Sonia Milani, University of British Columbia
Full Transcript:
Sonia Milani :
My name is Sonia Milani. I’m actually not in my PhD yet. I’m actually just still, finished my first year of my master’s in clinical psych at UBC, but we’re getting there. So I’m here today to talk to you about validating MouseView for sex research. So thank you to Tom, Edwin and Alex for validating this so that we can use it as a tool.
Sonia Milani :
And so in today’s talk, I will start by providing some background information to explain the role that attention plays in sexual response and review sexuality related research that I’ve used eye tracking methodology to examine attention. I will then dive into describing the current study and go over the methods and results. I will conclude with a discussion of what our findings suggest and as part of that, I will discuss our future plans for this line of research.
Sonia Milani :
So when we talk about sexual response, we are referring to an emotional state that is made up of physiological responses, such as genital sexual arousal, as well as subjective response, such as subjective sexual arousal or excitement. Sexual function involves moving through the different stages of sexual response without difficulty. So going through sexual desire, sexual arousal and orgasm. Not surprisingly, sexual function is an important aspect of quality of life. And studies have shown that sexual function is positively correlated with mental health, with physical health, with sexual and relationship satisfaction, as well as overall happiness.
Sonia Milani :
Theoretical models situate attention within sexual interactions as a key component of sexual response. This is a diagram of the emotion motivational model of sexual response. And as you can see, emotion acts early on and it’s involved in both the activation and maintenance of sexual response. This model predicts that focusing attention towards sexual cues. So for example, focusing attention on an attractive partner or sexual stimuli, this facilitates and increases sexual response, whereas distractions that divert attention away from such sexual cues, this inhibits sexual response and decreases that.
Sonia Milani :
Over the last 15 years, sex researchers have used eye tracking methodology to examine visual attention patterns given that visual attention is a central component of most sexual experiences. We see, we like, we get aroused. Specifically, eye tracking has been used to assess differences in the attentional processing of sexual and non-sexual cues. So really showing the salience of sexual cues. Studies have looked at gendered patterns of visual attention. We’ve examined attention as an index of sexual interest and attraction. And more recently eye tracking has been used to investigate attentional biases, underlying sexual function. So looking at differences in visual attention among clinical populations, experiencing sexual dysfunction and healthy controls. And this is just to really demonstrate the utility of eye tracking insects research. But for the purposes of this presentation, I will briefly go over findings from studies examining gender differences, as it is the most relevant for the current study.
Sonia Milani :
For a very long time, researchers have been puzzled by a gender difference in patterns of sexual response observed in the laboratory. Studies have consistently revealed that heterosexual men show gender specificity. And what this means is that they produce a greater magnitude of physiological sexual response to preferred female sexual cues. Heterosexual woman, on the other hand, show gender non-specific patterns, such that they exhibit a similar magnitude of physiological sexual response to both preferred male and non-preferred female cues. Now, given that attention is theorized to be important for sexual response. Some researchers have been interested in testing whether or not visual attention is a mechanism that might explain these gender differences. So in previous eye tracking studies and unlike Alex, I actually am using stimuli and not emojis. So bear with me. You’re going to see some nude images here.
Sonia Milani :
When participants are shown single images of sexual male and female targets separately, the results indicate that heterosexual men look more and look longer at their preferred female models. And this is a pattern that is consistent with their self-reported attraction, as well as sexual response patterns reported above. Heterosexual women distribute their visual attention more evenly and look similarly at preferred male and non-preferred female models. Women’s visual attention patterns appear to be consistent again with the gender non-specific sexual response patterns described above. Notably, these patterns of visual attention have been found to be strongly correlated with self-reported sexual attraction ratings of the models and so models that were male and female models that were rated as more sexually attractive were looked at more and these effects were much stronger in men.
Sonia Milani :
And although eye tracking has shed important light on our understanding of visual attention patterns and sex research, this method is not without limitations, some of which Alex has already described. But specific limitations for sex research include a lack of ecological validity. Given that we are studying something that is super personal and private, people typically view sexual stimuli in private. And so doing so in a laboratory setting could potentially be uncomfortable and unnatural for people. And this could influence results. As well, the self selection of participants who volunteer for laboratory based sexual research may impact the generalizability given that not everyone will volunteer to come to do a in laboratory based sexual research study.
Sonia Milani :
So to overcome these limitations of lab based sexuality research using eye tracking, we set out to start the validation process of MouseView for sex research and conducted the current study. So the goals of the study were to examine whether MouseView would reveal the gender patterns and the specificity of arousal that has been found using other experimental methods. And we also wanted to find out whether MouseViewing of sexual images would be associated with self-reported sexual arousal ratings. So do people look longer at what they like?
