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Age Effects on Women’s and Men’s Dyadic and Solitary Sexual Desire

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While most studies on sexuality in later life report that sexual desire declines with age, little is known about the exact nature of age effects on sexual desire. Using self-reported dyadic sexual desire relating to a partner, dyadic sexual desire relating to an attractive person, and solitary sexual desire from a large (N > 8000) and age diverse (14.6–80.2 years) online sample, the current study had three goals: First, we investigated relationships between men and women’s sexual desire and age. Second, we examined whether individual differences such as gender/sex, sexual orientation, self-rated masculinity, relationship status, self-rated attractiveness, and self-rated health predict sexual desire. Third, we examined how these associations differed across sexual desire facets. On average, the associations between age and both men and women’s sexual desire followed nonlinear trends and differed between genders/sexes and types of sexual desire. Average levels of all types of sexual desire were generally higher in men. Dyadic sexual desire related positively to self-rated masculinity and having a romantic partner and solitary desire was higher in people with same-sex attraction. We discuss the results in the context of the evolutionary hypothesis that predict an increase of sexual desire and female reproductive effort prior to declining fertility. Our findings both support and challenge beliefs about gender/sex specificity of age effects on sexual desire and highlight the importance of differentiating between desire types.
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Archives of Sexual Behavior (2022) 51:3765–3789
https://doi.org/10.1007/s10508-022-02375-8
ORIGINAL PAPER
Age Effects onWomen’s andMens Dyadic andSolitary Sexual Desire
LarissaL.Wieczorek1 · MeredithChivers2 · MonicaA.Koehn3 · LisaM.DeBruine4 · BenedictC.Jones5
Received: 11 November 2021 / Revised: 27 June 2022 / Accepted: 30 June 2022 / Published online: 2 August 2022
© The Author(s) 2022
Abstract
While most studies on sexuality in later life report that sexual desire declines with age, little is known about the exact nature of
age effects on sexual desire. Using self-reported dyadic sexual desire relating to a partner, dyadic sexual desire relating to an
attractive person, and solitary sexual desire from a large (N > 8000) and age diverse (14.6–80.2years) online sample, the current
study had three goals: First, we investigated relationships between men and women’s sexual desire and age. Second, we exam-
ined whether individual differences such as gender/sex, sexual orientation, self-rated masculinity, relationship status, self-rated
attractiveness, and self-rated health predict sexual desire. Third, we examined how these associations differed across sexual
desire facets. On average, the associations between age and both men and women’s sexual desire followed nonlinear trends and
differed between genders/sexes and types of sexual desire. Average levels of all types of sexual desire were generally higher
in men. Dyadic sexual desire related positively to self-rated masculinity and having a romantic partner and solitary desire was
higher in people with same-sex attraction. We discuss the results in the context of the evolutionary hypothesis that predict an
increase of sexual desire and female reproductive effort prior to declining fertility. Our findings both support and challenge beliefs
about gender/sex specificity of age effects on sexual desire and highlight the importance of differentiating between desire types.
Keywords Sexual desire· Solitary desire· Dyadic desire· Age· Gender/sex effects
Age Eects onWomens andMen’s Dyadic
andSolitary Sexual Desire
Sexual desire can be understood as the experience of sexual
thoughts, fantasies, and the motivation to engage in sexual
activity (Basson, 2002). Given the positive link between
sexual desire and general well-being (e.g., Davison etal.,
2009; Robinson & Molzahn, 2007; Willert & Semans, 2000),
it is important to understand the factors that predict sexual
desire across the life course. Several studies suggest that, on
average, sexual desire is negatively associated with age (e.g.,
Dawson & Chivers, 2014; DeLamater & Sill, 2005; Laumann
etal., 2005; Lindau etal., 2007). Looking at gender-/sex-
specific effects, Alfred Kinsey proposed that “the male may
be most desirous of sexual contact in his early years, while
[…] most females become less inhibited [over the years]
and develop an interest in sexual relations, which they may
maintain until they are in their fifties or sixties” (Kinsey etal,
1953, pp. 353). This prediction has seldom been questioned
(see Barr etal., 2002), yet assumptions regarding the specific
age when women’s desire is highest are more diverse. While
no certain point in life is known to mark a change in sexual
functioning for men, the transition into menopause is associ-
ated with a decrease in sexual functioning in women (Den-
nerstein etal., 2001; Petersen & Hyde, 2011). Given these
age-related biological changes, evolutionary psychologists
have hypothesized that women would experience an increase
of sexual desire around age 35 to maximize their reproduc-
tive output before they lose their fertility (Easton etal., 2010;
Schmitt etal., 2002). In Barr etal.’s (2002) survey on socially
shared cognitions regarding women and men’s sexual peak,
participants expected female desire to be highest around
age 27 and male desire to be highest around age 22. Finally,
* Larissa L. Wieczorek
larissa.wieczorek@uni-hamburg.de
1 Institute ofPsychology, Educational Psychology
andPersonality Development, University ofHamburg,
Von-Melle-Park 5, 20146Hamburg, Germany
2 Department ofPsychology, Sexuality andGender Lab,
Queen’s University, Kingston, Canada
3 Discipline ofPsychology, Faculty ofHealth, University
ofCanberra, Canberra, Australia
4 School ofPsychology & Neuroscience, University
ofGlasgow, Glasgow, Scotland
5 School ofPsychological Sciences andHealth, University
ofStrathclyde, Glasgow, Scotland
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3766 Archives of Sexual Behavior (2022) 51:3765–3789
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media, such as the popular TV series Sex and the City, paint
a picture of women who have adventurous sexual lives and
whose desire remains high through and after their thirties.
Despite these common assumptions on gender-/sex-specific
age effects on sexual desire—that women reach their peak of
sexual desire later than men do—corresponding scientific evi-
dence is lacking. Importantly, human sexuality is widely con-
ceptualized as a product of fundamentally entwined biological
and sociocultural influences (Fausto-Sterling, 2005; Levine,
2003). Thus, a wide range of biological and psychosocial fac-
tors should be considered when studying age effects on sexual
desire. The current study had three objectives: First, we exam-
ined sexual desire across women and men covering a broad age
range to empirically evaluate gender-/sex-specific age effects
on sexual desire. Second, we investigated which biological
and psychosocial factors (i.e., gender/sex, sexual orientation,
self-rated masculinity, relationship status, self-rated health
and self-rated attractiveness) relate to sexual desire. Third,
we examined how the associations between sexual desire and
the remaining study variables differed across specific facets
(Moyano etal.,; 2017; Spector etal., 1996) of sexual desire.
Facets ofSexual Desire
The Sexual Desire Inventory-2 (SDI-2; Spector etal., 1996)
is the most commonly used instrument for the measurement
of trait sexual desire in normative circumstances (see Dawson
& Chivers, 2014; Stark etal., 2015; Toledano & Pfaus, 2006).
In its original conceptualization (Spector etal., 1996), the
SDI-2 consists of two facets measuring dyadic sexual desire
(i.e., desire for partnered sexual activity) and solitary sexual
desire (i.e., desire for solitary sexual activity, like masturba-
tion). As noted by Holmberg and Blair (2009), however, it
might be more reasonable to split the dyadic sexual desire
scale into items referring to a (current) sexual “partner” or to
an “attractive person,” suggesting desire toward an acquaint-
ance or stranger. Conceptually, these two facets of dyadic
desire differ from each other in that desire relating to a partner
strongly depends on characteristics of the romantic partner or
relationship, whereas desire relating to an attractive person
may occur independent of a person’s current relationships
(Moyano etal., 2017). Moreover, the two facets of dyadic
sexual desire and corresponding sexual behaviors reflect
different psychological needs, which likely vary across the
life span. Specifically, having sex with a romantic partner
might follow the wish to express love and to feel connected,
whereas having sex with an attractive person might follow
the wish to experience sexual variety (Meston & Buss, 2007).
Using exploratory and confirmatory factor analyses in
two samples of heterosexual men and women in committed
romantic relationships (Noverall = 4,094), Moyano etal. (2017)
provided empirical support for the distinction of dyadic sexual
desire into dyadic desire (partner) and dyadic desire (attrac-
tive person). These further specified scales have also been
validated in a Columbian sample (Vallejo-Medina etal., 2020)
and a sexual minority sample (Mark etal., 2018). Moreo-
ver, Moyano etal. (2017) found that whereas dyadic desire
(partner) related to higher sexual satisfaction, dyadic desire
(attractive person) related to higher tendency to become sexu-
ally aroused. This way, both theoretical and empirical research
suggests a differential relevance of dyadic desire (partner)
and dyadic desire (attractive person). Given that our original
hypotheses were based on the distinction between the broader
constructs of dyadic and solitary sexual desire, however, dif-
ferences between these two more specific sexual desire facets
will be examined in an exploratory manner.
Factors Inuencing Sexual Desire
Age
Age is typically negatively related to sexual desire (Beutel
etal., 2008; DeLamater & Sill, 2005; Eplov etal., 2007).
Apart from this, less is known about variation in sexual desire
from early to late adulthood or how these age effects might
vary by gender/sex. Of note, age effects on sexual desire need
to be understood as a complex interplay of biological and psy-
chosocial factors (Levine, 2003; Tolman & Diamond, 2001).
For example, the wish to find a partner or to become a par-
ent can increase an individuals’ sexual desire in young years
(Levine, 2003). In contrast, sexual desire might be diminished
at higher ages by the loss of one’s romantic partner (Kontula
& Haavio-Mannila, 2009) or stigmatization of sex among the
elderly (DeLamater & Sill, 2005). Despite the undeniable rel-
evance of these psychosocial aspects, gender-/sex-specific
predictions are mainly based on biological explanations.
Menopause, defined as cessation of menstruation for
one year, usually occurs between ages 45 and 55 (National
Health Service, 2017), yet women’s fertility is believed to start
declining at age 32, and more rapidly after age 37 (Practice
Committee of the American Society for Reproductive Medi-
cine, 2008). The age of 35 therefore represents a marker of a
life phase where female reproductive capacity decreases, but
fertility persists for approximately another decade. Men’s fer-
tility, in contrast, is only barely affected by age (Dunson etal.,
2002). Given these gender/sex specificities in age-related
changes of fertility, evolutionary psychologists theorized that
women’s sexual desire should increase in the years prior to
declining fertility to maximize the probability of reproduc-
tion (Buss, 2016). In contrast, no such distinct patterns are
predicted for men. In line with this hypothesis, Schmitt etal.
