Regular STI testing amongst men who have sex with men and use social media is suboptimal

Abstract

Sexually transmitted infections (STIs) disproportionately affect men who have sex with men, with marked increases in most STIs in recent years. These are likely underpinned by coterminous increases in behavioural risks which have coincided with the development of Internet and geospatial sociosexual networking. Current guidelines advocate regular, annual sexually transmitted infection testing amongst sexually active men who have sex with men (MSM), as opposed to symptom-driven testing. This paper explores sexually transmitted infection testing regularity amongst MSM who use social and sociosexual media. Data were collected from 2668 men in Scotland, Wales, Northern Ireland and the Republic of Ireland, recruited via social and gay sociosexual media. Only one-third of participants report regular (yearly or more frequent) STI testing, despite relatively high levels of male sex partners, condomless anal intercourse and high-risk unprotected anal intercourse. The following variables were associated with regular STI testing; being more ‘out’ (adjusted odds ratio = 1.79; confidence interval = 1.20–2.68), HIV-positive (adjusted odds ratio = 14.11; confidence interval = 7.03–28.32); reporting ≥10 male sex partners (adjusted odds ratio = 2.15; confidence interval = 1.47–3.14) or regular HIV testing (adjusted odds ratio = 48.44; confidence interval = 28.27–83.01). Men reporting long-term sickness absence from work/carers (adjusted odds ratio = 0.03; confidence interval = 0.00–0.48) and men aged ≤25 years (adjusted odds ratio = 0.36; 95% confidence interval = 0.19–0.69) were less likely to test regularly for STIs. As such, we identify a complex interplay of social, health and behavioural factors that each contribute to men’s STI testing behaviours. In concert, these data suggest that the syndemics placing men at elevated risk may also mitigate against access to testing and prevention services. Moreover, successful reduction of STI transmission amongst MSM will necessitate a comprehensive range of approaches which address these multiple interrelated factors that underpin MSM's STI testing.

Keywords

Men who have sex with men sexually transmitted infection testing UK social media Europe homosexual men screening sexual behaviour

Introduction

In contrast to most other sub-groups, rates of HIV infection in men who have sex with men (MSM) are stable or rising in almost all developed and developing nations, consistent with a growing amplification of inequalities in sexual health.¹ Moreover, other sexually transmitted infections (STIs) also disproportionately affect MSM; although 2.6% of the British male population reported a same sex partner in last 5 years,² in 2014 MSM accounted for 86% of syphilis and 68% of gonorrhoea diagnoses amongst men in England.³ In the UK, there has been a steady increase in new HIV diagnoses amongst MSM,⁴ with a particularly marked recent increase in new diagnoses of other STIs in England (a 46% increase in syphilis and a 32% increase in gonorrhoea over 2013). Moreover in Scotland the proportion of rectal infections within all gonorrhoea diagnoses increased from 11.9% in 2005 to 37.5% in 2014, the highest ever proportion and a marker for condomless anal sex between men.⁵ It is likely that condomless anal intercourse (CAI), in association with serosorting, contributes to the high rates of STIs including Lymphogranuloma venereum (LGV)⁶ and hepatitis C⁷ seen in MSM living with HIV. Outbreaks of syphilis⁸ and enteric infections including shigella⁹ across the UK are associated both with high proportions of HIV-positive MSM, sexualised drug use (Chemsex) and the use of geospatial social networking apps^8,10 and may represent overlapping populations of dense sexual networks of HIV-positive MSM¹¹ and populations of men at high risk who are currently HIV-uninfected or undiagnosed. Overall then, not only have the number of STI diagnoses amongst MSM risen dramatically in recent years, these also account for the majority of increased diagnoses seen amongst men.³ This failure in disease prevention contrasts with seismic social changes for many MSM in multiple Western liberal democracies. In the UK these have included the legalisation of equal marriage, equality in health, parental and employment rights and increasing mainstream acceptance of homosexuality.¹

