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Development and validation of the Male Post-coital Affect Scale for heterosexual men

Published online by Cambridge University Press:  15 February 2023

Marta Pérez ,
Jørgen Hoppe ,
Anne M. Landau Open the ORCID record for Anne M. Landau [Opens in a new window]  and
Michael Winterdahl Open the ORCID record for Michael Winterdahl [Opens in a new window]
Marta Pérez
Affiliation:
Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark
Jørgen Hoppe
Affiliation:
Retired from General Practice, Copenhagen, Denmark
Anne M. Landau
Affiliation:
Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark Department of Nuclear Medicine and PET-Centre, Aarhus University, Aarhus, Denmark
Michael Winterdahl*
Affiliation:
Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark Department of Nuclear Medicine and PET-Centre, Aarhus University, Aarhus, Denmark
*
Author for correspondence: Michael Winterdahl, Email: michael.winterdahl@clin.au.dk
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Abstract

Objective:

The aim of this study was to examine the reliability and validity of the Male Post-coital Affect Scale (MPAS), which was developed to assess positive post-coital feelings in men.

Methods:

After a pilot study, we validated our scale on a sample of American heterosexual men, who answered our questionnaire on the internet through Amazon Mechanical Turk. We tested the reliability using internal consistency. The validity was examined by assessing content, face and construct validity by testing the association between our scale, the Experience in Close Relationships Scale and other instruments.

Results:

A total of 484 volunteers were included in the study. Cronbach’s α for the scale was 0.83. Our scale was negatively correlated with attachment avoidance, r(482) = −0.36, p < 0.001) and Perceived Stress Scale, r(482) = −0.18, p < 0.001, and positively correlated with sexual satisfaction, r(482) = 0.18, p < 0.001.

Conclusion:

The MPAS is a reliable and valid tool to assess positive post-coital feelings in men.

Keywords

psychological assessmentsexual satisfactionsexual distresssexual communicationmale sexual dysfunction
Type
Original Article
Information
Acta Neuropsychiatrica , Volume 35 , Issue 4 , August 2023 , pp. 241 - 246
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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Scandinavian College of Neuropsychopharmacology

Significant outcomes

  • Large and diverse sample of participants

  • Excellent internal consistency within the questionnaire

  • Novel tool for measuring male post-coital affect

Limitations

  • Not representative of non-heterosexual men

  • Lack of relevant instrument for comparison to our instrument

  • Symptoms of post-coital dysphoria not probed

Introduction

Often perceived as the peak of the sexual experience and the desired outcome of the sex act itself (Lavie-Ajayi and Joffe, Reference Lavie-Ajayi and Joffe2009), orgasm has been defined as a transient peak sensation of intense pleasure creating an altered state of consciousness, usually inducing long-lasting feelings of languor, well-being and contentment in the participants (Levin, Reference Levin2011). Orgasms are associated with emotions that lead to bonding and intimacy (Sadock and Sadock, Reference Sadock and Sadock2008; Sewell, Reference Sewell2006), with both men and women indicating a desire to engage in affectionate behaviour such as cuddling, caressing and shared intimacy with their partner after sex (Hughes and Kruger, Reference Hughes and Kruger2011; Kruger and Hughes, Reference Kruger and Hughes2011). Furthermore, orgasm has been associated with higher sexual satisfaction and, in turn, higher relationship satisfaction (Muise et al., Reference Muise, Giang and Impett2014).

