A Psychometric Study of a Trait and State Assessment of Sexual Pleasure - The Amsterdam Sexual Pleasure Inventory

We studied the Amsterdam Sexual Pleasure Inventory's (1.0) psychometric properties. The ASPI, a revised self-report battery designed to measure domains of state and trait sexual pleasure in diverse gender, sex, and relationship populations, is based on a recently proposed conceptual framework of sexual pleasure. We collected quantitative (n = 1371) and qualitative data (n = 637) using a cross-sectional multi-method design targeting the general (German-speaking) population. After pre-processing, we conducted analyses on a sample of n = 706 participants. The theory-based 5-factor exploratory structural equation model and the principal component analyses of the two general exploratory index-scales showed good and acceptable structural validity evidence respectively. Measurement invariance was confirmed separately for male and female participants and for those with sexually functional-scoring and dysfunctional-scoring levels. Coefficient omega indicated that all scales, except those of one facet, showed acceptable to very good internal consistency. The ASPI's convergent and discriminant associations with sexological and psychological constructs demonstrated good overall construct validity. Participants understood the items as intended and felt that the ASPI covered relevant facets of sexual pleasure. The ASPI might help understand how individuals differ in experiencing sexual pleasure and how different contexts enable some people to experience pleasure while disadvantaging others.

Cyberphysical Human Sexual Behavior Acquisition System (SeBA): Development and Implementation Study in China

Background

Sexual health is one of the principal components of human well-being. Traditional methods for observing human sexual behavior typically adopt manual intervention approaches (eg, interviews). However, the data obtained by such traditional approaches suffer from intrinsic bias and limited sample sizes. Sexual behavioral data that are more reflective of the actual situation can be collected by equipping sex toys with sensors.

Objective

To address the limitations of traditional human sexual behavior data observation methods, a novel cyberphysical system is proposed to capture natural human sexual behavior data in China at the nationwide level.

Methods

A cyberphysical human sexual behavior acquisition system (SeBA) was designed and implemented. SeBA jointly utilizes state of the art information and communication technologies such as smart sex toys, smartphones, and mobile social networks. Smart sex toys enable objective collection of data on human sexual behavior, while the mobile social network provides the possibility of partnered sex in a cyberphysical manner. The objectives and function settings are discussed, and the overall framework of the system architecture is presented.

Results

Operation and privacy policies are proposed and the technical solution of SeBA is described. The effectiveness of SeBA was verified based on analysis of users’ human sexual behavior data collected from January 2016 to June 2017. A total of 103,424 solo sexual behaviors were recorded involving 13,047 users, and 61,007 partnered sexual behaviors from 7,140 users were observed. The proportions of males and females in the solo and partnered sex groups were fairly consistent with recent statistics on unmarried individuals in China. We also found that only a small portion of individuals provided information on at least one other attribute besides the required input of gender, such as age, height, location, job, sex preferences, purposes, and interests.

Conclusions

To the best of our knowledge, this is the first study to analyze objective human sexual behavior data at the nationwide level. Although the data are restricted to China, this study can provide insight for further research on human sexual behavior based on the huge amount of data available from wireless smart sex toys worldwide. It is anticipated that findings from such objective big data analyses can help deepen our understanding of sexual behavior, as well as improve sexual health and sexual wellness.