Underpinning these increases in disease prevalence, there has been a continued increase in individual risk behaviours reported by a proportion of MSM in recent years, particularly unprotected anal intercourse,^12,13 more properly called CAI given the success of pre-exposure prophylaxis (PrEP)^14,15 though it must be acknowledged that such behaviour remains unprotected in relation to other STIs. Although the types of interventions most likely to reduce HIV transmission amongst MSM have been identified,^16,17 it remains unclear how to effectively target and combine these interventions. In addition, our developing understanding of the characteristics of those men most at risk, and their engagement with services, remains limited.¹⁸ Moreover, individual risk behaviours cannot fully explain the continuing HIV epidemic; specifically, sexual dyad and network determinants, along with community and structural barriers, may mean that some groups of MSM experience higher rates of HIV transmission despite lower rates of direct behavioural risk factors.¹⁹ For example, black MSM in the USA report less CAI with main partners, more condom use, fewer male partners and less drug use during sex than white MSM but have a three-fold higher risk of testing HIV-positive.²⁰ This group also experiences higher rates of a range of structural and social disadvantages (including unemployment, low education, lack of health insurance and low income), which might be assumed to contribute to risk (ibid). Similarly, a recent Scottish HIV prevention needs assessment²¹ found that higher risk MSM were significantly younger than lower risk men, more likely to be of an ethnic minority and less likely to have degree level education. Indeed, younger MSM across the world are also likely to be disadvantaged in accessing services.²²

Sharing social and sexual information on social media (e.g. Facebook) and gay-specific sociosexual networks (e.g. Gaydar and Grindr) has grown rapidly in recent years. In 2012 almost half of UK adults were recent users of social networks²³ and gay, lesbian and bisexual individuals use these sites more than heterosexuals.²⁴ Social media can provide access to MSM both for HIV prevention interventions and sexual health survey participation^25,26 and may facilitate access to younger men, minority groups and men living in rural areas not previously captured by initiatives based on the commercial gay scene.²⁵ This is important since individual MSM’s current knowledge limitations may be further compounded by the preponderance of literature derived from men recruited from clinics, gay commercial venues and Pride events and the recognition that older men are overrepresented both in research and prevention work.^19,27 MSM who source male sex partners through the Internet appear to be at higher risk of HIV through increased partner numbers, increased CAI with casual partners²⁶ and an increase in both assortative and disassortative sexual mixing.^28,29 Moreover, MSM who use smartphone-based sociosexual network apps are more likely to test positive for gonorrhoea and chlamydia (but not syphilis or HIV)³⁰ and report a higher prevalence of lifetime STI diagnoses.³¹ Therefore, recruitment of MSM through social media, including both website and smartphone apps, may provide access to a higher-risk subgroup.

Modelling evidence suggests that over 80% of new HIV infections in the UK stem from men who are unaware of their own positive status, most of whom are in seroconversion, and that a significantly increased testing frequency is required to reduce this incidence.³² This increased rate of testing must be combined with behavioural interventions and biological measures including treatment-as-prevention (TasP)³² and PrEP^33–35 in order to stem the epidemic. In tandem these biomedical developments in HIV prevention raise questions regarding the key outcome measures for both behavioural surveillance and intervention evaluation. Regularity of STI tests (for MSM, including HIV positive men) which correlate in many cases with regularity of HIV testing (amongst HIV negative men)³⁶ are key candidate approaches fit for an era where bio-behavioural interventions render measures of condom use, or recency of HIV tests, increasingly redundant. Moreover, recent British Association of Sexual Health and HIV (BASHH) guidelines suggest that all MSM should be tested annually for STIs, with higher risk men tested every three months,^37,38 prioritising the importance of understanding regular, as opposed to recent, testing.