(2002) found that women aged 30–34, compared to younger
(aged 18–24) and older (aged 35–54) women, showed higher
levels of desire. For men, Schmitt etal.’s results indicated
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3767Archives of Sexual Behavior (2022) 51:3765–3789
1 3
a peak of sexual desire that occurs at age 25–29, and thus
earlier than for women. In a study by Easton etal. (2010),
women aged 27–45 reported higher desire than younger (aged
18–26) and older (aged 46 and older) women; no men were
included in this study. Whereas these studies provide first
empirical support for the hypothesis that women’s sexual
desire is highest before fertility declines and men’s desire is
highest at a younger age, it is important to note some limita-
tions: First, given that only few participants aged 30–34 (Ns
ranging from 14 to 53) were included in Schmitt etal.’s (2002)
study, the comparison between this group and remaining par-
ticipants was likely underpowered. Second, in Easton etal.’s
(2010) study, the lack of male participants makes gender/sex
comparisons impossible. Third, in both studies, the use of
data aggregated in age groups complicates a more nuanced
interpretation on how sexual desire relates to age. Thus, find-
ings need to be replicated with a larger sample involving both
women and men and using a nuanced measure of age.
Overall, extant research suggests a negative relationship
between sexual desire and age, but that specific effects might
differ by gender/sex. Accordingly, we expected that, on aver-
age, sexual desire is negatively associated with age (Hypoth-
esis 1a). Moreover, we predicted that women’s sexual desire is
highest between ages 35 to 45, but negatively associated with
age thereafter (Hypothesis 1b), while men’s sexual desire is
negatively associated with age in a linear way (Hypothesis 1c).
Gender/Sex
Previous studies typically report lower sexual desire among
women (e.g., Kim etal., 2021; Lippa, 2009; Sutherland etal.,
2015), especially when solitary desire (e.g., masturbation) is
measured (Baumeister etal., 2001; Hyde, 2005; Stark etal.,
2015). Several theories have been proposed to explain the
gender/sex difference in trait sexual desire. Among the most
influential are sexual strategies theory (Buss & Schmitt,
1993), and social theories, including social learning theory
(Bandura, 1986). Sexual strategies theory proposes that males
should, on average, be more interested in a higher number
of short-term mates, while females should, on average, be
more interested in acquiring reliable long-term mates due to
their relatively higher reproductive costs (Buss & Schmitt,
1993; Gangestad & Simpson, 2000). Higher sexual desire
would therefore function as an evolutionary adaptation that
helps men to increase their reproduction rate, while the lower
desire would help women to only invest in offspring with suit-
able partners. According to social learning theory, gender/
sex differences in (expressions of) sexual desire follow social
learning from different behavior of same gender/sex role mod-
els in real life and media (Bandura, 1986; Chivers, 2014). In
addition, less reinforcement or more punishment for women
expressing sexual desire is believed to amplify gender/sex dif-
ferences (Bussey & Bandura, 1999; Petersen & Hyde, 2011).
Together, both theory and previous studies suggest higher
sexual desire in men. At the same time, such gender/sex effects
might vary across sexual desire facets and various biological and
social variables are likely to contribute to this difference. Thus,
we expected that, on average, men report higher sexual desire
than women (Hypothesis 2a), while men and women’s dyadic
desire is more similar than their solitary desire (Hypothesis 2b).
Sexual Orientation
Sexual orientation effects on sexual desire have also been sug-
gested, yet empirical evidence is mixed. On the one hand, data by
Lippa (Lippa, 2006, 2007) indicated that gay and bisexual men
had somewhat lower sex drive than heterosexual men, whereas
bisexual women were higher in sex drive than heterosexual and
lesbian women were. On the other hand, recent findings sug-
gest that gay men score higher on solitary and dyadic (attractive
person) sexual desire (Peixoto, 2019). Thus, whereas sexual ori-
entation effects on sexual desire remain a topic for investigation,
other findings from the sexuality research might inform about
corresponding associations: While it is more socially accepted for
men than for women to express sexual desire in general (Petersen
& Hyde, 2011), women with same-sex attraction are more likely
to deviate from heteronormative mating scripts that envisage a
rather passive role for women (Jackson, 2006). These women
might have learned to express their sexual desire to a greater
degree than typically reported by heterosexual women. Also,
findings from studies examining sexual concordance (i.e., the
agreement between genital and self-reported sexual arousal;
Suschinsky etal., 2017) point to the possibility that same-sex
attracted women have learned to register their sexual arousal
more precisely than heterosexual women and therefore experi-
ence more sexual desire (Everaerd & Both, 2001; Meana, 2010).
Overall, it seems likely that sexual orientation differences in
sexual concordance and socialization experiences are reflected
in different levels of sexual desire, especially among women.
Integrating these different results and assumptions, we expected
that same-sex attracted and heterosexual men show higher sex-
ual desire than same-sex attracted women, who show higher
sexual desire than heterosexual women do (Hypothesis 3).
Masculinity
To our knowledge, no study has examined how self-rated mas-
culinity and sexual desire are related. Given that self-rated mas-
culinity is related to sexual identity (Garcia & Carrigan, 1998),
gender/sex and sexual orientation (Lippa, 2008), and social
scripts and expectations (Eagly & Wood, 1999), we investigated
its role in predicting sexual desire. The expression of sexual
desire is usually considered male-typical or masculine within a
double standard (Petersen & Hyde, 2011; Tolman & Diamond,
2001). Importantly, masculinity varies not only between but
also within genders/sexes and many gender/sex differences
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3768 Archives of Sexual Behavior (2022) 51:3765–3789
1 3
might arise from femininity and masculinity (Vanwesenbeeck,
2009). In that sense, more masculine men and women could be
expected to express higher levels of sexual desire. Moreover,
a higher valuation of masculine characteristics in (Western)
society potentially facilitates a transgression into masculinity
by women and makes a transgression into femininity by men
more difficult (Sandford, 2005). These initial findings suggest
a masculine connotation of sexual desire and that women might
vary more so on the femininity–masculinity continuum than
men. Therefore, we expected that self-rated masculinity does
positively relate to sexual desire (Hypothesis 4a) and that this
effect is stronger for women (Hypothesis 4b).
Relationship Status
In previous studies, women’s sexual desire was higher in the
context of a relationship, whereas male desire was unaffected
by these circumstances (Impett etal., 2014; Petersen & Hyde,
2011). At the same time, enduring long-term relationships
dampen the sexual desire of both genders/sexes, but espe-
cially so for women (Dawson & Chivers, 2014; Klusmann,
2002; McNulty etal., 2019; Meana, 2010; Murray & Mil-
hausen, 2012). Using two large national samples in Finland
(Noverall = 3,682), Kontula and Haavio-Mannila (2009) found
that relationship duration had no effect on men’s and women’s
sexual desire when controlling for other factors, such as sexual
functioning. Looking at later life (age 65 or older), having a
sexual partner is a strong predictor for having sex and sexual
desire (DeLamater & Sill, 2005; Kontula & Haavio-Mannila,
2009), while widowed women (who are more common than
widowed men because more women partner with older men)
might have lower (dyadic) desire as an adaption to the lack
of access to sexual partners. In turn, having a partner likely
reduces solitary sexual desire, since one reason for feeling
the desire to masturbate can stem from the unavailability of a
partner (Carvalheira & Leal, 2013; Reece etal., 2010). Given
these observations, we examined the effects of relationship
status on the types of sexual desire, and their interaction with
age. Whereas previous evidence for relationship status effects
on sexual desire is mixed, associations might differ across
sexual desire facets and be moderated by age. Accordingly, we
predicted that having a partner relates positively to dyadic sex-
ual desire and negatively to solitary sexual desire (Hypothesis
5a) and that the interaction between relationship status and
age positively predicts dyadic sexual desire (Hypothesis 5b).
Health andAttractiveness
Unsurprisingly, clinicians consider health among one of
the key variables shaping sexual desire (Levine, 2003) and
numerous studies provide empirical support for this link (e.g.,
Dennerstein etal., 1999; Laumann etal., 1999; Shifren etal.,
2008). Age-related decreases of sexual desire can partly be
attributed to poorer health, including physiological changes
that alter sexual functioning (Willert & Semans, 2000; Kon-
tula & Haavio-Mannila, 2009). Next to health, self-rated
attractiveness might be an important predictor of sexual
desire as related variables such as poor body image and low
sexual self-esteem are frequently listed as factors contrib-
uting to sexual functioning concerns, including low sexual
desire in women (e.g., Koch etal., 2005; Kontula & Haavio-
Mannila, 2009; Seal etal., 2009). Moreover, objectification
theory (Fredrickson & Roberts, 1997) suggests higher levels
of self-consciousness and critical self-observation among
women. Therefore, self-rated attractiveness might have a
greater impact on female than male desire. Given these find-
ings, we examined the effects of self-rated health, self-rated
attractiveness and of the interaction between gender/sex and
self-rated attractiveness on sexual desire in the current study.1
Current Study
The current study aimed to examine relationships among age
and sexual desire using over 8000 participants’ responses
to the Sexual Desire Inventory-2 (Spector etal., 1996) in
an online survey. The impact of various additional biologi-
cal and psychosocial factors, including gender/sex, sexual
orientation, self-rated masculinity, relationship status, self-
rated health, and self-rated attractiveness, on sexual desire
were also examined. Hypotheses and analyses were preregis-
tered at https:// osf. io/ f7hsn via the Open Science Framework
(Center for Open Science, 2011–2022). Whereas some of
our preregistered hypotheses refer to dyadic sexual desire,
findings by Moyano etal. (2017) and results of confirmatory
factor analyses with our own data (see Appendix A), sug-
gested that a differentiation between dyadic desire (partner)
and dyadic desire (attractive person) in addition to solitary
desire would be more appropriate. Accordingly, in this arti-
cle, we report separate effects for both dyadic sexual desire
facets. Nonetheless, results from the analyses that were based
on the original SDI-2 facets (Spector etal., 1996) can be
retrieved from Appendix B. For reasons of parsimony, only
the most relevant hypotheses and corresponding results are
presented in the main part of the article, but results from
all preregistered analyses (i.e., analyses on self-rated attrac-
tiveness, mediation effects that might account for gender/
sex differences, and effects of hormonal contraception) are
reported in Appendix C.
1 To streamline our article, we do not report hypotheses on health and
self-rated attractiveness here. However, full details of our hypotheses
and corresponding results are given in our preregistration and Appen-
dices, respectively.
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3769Archives of Sexual Behavior (2022) 51:3765–3789
1 3
Method
Participants
Data collection was part of a larger online study on social
attitudes and personality conducted by [names masked for
review], which was administered via the Experimentum plat-
form (DeBruine etal., 2020). The study was advertised via a
number of social media platforms (e.g., stumbleupon.com).
