Fulfilling desire: Evidence for negative feedback between men's
testosterone, sociosexual psychology, and sexual partner number
David A. Puts
a,b,
⁎, Lauramarie E. Pope
a
, Alexander K. Hill
a
, Rodrigo A. Cárdenas
c
,LisaL.M.Welling
a,1
,
John R. Wheatley
a
, S. Marc Breedlove
d
a
Department of Anthropology, Pennsylvania State University, University Park, PA 16802, USA
b
Center for Behavior, Brain, and Cognition, Pennsylvania State University, University Park, PA 16802, USA
c
Department of Psychology, Pennsylvania State University, University Park, PA 16802, USA
d
Neuroscience Program, Michigan State University, East Lansing, MI 48824, USA
abstractarticle info
Article history:
Received 1 September 2014
Revised 21 January 2015
Accepted 23 January 2015
Available online 30 January 2015
Keywords:
Androgen
Sex differences
Sexual behavior
Sociosexuality
Testosterone
Across human societies and many nonhuman animals, males have greater interest in uncommitted sex (more
unrestricted sociosexuality) than do females. Testosterone shows positive associations with male-typical socio-
sexual behavior in nonhuman animals. Yet, it remains unclear whether the human sex difference in sociosexual
psychology (attitudesand desires) is mediated by testosterone, whether any relationships between testosterone
and sociosexualitydiffer between men andwomen, and what the nature of these possiblerelationships might be.
In studies to resolve these questions, we examined relationships between salivary testosterone concentrations
and sociosexual psychology and behavior in men and women. We measured testosterone in all men in our sam-
ple, but only in those women taking oral contraception (OC-using women) in order to reduce the influence of
ovulatory cycle variation in ovarian hormone production. We found that OC-using women did not differ from
normally-ovulating women in sociosexual psychology or behavior, but that circulating testosterone mediated
the sex difference in human sociosexuality and predicted sociosexual psychology in men but not OC-using
women. Moreover, when sociosexual psychology was controlled, men's sociosexual behavior (number of sexual
partners) was negatively related to testosterone, suggesting that testosterone drives sociosexual psychology in
men and is inhibited when those desires are fulfilled. This more complex relationship between androgens and
male sexuality may reconcile some conflicting prior reports.
© 2014 Elsevier Inc. All rights reserved.
Introduction
Across societies, men report greater interest than women inuncom-
mitted sex—that is, less restricted sociosexuality (Charles and
Alexander, 2011; Edelstein et al., 2011; Lippa, 2009; Penke and
Asendorpf, 2008; Schmitt, 2005; Simpson and Gangestad, 1991), but
there is also a high degree of overlap between the sexes (Gangestad
and Simpson, 2000). Between- and within-sex variation in
sociosexuality may be mediated partly by testosterone (T). In nonhu-
man animals, androgens such as T mediate male-typical sociosexual be-
havior (Hart, 1974; Martin and Baum,1986; Money and Ehrhardt, 1971;
Xu et al., 2012; Yang and Shah, 2014; Zuloaga et al., 2008). Testosterone
has also been investigated in relation to human sociosexuality with
mixed results (Cashdan, 1995; Charles and Alexander, 2011; Edelstein
et al., 2011; McIntyre et al., 2006; van Anders et al., 2007b, 2009). One
reason for these discrepancies may be that participants' gender varies
across studies, and T may be differently related to sociosexuality in
men and women (see below).
Another source of variability may be different means of assessing
sociosexuality. Sociosexual behaviors likely depend not only on desires
and attitudes, but also on extrinsic factors such as opportunity
(Edelstein et al., 2011; McIntyre et al., 2006; Ostovich and Sabini,
2005). For such reasons, recent research suggests that sociosexual be-
haviors should be treated as distinct from desires and attitudes
(Jackson and Kirkpatrick, 2007; Lukaszewski et al., 2014; Ostovich and
Sabini, 2005; Penke and Asendorpf, 2008; Webster and Bryan, 2007).
Consequently, some authors have omitted behavioral items from the
Sociosexual Orientation Inventory (SOI; Simpson and Gangestad,
1991), producing a composite from the remaining items (Lukaszewski
et al., 2014; Ostovich and Sabini, 2005), while others have produced
separate composites of the behavioral items and the items related to so-
ciosexual attitudes and desires (Charles and Alexander, 2011; Webster
and Bryan, 2007). Using the latter approach, Charles and Alexander
(2011) found no significant relationships between T and behavioral
and attitudinal composites in either men or women. Other authors
Hormones and Behavior 70 (2015) 14–21
⁎Corresponding author.
E-mail address: dap27@psu.edu (D.A. Puts).
1
Currentaddress: Department of Psychology, OaklandUniversity,Rochester, MI 48309,
USA.
http://dx.doi.org/10.1016/j.yhbeh.2015.01.006
0018-506X/© 2014 Elsevier Inc. All rights reserved.
Contents lists available at ScienceDirect
Hormones and Behavior
journal homepage: www.elsevier.com/locate/yhbeh
have analyzed the SOI items separately. Adopting this approach, van
Anders et al. (2007b) found a relationship between women's T levels
and responses on two SOI items related to sociosexual behavior, but
no relationships between men's T and total SOI score or scores on any
individual items.