This study is the first of its kind to explore regular STI testing as a key indicator of sexual health amongst the MSM population. It is unique in that it addresses MSM from Scotland, Wales, Northern Ireland (NI) and the Republic of Ireland (RoI) recruited using social and gay-specific sociosexual networking sites (both website and smartphone app based), sub-groups previously overlooked by other behavioural surveillance approaches. Given the promise of TasP and questions regarding the riskiness of CAI, we focus on the regularity of STI testing as an indicator of sexual health risk, as well as a marker of contact with services. This approach enables us to focus on a population level approach to understanding sexual health and to include HIV-positive men within the analysis.

Methods

Study design and population

The Social Media, MSM and Sexual Health (SMMASH) Survey collected anonymous, self-completed questionnaires from MSM recruited online from November 2012 to February 2013 in Scotland, Wales, NI and the RoI. Pop-up message ‘blasts’ and/or banner adverts invited men using three gay-specific social media websites (Gaydar, Recon and Squirt), two smartphone apps (Grindr and Gaydar) and Facebook to participate via Survey Monkey. The questionnaire was based on the triennial Chief Scientist Office / Medical Research Council (CSO/MRC) bar-based Gay Men’s Sexual Health Survey¹² and further developed in consultation with sexual health service providers, clinicians and MSM who advised on question style and content. Online questionnaires were piloted at Glasgow Gay Pride (2012), suggesting men were able and happy to participate, with only minor amendments required to improve clarity. Overall 2668 men completed useable questionnaires from Scotland (n = 1326), Wales (N = 459), NI (n = 301) and the RoI (n = 582). Questionnaires surveyed socio-demographics (age, ethnicity, country of residence, employment, education, sexual identity, proximity to and frequency of gay scene use), sexual health (self-report of HIV and STI testing, testing regularity and diagnoses) and sexual behaviours in the previous 12 months. A measure of CAI with higher risk for HIV infection was created to include men who reported CAI with ≥2 casual and/or status unknown/serodiscordant partners in the previous 12 months (compared with men reporting CAI with 0/1, regular and/or seroconcordant partners only). Ethical approval was granted by Glasgow Caledonian University School of Health and Life Sciences Ethics Subcommittee.

Statistical analysis

Data were analysed with IBM SPSS 21 by RA and JF to investigate associations between socio-demographics, sexual behaviours and regularity of STI testing in the previous 12 months (reflecting BASHH STI testing guidelines^37,38). The key dependent variable used in this study was reporting regular (at least yearly) STI testing.

Univariate associations between categorical independent variables and regularity of STI testing were investigated using Chi square tests and continuous variables were investigated using t tests. Variables significant at the bivariate level (p < 0.05) were entered into logistic regression models used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) of dependent variables for demographics, sexual risk behaviours, STI testing/results and gay community engagement, respectively. From the 2668 useable responses collected, sample sizes for individual variables varied by specific analysis, as shown in the relevant tables below. Multivariable associations, controlling for the effect of statistically significant socio-demographic variables, were investigated using hierarchical multiple logistic regression.

Results

Table 1 shows the demographic and behavioural profile of the whole sample. The average age of participants was 36.2 years (sd = 12.8, range 18–84) with 25% of the sample aged 18–25. The majority (96.8%) were white, reflecting the ethnic profile of Ireland and the UK outwith London. Most participants (70.1%, n = 1581) were employed/self-employed, 62.9% (n = 1410) were educated to at least degree level. One-third (34.1%; n = 692) were in a relationship with a man, 66% (n = 1336) were single, most 60.8% (n = 1354) were out to nearly everybody and over three-quarters (78.7%, n = 1750) never or rarely used the commercial gay scene. Overall, 78.6% (n = 2083) were gay identified, 19.4% bisexual (n = 515) and 2% (n = 53) straight. Most were HIV-negative/untested (93.6%, n = 1848) with only 6.4% (n = 126) reporting a known HIV-positive status. Just over 1 in 10 (10.8%) reported a diagnosed STI in the previous year. One-third (36%, n = 804) reported ≥10 male sex partners in the previous year and although 28.8% (n = 524) of participants reported ≥2 CAI partners, and 36.5% (n = 825) reported high risk CAI, almost two-thirds (63.3%, n = 1433) did not report regular STI or regular HIV (83.0%) testing.

