Personal and reported partner pornography viewing by Australian women, and association with mental health and body image

Additional keywords: muscularity, objectification, relationships, social media.

Body image, as conceptualised in objectification theory,^1,2 influences self-esteem, relationships and mental health, including depressed mood and disordered eating.^2–6 Body image concerns are common among young Australians, with 37.4% of women and 13.1% of men aged 15–19 years reporting being very/extremely concerned.⁷

Personal and partner pornography viewing may influence body image.^3,8,9 Understanding the effects of pornography is of public health interest, given emerging evidence of increasing use, particularly among young people.^10,11

Pornography’s effect on body image has been hypothesised as being predominantly negative – increasing objectification and internalisation of attractiveness standards, particularly for women, and creating narrow body expectations for men and women (e.g. about body hair, breast size, genital appearance/size, weight and muscularity).^3,9 However, evidence of pornography’s effect on body image, body dissatisfaction-related disorders and mental health is mixed.^12–16 Qualitative reports from women in relationship distress due to their partner’s pornography use indicate some felt ‘fat’ and ‘ugly’ when comparing themselves to women in pornography.¹⁷ Other qualitative reports indicate a multitude of perceived positive and negative consequences of pornography, including enhancing communication between partners about sex, setting unrealistic expectations about appearance, and for the majority of participants, no perceived effect.¹⁸ Previous research among women is largely qualitative.¹⁹ There are fewer quantitative studies that investigate the relationship between pornography and body image,^3,14 and specifically only one published peer-reviewed article among women that uses validated scales.⁸

We aimed to examine personal and reported partner pornography viewing among Australian women, and explore associations with mental health and body image. Given the high use of pornography and high prevalence of body image concerns among young people, we hypothesised that younger women (<25 years) would view pornography more frequently and have higher body image and mental health concerns compared with women aged ≥25 years. An open-ended question was included in the survey to allow further exploration of the perceived effect of pornography, to help interpret quantitative findings.

We implemented a cross-sectional survey, targeting people who accessed health and fitness content via social media. By using convenience sampling, participants were recruited over June–July 2016 via paid advertising and posts on Facebook and Instagram, and directed to the survey online. The advertisements did not mention pornography, and information given to participants in the consent process mentioned it among other health topics such as diet and exercise. Inclusion criteria were age ≥16 years, using social media and living in Australia. Ethics approval was obtained from the Monash University Human Research Ethics Committee.

Questions related to demographics, social media use, health and wellbeing; for pornography questions, see Table 1. Overall, 151 women and 27 men completed the survey and met inclusion criteria. This analysis relates to 111 women who answered any pornography-related questions.

Table 1.  Pornography-related questions included in survey

Outcomes were measured using pre-validated survey instruments. The Kessler 10 Psychological Distress Scale (K10) measured psychological distress relating to low mood and anxiety (Cronbach’s α (α) = 0.93 in sample).²⁰ Body image was measured using the Objectified Body Consciousness Scale (OBCS) and Drive for Muscularity Scale (DMS, α = 0.88 in sample). The OBCS measures body image constructs, including Body Surveillance (self-objectification and comparison against others, α = 0.63 in sample) and Body Shame (shame when not meeting image standards, α = 0.8 in sample).¹ Higher OBCS scores indicate higher objectified body consciousness, a risk factor for body dissatisfaction and poorer mental health.¹¹ Higher DMS scores indicate greater drive to be muscular.²¹

Pornography viewing was compared between age groups utilising Fischer’s exact test. Age of ≥25 years was used as the cut-off based on recent Lancet definitions of young people,²² and consistency with age cut-offs in national mental health surveys.²³ We used logistic regression to examine associations between pornography use and K10, OBSC and DMS scores, reported as odds ratios (OR) with 95% confidence intervals (95%CIs). To avoid over-adjustment, and given low numbers, only age was included in the multiple logistic regression, with results reported as adjusted ORs (aORs). Quantitative data were analysed with Stata Version 14 (StataCorp, College Station, TX, USA).

Participants were asked an open-ended question (Table 1); responses were examined using thematic analysis.^18,24 This involved familiarisation with responses, generating initial codes, combining these codes into themes (sentiment, effect category, use pattern, broader commentary) and iterative refinement and review of these themes. Findings are presented within themes, including sentiment (positive, negative, null or minimal, mixed) and effect category (body image, relationships, sex).

Demographic characteristics and mental health-related scores are shown in Table 2. It is worth noting that the proportion of female respondents aged <35 years with high/very high risk K10 scores was significantly higher than national estimates (18–24 years: 49% vs 20%, P < 0.001; 25–34 years: 46% vs 12%, P < 0.001).²³

Table 2.  Sample sociodemographic and health-related characteristics (n = 111)^A
IQR, interquartile range; s.d., standard deviation; BMI, body mass index

Three-quarters (76%, 75/99) of participants reported ever viewing pornography intentionally. Median age of first viewing pornography was 16 years (IQR 11–31). Table 3 shows pornography viewing frequencies and attitudes towards partner viewing.

Table 3.  Pornography-viewing characteristics by age
P value calculated with Fisher’s exact test

Most respondents (79%) reported infrequent (never/none in last 12 months/<monthly) personal pornography viewing. Of those with a partner (n = 48), 54% reported their partner viewed pornography frequently (monthly/weekly/daily). Younger respondents (<25 years) were more likely to report greater partner viewing frequency (P < 0.001). While most respondents (85%) were happy with their partner’s pornography viewing frequency, this was more likely among those aged ≥25 years (P = 0.011). Attitudes towards partner viewing were independent of viewing frequency (P = 0.80).

