Menstrual cycle-driven vs noncyclical daily changes in sexual desire.

BACKGROUND: Past research on the association between sexual desire and the menstrual cycle has provided inconclusive results and has not considered the potential influence of psychological and physical changes that are frequently associated with the menstrual cycle. AIM: To test the strength of association between the menstrual cycle (and associated symptoms) and changes in sexual desire. METHODS: Prospective daily reports across 2 full menstrual cycles (2 months) from a sample of female university students (n = 213), were analysed. Analyses tested for average effects of the menstrual cycle on sexual desire, individual differences in these effects, and cyclical and noncyclical associations between sexual desire and the 9 menstrual cycle-related changes. Note that data presented in the current article come from a larger study from which other reports have been published. OUTCOMES: Target variables were (1) daily change in sexual desire and (2) daily reports of 5 psychological changes and 4 physical changes that are commonly associated with the menstrual cycle. RESULTS: Results showed that when considering average effects across participants, the menstrual cycle was associated with a small midcycle increase in sexual desire. However, multilevel analyses showed large individual differences in how the menstrual cycle influences sexual desire. Specifically, some participants showed a midcycle increase, others a perimenstrual increase, and others no change across the menstrual cycle. Moreover, results demonstrated that psychological changes were more important for predicting sexual desire as compared with physical changes. CLINICAL IMPLICATIONS: These results suggest that daily measurement of sexual desire across multiple menstrual cycles may be an important tool in the assessment of sexual desire among some females. STRENGTHS AND LIMITATIONS: Strengths of this study are the daily assessment of sexual desire and all symptoms for 2 menstrual cycles and multilevel analyses that allow the study of individual differences. Limitations include limited measurement of sexual desire based on only 2 questions and the lack of measures of relationship status and sexual orientation. CONCLUSION: Emphasis is placed on the need to apply more rigorous research methods and to abandon simplistic average-effects models that are based on outdated theories and stereotypes.

Sexual Desire in Women: Paradoxical and Nonlinear Associations with Anxiety and Depressed Mood.

The aim of the present study was to expand previous findings regarding paradoxical effects of negative mood on sexual desire. This was done by considering the full range of depressed mood and anxiety symptoms and using methods that are unaffected by recall bias and that don't require participants to infer causal associations between their mood and sexual desire. A convenience sample of 213 university students completed daily questionnaires for approximately two months. Multilevel random-effects models were used to estimate average effects for the entire sample and to test for variability across participants in the associations between negative mood and sexual desire, controlling also for potential influences of the menstrual cycle. Previous findings showing that some women report decreased sexual desire and others increased sexual desire when depressed or anxious were confirmed. More importantly, for both depressed mood and anxiety, results demonstrated the presence of within-person paradoxical associations, whereby there were some women for whom both low and high levels of negative mood were associated with the same change (an increase or a decrease) in sexual desire. Related to these diverse response patterns, paradoxical associations between negative mood and sexual desire were also present at low levels of negative mood. The discussion underlines the importance of considering individual variability and multifactorial nonlinear models when studying sexual desire.

Affective neuroscience: applications for sexual medicine research and clinical practice.

INTRODUCTION: Affective neuroscience is the study of the brain substrates of emotional, embodied experiences. Affective neuroscience theory (ANT) is based on experimental evidence that all mammals are hardwired with 7 primary subcortical emotional operating systems, or "core emotions," that have overlapping but distinct circuits buried in the deep, ancient parts of the brain. Imbalances in the 7 core emotions can affect multiple aspects of the individual's psychosocial well-being (eg, depression, anxiety, substance abuse). Here, we propose that core emotions can also influence sexual function and, specifically, that imbalances in core emotions are the bridge connecting psychiatric symptoms (eg, anhedonia) to sexual dysfunction (eg, anorgasmia). OBJECTIVES: In this targeted review and commentary, we outline potential connections between ANT and sexual medicine research and clinical practice. We summarize ANT by defining the 3-level BrainMind and core emotions; examining how they relate to personality, behavior, and mental health; and determining the implications for sexual health research and clinical practice. METHODS: A targeted literature review was conducted. Case studies were adapted from client files and clinician interviews and then anonymized. RESULTS: We propose a novel organizational schema for implementing affective balance therapies for sexual dysfunction, which integrate psychoeducational, somatic, and cognitive therapeutic approaches under the ANT framework. We provide 3 patient case studies (anorgasmia, hypersexuality, spinal cord injury) outlining the implementation of this approach and patient outcomes. CONCLUSION: ANT has practical translational applications in sexual health research and clinical practice. By integrating our understanding of the role of core emotions in human sexuality, clinicians can better tailor treatments to address sexual dysfunction.

When the brain turns on with sexual desire: fMRI findings, issues, and future directions.

INTRODUCTION: More than 2 decades of neuroimaging research has sought to uncover the neurologic basis of sexual desire. However, the lack of a clear conceptual distinction between sexual desire and sexual arousal or even a broadly accepted definition of sexual desire has led to confusion in the literature regarding brain areas uniquely associated with sexual desire. OBJECTIVES: (1) To critically review the neuroimaging literature that seeks to identify brain areas and networks involved in sexual desire; (2) to identify and discuss those brain areas and potential networks that are most promising for providing insights to sexual desire; and (3) to offer recommendations for future studies. METHODS: Existing meta-analyses were used as a starting point to identify relevant neuroimaging studies on sexual desire, arousal, and love. This base was then expanded via Google Scholar and forward citation tracking of already identified studies. RESULTS: Brain areas that are commonly associated with sexual desire and arousal include the amygdala, hypothalamus, dorsal and ventral striatum, anterior cingulate, insula, and prefrontal and orbitofrontal cortex. However, because the same basic paradigm has been used to study sexual desire and arousal, unambiguous conclusions regarding areas uniquely involved in sexual desire cannot be drawn. Moreover, the lack of connectivity analyses and a failure to acknowledge negative BOLD (blood-oxygen level dependent) significantly limit conclusions on the neural basis of sexual desire. CONCLUSION: Five recommendations are made. First, stimulus types (ie, erotic vs sexually explicit) should be selected by the meaningful theoretical conceptualization of the constructs of interest. Second, participants should be provided with definitions of sexual desire, mental sexual arousal, and perceived genital sexual arousal, so they can choose which terms best describe their experience. Third, event-related designs should be used with caution when investigating sexual desire. Fourth, time series analyses should be used to identify both positive and negative BOLD. Fifth, connectivity analyses should be performed to identify brain networks.