Penke and Asendorpf (2008) emphasized the heterogeneous nature
of the items on the original SOI (Simpson and Gangestad, 1991) and de-
vised a 9-item Revised Sociosexual Orientation Inventory (SOI-R) with
separate Attitude, Desire, and Behavior subscales comprising 3 items
each. Using the SOI-R, Edelstein et al. (2011) found overall significant
positive relationships between T and men's scores on the sociosexual
Attitude and Desire, but not Behavior, subscales, and no relationships
between T and sociosexuality subscales in their full sample of women.
However, after considering a potential moderating role of relationship
status, Edelstein et al. (2011) found that sociosexual Behavior was pos-
itively associated with testosteronelevels among partnered, butnot sin-
gle, women, and both Edelstein et al. (2011) and McIntyre et al. (2006)
found that T was positively linked to sociosexuality among partnered,
but not single, men. Other studies have found positive relationships be-
tween men's T and sociosexual behaviors, including numbers of past sex
partners (Bogaert and Fisher, 1995; Peters et al., 2008; Pollet et al.,
2011) and polygynous vs. monogamous marriage (Gray, 2003).
Alvergne et al. (2009) found a positive relationship between T and po-
lygyny in Senegalese men under 50 years of age and a negative relation-
ship in men over 50 years of age.
Associations between T, sociosexual attitudes and desires (hence-
forth, “sociosexual psychology”), and sociosexual behaviors are compli-
cated by thefact that causality is likelyto be bidirectional (Archer, 2006;
see also Mazur and Booth, 1998). Testosterone may lead to more unre-
stricted sociosexual psychology, which may then influence sociosexual
behaviors (e.g., Mantzoros et al., 1995), but sexual behavior can also in-
fluence T levels (Goldey and van Anders, 2014). For example, T levels
have been found to increase during sexual interest and arousal in men
(Hellhammer et al., 1985; Lopez et al., 2009; Roney et al., 2007; van
der Meij et al., 2008) and after sexual activity in both sexes (Dabbs
and Mohammed, 1992; van Anders et al., 2007a), although T levels
did not remain elevated the day after sexual activity in women (van
Anders et al., 2007a). Sakaguchi et al. (2007) found that Japanese men
who reported regular sexual activity had lower T levels. Sakaguchi
et al. hypothesized that frequent sexual behavior may exert negative
feedback on T levels. Indeed, within-subjects studies have reported
that periods of sexual abstinence are associated with increases in
men's T (Exton et al., 2001; Kraemer et al., 1976).
A functional perspective is likely to be useful in clarifying these com-
plex relationships. Growing evidence indicates that T mediates men's
allocation of effort directed toward competition for mates (Ellison,
2001). For example, men's T levels rise in the presence of potential
mates (Roney et al., 2007) and in anticipation of intrasexual competi-
tion, often remaining elevated in the winners (Booth et al., 1989;
Mazur and Lamb, 1980; Mazur et al., 1997; Oxford et al., 2010). Con-
versely, men's T levels decrease in committed romantic relationships
(Booth and Dabbs, 1993; Gangestad et al., 2010; Gettler et al., 2011c;
Gray, 2003; Gray et al., 2002) and after having children (Gettler et al.,
2011a,b; Gray et al., 2002, 2006; Kuzawa et al., 2009; Muller et al.,
2009; Storey et al., 2000). Such findings suggest that T levels rise in re-
sponse to opportunities to augment mating success and decline in re-
sponse to alternative fitness opportunities.
That men's T levels decline in committed romantic relationships and
after having children highlights the opportunity costs of increased T: the
resulting mating effort interferes with pair-bonding and parental care.
In addition, T carries with it several other potential costs, including in-
creased risk of injury resulting from aggressive and/or risky behaviors,
increased energy consumption, oxidative stress, and suppression of
some types of immune function (Archer, 2004, 2006, 2009; Bouman
et al., 2005; McIntyre et al., 2006; Wingfield et al., 2001). Testosterone
production should thus be regulated in relation to these fitness costs
and the benefits of increased mating success.However, what constitutes
optimal investment in matingdepends in part on individual men's abil-
ity to win mates and the presence of alternative targets of reproductive
effort, such as existing mates and offspring—variables that are reflected
in men's sociosexual psychology (Gangestad and Simpson, 2000;
Lukaszewski et al., 2014). Hence,if a man's level of uncommitted mating
is low relative to his sociosexual psychology, then this indicates subop-
timal investment in mating effort, and T levels should be elevated. Con-
versely, high sociosexual behavior relative to desires indicates excess
investment in mating effort, and T levels should be reduced.
In sum, T may motivate sociosexual behavior, but the realization of
these desires should tend to reduce T levels in order to mitigate the
costs of high T. Such negative feedback not only makes adaptive
sense; it could alsoexplain inconsistent past results. If T increases socio-
sexual behavior through promoting favorable attitudes and desires, but
sociosexual behavior in turn decreases T levels (Fig. 1), then the result
might be overall weakassociations between T and bothsociosexual psy-
chology and behavior. This hypothesis makes specific predictions re-
garding relationships between men's sociosexuality and T in cross-
sectional samples: 1) When sociosexual psychology is statistically held
constant, sociosexual behavior should negatively predict T, and
2) when sociosexual behavior is statistically held constant, sociosexual
psychology should positively predictT. In the present research, we test-
ed these predictions. If relationships between T and sociosexual behav-
ior are bidirectional in a feedback loop, then these relationships should
be apparent whether T is measured at the beginning or end of the inter-
val over which behavioral patterns are assessed. In Study 1, we assayed
T from saliva collected prior to the one-year interval over which socio-
sexual behavior (specifically, sex partner number) is assessed by the
SOI-R, and in Study 2, we obtained behavioral data for the year preced-
ing the time of saliva collection.