Sonia Milani :
In terms of hypothesis, for our first research question, we predicted that MouseView will reveal gender specificity for MouseViewing and sexual arousal, meaning that men will show gender specific patterns and women will show gender non-specific patterns. And for the associations between MouseViewing and sexual arousal, we predicted that MouseViewing will be associated with subjective sexual arousal ratings.
Sonia Milani :
In terms of methods, we recruited a total of 226 undergraduate students through the University of British Columbia human subject pool. This included 166 women, 58 men, and one non-binary individual. Average age of our group was 20.5 years old and we had a diverse sample in terms of ethnicity. Using a direct link to the online experiment, participants first completed a sexual arousal rating task. They were provided with clear images of each male and female model, and they were asked to report how sexually aroused the image makes them feel. And this was done on a scale of 0 to 10. After the sexual arousal writing task participants completed the MouseViewing task. We used Gorilla as the experimental platform. In each trial, we presented participants with two images, one sexual image of either the male or female model that was paired with one neutral image depicting a random object. Participants use their mouse to move aperture, which is the clear circle to view the images.
Sonia Milani :
And here is a quick demo that I hope works. So each trial started with a central fixation cross. Once participants click that they got to view the two images as they wish. And each trial lasted eight seconds.
Sonia Milani :
So to examine hypothesis one, we looked at the gender specificity of sexual arousal, and we found that men as indicated by the orange lines and these graphs, men showed greater specificity in their MouseViewing of the images. And so for MouseViewing, that’s the graph on the left and then for subjective sexual arousal, that’s the graph on the right. So we see that mental, a very pronounced preference for the female model compared to the male model. And this is true for both the MouseView, as well as a subject of sexual arousal ratings. And so this is otherwise known as gender specific response patterns. Heterosexual women, as indicated by the blue lines in the graph show a very subtle preference for the male model. And so we can see gender non-specific patterns in women’s arousal ratings, as well as their MouseViewing.
Sonia Milani :
And then for hypothesis two, looking at the associations between MouseViewing and self-reported sexual arousal ratings. When examining the full sample, we see a robust association between subjective sexual arousal, which is found on the X axis and MouseViewing, which is found on the Y axis for both the female and the male model. So the female model graph is on the left male model is on the right. So across everyone in our sample, people look more at the stimuli they rate as more arousing. And these strong associations are observed when we look at each gender separately. So for men in our sample, we see the same positive correlations for both male and female models. And as you can see on the graph on the right for men viewing and rating male models, most data appear on the lower end of the scale. So low sexual arousal rating and less MouseViewing. And this is expected given our mostly heterosexual identifying sample.
Sonia Milani :
And similarly for women, we saw positive correlations for both male and female models. And as you can see, the magnitude of the correlations is slightly lower than mens. And this pattern again is consistent with the gendered patterns that are observed using other methods where the observed effects are much stronger among men than women.
Sonia Milani :
And so what does this all mean? Our data suggests that MouseViewing is related to sexual arousal. Our supported hypotheses are the replicated previous findings from studies using other methodologies, such as eye tracking and physiological measures. In terms of implications, online experimental methods applied to the study of sex, and obviously our research more broadly, offer an affordable and convenient alternative to in lab experiments, they increase our ability to recruit larger and more diverse samples. And this is particularly important in sex research because we really want to tap into populations with different sexual orientations and gender diverse populations as well. Additional benefits include levels of realism, it’ll hopefully be more comfortable and realistic for participants be viewing sexual stimuli in the comfort of their own home rather than in a laboratory setting.
Sonia Milani :
And our next steps for this line of research is to more comprehensively validate MouseView for sex research and to do so, we will compare attentional processing of sexual versus non-sexual cues to replicate eye tracking findings that demonstrate the salience of sexual stimuli. And we will also replicate forced attention paradigms that have been used for preferred and non-preferred sexual cues where participants are presented with a male and female model simultaneously. We also plan to conduct an in laboratory eye tracking, COVID permitting, to look at MouseView and eye tracking convergence, and we are going to be doing this within samples. So the same participants that participate in MouseView will abe invited to participate in an in lab eye tracking as well. And we also wanted to examine different masks in MouseView. So we want to use the blurred overlays that I showed earlier in the demo, but we also want to examine what the data might look like if we were to flash the images clearly for one second to participants before the blurred overlay, just to see if one iteration of MouseView is more closely matched with eye tracking data.
Sonia Milani :
Thank you for listening. I’m open to some questions.