Although existing literature explores this experience (Kruger and Hughes, Reference Kruger and Hughes2011; Maczkowiack and Schweitzer, Reference Maczkowiack and Schweitzer2019; Muise et al., Reference Muise, Giang and Impett2014), we have not yet found a specific instrument that measures positive post-coital affect in men. Some articles present subjective reports to open-ended questions with responses clearly associated with emotion, participants commonly reported feeling happy after orgasm, often reporting feelings of love for their partner and increased levels of intimacy and closeness (Opperman et al., Reference Opperman, Braun, Clarke and Rogers2014). Others focus primarily on the unexpected negative emotions experienced after sex or post-coital dysphoria by both women (Schweitzer et al., Reference Schweitzer, O’Brien and Burri2015) and men (Maczkowiack and Schweitzer, Reference Maczkowiack and Schweitzer2019). Other instruments are used to measure a broader experience outside of the period immediately following orgasm, for example, the Relationship Assessment Scale (Hendrick, Reference Hendrick1988) or the Sexual Satisfaction Scale for Women (Meston and Trapnell, Reference Meston and Trapnell2005).

Here, we suggest the need for the Male Post-coital Affect Scale (MPAS) a questionnaire that reflects the participant’s positive post-orgasmic feelings, including contentment, emotional closeness, relaxation and satisfaction. The development and initial validation of the MPAS are the objective of the present study.

Methods

We developed and validated the MPAS, a novel measure of the male post-coital affect, though a three step procedure: 1) the initial work of an expert committee, phrasing relevant questions, 2) a Danish pilot study to establish feasibility and get feedback from participants and 3) a full-size English online study, aimed to establish content and criterion-related validity and to identify essential facets through exploratory factor analysis. Steps are outlined below.

Expert committee

The expert committee consisted of experienced general practitioners and a professor of sexology. Their role was to identify the most important aspects of male post-coital affect. Their aim was to create a short questionnaire as to avoid practical problems associated with lengthy questionnaires such as participant frustration, careless responding, drop-out and reluctance to take part in future studies (Donnellan et al., Reference Donnellan, Oswald, Baird and Lucas2006; Schmidt et al., Reference Schmidt, Le and Ilies2003). The committee further reviewed the pilot data, feedback from participants, translation from Danish to English and reached consensus on any discrepancies, consolidating the final questionnaire.

Pilot study

The scale was initially developed in Danish, for which 12 items were phrased to assess feelings of relaxation, satisfaction, well-being and closeness right after orgasm. A preliminary pilot test was carried out by handing out paper questionnaires to volunteers by general practitioners in Copenhagen, Denmark. Each item had to be answered on a Likert four-point scale, indicating whether participants had experienced certain feelings right after ejaculation during intercourse with a partner, ranging from (1) ‘Not at all’ to (4) ‘Yes, a lot of the time’. One hundred and forty-eight men completed the questionnaire and provided feedback on the relevance of the 12 items.

Measures

After this pilot study, we started the process of translation by native English and Danish speakers, overlooked and reviewed by our expert committee, while also adjusting some items based on the preliminary results of the pilot study and feedback of the respondents. The answer options were changed into an odd 9-point Likert Scale of frequency, giving the respondents an option to answer neutrally while also obtaining a greater range of variability in the answers. Additionally, items 10 and 11 were negatively phrased with the aim of reducing the Acquiescence Bias (where participants tend to agree with all statements) and Extreme Response Bias (where participants provide all high or all low ratings) (Wetzel et al., Reference Wetzel, Böhnke, Brown, Leong and Iliescu2016). The resulting 12 items of the MPAS are shown in Table 1.

Table 1. The heterosexual Male Post-coital Affect Scale. Instructions: Please answer the questions below, in relation to how you generally feel right after an orgasm when you have had intercourse

Each item is rated on an odd 9-point Likert scale ranging from (1) ‘Not at all’ to (9) ‘Yes, a lot of the times’

Alongside our scale, participants had to answer socio-demographic questions as well as other instruments that were administered to obtain additional information on the validity of the questionnaire: the Experiences in Close Relationships Scale-R (Fraley et al., Reference Fraley, Waller and Brennan2000) measuring attachment avoidance and anxiety (‘When I show my feelings for romantic partners, I’m afraid they will not feel the same about me’) and the Perceived Stress Scale (PSS-10) (‘In the last month, how often have you been angered because of things that were outside of your control?’) (Cohen et al., Reference Cohen, Kamarck and Mermelstein1983) which is made up of 10 items assessing experienced levels of stress over the last month. Finally, participants had to answer an item about sexual satisfaction (‘Are you satisfied with your sexual life?’).

