘very unlikely’)
8 Not specified
4 Notspecified
0
P
29
.ll
Men
P
Expectation,
1
item (‘Over the next 12 ‘Regular’ partnersc Mixed 50 .63
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’)
Intention, 1 item (‘Whether they 8 Notspecified
intended
to
use a condom during
their next sexual encounter’; 7-point
scale, ‘definitely not intend’
to
‘
definitely intend
’)
Mixed 144 .49

Gallois, Terry, Heterosexual Intention,
1
item (‘Whether they
Timmins, Kashima undergraduates intended to perform their sexual
&
McCamish (1994) activities with themselves or their
Morrison (1993)
Morrison, Rogers
Gillmore
&
Baker
(1995)
Reinecke, Schmidt
&
Ajten (1996)
Rye (1995)
Sanderson
&
Jemmott (1996)
Heterosexual teenagers
at sexually
transmitted diseases
(STD) clinics and
juvenile detention
centres
Heterosexual adult
STD clinic attenders
(mean age
=
27.7
years)
Random household
survey of adolescents
(predominantly
heterosexual)
Predominantly
heterosexual
undergraduates
Predominantly
heterosexual
undergraduates
partner using a condom on their
next sexual encounter’; 7-point
scale, ‘definitely do not intend’ to
‘definitely intend
’)
Expectation,
1
item (‘How likely are
you to use condoms with your
steady/casual partner(s) over the
next
3
months?’, ‘very unlikely’ to
‘very likely’)
Expectation,
1
item (‘How likely are
you
to
use condoms with your
steady/casual partner(s) over the
next
3
months?’; ‘very unlikely’ to
‘very likely’)
Intention, 3 items (‘I insist on using
a condom with new sexual partners
even if my partner does not want
to’; 3-point scale, ‘yes, true’, ‘don’t
know’, ‘no, false’)
Intention, no details
Expectation, 2 items (e.g. ‘How
likely is it that
you
will use
condoms if you decide
to
have sex
in the next 3 months?’; 5-point
scale,
‘
very unlikely
’
to
‘
very
likely’), alpha
=
.72
8
12
12
52
8
12
Not specified
Casual partner
Steady partner
Casual partner
Steady partner
Casual partner
Steady partner
Casual partner
Steady partner
‘New’ partners
Not specified
Not specified
Women 91 .60
Men 70 .53
Women”
Women
Men
Men
Women
Women
Men
Men
Mixed
Women
Mixed
43
140
32
77
38
163
52
105
172
56
85
.18
.49
.32
.45
.28
.31
.26
.49
.22
1.24,
.20, .22]’
.55
[.50,
.60]’
.66

Table
1.
(cont.)
Time
interval
Intention versus expectation (weeks)
Author(s)
Stanton, Li, Black,
Ricardo, Galbraith,
Feigelman
&
Kaljee
(1 996)
van der Velde,
Hooykaas
&
van der Pligt
(1
996)
Sample
Heterosexual young
people aged 9-15
years
in
public
housing
developments
clinic attenders (age
>
17 years)
Heterosexual
STD
~ ~~ ~ ~~ ~
Expectation,
1
item (‘How likely is it
that you will use a condom the next
time
you
have sex?’; %point scale,
‘likely’, ‘uncertain’, ‘unlikely’)
24
Intention,
1
item (Intend to use 16
condoms with private/prostitution 16
contacts; 5-point scale, ‘definitely
no’
to
‘definitely yes’)
Respondent
Type
of
partner sex
N
f
Not specified Mixed 24 .05
‘Private’ partners* Mixed 100 .35
\
partners
2
a\
‘
Prostitution
’
Mixed 147 .42
3
a
White,
Hogg
Terry
&
Heterosexual Intention,
3
items (e.g.
‘I
intend
to
4
Not specified Mixed 164
.80
P
s
(1994) university students use a condom every time I have sex
5
during the next month’; 7-point
scale,
’
extremely unlikely’
to
‘extremely likely’), alpha
=
.96
2.
3
0
Bolder0
et
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
to
respondents’ perceptions of their intentions immediately prior
to
intercourse. Bccause intention in action was measured at the same time
as
condom
use,
only the prior
intention measure is included here.
Indicates a mixed
sex
sample. Data were not disaggregated for men and women.
Three independent samples were studied.
Respondents having insertive or receptive anal intercourse are not independent. In order
to
compute the overall intention-condom use effect size, the average-weighted
correlation for
the
two
measures was employed and the largest
N
in the analysis (cf. Gerrard, Gibbons
&
Bushman,
1996).
‘Respondents with
‘casual’
and ‘steady’ partners are not independent. In order
to
compute the overall intention-condom use effect
size,
the average weighted correlation
for the
two
measures was employed and the largest
N
in
the
analysis (cf. Gerrard
et
uJ.,
1996).
’Three measures of condom use were employed.
’“Private’ partners refer
to
respondents who only had private partners. Samples for private and prostitution partners are therefore independent.
Two measures of intention were employed.

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
:
J(N,
x
rzo
JN,
Average
Z
value
=
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 have

Intentions
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.
Time 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 do 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
Men
Adolescents
Older samples
'
Short'
time interval
'Long'
time interval
Intention
Expectation
9
8
9
19
14
14
18
10
825
485
661
1871
1040
1492
1700
832
.44
.45
.25
.50
.59
.33
.44
.43
.38-.50
.37-.52
.17-.32
.46-.53
.54-.62
.2&.37
.40-.48
.37-.48
41.76*
11.55
15.41
119.23*
91.77*
42.92*
11 1.12*
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 adolescents

244
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
=
3.84,~
<
.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
et
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
.44
was 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+
=
.44
is
very similar
to
the average correlations obtained by Randall
&
Wolff
(1994)
(r+
=
.45)
and Sheppard
et
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
et
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 use

Intentions
and
condom
use
245
relationship. Previous research showed that men have greater power in heterosexual
relationships (Holland
et
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
et
al.,
1996;
Stanton
et
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
et
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 ‘measure of behavioural intention versus behavioural
expectation influenced the intention-condom use correlation. Contrary to Sheppard
et
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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