Sunday, October 30, 2022

Modeling Female Sexual Desire

Modeling Female Sexual Desire: An Overview and Commentary. Abigail L. Kohut-Jackson, Johnathan M. Borland and Robert L. Meisel. In Sexual Disorders and Dysfunctions, Ed. Dhastagir Sultan Sheriff, October 25th, 2022.

Abstract: Hypoactive sexual desire disorder (HSDD) in women is a condition of low sexual desire that develops over time. Sexual desire normally diminishes over long-term relationships, but is also negatively affected by a demanding lifestyle, poor self-esteem and body image, and loss of intimacy in a relationship. HSDD elevates to a disorder when it is a concern for the woman, arising from conflict with a partner who is interested in a greater frequency of sexual interaction. Two drugs have been marketed (Addyi and Vyleesi) to treat HSDD. Neither drug was originally developed for this purpose, nor is either drug particularly effective. The lack of rational development of drugs to treat sexual disorders in women is due to the mistaken belief that components of female sexuality, such as sexual desire, cannot be effectively modeled in animals. To the contrary, sexual interest, desire, arousal, and reward are measurable aspects of sexual behavior in female rodents. Going forward, basic research using these pre-clinical models should be the starting point for drug development. At the same time, it is not clear that drug development represents the primary therapeutic approach to the problem, with behavioral therapies providing good options for first line of treatments for HSDD.

Keywords: sexual arousalsexual interestsexual rewardhypoactive sexual desire disorderAddyiVyleesianimal modelsmesolimbic systemnucleus accumbensdopamineglutamatemelanocortin receptors

6. Commentary

Nappi [7] presented an expert opinion on the relative lack of drugs to treat female sexual dysfunction. She highlighted the wide range of causes for sexual dysfunction in women, as opposed to simply erectile dysfunction in men. She noted that we still have an incomplete understanding of a woman’s sexuality, which is a prerequisite to developing treatments. She also pointed out that female sexual dysfunction is not a life-threatening clinical problem, so that it is important to balance the clinical effectiveness of drugs with the drug’s safety for the women taking them. Finally, Nappi [7] was concerned with drugs that needed to be taken chronically (e.g., Addyi), and hoped that on-demand medications (e.g., Vyleesi) could be developed. Nappi’s commentary is still very current and meaningful, and rational drug development (in her view) will only be achieved through the cooperative partnership of sexual experts, pharmaceutical companies and medical agencies [7].

6.1 A rational approach to drug development

In Section 4 we described how Addyi and Vyleesi went to clinical trials with remarkably little preclinical data supporting their effects on sexual behavior in animal models. If developing drugs to treat sexual dysfunction in women is an important endeavor, the starting point has to be investment in basic research in both the public and pharmaceutical sectors. This research should be designed to take advantage of current animal models (and develop new animal models [81]) to identify potential molecular targets for therapeutics. This is how drug development begins for essentially all diseases and is only emphasized here because this message clearly was lost in the development and marketing of drugs for HSDD in women.

6.2 Pathologizing the normal

Basson et al. [9] developed a comprehensive model of female sexuality that emphasized the complexity of a woman’s sexual response. At the same time that this model is a valuable contribution to understanding female sexuality, it also highlights the individual variability in sexual responses among women, making it difficult to define what a normal response pattern is. If we cannot define a normal sexual response, then how do we define sexual dysfunction in women [82, 83, 84]. Basson et al. [82] disagree with DSM criteria that quantify numbers of sexual fantasies or whether a woman initiates sexual activity as determinants of sexual dysfunction. They assert that few or no sexual fantasies are not a pathology, nor is it pathological if a woman does not initiate sexual activity.

Based on earlier arguments, Meixel et al. [84] lay out a historical account of the many examples of the drug industry’s marketing strategy of “condition branding”. With condition branding, the drug company creates a medical condition to support the development of a drug. In the example of Addyi, HSDD was elevated in significance as a treatable source of distress as part of the rebranding of the drug to address the disparity in the treatment of sexual dysfunction in men and women. It is disturbing that drug-company supported continuing medical education (CME) modules were developed to “educate” clinicians about this disorder. Meixel et al. [84] note (p. 860):

“Specific marketing messages that we identified within the CME modules included the following:

Hypoactive sexual desire disorder is very common and underdiagnosed.

Hypoactive sexual desire disorder can have a profound effect on quality of life.

Women may not be aware that they are sick or distressed.

