An Exploration of Individual Differences in Human Mating Preferences and Competitive
Tactics
Danielle Leigh Wagstaff
BSc (Newcastle); BPsyc (Hons 1) (Newcastle)
Submitted in fulfilment of the requirements for
Doctor of Philosophy
December, 2016
University of Newcastle, Australia INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Statement of Originality
This thesis contains no material which has been accepted for the award of any other
degree or diploma in any university or other tertiary institution and, to the best of my
knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text. I give consent to the final version of my thesis being made available worldwide when deposited in the University’s
Digital Repository**, subject to the provisions of the Copyright Act 1968.
**Unless an embargo has been approved for a determined period.
Signed,
Danielle Wagstaff
ii INDIVIDUAL DIFFERENCES IN MATING PREFERENCES
Statement of Authorship
I hereby certify that the work embodied in this thesis contains a published paper of which I am a joint author. I have included as part of this thesis a written statement, endorsed by my supervisor, attesting to my contribution to the joint publication.
Signed,
Danielle Wagstaff
iii INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Acknowledgements
To Darren, Dani and Bill. Each of you were unconditionally supportive and encouraging, always approached my emotional breakdowns with a solution, and encouraged me the many times I lost my way. You are all impressively motivated, your work ethic and intelligence always push me to work harder. More than supervisors, you have been mentors, colleagues and friends, and you have each armed me with the skills I need to succeed. To my fellow PhD candidates / caffeine addicts / HP fanatics. Thank you for sharing your homes, your beds, your laughter and tears, for feeding and clothing me, sharing many a drink with me, and being nothing but supportive. Christy and Jane, I look forward to many more years of travel, laughter, and champagne with you both. To my family. Thank you for supporting me through decades of education. You never questioned my decision to complete a doctorate, and I would not be here without all your encouragement and support. Special mention to all my colleagues at FedUni, I would not have finished my thesis without your support. I have learned so much in this past year, and I am grateful to have the opportunities you have provided me. Most importantly, to my wonderful husband. I could not ask for a more loving and supportive partner and I cannot thank you enough for your unwavering belief in my ability. Words cannot describe how grateful I am to have you by my side, and I am excited for the next chapter of our lives to begin.
iv INDIVIDUAL DIFFERENCES IN MATING PREFERENCES
Table of Contents Statement of Originality ...... ii
Statement of Authorship ...... iii
Acknowledgements ...... iv
List of Tables ...... xi
List of Figures ...... xii
Abstract ...... xiv
Chapter 1: General Introduction ...... 1
1.1 Thesis Aims and Chapter Overview ...... 1
1.2 Understanding Mating Strategies as Evolved Adaptations ...... 2
1.3 Sexual Strategies Theory and Strategic Pluralism ...... 4
1.3.1 The Developmental Trajectory of Mating Behaviour ...... 7
1.4 How Do We Judge Mate Quality? ...... 9
1.4.1 Why Faces Are So Special ...... 13
1.5 Mate Competition ...... 17
1.6 Assortative Mating ...... 19
1.7 The Role of Hormones in Mating Psychology ...... 22
1.7.1 The Cycle-Shift Hypothesis ...... 23
1.8 Thesis Structure and Research Questions ...... 26
1.9 Common Measurement Tools ...... 28
1.9.1 Sexual Orientation Scale ...... 28
1.9.2 Hormonal Details ...... 29
1.9.3 Socio-Sexual Orientation Inventory ...... 29
1.9.4 Mate Value Inventory ...... 30
1.9.5 Mating Intelligence Scale ...... 30
1.10 References ...... 32
v INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Chapter 2: Sex Differences in Importance of Faces or Bodies in Mating Decisions.49
2.1 Chapter Overview ...... 50
2.2 Introduction...... 50
2.2.1 Attention Allocation Between the Sexes ...... 50
2.2.2 Contextual Factors Influencing Allocation of Attention ...... 53
2.2.3 Cross-Sex Awareness of Cue Preferences ...... 55
2.2.4 Current Study ...... 55
2.3 Methods ...... 56
2.3.1 Participants ...... 56
2.3.2 Materials and Procedure ...... 57
2.4 Results ...... 58
2.4.1 Sex Differences in Box Choice ...... 58
2.4.2 Sex Differences in Importance of Information from Body versus Face ...... 58
2.4.3 Correlations Between Body Priority Ratings and SOI-R, MIS, and MVI-S ...... 59
2.4.4 Opposite-Sex awareness of Face/Body Preferences ...... 59
2.5 Discussion ...... 64
2.6 References ...... 68
Chapter 3: Further Exploration of Men’s Attention Allocation to Women’s Faces or
Bodies ...... 74
3.1 Chapter Overview ...... 74
3.2 Introduction...... 74
3.2.1 Current Study ...... 77
3.3 Methods ...... 78
3.3.1 Participants ...... 78
3.3.2 Stimuli ...... 79
3.3.3 Apparatus ...... 80
vi INDIVIDUAL DIFFERENCES IN MATING PREFERENCES
3.3.4 Procedure ...... 80
3.3.5 Eye-Tracking Analysis ...... 81
3.4 Results ...... 81
3.4.1 Contextual Effects on Eye-Tracking ...... 81
3.4.2 Mating Motivations ...... 83
3.5 Discussion ...... 84
3.6 References ...... 88
Chapter 4: Women’s Dress Choice Across the Menstrual Cycle ...... 91
4.1 Chapter Overview ...... 91
4.2 Introduction ...... 91
4.3 Method ...... 95
4.3.1 Participants ...... 95
4.3.2 Materials ...... 95
4.3.3 Procedures ...... 96
4.3.4 Skin Exposure and Clothing Analysis ...... 96
4.3.5 Independent Ratings of Full-Body Images ...... 96
4.3.6 Hormone Analysis ...... 97
4.4 Results ...... 98
4.4.1 Within-Cycle Change in Hormone Levels ...... 98
4.4.2 Within-Cycle Change in Skin Exposure ...... 98
4.4.3 Independent Ratings Analysis ...... 100
4.4.5 Mating Behaviour Scores Between Individuals ...... 101
4.5 Discussion ...... 101
4.6 References ...... 108
Chapter 5: Women’s Perfume Use as a Potential Cue to Mating Motivation ...... 111
5.1 Chapter Overview ...... 111
vii INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
5.2 Introduction...... 111
5.3 Methods ...... 114
5.3.1 Participants ...... 114
5.3.2 Materials and Procedure ...... 115
5.4 Results ...... 115
5.3.1 Mate-Value Inventory ...... 115
5.4.2 Frequency of Perfume Use over Two Weeks ...... 117
5.4.3 Day-of-Study Perfume Use ...... 118
5.5 Discussion ...... 120
5.6 References ...... 125
Chapter 6: The Effects of Dimorphism and Pupil Dilation on Facial Attractiveness
...... 129
6.1 Chapter Overview ...... 129
6.2 Introduction...... 129
6.2.1 Pupil Dilation in Mate Choice ...... 129
6.2.2 Role of Dimorphism on Facial Attractiveness ...... 132
6.2.3 Intra-Sexual Competition ...... 132
6.2.4 Current Study ...... 133
6.3 Methods ...... 134
6.3.1 Participants ...... 134
6.3.2 Stimuli and Materials ...... 134
6.3.3 Procedure ...... 136
6.4 Results ...... 137
6.4.0 Preliminary Data Screening ...... 137
6.4.1 Male Ratings of Female Faces ...... 137
6.4.2 Female Ratings of Male Faces ...... 138
viii INDIVIDUAL DIFFERENCES IN MATING PREFERENCES
6.4.3 Same-Sex Face Judgements ...... 139
6.5 Discussion ...... 140
6.6 References ...... 146
Chapter 7: The Role of Facial Structure in Mate Choice ...... 149
7.1 Chapter Overview ...... 149
7.2 Introduction ...... 149
7.2.1 Face Architecture and Signalling Value ...... 150
7.2.2 Current Study ...... 154
7.3 Methods ...... 155
7.3.1 Participants ...... 155
7.3.2 Materials ...... 155
7.3.3 Procedure ...... 155
7.3.4 Independent Ratings of Facial Images ...... 156
7.3.5 Hormone Analysis ...... 156
7.3.6 Morphometric Analysis ...... 157
7.4 Results ...... 157
7.4.0 Preliminary Data Screening ...... 157
7.4.1 Hormone Outcomes ...... 158
7.4.2 Subjective Ratings ...... 158
7.4.4 Objective Dimorphism – Morphometric Analysis ...... 162
7.4.4 Relationship Between Objective and Subjective Measures ...... 163
7.5 Discussion ...... 165
7.6 References ...... 171
Chapter 8: General Discussion ...... 176
8.1 Chapter Overview ...... 176
8.2 Reiteration of Thesis Aims ...... 176
ix INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
8.3 Key Findings ...... 177
8.4 Consideration of Limitations ...... 182
8.5 Future Research Directions ...... 184
8.6 Summary and Conclusions ...... 186
8.7 References ...... 189
Presentation of Results Arising From This Thesis ...... 194
Published Manuscripts ...... 194
Conference Presentations ...... 194
Appendix A - Common Scales ...... 195
A.1 Socio-Sexual Inventory-Revised ...... 195
A.2 Self-Rated Mate Value Inventory ...... 197
A.2 Mating Intelligence Scale ...... 199
Appendix B - Article published in Evolution, Mind and Behaviour, 2015 (Chapter 2)
...... 202
Appendix C – Stimulus Sets for Eye-Tracking Task (Chapter 3)...... 219
Appendix D – Vector Outcomes for Principle Component Analysis (Chapter 7). 223
x INDIVIDUAL DIFFERENCES IN MATING PREFERENCES
List of Tables
Table 2.1. Correlations between importance of information assigned to body, and mate value and sociosexual orientation measures for male and female participants………..…61
Table 5.1. Factor loadings for each item in the MVI-S onto five factors……………….116
Table 5.2. Correlations between subscales of the MVI-S, and artificial scent use over two weeks, for participants in a relationship (left) and those not
(right)…………………………………………………………………………………..117
Table 5.3. Multiple regression for predicting frequency of artificial scent use over a two- week period for participants in a relationship (top) versus those not (bottom)………….118
Table 5.4. Logistic regression analysis for predicting single participants day-of-study perfume use.……….…………………………………………………………………...119
Table 7.1. Fertile session only correlations between individual difference measures and subjective ratings……………………………………………………………………….160
Table 7.2. Correlations between individual difference measures and subjective ratings when considering averages for both fertile and non-fertile sessions……………………161
Table 7.3. Multiple linear regressions for predicting subjective face ratings (attractiveness, femininity and masculinity) for fertile faces……………………………………………163
Table 7.4. Correlations between subjective ratings and Vector and discriminant scores based on linear discriminant analysis for 39 male and 38 female faces………………..164
xi INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
List of Figures
Figure 1.1. Kinsey Heterosexual-Homosexual Rating Scale ...... 28
Figure 2.1. Demonstration of box choice, from left to right: complete box, female face
revealed, male body revealed ...... 57
Figure 2.2. Frequency distribution of body or face box choice for self (a) or cross-sex (b)
mating decisions in short-term or long-term context for male and female participants.
Average frequency of box choice collapsed across ST or LT condition indicated by dashed
lines ...... 60
Figure 2.3. Ratings of importance of information obtained from the face or body (higher
scores indicate preference for body), for male and female ratings, self-reported versus beliefs about cross-sex importance, in either short-term or long-term mating conditions.
...... 63
Figure 3.1. Examples of stimuli from party/revealing (left) and conservative (right)
conditions ...... 79
Figure 3.2. Proportion of total dwell time to body region as a function of context (short-
term or long-term) and clothing choice...... 83
Figure 4.1. Examples of body photographs of a participant, in the follicular (left) and luteal
(right) phase of the menstrual cycle ...... 97
Figure 4.2. Percentage of skin exposure of décolletage, arms, and legs, as a function of fertility...... 99
Figure 6.1. Female shape prototype (left) and male face prototype (right) for face
tranformations ...... 135
Figure 6.2. Examples of stimuli for face rating task. Feminised with large pupils (left) and
masculinised with constricted pupils (right)...... 136
xii INDIVIDUAL DIFFERENCES IN MATING PREFERENCES
Figure 6.3. Masculinity preference for male faces with constricted or dilated pupils, across short-term and long-term conditions between contraceptive using and non-contraceptive using women...... 139
Figure 7.1. Averages for Linear Discriminant Analysis between male and female faces
...... 163
xiii INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Abstract
Mating strategies are the set of traits, behaviours, preferences, perceptual biases, and
cognitions that affect individual navigation of the mating and dating world, the result of
tactics were selected for over time because they aided their ancestors in reproduction. The
difference in minimal parental investment between the sexes means that men and women
have often been under differential selection pressure to evolve particular mating strategies,
and so men are more likely than women are to pursue a short-term mating strategy,
whereas women are more likely than men are to pursue a long-term strategy. However,
both sexes engage in strategic pluralism, whereby both men and women employ multiple
mating strategies as a means of maximising individual reproductive success. The
principles of assortative mating also demonstrate that individuals often end up mating with people similar to themselves, as opposed to every individual seeking to mate with the highest quality exemplar. Therefore, evolutionary forces have resulted in a range individual variation, which reflects the individual costs and benefits of engaging in a particular mating strategy, and the effort put into either maximising reproductive output, seeking a high quality mate, or both. Thus, mating strategies are complex and multi- faceted. In order to navigate the mating and dating world, we need to be able to make decisions about another individual’s mate quality, by judging particular cues to characteristics that are important in a potential mate. We also signal our own mate quality to others, which can attract mates or ward off potential competitors. The expression and employment of these tactics is highly dependent on a number of factors, such as context, our cognitions about mating, and our own mate quality. This thesis is a body of work
examining these individual differences; that is, examination of those signals that
individuals might be sending to other people about their mate quality, and their responses
to variation in these cues in others. More specifically, the thesis explores: sex differences
xiv INDIVIDUAL DIFFERENCES IN MATING PREFERENCES in attention allocation to the faces and bodies of potential mates; within-sex variation in female mate signalling, via clothing choice and the use of artificial fragrance; as well as the role of facial characteristics in mate choice, by examining how we respond to facial variation in others, and exploring facial variation as a signal of underlying mate quality.
In doing so, several important variables that can affect the use of these mating tactics are considered, including socio-sexual orientation, self-rated mate value, circulating gonadal hormones, and relationship status. Overall, men and women employ different mating tactics, reflective of sex-differences in evolved sexual strategies, and these tactics interact in complex ways with other mating related variables, resulting in a broad range of individual differences.
xv INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
“What is the meaning of life? Why are we here? Philosophers have pondered
that question for centuries. I’m afraid the answer is disappointingly simple:
Mating. That’s it”
- Oliver Markus, Why Men and Women Can’t be Friends
---
“Never criticize your spouse’s faults. If it weren’t for them, your mate might
have found someone better than you”
- Jay Trachman
xvi CHAPTER 1
Chapter 1: General Introduction
1.1 Thesis Aims and Chapter Overview
Mating strategies refer to sets of preferences, traits, perceptual biases, behaviours, cognitions, and competitive tactics that individuals utilise in order to navigate the mating and dating world (Buss & Schmitt, 1993; Gangestad & Simpson, 2000). These strategies help us to compete with members of the same-sex for access to mates via intra-sexual competition, and encompass processes used to differentiate between and select potential mates via inter-sexual competition. In order to compete in the mating world, individuals must be able to judge the quality of potential mates or the characteristics of potential competitors, and thus have evolved preferences for attending to and evaluating particular signals of mate quality in others. Whilst doing so, individuals are also displaying their own mate qualities to others (whether mates or competitors), and thus a complex interaction between displaying and perceiving signals of mate quality exists. The aim of this thesis is to explore a range of those factors that influence both sex-differences and individual-differences in these mating strategies. In this thesis, I provide an overview of how individuals might display their mate quality to others, and their responses to these signals in potential mates and competitors. In doing so, I examine general sex-differences in these mating strategies, as well as explore which factors lead to individual variation. The purpose of this introductory chapter is not to provide an exhaustive literature review, but to outline the theoretical justification for this thesis. Each chapter then considers the specific literature leading to the topic of interest. More specifically, in this chapter I will:
demonstrate the utility of considering mating strategies as evolved adaptations;
outline the main theories surrounding our understanding of variation in mating
strategies;
provide an overview of potential cues and signals to mate quality;
1 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
discuss the impact of hormonal variation on mating strategies, and more
specifically female menstrual-cycle shifts and hormonal contraceptives; and
outline how certain factors may affect individual differences in mating strategy
employment.
1.2 Understanding Mating Strategies as Evolved Adaptations
Consideration of the evolutionary origin of human psychological mechanisms is still an emerging factor in the design of psychological studies. While an increasing number of researchers are considering psychological questions that are informed by our understanding of evolutionary pressures, ‘Evolutionary Psychology’ (EP) is largely perceived as its own field, with a divide in the methodologies and considerations of EP and the broader discipline of psychology. The reasons for this are likely varied (for discussion, see Burke, 2014), although there can be little doubt that our psychological mechanisms have been subject to evolutionary pressures. For example, our biological preparedness to locate spiders in an array, versus other less-threatening stimuli or stimuli that are threatening only when considered in a modern context
(New & German, 2015), demonstrates that many of our cognitions (or cognitive biases) have their origin in our ancestral history of experience with the world. While it is well accepted that some degree of plasticity in brain functioning and our patterns of responding to environmental cues characterises our psychology, this in no way diminishes the importance of understanding the evolutionary pressures that have also helped to shape those patterns of responding, or determined the scope of plasticity in behavioural patterns. According to Niko Tinbergen (1963), in order to truly understand any behaviour we have to address four levels of explanation. In addition to the proximate questions of cause (mechanism), and ontogeny (development), we also need to consider two ultimate levels: that of phylogeny (distribution), and ultimate function, or, the selective value of that behaviour (e.g., see Stephen, 2013). Thus, a complete understanding of behaviour can arise by asking not only what purpose it serves in the modern contexts (and,
2 CHAPTER 1 particularly, what environmental conditions it is responding to) and the question of developmental pressures (what proximate pressures have been influential, from conception onwards). We also need to consider whether similar traits exist in our closest genetic relatives
(and potentially, therefore, when in our evolutionary past this behaviour first arose, leading to questions of convergent and divergent evolution), and what selection pressures led to its evolution. This is not to say that all behaviours we are interested in observing in the study of psychology still serve the same function that they did 10,000, or more, years ago; but that at least asking these questions can help us understand, more holistically, what drives patterns of responding. It also encourages us to ask broader questions about the ecological context of behaviour. For example, when examining a pattern of behaviour in the lab, under very strict (and often unnatural) circumstances, we can (and often do) fall prey to the fallacy of believing that we are observing a cognitive function that is for whatever task that we are subjecting individuals to, such that our descriptions of behaviour and cognition derive from these paradigms
(Sulikowski & Burke, 2015). However, since these behaviours have not evolved in isolation, but rather in a varying environment, in which we have been active participants and not just passive recipients of information, asking these questions in the isolation of the lab may give us the false impression that we truly understand what ‘purpose’ that behaviour serves. When attempting to understand our mating psychology, therefore, it is pertinent to not only ask what sex differences exist and under what evolutionary circumstances these arose, and thus address the question of their ultimate function, but we also must consider under what current environmental conditions are they employed. So, for example, how do individuals vary in their employment of any particular mating strategy, and in what context? In this body of work, I explore some of these complex interactions between various factors that affect our mating repertoire and thus seek to gain an understanding of the operation of evolved preferences in a modern environment.
While the logistics of mating have changed little over time, the complexity of our modern environment fashions for us a great number of contexts in which we have to (consciously or
3 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES unconsciously) consider the best sexual strategy, weighing up the costs and benefits of each, with the aim of maximising our ultimate evolutionary function of reproductive success.
Understanding which factors affect evolved mating strategies can also allow us to understand, at an individual level, why people choose the sexual and romantic partners that they do; why they might begin or end a relationship, choose to stay single, have ten children or none.
Ultimately, empowering individual understanding of what are largely unconscious, evolved, preferences and behaviours, and the modern contexts on which they are dependent, could lead to the development of techniques to overcome potentially detrimental patterns of behaviour.
1.3 Sexual Strategies Theory and Strategic Pluralism
Taking into consideration archaeological and anthropological evidence, it was once thought likely that in the environment in which our ancestors evolved the chances of adult reproduction were quite good, with an estimated 80% chance of reproducing at least once (Volk
& Atkinson, 2008). More recent chromosomal evidence, however, suggests that over the past
10,000 years there has been large variation between males and females in reproductive success
(Karmin et al., 2015). This is attributed to culturally-driven changes in offspring number in men, and demonstrates the importance of considering both context and biological factors in the consideration of mating success and mating strategies. Firstly, in order to have the opportunity to reproduce, one must first survive infancy and childhood. Average instances of child death in a variety of ancient cultures were likely in the range of 40 – 50% (Volk & Atkinson, 2008). As a result, our ancestors had to invest considerable time and effort into passing on their genes, from surviving infancy and childhood, reproducing successfully, and finally rearing offspring until they were of reproductive age. In order to reproduce successfully, individuals have to attract and retain a mate for long enough to produce offspring. For individuals above pubertal age, reproductive advantage arises via intra-sexual competition, or, gaining access to the opposite sex through defeating same-sex conspecifics or possessing qualities that are attractive to the opposite
4 CHAPTER 1 sex; and inter-sexual competition, or, possessing preferences and mechanisms that help one to choose advantageous members of the opposite sex (Buss, 1988). Mating strategies refers to sets of preferences and traits that organisms possess that have historically led to reproductive success, variation in which have been selected for over evolutionary time (Gangestad & Simpson, 2000).
Understanding the origins of human mating choices is important as it provides us a basis for the consideration of current problems associated with human reproduction. According to
Buss and Schmitt’s (1993) Sexual Strategies Theory, somewhat different sexual psychologies have evolved in men and women, as the two sexes have faced different selection pressures over the course of evolutionary history. The difference in minimal parental investment (Trivers, 1972) between the sexes means that men have mostly been constrained in their reproductive success simply by the number of fertile women they can mate with, and so can invest more in short-term mating strategies. On the other hand, women have internal fertilisation, gestation and placentation, and as such are heavily constrained by the quality and quantity of resources they can secure. Women may employ more energy in long-term mating strategies, and can afford to be choosy when deciding with whom to mate (Buss & Schmitt, 1993). This results in a state of sexual conflict between the male and female members of the species, whereby men and women are competing for control of reproductive output. In support of this hypothesis, modern day sex differences in mate preferences can be observed, which are consistent across cultures (Buss,
2006). For example, on average, men and women differ in their attitudes to sexual relationships, with men more accepting of casual sexual relationships than women (Penke & Aspendorf, 2008).
Men and women also differ in the qualities they most value in short- and long-term mates, with women more selective about financial resources in long-term partners, and men more selective about attractiveness in short-term partners (Buss, 2006). Men and women may also differ in the tactics they employ and perceive as most effective in promoting a sexual encounter (Greer &
Buss, 1994). Further to this, changes in culture and social structures can further increase the
5 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES differential reproductive success of men and women, as implied by the genetic evidence outlined by Karmin et al. (2015).
It is clearly not the case, however, that men always seek short-term mating opportunities and women always long-term. Like any evolved mechanism, the benefits gained from any particular reproductive strategy are weighed against the costs. While women, on average, may have the most reproductive benefit to gain from long-term relationships, depending on their individual situation they still may have some benefit to gain from short-term mating opportunities, as much as men may have benefit to gain from long-term, and this can change over evolutionary time. Thus, men and women engage in both short-term and long-term sexual strategies. According to the concepts of Strategic Pluralism (Gangestad & Simpson, 2000), if both sexes can gain fitness benefits from pursuing alternative mating strategies, then the strategies employed should be conditional, that is, heavily dependent on context and life history factors. In accordance with this, selection has resulted in considerable variation in sexual strategies within each sex, in addition to the broad differences between the sexes (Gangestad &
Simpson, 2000). In addition, the preferences that men and women hold for particular characteristics in long-term and short-term partners varies in accordance with the likely benefits of engaging in that strategy, and can drive attention to signals of these traits in others. For example, both men and women rate physical attractiveness as more important in a short-term partner than a long-term (e.g., Regan, Levin, Sprecher, Christopher, & Gate, 2000), since physical attractiveness may be a cue to underlying genetic quality (see section 1.4.1), which is important in a short-term mate. These variations can also reflect how the preferences of one sex might influence the mating tactics of the opposite sex. For men, benefit can be gained from engaging in a long-term relationship if they are not likely to be in demand on the short-term mating market, that is, if they are lower in genetic quality (Gangestad & Simpson, 2000). These benefits can include securing a mate of high quality, guaranteeing the rearing of at least one offspring by avoiding the problem of ‘concealed’ ovulation (or, avoiding the costs of short-term
6 CHAPTER 1 mating strategies), guarding mates against extra-pair copulations, and long-term provisioning of resources (Buss & Schmitt, 1993). Women might gain benefits from engaging in a short-term strategy if consistent parental care is not an option. These benefits could include access to men of high genetic quality, since those males pursuing a short-term strategy are likely doing so because they can afford to (due to being in high demand), evaluation of long-term prospects, and short-term provisioning of resources and protection (Buss & Schmitt, 1993). Some reported sex differences may also be dependent on measurement context. For example, differences in preferences for particular characteristics such as physical attractiveness and status across short- term and long-term mating contexts have been reported (e.g., Li, Bailey, Kenrick, &
Linsenmeier, 2002). However, more recent evidence (Mogilski, Wade, & Welling, 2014) demonstrates that when assessing potential individual suitors, rather than rating traits on a scale, both men and women rate sexual fidelity highly for both short-term and long-term relationships, thus diminishing the sex difference. It is therefore important to consider context and the impact of a range of variables when individuals make mating decisions.
1.3.1 The Developmental Trajectory of Mating Behaviour
If mating preferences reflect evolved behaviours, then they should follow a developmental trajectory that closely maps lifespan variations in fertility. In support of this,
Little et al. (2010) demonstrated that women’s preferences for masculine male faces, a potential signal of male mate quality (see discussions by Fink & Penton-Voak, 2002; Rhodes, 2006;
Rhodes, Chan, Zebrowitz, & Simmons, 2003), are highest in women of reproductively active ages, and lower in peri-pubescent and post-menopausal women. Similarly, Vukovic et al. (2009) have found an increased preference for femininity in female faces circum-menopause, likely a reflection of the decrease in intra-sexual competition at this time. In addition, Boothroyd, Meins,
Vukovic, and Burt (2014) found that children’s preferences for facial cues associated with high mate quality changed between children at 4-5 years of age versus those of pubertal age or
7 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES entering adolescence. For example, children aged 4-8 had significantly lower attractiveness and symmetry preferences than children aged 13 and above. Similarly, Saxton, Debruine, Jones,
Little, and Roberts (2009) found differences between older and younger children in preferences for dimorphism in voice pitch, with older children preferring stronger dimorphic voice pitch traits in opposite-sex voices (that is, high pitch for female voices, low pitch for male voices) than younger children.
These results demonstrate that preferences for signals of mate quality in others are higher during those stages of the lifespan when ones reproductive ability is highest, and thus have likely been sexually selected. However, if variation exists in sexual strategies in order to maximise reproductive output, then other experiences over the developmental period should also affect an individual’s ideal mating strategy. These experiences may signal to an individual whom constitutes an ideal mate (given their environment), the accessibility of these mates, and even their own likelihood of attracting a high quality mate, amongst other things. Life history strategy refers to the relative resources an individual devotes to rates of development, sexual maturity, reproductive output, parental investment, and so on, and is dependent on both genetic and environmental variation (Figueredo et al., 2005). For example, exposure to a harsh environment can result in a faster life history strategy, characterised by younger age of first reproduction, larger number of offspring, and less investment in each offspring; as the unpredictability of the environment may signal that this strategy would be most successful owing to increased morbidity and mortality (see Brumbach, Figueredo, & Ellis, 2009). These variations in life history strategy also have measurable effects on mate preferences. For example, Figueredo and
Wolf (2009) demonstrated that assortative mating effects between sexual partners are stronger in individuals with a slow life history strategy than those with a fast life history strategy.
Assortative mating refers to the similarity of individuals to one another (see section 1.5 for further discussion) and can reflect the individual trade-off between investing effort into finding the ideal mate (which can result in fewer offspring but of higher quality) versus maximising
8 CHAPTER 1 reproductive output (which can result in more offspring but of lower quality). Hence, life history strategy can affect the effort an individual puts into seeking their ideal mate. In addition, experiences during childhood can affect preference for particular facial characteristics. For example Kocsor, Saxton, Láng, and Bereczkei (2016) have recently demonstrated that individuals who had lower scores on a retrospective perceived parental bonding scale, for their opposite-sex parent, were more likely to choose faces resembling that parent as a preferred partner. While Saxton (2016) has also showed that the developmental stage at which a female retrospectively reports receiving emotional support from her parents affects the strength of preference for partners whose eye-colour is closer to that of the parent, with stronger preference if emotional support was provided post-menarche but weaker preference if emotional support was provided pre-menarche. At this point, it should already be clear that while mating preferences reflect evolved adaptations, these strategies are not fixed, and instead are characterised by a huge range of strategic, adaptive variation.
1.4 How Do We Judge Mate Quality?
Given the variation in a potential mate’s suitability as a partner, evolutionary mechanisms have selected for psychological processes that allow us to judge whether an individual is worth investing in. If successful reproduction requires a combination of good genes, resources, and parental care, and these characteristics vary between individuals, then we should be able to judge these characteristics by looking to cues or signals to these in others. Throughout this thesis, when I refer to signals or cues of mate quality, I refer to those traits that show variation between individuals that might inform others about our capacity to reproduce or rear children via direct benefits (such as good genes) or indirect benefits (such as resources or parental care).
Cues represent those traits which may not have evolved to signal mate quality, but which nonetheless may have an effect on the behaviour of others, while signals have evolved specifically to create a response, whether or not they are attended to by others (Scott-Phillips,
9 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
2008). Consistently, both men and women place high preference on the characteristics of kindness, understanding, and intelligence in a potential partner (e.g., Buss & Barnes, 1986;
Cottrell, Neuberg, & Li, 2007), and thus both men and women should be attracted to cues and signals of these characteristics in others. In support of this, Moore, Filippou, and Perrett (2011) have demonstrated that faces high in perceived intelligence are also rated as more attractive.
However, general sex differences also emerge in the importance of other cues of mate quality such as physical attractiveness. For example, men rate physical attractiveness as more important in a potential partner than do women, whereas women rate resource potential as more important in a mate than do men (e.g., Buss & Barnes, 1986). Overall, the relative importance of those qualities desired in a potential sexual or romantic partner should drive both the cues that individuals use to assess the potential mate quality of others, and thus what individuals judge as attractive, as well as which traits may have evolved as signals.
These differences in preferences are likely to have arisen owing to those differences in minimal parental investment between the sexes (Trivers, 1972), and lifetime differences in men and women’s reproductive capacity, where women invest more and hence are the choosier sex
(Trivers, 1972). As such, we can observe differences in the cues that men and women tend to use to assess mate quality, and this can help us understand what these cues are potentially informing us about underlying mate quality. Overall, men show little to no cyclical change in fertility, and have a lifetime fecundity that can last for a much longer period of time than women’s (owing to a much later reproductive decline). In addition, much redundancy exists between modality judgements (i.e., between faces, voices, bodies, and scent) when judging attractiveness or suitability of men as a mate (e.g., Feinberg, DeBruine, Jones, & Little, 2008).
Thus, women can use one of many physical cues or signals at any given time to make a reasonable estimate of a man’s mate quality and therefore a male’s suitability as a romantic or sexual partner.
10 CHAPTER 1
On the other hand, women show a much more rapid lifetime change in fecundity (their lifetime reproductive potential) than men, as well as cyclical changes in fertility (or conception risk). Thus, while women have only the problem to solve of whether a man would provide good genes, good resources, or both, men also have the additional problem of judging both fertility and fecundity, with cues to both being distributed more differentially across body regions. For example, proximity to ovulation increases the subjective attractiveness of women’s dance (Fink,
Hugill, & Lange, 2012) and gait (Guéguen, 2012), the symmetry of soft tissues such as breasts
(Scutt & Manning, 1996), and is associated with wearing more revealing clothing (Durante, Li,
& Haselton, 2008; Saad & Stenstrom, 2012). Additionally, the waist-to-hip ratio provides a very obvious cue to pregnancy (Rebuffé-Scrive, 1987). While short-term changes in fertility owing to ovulation may also be perceived from changes in facial skin-tone (van den Berghe & Frost,
1986) and facial attractiveness (Roberts et al., 2004), these changes are subtle and perhaps more easily obscured (particularly with evolutionary novel means such as cosmetics). Changes in bodily movement, symmetry and dress, therefore, might act as a signal of current fertility, or of female mating motivation, in addition to those cues detected when looking at a female face, thus increasing their importance for short-term judgements. For long-term judgments, the face remains much more important than the body (Confer, Perilloux, & Buss, 2010).