Procedure

Participants completed an online survey using the TurkPrime interface between September and December of 2017. TurkPrime is a research platform linked with Mechanical Turk (MTurk) and supports tasks that are common to the social and behavioural sciences (Litman et al., Reference Litman, Robinson and Abberbock2017). MTurk respondents are a subset of individuals who decide to complete a given task; hence, participation is voluntary (Stewart et al., Reference Stewart, Chandler and Paolacci2017), and participants were compensated for their time. Data were collected as part of a larger study (Miani et al., Reference Miani, di Bernardo, Højgaard, Earp, Zak, Landau, Hoppe and Winterdahl2020). However, only data from heterosexual men 18 years or older living in the USA were included in the present study.

Data analysis

Data analysis was performed in Jamovi (Version 2.3). Firstly, items 10 and 11 were reverse scored since they were negatively phrased. Quantile-Quantile (QQ) plots were used to determine if the single items and the sum could be approximated by a normal distribution. To assure the MPAS’ reliability, we tested its internal consistency by calculating Cronbach’s alpha (Cronbach, Reference Cronbach1951). This estimate reflects the extent to which the questionnaire items are inter-correlated, meaning they are measuring the same construct. To test the validity, we assessed content, construct and face validity. Content validity refers to the degree to which an assessment instrument is relevant to, and representative of, the targeted construct it is designed to measure (Schultz and Whitney, Reference Schultz and Whitney2005). Construct validity refers to the extent to which a questionnaire accurately assesses a construct that is not directly observable. For this, a correlation matrix between the MPAS and other instruments was constructed. It has been suggested that correlation coefficients of 0.1 can be considered as small, 0.3 as moderate and 0.5 as large (Cohen, Reference Cohen1988). Face validity refers to the ability of an instrument to be understandable and relevant to the targeted population, which we assessed with the feedback of the respondents.

Exploratory factor analysis using the maximum likelihood method was conducted to examine sampling adequacy and factorability of the MPAS items using the Kaiser–Meyer–Olkin (KMO) test (Kaiser, Reference Kaiser1970) and Bartlett’s test (Bartlett, Reference Bartlett1951) of sphericity, which tests whether a correlation matrix is significantly different from an identity matrix. A KMO value over 0.6 and a significance level for the Bartlett’s test below 0.05 suggest that there is substantial correlation in the data and that it is suitable for factor analysis (Dziuban and Shirkey, Reference Dziuban and Shirkey1974). The number of factors was extracted based on a visual inspection of a Scree plot. Promax oblique rotation was used, allowing factors to be correlated.

Finally, the adequacy of the two-factor solution was tested via confirmatory factor analysis (CFA). Several indices of fit were used, and evaluation was based on convergence among findings (Bentler, Reference Bentler1990; Byrne, Reference Byrne2013; Tomarken and Waller, Reference Tomarken and Waller2005). First, the chi-square statistic was evaluated as the initial indicator of model fit, specifically whether the observed chi-square value was less than two times the model degrees of freedom. Second, the root mean square error of approximation (RMSEA) with 90% confidence intervals was evaluated. Established guidelines suggest that RMSEA values of less than 0.05 indicate close fit, less than 0.08 reasonable fit, and less than 0.10 mediocre fit. Finally, the goodness-of-fit index (GFI; close fit > 0.95, good fit > 0.90) and comparative fit index (adequate fit > 0.90) were examined.

Results

A total of 484 men participated in our study. All participants were 18 years or older and from the USA. The sample had an average age of 33.7 years (SD = 8.9), calculated as the mean ± the standard deviation. Demographics are summarised in Table 2.