Participants took part on a voluntary basis and were recruited
between July 2007 and March 2018.2 In the original study,
N = 8205 participants provided data about their sexual desire
and were therefore considered to be included in the current
study. From this original sample, participants providing no
information about their gender/sex (n = 42) or age (n = 5)
were excluded. Further, participants with an unrealistically
high age (> 100; n = 5) and intersex or non-binary individuals
(n = 3) were excluded due to their small number and the rel-
evance of gender/sex in all research questions. After applying
the exclusion criteria, the remaining total sample consisted
of N = 8150 participants that were aged between 14.6 and
80.2years (M = 24.89, SD = 7.91) and consisted of a larger
portion (67.88%) of women. As indicated by the mean age,
most participants were relatively young in comparison to
the large age range. With regard to sexual orientation, 5882
(72.17%) identified as heterosexual, 1600 (19.63%) indicated
same gender/sex attraction (i.e., attraction to the same gen-
der/sex or to both men and women), 25 (0.31%) indicated
asexual orientation and the rest indicated no sexual prefer-
ence. At the time of measurement, 2416 (29.64%) of the par-
ticipants had a partner, 2295 (28.16%) were single, and the
remaining participants did not provide any information about
their relationship status.
Since using an existing data set, the sample size was pre-
determined. Nonetheless, we performed sensitivity analy-
ses with the software G*Power (Faul etal., 2007) to deter-
mine whether our sample had sufficient power (95% power
at an alpha error-level of α = 0.05) to detect small effects
(f2 = 0.02 or d = 0.20). A subsample of N = 2744 participants
provided complete answers on all study variables. As for the
total sample, the expected sensitivity (95% power to detect
small effects) in our analyses remained high. Compared to
the total sample, participants providing complete informa-
tion on all variables was more likely to be non-heterosexual,
t(4735.3) = 2.37, p = 0.018, d = 0.05, 95%CI [0.01, 0.10], and
less likely to rate themselves as healthy, t(5767.7) = –2.03,
p = 0.042, d = –0.05, 95%CI [–0.10, –0.00], with negligible
effect sizes. With regard to age, gender/sex, relationship sta-
tus, self-rated attractiveness, self-rated masculinity, and all
sexual desire facets, no difference was found. The age dis-
tribution of our total sample and the subsample of complete
cases is illustrated in Fig.1.
Procedure andMeasures
The [institution masked for review] has approved data col-
lection. All measures were assessed via self-reports during
an online survey with the order of questionnaires randomized
across participants. The measures that were identified as
being relevant to research questions concerning sexual desire
over the life course und used in this study are described in
the following:
Demographic andIdentity Measures
Participants indicated their gender/sex with one of the answer
options (“male,” “female,” “prefer not to answer” or “does
not apply to me”), their age, and their relationship status as
being in a relationship or not. In addition, sexual orientation
was captured by indication of a sexual preference for men,
women, any (e.g., bisexual), or none (e.g., asexual). For all
Fig. 1 Age Distribu-
tion. NTotal Sample = 8150,
NComplete Cases = 2744
2 Data collection continued for several years to maximize the sample
size. Accordingly, the study link remained open as long as new indi-
viduals were interested in participating.
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3770 Archives of Sexual Behavior (2022) 51:3765–3789
1 3
participants except those who answered “none,” a new vari-
able coding their sexual orientation as heterosexual (attracted
to the opposite sex) or same gender/sex attracted (attracted to
the same gender/sex and both gender/sexes) was computed.
Sexual Desire
Sexual desire was measured with the SDI-2 (Spector etal.,
1996; see Table6 for items). Dyadic sexual desire (partner)
was measured with seven items, dyadic sexual desire (attrac-
tive person) with two items, solitary sexual desire with four
items, and the total score of sexual desire with all fourteen
items. Answers were given on 9-point scales ranging from 1
to 9 in the case of items assessing strength of sexual desire
and on 8-point scales ranging from 0 to 7 in the case of items
assessing frequency of sexual desire. The anchor labels of
the SDI-2 scales varied by item, but a higher value reflected
higher/ more frequent sexual desire in every item. Internal
consistencies as indicated by Cronbach’s α in our study were
0.88, 0.84, and 0.92 for dyadic (partner), dyadic (attractive
person), and solitary sexual desire, respectively.
Self‑Ratings
Participants rated their own masculinity, attractiveness, and
health on a 7-point scale ranging from 1 (much less mas-
culine/attractive/ healthy than average) to 7 (much more
healthy/attractive/masculine than average). Similar meas-
ures have been successfully used in research on vocal and
facial partner preferences (e.g., Feinberg etal., 2012; Kandrik
& DeBruine, 2012).
Data Analysis
All analyses were run with the statistical open source pro-
gram R version 3.6.0 (R Core Team, 2021), RStudio (RStudio
Team, 2021) and several R packages (Revelle, 2018; Tingley
etal., 2014; Torchiano, 2016; Wickham, 2011; Wickham
etal., 2018). Figures were generated using the R package
ggplot2 (Wickham, 2016). When possible, the whole sam-
ple (N = 8150) was analyzed as all participants completed
the SDI-2 and provided information on gender/sex and age
(see exclusion criteria above for additional information). If
participants provided incomplete information, they were
excluded from affected hypotheses testing but included in
the remaining, unaffected analyses. Therefore, used sample
sizes varied depending on the variables included in the analy-
ses. In addition, participants that answered “none” (e.g., this
could translate to “asexual”) in response to the question about
their sexual preference were excluded from analyses involv-
ing sexual orientation, because they were too few (n = 25).
Since all reported hypotheses included sexual desire as the
dependent variable, and in order to control for the effects of
the other predictor variables, many of the hypotheses were
tested with the same large multiple regression models (full
models) based on the subsample that provided complete
answers on all variables included (N = 2744). In the full mod-
els, total and subscale SDI-2 scores were predicted from age,
gender, sexual orientation, self-rated masculinity, self-rated
health, self-rated attractiveness, relationship status, and the
interactions between age and relationship status, gender/sex
and self-rated attractiveness, gender/sex and self-rated mas-
culinity, and gender/sex and sexual orientation. In addition
to analyzing predictor effects in the full models, the hypoth-
esized relationships between age, gender/sex and sexual ori-
entation, and self-rated masculinity with sexual desire were
further examined in linear and polynomial trend analyses,
t-tests, and mediation analyses, respectively. All metric meas-
ures in the regression models were z-standardized. The code
and the data that are necessary to reproduce all results can
be retrieved from https:// osf. io/ rba2x.
We deviated from our original analysis plan in three
aspects. First, some errors in our analysis script led to wrong
computations of (sub)sample sizes for power estimation:
In the preregistration, the total sample size was stated as
N = 8146 instead of the actual N = 8150 and the size of the
subsample with complete information on all measures was
stated as N = 3476 instead of the actual N = 2744. Second,
given our large sample size and the relatively high num-
ber of analyses, we have subsequently decided to interpret
effects with p values < 0.001 instead of < 0.05, as originally
stated, in order to account for the heightened risk of false
positive findings (e.g., Kaplan etal., 2014). Finally, we used
bootstrapping method to test whether effect sizes obtained
in t-tests significantly differed from each other instead of
simply comparing confidence intervals.
Results
Descriptive statistics and bivariate intercorrelations among
continuous study variables can be found in Table1 for men
and women separately. For both men and women, all types
of sexual desire were positively related to each other, with
higher correlations between the two facets measuring dyadic
sexual desire.
Full Models
All predictor variables were entered into the full models,
together with the interactions between age and relationship
status, gender/sex and self-rated attractiveness, gender/sex
and self-rated masculinity, and gender/sex and sexual ori-
entation (for an overview on the single associations between
each variable and total sexual desire, results from simple
regression models can be obtained from Table18). Four full
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3771Archives of Sexual Behavior (2022) 51:3765–3789
1 3
models were run with the data of a subsample of participants
that provided answers on all included measures, predicting
the total, dyadic (partner), dyadic (attractive person) and soli-
tary SDI-2 scores. The results of the full models are summa-
rized in Table2. Since the total desire score is an aggregate
of the dyadic and solitary desire scores (Spector etal., 1996)
and its information is less specific for that reason, we focus
on dyadic (partner and attractive person) and solitary sexual
desire only. Nonetheless, we report results concerning all
four scores.
Before describing the results in detail, we would like
to note that the adjusted R2 of the models was very small
(ranging from 0.071–0.090), indicating that little variance in
sexual desire was explained. Female gender/sex negatively
predicted dyadic desire (attractive person) and solitary desire.
Age positively predicted dyadic sexual desire (partner). Of
the self-perceptions, masculinity positively predicted both
measures of dyadic sexual desire, while health negatively
predicted solitary sexual desire and attractiveness was not
predictive for any of the outcome measure. Having a partner
positively predicted dyadic sexual desire (partner) and nega-
tively predicted dyadic sexual desire (attractive person). In
addition, having a partner negatively predicted solitary desire
but this effect was only significant at p = 0.006. Finally, same-
sex attraction positively predicted solitary sexual desire.
We found significant interaction effects, which are
illustrated in Figs.4 and 5: As indicated by the negative
interaction of age and relationship status, the positive effect
of having a partner on dyadic desire (partner) weakened with
age. As indicated by the negative interaction of gender/sex
and self-rated masculinity, the positive effect of self-rated
masculinity on both types of dyadic desire was weaker for
women compared to men. Of note, this effect was only sig-
nificant at p < 0.001 in the case of dyadic desire (partner).
Age Trends
In order to examine the effect of age on sexual desire in more
detail, we conducted linear and polynomial trend analyses
for all men (n = 2618) and women (n = 5532) separately. As
before, the adjusted R2 indicated that all models explained
only small amounts of variance (linear models: R2 ranging
from − 0.000–0.015; polynomial models: R2 ranging from
0.002–0.026). Results of the linear trend analyses are shown
in Table19. For women, age was a positive significant predictor
for solitary sexual desire, but unrelated to all other SDI-2 facets,
when tested in a linear model. For men, age was a significant
and positive predictor for all three SDI-2 facets except dyadic
sexual desire (attractive person), when tested in a linear model.