Consideration of the function of these preferences has led to arguments that that these preferences give benefits, either directly or indirectly, to our offspring. For example, bilateral traits can fluctuate from one generation to the next (known as fluctuating asymmetry), such that a higher level of asymmetry is a reflection of developmental instability (Gangestad, Thornhill,
& Yeo, 1994). Thus, mating with a person low in asymmetry can be beneficial to one’s offspring, as you will likely inherit those factors that aid in successful development. Considering this then, we can hypothesise that this preference should be more prevalent in mating relevant contexts
(and thus evolved to serve a particular function in mating), as opposed to being part of a more general preference for natural symmetry in all objects (and thus be an evolved preference not
11 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES specifically related to mating). Three studies (Jones et al., 2008a; Little & Jones, 2003; Little,
Jones, DeBruine, & Feinberg, 2008b) have demonstrated that men and women display a stronger symmetry preference for faces of the opposite sex than the same sex. In addition, as discussed previously, Boothroyd et al. (2014) found that preference for symmetry in faces increased between children aged 6 and 17, being significantly higher for children who had reached puberty.
These results provide evidence for the former hypothesis, that these preferences have a role to play in mating contexts, a more specific pattern that could not be explained without considering their ultimate function.
Further to this, we can examine the environmental contexts that might influence preference for symmetry. If this preference has evolved as a mechanism to increase the chances of healthy offspring development, then we might expect the preference to be strongest in cases where this outcome is more crucial. Little, DeBruine, and Jones (2011) demonstrated that exposure to cues of environmental pathogens increased preference for symmetry (and dimorphism) in opposite-sex but not same-sex faces, compared to no exposure (see also
DeBruine, Jones, Crawford, Welling, & Little, 2010a; DeBruine, Jones, Tybur, Lieberman, &
Griskevicius, 2010b). This further demonstrates that these preferences play an important role, specifically in our mating repertoire, and therefore the utility of considering their evolved function when deriving hypotheses.
Overall, humans use a wide range of cues and signals to judge the potential mate quality of another, traits which affect our attractiveness ratings of these individuals. On a behavioural level, we make judgements by observing an individual’s interactions with others, and their non- verbal communicative behaviour, such as gait and stance (e.g., Neave et al., 2011; Osborn, 1996;
Sakaguchi & Hasegawa, 2006). We also judge their physical appearance; skin tone, facial structure, and symmetry in body structures, and weight, height, and perceived age (e.g., Fink,
Grammer, & Matts, 2006; Furnham, Moutafi, & Baguma, 2002; Korthase & Trenholme, 1982;
Penton-Voak et al., 2001; Perrett et al., 1998). Additionally, we use non-visual cues to make
12 CHAPTER 1 judgements about mate quality, such as voice pitch and scent (e.g., Feinberg, Jones, Little, Burt,
& Perrett, 2005; Grammer, Fink, & Neave, 2005; Jones, Feinberg, Debruine, Little, & Vukovic,
2008b; Rikowski & Grammer, 1999; Thornhill, 2003; Thornhill & Gangestad, 1999). The role of researchers is then to determine what exactly variation in these traits is reflecting about the range of sought-after qualities in potential partners. For example, while excess testosterone can be an immune suppressant, according to Zahavi’s (1975) Handicap Principle, the ability to maintain secondary sexual characteristics that occur as a result of high levels of testosterone, and still remain healthy, is an honest signal of genetic quality. That is, only men that have a strong immune system could overcome the immunosuppressant effects of testosterone in order to maintain characteristics influenced by high testosterone levels, such as highly masculine faces.
Hence, a wealth of literature has sought to examine the link between masculine face architecture and underlying health and testosterone levels. More broadly, understanding the potential signalling value of face variation has dominated the literature on the evolution of mate preferences.
1.4.1 Why Faces Are So Special
An overwhelming body of evidence indicates that people prefer to look at faces that are symmetrical, sex-typical (that is, dimorphic), average, and attractive (see Rhodes, 2006).
Dimorphism in faces refers to the extent to which a face is ‘typically’ male or female, with significant sex differences in facial morphology visible from an early age (Bulygina,
Mitteroecker, & Aiello, 2006). Typical female or ‘feminine’ facial characteristics are qualitatively different to typical male or ‘masculine’ facial traits. Increases in dimorphic traits are triggered by puberty, and can therefore act as a signal of sexual maturity and reproductive potential (Thornhill & Gangestad, 1996). Typically, femininity is perceived to be attractive in female faces (e.g., Rhodes, 2006), whereas the attractiveness of masculinity in male faces varies considerably with contextual factors (e.g., Little, Connely, Feinberg, Jones, & Roberts, 2011;
13 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Rennels, Bronstad, & Langlois, 2008; Rhodes, 2006). The extent to which males and females find dimorphism attractive in faces also depends, in part, on their own sexuality (e.g.,
Glassenberg, Feinberg, Jones, Little, & Debruine, 2010), hormone levels (e.g., Roney &
Simmons, 2008; Welling et al., 2007; Welling et al., 2008) mate value (e.g., Little & Mannion,
2006), and menstrual cycle phase (see section 1.7.1), among other factors. This further demonstrates the importance of consideration of context and individual differences when examining mating strategies.
Symmetry is perceived as more attractive in opposite-sex faces than same-sex faces, as discussed above. However, faces contain more than just symmetry information that is potentially important in a mating context, so we might also expect men and women to find these other factors more attractive in mating relevant contexts. In addition, if these cues are an indication of underlying genetic fitness, we should find correlations between measures of heritable fitness
(such as physical strength and hormone levels, the features that are considered attractive in faces), and mating success. As per Zahavi’s (1975) handicap hypothesis, behaviours or morphology that would normally be detrimental to an individual can be selected for if they are an honest signal of fitness. That is, if the individual can maintain the morphology even though it is an immune suppressant, for example, then it can serve as an honest signal of their underlying health, the classic example being the peacock’s tail. In accordance with this, women’s facial attractiveness changes in synchrony with monthly fluctuations in hormone levels such that lower progesterone levels and relatively higher estradiol levels around the time of ovulation (the time at which the chances of conceiving from a single act of intercourse peak) correlate with higher ratings of facial attractiveness (e.g., Puts et al., 2013; Roberts et al., 2004). In addition, findings of negative correlations between women’s facial attractiveness and age have been reported in the literature (e.g., Matts, Fink, Grammer, & Burquest, 2007; Wheatley et al., 2014). Since women’s overall reproductive capacity peaks around age 25-30 and decreases with age
(Schwartz & Mayaux, 1982), it appears that facial attractiveness is related to overall fecundity,
14 CHAPTER 1 in addition to monthly fluctuations in fertility, thus indicating that changes in female faces provide some cue to long-term reproductive capacity. Wheatley et al. (2014) also demonstrated that age correlates negatively with facial attractiveness in females from both an industrialised nation and a hunter-gatherer group. In addition, between-subjects variation in female testosterone levels negatively correlated with male ratings of female facial attractiveness. Since lower levels of testosterone in females faces related to overall fecundity, this indicates attraction to faces with lower levels of testosterone could have evolved as a male adaptation to recruit highly fecund females for long-term pair bonds. Further supporting this is evidence that species that do not form long-term pair bonds do not demonstrate this preference for youthfulness in females. Muller, Thompson, and Wrangham (2006) found that male chimpanzees (Pan troglodytes) prefer older, not younger, females. Since female chimpanzees do not experience menopause in the same way that human females do, and instead continue to reproduce into later life (Emery Thompson et al., 2007), the preference for older females is likely an adaptation to seek genes for longevity or experience in parental care. This also potentially reflects a preference for traits associated with a higher social status, which in certain contexts may outweigh the benefits of youth and peak fertility. This further demonstrates that the consideration of phylogeny, and the evolution of mating preferences in general, can tell us something important about human mating behaviour.
The evidence regarding the link between male markers of heritable fitness, facial attractiveness and mating success are less clear. For example, Fink, Neave, and Seydel (2007) found significant positive correlations between men’s handgrip strength (characteristic of testosterone levels; Gallup, White, & Gallup, 2007) and female ratings of facial masculinity and attractiveness. Similarly, Honekopp, Rudolph, Beier, Liebert, and Muller (2007) found that physical fitness was correlated with male’s self-reported number of lifetime sexual partners (an indicator of reproductive success) and with bodily attractiveness, however, physical fitness was not correlated with facial attractiveness but did correlate with subjective ratings of masculinity.
15 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Additionally, no correlation emerged in Honekopp et al.’s findings between male testosterone measures and ratings of bodily or facial attractiveness, nor with objective measures of physical fitness. In addition, Peters, Simmons, and Rhodes (2008) found that male testosterone concentrations did predict mating success, but were unrelated to facial attractiveness or ratings of facial masculinity. Finally, Swaddle and Reierson (2002) demonstrated that male faces higher in testosterone were rated as more dominant, but not more attractive. Thus, the link between male facial masculinity, circulating testosterone, and mating success is equivocal (see Scott,
Clark, Boothroyd, & Penton-Voak, 2013). However, male testosterone may still tell us something important about male mate quality and mating success. Considering evidence from other species, Beehner, Bergman, Cheney, Seyfarth, and Whitten (2005) demonstrated in a group of chacma baboons (Papio hamadryas) that while testosterone did not relate to current mating success nor rank, it was predictive of future mating activity and future rank. In addition, Pound,
Penton-Voak, and Surridge (2009) found that while baseline testosterone levels did not relate to facial masculinity, levels of testosterone after success in a competitive task did. Thus, facial masculinity may still be providing us with some important information about potential success, as well as endocrine functioning. Overall, a deeper understanding of the relationship between reproductive capacity and morphology of facial attractiveness can inform us about the extent to which these traits are cues or signals of different aspects of mate quality, and their functional capacity.
While there is some doubt as to whether heritable fitness markers are subjectively more attractive, this potentially means that the benefits of attraction to a male with a masculine face
(and other masculine traits) may not always outweigh the potential costs. For males, mating with a fertile female, detected via facial structure and perceived age, is nearly always advantageous.
However, for females, the costs and benefits of good genes versus good resources are weighed against one another (Gangestad & Simpson, 2000), thus preference for heritable fitness markers is going to vary more based on context. More generally, variation in face preferences
16 CHAPTER 1 demonstrates similar relationships to other environmental and life history strategies as other mating behaviours, and this holds for both males and females. For example, Marcinkowska et al. (2014) have demonstrated that men’s preference for dimorphism in women’s faces is influenced by the national health index in their respective countries, with a stronger femininity preference in countries with a lower health index. Similarly, DeBruine et al. (2010a) demonstrated that as a nation’s health decreases (as indexed by mortality rates, life expectancy, and communicable disease impact), female preference for masculine faces increases. Thus, context matters.
1.5 Mate Competition
To summarise thus far, men and women possess a host of traits (which are potential cues) that members of the opposite-sex can use to judge the quality of a potential mate. As men and women compete with same-sex rivals for access to mates, active manipulation of those signals that inform us about the underlying mate quality of an individual can be useful tactics to attract members of the opposite sex and thus compete against same-sex individuals. As mentioned previously, men and women’s desire for particular characteristics in potential mates differ, and these preferences should drive the relative effort that individuals put into enhancing particular cues to mate quality. According to Greer and Buss (1994), the tactics perceived as being most effective in promoting a sexual encounter include enhanced physical appearance for women, and investing time and attention (i.e., investment) for men. This reflects the differential importance that men and women place on physical attractiveness versus capacity to acquire resources, and thus the likelihood that these signals might be enhanced or manipulated in order to attract a mate
(or deceive others about one’s mate quality). In accordance with this, we should also observe differences in the cues and signals that men and women pay attention to in order to judge the mate quality of others. As mentioned previously, while women prefer to look at the face regardless of the context of the relationship judgement (short-term or long-term), men’s attention
17 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES to female faces or bodies reflects the reflects the increased importance of information from the body for short-term relationship judgements. In support of this, Confer et al. (2010) demonstrated that men making short-term relationship judgments (where immediate fertility is most important) exhibit a stronger preference to see the body of a female rather than her face
(when given a mutually exclusive choice), than when making long-term relationship judgments, where long-term fecundity is more important. There is no such effect of relationship type on women’s preferences for the male face or body.
While inter-sexual selection involves the processes that men and women employ to choose between potential suitors, such as paying attention to particular cues to mate quality, intra-sexual competition refers to the direct (often subtle) competition between same-sex individuals, used to gain access to these mates. Men and women compete intra-sexually in different ways. For example, Tooke and Camire (1991) demonstrated a higher frequency of appearance-related deception in intra-sexual competition for women compared to men, which is not surprising given men’s preference for physical attractiveness in a mate. On the other hand, men compete via feigning resources. Women, moreso than men, compete via appearance enhancement (Buss, 1988), and derogation of the appearance of potential rival, such as through gossiping (Buss & Dedden, 1990). Several researchers have also demonstrated an increase in appearance-related competition as women’s fertility levels change (e.g., Cobey, Klipping, &
Buunk, 2013; Fisher, 2004). This is closely related to women’s increased desire for extra-pair copulations when fertile (e.g., see Gangestad, Thornhill, & Garver, 2002), and thus the increased likelihood that women will be competing for access to mates at this time. For example, Fisher
(2004) showed that derogation of female faces (i.e., rating them as less attractive) increases in the fertile compared to the non-fertile phase of the menstrual cycle. Cobey et al. (2013) found that female intra-sexual competition (as measured by a 12-item scale) was lower when pair- bonded women were using hormonal contraceptives than when regularly cycling. However, they did not observe any difference between fertile and non-fertile phases of the menstrual cycle (in
18 CHAPTER 1 a repeated-measures design; although this design was hindered by a small sample size, N = 28).
In addition, use of these tactics can differ according to contextual factors. For example,
Vaillancourt and Sharma (2011) demonstrated that women were much more likely to derogate a competitor who was wearing more revealing clothes, while Fisher and Cox (2010) found that pair-bonded women engaged in more competitor derogation than single women. Fisher and Cox, however, did not find that women’s and men’s tactics differed. The specific tactics that women use, therefore, in order to compete with other women for access to mates, as well as on which contexts these are dependent, is an area of research that requires more attention.
1.6 Assortative Mating
If sexual strategies have been under selection pressures, then this means that some variation in their use must exist or there would be nothing upon which selection could act. A strategy where all men sought a short-term pairing with a high quality female and all females sought a long-term pairing with a high quality male, and no one was deceptive as to their underlying mate quality, would result in reproductive success for only the lucky few. Instead, as has been discussed, these strategies are both condition and context dependent, since the costs and benefits of a particular sexual strategy are weighed on an individual basis, and the strategy that is most likely to be successful will be employed, resulting in a state of strategic pluralism in both sexes (Gangestad & Simpson, 2000). This means that individuals must have some (most likely unconscious) means of judging the host of factors, such as environmental circumstances and their own mating value (a proxy for their likely demand in the mating market) that are likely to affect the costs and benefits of engaging in a particular mating strategy. Thus, external factors
(e.g., socio-economic and cultural factors), self-perceived mate quality (e.g., based on feedback on one’s appearance from others; Reeve, Kelly, & Welling, 2016), and internal factors (including the proximate developmental influences that result in variation in underlying hormones), are likely to interact in a variety of ways to affect mating strategies (see Jennions & Petrie, 1997).
19 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
This mediates the effort that individuals will put into seeking a short-term or long-term partnership (or both, or neither), and with whom. In the end, not everyone is competing for access to the highest quality exemplar, but instead likely assesses the costs and benefits of putting effort into a potential mating opportunity. Thus people are likely to put effort into accessing the highest quality mate that they perceive they can realistically obtain, or, at least, would be best suited, given the circumstances (e.g., Gangestad & Simpson, 2000). This differs between individuals and is one of the factors that drives assortative mating, which is the concept that individuals typically end up mating with individuals who are very similar to them on a range of characteristics (e.g., Baldauf, Kullmann, Schroth, Thunken, & Bakker, 2009). For example, Buss and Shackleford (2008) demonstrated that women rated high in physical attractiveness had higher standards for four indicators of mate quality: good genes, good investment abilities, good parenting abilities, and good partner traits. Alternatively, women lower in physical attractiveness lowered their standards for these traits, thus compromising by desiring the best combination of characteristics from an individual, or engaging in a dual mating strategy, that is, seeking different qualities from different mates, potentially by provisioning resources from a long-term mate and good genes from a short-term or extra-pair mate. Indeed, there are a range of benefits that can be gained from pursuing a relationship with a self-similar mate rather than pursuing the highest quality exemplar, such as increased relationship stability, increased fecundity, and increased within-family altruism (Rushton, 1989).
One of the most striking examples of internal factors mediating attraction to potential mates comes from research demonstrating that women find attractive the scent of men whose
Major Histocompatibility Complex (MHC) is complementary to their own (Wedekind, Seebeck,
Bettens, & Paepke, 1995). Genetic relatives tend to share many of the same alleles in the MHC, and women will rate the scent of men who have an MHC complex that is most dissimilar to their own as more attractive than the scent of men with a similar MHC complex (Wedekind et al.,
1995). Since mating with someone with a dissimilar MHC complex will result in better overall
20 CHAPTER 1 genetic heterozygosity (and therefore increased disease resistance for offspring), this mechanism has likely been selected for as a means of inbreed avoidance, and as a means of mating with someone who will provide one with the healthiest offspring.
Another example of assortative mating comes from studies demonstrating that men and women are attracted to faces similar to their own, although with some caveats. That is, individuals are attracted to potential mates who have similar facial characteristics to their own, as long as they are not too similar, and therefore likely to be closely related kin. Additionally, these preferences are dependent on the mating goals of the individual. For example, DeBruine,
Jones, and Perrett (2005) demonstrated that women’s preferences for self-similar faces increase in the luteal phase of the menstrual cycle (when women are less likely to conceive and are more interested in seeking caregiving qualities), compared to the follicular phase (when they are more likely to conceive and therefore possess an increased desire to seek a quality genetic counterpart). This is likely because the peak in progesterone in the luteal phase of the mensutral cycle is designed to prepare the body for pregnancy, if a conception event has occurred (Jones et al., 2008a). Thus, attraction to particular faces is dependent on the underlying mating goals of the individual (in this case moderated by hormonal influences), and results in variation in what individuals find attractive.
As previously discussed, the traits that one can use to judge the quality of potential mates varies widely between individuals. Hence, based on the concepts of assortative mating, attraction to indicators of the highest quality mates should vary in accordance with variation in one’s own mate value and set of mating strategies. These processes have likely evolved to ensure that individual effort put into pursuing a particular mating strategy is going to result in the most successful level of reproductive output, given one’s own condition and environmental context.
Hence, the range of individual differences in the signals that one sends to others are likely to mediate the effort an individual will put into their own mating strategy, and thereby affect attraction to particular traits in others, preferences for relationship types, and self-perceived mate
21 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES value. This complex interaction between the signals sent to others and attraction to signals in others is the major focus of this thesis.
1.7 The Role of Hormones in Mating Psychology
The role of hormones in mating psychology (of all animals, not just humans) is the focus of a large body of research. There can be little doubt that our hormone levels are related strongly to our mating behaviour. For example, hormonal systems play a critical role in the development and maintenance of human social relationships in general (Gangestad & Grebe, 2016), and can even have specific effects on relationship investment following childbirth (Saxbe et al., 2016).
Endocrine systems motivate our behaviour in a variety of ways, assisting us to flee from potential threats (Kaldewaij, Koch, Volman, Toni, & Roelofs, 2016), and form attachments with our offspring (Atzil, Hendler, & Feldman, 2011). However, even with a long history of investigation, many questions remain unanswered. Even the role that specific sex hormones play in male and female sexual desire has lately produced mixed evidence (e.g., Cappelletti & Wallen, 2016;
Carvalho & Nobre, 2011; Giles, 2008; van Anders, 2012). Questions that remain unanswered include the extent to which hormonal variation is reliably correlated with facial shape variation
(e.g., Hodges-Simeon, Hanson Sobraske, Samore, Gurven, & Gaulin, 2016), or whether variation in women’s preferences for masculine faces is driven by estradiol level versus progesterone or testosterone (e.g., Marcinkowska et al., 2016; Welling et al., 2007). One of the most influential lines of research on our understanding of the role of hormones on human mating preferences has been that of the cycle-shift hypothesis (Gangestad et al., 2002), which examines the within-individual variation in mating preferences across the female menstrual cycle.
Investigation of the role of the menstrual cycle and specific hormone variation can help us to understand one of the potential mediating mechanisms of strategic pluralism in mating strategies.
22 CHAPTER 1
1.7.1 The Cycle-Shift Hypothesis
The cycle-shift hypothesis (Gangestad et al., 2002) proposes that women have evolved psychological mechanisms that increase preference for markers of high quality in the opposite sex specifically during the fertile phase of the menstrual cycle. This is supposed to reflect a dual strategy occurring within the same individual, wherein women may gain long-term care and resources from a partner when in the non-fertile phase of the menstrual cycle, but increase their desire for copulations with a male of high genetic quality when fertile, since their conception risk increases at this time. While some researchers argue about the existence of these effects (as discussed below), the majority of evidence indicates a clear shift (Gildersleeve, Haselton, &
Fales, 2014). This includes increased preference for the faces and voices of masculinised men, and dominating behavioural displays, and increased willingness to engage in sexual behaviour and copulate with extra-pair partners around the time of ovulation (e.g., Gangestad, Simpson,
Cousins, Garver-Apgar, & Christensen, 2004; Gangestad, Thornhill, & Garver-Apgar, 2005a,
2005b; Grebe, Gangestad, Garver-Apgar, & Thornhill, 2013; Jones et al., 2008a; Rosen &
López, 2009). For example, women who are naturally cycling (but not women who are using hormonal contraceptives), display shifts in attraction to masculine faced men in the days preceding ovulation, specifically when judging these males as potential short-term sexual partners (e.g., Little & Jones, 2012; Little, Jones, & DeBruine, 2008a; Penton-Voak & Perrett,
2000). Reliably capturing these changes and their relationship to hormonal variation appears to depend on a number of measurements, made at particular points in the menstrual cycle
(Gangestad et al., 2016). In addition, they are affected by individual differences between the women participating, such as menopausal changes in fertility status (e.g., Vukovic et al., 2009), relationship status, (e.g., Havlicek, Roberts, & Flegr, 2005), and between-subjects hormone levels (e.g., Feinberg et al., 2006). What these varying findings likely indicate is not necessarily the ‘dubious’ nature of these shifts (e.g., Harris, 2011; Harris, 2012), but rather the beautiful
23 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES complexity of mating strategies and their moderation by a number of biological, life history, and contextual factors.
For instance, Waynforth, Delwadia, and Camm (2005) demonstrated that women who have higher socio-sexual orientation (increased willingness to engage in a casual sexual encounter) display a higher preference for masculine faces than women lower in socio-sexuality.
Additionally, Little and Jones (2012) showed that cycle-shifts toward preferring masculine faces when in the fertile phase of the menstrual cycle is strongest when women are asked to judge faces for a short-term relationship partner, and that this effect disappears when asked to judge for long-term attractiveness. In a similar study, Little et al. (2008a) found that women’s increased preference for masculine faces in the fertile phase of the menstrual cycle is driven by the difference between fertile and non-fertile women who were already partnered. Women who were single displayed no difference in masculinity preference between the two phases of the menstrual cycle. In addition, Gangestad, Thornhill, and Garver-Apgar (2010) demonstrated that women’s preference for extra-pair partners in the fertile phase increased as their primary partner’s facial masculinity decreased. So increased masculinity preference might function to either orient women towards more masculine males when the chances of conception are high, or as a mechanism for increased sexual arousal to one’s own partner, depending on the quality of the primary partner and a female’s openness to sexual encounters. Thus, menstrual cycle phase is an important factor to consider when investigating mating strategies.
Questions have arisen as to whether or not these variations in mating preferences truly reflect functional evolutionary adaptations (Havliček, Cobey, Barrett, Klapilová, & Roberts,
2015), while others have questioned which preferences do, in fact, show a shift (e.g.,
Marcinkowska et al., 2016). In addition, researchers have questioned whether these shifts occur at all (e.g., Harris, 2011; Harris, 2012). For example, Wood, Kressel, Joshi, and Louie (2014) determined, based on a meta-analysis of 58 independent reports, that the evidence for cycle- shifts in female mare preferneces are largely non-supportive. However, another meta-analysis
24 CHAPTER 1 published in the same year by Gildersleeve et al. (2014) argues evidence for ‘robust cycle shifts’
(p.34). Importantly, Gildersleeve et al. examined the effects of short-term vs long-term mate preferences separately, an assertion that is theoretically supported (Gangestad & Simpson,
2000), whereas Wood et al. did not. Given that naturally occurring variation in hormones result in changes in behaviour that are subtle, it is not surprising that failing to separate short-term from long-term effects results in differences in conclusions between Gildersleeve et al. and Wood et al. Another way to examine this can be to artificially cease menstrual cycle variation in hormone levels via the use of hormonal contraceptives.
1.7.1.1 Hormonal Contraceptives.
The observable differences between women using hormonal contraceptives and those not demonstrates the influence not just of naturally occurring hormonal variation on female mating strategies, but the effects that artificially manipulating hormone levels can have. Hormonal contraceptives work to decrease the chances of a conception event (Alvergne & Lummaa, 2010).
In the combined oral contraceptive pill, the naturally occurring peak in follicle stimulating hormone and luteinizing hormone mid-cycle, which stimulates ovulation, are inhibited by artificial estrogen and progesterone levels (Alvergne & Lummaa, 2010). Given this, many of the effects of hormonal contraceptives are similar to those observed in naturally cycling women in the non-fertile phase of the menstrual cycle, and the cycle-shift is absent. For example, Little,
Burriss, Petrie, Jones, and Roberts (2013) demonstrated that initiation of hormonal contraceptives decreased women’s preferences for masculinity in faces. In this study, partners of women who were not using hormonal contraceptives upon initiation of the relationship had more masculine faces than partners of women who were using hormonal contraceptives at time of relationship initiation. While evidence exists that there is some pre-existing differences between hormonal contraceptive users and non-users (Oinonen, Jarva, & Mazmanian, 2008), a review of the effects of hormonal contraceptive use on female mating psychology (Welling,
2013) discusses how the uptake of hormonal contraceptives can have real impacts on mating
25 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES behaviours and psychology. For example, hormonal contraceptive use affects short-term sexual desire, number of sexual partners, stress responses, and increased information processing.
Inhibiting the naturally occurring variation of hormone levels can have real life consequences on women’s mating behaviour, further demonstrating that our internal biological state can drive our preferences.
1.8 Thesis Structure and Research Questions
In summary, men and women have been under differential evolutionary pressure to develop mating strategies that are in constant competition with one another. These strategies include variation in the cues signals of mate quality that same- or opposite-sex individuals might use to make judgements about potential mates and competitors, and attention allocation and perceptual preferences in order to distinguish between these. This has also driven the evolution of intra-sexual and inter-sexual competitiveness tactics. Given the concepts of assortative mating and strategic pluralism, then, on an individual level, these mating strategies are dependent on a huge range of factors and result in a wide range of individual differences. This body of research provides a detailed overview of individual variation in a range of these mating strategies, and the factors on which they are dependent, or interact with (such as context, or individual variation in mating motivations or mate quality). More specifically, the factors of interest were judgement context (that is, short-term or long-term relationship judgements), relationship orientation
(current relationship status, socio-sexuality, and desire to engage in a relationship), self-rated mate value (mate value and mating ‘intelligence’), signals of sexual arousal and promiscuity
(pupil dilation), and cues to health and internal biological state (circulating hormone measures, hormonal contraceptive use, and body mass index). The dependent mating strategies of interest were the signalling of mate quality to others (thus, intra-sexual tactics), whether physical or behavioural, via variation in facial dimorphism, clothing choice, and use of artificial scent; and the interpretation of information about mate suitability or potential competition from others
26 CHAPTER 1
(thus, inter-sexual tactics) via attention allocation and attractiveness ratings. In doing so, this thesis attempts to answer the following five questions:
1. How do men and women allocate attention when judging the suitability of a potential partner? In Chapter 2, I examine sex differences in attention allocation to the face or body of a potential mate, in line with sexual strategies theory. I also explore how mate value factors and socio-sexual orientation influence the subjective importance of the face or body in making a mating decision. In order to understand further how awareness of opposite-sex preferences can drive competitive tactics, I also examined the extent to which both sexes are aware of the attention allocation of the opposite sex.
In Chapter 3, I explore further attention allocation of men to women’s faces and bodies via eye-tracking analysis. In this way, we can observe whether judgement context, self-rated mate value, and the variation in a potential cue to mating motivation (female clothing choice) influence attention allocation.
2. Do women change their overt signalling of mate quality across the menstrual cycle?
In Chapter 4, I examine how women change their dress across the menstrual cycle, as a means of ascertaining whether clothing scarcity and perceived effort put into appearance vary with hormone levels and menstrual cycle phase, and thus act as a signal of mating motivation.
3. Do women signal their mate-value through means other than behaviour and appearance? Given the importance of scent, however subtly, to mate choice, variation in preferences based on the scent of someone MHC-compatible, and the popularity of perfume throughout history, particularly as a signal of status, I sought to examine the role of moderation of scent as a mate attraction tactic. Thus, in Chapter 5, I explore several factors that could influence women’s use of artificial scent.
4. How do individuals respond to variation in facial characteristics in potential mates or competitors? In Chapter 6, I examine men and women’s attractiveness ratings of faces that vary in dimorphism and pupil size. In this way, I was able to examine reciprocity of attraction (pupil
27 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES dilation being a potential signal of sexual arousal), and to determine whether this attraction to pupil dilation in others is dependent on context, sex, and individual difference variables. I also explored variation in competitor derogation of same-sex individuals.
5. How do men and women’s facial structure and perceived attractiveness vary in response to underlying hormone levels, and do perceived facial attributes and objective facial structure correlate? In Chapter 7, I examine how individual facial morphology varies with hormone concentrations, both between male individuals and within female individuals across the menstrual cycle, and how this influences subjective judgements made by others.
1.9 Common Measurement Tools
I have used several measurement tools consistently throughout this thesis. To avoid repetition, I have detailed each of these scales below, and present further specific details, where required, in each chapter.
1.9.1 Sexual Orientation Scale
The Sexual Orientation scale (Kinsey, Pomeroy, & Martin, 1948) measures sexual orientation on a continuous scale from 0 (exclusively heterosexual) to 6 (exclusively homosexual), similar to the scale displayed in Figure 1.1.
Figure 1.1. Kinsey Heterosexual-Homosexual Rating Scale
28 CHAPTER 1
Participants mark the number that best describes their sexuality, on the following scale:
0- Exclusively heterosexual
1- Predominantly heterosexual, only incidentally homosexual
2- Predominantly heterosexual, but more than incidentally homosexual
3- Equally heterosexual and homosexual
4- Predominantly homosexual, but more than incidentally heterosexual
5- Predominantly homosexual, only incidentally heterosexual
6- Exclusively homosexual
1.9.2 Hormonal Details
In several of the following chapters, I have been interested in examining the effects of menstrual cycle phase or hormonal contraceptive use on various behavioural and hormonal measures. Where I have specified that participants provided details of their menstrual cycle or contraceptive use, the questions asked were:
Are you currently pregnant or breastfeeding?
Are you currently using any form of hormonal contraceptive?
On what date did your most recent menstrual period start?
On what date do you expect your next menstrual period to start?
Generally speaking, are your periods regular or irregular?
What is your usual cycle length?
1.9.3 Socio-Sexual Orientation Inventory
The Socio-Sexual Orientation Inventory-Revised (SOI-R; Penke & Aspendorf, 2008) measures the tendency of individuals to engage in sexual relationships with little to no deeper emotional commitment. The revised scale measures short-term relationship orientation across three domains: behaviour, attitude, and desire. Each sub-scale consists of three questions, such as “Sex without love is ok” (1: Strongly disagree to 5: strongly agree), “How often do you
29 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES experience sexual arousal when you are in contact with someone with whom you do not have a committed romantic relationship?” (1: Never to 5: Nearly every day), and “With how many partners have you had sex in the past 12 months?” (1 – 0 to 5 – 8 or more). The behaviour sub- scale measures actual short-term relationship behaviour, the attitude sub-scale attitudes towards engaging in short-term relationships, and the desire sub-scale the frequency of engaging in sexual fantasies. For the full scale, see Appendix A.1.