Table 2. Demographic characteristics of participants

The MPAS showed an excellent internal consistency, with a Cronbach’s alpha of 0.83. According to the correlation values of the MPAS with other instruments, it seems that it measures emotional closeness to a greater extent than it measures other constructs, since attachment avoidance showed a moderate negative correlation with the MPAS, r(482) = −0.36, p < 0.001, compared to the smaller correlations of the MPAS with the PSS, r(482) = −0.18, p < 0.001, and sexual satisfaction, r(482) = 0.18, p < 0.001.

Exploratory factor analysis using the maximum likelihood method was conducted to examine the internal structure of the 12-item MPAS. Bartlett’s test of sphericity indicated that it was appropriate to use the factor analytic model on the items of the MPAS (χ2(66) = 2794, p < .001). The KMO measure of sampling adequacy indicated that the strength of the relationships among variables was high (KMO = 0.87); thus, it was acceptable to proceed with the analysis. A two-factor solution was extracted based on a visual inspection of the scree plot. Promax oblique rotation was used, allowing factors to be correlated. Following rotation, factor one accounted for 36.6% of variance whereas factor two only accounted for 13.4%. Each factor had a minimum of three items loading substantially (0.50 or greater) and univocally on to that factor. The few items that cross-loaded onto more than one factor were assigned to the factor that reflected their highest loading (see Table 3). The pattern of loadings reflected conceptually meaningful groupings; factor one, termed satisfaction (SA), reflected a feeling of satisfaction and happiness. The second factor, termed relaxation (RE), reflected the sensation of the body collapsing and being emptied of thoughts. Each factor had six elements and a high correlation was obtained between the two (r(482) = 0.515, p < 0.001). The main score of the Satisfaction Factor was 7.03, while the Relaxation Factor showed a main score of 5.93. On the MPAS as a whole, participants had a main score of 6.48.

Table 3. Factor loadings

’Maximum likelihood’ extraction method was used in combination with a ‘promax’ rotation. Items are sorted by loading size. The bolded values in the item list indicate which factor of the two-factor model the item belongs to.

CFA using chi-square statistic was evaluated as the initial indicator of model fit (χ2(53) = 151, p < 0.001). Although significant, it was noted that the observed chi-square value was larger than two times the model degrees of freedom. Second, RMSEA was 0.117 and GFI was 0.865, all indicating a less than adequate fit of the two-factor model.

Discussion

The aim of this study was to develop and validate the MPAS, which assesses positive post-coital feelings in men, for we have not found an existing scale that specifically measures this significant human experience.

With a Cronbach’s alpha of 0.8, we can conclude that the MPAS has a great internal consistency. Ideal values for Cronbach’s alpha have been suggested to be between 0.70 and 0.90, with values that are too high indicating that some items may be redundant (Nunnally, Reference Nunnally1978; Streiner, Reference Streiner2003). The items in the MPAS are inter-correlated and measure the same construct: positive post-coital affect, in which we have included contentment, relaxation, satisfaction and emotional closeness. Although the pattern of loadings reflected conceptually meaningful groupings, the factor intercorrelations mean that in practical use the MPAS can be considered a unidimensional measure.

Avoidant individuals, as identified by Hazan and Shaver’s self-report measure of adult attachment (Hazan and Shaver, Reference Hazan and Shaver1987) and based on Ainsworth’s (Ainsworth et al., Reference Ainsworth, Blehar, Waters and Wall1978) three patterns of childhood attachment, report relatively high levels of distress and fears of becoming close to others. Based on the correlation between MPAS and attachment avoidance, it seems that MPAS is measuring emotional closeness to a greater extent than it is measuring other factors, since attachment avoidance showed a moderate-to-large negative correlation with the MPAS. Hence, we can say that those who score higher on the MPAS are more comfortable with intimacy and will consequently feel closer to their partners after orgasm. In addition, they may be more likely to engage in affectionate behaviours than those with a more avoidant attachment style. This is important because of the impact it has on relationships. Shared intimacy after lovemaking has been associated with higher sexual and relationship satisfaction (Muise et al., Reference Muise, Giang and Impett2014). Other studies have also shown how insecure attachment styles (anxious and avoidant) affect adult romantic relationships. It has been found that insecure attachment styles in adults are associated with less frequent positive emotions and more frequent negative emotions in the relationship (Simpson, Reference Simpson1990). The avoidant attachment style has been negatively associated with general satisfaction, connectedness and general support in romantic relationships (Li and Chan, Reference Li and Chan2012). In contrast, a secure attachment style has been associated with greater relationship interdependence, trust, commitment and satisfaction (Simpson, Reference Simpson1990). This highlights the need for a consistent method to measure the experienced post-coital emotional closeness and intimacy, and it can be concluded that the MPAS is a valid instrument. Furthermore, it might be used as a predictor for the other factors that have been associated with intimacy after orgasm.