We also tested whether 3) T levels mediate the sex difference in so-
ciosexualpsychology, and whether 4) associations between T and socio-
sexual psychology differ by sex. Women do not face the same tradeoff
between mating effort and investment in mates and offspring that
men do. The payoffs of high mating effort are potentially much larger
for males, who can benefit reproductively from access to a large number
of partners, whereas women generally produce only one child at a time
regardless of theirnumber of mates. Therefore, factors that influence re-
productive strategies are expected to have a larger impact on the bal-
ance between mating effort and investment on the part of men
compared to women (Del Giudice and Belsky, 2010). While T may me-
diate the allocation of men's reproductive effort between mating andin-
vestment, we should expect that its effects would be less pronounced in
women.
Fig. 1. Hypothesized negative feedback—mediated by sociosexual psychology—between
testosterone and sociosexual behavior.
15D.A. Puts et al. / Hormonesand Behavior 70 (2015) 14–21
Study 1
Methods
Participants
Sixty-onemale (19.2 ± 1.4 y) and 126 female (19.3 ± 1.5 y; 52 tak-
ing oral contraception) students from a Midwestern United States uni-
versity participated in this institutional review board-approved study
as part of a larger study of human sex differences. Reported ethnicities
were 91.4% White, 3.6% Asian, 2.1% Hispanic or Latino, 1.2% Black or
African American, 0.6% American Indian or Alaska Native, and 1.2%
Other. Each participant attended three laboratory sessions as described
below.
Saliva collection
To minimize menstrual cycle-related hormonal changes, we exam-
ined the influence of T in women taking oral contraception (OC),
whose cyclic hormonal variation is suppressed. In previous research
(Edelstein et al., 2011; R. Edelstein, personal communication, May 31,
2013), hormonal contraception has not affected relationships between
testosterone and sociosexuality (but see Discussion section). We sched-
uled women taking OC and men for both a morning and an evening ses-
sion (the first two of three sessions), approximately one week apart, as
described in Puts et al. (2010). Men and OC-using women were ran-
domly allocated to attend their first session during the morning or eve-
ning, with their second session taking place at the other time of day.
Morning sessions began between 0820 h and 1000 h, and evening ses-
sions began between 1720 h and 1900 h. The difference between start
times of morning and evening sessions was 8.9 (±1.0) h. Normally-
cycling women were scheduled for two laboratory sessions between
1300 h and 1600 h according to self-reported menstrual cycle data to
coincide with the late follicular phase and the midluteal phase (see
Puts et al., 2013), but saliva collected during these sessions was not
assayed for T.
Participants were instructed not to eat, drink (except water),
smoke, chew gum, or brush their teeth for one hour before their ses-
sions. Participants rinsed their mouths with water before chewing a
piece of sugar-free Trident® gum to stimulate salivation. Some gums
may influence levels of T in saliva samples depending on brand, fla-
vor (Schultheiss, 2013; van Anders, 2010), and the specific antibod-
ies used in the hormonal assays. However, we used sugar-free
Trident® gum, which is inert in the salivary hormonal assays used
in the present study (Neuroendocrinology Assay Laboratory at the
University of Western Ontario, Canada, unpublished data). Partici-
pants collected approximately 9 mL of saliva in a sodium azide-
coated polystyrene tube. The tube was then capped, left at room
temperature for 18–24 h to allow mucins to settle, and frozen at
−20 °C until analysis.
Testosterone assays
We obtained salivary unbound testosterone concentrations through
radioimmunoassay. Following a double ether extraction, samples were
assayed in duplicate using a Coat-A-Count kit for total testosterone (Di-
agnostic Products, Los Angeles, CA), modified for saliva. Assays were
performed separately for men and women in two batches for each
sex. Sensitivity was 5–10 pg/mL, and the average intra-assay coefficient
of variation (CV) was 6.3%. Assay concentrations (log-transformed to
correct skew) correlated highly across duplicates (rsN.97, Psb.0001)
and sessions (r
95
=.91,Pb.0001) and showed expected decreases
from morning to afternoon (paired t-tests: men: t
57
= 7.5, Pb.0001;
women: t
36
= 5.6, Pb.0001; Table 1). Here, we are not interested in
morning or afternoon testosterone levels specifically, but rather in
between-participant differences in average hormonal concentrations
that may relate to sociosexual behavior and sociosexual psychology. Be-
cause the average of morning and afternoon testosterone concentra-
tions should provide a better estimate of each participant's average
level, and because testosterone concentrations correlated strongly
across duplicates and sessions, all concentrations were averaged for
each participant. Untransformed testosterone concentrations (Table 1)
compared well with previously published concentrations collected
across the day and assayed using this kit (Liening et al., 2010: men:
108.1 ± 33.9 pg/mL; OC-using women: 15.7 ± 5.9 pg/mL).
Sexuality assessment
Sexual orientation was assessed during the first session using the
sexual attraction and fantasy dimensions of the Kinsey Scale (Kinsey
et al., 1948), which is a 7-point scale used to identify the statement
that best describes the respondent's sexual feelings and fantasies at
present. For sexual attraction, possible responses ranged from “Iam
attracted to men only, never to women”to “I am attracted to women
only, never to men”, and for sexual fantasy, responses ranged from “al-
ways to a man, never a woman”to “always to a woman, never a man”.