Table 1.

Univariate associations between independent variables and regular STI testing over the previous 12 months.

	Regular STI testing
Variable	Whole sample N (% of n)	Self-reported regular testing (% of category)
Age
18–25	564 (25.0)	195 (34.6)*
26–35	556 (24.6)	209 (37.7)
36–45	504 (22.3)	161 (31.9)
45+	634 (28.1)	186 (29.3)
Ethnicity
white British	1902 (84.4)	618 (32.5)
white Irish	180 (8.0)	67 (37.2)
white other	99 (4.4)	37 (37.4)
non-white/other ethnic background	72 (3.2)	26 (36.1)
Country
Scotland	1130 (49.9)	390 (34.5)
Wales	396 (17.5)	119 (30.1)
Northern Ireland	247 (10.9)	81 (32.8)
Republic of Ireland	490 (21.7)	163 (33.3)
Employment status
Employed/self-employed	1581 (70.1)	538 (34.0)*
Unemployed	173 (7.7)	45 (26.0)
Retired	111 (4.9)	33 (29.7)
Student	369 (16.4)	132 (35.8)
Long-term sickness absence/carer	21 (0.9)	2 (9.5)
Educational qualification
No qualification	58 (2.6)	18 (31.0)**
Secondary	773 (34.5)	218 (28.2)
Degree	1092 (48.7)	387 (35.4)
Postgraduate	318 (14.2)	120 (37.7)
Relationship status
Single	1336 (65.9)	521 (39.0)
Male partner	692 (34.1)	261 (37.7)
How out
Not very out	873 (39.2)	204 (23.4)***
Out to nearly everyone	1354 (60.8)	537 (39.7)
Frequency of gay scene use
Rarely use gay scene	1750 (78.7)	524 (29.9)***
Frequently use gay scene	475 (21.3)	220 (46.3)
Perceived proximity to local gay scene
Very near to gay scene	687 (33.6)	292 (42.5)***
Quite near to gay scene	430 (21.0)	143 (33.3)
Slightly far from gay scene	316 (15.4)	105 (33.2)
Far from gay scene	267 (13.0)	89 (33.3)
Very far from gay scene	346 (16.9)	84 (24.3)
Travel time to local gay scene
≤30 minutes	982 (48.4)	403 (41.0)***
30 minutes–1 hour	647 (31.9)	199 (30.8)
1–2 hours	284 (14.0)	71 (25.0)
>2 hours	115 (5.7)	34 (29.6)
Affordability to gay scene using public transport
Very affordable	805 (39.7)	321 (39.9)***
Affordable	354 (17.4)	124 (35.0)
Quite affordable	241 (11.9)	72 (29.9)
Expensive	195 (9.6)	68 (34.9)
Too expensive	435 (21.4)	127 (29.2)
Self-reported HIV status
Negative/untested	1848 (93.6)	628 (34.0)***
Positive	126 (6.4)	94 (74.6)
Self-reported STI status
No STI diagnosed	2009 (89.2)	593 (29.5)***
STI diagnosed	242 (10.8)	157 (64.9)
Number of male sex partners
<10 men	1429 (64.0)	359 (25.1)***
≥10 men	804 (36.0)	384 (47.8)
Number of CAI partners
0 CAI partners	776 (43.3)	203 (26.2)***
1 CAI partner	502 (28.0)	150 (29.9)
2–4 CAI partners	334 (18.6)	150 (44.9)
≥5 CAI partners	182 (10.1)	90 (49.5)
High risk CAI measure
Low risk	1438 (63.5)	404 (28.1)***
High risk	825 (36.5)	349 (42.3)
Regularity of STI testing
No regular testing	1424 (63.3)
Tests every few years	77 (3.4)
Tests about once a year	315 (14.0)
Tests every 6 months	327 (14.5)
Tests every 3 months	108 (4.8)
Regularity of HIV testing
Every 6 months or less	368 (17.0)	333 (90.5)***
Less than 6 months or never	1791 (83.0)	398 (22.2)

p < 0.05.

p < 0.01.