As for the correlation of the MPAS with the PSS, we found some association between low perceived stress and high positive post-coital affect. Previous studies have found higher self-reported stress in daily life to be associated with lower levels of sexual and relationship satisfaction (Bodenmann et al., Reference Bodenmann, Atkins, Schär and Poffet2010). Although significant, the correlation found in the present study is small in terms of construct validity. This does not necessarily mean that our questionnaire is not a good measure of relaxation since the PSS is measuring perceived stress levels over the last month rather than relaxation at a certain point in time (in the case of the MPAS, right after orgasm). Nevertheless, a tendency for people with high perceived stress to experience fewer positive feelings after orgasm was observed.

Sexual satisfaction also showed a small-to-moderate significant correlation with the MPAS, indicating some association between positive post-coital affect and sexual satisfaction. These results fall in line with the existing literature discussed previously: partners who engage in affectionate behaviour after intercourse experience higher sexual and relationship satisfaction (Muise et al., Reference Muise, Giang and Impett2014), and as we have seen, individuals who score higher on the MPAS tend to feel more comfortable with intimacy and would be more likely to engage in shared intimacy after orgasm. Therefore, people who score higher on the MPAS should also present higher values for sexual satisfaction. Considering that the MPAS measures a construct broader than sexual satisfaction, a small-to-moderate correlation value seems adequate to indicate some part of our questionnaire assesses satisfaction.

On the whole of construct validity, we have concluded that the MPAS is a good instrument to assess experienced emotional closeness after orgasm and, to a lesser extent, sexual satisfaction. We believe that our scale is a good measure of post-coital relaxation, but that cannot be concluded from the correlation with the PSS. Moreover, although there is no correlation value to support this, we also believe that our scale is a good assessment of contentment after orgasm.

From the feedback of our expert committee, who were present throughout the process of development of the MPAS, and the feedback of the respondents, we were able to conclude that the MPAS has an adequate content validity and face validity. The scale’s items represent positive post-coital affect and are understandable and relevant to the targeted population.

The strength of the conclusions of this study should be tempered by an understanding of its limitations. First, the questionnaire could have included non-heterosexual men to acquire a better understanding of men’s post-coital experience. We could have done this by not gendering the questions from a heterosexual perspective and asking about a ‘her’, but rather referring to a ‘partner’. Although a portion of the respondents was queer, they ultimately had to be excluded from the study after reviewing their feedback, which suggested this factor might have skewed their answers.

When conducting surveys on the topic of sexuality, it is essential to be aware of how different cultural groups, with different beliefs and attitudes towards sexuality, may affect how participants interpret and respond to the questions. For example, some cultures may place more or less emphasis on emotional closeness after orgasm. This could lead to overreporting of socially desirable answers that do not accurately reflect participants’ true feelings or experiences. Additionally, the language used in the survey may also be a barrier for some participants. For example, some cultures may not have specific words or idioms to describe different sexual orientations, or the words used may have different connotations than in English. Some ideas may indeed be very endemic to a culture and no matter how accurately they are framed in English might not capture the central phenomenon and thus could lead to confusion or inaccuracies in participants’ responses. Finally, some cultural groups may also have a greater reluctance to discuss issues related to sexuality, which could lead to a low response rate. In that sense, our sample lacked ethnical diversity, which is expected since MTurk does not reflect the diversity of the US population in its entirety. Nevertheless, MTurk has been found to be a valid and reliable tool for acquiring data (Litman et al., Reference Litman, Robinson and Rosenzweig2015; Shapiro et al., Reference Shapiro, Chandler and Mueller2013; Sprouse, Reference Sprouse2011) and survey designers should be sensitive to these cultural differences and take steps to minimise bias and confusion when designing and administering surveys on sexuality.