Zero represents exclusive heterosexual orientation, and 6 r epresents ex-
clusive homosexual orientation. We excluded from further analysis one
female andtwo male participants whose responses on the sexual attrac-
tion or fantasy dimensions were N2. This exclusion did not alter the
results.
During a third and final session 1.19 (±0.28) years after their previ-
ous session,participants completed the Revised Sociosexual Orientation
Inventory (SOI-R) (Penke and Asendorpf,2008), a nine-item instrument
targeting sociosexual attitudes, desires and behaviors. For each item,
participants indicated their level of agreement on 9-point scales with la-
bels that varied by item (Penke and Asendorpf, 2008). Internal reliabil-
ity was high (Cronbach's αN.73) for each subscale, and for all subscales
combined. We distinguished between sociosexual behaviors and the
psychology that might motivate them (see, e.g., Jackson and
Kirkpatrick, 2007; Lukaszewski et al., 2014; Ostovich and Sabini, 2005;
Penke and Asendorpf, 2008; Webster and Bryan, 2007) by producing
Table 1
Descriptive statistics (mean ± SD) for raw (untransformed) data.
Study 1 Study 2
Women (non-OC) (N = 74) Women (OC) (N = 52) Men (N = 61) Men (N = 62)
AM T (pg/mL) –18.8 ± 11.2 (N = 43) 113.0 ± 44.9 (N = 57) 164.9 ± 62.4
PM T (pg/mL) –11.6 ± 7.1 (N = 45) 72.8 ± 33.5 (N = 58) –
SOI-R Attitude 3.1 ± 2.0 3.4 ± 1.6 4.8 ± 2.6 7.5 ± 1.4
SOI-R Desire 2.9 ± 1.5 2.9 ± 1.4 5.0 ± 1.7 6.5 ± 1.4
SOI-R Behavior 1.8 ± 1.0 1.9 ± 1.0 1.9 ± 1.2 3.9 ± 1.6
No. sex partners
a
2.1 ± 1.2 2.1 ± 0.7 2.2 ± 1.5 3.9 ± 1.7
SOI-R Total 2.6 ± 1.1 2.7 ± 1.0 3.9 ± 1.5 6.0 ± 1.1
Relationship status –––1.7 ± 0.7
Min. since waking –––135.0 ± 74.9
a
Response to Item 1 on the SOI-R.
16 D.A. Puts et al. / Hormonesand Behavior 70 (2015) 14–21
both a “sociosexual behavior”variable (the average response on the
three items comprisingthe Behavior subscale of the SOI-R) anda “socio-
sexual psychology”variable (the average of the Attitude and Desire
subscales of the SOI-R). Although scores on all three subscales intercor-
relate (Edelstein et al., 2011; Penke and Asendorpf, 2008), it is impor-
tant to distinguish between sociosexual behavior and sociosexual
psychology when exploring their relationships with T. This is because
both theory and prior empirical work suggest that T may positively
influence attitudes and desires,whereas behavior may negatively influ-
ence T. The distinct hypothesized causal relationships with T necessitate
treating sociosexual behavior and sociosexual psychology separately in
order to explore these relationships.
Results
Sociosexual attitudes, behaviors and desires intercorrelated signifi-
cantly (Table 2), and did not differ between women on and off hormon-
al contraception (t-tests: all PN.24; see also Charles and Alexander,
2011). As expected, testosterone (t
108
=−21.0, Pb.0001) and socio-
sexual psychology(t
182
=−7.8, Pb.0001) showed large sex differences
(Table 1). In a multiple regression model in which predictors were first
standardized (mean = 0, SD = 1) to reduce multicolinearity, testoster-
one was differently related to sociosexual psychology in men and OC-
using women (i.e., testosterone and sex significantly interacted), and
testosterone predicted sociosexual psychology, but sex did not
(Table 3; model F
3,109
= 16.46, R
2
= .31, Pb.0001). A bootstrap test
(number of resamples = 5000, P b.05; Preacher and Hayes, 2004)con-
firmed that the sex difference in sociosexual psychology was mediated
by testosterone.
In a separate regression model run on men, men with more
unrestricted sociosexual psychology had higher testosterone levels
(F
1,57
= 8.97, β= .37, t= 3.00, P= .004, see also Table 4). When
testosterone's relationship with sociosexual psychology was controlled,
sociosexual behaviors (log-transformed to correct skew) negatively pre-
dicted testosterone (multiple regression model: F
2,56
= 7.27, R
2
= .21,
P= .002; psychology: β=.54,t=3.81,Pb.001; behavior:
β=−.32, t=−2.22, P= .030). We then investigated whether any
particular behavioral item was driving the negative association with
testosterone by replacing sociosexual behavior with each individual be-
havioral item in the multiple regression model above. Behaviors that
most strongly negatively predict T should be those most representative
of mating success. On the SOI-R, number of sexual partners in the last
12 months (Item 1) best measures men's mating success (see,
e.g., Faurie et al., 2004; Hill et al., 2013; Hodges-Simeon et al., 2011),
whereas the other behavioral items do not measure mating success
per se. Items 1 (log-transformed to correct skew) and 3 (number of
sex partners in whom the participant was not interested in a long-
term committed relationship) were statistically significant predictors
(P= .011 and .043, respectively), but Item 2 (number of partners
with whom sex occurred only once) was not (P= .116). However,
Item 1 significantly (Pb.05) mediated the effect of Item 3, whereas
Item 3 did not significantly mediate the effect of Item 1 (bootstrap
test; bootstrap resamples = 5000; Preacher and Hayes, 2008). There-
fore, the negative relationship between sociosexual behavior and T
was attributable to the influence of SOI-R Item 1 (multiple regression
model: F
2,56
= 8.42, R
2
= .23, Pb.001; Table 5). After controlling for
partner number, the positive relationship between T and sociosexual
psychology was even more evident (Fig. 2).