1.9.4 Mate Value Inventory
The Mate Value Inventory (MVI; Kirsner, Figueredo, & Jacobs, 2003) is a multivariate assessment of attributes desired in social or sexual partners. The inventory consists of a number of scales that measure Ideal and Real/Attainable characteristics in a long-term partner, a short- term partner, a best friend, and one self. Each scale consists of 19 attributes (17 in the self-rated mate value scale) such as “attractive body”, “financially secure” and “ambitious”, that participants are asked to rate on a 7 point likert scale from -3 (extremely low on this trait) to 3
(extremely high on this trait). Throughout this thesis, I have exclusively used the self-rated mate- value inventory (hereafter denoted by MVI-S) to measure one’s perceptions of their own mate- value. For the full scale, see Appendix A.2.
1.9.5 Mating Intelligence Scale
The Mating Intelligence Scale (MIS; Geher & Kaufman, 2007) purports to measure relationship ‘effectiveness’, though reading the items at face value, the scale measures short- term mating confidence (whether or not this is always the best tactic, which would be denoted by mating intelligence). This is because the items include questions such as “Women definitely find me attractive”. The scale itself was originally designed as a ‘fun’ questionnaire for a popular psychology magazine, Psychology Today, though has since been shown to predict actual sexual behaviour in college age adults (O'Brien, Geher, Gallup, Garcia, & Kaufman, 2010). The scale has two forms, for men and women, with 24 questions such as “I can tell when a man is being
30 CHAPTER 1 genuine and sincere in his affections towards me” that participants answer about themselves as true or false. For the full scale, see Appendix A.3.
*All research reported in this thesis was conducted in line with the University’s Human
Research Ethics Committee’s approval, based on the National Guidelines for Ethical Conduct in Human Research.
Research protocols: H-2009-0311, H-2009-0312, H-2012-0398
31 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
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48 CHAPTER 2
Chapter 2: Sex Differences in Importance of Faces or Bodies in Mating Decisions.
Authors note:
Parts of this chapter were included in a manuscript published in Evolution, Mind and Behaviour.
Copyright remains with the publisher (See Appendix B). The manuscript was co-authored by
Danielle Wagstaff, Danielle Sulikowski, and Darren Burke. The author contributions were:
Danielle Wagstaff – conceptualisation, data collection and analysis, and preparation
Danielle Sulikowski – data analysis and preparation
Darren Burke – preparation
Signed,
Danielle Wagstaff
Danielle Sulikowski
Darren Burke
49 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
2.1 Chapter Overview
The purpose of the following chapter is to explore evolved sex-differences in attention allocation to the face or body, and how this varies based on context. By doing so, not only can I demonstrate variation in the distribution of cues to mate quality between the sexes, but also how mate-value factors, such as self-rated mate value and socio-sexuality, influence people’s attention allocation to these mate cues. In addition to this, I also sought to explore perceptions about opposite-sex attention allocation. Thus, I try to explore sex differences in signalling of sexual intent. This allows us to understand whether men’s and women’s attention to different cues of mate quality might impact on their awareness of which signals opposite-sex conspecifics will be paying attention to, allowing for the potential of individuals to manipulate them to suit their needs.
2.2 Introduction
2.2.1 Attention Allocation Between the Sexes
In humans, both sexes make mate-choice decisions that rely on multiple physical cues of different components of mate quality. In some cases, the same physical region might contain cues relating to different components of mate quality. Masculinity and femininity in faces, for example, can provide cues relating to investment potential and immunocompetence (Boothroyd,
Scott, Gray, Coombes, & Pound, 2013; although see also Scott, Clark, Boothroyd, & Penton-
Voak, 2013, for an alternative viewpoint on these arguments) and competitive advantage (Li et al., 2014) for males, and fertility (Rhodes, Simmons, & Peters, 2005) for females. Other cues and signals, such as symmetry (thought to be an indicator of genetic resistance to developmental stressors, Gangestad, Thornhill, & Yeo, 1994) are simultaneously displayed by both the face and body (Pflüger, Oberzaucher, Katina, Holzleitner, & Grammer, 2012). Importantly, some cues are likely to be more readily perceived, or more strongly signalled, from one region compared to another. Kramer, Gottwald, Dixon, and Ward (2012) showed that people more accurately
50 CHAPTER 2 judge physical health from women’s bodies, but more accurately estimate agreeableness (which relates to parental care investment; Bradley, Whiteside-Mansell, Brisby, & Caldwell, 1997) from women’s faces.
Women’s faces signal developmental quality, pathogen resistance, and phenotype quality
(Grammer & Thornhill, 1994) and are thus important in signalling both fertility (short-term reproductive potential) and fecundity (long-term). Indeed, moderate correlations are evident between men’s attractiveness ratings of women’s faces and bodies (e.g., Thornhill & Grammer,
1999). However, men show a consistent difference in their preference for looking at women’s faces or bodies, depending on whether they are making short-term or long-term judgments, with their preference for bodies increasing for short-term judgments (e.g., Confer, Perilloux, & Buss,
2010; Jing Lu & Chang, 2012). Proximity to ovulation increases the subjective attractiveness of women’s dance (Fink, Hugill, & Lange, 2012) and gait (Guéguen, 2012), the symmetry of soft tissues such as breasts (Scutt & Manning, 1996), and is associated with wearing more revealing clothing (Durante, Li, & Haselton, 2008; Saad & Stenstrom, 2012). Additionally, the waist-to- hip ratio may act as a cue to reproductive potential, with women with low WHR’s (0.7) being perceived by men as more attractive and with a higher desire and capacity for having children
(Singh, 1993). While ovulation may also be perceived from changes in facial skin-tone (van den
Berghe & Frost, 1986) and attractiveness (Roberts et al., 2004), these changes are subtle and may be more easily obscured (with cosmetics, for example). Changes in bodily movement, symmetry and dress, therefore, might offer a more readily perceptible cue to current fertility than the face, in a modern environment.
Sex differences in minimal parental investment (Trivers, 1972) mean that men, moreso than women, may benefit from copulation with a large number of partners and, as a result, are typically more willing than women are to engage in casual sexual encounters. For men pursuing such a strategy (Buss & Schmitt, 1993), the readily perceptible cues of cyclical fertility in the female body may offer more reliable signals of current fertility and intention than those in the
51 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES female face. For men pursuing a long-term mating strategy, however, the long-term fecundity cues present in a woman’s face may be of more importance.
Women on the other hand, gain maximally by increasing the quality, rather than quantity of sexual partners, whether they are pursuing a long-term or a short-term sexual relationship.
This coupled with the fact that male receptivity does not change cyclically, may lead women to exhibit a less changeable preference for the male face or body, respectively, when making judgments about long and short-term relationships. This is especially likely to be true given the apparent redundancy of mate quality cues seen in men's faces and bodies. There are high correlations in ratings of attractiveness between males' face, body, vocal pitch, and scent (e.g.,
Feinberg, DeBruine, Jones, & Little, 2008; Fink, Täschner, Neave, Hugill, & Dane, 2010) and high correlations between facial attractiveness and grip strength, and high shoulder to hip ratios
(Shoup & Gallup, 2008). While women have been shown to prefer increased masculinity when judging men for a short-term versus a long-term relationship, they prefer this increase in masculinity similarly across both the face and body (e.g., Little, Connely, Feinberg, Jones, &
Roberts, 2011). Given that women desire qualities in long-term partners, such as ability to acquire resources, and short-term partners, such as immediate acquisition of resources and physical protection (Buss, 2006) that are both readily observed from the face and body (Little et al., 2011), we should expect little difference in women’s preference for the face or body between contexts.
The differential distribution of cues of mate quality across faces and bodies is thought to be responsible for effects of sex (both observer and observed) and relationship-context on the relative importance of faces and bodies when making hypothetical mating judgments. For example, Confer et al. (2010) demonstrated that men making short-term relationship judgments
(where immediate fertility is most important) exhibit a stronger preference to see the body of a female rather than her face (when given a mutually exclusive choice), than when making long- term relationship judgments, where long-term fecundity is more important. There was no such
52 CHAPTER 2 effect of relationship type on women’s preferences for the male face or body. Similarly, Jing Lu and Chang (2012) showed that men spend more time looking at the waist/hip area than the face, when prompted for a short-term relationship, with equal time allocation to these areas following a long-term relationship prompt. Again, women were unaffected by long- or short-term context.
Currie and Little (2009) found that ratings of facial attractiveness when faces are presented independently of the body are better predictors of overall attractiveness of simultaneous face/body presentation than attractiveness ratings of the body presented independently.
Critically, this effect was stronger in long-term rating conditions than short-term conditions for men’s ratings of female bodies, but not for women’s ratings of male bodies.
2.2.2 Contextual Factors Influencing Allocation of Attention
A variety of environmental and life history factors influence mating strategies, and so might also predict the extent to which a man would rely on female facial or bodily cues of attractiveness. Confer et al. (2010) demonstrated a positive correlation between men’s socio- sexual orientation (positive attitudes, desires and behaviour toward casual sex, SOI-R: Penke &
Aspendorf, 2008) and rated priority of information from women’s bodies. Other measures that, similarly to the SOI-R, are influenced by the extent to which men are pre-disposed to pursue a short-term strategy, should also predict the extent to which men preferentially rely on female bodily cues. Two such measures are the MIS (Geher & Kaufman, 2007) and the MVI-S (Kirsner,
Figueredo, & Jacobs, 2003).
‘Mating Intelligence’, the set of cognitive constructs related to navigating mating interactions (Geher & Kaufman, 2007), while initially proposed as a ‘fun’ scale for a popular psychology magazine, has since been shown to predict ‘hook-up’ behaviour in college students
(O'Brien, Geher, Gallup, Garcia, & Kaufman, 2010): women with high MIS scores have more hook-ups with potentially higher quality men (men who would be good candidates for long-term relationships), and men with high MIS scores have more hook-ups overall. These findings also
53 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES suggest that MIS should correlate positively with the SOI-R scale. According to the scale's authors, though, MIS is less a measure of individual character, and more a measure of relationship ‘effectiveness’ (Geher & Kaufman, 2013, pp. 217-231). Our reading of the scale's items (and its behavioural correlates) suggests it may be even better characterised as a measure of short-term mating confidence. This is because the face validity of the items relate to confidence in the ability to attract members of the opposite sex (e.g., “I’m good at saying the right things to women I flirt with”) and self-esteem surrounding the opposite-sexes sexual interest in oneself (e.g., “Women definitely find me attractive”). Since men’s short-term mating strategy is characterised by pursuing more instances of intercourse, with emphasis on the body when judging short-term female mate value, we expect MIS to predict male preference for information from the female body. Additionally, given the MIS scale has only been used in a limited number of previous studies, we also sought to further investigate its construct validity, via its relationship to other scales more commonly used in mating research.
Self-rated mate value (MVI-S) is correlated with an individual’s preference for symmetry and dimorphism in a potential partner (Little, Burt, Penton-Voak, & Perrett, 2001), and increases in self-perceived mate value precede increases in men’s preference for casual sexual encounters
(Surbey & Brice, 2007). In addition, men who are aware of their own mate-value are typically more oriented toward a short-term mating strategy (Back, Penke, Schmukle, & Asendorpf, 2011) are sexually competitive (in the mating market) to be more successful in employing a short-term
(and long-term, for that matter) mating strategy. Women seeking extra-pair short-term partners typically seek high quality males for such encounters (Greiling & Buss, 2000), suggesting that such men would be more successful than low quality males at pursuing a short-term mating strategy. We predicted that MVI-S scores, therefore, should also positively correlate with men’s preference for female bodies.
54 CHAPTER 2
2.2.3 Cross-Sex Awareness of Cue Preferences
As discussed in Chapter 1, women often compete for access to men through changes in their appearance (e.g., Campbell, 2004; Goetz, Easton, & Buss, 2014), whereas men compete through either feigning or drawing attention to their commitment and ability to secure resources
(Tooke & Camire, 1991; Walters & Crawford, 1994). For example, manipulations of men’s monetary status (with cars and apartments) will affect women’s ratings of attractiveness, but manipulation of women’s status has no effect on men’s ratings of attractiveness (Dunn & Hill,
2014; Dunn & Searle, 2010). Indeed, men self-report tactical motives for giving gifts (such as displaying financial resources and creating a good impression) more frequently than women
(Saad & Gill, 2003). When asked about opposite-sex use of tactical motives, women report men as using these gift-giving tactics more frequently than themselves, whereas men believed both sexes used these tactics with similar frequency.
Awareness of men’s’ preferential reliance on face or body cues, would allow women to differentially enhance (or reduce) cues to their own fertility status (and intentions) dependent on their own mating goals and the perceived intentions of the man. On the other hand, as men’s mating tactics less often involve enhancement of attractiveness, and women seek qualities which are readily observed from both the face and body of men regardless of context, it is less likely that men have experienced selection pressure to be aware of where women will allocate attention when required to make a mating decision. We might therefore predict that women will more accurately predict the face or body preferences of men, than men will of women, and thus that women will accurately predict greater male preference for the body in short-term, compared to long-term, scenarios.
2.2.4 Current Study
Previously, Confer et al. (2010) presented participants with a figure occluded by two boxes, a face box and a body box, and asked participants to remove one of the boxes in order to
55 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES make a decision about whether the occluded person would be suitable as a short-term or long- term partner. They also asked participants to what extent the face or the body was important in making these decisions, correlating these measures with SOI-R. In the current study, we employed Confer et al's. (2010) basic design, asking participants whether they wished to remove a ‘head box’ or ‘body box’ covering a potential mate to assist in a long-term or short-term mate choice decision. In addition to this however, we also investigated how other mate-value factors
(MVI-S and MI) influenced this decision. Participants not only made the face/body judgment for themselves, but also indicated how they thought an opposite sex participant would respond in a similar scenario, allowing us to examine the extent to which individuals are aware of opposite-sex preferences for looking at the body or the face of potential mates. In line with
Confer et al. (2010), we predicted that men, but not women, would exhibit a stronger preference to view the body when prompted with a short-term, rather than a long-term mating scenario. We also predicted that SOI-R, MIS, and MVI-S would positively correlate with preferences for the body in men, but not women. Lastly, we predicted that women would be more accurate than men at predicting opposite-sex preference for the face or body.
2.3 Methods
2.3.1 Participants
Participants who indicated they were not heterosexual (n = 24), or who indicated they were pregnant (n = 2), were excluded from analysis. The remaining participants consisted of a convenience sample of students undertaking an introductory Psychology course from an
Australian University, and volunteers who were registered as part of an online experimental management system; comprising 65 males, age 18 - 34 years (M = 21.8, SD = 3.6) and 191 females, aged 18 - 36 years (M = 21.2, SD = 3.1).
56 CHAPTER 2
2.3.2 Materials and Procedure
Participants first provided information about age, sex, and sexual orientation (Kinsey
Sexual Orientation Scale; Kinsey et al. 1948), and then were provided with a stick figure diagram divided into two sections, a face box and a body box, beneath which was a figure of the opposite- sex (see Figure. 2.1). The occluded figures consisted of stock photos of two clothed individuals, one man and one woman, that were obtained through an Internet search, and the boxes were created using a stick figure on an ivory background, Participants were asked to imagine they were single and then were randomly assigned to judge the occluded figure as suitable for either a short-term (one-night stand/affair), or long-term (eventually move in with or marry) relationship.
Figure 2.1. Demonstration of box choice, from left to right: complete box, female face revealed,
male body revealed
To help guide their decision, participants could choose to look at either the occluded person’s face, or body. For continuity, once participants made their choice, they were shown either the face or the body of the occluded figure (as demonstrated in Figure 2.1). Participants then made a similar judgment based on what an imagined person of the opposite-sex would do in a scenario in which they were also judging a potential mate (with the same allocation to either
57 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES a short-term or long-term context). After both trials, participants were asked to rate how they prioritized information about which box to remove, on a scale from 1 (face much more important) to 7 (body much more important). Lastly participants completed the SOI-R (Penke
& Aspendorf, 2008), MVI-S (Kirsner et al., 2003), and MIS (Geher & Kaufman, 2007).
2.4 Results
Data were analysed using SPSS v21 for Mac. Statistics reported are two-tailed.
2.4.1 Sex Differences in Box Choice
We conducted a χ2 cross-tabulation within each sex to examine the effect of mating context on box choice. As predicted, men exhibited a significant association between mating
2 context and cue preference [χ 1 (N = 65) = 8.66, p = .004], with below chance removal of the body box in the long-term condition (16%) but not in the short-term condition (52.5%). Also, as
2 predicted, context had no effect on women’s choice of face or body box [χ 1 (N = 191) = .128, p
= .832] (see Figure 2.2). Women did exhibit an overall binomial preference for removal of the face box [86.4%, N = 191, p < .0005].
2.4.2 Sex Differences in Importance of Information from Body versus Face
We also predicted that, similarly to box choice, men, but not women, would indicate an increased preference for information from the body in the short-term than long-term relationship context. A 2x2 factorial ANOVA, with participant sex and relationship context
(short-term or long-term) as factors, and priority of information from the body as the outcome,
2 revealed significant main effects of sex [F1,251 = 17.49, p < .0005, ηρ = .065], and relationship
2 context [F1,251 = 8.10, p = .005, ηρ = .031] and a significant sex-by-relationship context
2 interaction [F1,251 = 5.95, p = .015 ηρ =.023]. Simple effects contrasts confirmed that the difference between short-term and long-term ratings was significant for men, [F1,251 = 9.30, p =
2 2 .01, ηρ = .036], but not for women [F1,251 = 0.166, p = .684, ηρ = .001]. Additionally, men rated information from the body as significantly more important [F1,251 = 27.76, p < .0005,
58 CHAPTER 2
2 ηρ =.100] than did women in the short-term condition only, with no difference [F1,251 = 1.25, p
2 = .264, ηρ =.005] between men’s and women’s mean scores in the long-term condition, see
Fig. 2.3, men’s priority as rated by men, and women’s priority as rated by women. (A previous
2x2x2 ANOVA with current relationship status as the third factor revealed no effect of being partnered or single, and so relationship status was dropped from the analysis).
2.4.3 Correlations Between Body Priority Ratings and SOI-R, MIS, and MVI-S
The MVI-S and SOI-R scales had good internal reliability (MVI-S Cronbach’s α = .83,
SOI-R Cronbach’s α = .85). Not all participants completed all scales. Table 2.1 indicates the sample size and outcomes for all correlations, including confidence intervals. As predicted, men’s priority ratings for the body box positively correlated with their total SOI-R, MVI-S and
MI scores. For women, only total SOI-R was positively correlated with body box priority ratings.
Additionally, the MVI-S was positively correlated with both the MIS and SOI-R in males and females; and, for males only the MIS was positively correlated with the SOI-R (correlations shown in Table 2.1).
We also performed a linear regression analysis, with body importance ratings as the outcome, and SOI-R, MVI-S and MIS entered as predictors in one step. We found that a
2 significant model emerged only for men [R adj = .16, F3,48 = 4.00, p = .013], with only SOI-R as a significant unique predictor [β = .312, t48 = 2.12, p = .040]; the same model was not significant
2 for female participants [R adj = .02, F3,181 = 2.39, p = .070].
2.4.4 Opposite-Sex awareness of Face/Body Preferences
We performed a χ2 cross-tabulation within each sex in order to determine the effect of context on perceptions of opposite-sex box choice. In line with the hypothesis, men believed women would choose the body significantly less frequently than chance in the long-term
2 condition (20.0%) and significantly more frequently in the short-term condition (57.5%) [χ 1(N
= 65) = 8.823, p =.004], with overall preference for the face or body at chance levels. Women
59 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
oice collapsed across ST or (b) mating decisions in short-term (b) mating Average frequency of box ch box choice for self (a) or cross-sex Frequency distribution of body or face or long-term context for male and female participants. and female or long-term context for male by dashed lines indicated LT condition Figure 2.2.
60 CHAPTER 2
ation assigned to body, and mate value for male and female participants Correlations between importance of inform Table 2.1 sociosexual orientation measures
61 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES displayed an overall binomial preference for body box removal [74.3%, N = 191, p<.0001], and believed men would choose the body box significantly less frequently than average in the long- term condition (58.5%), and significantly more frequently in the short-term condition (86.2%)
2 [χ 1(N = 191) = 18.828, p <.0005] as demonstrated in Figure. 2.2.
One way of looking at participant ratings of how the opposite-sex would allocate attention, is to determine how ‘accurate’ these perceptions are, that is, how do they compare to how the opposite-sex have rated importance of the face or body in the context of making a judgment for themselves? In order to explore this, we performed a 2x2 between-subjects
ANOVA, with sex of participant and condition (short-term or long-term) as independent variables and ratings of importance of bodily information (for female stimuli vs. male stimuli) as dependent variables. That is to say, we were able to compare ratings of one type of stimulus
(for example, female stimuli), between men (when they were making a decision for themselves) and women (when they were making a judgment about what men would do). We predicted that women would be more ‘accurate’ than men would be at predicting differences in priority of information from the body between the two conditions. For choices made about male stimuli
(female self-choice vs. male opposite-sex choice), a main effect of sex was revealed, with men significantly overestimating women’s importance assigned to the body [F1,251 = 19.08, p <.0005,
2 ηρ = .071]. There was no main effect of condition and no interaction. Thus, men’s overestimation as to female preference for the body was constant across conditions. Similarly, for female stimuli (male self-choice vs. female opposite-sex choice), women also significantly
2 overestimated men’s body importance, with a main effect of sex [F1,252 = 23.76, p <.0005, ηρ =
0.09]. In addition, there was also a main effect of condition, with both sexes rating male priority for the body as significantly higher in the short-term than long-term condition [F1,252 = 17.77, p
2 < .0005, ηρ = 0.07] (see Figure 2.3), indicating that women accurately estimated men’s higher preference for bodily information in the short-term than long-term condition.
62 CHAPTER 2
Figure 2.3. Ratings of importance of information obtained from the face or body (higher scores
indicate preference for body), for male and female ratings, self-reported versus beliefs
about cross-sex importance, in either short-term or long-term mating conditions.
In order to determine the extent to which women and men judged opposite-sex allocation based on their own preferences, we performed a paired-samples t-test on the self-reported preference for body, versus predicted opposite-sex ratings for each sex. Women’s rating’s for men’s priority were significantly higher than their own priority rating [t189 = -4.41, p < .0005], whilst men’s ratings for women’s priority were no different from their own priority ratings [t64
= -0.29, p = .770].
63 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
2.5 Discussion
As previous research has shown (Confer et al., 2010), men show an increase in their preference for looking at the body of women, rather than the face, when prompted for a short- term relationship judgment over a long-term relationship, whereas women do not show this difference and generally prefer to look at the face. In this study, we aimed to replicate this trend, as well as to determine to what extent individual differences in mating related factors correlate with this decision, given that mate value and mating intelligence (e.g., O'Brien et al., 2010) are factors that predict men’s willingness to pursue a short-term relationship strategy (and might therefore be more willing to prefer the body to the face of female stimuli). In addition, given that men and women might have different selection pressures to be aware of opposite-sex preferences for looking at the face or body of potential partners, we investigated how accurate individuals of both sexes were in this judgment.
In accordance with the hypothesis, and consistent with previous research (Confer et al.,
2010), a higher proportion of men chose to look at the body box in the short-term than in the long-term condition, whereas women did not show this trend, preferring to look at the face regardless of condition. Similar findings were observed regarding men and women’s ratings of the importance of the body to making their decisions. We hypothesized that these ratings would positively correlate with increased self-rated mate value, in men but less so in women. We found this to be the case, with positive correlations between men’s ratings of the importance of the body in making a mating relevant decision, and their scores on the MVI-S, MIS, and SOI-R total score (although only SOI-R scores predicted unique variance in body importance scores).
Women too showed a weak positive correlation between their total SOI-R score and their ratings of the importance of information from the body of male stimuli, but body importance scores did not correlate with MIS or MVI-S in women. Overall, however, the mean rating for importance of bodily information for men was still substantially higher than for women. As discussed previously, this correlation between mate value and mating intelligence factors with men’s
64 CHAPTER 2 importance of using bodily information to make a mating decision is likely due to men’s increased pursuit of a short-term mating strategy when confident of their own ability to secure a variety of mates. Given the differential signalling of short-term and long-term suitability from women’s bodies and faces (Currie & Little, 2009), men who have higher confidence to pursue a short-term partnership are more likely to devote attention to women’s bodies.
Given the potential difference in selection pressures for being aware of opposite-sex preferences, and the evidence demonstrating women are aware of men’s frequency of use of tactical gift giving (Saad & Gill, 2003), we hypothesized that women would be more accurate in their prediction of men’s preferences than men would be in their prediction of women’s preferences. We demonstrated that while both sexes overestimated the importance the opposite- sex will place on information from the body, women still accurately judged that men would find the body relatively more important in short-term than long-term relationship contexts, which differed significantly to women’s own pattern of short-term/long-term decisions. On the other hand, men’s judgment of opposite-sex choice more closely resembled their own decisions, as they believed women would also find the body to be more important for a short-term mating decision.
According to Error Management Theory (Haselton & Buss, 2000) women tend to underestimate men’s commitment, thereby minimizing the cost of being deceived as to male intentions, whereas men tend to overestimate female sexual intention, as the cost to them of missing a mating opportunity is greater than that of misjudged interest. This may be especially true in scenarios in which women's mating intentions are not readily apparent. Thus both men and women overestimate opposite-sex short-term relationship orientation (see also Perilloux,
Easton, & Buss, 2012). In the current study, men also over-estimated women’s willingness to choose to look at the body of male stimuli. This may be explained if we consider that men assume that women make mating decisions based on the same cues as they do. Combined with a
65 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES tendency to overestimate female interest in short-term mating, this would lead to an overestimate of how often women would choose to examine the male body.
Women, too, overestimated men’s willingness to look at the body of the female stimuli.
However, they were more accurate in their perception of men’s increased willingness to look at the body in a short-term relationship context, and overall estimated men’s preferences differently to their own, whereas men showed no difference between the decisions made for themselves and those made for the opposite-sex. Overall, women exhibit greater empathy and are more flexible in both their perspective taking (Baron-Cohen & Wheelwright, 2004) and their sexual orientation
(Baumeister, 2000; Kinnish, Strassberg, & Turner, 2005) than are men. These sex differences may help explain why women in the current study were better able to indicate opposite sex preferences that were different to their own, whereas men assumed that women made similar decisions to themselves.
In addition to replicating the increased preference for the body in a short-term relationship context for men but not women, first demonstrated by Confer et al. (2010), we have also demonstrated a sex difference in perspective taking Other variables may also contribute to changes in the relative importance of the face and body, and opposite-sex judgments of such preferences, such as the age of the participant, and the age of the imagined individual they are making this judgment for. A limitation of the current study is that we did not ask people to make a judgment about someone of a specific age, but just someone of the opposite-sex. Whether or not people’s perceptions of what the opposite-sex would choose is based on perceived age remains to be seen.
Sensitivity to men’s preferences potentially allows women to enhance (or reduce) cues to sexual availability or reproductive capacity as they see fit, dependent on their own mating strategies. An interesting question that arises from this research is whether those women who were better able to predict men’s preferences utilize this knowledge in some meaningful way.
For example, previous research indicates that women’s self-reported use of more ‘sexy’ clothing,
66 CHAPTER 2 and independent observer’s judgments of ‘effort put into appearance’, increase during the fertile phase of the menstrual cycle (Haselton, Mortezaie, Pillsworth, Bleske-Rechek, & Frederick,
2007; Saad & Stenstrom, 2012). The exact reason for this is unclear, although it could be a means of attracting a short-term partner when more fertile and therefore more likely to conceive. If, as we are speculating, awareness of opposite-sex preferences allows greater control over how to use these cues to one’s advantage in the mating game, it may be the case that women who are more aware take greater advantage of this information. They may (consciously or unconsciously) alter their own appearance and dress more markedly across the menstrual cycle. This should be explored in future research.
In conclusion, sex differences in men’s and women’s willingness to allocate attention to the face or body of a potential sexual mate in a binary choice task, are dependent on their own rated mate-value and their socio-sexual orientation, as well as the relationship context of the judgment. Such preferences likely reflect adaptive motivations for seeking the most informative cues for the individual generally, as well as for the specific context of the judgment at hand.
Similarly, sex differences in judgments of opposite-sex preferences in the same binary choice task may reflect evolutionarily-driven motivations to weigh the costs and benefits of over- or under-estimating the sexual motivations of members of the opposite sex.
67 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
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73 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Chapter 3: Further Exploration of Men’s Attention Allocation to Women’s Faces or Bodies
3.1 Chapter Overview
Since men’s preference for looking at faces and bodies is dependent on the context of the judgement and self-rated mate value, as demonstrated in Chapter 2, the purpose of this chapter was to explore further this attention allocation, using a more fine-grained eye-tracking task. In
Chapter 2, I asked men (and women) to make a judgement about an occluded figure, and thus participants could choose to look at either the face or the body. The preferences in a binary choice task are likely to be reflective of the relative importance of this information, but does not necessarily tell us how much time is required to make a decision about whether another person’s face or body is suitably attractive, nor does it inform us about whether these visual cues drive attention allocation. However, judgements about an individual in a more naturalistic setting would typically occur after observing, and potentially interacting, with the individual. Thus, while men increase their preference for information from the body in short-term contexts relative to long-term (see Chapter 2) this preference may not reflect attention allocation in a more naturalistic viewing situation. In this chapter, I explore men’s attention allocation to images of women that are visible from head to toe, and vary in signals to mating motivation (that is, clothing choice). Again, I sought to understand how individual differences in other mating related factors determine attention allocation to particular body areas.
3.2 Introduction
Attention allocation to cues that may provide us with information about the suitability of a potential partner can help us efficiently solve the problem of whom to mate with, and as discussed in Chapter 1, this attention allocation should depend on individual variation in mating strategies. As outlined in Chapter 2, Confer, Perilloux, and Buss (2010) have shown that men
74 CHAPTER 3 pay differential attention to women’s faces and bodies depending on the context of the judgement. When men were asked to rate the suitability of a potential female partner, information about the face was largely preferred for long-term judgements, but the importance of the body increased, to equal that of the face, in the context of a short-term judgement. Women, on the other hand, largely prefer to look at a man’s face, regardless of the hypothetical duration of the relationship. This effect has also been replicated with a simple binary choice task (as reported in Chapter 2), and similar effects found by Jing Lu and Chang (2012) in a dot-probe task. So, while both men and women rate the face as highly important when making mating related judgments, women’s bodies may increase in importance for short-term judgements, perhaps because cues to short-term fertility (such as pregnancy) can be more easily observed. In addition to the obvious cues of pregnancy though, women’s use of revealing clothing may also signal their mating motivations, and potentially their ovulatory status. For example, Durante, Li, and Haselton (2008) asked women to illustrate (using pencil and paper) what they would wear for a “social gathering”. Figure illustrations were rated (by independent raters) as more revealing and sexy when women were in the fertile compared to the non-fertile phase of the menstrual cycle, and this effect was strongest for women who were closer to ovulation on their high fertility day. In addition, women’s clothing choices (as worn in to the lab that day) were rated as more sexy/revealing (by independent raters) when the women were single (rather than in a relationship), when they were more sexually experienced, and when they were higher in socio- sexuality. So increased attention to revealing areas of the body might be beneficial for men when prompted for a short-term relationship encounter (and thus are more interested in discerning the potential mating motivation of a potential partner).
In the studies discussed above, men’s preference for looking at the face or body of potential mates has been examined relatively broadly, using a binary choice task (Confer et al.,
2010) or dot-probe task (Jing Lu & Chang, 2012), and utilising self-report about the importance of this information. However gaze patterns are relatively naturalistic and difficult to alter
75 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES consciously (Nummenmaa, Hietanen, Santtila, & Hyona, 2012), and there has been a recent increase in the use of eye-tracking technology in the evolutionary psychology of attractiveness literature (e.g., Dixson, Grimshaw, Linklater, & Dixson, 2010; Garza, Heredia, & Cieslicka,
2016; Rupp & Wallen, 2007). Examination of the more specific patterns of eye-movements can provide valuable information about how we allocate attention when making mating-related decisions under various contexts. This includes information about total dwell time to various regions of interest and the frequency of fixations to these areas. These analyses can inform us about the relative desire to view particular areas of the body, as well as how well they ‘capture’ attention (that is, how long after stimulus onset does fixation move to these areas).