The instruments used to assess construct validity were not measuring the same constructs as the MPAS. However, this is difficult to achieve when developing an instrument for a construct that has not previously been measured. For example, although somewhat helpful, the PSS is not a perfectly adequate assessment to conclude that the MPAS measures relaxation. Although there is not a validated scale that could have been administered to specifically assess relaxation after orgasm, we think the Positive and Negative Affect Schedule (Watson et al., Reference Watson, Clark and Tellegen1988), a scale that measure both positive and negative affect, could have been a better instrument to assess convergent validity.

A final limitation of our study was that participants only completed the online survey once. Had the participants been able to fill in the survey twice, we could have determined the degree to which MPAS produces stable and consistent results. However, this was initially deemed technically impractical and the lack of test–retest reliability data constitutes a significant limitation of our study.

In conclusion, the MPAS, the first questionnaire to measure the post-coital positive affect in a validated and reliable way, will be an essential instrument for future research in heterosexual men. Modified versions for the assessment of this experience in non-heterosexual men and women are warranted.

Data availability statement

The data that support the findings of this study are available on request from the corresponding author.

Acknowledgements

We thank Alessandro Miani for assistance with data collection and feedback, Professor John Brodersen for encouraging discussions and members of the expert committee.

Author contributions

MW initiated the study. MP performed statistical analyses and data interpretation, under the supervision of MW. JH collected pilot data. All authors contributed to the data interpretation. MP wrote the first draft of the manuscript and all authors edited and approved it for publication.

Funding statement

MP’s salary was supported by the ERASMUS programme at University of La Laguna and data were collected as part of a previous study funded by the Department of Clinical Medicine, Aarhus University.

Conflict of interest disclosure

The authors have no conflict of interest to disclose.

Ethics approval statement for work involving animals or human subjects

Not required.

Patient consent statement for work with human subjects

All participants gave written informed consent.