The results of the polynomial trend analyses can be observed
from Table3 and are illustrated in Fig.2. For women, negative
quadratic trends most consistently predicted their sexual desire
from age across sexual desire types, yet this effect was only
significant at p = 0.004 in the case of dyadic desire (attractive
Table 1 Descriptive statistics
and intercorrelations of the
continuous study variables by
gender/sex
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). All measures were assessed via self-reports. Correlations in bold font are significant
(p < .001, two-tailed). aSelf-rated
M SD Intercorrelations N
1 2 3 5 6 7 8
Men
1. Age 27.34 9.48 2618
2. SDI: Total 71.75 17.30 .12 2618
3. SDI: Dyadic-P 38.39 9.78 .09 .85 2618
5. SDI: Dyadic-A 10.50 3.71 .08 .69 .53 2618
6. SDI: Solitary 18.38 7.41 .10 .72 .30 .34 2618
7. Attractivenessa4.62 1.29 − .02 .10 .14 .09 − .01 1525
8. Masculinitya4.12 1.34 .13 .14 .22 .14 − .04 .31 1525
9. Healtha4.65 1.41 .02 .02 .08 .06 − .10 .42 .33 1239
Women
1. Age 23.74 6.75 5532
2. SDI: Total 61.89 19.90 .03 5532
3. SDI: Dyadic-P 35.76 11.07 − .00 .86 5532
5. SDI: Dyadic-A 8.05 4.02 − .03 .62 .45 5532
6. SDI: Solitary 14.76 8.80 .06 .76 .38 .33 5532
7. Attractivenessa4.48 1.29 .04 .17 .17 .12 .08 3530
8. Masculinitya3.08 1.53 .02 .05 − .01 .04 .09 − .06 3510
9. Healtha4.17 1.34 .02 .01 .06 .03 − .06 .36 − .04 3168
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3772 Archives of Sexual Behavior (2022) 51:3765–3789
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person). In the case of women’s solitary sexual desire, posi-
tive linear and cubic trends were also observed. Descriptively,
age effects on individual differences in women’s dyadic sexual
desire (both types) were marked by an initially positive effect
that plateaued between the mid-twenties and mid-forties fol-
lowed by a negative effect. In the case of women’s solitary
desire, we observed a peak in the thirties, which was first fol-
lowed by a negative effect and then by a slightly positive age
effect after the age of 60. For men, positive linear, and negative
quadratic trends significantly predicted sexual desire in the
case of all sexual desire types. With the exception of dyadic
sexual desire (attractive person), age effects on individual dif-
ferences in men’s sexual desire were descriptively marked by
a positive effect until age 40, by a slight negative effect fol-
lowed by a positive effect around the age of 50, and a negative
effect after age 60. Age effects on individual differences in
men’s dyadic sexual desire (attractive person), in contrast, were
descriptively marked by a positive effect until the late thirties
or early forties and a negative effect thereafter.
To explore possible interactions between gender/sex and
age, we conducted additional trend analyses using the data of
the whole sample (N = 8150), using gender/sex as a moderator.
Thus, in addition to the linear, quadratic, and polynomial effects
of age, we entered gender/sex and the interaction terms of gen-
der/sex and each of the age effects into our models. Results
were generally consistent with the gender-/sex-specific trend
analyses reported above (see Table20). Specifically, the addi-
tional analyses revealed three patterns: first, in addition to a
negative effect of female gender/sex, positive linear and nega-
tive quadratic effects of age predicted sexual desire across all
Table 2 Coefficients of the
multiple regression models (full
models) predicting the SDI-2
scores
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). Multiple regression models (full models) are each based on N = 2744 observations.
Participant gender/sex, relationship status, and sexual orientation were factor coded (0 = male, 1 = female;
0 = heterosexual, 1 = same-sex attracted; 0 = single, 1 = in a committed relationship). All continuous vari-
ables were z-standardized. Negative estimates indicate lower scores for women compared to men, for same-
sex attracted compared to heterosexual people, and for people having a partner compared to singles. aSelf-
rated. *p < .05, **p < .01, ***p < .001
SDI-2 score
Predictor Total Dyadic-P Dyadic-A Solitary
Age .10** .11*** − .00 .09**
Gender/sex –.31*** –.07 − .46*** − .28***
Sexual orientation .31*** .15 .13 .42***
Masculinity a.18*** .21*** .17*** .06
Relationship status .13*** .33*** − .16*** − .11**
Health a − .03 .02 − .03 − .08***
Attractiveness a.08* .06 .04 .07*
Age × relationship status − .09* − .16*** .02 .01
Gender/sex × Attractivenessa.07 .08* .04 .03
Gender/sex × Masculinitya − .13** − .21*** − .14** .04
Gender/sex × Sex. or ientation − .15 − .21* − .03 − .03
Adj. R2.081 .071 .090 .078
Table 3 Polynomial trends of sexual desire among men and women
SDI-2 = Sexual Desire Inventory-2 (Spector et al., 1996); dyadic-
P = dyadic (partner); dyadic-A = dyadic (attractive person). Polyno-
mial regression models are each based on the observation of n = 2618
men and n = 5532 women. All variables were z-standardized.
*p < .05, **p < .01, ***p < .001
Trend Men Women
SDI-2 score: Total
Age 6.31*** 1.95
Age2 − 5.36*** − 5.71***
Age31.41 2.62**
Adj. R2.026 .007
SDI-2 score: Dyadic-P
Age 4.62*** 0.22
Age2 − 3.63*** − 4.19***
Age32.27* 0.42
Adj. R2.014 .003
SDI-2 score: Dyadic-A
Age 4.18*** − 2.00*
Age2 − 3.78*** − 2.86**
Age3 − 0.29 1.35
Adj. R2.011 .002
SDI-2 score: Solitary
Age 5.17*** 4.47***
Age2 − 4.59*** − 5.54***
Age30.38 4.08***
Adj. R2.017 .012
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3773Archives of Sexual Behavior (2022) 51:3765–3789
1 3
facets; second, the interaction between female gender/sex and
the linear age effect was negatively associated with both facets
of dyadic sexual desire, indicating that the positive linear effect
of age on desire was less pronounced in women; third, and in
contrast to the findings for dyadic sexual desire, solitary sexual
desire was also predicted by a positive polynomial effect of age
while none of the interaction terms was significant at p < 0.001.
Group Comparisons byGender/Sex andSexual
Orientation
After obtaining effects of gender/sex and sexual orientation
on sexual desire in the full models, we examined these pre-
dictors by conducting group comparisons. Together, these
findings are illustrated in Fig.3.
The results of Welch t-tests comparing men’s with wom-
en’s sexual desire are shown in Table4. Mens sexual desire
score was significantly higher across all facets, with small to
medium effect sizes. Cohen’s d of the gender/sex effect was
largest for dyadic sexual desire (attractive person), followed
by solitary sexual desire, and smallest for dyadic sexual
desire (partner). Bootstrapped comparisons based on 10 000
simulations each indicated that all of these differences across
effect sizes were significantly different from each other.3
Fig. 2 Age Trends in Sexual Desire. The upper and the lower panel
show the sexual desire trends for women and men, respectively. The
blue dots represent sexual desire scores of individuals with a given
age. The black lines each represent the average sexual desire score
regressed across individuals at different ages. The gray area depicts
the corresponding 95% confidence bands
3 As can be seen from the analysis script (https:// osf. io/ q7n9x), we took
10,000 random resamples of our data, calculated Cohen’s d for the gen-
der/sex comparison on each desire scale and then calculated the difference
between the effect sizes. Finally, we calculated the confidence interval for
this difference. If zero was not included in the confidence interval, we con-
cluded that the effect sizes were significantly different from each other.
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3774 Archives of Sexual Behavior (2022) 51:3765–3789
1 3
The results of Welch t-tests comparing sexual desire
scores between heterosexual and same-sex attracted men, as
well as between heterosexual and same-sex attracted women
are shown in Table5. Looking at both men and women, indi-
viduals with same-sex attraction scored significantly higher
on solitary sexual desire with a small effect.
Robustness Check
In our sample, age was not evenly distributed, such that only
few participants under age 18 (n = 8) or above age 60 (n = 38)
were included. In order to test whether the data from these
participants biased the results, we repeated our analyses with
an age-truncated sample, excluding participants under age
18 and over age 60 (n = 46; Ntruncated = 8104) as a robust-
ness check. Results from these analyses can be obtained from
the online supplement at https:// osf. io/ jk5zh. Most results
from the main analyses were unaffected, but some deviations
occurred: In women, the negative quadratic trend (β = 3.15,
p = 0.002) predicting dyadic sexual desire (partner) and the
cubic trend (β = 2.72, p = 0.006) predicting solitary sexual
desire were no longer significant at p < 0.001. In men, the
negative quadratic trend (β = − 2.68, p = 0.007) predicting
dyadic sexual desire (attractive person) and the negative
quadratic trend (β = − 3.23, p = 0.001) predicting solitary
sexual desire were no longer significant at p < 0.001. Despite
these (mainly subtle) differences in the level of significance,
the direction of trends remained the same.
Discussion
Using a large online sample, covering a broad age range,
we examined effects of age, gender/sex, sexual orientation,
relationship status, and self-rated masculinity, attractiveness,
and health on sexual desire. Our findings add to the literature
on sexual desire in three important ways: First, trend analy-
ses revealed nonlinear associations between age and sexual
desire for both men and women, while differences across gen-
ders/sexes and sexual desire facets became apparent. Second,
Fig. 3 Interactions between Gender/Sex and Sexual Orientation. Means of sexual desire scores are shown with 95% confidence intervals as dots
(women) and triangles (men). Please note that the gray lines were added for illustrative purposes, but do not represent data points
Table 4 Descriptive statistics,
T-Test parameters and effect
sizes (Cohen’s d) of the
comparison of SDI-2 scores
between men and women
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). Means, standard deviations, and Welch t-tests for independent samples are each based
on the observation of n = 2618 men and n = 5532 women. *** p < .001
SDI-2 score M (SD)t df Cohen’s d95% CI
Men Women
Total 71.75 (17.30) 61.89 (19.90) 22.86*** 5837.3 0.52 [0.47, 0.56]
Dyadic-P 38.39 (9.78) 35.76 (11.07) 10.86*** 5752.9 0.25 [0.20, 0.29]
Dyadic-A 10.50 (3.71) 8.05 (4.02) 27.05*** 5522.3 0.62 [0.58, 0.67]
Solitary 18.38 (7.41) 14.76 (8.80) 19.35*** 6011 0.43 [0.38, 0.48]
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3775Archives of Sexual Behavior (2022) 51:3765–3789
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average sexual desire was higher among men. Going beyond
previous research, we found that the gender/sex difference
regarding dyadic sexual desire (partner) was smaller than the
difference regarding the other desire facets. Third, remark-
ably little variance in sexual desire was explained despite
the large number of predictors, pointing to the impact of
unknown variables. Below we review the effects of each
predictor in relation to dyadic (partner), dyadic (attractive
other), and solitary sexual desire.
Age Effects
Contrary to our prediction (Hypothesis 1a) and other studies
on sexual desire (e.g., Beutel etal., 2008), we did not find a
general (linear) negative association between age and sex-
ual desire when examined across men and women. Instead,
results are consistent with the studies that found the most
pronounced declines of sexual desire starting at higher age
(i.e., around age 60; Burghardt etal., 2020; DeLamater &
Sill, 2005). Moreover, our findings might reflect a more com-
plex, nonlinear relationship between age and different forms
of sexual desire that varies by gender/sex. Given the small
effect sizes, however, these findings have to be regarded with
caution and further replication attempts should be initiated.
