Archives of Sexual Behavior

, Volume 41, Issue 2, pp 467–476 | Cite as

The Partner-Specific Sexual Liking and Sexual Wanting Scale: Psychometric Properties

Original Paper


Inspired by research showing that wanting (one’s motivation to engage in an activity) often diverges from liking (one’s enjoyment of the activity), this article details the development and validation of a new measure to examine the distinction between sexual wanting and liking within a relationship: the partner-specific sexual liking and wanting (PSSLW) scale. In Study 1, participants (N = 1145; 63% female) completed items intended to measure PSSLW. Factor analysis supported a 15-item two-factor solution that explained 64.7% of the total variance. The partner-specific sexual liking (PSSL) subscale (Cronbach’s α = .93) and the partner-specific sexual wanting (PSSW) subscale (Cronbach’s α = .87) showed good internal validity. Test–retest reliability on a subsample (n = 30) was high (Pearson’s r = .75). In Study 2, participants (N = 67; 71.6% female) completed the PSSLW scale and additional measures of satisfaction and desire. Both scales displayed satisfactory discriminant and convergent validity. In Study 3, participants (N = 2589; 45.3% female) completed the PSSLW scale and answered questions about sexual behavior within their relationships. The two subscales were distinctly correlated with measures of self-reported behavior. Moreover, confirmatory factor analysis (CFA) yielded a good-fit two-factor model, where the Comparative Fit Index (CFI) = .97, Tucker Lewis Index (TLI) = .96, and root mean square error of approximation (RMSEA) = .06. Data from these three studies suggested that PSSLW were distinct, measurable, and valid constructs that have the potential to enrich future studies of sexual experience and behavior within sexual partnerships.


Sexual liking Sexual wanting Intimate relationships Scale development 


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Social and Decision SciencesCarnegie Mellon UniversityPittsburghUSA

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