References

Ainsworth, MDS, Blehar, MC, Waters, E and Wall, S (1978) Patterns of Attachment: A Psychological Study of the Strange Situation. Hillsdale, NJ.: Erlbaum.Google Scholar
Bartlett, MS (1951) The effect of standardization on a χ2 approximation in factor analysis. Biometrika 38(3-4), 337–344. doi: 10.1093/BIOMET/38.3-4.337.Google Scholar
Bentler, PM (1990) Comparative fit indexes in structural models. Psychological Bulletin 107(2), 238–246. doi: 10.1037/0033-2909.107.2.238.CrossRefGoogle ScholarPubMed
Bodenmann, G, Atkins, DC, Schär, M and Poffet, V (2010) The association between daily stress and sexual activity. Journal of Family Psychology 24(3), 271–279.10.1037/a0019365CrossRefGoogle ScholarPubMed
Byrne, BM (2013) Structural Equation Modeling with AMOS: Basic concepts, Applications, and Programming, 2nd, 1–396, 10.4324/9780203805534,Google Scholar
Cohen, J (1988) Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Hillsdale, NJ.: Erlbaum.Google Scholar
Cohen, S, Kamarck, T and Mermelstein, R (1983) A global measure of perceived stress. Journal of Health and Social Behavior 24(4), 385–396.10.2307/2136404CrossRefGoogle ScholarPubMed
Cronbach, LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16(3), 297–334.10.1007/BF02310555CrossRefGoogle Scholar
Donnellan, MB, Oswald, FL, Baird, BM and Lucas, RE (2006) The Mini-IPIP Scales: Tiny-yet-effective measures of the big five factors of personality. Psychological Assessment 18(2), 192–203.CrossRefGoogle ScholarPubMed
Dziuban, CD and Shirkey, EC (1974) When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin 81(6), 358–361. doi: 10.1037/H0036316.CrossRefGoogle Scholar
Fraley, RC, Waller, NG and Brennan, KA (2000) An item response theory analysis of self-report measures of adult attachment. Journal of Personality and Social Psychology 78(2), 350–365.10.1037/0022-3514.78.2.350CrossRefGoogle ScholarPubMed
Hazan, C and Shaver, P (1987) Interpersonal Relations and Group Processes Romantic Love Conceptualized as an Attachment Process,Google Scholar
Hendrick, SS (1988) A generic measure of relationship satisfaction. Journal of Marriage and Family 50(1), 93.10.2307/352430CrossRefGoogle Scholar
Hughes, SM and Kruger, DJ (2011) Sex differences in post-coital behaviors in long-and short-term mating: an evolutionary perspective. Journal of Sex Research 48(5), 496–505. doi: 10.1080/00224499.2010.501915.CrossRefGoogle ScholarPubMed
Kaiser, HF (1970) A second generation little jiffy. Psychometrika 35(4), 401–415. doi: 10.1007/BF02291817.CrossRefGoogle Scholar
Kruger, DJ and Hughes, SM (2011) Variation in reproductive strategies influences post-coital experiences with partners. Journal of Social, Evolutionary, and Cultural Psychology 4(4), 254–264. doi: 10.1037/H0099285.CrossRefGoogle Scholar
Lavie-Ajayi, M and Joffe, H (2009) Social representations of female orgasm. Journal of Health Psychology 14(1), 98–107. doi: 10.1177/1359105308097950.CrossRefGoogle ScholarPubMed
Levin, RJ (2011) Physiology of orgasm, Cancer and Sexual Health. Humana Press, pp. 35–49, 10.1007/978-1-60761-916-1_4.10.1007/978-1-60761-916-1_4CrossRefGoogle Scholar
Li, T and Chan, DKS (2012) How anxious and avoidant attachment affect romantic relationship quality differently: a meta-analytic review. European Journal of Social Psychology 42(4), 406–419. doi: 10.1002/EJSP.1842.CrossRefGoogle Scholar
Litman, L, Robinson, J and Abberbock, T (2017) TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior Research Methods 49(2), 433–442. doi: 10.3758/s13428-016-0727-z.CrossRefGoogle ScholarPubMed
Litman, L, Robinson, J and Rosenzweig, C (2015) The relationship between motivation, monetary compensation, and data quality among US- and India-based workers on Mechanical Turk. Behavior Research Methods 47(2), 519–528. doi: 10.3758/S13428-014-0483-X/FIGURES/1.CrossRefGoogle ScholarPubMed
Maczkowiack, J and Schweitzer, RD (2019) Postcoital dysphoria: prevalence and correlates among males. Journal of Sex & Marital Therapy 45(2), 128–140. doi: 10.1080/0092623X.2018.1488326.CrossRefGoogle ScholarPubMed