Partly supporting our prediction that women’s sexual
desire would show a zenith in mid-adulthood (Hypothesis
1b), we found significant negative quadratic age trends pre-
dicting all forms of women’s sexual desire. However, patterns
did not exactly meet our age predictions: Whereas women’s
dyadic sexual desire was positively associated with age
until the mid-twenties, it was at a similar level for women
between their mid-twenties and -forties, rather than being
highest among women in their early thirties as predicted by
evolutionary theories (Easton etal., 2010; Schmitt etal.,
2002). Still, this pattern is compatible with the hypothesis
that women’s dyadic sexual desire is heightened during the
life phase where women are most fertile. In addition, it could
be argued that women’s dyadic sexual desire is influenced by
family planning and is highest at ages where many women
wish to become mothers (Levine, 2003). In contrast, women’s
solitary sexual desire was highest among women in their
mid-thirties, negatively associated with age afterward, but
again positively associated with age after age 60. Consistent
with evolutionary hypotheses, this might be understood in
the way that women's solitary sexual desire is less affected
by age-related biological changes than their dyadic sexual
desire. Since solitary sexual activity does not directly relate
to reproduction as partnered sex, women’s solitary sexual
desire might fulfill a different, less age- and fertility-related
function than their dyadic sexual desire. In addition to
these biological factors, solitary sexual desire might be less
affected than dyadic sexual desire by the loss of a partner,
which becomes more likely as people age and is more likely
for women compared to men (Kontula & Haavio-Mannila,
2009).
In contrast to our prediction (Hypothesis 1c), age was nei-
ther negatively nor purely linearly associated with male par-
ticipants’ sexual desire: Trend analyses revealed that men’s
sexual desire followed both a positive linear and a negative
quadratic trend across the different facets of sexual desire. On
average, men’s sexual desire was positively associated with age
until age 40 and illustrated a more complex pattern afterward.
Dyadic (partner) and solitary desire were at a similar level for
men aged between 40 and 60. In contrast, dyadic sexual desire
(attractive person) was negatively associated with age after the
age 40. This age effect on sexual desire relating to an attrac-
tive person might reflect this shift in social needs: According
to socioemotional selectivity theory (Carstensen, 1991), most
Table 5 Descriptive statistics,
T-Test parameters and effect
sizes (Cohen’s d) of the
comparison of SDI-2 scores
between heterosexual and same-
sex attracted individuals by
gender/sex
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996). Means, standard deviations, and Welch t-tests
for independent samples are based on the comparisons between N = 524 same-sex attracted and N = 1815
heterosexual men, and between N = 1076 same-sex attracted and N = 4067 heterosexual women. *p < .05,
**p < .01, ***p < .001
SDI-2 score M (SD)t df Cohen’s d95% CI
Heterosexual Same-sex attracted
Men
Total 71.05 (17.35) 74.44 (16.02) 4.19*** 907.38 0.20 [0.10, 0.30]
Dyadic-P 38.56 (9.74) 38.17 (9.73) − 0.81 849.24 − 0.04 [− 0.14, 0.06]
Dyadic-A 10.43 (3.71) 10.78 (3.55) 2.01* 879.95 0.10 [0.00, 0.19]
Solitary 17.62 (7.51) 20.84 (6.50) 9.63*** 963.31 0.44 [0.34, 0.54]
Women
Total 61.42 (19.19) 65.23 (20.57) 5.47*** 1604.8 0.20 [0.13, 0.26]
Dyadic-P 36.05 (10.59) 35.59 (11.63) − 1.18 1578.3 − 0.04 [− 0.11, 0.02]
Dyadic-A 8.04 (3.97) 8.37 (4.04) 2.42* 1667.0 0.08 [0.02, 0.15]
Solitary 14.07 (8.76) 17.67 (8.29) 12.51*** 1763.9 0.42 [0.35, 0.48]
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3776 Archives of Sexual Behavior (2022) 51:3765–3789
1 3
people have a strong motive for exploration and novel experi-
ences when they are young, but an increasing need for close
and familiar relationships after midlife. Thus, after age 40,
dyadic desire of most men might focus on sex with a commit-
ted romantic partner instead of sex with unfamiliar people.
In sum, our results on age effects point to both similari-
ties and differences between men and women. First, overall,
effects were very small, pointing to a subordinate role of age
in explaining individual differences in sexual desire within
our sample. Second, as reflected by the negative quadratic
effects in our trend analyses, sexual desire might profit from
increases in sexual experience (Hally & Pollack, 1993; Impett
& Tolman, 2006) in both gender/sexes, until other factors,
such as losses of sexual and relationship functioning or
declines in health, cancel these gains (also see Forbes etal.,
2017). Thus, challenging common assumptions (e.g., Barr
etal., 2002; Basson, 2000; Baumeister, 2000), men’s desire,
similar to women’s, might be influenced by a number of life
circumstances instead of being only driven by biological
factors. At the same time, our results pointed to gender/sex
specificities in age effects on sexual desire: First, compared
to women, men might maintain higher sexual desire until
higher ages. Second, the associations between women’s age
and their dyadic and solitary desire might be relatively inde-
pendent from each other, but more parallel in men.
Gender/Sex Effects
As expected (Hypothesis 2a) and consistent with the large body
of previous studies (e.g., Baumeister etal., 2001; Hyde, 2005),
men reported higher dyadic and solitary sexual desire on aver-
age than women. Notably, this effect was smaller for dyadic
sexual desire (partner) compared to all other facets of sexual
desire. Even though we based our prediction on the original
dyadic desire instead of the more specific dyadic desire (part-
ner) scale, this finding supports our prediction that men and
women’s dyadic desire would be more similar than their solitary
desire (Hypothesis 2b). Our results add to the understanding of
gender/sex differences in trait sexual desire, by showing that
difference in dyadic desire might be mainly driven by desire for
attractive others as opposed to desire for a partner.
In sexual strategies theory (Buss & Schmitt, 1993; Gang-
estad & Simpson, 2000), relatively high sexual dyadic desire
(partner) in women could be understood as an adaptation
supporting the goal to find and reproduce with long-term
mates, while the higher dyadic desire (attractive person) in
men could serve the goal to reproduce with more short-term
mates. While evolutionary theory holds little explanation for
the gender/sex effects on solitary sexual desire, both higher
solitary and dyadic (attractive person) desire in men, as well
as relative gender/sex similarity in dyadic desire (partner)
could be explained from social learning theory (Bandura,
1986; Bussey & Bandura, 1999). For women, sexual desire
relating to a partner, compared to desire for masturbation
and sexual activity outside the relationship context, might
be more accepted in society, easier to observe, and more
reinforced. Finally, findings can be interpreted in the context
of social structural theory (Eagly & Wood, 1999). While the
higher societal status of men compared to women is often
replicated in (heterosexual) couple dynamics (KnudsonMar-
tin, 2013), the greater gender/sex similarity in dyadic sexual
(partner) desire might reflect smaller power discrepancies
between genders/sexes within close relationships compared
to other social contexts.
Sexual Orientation Effects
Our prediction regarding the link between sexual orienta-
tion and sexual desire (Hypothesis 3) was partly supported:
same-sex attracted women reported higher levels of solitary
sexual desire than heterosexual women and, contrasting with
our prediction, the same was found for men; the difference
between same gender/sex attracted and heterosexual individu-
als did not hold for dyadic sexual desire in either gender/sex.
These findings correspond with other studies that found higher
level of solitary sexual desire in non-heterosexual compared to
(exclusively) heterosexual participants (Lorenz, 2019; Peixoto,
2019). Notably, Peixoto found higher dyadic desire relating to
an attractive other in gay compared to heterosexual men, but
this finding did not replicate in our study. Therefore, results
suggest that same-sex attraction positively relates to solitary
sexual desire, regardless of gender/sex. One possible expla-
nation for this finding is that same-sex attracted individuals
might spend more time reflecting their own sexuality and are
therefore more aware of their solitary desire. Another possibil-
ity is that same-sex attracted people might be more used to
non-compliance with social norms than heterosexual ones and
therefore less inhibited in reporting solitary desire in spite of the
fact that masturbation is still stigmatized by society. Finally, in
comparison to hetero- and bisexual people, same-sex attracted
individuals (especially when not living in big cities) have access
to a smaller mating pool. If this is true, they might engage in
more solitary sexual activities (see Persson etal., 2016) and
therefore cultivate higher solitary desire. Future research on
sexual orientation effects on sexual desire and how this relates
to dyadic and solitary sexual behavior is required.
Self‑Rated Masculinity Effects
In line with our prediction (Hypothesis 4a), dyadic sexual
desire (both types) was positively related to self-rated mascu-
linity, even though the effect on dyadic desire (attractive per-
son) was not significant below p = 0.001. However, no effect
was found for solitary sexual desire. Since men usually report
higher solitary sexual desire and that corresponding behavior
is more typical and accepted for men than women (Petersen &
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3777Archives of Sexual Behavior (2022) 51:3765–3789
1 3
Hyde, 2011, masculinity could be expected to have a greater
effect on solitary than dyadic sexual desire. Instead, our find-
ings suggest a social role of self-rated masculinity in the con-
text of desire for a sexual partner. In addition, self-rated mascu-
linity did not have a stronger effect on female compared to male
sexual desire, as we had expected (Hypothesis 4b). Instead, the
opposite was true: While no interaction effect occurred in the
case of solitary sexual desire, the effect of self-rated mascu-
linity on dyadic desire was stronger for men. Thus, perceiving
oneself as masculine within a dyadic sexual context might be
mainly relevant for men’s positive sexual experience.
Relationship Status Effects
As predicted (Hypothesis 5a), having a partner positively pre-
dicted dyadic sexual desire (partner) and negatively predicted
solitary sexual desire, even though this effect was not signifi-
cant below p = 0.001. In addition, we found a negative effect
on dyadic desire (attractive person). Our results highlight the
potential effect of life circumstances on sexual desire: People’s
sexual desire might adapt to the given possibilities to act out
their desired sexual activities, with higher dyadic sexual desire
relating to a partner when a partner is also available, and higher
dyadic desire relating to an attractive person and higher solitary
desire when not. Alternatively, people with higher dyadic desire
(partner) might be more likely to enter and stay in a romantic
relationship. Contrasting with our prediction (Hypothesis 5b;
c.f. Kontula & Haavio-Mannila, 2009), we found that the posi-
tive effect of having a partner on dyadic desire (partner) was
weaker for older individuals. Since age was not evenly distrib-
uted across the sample, such that only few older individuals
without a partner (15 out of 65 adults over age 50) participated,
however, power of this interaction effect was probably low and
the finding should be treated with caution. As an alternative
explanation, the negative interaction might reflect that age is
confounded with relationship duration, which was associated
with lower sexual desire (Dawson & Chivers, 2014; Murray
& Milhausen, 2012). Because relationship duration was not
measured in this study, we could not examine this possibility.
