Why Men Lie About How Many Women They've Slept With | Men's Health Magazine Australia

Why Men Say They’ve Slept With So Many Women

Ask a guy how many girls they’ve slept with and there’s a good chance they won’t give you the right answer. There’s a good reason for it. 

According to a new study published in The Journal Of Sex Research, men will (over) estimate rather than actually tally up their lifetime total. 

The research conducted by the University of Glasgow analysed the responses 15,000 men and women. Scientists delved into why men always report that they have more sexual partners than women, despite the fact that numbers should be roughly even. 

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The survey found that over the course of their lifetime, men suggest they have an average of 14 partners while women only have 7. The age range of the participants was 16 to 74. 

Interestingly, men and women in the top one per cent reported 110 and 50 or more sexual partners respectively. Without including these participants, the overall average was closer between the two genders. 

Researchers also put down the results to social attitudes: 18 per cent of men viewed one-night stands as ‘not wrong at all’ while only 9 per cent of women could say the same. Worryingly, only 57 per cent of men viewed a ‘married person having sexual relations with someone other than his or her partner’ as ‘always wrong’ compared to 65 per cent of women. 

Taking this into account narrowed the gap even further. 

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Paid-for-partners didn’t have a huge bearing on the results and excluding them only made a small difference. 

“Accurate reporting of sexual partners is crucial for many reasons, including assessing individual risk of sexually transmitted infections (STIs) and estimating the rate of STI/HIV transmission,” says Dr. Mitchell.

“Most existing studies of reporting bias are limited to students or high-risk populations, or are conducted as ‘laboratory’ settings, so they don’t show how members of the public respond in a ‘real-life’ survey. To our knowledge, our study is the first attempt to look at all the key types of explanation for the gender discrepancy within the same large and representative sample.”

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