Meston, C and Trapnell, P (2005) Development and validation of a five-factor sexual satisfaction and distress scale for women: The Sexual Satisfaction Scale for Women (SSS-W). Journal of Sexual Medicine 2(1), 66–81. doi: 10.1111/j.1743-6109.2005.20107.x.CrossRefGoogle ScholarPubMed
Miani, A, di Bernardo, GA, Højgaard, AD, Earp, BD, Zak, PJ, Landau, AM, Hoppe, J and Winterdahl, M (2020) Neonatal male circumcision is associated with altered adult socio-affective processing. Heliyon 6(11), e05566. doi: 10.1016/J.HELIYON.2020.E05566.CrossRefGoogle ScholarPubMed
Muise, A, Giang, E and Impett, EA (2014) Post sex affectionate exchanges promote sexual and relationship satisfaction. Archives of Sexual Behavior 43(7), 1391–1402. doi: 10.1007/s10508-014-0305-3.CrossRefGoogle ScholarPubMed
Nunnally, J (1978) Psychometric Theory. New York: McGraw-Hill.Google Scholar
Opperman, E, Braun, V, Clarke, V and Rogers, C (2014) It feels so good it almost hurts. Journal of Sex Research 51(5), 503–515. doi: 10.1080/00224499.2012.753982.CrossRefGoogle ScholarPubMed
Sadock, BJ and Sadock, VA (2008) Kaplan & Sadock’s Concise Textbook of Clinical Psychiatry, 3rd edn. Philadelphia, PA: Lippincott Williams & Wilkins.Google Scholar
Schmidt, FL, Le, H and Ilies, R (2003) Beyond alpha: an empirical examination of the effects of different sources of measurement error on reliability estimates for measures of individual differences constructs. Psychological Methods 8(2), 206–224. doi: 10.1037/1082-989X.8.2.206.CrossRefGoogle ScholarPubMed
Schultz, KS and Whitney, DJ (2005) Measurement Theory in Action: Case Studies and Exercises. Thousand Oaks, CA.: Sage.CrossRefGoogle Scholar
Schweitzer, RD, O’Brien, J and Burri, A (2015) Postcoital dysphoria: prevalence and psychological correlates. Sexual Medicine 3(4), 235–243. doi: 10.1002/sm2.74.CrossRefGoogle ScholarPubMed
Sewell, KW (2006) The experience cycle and the sexual response cycle: conceptualization and application to sexual dysfunctions. Journal of Constructivist Psychology 18(1), 3–13. doi: 10.1080/10720530590522973.CrossRefGoogle Scholar
Shapiro, DN, Chandler, J and Mueller, PA (2013) Using mechanical Turk to study clinical populations. Clinical Psychological Science. 1(2), 213–220. doi: 10.1177/2167702612469015.CrossRefGoogle Scholar
Simpson, JA (1990) Influence of attachment styles on romantic relationships. Journal of Personality and Social Psychology 59(5), 971–980.CrossRefGoogle Scholar
Sprouse, J (2011) A validation of Amazon Mechanical Turk for the collection of acceptability judgments in linguistic theory. Behavior Research Methods 43(1), 155–167. doi: 10.3758/S13428-010-0039-7/FIGURES/6.CrossRefGoogle ScholarPubMed
Stewart, N, Chandler, J and Paolacci, G (2017) Crowdsourcing Samples in Cognitive Science. Trends in Cognitive Sciences 21(10), 736–748. doi: 10.1016/j.tics.2017.06.007.CrossRefGoogle ScholarPubMed
Streiner, DL (2003) Starting at the beginning: an introduction to coefficient alpha and internal consistency. Journal of Personality Assessment 80(1), 99–103. doi: 10.1207/S15327752JPA8001_18.CrossRefGoogle ScholarPubMed
Tomarken, AJ and Waller, NG (2005) Structural equation modeling: strengths, limitations, and misconceptions. Annual Review of Clinical Psychology 1(1), 31–65. doi: 10.1146/ANNUREV.CLINPSY.1.102803.144239.CrossRefGoogle ScholarPubMed
Watson, D, Clark, LA and Tellegen, A (1988) Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology 54(6), 1603–1070.CrossRefGoogle ScholarPubMed
Wetzel, E, Böhnke, JR and Brown, A (2016) Response biases. In Leong, FTL and Iliescu, D (ed), The ITC International Handbook of Testing and Assessment. New York City: Oxford University Press, pp. 349–363.CrossRefGoogle Scholar
Figure 0

Table 1. The heterosexual Male Post-coital Affect Scale. Instructions: Please answer the questions below, in relation to how you generally feel right after an orgasm when you have had intercourse

Figure 1

Table 2. Demographic characteristics of participants

Figure 2

Table 3. Factor loadings