Other Effects
Somewhat surprising, self-rated health did not relate to any
of the dyadic sexual desire facets and negatively predicted
solitary sexual desire (c.f., Mitchell etal., 2013). It could be
speculated that these findings reflect that poor health affects
the ability to have partnered sex and that sexual activity out-
side an interpersonal context is more attractive for individuals
not feeling well. However, we did not find a positive effect
of health on dyadic desire, adding no support to the idea that
health might set preferences regarding dyadic versus solitary
sexual activity. Finding little health effects overall might be
due to the fact that health was assessed in relation to the
participants’ perception of other people’s health. This way,
it is unclear who the participants referred to and what their
actual, objective health status was. Nonetheless, the measure
should reflect subjective well-being to some degree.
While self-rated attractiveness was positively related to most
types of sexual desire, it did not predict any outcomes in the full
models. This is surprising since previous studies found positive
effects of related variables, such as sexual self-esteem (Kontula
& Haavio-Mannila, 2009) and positive body image (Koch etal.,
2005; Seal etal., 2009). Therefore, we assume shared variance
with other predictors of sexual desire included in this study:
In both genders/sexes, self-rated attractiveness was related to
health and, in men, it was additionally related to masculin-
ity. The lack of self-rated attractiveness effects could not be
explained by gender/sex differences either: Descriptively, self-
rated attractiveness had a more pronounced effect on female
sexual desire, but these effects were small and not significant.
Strengths andLimitations
The current study had several strengths. First, we pursued a
high degree of transparency and reduced researcher degrees
of freedom (e.g., Nosek etal., 2015; Wicherts etal., 2016)
by preregistering our hypotheses and analyses. Second, our
sample was large, enabling us to test our hypotheses with
sufficient power, and relatively diverse with regard to age
and different sexual orientations. Third, the use of nonlinear
trend analyses shed new light on previously oversimplified
age effects on men and women’s sexual desire. Finally, by
differentiating across dyadic (partner), dyadic (attractive per-
son), and solitary sexual desire, we provide nuanced insights
into different aspects of sexual desire that match the fac-
tor structure of our data and keep up with current standards
on sexual desire measured with the SDI-2 (e.g., Mark etal.,
2018; Moyano etal., 2017; Vallejo-Medina etal., 2020).
Our study also had some limitations. First, the cross-
sectional design of the study cannot address age effects on
sexual desire that may be due to cohort effects. In a study
covering the years 2000–2018, Ueda etal. (2020) found that
sexual inactivity increased among young adults. Similarly, age
effects on sexual desire found in this study might reflect that
participants in the mid-age range show higher sexual desire
than those born before or after independent from age. There-
fore, it would be helpful to track individual trajectories of age-
associated changes in sexual desire in a longitudinal design.
Second and related to the first limitation, the correlational
nature of our data did not allow for causal conclusions, even
though some directions of influence (i.e., influence from bio-
logical and psychosocial predictors on sexual desire) seem
more likely than others. By examining the effects of previously
assessed variables on sexual desire at later measurements, a
longitudinal study design would address this limitation, too.
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3778 Archives of Sexual Behavior (2022) 51:3765–3789
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A third limitation pertains to the exclusive use of self-
reports. Self-reports can be biased by effects of social desir-
ability. For example, women are known to underreport sexual
motivation, thoughts, and behavior more frequently than men
(Petersen & Hyde, 2011). At the same time, self-reports are
the best way to assess an individual’s subjective experience
and therefore essential for the assessment of sexual desire.
Future studies could include measures of social desirability
(e.g., Stöber, 2001) to control for potential biases.
Finally, very little variance was explained in our analyses.
As a possible explanation, there are numerous variables poten-
tially relevant to sexual desire, such as frequency of sexual
intercourse (Kontula & Haavio-Mannila, 2009) or relation-
ship satisfaction (Brezsnyak & Whisman, 2004; Davies etal.,
1999) that remained unconsidered. In addition, many of the
included variables might have been assessed in too unspecific
ways to explain individual differences in sexual desire. For
example, relationship status did not inform about relationship
length, a factor that has been negatively associated with sexual
desire in previous research (Dawson & Chivers, 2014; Murray
& Milhausen, 2012). Similarly, single items have proven as
useful measures for self-rated masculinity, attractiveness, and
health when studying mate preferences (e.g., Feinberg etal.,
2012; Kandrik & DeBruine, 2012), but are likely insufficient
to capture more complex aspects of these constructs that might
relate to sexual desire. In future studies on sexual desire, more
and more detailed measures of variables relevant to a person’s
romantic relationships and identity should be included.
Concluding Remarks
Sexual desire represents an essential component of human
sexuality, but relatively little is known about the exact nature
of age effects on sexual desire. In this study, we found evidence
for both differences and similarities between the sexual desire
of men and women and corresponding age effects. While men
showed higher sexual desire levels on average, sexual desire
was highest among middle-aged individuals in both genders/
sexes. Generally, study results are compatible with the hypoth-
esis that women experience their highest levels of sexual desire
during fertile years, (Easton etal., 2010; Schmitt etal., 2002).
Furthermore, they suggest that both men and women’s sexual
desire levels and corresponding age effects relate to a wide
array of biological and psychosocial variables. Facing the
small portions of variance explained, it is suggested that addi-
tional variables, that were not included in the study—such as
relationship length (Dawson & Chivers, 2014) and satisfac-
tion (Davies etal., 1999)—might play an important role as
well. In these terms, women’s and men’s sexual desire may be
more similar than many commonly believe. Differentiating
between dyadic sexual desire relating to a partner and to an
attractive person provided valuable and nuanced insights into
effects of age, gender/sex, and relationship status on sexual
desire. Therefore, we recommend that researchers measuring
sexual desire with the SDI-2 should consider using the facets
suggested by Moyano etal. (2017). Moreover, future studies
should assess sexual desire longitudinally and include relation-
ship-specific measures, as well as more nuanced measures of
health and aspects relating to a person’s self-concept.
Appendix A
Originally, Spector etal. (1996) conceptualized the SDI-2 with
two subfacets named dyadic sexual desire and solitary sexual
desire. In a recent study however, Moyano etal. (2017) recom-
mend further splitting the dyadic sexual desire scale, resulting
in three subscales of the questionnaire. Even though we had
already preregistered our hypotheses and conducted the corre-
sponding analyses based on the original facets by Spector and
colleagues, we wished to examine which model—two or three
factors—fitted our data best before proceeding to hypothesis
testing. Table6 provides an overview over the SDI-2 items and
their assignment to the original scales (Spector etal., 1996)
or the scales suggested by Moyano etal. (2017), using a two-
factor or a three-factor structure, respectively.
In order to determine, which of these structures provides
a better fit for our data, we conducted a set of confirmatory
factor analyses (CFAs) using the R package lavaan (Rosseel,
2012). Scale reliability measures were calculated using the
package userfriendlyscience (Peters, 2014). In CFA, a critical
concern is whether factors represent meaningful, distinguish-
able constructs or method effects (Marsh, 1996): While previ-
ous research (e.g., Mark etal., 2018) conceptualizes dyadic
desire (partner) and dyadic desire (attractive person) as sub-
stantial factors, distinguishable components in CFA might
simply reflect the fact that these items share common wording
(i.e., “a partner” versus “an attractive person”). To investigate
this possibility, we conducted total of four CFAs. First, we
specified two simple models defining either a two- or three-
factor structure. Second, for each of these factor solutions,
we specified an additional model, which included autocor-
relations of the items sharing common wording in order to
represent potential method effects(see Marsh, 1996). The fit
indices of all four models are shown in Table7. As can be
seen, model fit indices improved (a) by including autocorrela-
tions and (b) by distinguishing between three instead of two
factors. Factor loadings and internal consistencies of the two-
factor and three-factor solutions including autocorrelations
of items with shared wording can be found in Tables8 and 9.
Comparing both of these models, likelihood ratio test indi-
cated a significantly better fit for the model with a three-factor
structure compared to the model with a two-factor structure
(χ2Diff (2) = 389.04, p < 0.001). Thus, even after controlling
for a method effect, our results suggested that a differentiation
between two different dyadic facets—dyadic desire (partner)
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3779Archives of Sexual Behavior (2022) 51:3765–3789
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and dyadic desire (attractive person)—and solitary desire,
resulting in a total of three sexual desire facets, would be
more appropriate for analyzing our data.
See Tables6, 7, 8, and 9.
Table 6 Items and descriptive statistics of the SDI-2
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); Means and standard deviations are based on N = 8150 observations. The factors indi-
cated in the rows resemble the original structure with two factors. For each of the dyadic items, upper case letters indicate to which of the scales
it is assigned when applying the three-factor structure (P = partner; A = attractive person)
Factors and Items M (SD)
Dyadic desire
1. During the last month, how often would you have liked to engage in sexual activity with a partner (for example, touching each
other’s genitals, giving or receiving oral stimulation, intercourse, etc.)? P4.77 (1.88)
2. During the last month, how often have you had sexual thoughts involving a partner? P4.71 (1.98)
3. When you have sexual thoughts, how strong is your desire to engage in sexual behavior with a partner? P5.71 (1.87)
4. When you first see an attractive person, how strong is your sexual desire? A4.12 (2.21)
5. When you spend time with an attractive person (for example, at work or school), how strong is your sexual desire? A4.72 (2.19)
6. When you are in romantic situations (such as candle-lit dinner, a walk on the beach, etc.), how strong is your sexual desire? P5.35 (2.06)
7. How strong is your desire to engage in sexual activity with a partner? P6.12 (1.94)
8. How important is it for you to fulfill your sexual desire through activity with a partner? P5.24 (2.30)
9. Compared to other people of your age and sex, how would you rate your desire to behave sexually with a partner? P4.70 (2.11)
Solitary desire
10. During the last month, how often would you have liked to behave sexually by yourself (for example, masturbating, touching
your genitals, etc.)?
3.78 (2.22)
11. How strong is your desire to engage in sexual behavior by yourself? 4.18 (2.39)
12. How important is it for you to fulfill your desires to behave sexually by yourself? 3.92 (2.62)
13. Compared to other people of your age and sex, how would you rate your desire to behave sexually by yourself? 4.04 (2.35)
No factor (item adds to total desire only)
14. How long could you go comfortably without having sexual activity of some kind? 3.70 (1.90)
Table 7 Model fits of different
factor solutions with the SDI-2
items
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); Confirmatory factor analysis (CFA) was based on
N = 8150 observations and estimated using maximum likelihood method. *** p < .001
Model Model fit
χ2Df CFI TLI RMSEA SRMR
1. Two factors, no autocorrelation 8664.475*** 64 .863 .833 .128 .078
2. Two factors, autocorrelation 2921.760*** 58 .954 .939 .078 .061
3. Three factors, no autocorrelation 3993.944*** 62 .937 .921 .088 .049
4. Three factors, autocorrelation 2532.723*** 56 .961 .945 .074 .046
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3780 Archives of Sexual Behavior (2022) 51:3765–3789
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Appendix B
In the following, we report all results from the main article
including the original dyadic desire scale (Spector etal., 1996).