In separate regression models run on OC-using women, sociosexual
psychology was unrelated to testosterone (F
1,49
= .12, β=.05,t=.35,
P= .727). Sociosexual behaviors (log-transformed to correct skew)
were also unrelated to testosterone alone (F
1,49
=.11,β=.05,t=
.33, P= .746) and when controlling for sociosexual psychology (multi-
ple regression model: F
2,49
= .14, R
2
b.01, P= .929; psychology: β=
.04, t=.21,P=.837;behavior:β=.03,t= .16, P= .873).
Controlling for session order (morning or evening session first) did
not influence any of the above results, and session order was not a sig-
nificant predictor when added to any model.
Study 2
We attempted to replicate the results from men in Study 1 in a new
sample, this time including time since waking, which negatively pre-
dicts T levels (Liening et al., 2010) and relationship status,which also in-
fluences men's T levels (Booth and Dabbs, 1993; Burnham et al., 2003;
Gettler et al., 2011c; Gray, 2003; Gray et al., 2002)andhasbeenfound
to interact with sociosexuality in predicting men's T levels (Edelstein
et al., 2011; McIntyre et al., 2006). We also collected data on men's
peer- and self-rated social status (attractiveness, leadership, domi-
nance, likeability), using these data to explore the mode by which T
might relate to men's sociosexual behavior.
Methods
Participants
In order to obtain evaluations by familiar peers, we recruited mem-
bers of two fraternities (N= 63, mean age = 19.9, SD = 1.2) and two
sororities (N= 72, mean age = 19.4, SD = 1.0) from a large university
in the northeastern United States. Each fraternity was socially affiliated
with one of thesororities, with members regularly attending joint social
functions. Male participants were paid US$15, and female participants
Table 2
Intercorrelations between subscales of the SOI-R.
Study 1 Study 2
Women (N = 126) Men (N = 61) Men (N = 62)
Attitude–Behavior
a
.56⁎⁎ .46⁎⁎ .29⁎
Attitude–Desire .18⁎.52⁎⁎ .36⁎⁎
Behavior
a
–Desire .18⁎.51⁎⁎ .28⁎
a
Log-transformed in Study 1.
⁎Pb.05.
⁎⁎ Pb.01.
Table 3
Multiple regression predicting sociosexual psychology in Study 1 participants.
βtp
Testosterone .53 2.71 .008
Sex −.05 −.11 .916
Testosterone × Sex .24 2.89 .005
Table 4
Zero-order correlations with log-transformed testosterone concentrations.
Study 1 Study 2
Women (N= 51) Men (N= 59) Men (N= 62)
SOI-R Attitude −.03 .33⁎.21
+
SOI-R Desire .12 .31⁎.16
SOI-R Attitude + Desire .05 .37⁎⁎ .23
+
SOI-R Behavior
a
.05 −.02 −.01
Number of sex partners
a
.01 −.06 −.16
SOI-R Total .06 .29⁎.16
Relationship status ––−.29⁎
Min. since waking
b
––−.22
+
a
Log-transformed in Study 1.
b
N=61.
+
Pb.1.
⁎Pb.05.
⁎⁎ Pb.01.
17D.A. Puts et al. / Hormonesand Behavior 70 (2015) 14–21
were paid US$10. All methods were approved by the university's insti-
tutional review board.
Procedures
We collected data at male participants' residence (fraternity) houses
using a series of stations. The first station acquired informed consent;
other stations collected saliva, photographs,answers to online question-
naires, and data not used in this study (see Doll et al., 2014; Hill et al.,
2013). Each male participant provided two saliva samples via passive
drool 19.2 ± 6.9 min apart between 900 h and 1330 h. We aliquotted
0.5 mL from each sample into a cryovial and froze it at −20 °C until hor-
mone analysis. Participants provided facial photographs and completed
online questionnaires between saliva collections. Online instruments
included the SOI-R (items answered on 9-point scales, as in study
1) and questions on time since waking, sexual attraction and fantasy di-
mensionsof the Kinsey sexual orientation questionnaire (as in study 1),
and current relationship status (options “not seeing anyone”[N=27],
“casual relationship”[N=27],and“serious relationship”[N=8]
coded with increasing commitment level as 0–2, respectively). With
the exception of one participant who reported 1 on the sexual attraction
dimension, all male participants reported exclusive heterosexuality (0
on both sexual attraction and fantasy). On the SOI-R, internal reliabil-
ities were high (Cronbach's αN.79 for each subscale, and for all sub-
scales combined). Male participants were also asked what percentage
of men they could defeat in a physical fight, how good a leader they
were, and how attractive they were. All rating tasks used an 11-point
Likert scale (0–10) except for the question “What percentage of men
your age could you beat in a physical fight?”for which choices were
listed from 0% to 100% in increments of 10%.