Without considering the context of the relationship judgment (i.e., short-term or long- term), the visibility of potential cues to mate quality (such as breasts, waists, and hips) drives men’s attention allocation to various regions of the body. For example, Lykins, Meana, and
Kambe (2006) demonstrated (using eye-tracking) that both men and women increase time looking at the body (as opposed to the face) of opposite-sex individuals when presented in an erotic scene (where the individuals are naked) rather than a non-erotic scene (where the actors are positioned similarly, however are clothed and devoid of erotic content; see also Lykins,
Meana, & Strauss, 2008). Additionally, Nummenmaa et al. (2012) showed that men will spend less time examining the face and more time examining the breasts and pelvic region of female images in neutral positions, when naked rather than clothed, thus demonstrating that the visual system is biased to automatically process biologically relevant information when visible.
Similarly, time spent looking at various regions of the body varies depending on physical characteristics of the individual stimulus, such as waist-to-hip ratio (Dixson et al., 2010; Garza et al., 2016).
Priming a participant for different contexts can also affect allocation of attention to regions of the body. For example, Bolmont, Cacioppo, and Cacioppo (2014) showed that when prompted to consider a sexual relationship (that is, decide whether the photographs elicit feelings
76 CHAPTER 3 of sexual desire), individuals are more likely to visually fixate on the body (rather than the face), than when prompted to consider a romantic relationship (that is, decide whether photographs elicit feelings of romantic love). While researcher manipulation of context can affect attention allocation, the pre-existing mate preferences of observers can also affect dwell time to particular regions of the body. Hall, Hogue, and Guo (2011) demonstrated that differential viewing patterns are apparent when males view preferred over non-preferred individuals. That is, 20 year-old female images (as opposed to, for example, 60 year-old female images), get relatively more dwell time to the upper body and waist hip regions than the lower body and face. Additionally,
Hall, Hogue, and Guo (2012) showed that men with increased sexual compulsivity pay relatively more attention to the waist-hip and breast regions of female stimuli than those low in sexual compulsivity. Both Confer et al. (2010) and the results presented in Chapter 2 demonstrate a positive correlation between men’s SOI-R scores and ratings of the importance of looking at the body (rather than the face) in short-term mating judgements. Given men’s self-perceived attractiveness can influence the effort they will put into a short-term sexual strategy, and how strict their desire for particular characteristics in a mate (Buss & Schmitt, 1993), one can reasonably hypothesise that attention allocation will vary depending on men’s sexual motivations, such as to what extent they are seeking a short-term versus long-term relationship.
3.2.1 Current Study
Previous studies have been informative for examining the effects of visibility of sexual cues (and more specifically erotic versus non-erotic scenes or clothed versus naked stimuli), and the characteristics of the individual being observed (e.g., weight and waist-to-hip ratio), on attention allocation processes of the observer (Dixson et al., 2010; Lykins et al., 2006; Lykins et al., 2008; Nummenmaa et al., 2012). However, no research to date has examined the effects that different clothing types, rather than clothing versus no clothing can have on attention allocation, particularly across contexts. It is reasonable to assume, given most people are able to make a
77 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES judgement about the attractiveness of a potential partner without the necessity to see them naked, that clothing scarcity/style will have an effect on attention allocation. Grammer, Renninger, and
Fischer (2004) demonstrated that women are aware of the social signalling value of their clothes, and clothing options can change depending on mating motivations, or even fertility status
(Haselton, Mortezaie, Pillsworth, Bleske-Rechek, & Frederick, 2007). It is important to investigate not only the ultimate evolutionary explanations for men’s increased attention to bodies, but also how modern context can vary individual mating strategies. Therefore, in the following study, I aimed to determine whether the context of the judgment (short-term or long- term) interacts with women’s clothing choice to affect men’s eye-tracking of women’s bodies, when female stimuli were wearing either ‘conservative’ or ‘party/revealing’ attire. Given the difference in men’s preference for face or body is dependent on the context of the judgement
(Chapter 2), I expected men to look less at the face of women in the short-term context compared to the long-term. Additionally, given men’s increased preference for looking at the body when naked rather than clothed, I hypothesised that men would increasingly dwell on the body in the party/revealing compared to the conservative clothing condition. Finally, if attention capture by visible areas of the body is dependent on the context of the judgement, we may expect the difference in gaze patterns between party and conservative clothing types to depend on whether the observer is making a short-term or long-term judgment. In order to explore individual variation in this attention allocation, I also collected a range of individual difference measures including self-reported short-term and long-term relationship desire, self-rated mate-value, and socio-sexuality.
3.3 Methods
3.3.1 Participants
Twenty-seven heterosexual male participants aged 18-35 years (M = 23.74, SD = 4.72) were recruited as a convenience sample via research awareness exercises as part of
78 CHAPTER 3 undergraduate Psychology courses at an Australian University, and via advertisements in local online bulletin boards. All participants had normal or corrected to normal vision, and I personally ran all eye-tracking sessions.
3.3.2 Stimuli
Twenty images of women were obtained from a variety of Internet sources such as fashion websites and stock image databases. Ten images were wearing ‘party/revealing’ clothes, chosen for one or more of the following characteristics: shoulders exposed, cleavage exposed, legs exposed from ankles to knees or higher. The remaining ten images were wearing
‘conservative’ clothes, chosen as they had shoulders and upper arms covered, legs covered, and cleavage covered (see Figure 3.1 for examples or Appendix C for the full set of images). Half of the each of the two ‘clothing’ sets were assigned to Stimulus Set 1 or Stimulus Set 2, resulting in five ‘party’ images, and five ‘conservative’ images in each set. Stimuli were standing in a range of poses, and could either be smiling or not smiling. No systematic differences were apparent between conditions for either body pose or facial expression, and pilot testing showed there was no significant difference in mean attractiveness ratings between the two image sets
[Stimulus Set 1 M = 6.41, SD = 1.40; Stimulus Set 2 M = 6.46, SD = 1.24; F1,13 = 0.15, ns].
Figure 3.1. Examples of stimuli from party/revealing (left) and conservative (right) conditions
79 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
While the stimulus sets on a range of characteristics (including model identity), the key differences between the conditions was the type of clothing worn, which included a difference in the proportion of skin exposed. All stimuli in the ‘conservative’ condition were wearing long pants, had their shoulders and cleavage covered, and their arms covered at least to the elbow. These stimuli were wearing mostly business or winter attire. The stimuli in the
‘party/revealing’ condition had a portion of their legs or arms exposed, or both, and were all wearing party dresses. These stimuli had a larger proportion of skin showing than the models in the conservative condition.
3.3.3 Apparatus
Eye-tracking was conducted using an Eyelink 1000 Tower mount head supported system
(SR research Ltd., Ontario, Canada). Eye position and eye movements were determined by measuring the corneal reflection and dark pupil with a video-based infrared camera and an infrared reflective camera (sampling rate 1000Hz). While viewing was binocular, recording was monocular, measuring right eye movements only. Calibration and validation of measurements occurred before each participant.
3.3.4 Procedure
Participants were instructed to complete a series of questionnaires including the SOI-R,
MVI-S, self-reported mating motivation (“to what extent are you currently seeking a short- term/long-term relationship?", 1 not at all to 9, extremely), and relationship status (”are you currently in a committed, romantic relationship, defined as three months or longer”, yes or no).
For the eye-tracking task, participants faced the monitor at an approximate distance of
57cm, maintained by a forehead and chin rest. All participants completed two blocks of trials in which each of which the ten images from Stimulus Set 1 or Stimulus Set 2 were presented in random order. Images remained on the screen for 5000ms and participants were not required to respond. In one block, participants were instructed to think about the images in terms of their
80 CHAPTER 3 suitability for a short-term affair, defined as a one-night stand, a brief relationship, or an affair within a current relationship. In the other block, participants were instructed to judge the images for long-term attractiveness, defined as a relationship that might result in moving in together, and/or entering into a relationship like marriage. Block order was counterbalanced between participants. Stimulus Sets were randomly assigned to either the first or second block and counterbalanced between participants.
3.3.5 Eye-Tracking Analysis
For each stimulus, regions-of-interest (ROI) were delineated, which included the head
(plus hair), the breast/chest region (base of neck down to the mid torso, including shoulders and upper arms), waist/hip region (mid torso down to base of the hips), and legs (from base of hips down, including feet). I also examined three fixation variables including proportion of total dwell time to each ROI, as well as the proportion of total separate fixations made to each ROI and the time taken from stimulus onset to first face fixation.
3.4 Results
Data were analysed using SPSS v21 for Mac. Statistics reported are two-tailed.
Greenhouse-Geisser corrections are reported where homogeneity assumptions are violated.
3.4.1 Contextual Effects on Eye-Tracking
A 2 x 2 x 4 ANOVA was conducted on men’s proportion of total dwell time and proportion of separate fixations across the four ROI with judgement context (short-term or long- term), and clothing type (revealing or conservative) as independent variables. A significant main
2 effect of ROI on total dwell time was revealed [F1.58,41.03 = 74.75, p < .001, ηρ = 0.74], with
55.3% of the dwell time to the face, which was significantly higher than the breasts (15.1%) [t24
= 9.57, p < .001], the waist/hip region (13.9%) [t24 = 9.41, p < .001] and the legs (12.4%) [t24 =
9.32, p < .001]. Additionally, a significant clothing type by ROI interaction emerged [F2.14,55.61
2 = 6.25, p = .003, ηρ = 0.19]. Simple effects contrasts showed that for revealing clothing less
81 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
time was spent dwelling on the face (revealing 52.9%, conservative 57.7%) [t26 = 3.00, p = .006] and more time on breasts (revealing 15.9%, conservative 14.2%) [t26 = 2.25, p = .032] and more time on the legs (revealing 13.9%, conservative 10.9%) [t26 = 3.33, p = .003], than for conservative images, which was in line with the hypothesis. This was qualified by a three-way
2 interaction between clothing type, ROI, and context of judgment [F2.11,54.81 = 4.64, p = .012, ηρ
= 0.15]. Simple contrasts showed this was because in the short-term condition, participants spent less time looking at the face [t26 = 3.36, p = .003], and more time at breasts [t26 = 2.71, p = .009] and more time at the legs [t26 = 3.85, p < .001], when looking at the revealing models versus the conservative, whereas in the long-term condition, no differences in dwell time were apparent between revealing or conservative clothing, for any body region. Importantly, no differences emerged between short-term and long-term conditions for proportion of dwell time to conservative clothing, while for revealing clothing, dwell proportion in the short-term condition was significantly lower to the head [t26 = 2.72, p = .012], and higher to the breasts [t26 = 2.11, p
= .049] and legs [t26 = 2.46, p = .019]. These details are shown in Figure 3.2.
Also in line with the hypothesis, similar results were found in a 2 x 2 x 4 ANOVA on the proportion of separate fixations to each region. That is, there was a main effect for ROI
2 [F1.64,42.64 = 34.67, p < .001, ηρ = 0.57], with 44.6% of individual fixations made to the face, which was significantly more than the breasts (19.6%) [t26 = 6.10, p < .001], the waist/hip region (16.4%) [t26 = 6.41, p < .001] and the legs (14.5%) [t26 = 6.84, p < .001]. There was also
2 a significant interaction between clothing and ROI [F2.21,57.5 = 5.72, p = .004, ηρ = 0.18] with revealing clothing having fewer fixations to the face (revealing 42.6%, conservative 46.6%)
[t26 =28.57, p = .011] and more to the legs (revealing 16.2%, conservative 12.8%) [t26 = 3.78, p
= .001], than for conservative images. Finally, a three-way interaction between clothing, ROI,
2 and condition approached significance [F3,78 = 2.67, p = .053, ηρ = 0.09], with fewer fixations to the face [t26 = 3.24, p = .003], and more to the legs [t26 = 4.15, p < .001], when looking at the
82 CHAPTER 3 revealing models compared to the conservative for the short-term condition, but no differences for the long-term condition.
A 2 x 2 ANOVA was also conducted on the total time from stimulus onset to first face fixation (M = 239.73ms, SD = 294.15) between short-term and long-term conditions and across clothing types. No main effects or interactions were observed [all p > .05].
Figure 3.2. Proportion of total dwell time to body region as a function of context (short-term or
long-term) and clothing choice.
3.4.2 Mating Motivations
In order to determine whether individual difference factors were related to the variation in attention allocation between conditions, I calculated the difference in proportion of time spent looking at the face between revealing and conservative clothing specifically for the short- term condition (given this is where differences emerged). Hence, higher scores mean more time looking at the face in the conservative compared to than the revealing condition. I then correlated this with the individual difference factors MVI-S, age, BMI, SOI-R and self-
83 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES reported short-term and long-term relationship seeking. The only correlation to emerge was between the difference score and self-reported short-term seeking [r27 = 0.40, p = .037]. This indicates participants who were seeking a short-term relationship showed a larger difference in dwell time to the head between revealing and conservative clothing in the short-term condition.
Secondly, without consideration for clothing type, I calculated the difference between dwell time to the head between short-term and long-term conditions, and correlated this with the same individual difference factors. Hence, higher scores meant a larger proportion of time looking at the face in the long-term compared to the short-term condition. The only significant correlation was between the difference score and the attitudes sub-scale of the SOI-R [r26 =
0.49, p = .009]. Hence, those higher in socio-sexuality showed a larger difference in head dwell time between short-term and long-term conditions. Given the number of correlations performed, however, and with sequential Bonferroni adjustments for multiple comparisons
(Peres-Neto, 1999), these correlations no longer remained significant. Repetition of this with a larger sample size should therefore be conducted.
3.5 Discussion
Previous research has shown that men’s attention to female faces and bodies is dependent on context (Bolmont et al., 2014), the characteristics of the stimuli (Dixson et al., 2010), and the preferences of the participants (Hall et al., 2012). Thus, in this study I aimed to demonstrate how these factors interact to affect attention allocation, in a task in which the stimuli were wearing different clothing amounts and styles (rather than being clothed or naked), and where I manipulated the context of the judgement (short-term or long-term). A three-way interaction between relationship context, clothing type, and ROI on proportion of both total dwell time and fixation number was observed. In the short-term condition, attention was devoted towards the breasts and legs more when women were wearing revealing clothing than when they were wearing conservative clothing, whereas for long-term judgements men’s attention to head and
84 CHAPTER 3 body regions was similar regardless of the attire of the stimuli. This was in line with the hypothesis and similar to previous research demonstrating that priming for a sexual relationship increases attention to the body compared to priming for a romantic relationship (Bolmont et al.,
2014). The findings also suggest that the effects of priming for context can be moderated by cues to sexual motivation evident in female clothing choice.
In both Confer et al. (2010) and the results reported in Chapter 2, men rated the importance of information from the body (rather than the face) as higher in short-term judgement contexts. Here, dwell time and proportion of fixations to the body made in a short-term condition only increased above that from the long-term condition when the female was wearing revealing/party clothing. As such, men’s increased ratings of the importance of information from the body and preference to look at the body in a binary choice task appears also to depend on clothing choice. In Chapter 2, men were asked to simply choose to look at the face or body of a concealed figure, in order to decide the suitability of the individual as a potential short-term or long-term partner. Given that bodily attractiveness is more important when judging for short- term rather than long-term relationships (Buss & Schmitt, 1993; Currie & Little, 2009) this suggests that information from the body might provide a cue to short-term mating orientation in women. As discussed in the introduction, Durante et al. (2008) demonstrated that women will illustrate (using pencil and paper) that they will wear more sexy and revealing clothing as they approach ovulation, which increases short-term relationship orientation (Gangestad, Garver-
Apgar, Simpson, & Cousins, 2007). Hence, men’s increased attention to women’s bodies in short-term conditions may be a mate selection mechanism. This does not necessarily mean that men need to spend a large proportion of time, however, making a judgement about a woman’s short-term relationship orientation. In the case of the conservative clothing, men’s attention may get directed back to the face, which is consistent with research showing that men are less likely to look at the body of a woman if she is clothed rather than naked (Lykins et al., 2006).
85 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Some limitations require consideration in this study. While the sample size was sufficient to detect a significant difference in men’s attention allocation between conditions, consistent with sample sizes in previous research (e.g., Dixson et al., 2010; Rupp & Wallen, 2007), the sample was not large enough to produce reliable correlations between attention allocation and individual difference variables such as socio-sexuality and self-rated mate value. These variables are likely to have an effect on eye-tracking measures given previous research (Hall et al., 2012), and thus are important to consider with a larger sample in future research. In addition, the stimuli used in this study might also limit the generalisability of these findings. Model identity, clothing colour, posture, and other factors varied between the stimuli. In order to confirm the findings presented here, future research should seek to control for a larger number of variables, including model identity and clothing colour. Further, to systematically examine whether clothing choice or skin exposure had a larger effect on attention allocation, future research could present participants with the same amount of skin exposed, but differing clothing, or the same clothing with differing amounts of skin exposed.
In summary, men’s attention allocation to the face or body of female figures not only depends on the context of the judgement (short-term or long-term), but also varies with female clothing choice. This has been demonstrated using a methodology that is in contrast to previous research, which has utilised images of women that are clothed versus naked (e.g., Nummenmaa et al., 2012). Instead, I investigated the effects of clothing choice on eye-tracking, which is an under-explored phenomenon, and more consistent with men’s interactions with women in the real world. While women’s clothing options may reveal something about their mating strategies, this is only of potential use to males when they are making judgements for a short-term relationship. These results are important as they demonstrate that women’s clothing choices do not automatically capture attention when they are revealing, nor are men necessarily ‘hard- wired’ to fixate on women’s cleavage or legs when they are visible. Instead, an interaction
86 CHAPTER 3 between judgement context and clothing choice can affect the amount of time men spend looking at female bodies.
87 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
3.6 References
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Buss, D. M., & Schmitt, D. P. (1993). Sexual strategies theory: an evolutionary perspective on
human mating. Psychological Review, 100(2), 204-232.
Confer, J. C., Perilloux, C., & Buss, D. M. (2010). More than just a pretty face: men's priority
shifts toward bodily attractiveness in short-term versus long-term mating contexts.
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Currie, T. E., & Little, A. C. (2009). The relative importance of the face and body in
judgments of human physical attractiveness. Evolution and Human Behavior, 30(6),
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Dixson, B. J., Grimshaw, G. M., Linklater, W. L., & Dixson, A. F. (2010). Watching the
Hourglass. Eye tracking reveals men's appreciation of the female form. Human Nature,
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Durante, K. M., Li, N. P., & Haselton, M. G. (2008). Changes in women's choice of dress
across the ovulatory cycle: naturalistic and laboratory task-based evidence. Personality
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Gangestad, S. W., Garver-Apgar, C. E., Simpson, J. A., & Cousins, A. J. (2007). Changes in
women's mate preferences across the ovulatory cycle. Journal of Personality and
Social Psychology, 92(1), 151-163. doi:10.1037/0022-3514.92.1.151
Garza, R., Heredia, R. R., & Cieslicka, A. B. (2016). Male and female perception of physical
attractiveness: An eye movement study. Evolutionary Psychology, 14(1).
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88 CHAPTER 3
Grammer, K., Renninger, L., & Fischer, B. (2004). Disco clothing, female sexual motivation,
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Hall, C., Hogue, T., & Guo, K. (2011). Differential gaze behavior towards sexually preferred
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Hall, C., Hogue, T., & Guo, K. (2012). Sexual cognition guides viewing strategies to human
figures. Journal of Sex Research, 51(2), 184-196. doi:10.1080/00224499.2012.716872
Haselton, M. G., Mortezaie, M., Pillsworth, E. G., Bleske-Rechek, A., & Frederick, D. A.
(2007). Ovulatory shifts in human female ornamentation: near ovulation, women dress
to impress. Hormones and Behavior, 51(1), 40-45. doi:10.1016/j.yhbeh.2006.07.007
Jing Lu, H., & Chang, L. (2012). Automatic attention towards face or body as a function of
mating motivation. Evolutionary Psychology, 10(1), 120-135.
Lykins, A. D., Meana, M., & Kambe, G. (2006). Detection of differential viewing patterns to
erotic and non-erotic stimuli using eye-tracking methodology. Archives of Sexual
Behavior, 35(5), 569-575. doi:10.1007/s10508-006-9065-z
Lykins, A. D., Meana, M., & Strauss, G. P. (2008). Sex differences in visual attention to erotic
and non-erotic stimuli. Archives of Sexual Behavior, 37(2), 219-228.
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Nummenmaa, L., Hietanen, J. K., Santtila, P., & Hyona, J. (2012). Gender and visibility of
sexual cues influence eye movements while viewing faces and bodies. Archives of
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Rupp, H. A., & Wallen, K. (2007). Sex differences in viewing sexual stimuli: an eye-tracking
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90 CHAPTER 4
Chapter 4: Women’s Dress Choice Across the Menstrual Cycle
4.1 Chapter Overview
Thus far, I have demonstrated that men and women allocate attention differently when judging whether someone would make a suitable short-term or long-term partner, and this allocation is a reflection of the broad sex-differences in mating strategies, as well as the location of important cues to mate quality. In addition, we saw that women are more accurate in judging the attention allocation of men (than men are of judging women’s attention allocation), and this is likely a reflection of sex-differences in intra-sexual competitiveness tactics. Finally, we saw that men’s attention allocation to women’s bodies is dependent on a complex interplay between judgement context, the potential signalling value of women’s clothing, and men’s mating motivations. In this chapter, I shift away from considering how individuals allocate attention to perceive cues to mate quality, and towards an understanding of variation in these signals as a result of menstrual cycle shifts. Given men’s particular interest in the body for short-term relationship judgements (Chapter 3), and the increase in the importance of information from the body when men rate themselves as higher in mate-value (Chapter 2), in this chapter I examined changes in dress choice as a potential mating signal.
4.2 Introduction
Whilst the cues that assist women in judging whether a man would make a suitable partner are relatively redundant between men’s body, face, voice, and scent (Feinberg,
DeBruine, Jones, & Little, 2008; Fink, Täschner, Neave, Hugill, & Dane, 2010; Shoup & Gallup,
2008), the face and body of women can offer differentially important information, depending on whether a man is making a short-term or a long-term judgement. This has been demonstrated in a number of previous studies, with Confer, Perilloux, and Buss (2010) showing that when prompted for a short-term relationship, men increase their preference for looking at the body,
91 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES rather than the face, of women, compared to a long-term relationship (also see Chapter 2; Currie
& Little, 2009; Jing Lu & Chang, 2012). On the other hand, women have a preference for looking at the face in both short-term and long-term conditions. This finding has also been replicated in
Chapter 2, and similar findings have been shown by Jing Lu and Chang (2012) using a dot-probe task. In addition, we saw in Chapter 3 that men’s dwell time to body areas increased for a short- term judgement for party/revealing clothing.
When considering what information might be accessible by looking at a woman’s body, there is evidence that women’s clothing choices vary across the menstrual cycle, and hence clothing options may provide a cue to ovulatory status. Durante, Li, and Haselton (2008) demonstrated that when asked to draw what they would wear for a ‘social event’, women illustrate on paper they will wear more ‘revealing’ and ‘sexy’ clothes in the fertile phase of the menstrual cycle than the non-fertile phase. Similarly, Saad and Stenstrom (2012) asked women to self-report for a 35-day period their clothing-related behaviour, and found that women self- report greater use of ‘wearing sexy clothes’, ‘wearing clothes that showed a lot of skin’, and
‘wearing clothes that attract attention’ when fertile than not. Consistent with this, women are rated by independent observers as wearing more revealing and sexy clothes when in the fertile phase of the menstrual cycle compared to the non-fertile. That is, Haselton, Mortezaie,
Pillsworth, Bleske-Rechek, and Frederick (2007) showed 42 independent observers images of women who had been photographed once during the fertile phase of the menstrual cycle and once during the non-fertile phase. When presented side-by-side, the photograph in which the woman was in the fertile phase of the menstrual cycle was chosen more frequently as putting more effort into her appearance. This was also affected by proximity to ovulation, with increased chances of the fertile photo being chosen when this photograph was taken closer to the day of ovulation. Thus, women’s dress choice may tell us something about their underlying mating mindset as a function of cyclical fertility, and could be a potential cue to ovulation.
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Similarly, women’s self-reported mating motivations can influence their dress choice. In a seminal study by Grammer, Renninger, and Fischer (2004), when making naturalistic observations in a nightclub, clothing sheerness correlated with self-reported motivation to seek a short-term partner. Skin exposure also correlated positively with estradiol concentration, for women who were in a relationship but attending the club alone. Grammer et al. (2004) argued that females are aware of the social signal of their choice of clothing, which also aligns with theoretical arguments that women will compete with other women for access to men by putting effort into their appearance (Buss, 1988). These findings suggest that men’s increased interest in looking at the body of a woman (particularly when making a short-term attractiveness judgement) is likely a strategy that assists in judging rapidly the ovulatory status and/or mating motivations of the individual in question and similarly, that women’s choice of dress is used to manipulate perceptions of their mating intention by others.
While Durante et al. (2008) and Saad and Stenstrom (2012) reported within-subject increases in self-reported use of revealing clothing across the menstrual cycle, and Haselton et al. (2007) showed increased ratings of attractiveness from independent observers, these studies did not explore objective variation in skin-exposure as women move from the fertile to the non- fertile phase of the menstrual cycle. That is, the studies have examined either women’s reported use of revealing clothing or independent observer’s judgements about the revealingness of clothing, rather than measuring the actual proportion of skin exposed on that day. Similarly, while Grammer et al. (2004) showed that a larger proportion of skin exposure correlated with circulating hormone levels, this study was cross-sectional, and thus did not capture within- individual changes in objective skin exposure. In addition, Grammer et al. performed their study in the specific environment of a night-club. I propose that women are more likely to make clothing choices in which they are likely to put more conscious effort into their appearance when attending a night club (which may interact with their mating motivations), and that this does not
93 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES necessarily reflect everyday change in dress choice across the menstrual cycle, which could reflect more subtle, less conscious, wardrobe decisions.
In this study, I sought to measure objective change in skin-exposure in everyday dress
(clothing options for a day of attendance at University), between fertile and the non-fertile phases of the menstrual cycle, in a cohort of young Australian women. In addition, I aimed to examine how everyday dress choices were related to self-reported mating motivations; including desire for a short-term or long-term relationship, socio-sexual orientation, and self-reported mate value; variables which tell us a great deal about individual differences in mating behaviour, and which have not been thoroughly explored with regards to their relationship to clothing choices. I achieved this by asking women who were not using hormonal contraceptives to come in to the lab on two occasions: once during the follicular phase, and once during the luteal phase of the menstrual cycle. Full body photographs were taken in a naturalistic setting, since the participants wore clothing that they had chosen for a day of attendance at University. In this way, I could determine whether the objective variation in skin exposure, as demonstrated by Grammer et al.
(2004) in a nightclub, translate into everyday clothing choices. On both occasions, I asked participants to provide a saliva sample and to fill out the SOI-R, the MVI-S, and self-reported mate-seeking behaviour. I later had these images rated for attractiveness and perceived effort put into appearance by independent observers, and measured the proportion of skin exposed in each image using Photoshop, in an effort to examine the relationship between objective changes in skin exposure (and the underlying mating motivations of the individual) and others’ perception of effort and attractiveness. If Grammer et al.’s observations in a night club do, in fact, translate into everyday settings, and Haselton et al.’s findings of increased perceived effort are due to increases in objectively measured skin exposure, then I expected women’s skin exposure to be higher during the fertile than the non-fertile phase, for independent observers to rate the fertile
(compared to the non-fertile) photographs as both more attractive and putting more effort into their appearance, and for these changes to correlate positively with estradiol change.
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4.3 Method
4.3.1 Participants
Participants were originally 36 naturally cycling (i.e., not using hormonal contraceptives) heterosexual women (M age = 25.53, SD = 5.51, range = 19-36) from an Australian University and the surrounding community. Participants were awarded with course credit or a $40 voucher.
They were initially contacted via recruitment materials located at the University and in local online bulletin boards, and as best as possible were scheduled for their two sessions after reporting the onset of their last menstrual period, the expected date of their next menstrual period, plus their typical cycle-length. For any fertility analyses, phases were determined based on the backwards-counting method (based on actuarial data from Wilcox, Dunson, Weinberg,
Trussell, & Baird, 2001), where the day of ovulation was calculated as 14 days prior to the onset of menstruation. The fertile phase was calculated as the period 5 days prior to the day of ovulation, and the luteal phase as the period 11 days prior to the onset of the next menstrual period. Ten participants attended their sessions outside of the required window and so were excluded from within-individual analysis.
4.3.2 Materials
Saliva samples were taken for both lab sessions. Saliva samples were collected via the passive drool technique. Participants were instructed to not eat, drink, or smoke for a period of at least two hours prior to attending their sessions. All sessions were scheduled in the morning
(between 8am and 11am, within 3 hours of waking) to control for diurnal rhythms. Both sessions were scheduled at the same time.
Photographs were taken using a Fujifilm FinePix 3D camera, placed approximately 1.5m from the participant. Photographs were taken in the same conditions with the participant standing, instructed to let arms fall by sides, and to maintain a relaxed posture (as shown in
Figure 4.1). Participants were told these photographs were being taken to determine to what
95 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES extent body posture changed between the two sessions, and were not told of the true purpose until both sessions were completed.
4.3.3 Procedures
On both occasions, participants were instructed on the passive drool technique for collection of the saliva sample. While this was being completed they filled in a series of questionnaires including the SOI-R, the MVI-S, and self-reported mating motivation (“to what extent are you currently seeking a short-term/long-term relationship?”), before finally posing for the photographs. Participants completed the same tasks on both occasions. Session order (fertile or non-fertile session first) was counterbalanced between participants.
4.3.4 Skin Exposure and Clothing Analysis
Body photographs were imported into Adobe Photoshop, and cropped so both images were visible from the same location on the neck down (as per Figure 4.1). The entire figure was selected and surface area was calculated. I then selected each area of exposed skin, and calculated exposed skin as a proportion of the surface area of the whole figure. In order to determine whether skin exposure varied between different body regions, I chose to examine three regions- of-interest, the arms, décolletage (collarbone and cleavage areas), and legs.
4.3.5 Independent Ratings of Full-Body Images
Independent raters were 37 male (M age = 31.62, SD = 11.16) and 80 female (M age =
23.92, SD = 8.51) students and interested volunteers who were recruited as a convenience sample via an online survey engine. Stimuli consisted of the fertile and non-fertile images of each woman’s body presented side-by-side (side of fertile image presentation counter-balanced), cropped so the face was not visible, and participants were asked to choose in which photograph the individual was trying to look more attractive. Raters were then presented with each of these images individually, and asked to make a rating of their attractiveness, on a scale of 1 (not at all attractive) to 9 (very attractive). Stimulus order was randomized between participants.
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Figure 4.1. Examples of body photographs of a participant, in the follicular (left) and luteal
(right) phase of the menstrual cycle
4.3.6 Hormone Analysis
Saliva samples were assayed for concentrations of estradiol and progesterone. Estradiol concentrations were run in duplicate using high-sensitivity human saliva 17β-estradiol ELISA
(Abnova Corporation, Taipei, Taiwan). Concentrations of progesterone were run in duplicate using Progesterone ELISA kits (Enzo Lifesciences, Farmingdale, NY). Intra-assay CV’s were maintained below 10%.
97 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
4.4 Results
Data were analysed using SPSS v21 for Mac. Statistics reported are two-tailed.
4.4.1 Within-Cycle Change in Hormone Levels
While I collected samples to measure three hormones: estradiol, progesterone and testosterone, uncontrollable circumstances (see Chapter 8) meant that a large number of samples were destroyed inadvertently before testosterone analysis could be completed. As such, testosterone measures were completed, thus only estradiol and progesterone results are reported.
There was no significant difference in estradiol levels between fertile (M = 5.50pg/mL, SD
= 1.90) and non-fertile (M = 5.20pg/mL, SD = 1.65) sessions [t21 = 0.92, p = .371], though progesterone levels were significantly higher in the non-fertile (M = 162.04pg/mL, SD = 83.38) than the fertile (M = 115.66pg/mL, SD = 45.72) phase [t23 = 2.59, p = .016], which was in the expected direction. I also calculated an estradiol-to-progesterone ratio. The ratio was significantly higher for the fertile (M = 0.05, SD = 0.02) than in the non-fertile period (M = 0.04,
SD = 0.02) [t21 = 2.13, p = .046] which is predicted if the fertile sessions are in a higher conception risk phase (e.g., Eisenbruch, Simmons, & Roney, 2015).