See Tables10, 11, 12, 13 and 14.
Table 8 Factor loadings and internal consistencies of the two-factor
solution with the SDI-2 items
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996). The con-
firmatory factor analysis was based on N = 8150 observations and
estimated using maximum likelihood method. Item 14 was not
included in the model because it is a part of the total desire score but
not of one of the desire subscales. Internal consistencies are given as
Cronbachs’s α, total omega ω, and greatest lower bound (GLB)
Factors and items Loadings (SE) Stand. loadings α ω GLB
Dyadic desire .88 .88 .88
1 1.31 (.02) 0.70
2 1.26 (.02) 0.64
3 1.42 (.02) 0.76
4 1.13 (.02) 0.51
5 1.14 (.02) 0.52
6 1.16 (.02) 0.56
7 1.67 (.02) 0.86
8 1.57 (.02) 0.68
9 1.66 (.02) 0.79
Solitary desire .91 .92 .93
10 1.71 (.02) 0.77
11 2.19 (.02) 0.92
12 2.26 (.02) 0.86
13 2.04 (.02) 0.86
Table 9 Factor loadings and
internal consistencies of the
three-factor solution with the
SDI-2 items
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996). The confirmatory factor analysis was based on
N = 8150 observations and estimated using maximum likelihood method. Item 14 was not included in the
model because it is a part of the total desire score but not of one of the desire subscales. Internal consist-
encies are given as Cronbachs’s α, total omega ω, and greatest lower bound (GLB). For the dyadic desire
(attractive person) scale, no ω and GLB could be calculated because it consists of too few items
Factors and items Loadings (SE) Stand. loadings α ω GLB
Dyadic desire (partner) .88 .88 .89
1 1.32 (.02) 0.70
2 1.26 (.02) 0.64
3 1.42 (.02) 0.76
6 1.15 (.02) 0.56
7 1.69 (.02) 0.87
8 1.59 (.02) 0.69
9 1.67 (.02) 0.79
Dyadic desire (attractive person) .84
4 1.87 (.02) 0.85
5 1.88 (.02) 0.86
Solitary desire .91 .92 .93
10 1.71 (.02) 0.77
11 2.19 (.02) 0.92
12 2.26 (.02) 0.86
13 2.04 (.02) 0.86
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3781Archives of Sexual Behavior (2022) 51:3765–3789
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Table 10 Descriptive statistics
and intercorrelations of the
continuous study variables by
gender/sex
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). All measures were assessed via self-reports. Correlations in bold font are significant
(p < .001, two-tailed). a Self-rated
M SD Intercorrelations N
1 2 3 4 5 6 7 8
Men
1. Age 27.34 9.48 2618
2. SDI: Total 71.75 17.30 .12 2618
3. SDI: Dyadic 48.89 12.17 .10 .90 2618
4. SDI: Dyadic-P 38.39 9.78 .09 .85 .97 2618
5. SDI: Dyadic-A 10.50 3.71 .08 .69 .73 .53 2618
6. SDI: Solitary 18.38 7.41 .10 .72 .35 .30 .34 2618
7. Attractivenessa4.62 1.29 − .02 .10 .14 .14 .09 − .01 1525
8. Masculinitya4.12 1.34 .13 .14 .22 .22 .14 − .04 .31 1525
9. Healtha4.65 1.41 .02 .02 .08 .08 .05 − .10 .42 .33 1239
Women
1. Age 23.74 6.75 5532
2. SDI: Total 61.89 19.90 .03 5532
3. SDI: Dyadic 43.81 13.37 − .01 .90 5532
4. SDI: Dyadic-P 35.76 11.07 − .00 .86 .96 5532
5. SDI: Dyadic-A 8.05 4.02 − .03 .62 .67 .45 5532
6. SDI: Solitary 14.76 8.80 .06 .76 .42 .38 .33 5532
7. Attractivenessa4.48 1.29 .04 .17 .18 .17 .12 .08 3530
8. Masculinitya3.08 1.53 .02 .05 .01 − .01 .04 .09 − .06 3510
9. Healtha4.17 1.34 .02 .01 .06 .06 .03 − .06 .36 − .04 3168
Table 11 Coefficients of the
multiple regression models (full
models) predicting the SDI-2
scores
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). Multiple regression models (full models) are each based on N = 2744 observations. Par-
ticipant gender, relationship status, and sexual orientation were factor coded (0 = male, 1 = female; 0 = het-
erosexual, 1 = same-sex attracted; 0 = single, 1 = in a committed relationship). All continuous variables
were z-standardized. Negative estimates indicate lower scores for women compared to men, for same-sex
attracted compared to heterosexual people, and for people having a partner compared to singles. aSelf-
rated. *p < .05, **p < .01, ***p < .001
SDI-2 score
Predictor Total Dyadic Dyadic-P Dyadic-A Solitary
Age .10** .09** .11*** − .00 .09**
Gender/sex –.31*** –.20*** –.07 − .46*** − .28***
Sexual orientation .31*** .16* .15 .13 .42***
Masculinitya.18*** .22*** .21*** .17*** .06
Relationship status .13*** .22*** .33*** − .16*** − .11**
Health a − .03 .01 .02 − .03 − .08***
Attractivenessa.08* .07* .06 .04 .07*
Age × relationship status − .09* − .13** − .16*** .02 .01
Gender/sex × Attractivenessa.07 .08 .08* .04 .03
Gender/sex × Masculinity a − .13** − .22*** − .21*** − .14** .04
Gender/sex × Sex. or ientation − .15 − .18 − .21* − .03 − .03
Adj. R2.081 .071 .071 .090 .078
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3782 Archives of Sexual Behavior (2022) 51:3765–3789
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Table 12 Polynomial trends of sexual desire among men and women
SDI-2 = Sexual Desire Inventory-2 (Spector et al., 1996); dyadic-
P = dyadic (partner); dyadic-A = dyadic (attractive person). Polyno-
mial regression models are each based on the observation of n = 2618
men and n = 5532 women. All variables were z-standardized.
*p < .05, **p < .01, ***p < .001
Trend Men Women
SDI-2 score: Total
Age 6.31*** 1.95
Age2 − 5.36*** − 5.71***
Age31.41 2.62**
Adj. R2.026 .007
SDI-2 score: Dyadic
Age 4.99*** − 0.42
Age2 − 4.07*** − 4.33***
Age31.82 0.75
Adj. R2.016 .003
SDI-2 score: Dyadic-P
Age 4.62*** 0.22
Age2 − 3.63*** − 4.19***
Age32.27* 0.42
Adj. R2.014 .003
SDI-2 score: Dyadic-A
Age 4.18*** − 2.00*
Age2 − 3.78*** − 2.86**
Age3 − 0.29 1.35
Adj. R2.011 .002
SDI-2 score: Solitary
Age 5.17*** 4.47***
Age2 − 4.59*** − 5.54***
Age30.38 4.08***
Adj. R2.017 .012
Table 13 Descriptive statistics,
T-Test parameters and effect
sizes (Cohen’s d) of the
comparison of SDI-2 scores
between men and women
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). Means, standard deviations, and Welch t-tests for independent samples are each based
on the observation of n = 2618 men and n = 5532 women. *** p < .001
SDI-2 score M (SD)t df Cohen’s d95% CI
Men Women
Total 71.75 (17.30) 61.89 (19.90) 22.86*** 5837.3 0.52 [0.47, 0.56]
Dyadic 48.88 (12.17) 43.81 (13.37) 17.03*** 5597.8 0.39 [0.34, 0.44]
Dyadic-P 38.39 (9.78) 35.76 (11.07) 10.86*** 5752.9 0.25 [0.20, 0.29]
Dyadic-A 10.50 (3.71) 8.05 (4.02) 27.05*** 5522.3 0.62 [0.58, 0.67]
Solitary 18.38 (7.41) 14.76 (8.80) 19.35*** 6011 0.43 [0.38, 0.48]
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3783Archives of Sexual Behavior (2022) 51:3765–3789
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Appendix C
In our preregistration, we conducted a number of analyses
testing hypotheses, which are not presented in the main arti-
cle. First, we hypothesized that men would perceive their
own attractiveness more positively than women. Second,
we expected that self-rated attractiveness would partly
explain the gender/sex difference in sexual desire (partial
mediation). Likewise, we expected that self-rated masculin-
ity would partly explain the gender/sex difference in sexual
desire (partial mediation). Finally, we conducted explora-
tory analyses testing whether hormonal contraception affects
the sexual desire of women prior menopause. In the follow-
ing, we present the results of the tests corresponding to each
of these hypotheses for all sexual desire scales (i.e., total,
dyadic, dyadic (partner), dyadic (attractive person), and soli-
tary sexual desire).
See Tables15, 16 and 17.
Table 14 Descriptive statistics,
T-test parameters and effect
sizes (Cohen’s d) of the
comparison of SDI-2 scores
between heterosexual and same-
sex attracted individuals by
gender/sex
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996). Means, standard deviations, and Welch t-tests for
independent samples are based on the comparisons between N = 524 same-sex attracted and N = 1815 het-
erosexual men, and between N = 1076 same-sex attracted and N = 4067 heterosexual women
* p < .05, ***p < .001
SDI-2 score M (SD)t df Cohen’s d95% CI
Heterosexual Same-sex attracted
Men
Total 71.05 (17.35) 74.44 (16.02) 4.19*** 907.38 0.20 [0.10, 0.30]
Dyadic 48.99 (12.14) 48.96 (11.87) − 0.05 863.84 − 0.00 [− 0.10, 0.09]
Dyadic-P 38.56 (9.74) 38.17 (9.73) − 0.81 849.24 − 0.04 [− 0.14, 0.06]
Dyadic-A 10.43 (3.71) 10.78 (3.55) 2.01* 879.95 0.10 [0.00, 0.19]
Solitary 17.62 (7.51) 20.84 (6.50) 9.63*** 963.31 0.44 [0.34, 0.54]
Women
Total 61.42 (19.19) 65.23 (20.57) 5.47*** 1604.8 0.20 [0.13, 0.26]
Dyadic 44.09 (12.77) 43.96 (14.07) − 0.27 1575 − 0.01 [− 0.08, 0.06]
Dyadic-P 36.05 (10.59) 35.59 (11.63) − 1.18 1578.3 − 0.04 [− 0.11, 0.02]
Dyadic-A 8.04 (3.97) 8.37 (4.04) 2.42* 1667.0 0.08 [0.02, 0.15]
Solitary 14.07 (8.76) 17.67 (8.29) 12.51*** 1763.9 0.42 [0.35, 0.48]
Table 15 Coefficients of the
mediation analyses: gender/sex–
self-rated attractiveness–sexual
desire and sobel tests (Z-values)
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). Simple and multiple regressions are each based on N = 5055 observations from par-
ticipants that rated their attractiveness. Gender/sex was factor coded (0 = male, 1 = female). All continuous
variables were z-standardized. aSelf-rated. **p < .01, ***p < .001
Step 1: Regression of gender/sex on self-rated attractiveness: .11***
Step 2–4: Regressions on sexual desire
Predictor SDI-2 score
Total Dyadic Dyadic-P Dyadic-A Solitary
Step 2: Gen-
der/sex
− .48*** − .36*** − .23*** − .57*** − .41***
Step 3–4:
Gender/sex
− .47*** − .34*** − .21*** − .56*** − .41***
Attractivenessa.15*** .17*** .16*** .11*** .06***
Sobel test − 3.34*** − 3.38*** − 3.37*** − 3.21** − 2.69**
Mediation (%) 3 5 8 2 2
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3784 Archives of Sexual Behavior (2022) 51:3765–3789
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Appendix D
See Figs.4 and 5.Tables18 and 19.