Ratings
One week after the initial data collection, we returned to the resi-
dences, at which time male participants were sequentially shown facial
photographs of all other male participants from their fraternity and
asked what percentage of men each could beat in a physical fight,
how good a leader he was, and how much they liked him. The same
scales used for self-assessments were used for assessment of other
male participants. Order of rating tasks and presentation order of stim-
uli were randomized. For each participant, all of the stimuli for a partic-
ular dimension were rated before moving on to the next dimension. As
before, participants were seated privately.
Female participants were brought individually into the lab, sequen-
tially shown facial photographs of all male participants from their affil-
iated fraternity on a computer, and asked to rate on a 10-point Likert
scale how much they liked each man and how attractive each was for
a“short-term, purely sexual relationship, such as a one night stand”
and for a “long-term, committed relationship, such as marriage.”Rating
task and stimulus presentation order were randomized as above.
Interclass correlations were computed to determine inter-rater reli-
ability. For each male participant, some data weremissing because male
participants rated other members, but not themselves.Thus, to compute
inter-rater reliability in a way not likely to bias existing ratings, we im-
puted a random value from the pool of observed ratings for each miss-
ing value. Average two-way agreement interclass correlations were
computed for each variable for each fraternity, as members of one fra-
ternity did not rate members of the other fraternity. Six female partici-
pants' ratings were removed because they were missing more than 16
of 34 trials. All interclass correlations were high (N0.8).
Testosterone assays
We assessed salivary unbound testosterone concentrations through
enzyme immunoassay (EIA). Samples were assayed in duplicate using
Enzyme Immunoassay Kits (Salimetrics, State College, PA). Sensitivity
was b1.0 pg/mL, and the intra-assay CV was 2.5%. Duplicate assay con-
centrations correlated r
64
=.97,Pb.0001 and consequently were aver-
aged. Untransformed testosterone concentrations (Table 1) compared
well with previously published concentrations assayed using this kit
(Josephs et al., 2006; Mehta and Josephs, 2006; Newman et al., 2005).
Results
In a multiple regression predicting log-transformed testosterone
(F
5,55
= 3.83, R
2
= .26, Pb.005), testosterone was again positively relat-
ed to sociosexual psychology and negatively related to sex partner num-
ber (SOI-R Item 1; Table 6). In this model, sociosexual psychology and
relationship status were first standardized to reduce multicolinearity,
and then their interaction was calculated. Testosterone was lower in
committed relationships and when measured later in relation to the
time of waking, but sociosexual psychology and relationship status did
not significantly interact. In separate multiple regression models replac-
ing Item 1 in the model above with Items 2 and 3 (the remaining items
on the behavior subscale), neither Item 2 nor Item 3 was a significant
predictor (both PN.5), and thus neither significantly mediated the effect
Table 5
Multiple regression predictingtestosterone in Study 1 male participants.
βtP
No. sex partners
a
−.37 −2.63 .011
Sociosexual psychology .57 4.08 .0001
a
Response to Item 1 on the SOI-R.
Fig. 2. Men's testosterone levels predicted their sociosexual psychology (combined
Attitude and Desire subscales of the SOI-R), r(59) = .48, P= .0001. Sociosexual psychol-
ogy and testoste rone are conditi oned on number of sexual partners in the past year.
Dashed lines represent 95% confidence interval for least-squares regression line.
Table 6
Multiple regression predicting testosterone in Study 2 male participants.
βtP
No. sex partners
a
−.27 −2.15 .036
Relationship status −.31 −2.49 .016
Sociosexual psychology .31 2.27 .027
Sociosexual psychology × Relationship status −.16 −1.26 .214
Time since waking −.25 −2.09 .041
a
Response to Item 1 on the SOI-R.
18 D.A. Puts et al. / Hormonesand Behavior 70 (2015) 14–21
of sex partner number, as in study1 (bootstrap test; bootstraps = 5000;
Preacher and Hayes, 2008).
In order to further explore our failure to replicate previous findings
(Edelstein et al., 2011; McIntyre et al., 2006) of an interaction between
relationship status and sociosexuality in predicting T, we recoded rela-
tionship status into single = 0 vs. partnered (casual or serious relation-
ship) = 1. We then standardized relationship status, computed its
interaction with standardized sociosexual psychology, and replaced
the corresponding variables in the multiple regression model described
in Table 6. Once again, the model was statistically significant (F
5,55
=
3.29, R
2
= .23, P= .011), as were sociosexual psychology (β=.35,
t= 2.39, P= .020) and sex partner number (β=−.28, t=−2.15,
P= .036), but again sociosexual psychology and relationship status
did not significantly interact (β=−.13, t=−.96, P= .340). Time
since waking (β=−.22, t=−1.87, P= .066) and relationship status
were (β=−.22, t=−1.77, P= .082) marginally significant negative
predictors of T.
We then explored relationships between sociosexuality and T in
partnered men and single men separately by entering sociosexual psy-
chology, partner number, and time since waking into separate multiple
regression models to predict T. In partnered men, this model wasstatis-
tically significant (F
3,30
=5.67,R
2
= .36, P= .003), as were sociosexual
psychology (β= .31, t=2.09,P= .045), partner number (β=−.39,
t=−2.55, P= .016), and time since waking (β=−.38, t=−2.53,
P= .017); however, in single men, this model was not statistically sig-
nificant (F
3,23
=.49,R
2
= .36, P= .696),nor were sociosexual psychol-
ogy (β= .27, t= 1.12, P= .272), partner number (β=−.10, t=−.41,
P= .686), or time since waking (β=−.07, t=−.35, P= .733).