4.4.2 Within-Cycle Change in Skin Exposure
A 3 x 2 repeated-measures ANOVA was conducted on the proportion of total skin exposure, with the region of interest (décolletage, arms, legs) as one factor, and the fertility session (fertile or non-fertile) as the other. The interaction between region and fertility session
2 approached significance [F2,50 = 2.87, p = .066, ηρ = 0.10], with paired comparisons demonstrating this was due to increased rates of skin exposure on the arms in the fertile session compared to the non-fertile session [t25 = 2.43, p = .023], but no difference in exposure of the legs [t25 = 1.71, p = .100] or décolletage [t25 = 0.55, p = .586], as shown in Figure 4.2. There
2 was also a significant main effect of fertility [F1,25 = 8.10, p = .009, ηρ = 0.25], with larger proportion of skin exposure in the fertile (M = 6.36, SD = 1.25) compared to the non-fertile (M
98 CHAPTER 4
2 = 3.99, SD = 2.77) period. There was also a main effect of region [F2,50 = 7.45, p = .001, ηρ =
0.23], with larger areas of skin exposure on the arms compared to the decollotage [t25 = 3.99, p
= .002] and the legs [t25 = 2.68, p = .038]. In order to control for external temperature
fluctuations, I took a reading of the ambient air temperature when the participants came in to
the lab. There was no significant difference in ambient air-temperature between fertile and
non-fertile sessions [t25 = 0.13, p = .896].
14 *p = .023 fertile 12 non-fertile 10
8 p = .100 p = .586 6
4
Percentage of total skin exposure 2
0 decolletage arms legs Region Figure 4.2. Percentage of skin exposure of décolletage, arms, and legs, as a function of fertility
I calculated difference scores for skin exposure, progesterone, and estradiol, between
fertile and non-fertile sessions (such that positive values indicated higher values in the fertile
period and negative values indicated higher levels in the non-fertile period). I then correlated
these difference scores. The only significant difference to emerge was for estradiol difference
and skin exposure difference [r22 = 0.43, p = .046]. Thus, change in skin exposure between the
two sessions appears to be related to change in estradiol level between the two sessions. Given
the small sample size, however, this correlation should be interpreted with caution.
99 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
4.4.3 Independent Ratings Analysis
Based on the independent ratings, I calculated average body attractiveness scores for each individual female for each session. No significant differences between fertile and non-fertile attractiveness scores emerged for a within-subjects analysis, which is unsurprising given the small sample size. There were also no significant correlations between individual hormone concentrations and bodily attractiveness scores, nor between any self-rated mate value measures and body attractiveness.
In addition to the body attractiveness ratings, I also calculated the proportion of times each individual’s fertile photograph was chosen as the one in which the model put more effort into their appearance. As per Haselton et al. (2007), I performed an ANOVA with the stimuli as the unit of analysis. Thus, if each individual’s fertile photograph was chosen by 100% of the raters, they received a score of 1, and if their non-fertile photograph was chosen by 100% of the raters, their score was 0. At a stimulus level, these scores did not differ from chance (0.5) for either female raters or male raters. However, higher estradiol scores in the fertile session relative to the non-fertile session were correlated with a higher proportion of choice of the fertile photo for both male raters [r21 = -0.43, p = .049] and female raters [r21 = 0.51, p = .018], in line with the hypothesis. However, no correlation emerged between skin exposure difference scores and proportion of choice of the fertile photo as putting in more effort.
When treating the raters as the units of analysis (therefore examining rater preferences), I performed one-sample t-tests on the proportion of each rater’s choice of fertile photo as the one in which the individual was putting more effort into their appearance, and did so separately for male and female raters. Female raters chose fertile photographs significantly more frequently than chance [t79 = 2.92, p = .005]; although male raters did not [t36 = 0.03, p = .979], however, the difference between male and female proportion of choice did not reach significance in an independent samples t-test (p > .05). Overall, no significant difference in attractiveness ratings between fertile and non-fertile photographs were observed, for either female or male raters.
100 CHAPTER 4
4.4.5 Mating Behaviour Scores Between Individuals
When considering both fertile and non-fertile phase scores, several correlations emerged between the various self-rated mate value measures, and hormonal concentrations. Short-term mate seeking behaviour when fertile correlated with the attitudes subscale of the SOI-R [r26 =
0.40, p = .044], whereas short-term mate seeking behaviour when non-fertile correlated with the desire subscale of the SOI-R [r27 = 0.41, p = .033]. The attitudes subscale of the SOI-R correlated negatively with estradiol concentrations when non-fertile [r22 = -0.50, p = .019], though not when fertile. When considering only the participant’s first sessions, regardless of fertility, a positive correlation emerged between estradiol and MVI-S [r33 = 0.38, p = .029] and a negative correlation between estradiol and socio-sexual desire [r33 = -0.39, p = .026]. There was also a positive correlation between progesterone and MVI-S [r33 = 0.38, p = .030]. Given the number of correlations performed, however, and with sequential Bonferroni adjustments for multiple comparisons (Peres-Neto, 1999), these correlations no longer remained significant. Repetition of this with a larger sample size should be conducted.
4.5 Discussion
The purpose of this study was to examine objective changes in skin exposure in everyday clothing choices between fertile and non-fertile phases of the menstrual cycle, as measured in a cohort of young Australian women. I used the backwards counting method (based on Wilcox et al., 2001) to recruit women in the fertile and non-fertile phases of the menstrual cycle, and while estradiol levels did not change significantly between the two sessions, progesterone levels were significantly higher in the non-fertile phase. In light of this, my restrictions for including individuals in the within-individuals analysis was strict, resulting in only 26 participants (out of a possible 36) included. In addition, as per Eisenbruch et al. (2015), I calculated an estradiol-to- progesterone ratio. This ratio was significantly higher in the fertile than the non-fertile period, thus indicating that conception risk was higher when we categorized women as fertile. While I
101 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES was able to measure estradiol and progesterone in this study, I was unable to obtain testosterone levels for these participants owing to the loss of material. This should be noted as a limitation of the conclusions of this study, particularly since testosterone can have important effects on mating related behaviour in females (e.g., see Welling et al., 2007). In addition, the small sample size here means that any generalisation of these findings must be considered with care. Gangestad et al. (2016) recommend that for a within-subjects menstrual cycle study, a minimum of 71 participants is required to overcome the noise associated with anovulatory cycles (in which no ovulation occurs). Since this useful guide was not published until 2016, and with considerations of recruitment costs, the minimum sample size considered sufficient for this study was based on research that detected a within-cycle effect with as little as 30 participants (Haselton et al., 2007;
Rosen & López, 2009). Thus, in light of these recommendations, I consider these findings to be a preliminary examination of variation in skin exposure across the menstrual cycle, and further research should be conducted before firm conclusions can be drawn.
In accordance with the hypothesis, I observed an increased proportion of skin exposure in the fertile relative to the non-fertile phase, with increased skin exposure specifically on the arms, although no significant changes between the two sessions for décolletage or legs. In addition, this change in skin exposure was correlated with change in estradiol between the two sessions, such that higher estradiol levels in the fertile relative to the non-fertile session was associated with increased skin exposure in the fertile relative to the non-fertile session. I can be confident the observed changes in skin exposure are unrelated to external temperature, given no mean difference in ambient air temperature between sessions. These changes are also unlikely to be related to internal temperature at the time of ovulation, given the fertile session was scheduled as the 5 days preceding ovulation (using the counting method), and internal temperature peaks on the day of ovulation and falls away during the start of the luteal cycle (e.g.,
Refinetti & Menaker, 1992). Hence, estradiol possibly mediates the relationship between fertility and skin exposure. The hormone measures showed some expected correlations with self-rated
102 CHAPTER 4 measures, such as higher estradiol and progesterone correlating with higher MVI-S between subjects. Only non-fertile phase estradiol levels correlated negatively with the attitudes sub-scale of the SOI-R. However, the number of correlations performed and sequential adjustments to the critical p-values mean these correlations should be interpreted with caution, and future research should seek to increase sample size, and confirm ovulation (Gangestad et al., 2016).
Importantly, a large number of saliva samples were unable to be assayed for this study, owing to uncontrollable circumstances and subsequent loss of material. Thus, I was unable to complete planned analyses of female testosterone levels. Since testosterone can have an important effect on female mating behaviour (Welling et al., 2007), the change in skin exposure between fertile and non-fertile sessions may also have been mediated by testosterone, particularly as testosterone levels peak around ovulation. For example, Grammer et al. (2004) demonstrated that testosterone levels were associated with clothing sheerness for naturally cycling women attending a discotheque without their primary partner. However, given I was unable to examine testosterone levels future research should consider the relationship between testosterone and skin exposure variation across the menstrual cycle.
Based on previous findings (Haselton et al., 2007), I expected that the fertile photographs would be considered more attractive, and that on both a stimulus level and a rater level, the models would be perceived to be putting more effort into their appearance. Thus, as per Haselton et al (2007), I performed an analysis of perceived effort put into appearance, with the individual stimuli as the units of analysis. In this way, I was able to examine which factors were affecting women’s skin exposure, rather than which factors effect raters’ preferences. However, I found no difference in attractiveness ratings between the fertile- and non-fertile photos, and no preference above chance for the perceived effort put into appearance. This lack of an effect is possibly due to noise associated with anovulatory cycles in a small sample. While a larger sample size may overcome this, Haselton et al. detected a significant difference with only 30 female participants, and 42 independent judges. In light of this, however, I still observed a significant
103 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES correlation between proportion of choice of the fertile photograph as putting more effort into appearance, and higher estradiol levels in the fertile relative to the non-fertile phase of the menstrual cycle. Thus, perceptions of increased effort in appearance could be mediated by change in estradiol level across the menstrual cycle, given estradiol change correlated with change in skin exposure, and Grammer et al.’s (2004) findings that estradiol was correlated with clothing revealingness. When considering the preferences of the raters, and thus considering the raters as units of analysis, I showed that female raters chose the fertile photo as the one in which the model was making more of an effort with her appearance. However, this choice was unrelated to rates of skin exposure on the models, and did not differ significantly from male rater proportion of choice. Thus, in this sample, estradiol (but not progesterone) was related to perceived effort put into appearance, as well as skin exposure across the menstrual cycle, but not subjective attractiveness; and skin exposure did not correlate with effort put into appearance and did not correlate with any hormone measures. These results suggest that estradiol mediates variation in clothing choice across the menstrual cycle, which is in line with previous research
(Grammer et al., 2004), although the relationship with hormone levels is still inconclusive, particularly owing to the inability to measure testosterone levels and the small sample size.
Hence, future research should seek to confirm these findings.
In this study, only females demonstrated a significant preference for the fertile photo when choosing the photo in which the models put more effort into their appearance. In Chapter
2, female participants were able to more accurately ‘imagine’ what a male would choose when asked to pick either the face or body, by demonstrating a similar (albeit over-estimated) pattern of rating the body as more important for short-term relationship decisions compared to long- term relationship decisions. On the other hand, male participants were not able to ‘imagine’ what a female participant would do, as their ratings of what they perceived a woman would find important did not differ from their own. Given only females chose the fertile photos as putting additional effort into their appearance this study, it is possible that women are better able to
104 CHAPTER 4 detect variation in appearance across the ovulatory cycle in other women, and thus change in appearance may serve as an intra-sexual competitiveness signal. It is unclear whether this appearance change has any role to play in male sexual choice, given that in our sample, males showed no preference for fertile or non-fertile photos when judging effort put into appearance, nor when making attractiveness ratings. While Durante et al. (2008) reported no information about sex-differences between judges in their ratings of illustrations, these findings contrast with
Haselton et al. (2007), who found that both male and female raters more frequently chose the fertile photo as the one in which the individual was putting more effort into their appearance.
However, since I did not observe a significant difference between male and female proportion of choice, this lack of an effect for male raters needs to be considered with care.
The difference (albeit not reaching significance) between female and male rater preference could be due to the relatively more subtle clothing choices that are reflective of a day of attendance at University, rather than the more effortful clothing choices made for a ‘night out’. While change in skin exposure was observed in this sample between fertile and non-fertile phases of the menstrual cycle, this did not affect attractiveness ratings, as was expected based on previous research. Thus, women’s use of clothing as a mate attraction tactic, to the extent that it is detectable by men, may not occur when not prompted to do so by the context (such as in a discotheque; Grammer et al., 2004).
Although in this study female raters judged other women as putting more effort into their appearance when in the fertile phase, this was also unrelated to skin exposure. This raises the additional question of which signal might be driving these effort judgements. Evidence suggests there are increases in women’s use of red clothing when fertile than when not, with some arguing this increase in red clothing use is a proxy for the use of red sexual swellings in other primate species when aiming to attract a male (see Prokop, Hromada, & Herberstein, 2013). However, findings are mixed. More recently, research suggests that there is an increase in red only when ovulation is measured in a specific manner (as with any other menstrual cycle change). That is,
105 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Eisenbruch et al. (2015) demonstrated that the estradiol to progesterone ratio mediated the within-cycle odds of wearing red or pink, rather than the main effect of either hormone. It is worth noting that in this sample only two individuals wore red on any one of the days, thus rendering any analysis of the use of red clothing impossible. Instead, other aspects of the participants’ clothing choices or potentially even changes in skin tone may be influencing female judgements of effort. For example, in Haselton et al. (2007), independent judges rated high fertility photos as ‘more fashionable’ and ‘nicer’, although not as ‘wearing more accessories’.
These changes in clothing options were difficult to quantify in this sample. For example, only four participants wore a scarf in one session but not in the other, but two of these were in the fertile session, and two were in the non-fertile session. There was also a large variation in colour of clothing choices between sessions. It would be interesting to investigate variation across the menstrual cycle in clothing in terms of accessorising, colour choices, sheerness, for example, in a within-subjects design with a larger number of participants, as per Gangestad et al.’s (2016) recommendations. Both proportion of choice of the fertile photo and change in clothing exposure were related to estradiol level, if not to one another.
Overall, the results of this study illuminate several important points. Firstly, that women do objectively increase their use of revealing clothing across the menstrual cycle, at least when measuring proportion of skin exposure on 2D photographs, when dressing for an everyday setting (at least in this sample); but, that this does not relate to self-reported mating motivation, nor does it necessarily increase subjective ratings of attractiveness from independent observers.
Moreover, subjective judgements of perceived effort put into appearance appear to relate to changes in estradiol levels, and change in skin exposure relates to estradiol level. These findings complement previous literature on intra-sexual competitiveness amongst women, with change in appearance as a competitive signal. However, the use of revealing clothing as a sexual attraction tactic appears to be less clear, given no change in men’s subjective attractiveness ratings, although the generalisation of these findings to other samples needs to be considered
106 CHAPTER 4 with care. In addition, women’s use of appearance-related tactics across the menstrual cycle might not always increase in the fertile phase, with recent evidence suggesting women’s acceptance of cosmetic surgery is lower in the fertile compared to the non-fertile phase of the menstrual cycle (Nicolas & Welling, 2016). Based on the findings presented in this chapter, estradiol could mediate the use of revealing clothing in an everyday setting as a function of menstrual cycle phase. Further research into women’s use of appearance as a mate attraction or competitive tactic is clearly warranted.
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Shoup, M. L., & Gallup, G. G. (2008). Men's faces convey information about their bodies and
their behavior: what you see is what you get. Evolutionary Psychology, 6(3), 469-479.
Welling, L. L., Jones, B. C., DeBruine, L. M., Conway, C. A., Law Smith, M. J., Little, A. C., .
. . Al-Dujaili, E. A. (2007). Raised salivary testosterone in women is associated with
increased attraction to masculine faces. Hormones and Behavior, 52(2), 156-161.
doi:10.1016/j.yhbeh.2007.01.010
Wilcox, A. J., Dunson, D. B., Weinberg, C. R., Trussell, J., & Baird, D. D. (2001). Likelihood
of conception with a single act of intercourse: providing benchmark rates for
assessment of post-coital contraceptives. Contraception, 63(4), 211-215.
110 CHAPTER 5
Chapter 5: Women’s Perfume Use as a Potential Cue to Mating Motivation
5.1 Chapter overview
Whilst variation in women’s physical appearance and behaviour may signal women’s sexual interest, underlying mate value, or desire to engage in a short-term relationship, one of the earliest cycle-based effects reported in the mating literature was that of change in women’s scent across the menstrual cycle. This, coupled with the fact that perfumes have had a long history of use and supposed effects on sexual behaviour, leads to the question of whether perfume use has some role in signalling mate quality, and therefore whether it varies across the menstrual cycle like other signals do, and/or shows individual variaiton. Thus, the purpose of this chapter was to explore variation in perfume use amongst women and to determine which mating related factors might vary the frequency of perfume use.
5.2 Introduction
The long-held notion that human ovulation is ‘concealed’ has been increasingly challenged, as overwhelming evidence demonstrates that variation in a variety of physical and behavioural domains around the time of ovulation can be subtly detected by conspecifics
(although not necessarily consciously). For example, as discussed in Chapter 1, a host of studies have shown cyclical changes in dress (Durante, Li, & Haselton, 2008), receptivity to courtship
(Guéguen, 2009), gait (Guéguen, 2012), and cognitions about one’s own attractiveness (Haselton
& Gangestad, 2006), with varying strengths of effects. Some of the pioneering studies demonstrating cyclical changes in attractiveness examined changes in scent, showing that women’s scent varies across the luteal and follicular phases of the menstrual cycle. Singh and
Bronstad (2001) asked men to smell cotton t-shirts that had been worn by women at varying stages of the menstrual cycle. The t-shirts worn during the fertile phase were rated as more
111 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES attractive and more pleasant than those worn during the luteal phase. In a similar experiment,
Gildersleeve, Haselton, Larson, and Pillsworth (2012) asked women to wear gauze pads under their arms for a period of 24 hours. In this experiment, luteinising hormone surge was confirmed using hormonal tests. The odour of women in the fertile phase of the menstrual cycle was rated as more attractive than the same woman’s odour in the luteal phase. When the odour in the two phases was more easily distinguished, the attractiveness ratings of the fertile phase were even stronger relative to the non-fertile phase.
As discussed in Chapter 1, the concept that these within-cycle shifts have been evolutionarily selected for, and therefore function to signal fertility within the menstrual cycle, is still being debated (Havliček, Cobey, Barrett, Klapilová, & Roberts, 2015). In addition, not all researchers have found a clear link between odour attractiveness and mate quality between individuals. For example, Thornhill and Gangestad (1999) found no correlation between women’s facial attractiveness ratings or their fluctuating asymmetry, and their odour ratings by men. However, Rikowski and Grammer (1999) did find that body odour sexiness was correlated with attractiveness ratings of women’s faces, as well as with asymmetry of non-directional traits.
Debates as to the ultimate function of these within-cycle shifts does not undermine the possibility that they still provide useful information in a proximate context. In addition, it is still possible, regardless of the underlying variation in women’s natural scent, that their motivation to use artificial scent varies either across the menstrual cycle as women’s sexual behaviour varies, and/or between individuals depending on their underlying mating motivation.
Perfume has been in use for over 5000 years in human history (see discussion in Milinski
& Wedekind, 2001) and research has demonstrated that perfumes can increase sexual arousal
(Graham, Janssen, & Sanders, 2000), perhaps even more so than natural body odours (Herz &
Cahill, 1997). Indeed, celebrity endorsements of perfume are a lucrative business. While women may enhance their appeal through changes in make-up and dress, the potential to enhance olfactory cues of health (and potentially ovulation, if body odour does reliably signal fertility
112 CHAPTER 5 status) is an under-explored area of literature. The major histocompatibility complex (MHC) is a set of genes that play an important role in immune function, with individuals preferring the scent of those with an MHC genome complementary to their own (Wedekind, Seebeck, Bettens,
& Paepke, 1995). Preferences for particular perfumes are correlated with the structure of the
MHC-genome (Milinski & Wedekind, 2001), such that they are selected ‘for self’. Thus, perfumes potentially serve as advertisements of one’s own scent. Lenochova et al. (2012) demonstrated that perfumes mix with body odour, creating a unique odour combination.
Mixtures of body odour with perfume of the participant’s choice were rated as more pleasant than the same body odour combined with an equally pleasant (when independently rated) but randomly assigned perfume. In addition, perfume selection may serve the function of masking the effects of illness and/or disease, since body odour could signal variation in underlying health.
For example, Havlicek and Lenochova (2006) found that meat consumption lowers the body odour attractiveness of males. Thus, diet can have a large effect on body odour (for a discussion, see Havlicek & Saxton, 2009), potentially having a more salient effect than MHC type
(Schellink, Slotnick, & Brown, 1997). Perfume use may therefore have some role to play in enhancing one’s attractiveness to others in a mating relevant context.
Perfume use has the capacity to change behaviour and thought patterns. Japanese women who were given a perfume were perceived by others to relax, and self-reported feeling more dominant (Higuchi, Shoji, Taguchi, & Hatayama, 2005). Men who put on deodorant containing active compounds, such as antimicrobial agents and perfume, displayed an increase in self- esteem within 15 minutes, whereas men who put on deodorant lacking active compounds, who did not report an increase in self-esteem (Roberts et al., 2009). Subliminal smells can also influence social judgments. Li, Moallem, Paller, and Gottfried (2007) found that presenting participants with pleasant versus unpleasant odours led them to alter their likeability ratings of neutral faces. However, this effect diminished as the scents came into conscious awareness.
Given that smells have the ability to alter behaviour and cognitions in both the wearer and the
113 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES observer, and that the choice of scents depends on one’s own underlying MHC-complex, there is likely to be some functional value to their use, particularly since the use of scents has a long tradition in human history. That is, if women demonstrate attempts to enhance visual appeal through variation in dress (Haselton, Mortezaie, Pillsworth, Bleske-Rechek, & Frederick, 2007) and behavioural cues, such as gait (Guéguen, 2012) and behavioural engagement (Flowe,
Swords, & Rockey, 2012), it may also follow that women seek to enhance their olfactory cues of health/underlying mate quality, dependent on their own mating motivations.
Given Higuchi et al. (2005) demonstrated that perfume use can increase self-reported feelings of dominance, it is possible that individuals who report wearing perfume more frequently are higher in other traits related to self-esteem, such as self-rated mate value. On the other hand, those women whose self-perceived mate value is lower might be using perfume more frequently to compensate for this. Thus, in the following study, I aimed to explore whether there were any differences between women who wore perfume on the day of the study and those who did not, as well as to examine which factors were able to predict the frequency of artificial scent use over a two-week period.
5.3 Methods
5.3.1 Participants
Participants were 193 female undergraduate students and interested volunteers from an
Australian University. I excluded participants older than 36 to account for lifespan changes in fertility, and women who were already pregnant (or unsure of their pregnancy status). Included in the final analysis were 174 participants (M age = 21.63; SD = 3.65, range = 18 - 36). Of these,
101 indicated they were currently in a relationship, and 72 were not (1 unsure). In addition, 104 women indicated they were currently using hormonal contraceptives, whereas 70 did not.
114 CHAPTER 5
5.3.2 Materials and Procedure
Participants completed the survey online. Participants were asked to provide details of their age, to complete the Kinsey scale (Kinsey, Pomeroy, & Martin, 1948), and to report whether or not they smoked cigarettes on a daily basis. Participants provided menstrual cycle information and relationship status. Women in a relationship were asked how satisfied they were with their relationship on a scale of 1 (very unsatisfied) to 7 (very satisfied), as well as how long they had been in their relationship. Single women also indicated their self-reported mating motivation (“to what extent are you currently seeking a short-term/long-term relationship?”, 1
‘not at all’ to 9 ‘extremely’).
Finally, I asked participants to indicate whether they were wearing any form of artificial scent (i.e., a perfume/cologne/scented deodorant) on the day of survey completion (yes or no).
They also estimated the number of days they had worn perfume/cologne/scented deodorant in the previous 2 weeks. If participants indicated they were wearing an artificial scent that day, they were also asked to name the scent. All participants then completed the MVI-S and SOI-R scales.
5.4 Results
Data were analysed using SPSS v21 for Mac. Statistics reported are two-tailed.
5.3.1 Mate-Value Inventory
Reliability analysis revealed that the items of the MVI-S had a Cronbach’s α of .79.
However, since I was interested in the extent to which different aspects of self-rated mate value might affect behaviour, a principle components factor analysis was conducted on the MVI-S scale. Initially, an oblique factor matrix rotation (direct oblimin) was used to determine whether any inter-factor correlations would emerge. Measures of sampling adequacy showed that the
Kaiser-Meyer-Olkin value was .795, and Bartlett’s test of sphericity was highly significant [χ2 =
937.53, df = 136, p < .0001], both statistics indicating the data was appropriate for factor analysis.
I subsequently extracted five factors that explained 59.52% of the variance. The component
115 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES correlation matrix showed a correlation between components 1 and 3 of .325. Tabachnick and
Fiddell (2007) argue that “if correlations exceed .32, then there is 10% (or more) overlap in variance among factors, enough variance to warrant oblique rotation” (p. 646). Thus, the oblique solution was retained. Several items had cross-loadings above 0.3 onto other factors. Items were selected for inclusion in a factor if a) the primary factor loading was above |0.5|, and either b) the next highest cross-loading was at least 0.2 smaller than the primary loading or c) their removal from a factor did not drastically increase the Chronbach’s α for that sub-scale. Loadings of each item onto the five factors are shown in Table 5.1, and the final inclusion of each item onto each factor is highlighted. Chronbach’s α values for each final factor are also provided.
Two single-item factors emerged in the best solution, while the other factors contained between three and six items. Sociable was the only item that did not form part of any factor.
Table 5.1. Factor loadings for each item in the MVI-S onto five factors
Component 12345 Ambitious -.078 .000 .614 .035 .188 Attractive body -.019 -.699 .257 -.350 -.089 Attractive face .207 -.738 .023 -.049 -.140 Desires children .104 .040 .017 .585 .124 Enthusiastic about sex .020 -.622 -.035 .302 .290 Faithful to partners .070 -.048 .091 .069 .830 Financially secure -.161 -.161 .666 .092 .100 Generous .725 .082 .060 .232 -.007 Good sense of humour .782 -.212 -.107 .067 -.063 Healthy .117 -.217 .570 -.063 -.223 Independent .108 .113 .691 -.307 .072 Intelligent .559 - .255 .125 - .371 .051 Kind and understanding .848 -.023 -.077 .000 -.005 Loyal .631 .112 .198 -.041 .408 Responsible .366 .249 .563 .030 .010 Sociable .127 -.127 .433 .496 -.313 Emotionally Stable .085 -.082 .631 .147 -.202 Chronbach's α for final sub-scale .798 .569 .700 ------
116 CHAPTER 5
Based on face validity, the factors were named Personability (component 1), Sexual
Confidence (component 2), Maturity (component 3), and the two single-item factors, Desires
Children (component 4) and Faithfulness (component 5).
5.4.2 Frequency of Perfume Use over Two Weeks
A bivariate correlational analysis revealed positive correlations among pair-bonded participants between frequency of artificial scent use over the previous two weeks and the Sexual
Confidence sub-scale of the MVI-S. For single participants however, significant correlations emerged between frequency of artificial scent use and the Personability and Maturity factors, and the single-item factors Desires Children and Faithful to Partners. Using an r-to-z transformation, correlations for pair-bonded and single women were directly compared. The difference reached significance for the Personability correlations (p = .041, two-tailed), and approached significance for the Desires Children item correlations (p = .077, two-tailed).
Table 5.2. Correlations between subscales of the MVI-S, and artificial scent use over two weeks, for participants in a relationship (left) and those not (right)
Frequency of perfume use Relationship No Relationship Personability -.014 .297* Sexual Confidence .201* .124 Maturity .134 .318** Desires Children .047 .314** Faithful to Partners .067 .239* *p < .05, **p < .001
Based on these significant differences in correlations, and to determine which of these variables were significant predictors when controlling for the other variables (and thus overcome the confounds of multiple bivariate correlations), subsequent stepwise linear regressions were separately conducted for pair-bonded and single participants. In both cases the five sub-scale
117 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES scores of the MVI-S were predictors, and frequency of artificial scent use over a two-week period was the outcome variable. For pair-bonded participants, the final model predicted a significant
2 2 amount of the variance in frequency of artificial scent use [F1,99 = 4.18, p = .044, R = .041, R adj
= .031], with Sexual Confidence emerging as a significant predictor (see Table 5.3). For the single participants, the final model also predicted a significant amount of the variance in
2 2 frequency of artificial scent use [F2,69 = 7.10, p = .002, R = .171, R adj = .147], with Maturity and Desires Children emerging as significant predictors (see Table 5.3).
Table 5.3. Multiple regression for predicting frequency of artificial scent use over a two-week period for participants in a relationship (top) versus those not (bottom)
Relationship β tp Sexual Confidence .20 2.05 .044 2 2 Model Summary: R (Adjusted R ) .04 (.03) No Relationship β tp Emotional Maturity .27 2.44 .017 Desires Children .27 2.40 .019 2 2 Model Summary: R (Adjusted R ) .17(.15)
A 2 x 2 between-subjects ANOVA was conducted to examine the effect of relationship status (yes or no) and HC use (yes or no) on the frequency of artificial scent use, however, no effects were observed.
5.4.3 Day-of-Study Perfume Use
Most participants (n = 138, 79%) indicated they were wearing a perfume or scented deodorant on the day of the study. In order to explore the effect of perfume, rather than everyday deodorant use, participants’ responses regarding which artificial scents they were wearing on the day of the study were examined, and responses coded into a binary perfume (yes or no) variable.
118 CHAPTER 5
Of those women who reported wearing some form of artificial scent, 116 (84%) reported wearing perfume.
Chi-square analysis revealed no significant difference from expected frequency between relationship status (yes or no), nor between HC users (yes or no) for perfume use on the day of the study. Given the difference in correlations between frequency of perfume use and the five sub-scales of the MVI-S, I performed separate binary logistic regression analyses for single versus pair-bonded women. No significant predictors emerged for day-of-study perfume use for pair-bonded participants. On the other hand, for single participants, a total of 71 cases were analysed and the full model significantly predicted perfume use [omnibus χ2 = 15.21, df = 5, p =
.009]. The model accounted for between 19.3% and 26.4% of the variance in perfume use, with
84.4% of the perfume wearers successfully predicted, but only 46.2% of the non-perfume wearers successfully predicted. Overall 70.4% of the predictions were accurate. Table 5.3 gives the coefficients and the Wald statistic and associated degrees of freedom and probability values for each of the predictor variables. This shows that only Maturity reliably predicted perfume use, although Faithfulness was close to significant. The coefficients revealed that an increase in
Maturity by one unit is associated with an increase in the odds of perfume use by 1.40, while each unit increase in Faithfulness is associated with an increase in the odds of perfume use by a factor of 0.62.
119 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Table 5.4. Logistic regression analysis for predicting single participants day-of-study perfume
use.
β SE β Wald's χ2 df p Exp(β) Predictor Constant 7.557 3.018 6.269 1 .012 N/A Personability .335 .541 .383 1 .536 1.398 Sexual Confidence -.137 .360 .144 1 .705 .872 Maturity -1.018 .535 3.617 1 .057 .361 Desires Children -.218 .151 2.101 1 .147 .804 Faithfulness -.479 .272 3.098 1 .078 .619
I also compared each MVI-S sub-scale score and scores on the all other scales (SOI-R,
relationship satisfaction, relationship length, short-term and long-term seeking) between
perfume and non-perfume wearers by conducting a series of independent samples t-tests. Sexual
Confidence scores were significantly higher for perfume wearers (M = 4.87, SD = 1.05) than
non-wearers (M = 4.54, SD = 1.01) [t170 = 2.00, p = .048, 95%CI =.003, .66], and a marginally
significantly higher Desires Children score for perfume wearers (M = 5.11, SD = 1.75) than non-
wearers (M = 4.55, SD = 1.88) [t170 = 1.91, p = .057, 95%CI = -.02, 1.12]. The Maturity scale
also approached significance (perfume wearers M = 5.45, SD = 0.87; non-wearers M = 5.20, SD
= 0.88) [t170 = 1.81, p = .073, 95%CI = -.02, 0.53]. No differences emerged between perfume
wearers and non-wearers on any other scales.