Table 4 shows associations between pornography use and K10, OBCS and DMS scores. The crude association between more frequent pornography viewing and high/very high risk K10 scores (OR 2.78, 95%CI 1.01–7.62) lost significance once controlled for age (aOR 2.30, 95%CI 0.82–6.49), but the crude association between more frequent partner pornography viewing and higher DMS scores (OR 2.35, 95%CI 1.12–4.9) remained significant (aOR 2.20, 95%CI 1.01–4.80). No other significant associations were demonstrated between pornography use and body image/mental health scores.

Table 4.  Association between pornography viewing and mental health and body image-related scores
K10, Kessler 10 Psychological Distress Scale; DMS, Drive for Muscularity Scale; OR, odds ratio; CI, confidence interval; aOR, odds ratio adjusted for age as continuous variable. Bold values indicate P < 0.05

Eighty-nine participants responded to the open-ended question. The most common statement (n = 58, 65%) was that pornography had no/minimal influence on the participant’s life, followed by positive effects (n = 25, 29%), negative effects (n = 23, 26%) and mixed responses (including both negative, positive or null aspects) (n = 17, 19%). Twelve responses referred to body image – predominantly that pornography presents unrealistic norms for female bodies and what is sexually attractive; for example, one participant (23 years) reported pornography ‘distorts your body perception – that bodies have to look a certain way to be attractive to the opposite sex’, while another said it ‘makes me feel like my stomach, thighs and arms are too fat and that I need to wax all of my pubic hair…’ (18 years). Conversely, one participant reported benefits associated with viewing diverse bodies in pornography: ‘…not all the women are ‘skinny skinny’ and it reminds me there are normal-sized girls’ (16 years).

Several participants indicated that pornography’s potential harm, on body image and more broadly, was moderated by factors such as the viewer’s age, with younger people more vulnerable to negative effects, and the internalisation of norms presented in pornography: ‘When I was growing up I always thought that my body would never look as good as the bodies of the girls in porn. And I guess I still think I won’t ever look the way they do, but that’s okay, I look like me…’ (19 years). ‘Pornography is harmless unless we start to think that’s how we should be and act in real life – it can sometimes set unrealistic expectations’ (25 years).

Regarding pornography’s effect on intimate relationships, disparate viewpoints emerged. Negatively, that a partner’s pornography use could be harmful: ‘…due to my last partners watching a lot of porn it lead to him have [sic] a very unhealthy view of what sex in a relationship should be’ (39 years). Positively, that pornography could facilitate communication and intimacy within relationships: ‘It can be a great way to engage with my partner, even if it is just to laugh and wonder how they did what happened in the film. Sometimes it can assist with getting ‘in the mood’…’ (27 years).

Within our sample, the median age of first viewing pornography (16 years) was comparable to other sources.²⁵ Like recent similar studies,²⁵ we found more women reporting ever viewing pornography (76%) than national estimates;²⁶ however, fewer participants (21%) reported viewing pornography frequently than in previous research (48%).²⁵

Importantly, primary data were not collected from partners, and reported/perceived frequency may not reflect actual frequency. A recent Australian study found 84% of men aged 15–29 years reported watching pornography daily or weekly²⁵ versus 31% (by partner report) in our study. Of the 48 participants who reported a partner, 44 (92%) reported being heterosexual, so we assumed most partners were male.

Frequent partner pornography viewing and higher DMS scores were positively associated. Male partners who view pornography more frequently have been shown to have higher expectations for partner attractiveness.²⁷ In the context of our findings, male partners who frequently view pornography may have greater expectations for women with a muscular physique, and their female partners may feel pressured to meet these muscular ideals. Alternatively, men who frequently view pornography may be attracted to women with a higher drive for muscularity. Tylka et al.³ found that previous male partners’ pornography viewing was associated with sexual objectification and internalisation, and indirectly predicted body surveillance and body shame. Our findings contribute to the evidence for a relationship between partners’ pornography use and appearance ideals, specifically higher DMS. Further research is required to better understand this association.

Although we did not quantitatively measure relationship quality in this study, the association between partners’ pornography viewing and higher DMS may also contribute to lower relationship satisfaction. Previous studies have found male partners’ frequency of viewing,²⁸ and greater perceived objectification of their female partner,²⁹ was negatively associated with relationship quality and satisfaction.

Our findings may have been influenced by participants being users of online health and fitness content. Participants already viewed and demonstrated a preference to seek out images of bodies, often minimally clothed and sexualised.³⁰ Viewing this content may itself increase body dissatisfaction,³¹ masking additional effects of pornography. Furthermore, higher baseline levels of psychological distress may have hindered detection of additional effects of pornography. These study group factors may have caused underestimation of the effects of pornography.

The qualitative data revealed a minority of respondents felt pornography significantly affected their life, with the most common response being that pornography had no/minimal influence. As in other studies, pornography use was generally accepted and normalised within young people’s relationships.³² The limited effect of pornography on women’s body image has been suggested as being related to women’s ‘habituation to idealised media presentations of the female body’.^8(p304) Given young women’s high exposure to idealised bodies in media generally, and comparatively lower exposure to pornography, pornography may not be the principal source of poor body image. However, qualitative responses revealed a range of perceptions and complexity in sentiment towards and experience of pornography. For those who discussed body image, pornography’s effect was predominantly negative. This aligns with previous research that found a significant minority of women perceive pornography as setting unrealistic appearance expectations.¹⁸ Further research is needed to explore the potential effect of pornography on body image, particularly among vulnerable individuals.

This study has limitations. Our sample size was small. Convenience sampling prevents generalisation of findings to the Australian population. The open-ended question did not ask about mental health and body image effects directly, so may not have revealed them. The cross-sectional design allows comment only on correlation, not causation. Responses were subject to recall and self-presentation bias. Nevertheless, this research offers useful preliminary insights that warrant further exploration.

The authors declare that they have no conflicts of interest.