***

p < 0.001.

Univariate associations between independent variables and regular STI testing in the previous 12 months

Several socio-demographic and sexual health-related variables were significantly associated with regular STI testing (see Table 1). Specifically, younger age (≤25 years), employment status, educational qualifications, being out to nearly everyone, frequent gay scene use, perceived proximity of, shorter travel time and affordability of travel to the local gay scene, HIV-positive status, reporting a diagnosed STI, sexual contact with ≥10 men, ≥2 CAI partners, higher risk CAI in the last year and more regular HIV testing were all significantly associated with regular STI testing.

Multivariable logistic regression analysis predicting regular STI testing in the previous 12 months from socio-demographics and sexual health related variables

Socio-demographic and sexual health-related variables significantly predicted regular STI testing (χ² [df 30] = 545.88 p < 0.001) and explained 55% of the variation (Nagelkerke R²= 0.55) in regular STI testing (see Table 2). The model correctly predicted 83% of the data and Hosmer and Lemeshow goodness of fit checks indicated good fit of the model to the data (χ² [df 8] = 12.66, p = 0.12).

Table 2.

Multivariate logistic regression predicting regular testing from socio-demographic and sexual health-related variables.

Predictor variable	B (SE) (unadjusted odds ratio)	Exp (B) (adjusted odds ratio)	95% CI for Exp (B)
Predictor variable	B (SE) (unadjusted odds ratio)	Exp (B) (adjusted odds ratio)	Lower	Upper
Age group
18–25 years	–101 (0.33)	0.36**	0.19	0.69
26–35 years	–0.10 (0.25)	0.90	0.55	1.47
36–45 years	–0.30 (0.26)	0.74	0.45	1.23
45+ years	1	1
Employment status
Employed/self-employed	1	1
Unemployed	–0.67 (0.37)	0.51	0.25	1.05
Retired	0.03 (0.42)	1.03	0.45	2.34
Student	0.50 (0.30)	1.65	0.91	2.99
Long-term sickness absence/carer	–3.65 (1.49)	0.03*	0.00	0.48
Educational qualification
No qualification	1	1
Secondary	–0.48 (0.61)	0.62	0.19	2.03
Degree	–0.20 (0.60)	0.82	0.25	2.66
Post-graduate	–0.07 (0.63)	0.93	0.27	3.17
How out
Not very out	1
Out to nearly everyone	0.58 (0.21)	1.79**	1.20	2.68
Frequency of gay scene use
Rarely use gay scene	1	1
Frequently use gay scene	0.37 (0.21)	1.45	0.97	2.17
Perceived proximity to gay scene
Very near to gay scene	1	1
Quite near to gay scene	–0.36 (0.26)	0.70	0.43	1.15
A bit far from gay scene	–0.47 (0.34)	0.62	0.32	1.22
Far from gay scene	–0.16 (0.40)	0.85	0.39	1.87
Too far from gay scene	–0.52 (0.47)	0.60	0.24	1.49
Travel time to local gay scene
≤30 minutes	1	1
30 minutes–1 hour	–0.34 (0.26)	1.40	0.84	2.32
1–2 hours	–0.14 (0.41)	0.87	0.39	1.95
>2 hours	–0.47 (0.59)	0.63	0.20	2.00
Affordability to gay scene using public transport
Very affordable	1	1
Affordable	0.12 (0.27)	1.13	0.67	1.91
Quite affordable	–0.87 (0.36)	0.42*	0.21	0.85
Expensive	0.10 (0.38)	1.10	0.52	2.33
Too expensive	0.30 (0.36)	1.35	0.67	2.74
Self-reported HIV status
Negative/untested	1	1
Positive	2.65 (0.36)	14.11***	7.03	28.32
Number of male sex partners
<10 men	1	1
≥10 men	0.76 (0.20)	2.15***	1.47	3.14
Number of CAI partners
0 CAI partners	1	1**
1 CAI partner	–0.36 (0.26)	0.70	0.42	1.16
2–4 CAI partners	0.48 (0.40)	1.62	0.73	3.57
≥5 CAI partners	–0.54 (0.47)	0.58	0.23	1.47
High-risk CAI measure
Low risk	1	1
High risk	–0.05 (0.33)	0.95	0.50	1.82
Regularity of HIV testing
Less regular (>6 months/never)	1	1
Regular (≤6 monthly)	3.88(0.28)	48.44***	28.27	83.01
Constant	–1.48 (0.66)	0.23*