5.5 Discussion
Based on the results of a principle components factor analysis, I extracted five factors
that contribute to the full self-rated mate-value inventory score. These sub-scales were labelled
Personability, Sexual Confidence, Maturity, Desires Children, and Faithfulness to partners,
based on the individual items that subsumed them. These factors were demonstrated to correlate
significantly differently with the frequency of artificial scent use over a two week period for
single women compared to pair-bonded women. Specifically, Personability and Desires
120 CHAPTER 5
Children scores correlated with scent use for single women, but not pair-bonded. Sexual
Maturity scores correlated with scent use for pair-bonded women, although the difference from the single participant correlation did not reach significance. To examine this further, and to overcome the problems with conducting a series of correlations, two linear regression analyses were conducted, which revealed that the frequency of artificial scent use was predicted by Sexual
Maturity scores in pair-bonded women, and by Maturity and Desires Children scores in single women. No other factors were significant predictors of frequency of artificial scent use in this sample. Similarly, the odds of perfume use on the day of the study was predicted for single women by Maturity and Faithfulness scores. Overall, scores on the Sexual Confidence sub-scale were higher for those participants wearing perfume on the day of the study than those not. No effect was observed for HC use on frequency of artificial scent use nor on the odds of wearing perfume on the day of the study. While I cannot conclusively establish causality with this design
(that is, whether perfume use was increasing mate-value or mate-value influenced frequency of perfume use), and thus generalisations to other samples are considered with care, these findings do suggest that some differences exist in motivations for perfume use between women who are in a relationship versus those who are single.
Given independence, responsibility, desire for children, and faithfulness, are characteristics that men desire in a long-term partner (Buss & Schmitt, 1993), the correlations between the MVI-S subscales to which these items belonged and frequency of artificial scent use suggest single women are potentially using perfume to present themselves as an ideal long- term partner (alternatively, that the women who possess these characteristics are more likely to use perfume). This is in contrast to the use of perfume being a signal to confidence in one’s appearance or enthusiasm for sex (as indicated by the Sexual Confidence sub-scale). On the other hand, women who are already in a committed long-term, relationship showed no variation in perfume use based on the Personability or Maturity sub-scales of the MVI-S. Instead, these women had increased rates of artificial scent use with higher rates of Sexual Confidence
121 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
(enthusiasm about sex and self-perceived attractiveness). These differences were not due to a lack of variability of scores on these scales for women in a relationship, since variation on these scales was roughly equal for single women versus those in a relationship.
If women are unconsciously using perfumes to increase the perception of their mate qualities to others, then the results of this study suggest those qualities sought to be enhanced could be mediated by current relationship status. Previous research demonstrates that single women versus those in a relationship show differences in their mate-seeking and competitiveness behaviour. For example, Caryl et al. (2009) showed that women categorized as fertile (within a cycle) were marginally more attracted to large pupil size if they were currently in a relationship. Hahn, Fisher, Cobey, DeBruine, and Jones (2016) also demonstrated that partnered women are marginally less romantically jealous than single women are. While
Stenstrom (2007) found that the desire to spend money on clothes, shoes and accessories on fertile days is stronger in partnered women than single. Thus, women’s perception of others, their competitiveness behaviour, and cognitions regarding relationships, differ dependent on whether or not they are currently in a romantic relationship or not. This variation could explain underlying differences between this sample’s single and pair-bonded women in their desire to enhance particular characteristics of their perceived mate value.
In this sample, HC use did not predict artificial scent or perfume use. While perfume use may have an effect on self-rated mate value, variation as a function of hormones either does not occur, or else the nature of the research design and the sample size did nor provide enough power to detect an effect. The lack of any effect is interpreted with caution, and examination of the effect of HC use on perfume use in future studies is warranted.
Both women and men rate scent as important in mate choice. For example, Herz and
Cahill (1997) showed that both sexes rate olfactory information as important in selecting a lover, although men also rated visual information as equally important. Additionally, arousal during sexual and non-sexual activity was more dependent on tactile stimulation than odours, for both
122 CHAPTER 5 sexes. Similarly, Havlicek et al. (2008) showed that olfactory cues are more important to women in mate selection, and less so to men, who rate visual information as more important. If the mate attraction tactics of one sex are driven by the desires of the opposite-sex, then it would hold that variation in women’s use of perfume would indicate that men’s reliance on olfactory information is high. However, given women’s reliance on olfactory information is substantially higher than men’s, and men have an equally sizeable reliance on visual information, women’s use of perfume may not solely serve a mate attraction function. Instead, perfume use may have some role to play in enhancement of self-confidence, or potentially play a role in intra-sexual competition. In
Chapter 4, I demonstrated that women are more likely than men are to perceive additional effort put into the clothing styles of other women. Women are also able to predict more accurately than men were how a member of the opposite-sex would allocate attention in a mate choice-task
(Chapter 2). Given women are more likely to compete intra-sexually through means other than direct combat (Buss, 1988), it is possible that the signals of mate quality enhanced by the use of artificial scent could also serve as a dominance signal to other women. This is in line with
Higuchi et al. (2005), who demonstrated that women do, in fact, feel more dominant after perfume application. It is interesting to note that no relationship emerged between socio- sexuality and perfume use nor desire to engage in a short-term relationship. In addition, there were no differences between those women using hormonal contraceptives and those not. This further suggests that perfume use might serve some role other than (or in addition to) enhancing attractiveness to members of the opposite-sex.
This study has a number of limitations that are important to address. For the analyses regarding the frequency of artificial scent use over a two week period the questions pertained to the use of any artificial scent, and so it was not possible to account for how many of these days a perfume was used as opposed to a deodorant alone. In addition to this, the factor analysis (while yielding some interesting potential sub-scales) is preliminary, and conducted on a relatively small sample. Future research should address the reliability of these factors in larger, more
123 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES diverse, samples of participants. Finally, here I measured perfume use as a function of mating motivation, however, perfume choice as a function of mating motivation would reveal more about the potential use of perfume as part of a mating strategy. To address this, future studies could examine purchasing behaviour of perfume as it relates to other measures of mating motivation.
While the question of causality remains unanswered, it is clear that single and partnered women show underlying variation in the link between feelings about oneself and their frequency of perfume use, and these results complement previous research on the effects of scent on cognitions (Higuchi et al., 2005). It would be fruitful to explore further the use of perfumes across the menstrual cycle and factors that drive between-individual perfume use.
Following women’s perfume use across the menstrual cycle, using a within-individual sequential design would allow the detailed examination of individual factors that might affect use of artificial scent. In addition to this, examining which scents in particular are being used could provide further information about the signalling value of perfume, and the relationship to underlying mate cues. One might also examine the effects of this perfume use on others behaviours and interactions with individuals. If perfume use has a role to play in intra-sexual competition, for example, then the combination of scent with other stimuli could increase derogation from potential competitors. This area of research is clearly worth exploring, given recent interest in the role of artificial fragrances on the assessment of mate quality cues in body odour (Allen, Cobey, Havlíček, & Roberts, 2016).
124 CHAPTER 5
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128 CHAPTER 6
Chapter 6: The Effects of Dimorphism and Pupil Dilation on Facial Attractiveness
6.1 Chapter Overview
Having explored sex differences in attention allocation when judging potential mates, as well as variation in signals used to indicate potential mate value or mating motivation amongst women, the final two experimental chapters in this thesis take a more specific look at the role of faces in mate selection. In this chapter, I examine the role of pupil dilation in mate choice and intra-sexual competition. Since pupil dilation can be interpreted as a signal of state sexual arousal or trait promiscuity, I was interested in whether variation in pupil dilation on faces of potential mates and competitors could change the perceiver’s attraction to these stimuli. More specifically,
I attempted to determine whether pupil dilation would increase or decrease the attractiveness of faces that were masculinised and feminised, and thus to determine the interaction between sex- typical features and perceptions of arousal on attractiveness ratings, in both a mate selection context and an intra-sexual competition context.
6.2 Introduction
6.2.1 Pupil Dilation in Mate Choice
Pupil dilation can occur for a large number of reasons: as a corollary to sympathetic and parasympathetic nervous activity (Beatty & Lucero-Wagoner, 2000), reflexively to light and other stimulation, and because of cognitive load (Beatty & Lucero-Wagoner, 2000). Observing pupil dilation can therefore tell us about a variety of underlying processes, interpreted depending on context and task type. Pupil dilation can also inform us about the sexual interest that an individual has in a particular stimulus. Pupil dilation indicates activation of the autonomic nervous system (which is linked with blood pressure, heart rate, and perspiration), thus dilation reflects unconscious attention to stimuli that are sexually attractive (Rieger & Savin-Williams,
129 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
2012). As such, a number of researchers have examined the role of pupil dilation in mate choice by measuring individual preference for pupil size, along with pupillary reactions to others. In one of the classic studies in this field, Hess (1965) showed that men were more attracted to women’s faces that were rendered with larger pupils than those with smaller pupils.
Subsequently, Simms (1967) demonstrated that participants’ pupils dilated more to images of opposite-sex individuals than same-sex, and that this was moderated by the pupil size of the stimuli, with larger dilation responses to stimuli displaying dilated pupils. This early research suggested that individuals are able to detect pupil dilation in an opposite-sex individual (whether or not this was conscious) and respond by becoming more interested in or attracted to these stimuli. This is of particular interest as pupil dilation may act as a cue as to whether or not an individual is sexually aroused. More recently, a host of studies have continued to examine the role of pupil dilation in mate choice, in light of our increased understanding of mating strategies.
Tombs and Silverman (2004) presented images of faces on which pupil size had been manipulated, resulting in small, moderate and large pupiled stimuli, to 29 male and 30 female undergraduates. Mean attractiveness ratings of the faces showed that male participants found large pupils to be more attractive than moderate, and moderate more attractive than small, when judging female stimuli. On the other hand, female participants preferred both large and moderate pupils similarly more highly than small pupils. In a follow up study, the researchers demonstrated female participants were more attracted to large pupils if they had a preference for characteristics that describe a ‘bad boy’ (i.e., frivolous, opportunistic, handsome), although no correlation between attraction to large pupils and preference for ‘nice guys’ (i.e., sensitive, sentimental, considerate), or ‘mover shakers’ (i.e., foresighted, industrious, assertive). Given the sexual dimorphism in mating strategies (Buss & Schmitt, 1993), men showed strong attraction to sexual arousal, as signalled by the dilated pupils on female stimuli. Women’s pupils dilate more to preferred faces than novel (at least, when not using hormonal contraceptives; Laeng &
Falkenberg, 2007), and so it makes sense that men may have evolved a sensitivity to variation
130 CHAPTER 6 in pupil dilation in women in order to determine whether a potential mate is reciprocating sexual interest. On the other hand, Tombs and Silverman showed women had a less pronounced attraction to large pupils, with this attraction becoming stronger only when women indicated a preference for ‘bad boy’ characteristics (but not ‘nice guys’). Tombs and Silverman refer to strategic pluralism in female mate choice in order to explain their findings. That is, women are more attracted to ‘dads’ (who provide parental care) for long-term partners, and ‘cads’ (who provide good genes) for short-term affairs (Aitken, Lyons, & Jonason, 2013). Thus, if a woman is not specifically attracted to short-term cues (preference for ‘bad boys’), then the dilated pupils of a ‘bad boy’ may otherwise be potentially threatening. Women are more likely than men to underestimate the long-term relationship devotion of a potential partner, as per Error
Management Theory (Haselton & Buss, 2000), since the risks of missing a potential mating opportunity are outweighed by the benefits of avoiding unwanted pregnancy and potential abandonment and reputational risk. Thus, women have to weigh the risks of a missed mating opportunity, potentially signalled by dilated pupils, against the benefits. On the other hand, men are more likely to over-estimate the sexual interest of a potential mate, since the benefit of a potential mating opportunity outweighs the risk of rejection. Given this, differences in men’s and women’s attraction to dilated pupils might be a reflection of these varying risk-benefit trade- offs.
If women’s attraction to pupil dilation in male faces relates to preference for certain behavioural characteristics, it also makes sense that preferences for dilated pupils might depend on context. Similarly, if women’s attraction to dilated pupils reflects strategic pluralism in mate choice, then the cycle-shift in women’s sexual motivations should also change their preference for dilated pupils. Consistent with this, Caryl et al. (2009) demonstrated that menstrual cycle phase, hormonal contraceptive use, socio-sexuality, and relationship status, affected pupil size preference. Preference for large pupils was highest in women who were at high conception risk, compared to those who were low conception risk, or using hormonal contraceptives. This
131 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES preference was also larger in women who stated they were currently in a relationship than those who were not. Thus, individual difference factors are important to take into consideration.
6.2.2 Role of Dimorphism on Facial Attractiveness
The literature demonstrating the effects of facial sexual dimorphism on attractiveness is extensive (although not necessarily consistent, see Chapter 1). A host of factors such as gender, sexuality, hormonal contraceptive use, relationship status, resource scarcity, and short-term or long-term context, influences individual preference for masculinity or femininity in faces.
Interest in facial dimorphism attractiveness in the evolutionary psychology literature arose in part due to the seminal finding that women’s preferences for masculinity in men’s faces is influenced by their conception risk (Penton-Voak et al., 1999), and general preference for sex typicality in faces (Rhodes, Hickford, & Jeffery, 2000), proposed to be adaptive in mate choice
(Rhodes, 2006). Amongst the pupil dilation literature, there is currently no examination of the combined effects of sexual dimorphism in facial shape and stimulus pupil dilation on attractiveness ratings of stimuli. Male and female preference for masculine and feminine faces is well researched, as is preference for symmetry and colour characteristics of faces. However, given the sex difference in preference for dilated pupils, and the sex difference in preference for sexually dimorphic faces, it raises the question of whether attraction to these facial features might well be additive. This question was the basis for this study.
6.2.3 Intra-Sexual Competition
A host of previous studies have demonstrated that women, more so than men, are likely to compete intra-sexually through derogation of the appearance of potential competitors. For example, Vaillancourt and Sharma (2011) found that women were more likely to react negatively to an attractive woman when she was dressed in a provocative manner, but not when dressed conservatively. In Chapter 2, I demonstrated that women were more accurate than men were in judging how the opposite-sex would allocate attention in a binary choice task related to mating
132 CHAPTER 6 judgements. Additionally, in Chapter 4, we saw that women judged other women as putting more effort into their appearance when in the fertile phase of the menstrual cycle; however, men did not perceive a difference between fertile and non-fertile phases. One of the most frequently employed tactics in female intra-sexual competition involves appearance, whether it is spending more money on appearance-related products (Hudders, De Backer, Fisher, & Vyncke, 2014), or derogating the appearance of competitors (Fisher & Cox, 2009). Thus, women may have evolved a heightened sensitivity to variation in other women’s appearance and, given that women are also more likely to derogate when another woman appears sexually available (Vaillancourt &
Sharma, 2011), might decrease their attractiveness ratings of same-sex faces when pupils are dilated (a cue to sexual arousal). On the other hand, men compete less frequently through change in appearance (Tooke & Camire, 1991), and so are less likely to decrease attractiveness ratings when judging the appearance of attractive or sexually aroused men.
6.2.4 Current Study
In this study, I aimed to determine the extent to which stimulus pupil dilation affected attractiveness ratings of masculinised and feminised faces. I asked participants to rate the attractiveness of opposite-sex faces, in both short-term and long-term relationship conditions.
These faces were masculinised and feminised, and had pupils rendered dilated or constricted.
Participants also rated same-sex faces that varied in masculinity and pupil size, with the instruction to imagine how a member of the opposite-sex would rate these face (without consideration of relationship length). In keeping with the aims of the thesis, I also measured a range of individual difference variables, such as SOI-R, MVI-S, MIS and, for female participants, hormonal contraceptive use. I predicted that male participants would find feminine female faces more attractive when pupils were dilated, regardless of relationship condition. I also expected female participants to find dilated pupils on masculine male faces relatively more attractive for short-term judgements, when women are more likely seeking a cad, but not long-
133 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES term judgements, when they are seeking dad qualities (Aitken et al., 2013). For the same-sex judgements, I expected pupil dilation to have no effect on males’ ratings of male faces (given men’s decreased use of appearance derogation as a competitive strategy), but dilated pupils to decrease attractiveness ratings of feminine faces for females judging other females (since attractiveness and signals of sexual availability increase competitor derogation in women, as discussed above).
6.3 Methods
6.3.1 Participants
Participants were 60 heterosexual females (M age= 26.12, SD = 7.34, range = 18-47), and 56 heterosexual males (M age= 22.31, SD = 3.69, range = 18-35). I recruited participants from an Australian university as part of the Psychology participant pool, and volunteers from the local community, as well as online advertisements. Those participants who were recruited as part of a larger study (including the data reported in Chapters 4 and 7) were awarded with either course credit or a $20 shopping voucher. Those male participants recruited online (n = 35) were not awarded. For female participants, 24 stated they were using some form of hormonal contraceptive, while 36 did not.
6.3.2 Stimuli and Materials
Face sets were created using stimuli from the Radboud faces database (Langner et al.,
2010). Male and female face stimuli, with a forward facing neutral expression, were chosen for inclusion. Prototypes male and female face shapes were created by taking the composite face shape of 20 male and 20 female faces after delination with 174 landmarks (as shown in Figure
6.1). The face stimuli for use in this study were then delineated with 174 landmarks, standardised for inter-pupillary distance, and transformed along a linear dimension using PsychoMorph, with the female and male prototypes as anchors. This method exaggerates the sex typical shape differences between female and male faces by 50%, thus creating a 50% feminised and 50%
134 CHAPTER 6
masculinised version of each stimulus (Rowland & Perrett, 1995; Tiddeman, Perrett, & Burt,
2001). Stimulus pupil size was then manipulated using FantaMorph (Abrosoft). Thus, four
versions of each face identity were created: masculinised/constricted pupil, masculinised/dilated
pupil, feminised/constricted pupil, and feminised/dilated pupil (for stimuli examples see Figure
6.2). Two face ‘sets’ were then chosen (at random) from the total of male and female face
identities, so each set contained all four versions of that identity. Thus, each set contained eight
identities, for a total of 32 stimuli per set. For those participants who completed the study in the
lab, they viewed individual stimuli on a 25’ iMac computer screen, and responded using the
digits 1 to 9 on a standard QWERTY keyboard. Superlab 4.5 experiment software was used to
present stimuli For those participants who completed the study online, stimuli were presented
on the participant’s own device, and SurveyMonkey software was used to present stimuli.
Participants responded by sliding a scale on the screen.
Figure 6.1. Female shape prototype (left) and male face prototype (right) for face tranformations
135 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Participants also filled out a series of questionnaires, including the SOI-R, MVI-S, and the MIS, and a demographic questionnaire (age, gender, sexual orientation and HC use) as detailed in Chapter 1.
Figure 6.2. Examples of stimuli for face rating task. Feminised with large pupils (left) and
masculinised with constricted pupils (right).
6.3.3 Procedure
Participants first completed the questionnaire, and then completed the opposite-sex rating task, followed by the same sex-rating task.
For the opposite-sex judgement condition, participants were asked to rate the attractiveness of faces on a scale of 1 (not at all attractive) to 9 (very attractive) for a short- term condition (defined as a one-night stand or brief affair), and a long-term condition (defined as an ongoing relationship that may result in marriage-like commitment). Stimuli remained on the screen until participants made a response. Each face set was presented in either the short- term or long-term condition, with assignment to each condition counterbalanced between
136 CHAPTER 6 participants. The order in which participants completed the short-term and long-term conditions was also randomised.
For the same-sex judgement condition, participants were to imagine how someone of the opposite-sex would rate faces in attractiveness (without consideration of short-term or long-term condition) on a scale of 1 (not at all attractive) to 9 (very attractive) (e.g., for female participants:
“how would a male judge the attractiveness of this face?”). Participants were presented with one of the same-sex face sets, with face set counterbalanced between participants. Participation took approximately 1 hour.
6.4 Results
Data were analysed using SPSS v21 for Mac. Statistics reported are two-tailed.
6.4.0 Preliminary Data Screening
Not all participants completed all scales. For male participants, only 19 completed the
MVI-S, 52 the SOI-R and 52 the MIS. In addition, only 21 completed the same-sex face rating task. For female participants, only 58 completed the SOI-R and the MIS, and 59 completed the opposite-sex face rating task. Participants were excluded from analysis if they indicated they were homosexual.
6.4.1 Male Ratings of Female Faces
A 2(dimorphism) x 2 (condition) x 2 (pupil size) ANOVA was run with attractiveness ratings as the dependent variable. A main effect of femininity was observed, with males having a significantly higher attractiveness rating for feminised faces (M = 4.27, SD = 1.27) compared
2 to masculinised faces (M = 2.89, SD = 1.12) [F1, 55 = 171.71, p < .001, ηρ = 0.76]. No main effect of condition nor pupil size was observed, nor any interactions. Femininity preference was calculated as the difference between attractiveness ratings for feminine and masculine faces.
This was then correlated with the individual difference variables measured. However, no significant correlations were observed.
137 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
6.4.2 Female Ratings of Male Faces
For female participants, a 2 (dimorphism) x 2 (condition) x 2 (pupil size) x 2
(contraceptive use) ANOVA was conducted with attractiveness ratings as the dependent variable. A main effect of masculinity was observed, where women had a significantly higher attractiveness rating for masculinised male faces (M = 3.66, SD = 0.91) compared to feminised
2 male faces (M = 3.28, SD = 0.84) [F1,57 = 27.07, p < .001, ηρ = 0.32]. There was also a significant main effect of condition, where women rated all faces as more attractive in the long-term (M = 3.66, SD = 1.07) compared to the short-term (M = 3.29, SD = 0.84) condition
2 [F1,57 = 9.65, p = .003, ηρ = 0.15]. Finally, a four way interaction emerged between
2 masculinity, condition, pupil size, and contraceptive use [F1,57 = 5.84, p = .019, ηρ = .09]. In order to make this simpler to observe and interpret, masculinity preference was calculated whereby attractiveness ratings for feminised faces were subtracted from attractiveness ratings for feminised faces. As can be seen in Figure 6.3, in the short-term condition masculinity preference when pupils were dilated was higher for naturally-cycling women compared to those using contraceptives, while there was little difference for constricted pupils. Hence, in the short-term condition, the masculine faces were made relatively more attractive when pupils were dilated, which was in line with the hypothesis, but only for naturally cycling women. The subsequent simple comparisons showed that this interaction was due to a significant difference between contraceptive users and non-users when judging the attractiveness of dilated pupils in
2 the short-term condition [F1,57 = 4.67, p = .035, ηρ = .08]. In addition, the difference between constricted and dilated pupils in the short-term condition for women who were naturally
2 cycling approached significance [F1,57 = 3.90, p = .053, ηρ = 0.06]. In the long-term condition, the opposite effect emerged, whereby masculine faces were made more attractive when pupils were constricted for naturally cycling women compared to those using contraceptives, while dilated pupils did not change attractiveness ratings between naturally-cycling and
138 CHAPTER 6 contraceptive using women. However, with corrections made for multiple comparisons, this simple effect did not reach significance. No other main effects or interactions were observed.
Masculinity preference was then correlated with the individual difference variables measured. A significant positive correlation was observed between masculinity preference and desire for a short-term relationship [r56 = 0.30, p = .024] as well as with SOI-R [r56 = 0.31. p =
.019].
0.80 p = .053 constricted dilated 0.70 *p = .019
0.60
0.50
(masculine -(masculine feminine) 0.40
0.30
0.20
0.10 Masculinity Preference 0.00 Naturally cycling Contraceptive Naturally cycling Contraceptive Short-term Long-term Contraceptive use * Condition
Figure 6.3. Masculinity preference for male faces with constricted or dilated pupils, across short-
term and long-term conditions between contraceptive using and non-contraceptive using
women.
6.4.3 Same-Sex Face Judgements
A 2 x 2 mixed-model ANOVA with masculinity of same-sex faces as one factor, and pupil dilation as another, and relationship status as the between subjects factor, was conducted for male participants. Males rated masculine male faces as significantly more attractive than
139 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
2 feminine male faces [F1,18 = 8.70, p = .009, ηρ = 0.33], although no effect of pupil dilation was observed.
For female participants, contraceptive use was also added into the ANOVA (2 x 2 x 2).
For female participants, a significant main effect of masculinity was also observed, with higher attractiveness ratings for feminine female faces (M = 4.86, SD = 1.21) than masculine female
2 faces (M = 3.74, SD = 1.11) [F1,56 = 127.83, p < .001, ηρ = 0.70]. No other main effects or interactions were observed.
Average attractiveness ratings of same-sex faces were correlated with individual difference measures MVI-S, SOI-R and MIS. For male participants, average attractiveness ratings of male faces were negatively correlated with MVI-S scores [r18 = -0.50, p = .033]. There was also a negative correlation with scores on the MIS [r17 = -0.62, p = .008]. I found no correlations for female participants between same-sex face attractiveness ratings and any individual difference variables. However, with corrections for multiple correlations (Peres-Neto,
1999), the correlations should be replicated before solid conclusions can be drawn.
6.5 Discussion
In this Chapter, I demonstrated that men are more attracted to feminine female faces than masculine, which is consistent with previous research (see Glassenberg, Feinberg, Jones, Little,
& Debruine, 2010; Rhodes, 2006). I also found that women were more attracted to masculine male faces than feminine. This is not in line with the majority of previous research which typically demonstrates that feminine male faces are more attractive than masculine, until other factors such as relationship status, fertility, and contraceptive use are taken into account (Rhodes,
2006), though some previous studies have shown an average masculinity preference (e.g.,
Johnston, Hagel, Franklin, Fink, & Grammer, 2001). This masculinity preference is possibly an artefact of the stimuli that were used in this study. Overall, the male faces were relatively feminine to begin with. Exaggerating feminine features meant that many of the feminised male
140 CHAPTER 6 faces began to appear as though they were female (several could easily be mistaken for female faces). Since women were rating these faces as short-term or long-term partners, and none of our participants was homosexual, it is likely that the faces that were more easily categorised as male were the ones rated as more attractive. Other aspects of our stimuli, such as the visibility of hair, may have had an effect on masculinity preference, since DeBruine, Jones, Smith, and Little
(2010) demonstrated that unmasked images resulted in higher masculinity preferences than masked images. However, this was only evident with composite faces based on perceived masculinity, rather than variation in sexual dimorphism as achieved by the transforming technique described above. As such, this is something to be addressed in future research.
Pupil dilation could act as a cue of sexual attraction and there is evidence that men and women find dilated pupils more attractive (e.g. Simms, 1967). For example, Tombs and
Silverman (2004) showed that both men and women find dilated pupils to be more attractive than constricted, thus, I expected to find the same pattern of results here. However, no main effect of pupil dilation was evident in this sample, and the effect only reached significance when interacting with other variables, for female participants. This was not in line with the hypothesis, and not in line with previous research (e.g., Hess, 1965). It is possible that a methodological limitation can explain this non-significant effect. For example, the small number of stimulus identities used in this study (n = 16) may not have been enough to create reasonable variation in attractiveness ratings large enough to be detected. However, Tombs and Silverman were able to find a significant effect using only three male and three female models. Thus, the number of stimuli is unlikely the cause. Instead, the method of rating stimuli may have been responsible for the effect. In Tombs and Silverman’s research, participants were required to rank three versions of each model identity, whereas in this study, the participants were required to make a rating of attractiveness on a Likert scale between 1 and 9. It is possible that the use of a ranking or forced-choice task would yield different results, and should be addressed in future research.
141 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
I also expected that pupil dilation would moderate attraction to sexually dimorphic faces.
For male participants, this was not the case. It is likely this interaction was not significant owing to the same methodological limitations as discussed above. Given there was no significant main effect of pupil dilation on attractiveness, which was expected, it is unlikely this would interact with sexual dimorphism. For female participants, however, I found a significant interaction between masculinity, pupil size, contraceptive use, and condition, on attractiveness ratings of male faces. For participants using hormonal contraceptives, their masculinity preference was higher when pupils were dilated rather than restricted for long-term judgements, but lower when pupils were dilated rather than restricted for short-term judgements. For naturally cycling participants, the opposite effect emerged; with a higher masculinity preference when pupils were dilated rather than restricted for short-term judgements, and a higher preference for masculine faces when pupils were constricted for long-term judgements. Error Management Theory
(Haselton & Buss, 2000) can offer some insight into these findings. Hormonal contraceptive use works to increase progesterone to decrease conception risk, thus acting similarly to the non- fertile phase of the menstrual cycle (Alvergne & Lummaa, 2010). Thus, for hormonal contraceptive users making long-term judgments (in which individuals are likely seeking good
‘dad’ qualities) masculine faces were relatively more attractive when pupils were dilated than when they were constricted, since this might indicate that a masculine male (potentially provisioning resources or protection from aggressive other males) is displaying a signal of sexual interest/arousal. Thus, this male could represent the best combination of good genes (masculine face) and reciprocated sexual attraction (pupil dilation). On the other hand, for short-term judgements, the display of sexual arousal in masculine faces is potentially a signal of aggression, particularly as more masculine faces are typically perceived as being more dominant and less trustworthy (Oosterhof & Todorov, 2008). Thus, this variation could reflect a trade-off between the risks and benefits of dominance of the male and signals of attraction in a short-term or long- term encounter. For those women who were not using hormonal contraceptives (and overall had
142 CHAPTER 6 higher preferences for masculinity), masculine faces were made relatively more attractive if pupils were dilated in short-term judgements. Women who are not using hormonal contraceptives could be more willing to take risks with a masculine male for short-term relationships, since their desire to seek an extra-pair mate is increased, relative to hormonal contraceptive users, particularly as they approach ovulation (Alvergne & Lummaa, 2010). Thus, the risks and benefits of engaging with masculine faced males displaying signals of sexual arousal and/or promiscuity are dependent on the context of the judgement and contraceptive use.
Given the lack of significant main effects detected for pupil preference, and the finding that women in this study preferred masculine male faces over feminine, which was not expected, these results should be interpreted with caution. Importantly, in order to corroborate these findings, this study should be replicated using different stimuli and a more diverse sample.
As we expected, men rated masculine male faces as more attractive than feminine male faces, and this did not vary with pupil size. This may be because men are unaware of the sexual signalling value of dilated pupils in potential competitors, or more likely, given no main effect of pupil dilation for opposite-sex faces, the pupil dilation manipulation was not effective. Again, this study should be replicated. While men are less likely to engage in intra-sexual competitiveness via appearance related derogation than women (Buss, 1988), I did find negative correlations between attractiveness ratings of male faces, and male participants MVI-S and MIS scores. Thus, men who are higher on mating related self-esteem were more likely to rate the appearance of a potential competitor as lower. However, given the number of correlations, these need to be interpreted with caution (Peres-Neto, 1999)
For females making same-sex face judgements, I found no evidence for the hypothesis that female pupil dilation would moderate attractiveness ratings. Given women are likely to be aware of intra-sexual competitive tactics in other women (such as putting more effort into their clothing, see Chapter 4) I assumed they would also respond to pupil dilation in female facial stimuli. Since this was not the case, it is possible that pupil dilation is not something women
143 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES have evolved a sensitivity to in other women. Again, however, limitations regarding the stimuli used need to be noted. Finally, although participants were instructed to consider how a member of the opposite-sex would rate the same-sex faces on attractiveness, there was no indication of in what context the opposite-sex individual would rate these faces. That is, the participants were not informed whether the imaginary opposite-sex individual would be heterosexual or not, nor whether they would be rating them as sexually attractive or attractive as a long-term partner.
Thus, it is likely that participants interpreted this question differently, which could have resulted in the findings presented here.
There are a number of limitations in this study that require consideration. First of all, one aim with regard to female participants was to not only consider contraceptive effects, but the effects of fertility across the menstrual cycle. However, given the small sample that fell into the naturally-cycling group (n = 35), this was not possible to analyse. Secondly, the stimuli that were used for this study could be improved. Many of the male faces were relatively feminine to begin with, and applying a femininity manipulation led to many of them appearing to be, in fact, female faces. Both increasing the number of stimuli used, and changing to male faces that show more natural variation in masculinity, could allow the detection of pupil size effects. In addition, the lack of significant main effect of pupil dilation on attractiveness ratings means the pupil dilation manipulation may not have been effective. This highlights the need to be cautious in interpretation of the interaction between dimorphism, contraceptive, condition and pupil size for female participants rating male faces. In addition, the majority of male participants in this study also did not complete the full set of scales. As such, any correlations detected in male same-sex face judgements should also be considered with caution. That being said, there are studies that have found significant effects of face judgements when using only a sample size of 20 male and
48 female participants (Little & Harcus, 2016). Finally, the stimuli used in this study were static.