Next, we explored whether the negative association between num-
ber of sex partners and testosterone in the multiple regression model
described in Table 6 was due to more attractive, high status or well-
liked men having lower testosterone. We examined as potential media-
tors female peer-rated attractiveness for short- and long-term relation-
ships, male peer-rated physical dominance and leadership abilities, and
how well participants were liked by male and female peers. None of
these significantly mediated the relationship between number of sex
partners and testosterone; 95% confidence intervals included zero for
indirect effects through all proposed mediators (bootstrap test;
bootstraps = 5000; Preacher and Hayes, 2008).
We performed a similar set of mediation analyses to explore wheth-
er increased number of sex partners with decreasing testosterone was
due to a tendency for men with lower testosterone to engage in more
self-serving exaggeration. We first standardized each male participant's
self-rated attractiveness, fighting ability, and leadership ability, as well
as his male peer-rated fighting and leadership abilities and his female
peer-rated long- and short-term attractiveness. The last two of these
correlated highly (r
58
=.93,Pb.0001) and were thus averaged. We
then computed the difference between standardized self- and peer-
ratings for each attribute, such that positive values indicated a tendency
to view oneself as higher on that attribute than peers do. None of these
difference scores significantly mediated the relationship between num-
ber of sex partners and testosterone.
Finally, to more exactly replicate the analysis from Study 1, we ran a
multiple regression predicting log-transformed testosterone (F
2,59
=
3.72, R
2
=.11,P= .030), including only sociosexual psychology and
sex partner number as predictors. Sociosexual psychology was again a
significant positive predictor (β=.31,t=2.40,P= .020), and sex part-
ner number fell just short of statistical significance as a negative predic-
tor (β=−.26, t=−1.99, P=.051).
Discussion
In Study 1, the sex difference in sociosexual psychology was fully
mediated by testosterone, which wasalso differentially related to socio-
sexual psychology in men and OC-using women. Testosterone did not
predict OC-using women's sociosexual psychology, but it positively
predicted men's in both samples. This sex difference in the relationship
between T and sociosexual psychology may reflect sex differences in re-
productive strategies (Bussand Schmitt, 1993; Gangestad and Simpson,
2000). Because ancestral men could benefit reproductively from un-
committed mating with a high number of sexual partners in a way
that ancestral women could not, mechanisms that encourage uncom-
mitted mating in men may do so to a lesser degree or not at all in
women (Del Giudice and Belsky, 2011). At a proximate level, perhaps
sociosexual responsiveness to testosterone in adulthood requires
threshold testosterone concentrations or early organizational effects of
sex hormones, such as high fetal testosterone. Such organizational ef-
fects are necessary for later activational effects of sex hormones across
a wide variety of traitsand species (Nelson, 2005; Phoenix et al., 1959).
Functionally, men's testosterone may represent a trigger mediating
the allocation of reproductive effort from investment in a mate and/or
offspring to seeking additional mating opportunities (Archer, 2006;
McIntyre et al., 2006). It is also possible that the relationship between
sociosexual psychology and testosteroneis bidirectional in men; Testos-
terone may not only increase interest in and positive attitudes toward
uncommitted sex—thinking about uncommitted sex may also increase
men's testosterone levels. However, while abundant research indicates
that exposure to sexual stimuli raises men's testosterone levels (Roney
et al., 2007, 2010), merely thinking about sex does not appear sufficient
to do so (Goldey and van Anders, 2012, 2014).
Finally, controlling for sociosexual psychology, testosterone nega-
tively predicted men's sociosexual behavior, particularly their number
of sex partners in the previous year. This was true regardless of whether
testosterone was measured before (Study 1) or at the end of (Study
2) the interval over which number of sex partners was reported. This
was also true across samples of male undergraduates that differed
markedly in sociosexual attitudes, behavior, and desires, as well as
number of reported sexual partners (Cohen's d=1.0–1.3), likely
reflecting differences between fraternity members (Study 2) and a
broader sample of undergraduate men (Study 1). One explanation for
this negative relationship between testosterone and sociosexualbehav-
ior is that testosterone may decrease men's ability to acquire sexual
partners. However, this relationship was not mediated by men's attrac-
tiveness, dominance, leadership or likeability. Another explanation is
that men with lower testosterone may be more prone to exaggerating
their partner numbers. However, testosterone did not reflect general
self-serving exaggeration, as it was unrelated to any exaggeration re-
garding attractiveness, dominance or leadership.
We favor a third possibility: men's general satisfaction in the mating
sphere decreases testosterone. Although T may increase mating oppor-
tunities through elevating sociosexual psychology (Edelstein et al.,
2011; this study), intrasexual competitiveness (Archer, 1991, 2006;
Mazur and Booth, 1998), and the production of the anatomical traitsrel-
evant to intrasexual competition (Puts et al., 2012), there are numerous
costs to high levels of T. These include interference with pair-bonding
and parental care, increased energy consumption, oxidative stress, sup-
pression of some types of immunefunction,and increased risk of injury
resulting from aggressive and/or risky behaviors (Archer, 2004, 2006,
2009; Bouman et al., 2005; McIntyre et al., 2006; Wingfield et al.,
2001). Men who achieve what, for them, represents a successful pattern
of mating, whether through committed relationships or uncommitted
sex, should lower these costs by decreasing T production. The present
results thus point to negative feedback in which T promotes copulatory
success, and copulatory success in turn down-regulates T production
(Fig. 1).