Hypoactive sexual desire disorder and distress can have other names.

Clinicians should initiate conversation with their patients about their sexual health.

Clinicians find it difficult to discuss their patients’ sexual concerns and lack training and confidence in the diagnosis of sexual problems.

Clinicians need tools and resources to help them diagnose hypoactive sexual desire disorder.

Simple tools, including the decreased sexual desire screener (DSDS) and Female Sexual Function Index (FSFI) can assist clinicians in diagnosing hypoactive sexual desire disorder.

A major barrier to clinicians talking about hypoactive sexual desire disorder/female sexual dysfunction is the lack of medications.

It is problematic that there are medicines available to treat sexual problems for men but not women.”

Key elements in the continuing education modules to be noted here are that the lack (at the time) of medications for HSDD was an impediment for physicians to have discussions about sexual desire with their patients and that women may have HSDD even if they are unaware of it.

6.3 Therapeutic approaches

A starting point for therapy may lie in reassuring women that their sexual feelings are not abnormal and are shared by many other women [82]. This does not alleviate tensions and conflict in a relationship, but can more effectively set the stage for other therapeutic approaches. For example, changing a women’s view of herself can aid in communication with her partner about her sexuality to alleviate interpersonal conflicts [82]. Knowing that her feelings are normal and shared will boost self-esteem and relieve personal insecurities, both of which are barriers to promoting relationship satisfaction and feeling sexually desirable. This is clearly a simplistic approach that in isolation will not be sufficient for most women [85]. Still, this is an important component of any therapeutic plan.

Given that fatigue is a key factor underlying low sexual desire in women, approaches to reduce lifestyle stress and fatigue may be helpful. Mindfulness strategies can be helpful in this regard [86, 87, 88, 89] and have the advantage of being easy to apply and are inexpensive. Presumably other lifestyle approaches may also be beneficial when HSDD results from these types of life events.

Cognitive processes impact HSDD when women view their own behavior, rather than relationship issues, as central to their levels of sexual desire. A rather thorough review [90] supports a role of cognitive behavioral therapies in treating women with HSDD. The goals of these approaches are straightforward, aiming to increasing the rewarding experiences for women and improve relationships through cognitive restructuring and communication. As with mindfulness strategies, cognitive behavioral therapy can be conducted through online training as well as in person.

Drugs should be a last line of treatment [2, 91], and used perhaps in conjunction with behavioral therapies. The worry with drug therapies is that they necessarily carry side effects that vary in severity. This is unavoidable with any compound that affects neurotransmission, as there will be direct and indirect effects on chemical transmission that are spread throughout the central nervous system, beyond the specific circuits targeting the behaviors in question [36].

Today’s Older Adults Are Cognitively Fitter Than Older Adults Were 20 Years Ago, but When and How They Decline Is No Different Than in the Past

Today’s Older Adults Are Cognitively Fitter Than Older Adults Were 20 Years Ago, but When and How They Decline Is No Different Than in the Past. Denis Gerstorf et al. Psychological Science, October 25, 2022.

Abstract: History-graded increases in older adults’ levels of cognitive performance are well documented, but little is known about historical shifts in within-person change: cognitive decline and onset of decline. We combined harmonized perceptual-motor speed data from independent samples recruited in 1990 and 2010 to obtain 2,008 age-matched longitudinal observations (M = 78 years, 50% women) from 228 participants in the Berlin Aging Study (BASE) and 583 participants in the Berlin Aging Study II (BASE-II). We used nonlinear growth models that orthogonalized within- and between-person age effects and controlled for retest effects. At age 78, the later-born BASE-II cohort substantially outperformed the earlier-born BASE cohort (d = 1.20; 25 years of age difference). Age trajectories, however, were parallel, and there was no evidence of cohort differences in the amount or rate of decline and the onset of decline. Cognitive functioning has shifted to higher levels, but cognitive decline in old age appears to proceed similarly as it did two decades ago.


Our findings indicate that later-born older Berliners tested in the 2010s outperformed their earlier-born age peers tested in the 1990s. Contrary to our hypotheses, results showed that later-born older adults did not exhibit shallower declines on perceptual-motor speed or a later onset of decline. The later born cohort’s cognitive performance was shifted upward from the earlier-born cohort’s, but trajectories of cognitive aging were parallel.