Given trait pupil dilation may actually be a cue to promiscuity (Lick, Cortland, & Johnson,
2016), it is possible that using moving stimuli, on which pupil dilation increases as the stimulus
144 CHAPTER 6 is being viewed, could activate other mechanisms engaged to detect change in sexual arousal, specifically, rather than those used to make trait judgements. Therefore interactive and moving stimuli should be considered for use in future research, in order to understand more about the way in which pupil dilation affects attractiveness judgements of masculine and feminine faces.
Overall, this study highlights the importance of considering pupil dilation in research on opposite-sex attractiveness. Signals of promiscuity or sexual arousal might moderate the effects of facial dimorphism on ratings of attractiveness. Specifically, in this study, women’s attraction to dilated or constricted pupils on masculine male faces depended on the interplay between context and contraceptive use, and is best understood when considering individual variation in the costs and benefits of interacting with a masculine male who might be signalling a high level of sexual arousal or promiscuity. This research also leads to a number of interesting questions that could be addressed in future research. Other than increasing the number and quality of stimuli used, it would also be fruitful to use interactive, dynamic stimuli. Given that static facial images are relatively un-natural, particularly in terms of signalling cues of reciprocal interest, for example, a paradigm involving dynamic stimuli in which pupil dilation varies in real time, could offer a more comprehensive understanding of the role of pupil dilation in perceptions of attractiveness of faces.
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6.6 References
Aitken, S. J., Lyons, M., & Jonason, P. K. (2013). Dads or cads? Women’s strategic decisions
in the mating game. Personality and Individual Differences, 55(2), 118-122.
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148 CHAPTER 7
Chapter 7: The Role of Facial Structure in Mate Choice
7.1 Chapter Overview
In Chapter 6, I examined how individuals rate the attractiveness of dimorphism in facial shape of potential mates and competitors, and how pupil dilation, a signal of promiscuity or sexual arousal, can affect these ratings. In this Chapter, I explore whether the same underlying factors drive objective variation in face shape and subjective perceptions of face typicality. In addition, I sought to examine the correlation of objective and subjective face shape with individual differences in mating factors, and to determine the extent to which each affects ratings of facial attractiveness.
7.2 Introduction
As discussed in Chapter 1, faces are clearly an important part of the way in which humans make judgements about the suitability of an individual as a potential partner (Rhodes, 2006).
Overall, people prefer to look at faces that are symmetrical, sex-typical, average, and attractive
(Rhodes, 2006). Historically, debates have arisen as to the specific functioning of facial shape variation, as well as the relationship between facial shape variation and mate quality and sexual strategies. For example, dimorphism in facial shape can differentially affect attractiveness ratings depending on the context, sexual history, and relationship status of the individual rating the images (see Chapter 6). However, whether or not face shape is a reliable predictor of between- (or even within-) individual variation in underlying hormone levels is not as clear. In addition, the relationship between subjective perception of sex-typicality and objective variation in face shape has only received limited scope in the literature (Fink et al., 2005; Mitteroecker,
Windhager, Muller, & Schaefer, 2015). Studies that have examined the effects of masculinity or femininity on a host of social judgements have typically examined either subjective ratings or
149 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES objective variation in the relative locations of various facial landmarks, but not both (e.g., female preferences for masculinity in male faces depends on the type of stimuli used; DeBruine, Jones,
Smith, & Little, 2010). Therefore, it is not clear whether both are affected by the same variation in underlying hormone levels, nor whether they both have the same effect on subjective ratings of attractiveness.
7.2.1 Face Architecture and Signalling Value
Masculine male face shape clearly has some mating-related signalling value, since women are differentially attracted to masculine face shape dependent on whether or not they are ovulating (e.g. Penton-Voak & Perrett, 2000). Thus, masculinity could signal underlying traits that are more or less important to women as they approach ovulation. According to the cycle- shift hypothesis (Gangestad, Thornhill, & Garver, 2002), as women approach ovulation, their chances of conception from a single act of intercourse increase and, as such, they are more attracted to cues of genetic fitness. Thus, if women prefer masculine faces more at this time, then masculinity might be a cue to genetic fitness. However, while typical arguments propose that masculine face shape is an honest signal of heritable immuno-competence, this assumption has been questioned by a number of researchers (e.g., see Mays & Hill, 2004; Scott, Clark,
Boothroyd, & Penton-Voak, 2013). Thus, it is important to understand the extent to which measures of masculinity and femininity may actually be affecting these contradictory findings.
In favour of the good genes view of facial structure, Thornhill and Gangestad (1996) demonstrated that fluctuating asymmetry and facial masculinity (as measured by a principle axis factor analysis using five face measurements) correlated with self-reported number of respiratory illnesses in a health history questionnaire. In addition, Penton-Voak and Chen (2004) showed that perceived masculinity of male faces was associated with higher testosterone levels. Though
Pound, Penton-Voak and Surridge (2009) later found no relationship between circulating testosterone and the structure of male face shape, when using a more objective measure of
150 CHAPTER 7 masculinity consisting of measuring five facial dimensions previously shown to be sexually dimorphic (such as eye size, mean eyebrow height and cheekbone prominence). However, Pound et al. did find that after competition, differences arose in the rate of change of testosterone between masculine and non-masculine faced males. Testosterone works during puberty to affect the growth of a number of facial features, including cheekbones, chin, and eyebrow ridges (Fink
& Penton-Voak, 2002). As such, circulating testosterone levels post-puberty will only be indirectly related to masculine facial shape, as more proximate factors such as parenting and age can also affect circulating hormone levels (e.g., Gettler, McDade, Feranil, & Kuzawa, 2011), whereas masculine face shape becomes fixed. However, as demonstrated with Pound et al.’s research, face structure may be telling us something about the functioning of the endocrine system, and thus still has a role to play as a cue to mate quality. Lefevre, Lewis, Perrett, and
Penke (2013) showed that facial width to height ratio was associated with higher testosterone levels, but facial dimorphism was not. These measures of masculinity calculate variation of these landmarks between female and male members of the species, and so are a more robust measure of sex typicality, being the basis for most transformations of female and male faces along a masculine-feminine scale (Rowland & Perrett, 1995). More recently though, Rantala et al.
(2013) have argued that facial adiposity is a more valid cue to immuno-competence than structural dimorphism. Adiposity in modern environments is related to a host of underlying health problems such as heart disease and risk of stroke (Despres, 2012). Hence, facial dimorphism might not be as strong a signal of underlying health or hormonal variation, as once thought.
It is clear that facial shape is signalling something about a male’s potential mate value, since the attractiveness of these male facial features varies in accordance with important mating- related factors in those women making judgements of these faces, such as current relationship status (e.g., Little & Jones, 2012), contraceptive use (e.g., Little, Burriss, Petrie, Jones, &
Roberts, 2013), and impulsivity (Boothroyd & Brewer, 2014). Femininity in male faces is
151 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES typically more attractive (Rhodes, 2006), and women perceive masculinity in male faces to be more attractive than femininity only under certain contexts. For example, Little and Jones (2012) demonstrated that the cyclical shift to perceive masculine faces as more attractive is stronger in women when judging for short-term relationships than long-term. Little, DeBruine, and Jones
(2011) showed that exposure to visual cues of environmental pathogens increased individual masculinity preference in opposite-sex faces. Variation in the preference for masculine or feminine male faces, as well as a potential reason for contradictory findings on the link between circulating testosterone and masculinity, is related to the specific manipulations performed on these faces. That is, faces can be transformed along a linear scale using facial gender prototypes
(as in Chapter 6), in which case a percentage of the differences between prototypical male and female faces are added or subtracted from a face, and this can occur with only facial shape or with facial shape and colour (DeBruine et al., 2010). Alternatively, faces that have been pre- rated as masculine or feminine can be combined to create prototypes, and then faces transformed towards or away from these (DeBruine et al., 2010). Finally, faces may be morphed toward these masculine and feminine prototypes. Slightly different results may arise, bringing into question the scale of variation between male faces and female faces. For example, Rennels, Bronstad, and
Langlois (2008) demonstrated that faces created using dimorphic transformations based on average male and female prototypes resulted in a femininity preference, whereas faces created using prototypes based on faces pre-rated as high or low in masculinity resulted in a masculinity preference. The linear dimorphism scale does not result in the same attractiveness ratings or preferences as the subjective masculinity – femininity scale. Hence, the relationship between perceived masculinity, objective dimorphism, testosterone, and attractiveness is not clear.
Femininity in female faces may also reflect variation in underlying immuno-competence.
For example, Wheatley et al. (2014) showed that facial and vocal attractiveness in women correlates with testosterone levels, age, and body mass index. However, just as with the immuno- competence model of male faces, there has been conflicting evidence surrounding the role of
152 CHAPTER 7 female facial shape in signalling underlying health cues. For example, Rhodes, Chan, Zebrowitz, and Simmons (2003) showed that subjective ratings of femininity in adolescent female faces did not correlate with actual health, although subjective femininity was perceived as healthy and attractive. On the other hand, perceived masculinity in male faces had some correlation with actual health and was perceived as healthy, but had no correlation with attractiveness ratings.
However, Thornhill and Gangestad (2006) demonstrated that masculinity in female faces was related to frequency of respiratory infections in women. Similarly, Gray and Boothroyd (2012) showed that rated femininity in female faces was related to health history. This further illustrates the potential confounds of measuring perceived femininity and masculinity, versus objective face shape dimorphism, and further highlights the potentially different signalling value of masculinity and femininity in male and female faces.
In addition to underlying immuno-competence, variation in female facial shape has been implicated as signalling within-cycle variation in hormone levels. For example, Oberzaucher et al. (2012) found evidence for variation in facial shape between the fertile and non-fertile phase of the menstrual cycle. Fertile faces were significantly more frequently chosen as being more attractive, healthy and sexy. In addition, variation in several principle components in face shape were observed, as well as variation in hue, contrast and colour homogeneity. However, Burriss et al. (2015) have demonstrated that while variation in redness in women’s faces does occur across the menstrual cycle, it is unlikely that these changes are detectable by the human visual system. Thus, this research calls into question the value of changes in hue as a signal of fertility.
Variation in femininity across the menstrual cycle is likely related to fat distribution, as ovulation can affect adiposity (Kirchengast & Gartner, 2002).
A few researchers have attempted to resolve the issues regarding morphometric variation in face shape versus subjective perceptions of masculinity and femininity. Mitteroecker et al.
(2015) measured objective face variation in 21 female and 24 male faces, as well as had these faces rated by independent observers on a scale of feminine to masculine. The researchers
153 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES demonstrated that male faces rated higher in masculinity had wider faces, wider nose, thinner lips, and larger and more rounded lower facial outline. Overall, the face shape variation accounted for 25% of the variation in masculinity ratings. What remains to be seen is the extent to which morphometric variation or subjective ratings of masculinity and femininity better account for variation in attractiveness, as well as their relationship to other individual difference factors. Valenzano, Mennucci, Tartarelli, and Cellerino (2006) found that distance of female faces from an average face shape was correlated with attractiveness ratings (r = -0.35), but overall that attractiveness ratings were related to a specific principle component that was not actually sexually dimorphic.
7.2.2 Current Study
In summary, it is clear that variation in facial masculinity and femininity has some role to play in mate choice, however the relationship between hormone variation, objective face variation, subjective perceptions of sex-typicality, and attractiveness, is still not clear (although this question is receiving more exposure in recent literature, see Mitteroecker et al., 2015). In this study, I sought to determine whether subjective and objective measures of masculinity and femininity in faces correlated, and to what extent variation in perceived sex-typicality and attractiveness were related to underlying hormone levels. In addition, I examined whether subjective and objective masculinity and femininity related to self-rated mate value factors and subjective measures of attractiveness by independent observers. By doing so, we may develop a more holistic understanding of the role of objective versus subjective variation in face shape on mate choice, and thus gain a better understanding of what information might be available when looking at the faces of potential mates. I hypothesised that objective variation in face shape would explain a small but significant portion of the variation in perceived femininity and masculinity, in line with Mitteroeker et al. (2015). I also hypothesised that estradiol and progesterone would explain variation in attractiveness ratings and perceived femininity in female
154 CHAPTER 7 faces, but that testosterone would not explain attractiveness and masculinity in male faces (see
Pound et al., 2009 and Puts et al., 2013).
7.3 Methods
7.3.1 Participants
Participants were 38 female (M age = 25.26, SD = 5.48, range = 19-36) and 39 male (M age = 24.00, SD = 5.27, range = 18-42) undergraduate psychology students and volunteers.
Participants were awarded with course credit or a $20 voucher per hour of participation. They were initially contacted via recruitment materials located at the University and in local online bulletin boards, and female participants were scheduled to their sessions after reporting the onset of their last menstrual period, the expected date of their next menstrual period, plus their typical cycle-length (36 female participants also completed the study reported in Chapter 4). Male participants were scheduled according to availability.
7.3.2 Materials
The same procedures for collection of the saliva samples and participant scheduling was followed as in Chapter 4. Photographs were taking using a Fujifilm FinePix 3D camera, approximately 1.5m from the participant. Participants were instructed to wear no makeup and to assume a natural face posture. Vertical axis rotation and horizontal head-tilt were avoided where possible, although some variation remained even after controlling for pupil alignment (see vector outputs). In addition having their photographs taken, participants also filled out questionnaires pertaining to their sexual orientation, age, relationship status and satisfaction, body weight and height, and also completed the MVI-S and SOI-R (as detailed in Chapter 1).
7.3.3 Procedure
Participants were instructed on the passive drool technique for collection of the saliva sample. While this was being completed they filled in the questionnaires, before finally posing
155 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES for the photographs. Female participants completed the same tasks on both occasions. Session order (fertile or non-fertile session first) was counterbalanced. Male participants completed only one session.
7.3.4 Independent Ratings of Facial Images
Independent raters were 24 male (M age = 28.08, SD = 7.98, range = 20 - 49) and 54 female (M age = 22.67, SD = 7.04, range = 18 - 60) who were recruited as a convenience sample via an online research management system and social media (Facebook). The survey was hosted on SurveyMonkey. Stimuli consisted of the facial images collected from the main study participants (male faces, and female faces from both sessions). Raters were presented with each of these images in random order, and asked to make a rating of their attractiveness, on a scale of
1 (not at all attractive) to 9 (very attractive); femininity, on a scale of 1 (not very feminine) to 9
(very feminine); and masculinity, on a scale of 1 (not very masculine) to 9 (very masculine).
Participants also indicated how well they knew the person being depicted on a scale of 1 (I have never seen them before today) to 9 (I know this person extremely well). Stimuli remained on the screen until participants made a response.
7.3.5 Hormone Analysis
Saliva samples were assayed for concentrations of estradiol and progesterone (for female participants), and testosterone (for both female and male participants). Estradiol concentrations were run in duplicate using high-sensitivity human saliva 17β-estradiol ELISA (Abnova
Corporation, Taipei, Taiwan). Concentrations of progesterone were run in duplicate using
Progesterone ELISA kits (Enzo Lifesciences, Farmingdale, NY). Testosterone samples were run in duplicate using Testosterone ELISA kits (Enzo Lifesciences, Farmingdale, NY). Intra-assay
CV’s were maintained below 10%.
156 CHAPTER 7
7.3.6 Morphometric Analysis
Participant faces were delineated in PsychoMorph (Rowland & Perrett, 1995) using a template of 174 points, similar to Benson and Perrett (1993). Face sets were aligned for both eyes and mouth prior to principle component analyses (PCA). For the male to female variation analysis, PCA was run using all male faces and the female faces from their first session only, regardless of fertility (fertile n = 22, non-fertile n = 16). Following each PCA, linear discriminant analysis was run using SPSS.
7.4 Results
Data were analysed using SPSS v21 for Mac. Statistics reported are two-tailed.
7.4.0 Preliminary Data Screening
For any fertility analyses, phases were determined based on the backwards-counting method (based on actuarial data from Wilcox, Dunson, Weinberg, Trussell, & Baird, 2001), where the day of ovulation was calculated as 14 days prior to the onset of menstruation. To increase sample size, non-fertile phases did not fall within a specified number of days, resulting in a total of 33 women included in within-cycle analyses. For the between-subjects analyses, cycle-phase was not considered, in which case 38 women were included for analyses. Not all participants completed all variables nor provided viable saliva samples for analyses. Twenty- nine women provided a viable saliva sample, while 32 males provided a viable saliva sample.
Only 25 males provided their weight and height for BMI calculations. In addition, not all participants agreed to have their faces rated by independent raters. Thirty-one males agreed to have their faces rated while only 21 females agreed. Any analyses that involve hormone concentrations are recommended to have a sample size of at least 71 to detect an effect with a correlation across phases of 0.70 and an effect size of d = 0.5 (Gangestad et al., 2016). However, the majority of this research was conducted over the period between 2012 and 2013, prior to the publication of these recommendations. In addition, given prior research has reported a detectable
157 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES effect with hormone measures within-subjects of only 30 participants (e.g., Jones et al., 2005), and the associated costs of hormone analyses, it was determined that a sample size of < 40 women would be sufficient. However, in keeping with up-to-date recommendations, further research is needed to confirm any trends observed. Finally, a number of the female participants in this study also completed the study presented in Chapter 4. The same issues with the loss of material before testosterone analyses are therefore relevant here.
7.4.1 Hormone Outcomes
For fertile to non-fertile analyses, estradiol concentrations did not differ between the fertile (M = 5.71pg/mL, SD = 1.87) or non-fertile (M = 5.16, SD = 1.56) phases [t28 = 1.46, p =
.157], although non-fertile progesterone (M = 155.77, SD = 77.64) was significantly higher than fertile progesterone (M = 119.77, SD = 50.17) [t30 = -2.41, p = .022]. Plus, the estradiol-to- progesterone ratio was significantly higher in the fertile (M = 0.05, SD = 0.02) than the non- fertile session (M = 0.04, SD = 0.02) [t28 = 2.50, p = .018], which is in the predicted direction if these sessions varied in fertility (Eisenbruch, Simmons, & Roney, 2015). For male participants, average testosterone concentration was 297.38 pg/mL (SD = 174.14).
7.4.2 Subjective Ratings
As detailed in section 7.4.0, not all participants agreed to have their faces independently rated, and of those who did, not all provided viable hormone samples. Thus, only n = 20 women provided saliva samples for both sessions as well as has their faces independently rated. Those raters who indicated they knew the participant faces reasonably well (> 3/9) had their data excluded from average calculations. Therefore not every participant had the same number of raters. Number of raters for each face ranged between 66 and 75 (M = 72, SD = 2.16). After data exclusion, I calculated a subjective attractiveness, femininity and masculinity score for each participant, and performed further analysis using these values. Overall, female faces were rated
158 CHAPTER 7
as higher in attractiveness [t50 = -4.19, p < .001], higher in femininity [t50 = -10.29, p < .001], and lower in masculinity [t50 = 15.46, p < .001] than male faces.
I correlated subjective scores with the individual difference variables. Subjective masculinity scores for men correlated with their total SOI-R [r31 = 0.40, p = .029] and marginally with the attitudes subscale [r31 = 0.35, p = .056]. Subjective masculinity also correlated positively with age [r31 = 0.46, p = .010]. There was no correlation between subjective masculinity and attractiveness scores, nor between either of these measures and the men’s testosterone levels, short-term or long-term mate seeking behaviour, or MVI-S scores. Testosterone correlated negatively with body mass index (BMI, calculated based on self-reported height and weight) [r24
= -0.48, p = .018], as did age [r31 = 0.51, p = .004]. Finally, attractiveness ratings were unrelated to masculinity or femininity ratings. Given the number of correlations, the results should be replicated before meaningful conclusions can be drawn.
For within-subject cycle analyses for female participants, no differences were observed between fertile and non-fertile phases for subjective ratings of attractiveness, femininity, or masculinity (all p > .05). As such, no further analyses for subjective ratings were considered within subjects across cycle-phase. Instead, between-individual analyses were conducted, specifically for the measurements taken during fertile phase. Pearson’s correlations were run between subjective attractiveness ratings and age, BMI, progesterone and estradiol levels, and their ratio, and the individual difference variables. Correlations are presented in Table 7.1. As shown here, a significant positive correlation was observed between estradiol and progesterone concentrations and attractiveness and femininity ratings, and a negative correlation between estradiol and progesterone concentrations and masculinity ratings. In addition, a negative correlation was observed between self-reported short-term relationship seeking and masculinity ratings. While a number of correlations was performed, the size of the correlations is large, and consistent between estradiol and progesterone across three measures. Hence, they are unlikely to be due to chance.
159 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
In addition, without consideration of fertility level, I calculated the average ratings for both sessions, and correlated these with the average hormone levels across both sessions. As shown in Table 7.2, a negative correlation emerged between BMI and attractiveness ratings, as well as negative correlations between estrogen and masculinity rating, and between self-reported short-term relationship seeking and masculinity ratings. Even though a number of correlations were performed and thus should be interpreted with caution, the size of the correlations were large. Finally, attractiveness ratings were correlated positively with femininity ratings [r21 =
0.77, p < .001] and negatively with masculinity ratings [r21 = -0.79, p < .001].
Table 7.1 Fertile session only correlations between individual difference measures and subjective ratings. Attractiveness Femininity Masculinity Rating Rating Rating Age -0.16 -0.14 0.18 BMI -.461* -0.33 0.36 Estrogen 0.26 0.41 -.537* Progesterone 0.21 0.27 -0.30 Short-term 0.39 0.41 -.579** Long-term -0.06 0.24 -0.12 SOI-R -0.08 0.01 -0.08 MVI-S 0.03 -0.10 -0.11 n = 20 *p < .05 ** p<.01
160 CHAPTER 7
Table 7.2. Correlations between individual difference measures and subjective ratings when considering averages for both fertile and non-fertile sessions.
Attractiveness Femininity Masculinity Rating Rating Rating
Age -.033 -.059 .118
BMI -.443 -.229 .282 Estrogen .560* .518* -.649** Progesterone .557* .491* -.564* Short-term .403 .390 -.481* Long-term .011 .369 -.308 SOI-R .066 -.174 -.118 MVI-S .172 .154 -.250 n = 20 *p < .05 ** p<.01
In order to determine whether hormone levels best explained variation in female subjective face ratings, I ran two regression analyses, one using only the fertile phase data, and one using data averaged across both sessions. In both cases, I controlled for age and BMI, and entered the progesterone and estradiol levels as predictors. As demonstrated in Table 7.3, for the fertile day analysis, progesterone emerged as the only predictor of attractiveness ratings. For femininity and masculinity ratings, estradiol emerged as the best predictor. For the analysis of values collapsed across sessions, no significant predictors emerged for attractiveness ratings or femininity ratings, although estradiol again emerged as the significant predictor for masculinity
2 ratings [F1,16 = 8.20, p = .013; R adj = 0.32; B = -0.23, SE(B) = .08, β = -0.61, t = -2.86, p = .013].
161 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Table 7.3. Multiple linear regressions for predicting subjective face ratings (attractiveness, femininity and masculinity) for female faces during the fertile phase of the menstrual cycle.
Variable BSE(B)β t p Attractiveness Rating Progesterone 0.01 0.004 0.66 3.37 .004 2 F1,16 = 11.33, p = .004, R adj = 0.39 Femininity Rating Estradiol 0.34 0.14 0.52 2.63 .032 2 F1,16 = 5.57, p = .032, R adj = 0.22 Masculinity Rating Estradiol -0.20 0.06 -0.65 -3.3 .005 2 F1,16 = 10.90, p = .005, R adj = 0.38
7.4.4 Objective Dimorphism – Morphometric Analysis
For the male to female face shape variation analysis, I included all male faces (n = 39) and female faces from their first lab session only, regardless of menstrual cycle phase (n = 38 identities). Faces were aligned for eyes and mouth to the average of all faces prior to analysis.
In order to conduct a PCA, PsychoMorph (Rowland & Perrett, 1995) was used. Each face was delineated using 174 landmarks, and an average face shape template created for the whole sample. An Active Shape Model was created and used to determine seven vectors that explained >75% of the variance in face shape for the whole image set. For each individual face, each value for each of the seven vectors was saved. Using SPSS, linear discriminant analysis was then performed by coding faces as male or female (for averages, see Figure 7.4).
Discriminant scores (the extent to which each face differed from the average, and in which direction) and probability of group membership (male or female) based on vector scores were saved for each face. The linear discriminant analysis correctly categorised 92.3% of male participants and 89.5% of female faces.
The seven vectors that emerged from the PCA are shown in Appendix D, and are described below. Vector 0 consisted largely of head pitch, with low scores representing downward pitch and high upward. Vector 1 combines some aspect of asymmetry in head shape as well as dimorphism of brow shape and some yaw, with low scores having thicker lips,
162 CHAPTER 7 thinner brows, and a more oval face shape with some rightward yaw, and high scores thicker brows, thinner lips, and a squarer face shape, with some leftward yaw. Vector 2 consisted largely of facial width and height, whereas low scores were wider and shorter, and high scores taller and thinner. Vector 3 also had some small variation in yaw, asymmetry in head shape, and dimorphism in lip size. Vectors 4 and 5 showed variation in dimorphic characteristics such as face shape (low square, high oval) as well as brow and lip shape (low masculine, high feminine). Finally, Vector 6 also showed variation in asymmetry and brow shape, with higher scores representing thinner brows and lips, and low scores thicker and lower brows.
Figure 7.1. Averages for Linear Discriminant Analysis between male and female faces
7.4.4 Relationship Between Objective and Subjective Measures
In order to determine whether objective variation and subjective judgements were related, values for each vector, the discriminant score and probability of group membership were correlated with subjective ratings. As shown in Table 7.4, both Vector 1 and Vector 4 scores were correlated with all three ratings. In addition, Vector 6 scores were correlated with femininity and masculinity ratings, but not attractiveness ratings. Finally, the total discriminant score was correlated positively with attractiveness and femininity ratings, and negatively with masculinity ratings. Thus, 63% of the variance in femininity scores was accounted for by facial
163 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES variation, whereas 76% of the variation in masculinity scores was accounted for by facial variation. Again, while there are a large number of correlations, the size of these correlations and the large p-values mean they are unlikely to be due to chance.
Table 7.4. Correlations between subjective ratings and Vector and discriminant scores based on linear discriminant analysis for 39 male and 38 female faces.
Attractiveness Femininity Masculinity Ratings Ratings Ratings Vector 0 -.186 -.176 .168 Vector 1 -.431** -.448** .466** Vector 2 .237 .153 -.073 Vector 3 -.093 -.114 .141 Vector 4 .336* .683** -.752** Vector 5 .119 .067 -.029 Vector 6 .210 .335* -.353* Discriminant .469** .797** -.875** Score Probability of .156 .098 -.133 group female n = 52 *p < .05 ** p < .01
Given this analysis included the whole set of both male and female faces, I then conducted separate analyses for male and female discriminant scores with the subjective ratings. For female participants, the correlations were no longer significant (all p > .07).
Hence, variation in facial dimorphism did not explain variation in subjective femininity or attractiveness ratings for female faces. For the male participants, total discriminant scores correlated positively with femininity ratings [r31 = 0.51, p < .004] and negatively with masculinity ratings [r31 = -0.43, p = .017]. Hence, 18.5% of the variation in masculinity ratings of male faces was attributable to dimorphism of face shape.
Finally, in order to determine whether dimorphism of face shape was related to self- reported individual difference variables, and thus whether the variation in this group of faces
164 CHAPTER 7 could potentially provide information about mating related factors to others, the vectors and discriminant scores were correlated with age, BMI, SOI-R and MVI-S, as well as short-term relationship seeking and long-term relationship seeking. For female participants, Vectors 1 and
6 correlated positively with BMI [r36 = 0.35, p = .036; and r36 = 0.36, p = .032 respectively].
Interestingly, vectors 4 [r36 = 0.32, p = .047] and 6 [r36 = 0.34, p = .040] as well as the discriminant score [r36 = 0.39, p = .014] correlated positively with the behaviour sub-scale of the SOI-R. Hence, faces that possessed characteristics that are more feminine were higher in socio-sexuality. For male participants, there was no correlation between any individual difference variables and Vector scores, but age [r36 = -0.44, p = .005] and BMI [r29 = -0.52, p =
.004] correlated negatively with Vector 5.
7.5 Discussion
The aim of this chapter was to determine the extent to which objective facial morphometries, determined using 174 landmarks and principle component analysis, correlated with subjective masculinity and femininity ratings, as well as the relationship between these and ratings of attractiveness. In addition, I sought to examine the relationship between these factors and other individual difference variables such as SOI-R, MVI-S and BMI. Owing to small sample size, any interpretations made based on this data are preliminary, and limitations are noted regarding the generalisability of these findings. However, the results offer avenues for future research.
Firstly, I discuss the relationship between subjective ratings and hormone levels and individual differences. Subjective masculinity scores for males were positively correlated with socio-sexuality. Hence, men who are more open in their sexual attitudes and behaviour are also rated as being more masculine. This is in line with previous research by Boothroyd, Jones, Burt,
DeBruine, and Perrett (2008), who showed that composite faces made up of men high in socio- sexuality were rated as higher in masculinity by independent observers. Perceived masculinity
165 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES did not correlate with attractiveness ratings of testosterone levels for male faces, which not surprising given previous research surrounding the relationship between masculine male faces and attractiveness (e.g., Rhodes, 2006), although is not in line some research demonstrating a relationship between perceived masculinity and testosterone (Penton-Voak & Chen, 2004).
There are likely a number of reasons for this. Either the link between testosterone and attractiveness does not exist (Rhodes et al., 2003; Swaddle & Reierson, 2002), or the methodology used was not sufficient to detect a difference between faces high and low in testosterone. For example, Penton-Voak and Chen (2004) had a sample of 50 male faces
(whereas I only had 31), and used a forced-choice task rather than a Likert rating. Thus, a larger sample size, and more reliable testosterone measures (such as change in testosterone as measured by Pound et al., 2009) should be utilised in future studies.
For female faces, a positive correlation was observed between estradiol and attractiveness and femininity ratings, as well as a positive correlation between progesterone levels and attractiveness and femininity ratings, when considering female participants’ fertile sessions. The limitations of using such a small sample size have been addressed (Gangestad et al., 2016), although the correlation between estradiol levels and attractiveness ratings are consistent with previous research. For example, Grillot, Simmons, Lukaszewski, and Roney
(2014) showed that once controlling for BMI, estradiol was positively associated with body attractiveness ratings (though the generalisability of these findings to facial attractiveness should be considered carefully). However, the positive correlation between progesterone concentrations and attractiveness is not in line with previous research, with Puts et al. (2013) showing that lower progesterone levels were associated with increased attractiveness rating. Interestingly, when entered into a regression analysis, progesterone levels predicted facial attractiveness, whereas estradiol levels predicted masculinity and femininity ratings. Estrogen is related to the development of female reproductive features (Alonso & Rosenfield, 2002), and so this link is not surprising. However, the positive correlation between progesterone and attractiveness ratings
166 CHAPTER 7 is not clear. Future research should seek to clarify these findings with a larger sample size and more reliable detection of ovulation. Lastly, when considering individual differences in mating- related measures, a negative correlation emerged between self-reported short-term relationship seeking and subjective masculinity ratings of female faces. Female attractiveness (significantly related to high femininity / low masculinity) is a large component of female mate value (Buss &
Shackleford, 2008), and women who are more attractive have been shown to be more demanding in all those characteristics desired in a potential partner (Buss & Shackleford, 2008). Hence, it is not surprising that women who were rated as less masculine also has higher desire for short- term relationships. Thus far, variation in perceptions of masculinity and femininity in male and female faces is related to some aspects of socio-sexuality and short-term relationship seeking.
So perception of these traits in other faces is likely telling us something about those individual’s mating strategies.
For the morphometric analysis, a number of vectors emerged that showed clear deviation between male and female faces. These differences included lip size (thinner or thicker), eyebrow thickness, and face shape (oval or square). Including all female and male faces in a correlation analysis, Vectors 1, 4 and 6 were most strongly related to perception of variation in masculinity and femininity. That is, low scores on Vector 1 were considered more feminine / less masculine.