We also replicated the finding that men in more committed relation-
ships have lower testosterone (Booth and Dabbs, 1993; Burnham et al.,
2003; Grayet al., 2002; McIntyre et al., 2006) and found partial support
for previous findings that sociosexuality is related to T in partnered but
not single men (Edelstein et al., 2011; McIntyre et al., 2006). Although
we found no significant interaction between sociosexual psychology
and relationship status in predicting testosterone using two coding
19D.A. Puts et al. / Hormonesand Behavior 70 (2015) 14–21
schemes for relationship status, the interaction was in the predicted di-
rection, and sociosexual psychology was significantly related to T in
partnered but not single men. Functionally, such an effect of partnered
status may reflect adaptations related to extra-pair mating (McIntyre
et al., 2006). Both partnered and single men vary in their opportunities
for uncommitted mating and hence the degree to which they could ben-
efit reproductively from an interest in uncommitted mating and the
mating effort that it promotes (Gangestad and Simpson, 2000;
Lukaszewski et al., 2014). However, the costs of mating effort should
be particularly great for partnered men, who would suffer a proportion-
ate decrement to their investment and may lose their mate altogether.
Consequently, in partnered men, sociosexual psychology may be partic-
ularly strongly tied to physiological factors such as T that track this cost/
benefit tradeoff. In other words, T may be more strongly tied to uncom-
mitted mating orientation in partnered men in order to promote extra-
pair mating effort in those with high T and many extra-pair mating op-
portunities, and to decrease mating effort and promote investment by
partnered men with low T and few such opportunities.
Limitations
Due to the cross-sectional nature of our data, we cannot definitively
discriminate between whether T is a cause, consequence, or merely a
correlate of sociosexual behavior or psychology. Total SOI-R and all
three subscales tend to be stable over time, with measures taken a
year apart correlating at r=0.7–0.8 (Penke and Asendorpf, 2008). Con-
sequently, comparing results when T is sampledat the beginning (Study
1) vs. at the end (Study 2) of the year over which participants reported
their sociosexual behavior would not resolve the direction of causality.
Each sampling regime used in the present research has advantages
and disadvantages for testing the hypothesized relationships. Testoster-
one data collected prior to the interval over which partner number was
assessed (Study 1) should be more useful in testing possible effects of T
on sexual behavior, but relationships between T and sociosexual psy-
chology should be attenuated in proportion to the length of the interval,
despite the temporal stability of the measures. Testosterone data col-
lected at the end of the interval over which partner number was
assessed (Study 2) should be more useful in testing the influence of sex-
ual behavior on T, and relationships between T and sociosexual psychol-
ogy, but less valuable for testing an influence of T on behavior. The
combination of these two approaches and strong agreement between
their results increases confidence in the hypothesized relationships.
Nevertheless, the correlational nature of our data, along with temporal
separation between when T and behavior were measured, necessitate
that caution be used in interpreting these results. Future longitudinal
data in which changes in sociosexuality and behavior are related to
changes in T may help clarify these relationships.
Another potential concern is that we measured T only in female par-
ticipants who were taking OC, and that the observed relationships with
Treflect effects of OC. However, while OC use lowers free (bioavailable)
T, it does so to a similar degree across OC types (van der Vange,
Blankenstein, Kloosterboer, Haspels, & Thijssen, 1990), particularly
after the first cycle of use (Wiegratz et al., 2003). Furthermore, we
found no differences in sociosexuality between normally cycling and
OC-using women, and Edelstein and colleagues (Edelstein et al., 2011;
R. Edelstein, personal communication, May 31, 2013) found no effect
of OC use on relationships between sociosexuality and T. We view the
inclusion of OC-using women as a strength of our methods, as it should
reduce the influence of cyclic fluctuations in ovarian hormones. Never-
theless, it remains possible that any relationships between women's T
levels and sociosexuality were attenuated or otherwise influenced by
our use of OC-using subjects (Goldey and van Anders, 2011), and future
research should also explore these relationships in normally-cycling
women.
Our samples were also modest in size and comprised students of a
narrow age range around young adulthood. Mating motivation can be
expected to be especially strong in this age range, and thus it will be im-
portant for future studies to explore the extent to which the present re-
sults generalize to other age groups and populations. In Study 2, we also
collected some potentially useful data, such as relationship status, that
were not available in Study 1. Given prior evidence, with some support
from the present research, that this variable mediates relationships
between T and sociosexuality, these data should be collected in future
research. Finally, it will be important for future research to examine
the extentto which these results generalize to other aspectsof sociosex-
ual behavior, such as the frequency of sex and whether it occurred with-
in the context of a long-term partnership, and these data should be
collected over different time intervals.
Summary
We found that sociosexuality was related to testosterone in men, but
not OC-using women. In two samples of men, we showed positive rela-
tionships between testosterone and interest in uncommitted sex and
negative relationships between number of sex partners and testosterone,
when both sociosexual psychology and number of sex partners were en-
tered into a multiple regression model to predict testosterone. These re-
sults are consistent with a negative feedback loop, supported by prior
empirical research and adaptive reasoning, in which testosterone in-
creases desires for uncommitted sex and hence numbers of sexual part-
ners, and in which the satisfaction of these desires lowers testosterone.
Acknowledgments
We thank Kim Wallen and three anonymous reviewers for their
helpful comments on a previous draft of this paper. DAP was funded
on NIH grant number T32MH070343-05 awarded to SMB.
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