Table 16 Coefficients of the
mediation analyses: gender/
sex–self-rated masculinity–
sexual desire and Sobel Tests
(Z-values)
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996); dyadic-P = dyadic (par tner); dyadic-A = dyadic
(attractive person). Simple and multiple regressions are each based on N = 5035 observations from partici-
pants that rated their masculinity. Gender/sex was factor coded (0 = male, 1 = female). All continuous vari-
ables were z-standardized. aSelf-rated. ***p < .001
Step 1: Regression of gender/sex on self-rated masculinity: .67***
Step 2–4: Regressions on sexual desire
Predictor SDI-2 score
Total Dyadic Dyadic-P Dyadic-A Solitary
Step 2: Gen-
der/sex
− .48*** − .36*** − .23*** − .59*** − .41***
Step 3–4:
Gender/sex
− .43*** − .32*** − .19*** − .53*** − .37***
Masculinitya.07*** .06*** .05*** .06*** .06***
Sobel test − 5.06*** − 4.17*** − 3.49*** − 4.34*** − 4.24***
Mediation (%) 10 11 15 7 10
Table 17 Simple regressions predicting total SDI-2 scores in a sub-
sample of women prior menopause
SDI-2 = Sexual Desire Inventory-2 (Spector et al., 1996); dyadic-
P = dyadic (partner); dyadic-A = dyadic (attractive person). Simple
regressions are each based on N = 1200 (n = 809 women without and
n = 391 women with hormonal contraception) observations from
female participants that indicated their use of hormonal contracep-
tion. Hormonal contraception was factor coded (0 = no use, 1 = use).
All continuous variables were z-standardized
Predictor SDI-2 score
Total Dyadic Dyadic-P Dyadic-A Solitary
Hormonal
contracep-
tion
−.04 .02 .08 −.13 −.16
P-value .483 .669 .187 .035 .009
Fig. 4 Interactions between Age and Relationship Status. The black
lines each represent the simple slopes derived from the correspond-
ing regression model (without control variables) for people without
(dashed) and with (solid) a current romantic relationship. The gray
area depicts the corresponding 95% confidence bands
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3785Archives of Sexual Behavior (2022) 51:3765–3789
1 3
Fig. 5 Interactions between Self-Rated Masculinity and Gender/Sex.
The black lines each represent the simple slopes derived from the
corresponding regression model (without control variables) for men
(dashed) and women (solid). The gray area depicts the corresponding
95% confidence bands
Table 18 Simple regressions predicting total SDI-2 scores
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996). Participant
gender/sex, relationship status, and sexual orientation were factor
coded (0 = male, 1 = female; 0 = single, 1 = in a committed relation-
ship; 0 = heterosexual, 1 = same-sex attracted). All continuous vari-
ables were z-standardized. **p < .01, ***p < .001
Predictor NEffect on total desire Adj. R2
Gender/sex 8150 − .50*** .058
Age 8150 .11*** .011
Self-rated attractiveness 5054 .16*** .024
Self-rated masculinity 5036 .13*** .018
Self-rated health 4407 .05** .002
Relationship status 4711 .12*** .003
Sexual orientation 7482 .20*** .007
Table 19 Linear age trends predicting the SDI-2 scores
SDI-2 = Sexual Desire Inventory-2 (Spector etal., 1996). All continu-
ous variables were z-standardized
* p < .05, **p < .01, ***p < .001
Men Women
Outcome: SDI-2 score Age Trend Adj. R2Age Trend Adj. R2
Total .12*** .015 .03 .001
Dyadic (Partner) .09*** .008 .00 − .000
Dyadic (Attractive
Person)
.08*** .006 − .03* .001
Solitary .10*** .010 .06*** .003
Appendix E
See Tables20.
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3786 Archives of Sexual Behavior (2022) 51:3765–3789
1 3
Authors' contributions LLW, MC, MAK, and BCJ carried out con-
ceptualization; LLW, MC, and BCJ took part in methodology; LLW
conducted formal analysis; LMD and BCJ performed investigation;
LLW and MC wrote and prepared the original draft; LLW, MC, MAK,
LMD, and BCJ were involved for writing, reviewing, and editing; LMD
and BCJ were responsible for resources; MC supervised the study. All
authors read and approved the final manuscript.
Funding Open Access funding enabled and organized by Projekt
DEAL. No funding was received for conducting this study.
Data Availability On our OSF page (https:// osf. io/ rba2x), we publish
all data necessary to reproduce reported results and provide scripts
for all data analyses reported in this manuscript. In addition, we share
a complete list with item wordings and response formats used in the
current study at OSF.
Declarations
Conflict of interest The authors have no known conflict of interest to
disclosure.
Ethical Approval The College of Science and Engineering ethics com-
mittee at the University of Glasgow has approved data collection.
Consent to Participate Informed consent was obtained from all subjects
involved in the study.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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Article
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The Sexual Desire Inventory (SDI; Spector, Carey, & Steinberg, 1996) is one of the most popular scales used to measure dyadic and solitary sexual desire. Research on sexual desire has primarily focused on heterosexual cisgender experiences, and the SDI has not been validated in lesbian, gay, bisexual, trans, or queer (LGBTQ) populations. To address the dearth of research using the SDI on LGBTQ populations, the primary aim of this study was to examine the internal structure of the SDI by examining and comparing the fit of the original 2-factor structure suggested by Spector et al. (1996) with a 3-factor structure found by Moyano, Vallejo-Medina, & Sierra, (2017) in a sample of LGBTQ adults. The secondary aim of this study was to provide convergent evidence of validity for SDI scores. Findings provide evidence for a 3-factor structure solution of the SDI: (1) dyadic sexual desire for partner, (2) solitary sexual desire, and (3) dyadic sexual desire for attractive other. These findings are consistent with the structure reported by Moyano and colleagues (2017). Convergent validity with the SDI and the Hurlbert Index of Sexual Desire (Apt & Hurlbert, 1992) and Global Measure of Sexual Satisfaction (Lawrance & Byers, 1995) was also established. Results provide new information on the appropriateness of a 3-factor structure for using the SDI in an adult LGBTQ sample. The need for additional research on the SDI is discussed.
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While sexual frequency and satisfaction are strong contributors to the quality and longevity of romantic relationships and overall well-being, mismatches in sexual desire between partners are common and have been linked with poorer satisfaction. Previous findings linking mismatches in desire with poorer relationship and sexual outcomes have typically been derived using difference scores, an approach that does not account for partners’ overall levels of desire. In a sample of 366 couples, we investigated whether partners who match in desire are more satisfied than desire-discrepant couples. Results of dyadic response surface analyses provided no support for a unique matching effect. Higher desire rather than matching in desire between partners predicted relationship and sexual satisfaction. These findings shed new light on whether the correspondence between partners’ levels of sexual desire is associated with satisfaction and suggest the need to focus on sustaining desire and successfully navigating differences rather than promoting matching in desire.
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Sexual desire is a cognitive and affective state that motivates an individual to engage in sexual activity. There are no validated measures to assess this construct in Colombia. The present study aimed to validate the Sexual Desire Inventory (SDI) and explore gender-and age-based differences in sexual desire in Colombian population. The sample was composed of 2,125 men and women who answered the Colombian version of the SDI. Results indicated strict invariance between genders, a three-dimension model, and acceptable validity and reliability indicators. Gender-based and age-based differences were observed in the three types of sexual desire. Implications and conclusions of these findings are presented.
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Objective: To assess differences in sexual wellbeing among men and women with exclusively heterosexual, mostly heterosexual, and bisexual attractions. Method: An anonymous online survey in a convenience sample of 597 young adults (394 women, 203 men; average age = 20.04) assessed patterns of sexual attraction, desire, sexual functioning, and sexual satisfaction using validated questionnaires. Results: Individuals with mostly heterosexual attractions reported significantly higher solitary sexual desire than exclusively heterosexual individuals (women: d = 0.64; men: d = 0.68). Partnered sexual desire did not differ between groups. Women with exclusively heterosexual attractions reported significantly higher sexual functioning and satisfaction than either mostly heterosexual or bisexually attracted women (functioning: d = 0.29; satisfaction: d = 0.47). Men with mostly heterosexual attractions reported significantly lower sexual functioning than either exclusively heterosexual or bisexually attracted men (d = 0.40). Conclusions: There were significant differences between exclusively vs. mostly heterosexual individuals in several aspects of sexual wellbeing, supporting the assertion that mostly heterosexual may constitute a distinct orientation. Taken together with prior research showing higher rates of sexual dysfunction in bisexual women, these findings highlight sexual health disparities among nonmonosexual women. Efforts to support the sexual wellbeing of sexual minority individuals should include consideration of mostly heterosexual individuals, as this population may have unique sexual health needs.
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Research on male sexual desire and satisfaction, according to sexual orientation remains insufficient. An online-survey was fulfilled by 415 men (142 gay; 273 heterosexual), and participants completed the SDI-2 and the GMSEX. Main findings suggested that gay men scored significantly higher on both solitary sexual desire and attractive person-related dyadic sexual desire subscales, but not on partner-related dyadic sexual desire subscale, compared to heterosexual men. Despite sexual orientation, partner-related dyadic sexual desire positively predicts sexual satisfaction, whereas solitary and attractive person-related dyadic sexual desire negatively predicts sexual satisfaction in men. Overall, gay men appear to experience higher levels of both attractive person-related dyadic and solitary sexual desire. Also, experiencing sexual desire towards a partner predicts positively, whereas experiencing desire to engage in sexual behavior with oneself and towards an attractive person predict negatively sexual satisfaction in men.