Faces with low scores on Vector 1 were more oval in shape, had thinner brows, fuller lips, and a more pointed chin than faces higher on Vector 1. High scores on Vector 4 were associated with higher femininity ratings and lower masculinity ratings. High scores on Vector 4 were defined by a more pointed chin, higher arched brows, and fuller lips than faces with low scores on Vector
4. Finally, higher scores on Vector 6 were associated with higher femininity and lower masculinity ratings. Faces with higher scores on Vector 6 were seen to have thinner brows, and rounder foreheads than those faces low on Vector 6. Overall, the range of variation between male and female faces was able to account for 63.5% of the variation in femininity ratings between male and female faces, a substantial amount. Hence, femininity and masculinity ratings
167 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES appear to be strongly related to discriminant variation between male and female faces. However, over 35% of the variation in masculinity and femininity ratings was not accounted for by dimorphism of shape. When considering only female faces, variation in femininity, masculinity and attractiveness scores was no longer accounted for by morphometric variation. For male participants, 18.5% of the variation in masculinity ratings of male faces was accounted for by the discriminant function. This is similar to previous research by Mitteroecker et al. (2015) who showed that variation in masculinity shape scores accounted for 25% of the variation in masculinity ratings in male faces. Hence, a significant proportion of dimorphism of face structure accounts for masculinity ratings in male faces. The relationship between dimorphism and femininity in female faces is not as clear. Similar to the subjective femininity ratings for female faces, the discriminant function (and Vectors 4 and 6) in female faces was correlated with socio-sexuality, this time with SOI-R scores.
A number of limitations are important to consider. The issues with sample size, hormone measurements, and fertility cycle calculations have all been addressed in previous chapters.
Another limitation to consider relates to the ratings of faces by independent observers. Again, the loss of testosterone samples leaves an incomplete picture, as testosterone has previously been shown to have a significant effect on female facial attractiveness (Wheatley et al., 2014)In order to increase sample size, participants who indicated that they had some familiarity with the subject were included in analysis. That is, on a scale of 1 (I have not seen them before today) to 9 (I know this person extremely well), answers larger than 4 were excluded. This means that some participants may have recognised the stimuli, although would not have a close relationship with them. In any case, even slight familiarity can affect attractiveness ratings of faces (Peskin &
Newell, 2001). As such, the use of wholly unfamiliar stimuli should be considered for future research. Further, the ratings provided by independent observers were collapsed without consideration for rater sex. Since a number of factors can affect the ratings of attractiveness that an individual gives a face (e.g. menstrual cycle phase in women, Little & Jones, 2012),
168 CHAPTER 7 consideration of rater sex should be incorporated in future studies. I also performed a number of correlations in this study, which increases the chance of a Type I error (Peres-Neto, 1999).
However, the size of the r-values, and the magnitude of the p-values, as well as a consistent pattern of correlations, indicates that these correlations are not due to chance. Finally, another limitation is evident in the use of a principle component analysis and linear discriminant function for the morphometric analysis. Mitteroecker et al. (2015) found that the discriminant function in their sample accounted for only 2% of explained variance in masculinity scores and depended on the number of principle components chosen. Moreover, allometric sexual dimorphism (i.e., when the relationships between size and shape are not geometric) explained a larger proportion of variation in masculinity ratings, rather than non-allometric. However, vectors were not decomposed in such a way in this study. In addition, Valenzano et al. (2006) found that a principle component in female face shape that was not dimorphic correlated significantly with attractiveness ratings. Using a range of morphometric analyses, considering aspects of faces shape that are not dimorphic, and considering the relationship of these to other individual difference factors, should be a focus of future research. This will contribute to a more in-depth understanding of what exactly the information contained in faces is telling us about an individual, as well as the relationship of face shape to mate selection.
Overall, perceived femininity and masculinity appear to be only partially explained by morphometric variation between faces. As discussed by Mitteroecker et al. (2015), the unexplained variation is likely attributable to fluctuating asymmetry, facial texture and hair colour, and other factors such as menstrual cycle phase and psychological status (of the raters).
In addition, attractiveness ratings for female faces were associated with perceived femininity, while attractiveness of male faces was not associated with perceived masculinity. Attractiveness ratings were also only significantly related to the discriminant function when considering both male and female faces (given female faces were higher in attractiveness overall), but no variation within-gender was associated with variation in discriminant scores. This further illustrates the
169 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES importance of considering both perceptions of masculinity and femininity versus biological variation between the sexes when considering the relationship between dimorphism and mating selection.
170 CHAPTER 7
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175 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Chapter 8: General Discussion
8.1 Chapter Overview
In this Chapter, I restate the overall aims of the thesis. I also reiterate the main findings of each chapter, provide a general discussion of strengths and limitations of this thesis, and present new directions for theoretical research on mating strategies.
8.2 Reiteration of Thesis Aims
The aim of this thesis was to explore individual variation in mating strategies as understood from the perspective of Sexual Strategies Theory (Buss & Schmitt, 1993). Given the difference in minimal parental investment between the sexes (Trivers, 1972), men and women have been under differential selection pressures and thus have evolved slightly different mating psychologies (Buss & Schmitt, 1993). Men and women therefore compete with conspecifics for access to mates in different ways (Buss, 1988; Thornhill & Gangestad, 1996). However, in addition to general sex differences in mating behaviour, the employment of mating strategies is context dependent, giving rise to a range of individual differences (e.g., Glassenberg, Feinberg,
Jones, Little, & Debruine, 2010; Little & Mannion, 2006; Rhodes, 2006; Welling et al., 2008).
These differences are a reflection of the weighing of costs and benefits associated with either displaying a particular signal to mate quality, or pursuing a relationship, enacted in order to maximise individual reproductive success. Thus, each individual has a set of mating preferences, traits, signals, and perceptual biases that differ from other individuals. Based on this, I aimed to explore further the factors that affect these individual differences in mating strategies.
Throughout this thesis, I attempted to explore how men and women might send signals of their mate quality and/or respond to information about the suitability of a potential mate or the characteristics of a competitor, as well as which individual differences in mating relevant
176 CHAPTER 8 variables interact with these signals to vary measurable behaviour. Thus, I was interested in how context, mating-related individual differences (such as socio-sexuality, self-rated mate value, and physical attractiveness), and hormone variation (including circulating hormone levels or hormonal contraceptive use) could vary the way that individuals display their mate value to others, and how they react to variations in these signals in potential mates and competitors. The signals of mate value I explored included facial structure, clothing choices, and use of artificial scent. The behavioural responses of interest included attention allocation and attractiveness ratings of stimuli. In doing so, I considered tactics of both inter- and intra-sexual competition, and addressed five broad research questions:
1. How do men and women allocate attention when judging the suitability of a potential
partner?
2. Do women change their overt signalling of mate quality across the menstrual cycle?
3. Do women signal their mate-value through means other than behaviour and
appearance?
4. How do individuals respond to variation in facial characteristics in potential mates
or competitors?
5. How do men and women’s facial structure and perceived attractiveness vary in
response to underlying hormone levels, and do perceived attributes and objective
facial structure correlate?
8.3 Key Findings
In Chapter 2, I demonstrated that men and women place differential importance on information from either the face or body of a potential mate when asked to make a judgement for either a short-term or long-term relationship. Overall, we saw that both sexes perceive the face to be more important than the body, thus emphasising the importance of facial attractiveness in mate choice. However, men’s (but not women’s) ratings of the importance of information
177 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES from the body increased in short-term (but not long-term) mating contexts. In addition to this, I was able to demonstrate that women are more accurate than men are when making the same decision about bodies or faces for what they thought an opposite-sex individual would choose.
Therefore, men’s attention to bodies is dependent on context, and women are aware of the importance men place on information from the body in short-term relationship judgements.
Based on these findings, in Chapter 3, I decided to explore male attention allocation to female faces and bodies using an eye-tracking paradigm. Eye-tracking allows us to examine in more detail how visual attention can be drawn to particular areas, as well as general preferences for looking at the face or body, rather than the relative, consciously judged, importance of these areas. Previous research has largely chosen to examine the effects clothing versus no clothing
(e.g., Lykins, Meana, & Kambe, 2006; Nummenmaa, Hietanen, Santtila, & Hyona, 2012).
However, women’s clothing choice could have an important role to play in mate choice (e.g.,
Prokop & Pazda, 2016). Given it is important to understand how men’s mate preferences and attention allocation might work in modern contexts (see Chapter 1), I asked men to consider the attractiveness of female figures as either a short-term or long-term relationship partner, and manipulated the potential signalling value of their clothes by varying clothing type. I demonstrated that in the short-term condition, men’s attention to the face decreased for party/revealing clothing, but not conservative clothing; whereas in the long-term condition, attention to the face or body did not differ between clothing types. These results suggests that men’s attention to female faces and bodies is not only dependent on short-term or long-term context (as demonstrated in Chapter 2), but also on the interaction with clothing type
(party/revealing clothing versus conservative clothing), meaning men’s automatic attention to women’s visible skin is not a foregone conclusion. This, coupled with evidence that women are aware of the social signalling value of their clothes (Grammer, Renninger, & Fischer, 2004), and that women are rated as wearing more sexy and revealing clothing as they approach ovulation
178 CHAPTER 8
(Haselton, Mortezaie, Pillsworth, Bleske-Rechek, & Frederick, 2007), was the basis for Chapter
4.
In Chapter 4, I examined naturalistic dress choice variation across the menstrual cycle, as well as explored the relationship of these factors to other mating-related individual differences. Overall, I found that women increase objective skin exposure when in the fertile phase of the menstrual cycle compared to the non-fertile phase. However, in this sample, objective skin exposure was unrelated to subjective attractiveness ratings given by independent observers, although both measures correlated with estradiol change. Female independent observers chose the models’ fertile photographs as the ones in which they were putting more effort into their appearance, although male observers did not. Higher estradiol levels in the fertile session relative to the non-fertile session were associated with a larger proportion of the fertile photo as the one in which the model was putting more effort, and estradiol change across the menstrual cycle was also related to increased skin exposure in the fertile session. Hence, estradiol could mediate the relationship menstrual cycle phase and dress choice. Recent suggestions that a sample size of at least 71 is required to detect reliable within-subjects effects related to menstrual cycle phase (Gangestad et al., 2016) mean the relationship between estradiol level and skin exposure may require a larger sample size to be reliably detected. Even so, the effect size of the shift in clothing was 0.25, which is reasonable. The change in skin exposure was also in line with previous research showing women’s illustration of their clothing choices change across the menstrual cycle (Haselton et al., 2007). Overall, the results suggest that estradiol could mediate clothing choice across the menstrual cycle.
In Chapter 5, I shifted away from female signalling using clothing, and instead sought to examine variation in another potential signalling tool: artificial scent. Perfume use has a long human history, and research has demonstrated that individuals self-select perfumes based on their MHC structure (Milinski & Wedekind, 2001). Given the role of MHC-compatibility in mate choice (Wedekind, Seebeck, Bettens, & Paepke, 1995), I hypothesised that perfume use
179 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES would relate to variation in mating strategies between individuals. While I found no variation in scent use between contraceptive users and non-users, I did find differences between pair-bonded and single women. Overall, pair-bonded women showed a relationship between perfume use and sexual confidence. On the other hand, single women showed a relationship between perfume use and emotional maturity and a desire for children. In addition, the difference between perfume wearers and non-wearers (on the day of the study) were such that perfume wearers were higher in sexual confidence scores. These results suggest that perfume use may serve a mating function.
Women may use perfume as a mate attraction tactic, otherwise it might serve to increase the confidence of the wearer, which is in line with previous research by Higuchi, Shoji, Taguchi, and Hatayama (2005). The relationship between perfume and mating strategies is one that warrants further exploration.
Finally, in Chapters 6 and 7, I focussed more closely on the role of faces in mate choice.
In Chapter 6, women’s attractiveness ratings of masculine male faces varied depending on the interaction between hormonal contraceptive use, the context of the judgement, and the pupil dilation of the stimuli. Women who were naturally cycling preferred masculine faces more when presented with dilated pupils for short-term judgements, whereas women using hormonal contraceptives showed a higher preference for masculine faces displaying dilated pupils for long- term judgements. The risks and benefits of interacting with a masculine faced male with dilated pupils is likely different between women using hormonal contraceptives and those naturally cycling, and can be understood from the context of Error Management Theory (Haselton & Buss,
2000). That is, for hormonal contraceptive users making long-term judgements, ‘dad’ qualities are likely sought, whereas for non-contraceptive users making short-term judgements, ‘cad’ qualities will be more attractive (Aitken, Lyons, & Jonason, 2013). Thus, the combination of a masculine face (good genes) and dilated pupils (sexual arousal/promiscuity) could serve to increase the attractiveness of these male faces for short-term judgements for women who are
180 CHAPTER 8 naturally cycling, but could act as a warning signal for long-term judgements, in that the risk of desertion by a cad could be too great to ignore.
In Chapter 7, I aimed to explore in more detail the potential mate signalling value of human faces, and to correlate subjective perceptions of sexual dimorphism with objective variation in facial configuration. This is because of contrasting findings in the literature regarding the attractiveness of masculine and feminine faces (e.g., Rennels, Bronstad, &
Langlois, 2008), and the ambiguity surrounding the relationship between subjective perceptions of masculinity and morphometric measures (e.g., Mitteroecker, Windhager, Muller, & Schaefer,
2015). Female faces were rated as more attractive, more feminine, and less masculine than male faces, and these subjective perceptions of femininity were correlated with estradiol levels, whereas subjective perceptions of attractiveness were correlated with progesterone. This is interesting since variation in clothing choice in Chapter 4 was related to estradiol levels.
Estradiol and the menstrual cycle shift clearly has an important role in mate choice (Gildersleeve,
Haselton, & Fales, 2014), and these findings are in line with previous research, further suggesting that variation in estradiol underlies both attractiveness ratings and clothing choice, despite the limited sample sizes. For male faces, subjective masculinity and attractiveness did not correlate with testosterone levels. When considering morphometric variation, the variation between male and female faces accounted for 63% of the variation in femininity scores, which is not surprising given female faces were rated as more feminine. Interestingly, when considering only the variation within-sex, variation between faces accounted for only 18.5% of the variation between male faces in masculinity scores. Hence, subjective masculinity and femininity judgements are not wholly dependent on morphometric variation between faces. In female faces, both subjective variation in masculinity judgements and morphometric variation were related to relationship orientation, with subjective masculinity correlated with short-term relationship desire, and morphometric masculinity correlated with socio-sexual behaviour. Hence, our
181 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES subjective perceptions of masculinity, while only partially explained by morphometric variation, might tell us something about the mating motivations of the individual.
8.4 Consideration of Limitations
The strength of this thesis lies in its broad overview of individual variation in mating signals (both the perception of these from others and the signalling of these to others) across a variety of signalling modalities (faces, bodies, clothing, scent), and using a host of research techniques. I was able to explore, in detail, men’s and women’s mating strategies, including tactics of mate attraction and intra-sexual competition, and their relationship with other important mating-related individual differences, such as socio-sexuality, self-rated mate-value, and physical attractiveness. In completing the body of work presented in this thesis, I have also identified several important avenues for future research, including differences in the signalling value of female clothing in different contexts, the potential role of perfume in mate selection, and the relationship between subjective and objective measures of femininity and masculinity.
Several limitations require consideration. Hormone measures are exquisitely sensitive to individual fluctuations. Testosterone in particular can increase or decrease depending on exercise, sexual activity, and time of day (e.g., Dabbs Jr. & Mohammed, 1992). Different methods of estimating the fertile window using counting methods may result in low validity estimates compared to more accurate detection of luteinizing hormone surges, and assay of circulating hormones (Gangestad et al., 2016). In an attempt to overcome this, I used both the backwards counting method to estimate the fertile window, as well as measurement of hormone levels, in both within-subjects analyses and between-subjects analyses. The research reported in this thesis was designed based on sample sizes that led to the detection of significant effects in previous research (Dixson, Grimshaw, Linklater, & Dixson, 2010;
Haselton et al., 2007; Rosen & López, 2009; Rupp & Wallen, 2007). However, given the small sample sizes in those chapters in which I was interested in gonadal hormonal variation (that is,
182 CHAPTER 8
Chapters 3, 4 and 7), and recent guidelines that suggest that a minimum of 71 participants is required for any within-subjects cycle analysis (Gangestad et al., 2016), it is important to consider these as preliminary findings, and thus seek to replicate these with larger samples.
On a personal note, and as detailed throughout the thesis, a large number saliva samples were unable to be assayed for this thesis, owing to uncontrollable circumstances (that is, weather incidents leading to power shortages and subsequent loss of material). Thus, I was unable to complete planned analyses of female testosterone levels, which is unfortunate as testosterone can have important effects on female mating strategies (e.g., Welling et al., 2007).
Had I examined variation in testosterone, we might have gained a more complex understanding of the role of testosterone on female facial structure and on everyday dress choices, although this is an avenue of research to explore in the future.
In saying this, the relationship between circulating hormone levels and various mating factors continues to be a point of debate in the literature, as outlined in Chapter 1. For example,
Havliček, Cobey, Barrett, Klapilová, and Roberts (2015) have argued recently that only between-individual variation in mating preferences has been evolutionarily selected for, and that any within-cycle fluctuations in preferences are merely by-products, a result of the activating and organising effects of hormones. Indeed, several researchers have questioned at all the relationship between circulating hormone levels and various mating preferences. For example, recently Marcinkowska et al. (2016) found no relationship between estradiol and women’s masculinity preferences in differing contexts. However, as has been detailed in a meta-analysis by Gildersleeve et al. (2014), there is overwhelming evidence for the effects of menstrual cycle phase on mating preferences. That is, a robust shift is evident in women’s mate preferences when making judgements for short-term relationships but not long-term relationships. Although the meta-analysis by resulted in different conclusions, with the researchers claiming to find no support for menstrual-cycle effects on female mate preferences.
Thus, the question is far from settled in the literature.
183 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
While here I did examine within-cycle variation in two of the Chapters (4 and 7), I also endeavoured to analyse between-individual variations. In doing so, I found evidence for within-cycle changes in dress, although no evidence for within-cycle changes in ratings of facial attractiveness or subjective ratings of masculinity or femininity. While the question may remain whether within-cycle fluctuations in mating strategies were indeed evolutionarily selected for, and thus their ultimate function, these changes are clearly detectable and have a genuine effect on proximate behaviour, hence demonstrating the importance of considering the modern context in questions of mating strategies. Whether or not the effect size of within- individual variation in mating strategies is smaller than between-individual differences
(Havliček et al., 2015), hormonal variation is more readily detectable when considering within- individual change. For example, the administration of testosterone to men can change their self-perception of facial masculinity, although only for men with lower levels of baseline testosterone than those with high levels (Welling, Moreau, Bird, Hansen, & Carre, 2016).
Thus, mixed-model designs can reveal important information about the effects of hormones on mating-related behaviours. Hence, it is important to examine both between- and within- individual variations, and to consider the effect of individual differences in other mating- related measures these designs.
8.5 Future Research Directions
Based on the findings of this body of research, there are a number of future research opportunities that present themselves. For example, although a wealth of research has examined the relationship between contraceptive use and mate preferences, there is an extent to which it remains unclear how much these differences are due to other factors, such as pre- existing hormonal differences between users and non-users (see Oinonen, Jarva, &
Mazmanian, 2008 for a discussion). There is evidence that the uptake of the contraceptive pill can have genuine effects on mating behaviour (see Welling, 2013, for a review of the effects of
184 CHAPTER 8 contraception on human behaviour). Research in neurology also indicates that contraceptive use can change neural structure and cognitions (Lisofsky, Riediger, Gallinat, Lindenberger, &
Kühn, 2016). Given this, it can be argued that contraceptive use is causing variation in these mating factors, however, the paucity of research examining these mating cognitions before, during, and after contraceptive use within individuals leads naturally to question these assumptions. Thus, future research should attempt to address these issues, by increasing recruitment of women before and after use of the contraceptive pill, such as in Cobey,
Klipping, and Buunk (2013).
In addition to variation within individuals in their contraceptive use, the differential role of progesterone, estradiol and testosterone on mating strategies leads to another interesting question. Although hormonal contraceptives work by decreasing the chances of a conception event, not all do so in the same way. Most increase progesterone, but not all increase estradiol.
In addition, fluctuations in the time of day that women take these contraceptive pills, and the differences between oral contraceptives and those that are taken non-orally (such as implants, injections, or vaginal rings), could give rise to different effects. Although a relatively large sample size would be required in studies examining these effects, it would be fruitful to explore potential variation between different types of hormonal contraceptives and their effect on mating behaviours.
There is also the possibility that bearing children can have a huge impact on these mating-related behaviours. Mating-related preferences and behaviours change in accordance with developmentally important life stages, for example, as we move through puberty
(Boothroyd, Meins, Vukovic, & Burt, 2014). This lends evidence to the argument that they are specifically mating-related, and not general perceptual preferences. In addition, we know that pair-bonded and single women vary in their mating behaviours (Cobey et al., 2013), and that age can decrease preferences for masculinity in faces, for example (Little et al., 2010).
However, a more in-depth examination of the variation in mating preferences of those women
185 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES who are either pregnant or have recently given birth, or between women who have one, two, or more, children (for example), remains relatively unexplored. This research would likely provide us with a more comprehensive overview of the role of successful reproduction on subsequent mating strategies, and not just those that change over the life cycle of reproductive capacity.
Of particular interest, the findings of Chapters 2, 3 and 4 suggest that while women’s bodies are important to men in short-term mating contexts, women’s clothing choice can have an effect on this. Women’s clothing choice was also observed to change across the menstrual cycle, and this was related to variation in estradiol. Expanding on these findings by means of larger sample sizes, more reliable detection of ovulation, and potentially using 3D imaging to more specifically measure skin exposure, would increase our understanding of how women’s clothing choice could act as a potential mate signal. In addition, clothing choice can have an important effect on the wearer (Adam & Galinsky, 2012). Exploring the relationship between clothing choice and mating orientation in women is a path worth exploring.
8.6 Summary and Conclusions
Men and women have been under differential selection pressures and thus have evolved differing mating psychologies (Buss & Schmitt, 1993). Within each sex, a huge range of individual variation arises, as each individual weighs the costs and benefits of a particular set of mating strategies (Gangestad & Simpson, 2000). Thus, each individual possesses a set of traits, cognitions, behaviours, preferences, and perceptual biases that help them to navigate the mating and world, by signalling their mate quality to others, and driving the detection of these signals from others. In this thesis, findings suggest men and women place differential importance on information from the face or body in different contexts, that women’s clothing choice has an effect on men’s attention allocation to women’s bodies under differing contexts.
I also found that women’s choice of everyday dress varies across the menstrual cycle and is
186 CHAPTER 8 related to change in estradiol, and that these naturalistic clothing choices might act as potential signals to intra-sexual competitors. In addition to variation in clothing choices, I explored the potential signalling value of perfume use, and found that pair-bonded women and single women have a differential relationship between perfume use and self-rated mate value. Finally,
I found that men and women’s preferences for dimorphism in facial structure might be moderated by cues to sexual arousal (pupil dilation), and that this only occurs when making mating judgements, but not when rating the attractiveness of potential competitors. In addition, objective variation in facial shape only explains a portion of the variation in perceptions of masculinity and femininity. Finally, estradiol explained variation in perception of femininity in female faces, although testosterone had no effect on perceptions of masculinity in male faces.
Of particular interest, the findings presented in this thesis suggest that female bodies are important to men in short-term mating contexts although clothing choice can vary this. In addition, women’s clothing choice changes across the menstrual cycle, mediated by estradiol.
With this in mind, it is clear that preferences for viewing particular information, or attraction to facial characteristics, as well as those signals that are being displayed to other individuals (clothing choices, face structure, and artificial scent use) show large amounts of individual variation. While in this thesis I examined the relationship between these behaviours and socio-sexuality, mating intelligence, and self-rated mate value (as well as age, body-mass index, desire to engage in a relationship, hormonal contraceptive use, and relationship status), there are a huge range of variables that were unexplored (e.g., life history strategy, socio- economic factors, and number of offspring, to name a few). Considering these variations as evolved strategies can help to explain why they exist, and allows us to consider the costs and benefits, at both a group and individual level, of the employment of these strategies. Future research on sexual strategies should consider the role of perfume use on mate choice, for example, or the role of different forms of hormonal contraceptive on mating preferences. The
187 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES more we understand about the role of these factors on mate choice, the more we can inform individuals about what might be driving their idiosyncratic dating and mating behaviours.
188 CHAPTER 8
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193 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Presentation of Results Arising From This Thesis
Published Manuscripts
Wagstaff, D.L., Sulikowski, D. & Burke, D. (2015). Sex-differences in preference for looking
at the face or body in short-term and long-term mating contexts. Evolution, Mind and
Behaviour DOI: 10.1556/2050.2015.0003
Conference Presentations
Wagstaff, D.L., Sulikowski, D. & Burke, D. (2016). Effects of pupil dilation and contraceptive
use on masculine face preference. 43rd Annual Australasian Experimental Psychology
Conference, March 2016, Melbourne Australia.
Wagstaff, D.L., Sulikoswki, D., Makin, J. & Burke, D. (2015). Human female sexual
signalling: hormones, physiology and behaviour. Behaviour 2015, August 2015, Cairns
Australia.
Wagstaff, D.L., Makin, J., Sulikowski, D. & Burke, D. (2015). Further evidence that women
dress to impress: naturalistic observations and mating motivations. 42nd Annual
Australasian Experimental Psychology Conference, April 2015, Sydney Australia.
Wagstaff, D.L., Sulikowski, D. & Burke, D. (2015). Men’s attention to female faces and
bodies is a function of context: an eye-tracking study. 6th Annual European Human
Behaviour and Evolution Association Conference, March 2015, Helsinki Finland
Wagstaff, D.L. & Burke, D. (2013). Do women know what men want? Perceptions of
opposite-sex allocation of resources to aid mate selection. 40th Annual Australasian
Experimental Psychology Conference, April 2013, Adelaide Australia
194 APPENDICES
Appendix A - Common Scales
A.1 Socio-Sexual Inventory-Revised
Adapted from Penke and Asendorpf (2008) 1. With how many different partners have you had sex with in the past 12 months?
0 1 2-3 4-7 8 or more
2. With how many different partners have you had sex on one and only one occasion (one- night stand)?
0 1 2-3 4-5 8 or more
3. With how many different partners have you had sex with without having an interest in a long-term committed relationship with this person?
0 1 2-3 4-5 8 or more
4. Sex without love is OK.
Strongly disagree 1 2 3 4 5 Strongly agree
5. I can imagine myself being comfortable and enjoying “casual” sex with different partners.
Strongly disagree 1 2 3 4 5 Strongly agree
6. I do not want to have sex with a person until I am sure that we will have a long-term, serious relationship.
Strongly disagree 1 2 3 4 5 Strongly agree
7. How often do you have fantasies about having sex with someone with whom you do not have a committed relationship? (Please circle the appropriate response).
1) Never 2) Very Seldom 3) About once a month 4) About once a week 5) Nearly every day
8. How often do you experience sexual arousal when you are in contact with someone with whom you do not have a committed romantic relationship?
1) Never 2) Very Seldom 3) About once a month 4) About once a week 5) Nearly every day
195 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
9. In everyday life, how often do you have spontaneous fantasies about having sex with someone you have just met?
1) Never 2) Very Seldom 3) About once a month 4) About once a week 5) Nearly every day
196 APPENDICES
A.2 Self-Rated Mate Value Inventory
Adapted from Kirsner, Figueredo, and Jacobs (2003)
How well do you feel that each of the following attributes applies to you currently? Please
answer honestly and the best of your ability. Please tick the box that most closely resembles
your response for each attribute.
Extremely low on this Extremely high on this
trait Neutral trait
-3 -2 -1 0 1 2 3
Ambitious ☐ ☐ ☐ ☐ ☐ ☐ ☐
Attractive body ☐ ☐ ☐ ☐ ☐ ☐ ☐
Attractive face ☐ ☐ ☐ ☐ ☐ ☐ ☐
Desires children ☐ ☐ ☐ ☐ ☐ ☐ ☐
Enthusiastic about ☐ ☐ ☐ ☐ ☐ ☐ ☐ sex
Faithful to partners ☐ ☐ ☐ ☐ ☐ ☐ ☐
Financially secure ☐ ☐ ☐ ☐ ☐ ☐ ☐
Generous ☐ ☐ ☐ ☐ ☐ ☐ ☐
Good sense of ☐ ☐ ☐ ☐ ☐ ☐ ☐ humour
Healthy ☐ ☐ ☐ ☐ ☐ ☐ ☐
Independent ☐ ☐ ☐ ☐ ☐ ☐ ☐
Intelligent ☐ ☐ ☐ ☐ ☐ ☐ ☐
Kind and ☐ ☐ ☐ ☐ ☐ ☐ ☐ understanding
197 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Loyal ☐ ☐ ☐ ☐ ☐ ☐ ☐
Responsible ☐ ☐ ☐ ☐ ☐ ☐ ☐
Sociable ☐ ☐ ☐ ☐ ☐ ☐ ☐
Emotionally stable ☐ ☐ ☐ ☐ ☐ ☐ ☐
198 APPENDICES
A.2 Mating Intelligence Scale
From Geher and Kaufman (2007)
Male version
The following questions ask you about your opinions about yourself as a potential romantic partner. You are required to read the statements, and think about whether or not they describe you in general. Mark with T (true) or F (false). Please answer honestly and to the best of your ability.
1. I think most women just like me as a friend.
2. I have slept with many beautiful women.
3. I’m pretty good at knowing if a woman is attracted to me.
4. I’m definitely not the best at taking care of kids.
5. I’m good at saying the right things to women I flirt with.
6. I haven’t had as many sexual partners compared with other guys I know (who are my age).
7. I have a difficult time expressing complex ideas to others.
8. I am good at picking up signals of interest from women.
9. I’m definitely near the top of the status totem pole in my social circles.
10. I doubt that I’ll ever be a huge financial success.
11. If I wanted to, I could convince a woman that I’m really a prince from some little-known European country.
12. Honestly, I don’t get women at all.
13. Women tend to flirt with me pretty regularly.
14. If a woman doesn’t seem interested in me, I figure she doesn’t know what she’s missing.
15. Women definitely find me attractive.
16. I’ve dated many intelligent women.
17. People tell me that I have a great sense of humour.
18. When I lie to women, I always get caught!
199 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
19. I am usually wrong about who is interested in me romantically.
20. It’s hard for me to get women to see my virtues.
21. At parties, I tend to tell stories that catch the attention of women.
22. I’m not very talented in the arts.
23. I can attract women, but they rarely end up interested in me sexually.
24. When a woman smiles at me, I assume she’s just being friendly.
Female version
The following questions ask you about your opinions about yourself as a potential romantic partner. You are required to read the statements, and think about whether or not they describe you in general. Mark with T (true) or F (false). Please answer honestly and to the best of your ability.
1. I can tell when a man is being genuine and sincere in his affections towards me.
2. I doubt I could ever pull off cheating on my partner.
3. I look younger than most women my age.
4. When a guy doesn’t seem interested in me, I take it personally and assume something is wrong with me.
5. Good looking guys never seem into me.
6. I have a sense of style and wear clothes that make me look sexy.
7. I attract many wealthy, successful men.
8. Honestly, I don’t think I understand men at all!
9. With me, a guy gets what he sees – no pretences here.
10. If I wanted to make my current guy jealous, I could easily get the attention of other guys.
11. Men don’t tend to be interested in my mind.
12. I’m definitely more creative than most people.
13. I hardly ever know when a guy likes me romantically.
14. I laugh a lot at men’s jokes.
15. If a guy doesn’t want to date me, I figure he doesn’t know what he’s missing!
200 APPENDICES
16. I am not very artistic.
17. My current boyfriend spends of money on material items for me (such as jewellery).
18. I am usually right on the money about a man’s intentions toward me.
19. I really don’t have a great body compared with other women I know.
20. Intelligent guys never seem interested in dating me.
21. I believe that most men are actually more interested in long-term relationships than they are given credit for.
22. Most guys who are nice to me are just trying to get in my pants.
23. When it comes down to it, I think most men want to get married and have children.
24. If I have sex with a man too soon, I know he will leave me.
Scoring
Male version: 1 point for every TRUE answer to questions 2, 3, 5, 8, 9, 11, 13, 14, 15, 16, 17, and 21. 1 point for every FALSE answer to all other questions. Sum scores.
Female version: 1 point for every TRUE answer to questions 1, 3, 6, 7, 10, 12, 14, 15, 17, 18, 22, and 24. 1 point for every FALSE answer to all other questions. Sum scores.
Appendix B - Article published in Evolution, Mind and Behaviour, 2015 (Chapter 2)
*Article removed due to copyright restrictions*
201 APPENDICES
Appendix C – Stimulus Sets for Eye-Tracking Task (Chapter 3).
Stimulus Set 1
Conservative
219 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Party/Revealing
220 APPENDICES
Stimulus Set 2
Conservative
221 INDIVIDUAL DIFFERENCES IN MATING STRATEGIES
Party/Revealing
222 APPENDICES
Appendix D – Vector Outcomes for Principle Component Analysis (Chapter 7).
223