Historical change in cognitive performance

Consistent with the Flynn effect (Pietschnig & Voracek, 2015), results from our carefully matched longitudinal data obtained from same-aged older adults tested two decades apart provide more evidence of historical change in levels of performance. The effect size (d = 1.20) is striking and even larger than that obtained in our earlier time-lagged cross-sectional analysis of a subset of participants (Gerstorf et al., 2015d = 0.85). This constitutes one more set of evidence that cultural changes over the last 30 years, including better access to individual resources (e.g., quantity and quality of education) and innovations in science and technology (e.g., advances in medicine and nutrition; Drewelies et al., 2019), have contributed to improved cognitive performance in old age. Future work should detail how the many different mechanisms that drive improvements in unique and specific resource constellations can further improve cognitive functioning (and productivity) of older adults.

Are old-age cognitive declines today shallower or postponed to later ages?

Our results parallel those of studies that did not find history-graded improvements in cognitive aging trajectories (e.g., Brailean et al., 2018) but differ from studies that had found such improvements (e.g., Dodge et al., 2014). Beyond similarities in the calendar years participants were born and tested, the discrepant findings may result from country-level differences in health care and differences in the studies’ measurement and analysis procedures.
In the 1990s, studies had documented that elevated blood pressure in midlife (rather than old age) is predictive of steeper cognitive declines in old age (Launer et al., 1995). Since then, widespread prescription and use of effective anti-hypertensive medication may have weakened those links. However, implementation in Germany occurred about a decade later than in the United States and other nations (Wolf-Maier et al., 2003). Consequently, our later-born older Berliners may have already been too old to have benefitted from widespread changes in delivery of health care. Back when this generation of older adults was in midlife, blood pressure treatment had not yet improved (Koenig et al., 2018). Going forward, cross-national studies can be used to test hypotheses about long-latency treatment effects of midlife blood pressure for cognitive decline in old age.
Interestingly, studies that reported cohort differences in rates of cognitive decline either did not include perceptual speed measures (Dodge et al., 2017 and Gerstorf et al., 2011: reasoning, verbal meaning, and memory), did not find cohort effects on perceptual speed measures (but on verbal fluency and working memory; Grasset et al., 2018), or found that cohort differences in perceptual speed measures were smaller than for other measures (executive functions; Dodge et al., 2014). Although measures of perceptual speed capture age-related declines well, they may not be very sensitive to history-graded changes in decline. More systematic charting of how cohort differences manifest across a wider set of aging-sensitive (e.g., memory) and more aging-resilient (e.g., crystallized) abilities is needed.
Our analytic approach also differed from approaches used in other studies. The nonlinear growth-modeling framework allowed us to account for a variety of potential confounds. First, the observation-level age matching between BASE and BASE-II samples drawn from the same underlying population provided a strong foundation for testing differences between same-age observations obtained from different cohorts. Second, we modeled and accounted for retest effects that often emerge with repeated test taking. Third, our model explicitly separated between-person from within-person age effects (age gradients vs. intraindividual change), allowing for more precise testing of hypotheses about history-graded shifts in cognitive aging—a distinctly intraindividual process.
To our knowledge, this is the first study to directly test cohort differences in the age of onset of cognitive decline. Contrary to the cognitive-reserve hypothesis, results showed no evidence for a shift in the onset of decline. However, this finding is consistent with both the preserved-differentiation perspective (Salthouse, 2006), by which level differences established in early life are maintained and carried forward into old age, and recent meta-analyses showing that differences in education have substantial effects on levels of cognitive functioning but null effects on rates of cognitive aging (Lövdén et al., 2020) or brain aging (Nyberg et al., 2021). It seems that history-graded improvements resulting from early-life education, cognitive stimulation, and health care persist into old age, but not because aging processes have been any kinder.

Limitations and future directions

Several limitations in our design and sample must also be noted. A time window of two decades may suffice to identify historical change in levels of perceptual-motor speed but may not be long enough to identify historical change in key features of cognitive aging trajectories. Further, because our assessments were obtained only in old age, we were unable to disentangle late-life processes from those unfolding during early life and mid-life. With the Flynn effect reversing among young men (Bratsberg & Rogeberg, 2018), future research should systematically examine how history-graded changes may proceed differentially throughout life.
Participants were drawn from one geographical region and represent a positively selected population segment. One key question is whether our findings apply to resource-poor population segments. Conceptual perspectives on manufactured survival (Olshansky & Carnes, 2019) suggest that some older adults today carry disease burdens longer than did older adults in the past. Future research should carefully examine whether cohort differences in decline emerge in more diverse samples and are moderated by access to resources.