Model χ2 (df 30) = 545.88, p < 0.001; Nagelkerke R²= 0.55; overall classification correctly predicted=83%.

p < 0.05.

p < 0.01.

***

p < 0.001.

Three socio-demographic variables; age (Wald 11.23, p = 0.01), employment status (Wald = 12.22, p = 0.02) and being out (Wald = 8.10, p = 0.004) significantly contributed to the multivariable model. Specifically, compared to 45⁺-year-olds 18- to 25-year-olds had lower odds of testing regularly for STIs (AOR = 0.36; 95% CI: 0.19–0.69). Compared to the employed, men reporting long-term sickness absence from work and their carers were less likely to test regularly (AOR = 0.03; 95% CI: 0.00–0.48). Also, men who perceived themselves to be more ‘out’ were more likely to test regularly (AOR = 1.79; 95% CI: 1.20–2.68).

After controlling for these significant socio-demographic factors, HIV status (Wald = 55.49, p < 0.001), number of male sex partners in the last year (Wald = 15.38, p < 0.001) and HIV testing regularity (Wald = 199.39, p < 0.001), significantly contributed to the variation in regular STI testing.

Men who reported an HIV-positive status (AOR = 14.11; 95%CI, 7.03–28.32) and men reporting ≥10 male sex partners (AOR = 2.15; 95% CI: 1.47–3.14) were significantly more likely to regularly test for STIs. Testing regularly for HIV (≤6 monthly) was associated with regular testing for STI (AOR = 48.44; 95% CI: 28.27–83.01). Two other variables, number of CAI partners (Wald = 13.40, p = 0.004) and perceived affordability of using public transport to the gay scene (Wald = 10.74, p = 0.03), contributed significantly in predicting regularity of STI testing in the last 12 months. However, no clear group-specific differences were discernible for these two variables. Self-report STI diagnosis was not included in this analysis due to the tautology between STI diagnosis and STI testing.

Discussion

This paper has demonstrated that only one-third (33.3%) of MSM adhere to BASHH guidelines³⁷ of undergoing annual STI testing. This is despite relatively high levels of male sex partners, CAI partners and high-risk CAI amongst this sample. Therefore, increasing regular STI testing amongst MSM who use social and sociosexual media is paramount. In identifying correlates of regular STI testing amongst these MSM, this paper pinpoints key sub-populations to be targeted within intervention delivery.^26,39

The use of social and sociosexual media to recruit participants produced a sample of MSM with a broad age range, where bisexual men, those who did not use the gay scene and men who were not ‘out’ were well represented. In common, with studies recruited from the gay scene,¹² this was a highly educated population, but reported STI and HIV risk were far higher than in previous studies, with 28.7% of men reporting multiple (≥2) CAI partners in the last year, in contrast to rates of 13.1–14.5% reported in the triennial CSO/MRC bar-based Gay Men’s Sexual Health Survey on which our questionnaire was based.¹²

Previous studies³⁶ have shown a positive relationship between STI testing and increasing age, indicative of the gradual exposure to STIs over time amongst sexually active MSM. Herein, older MSM were over twice as likely to test regularly for STIs than men in the youngest (18–25 year) age group. This finding suggests habit formation or broader adoption of sexual health-promoting activity by older men. This resonates with previous findings that younger men seek testing only when symptomatic²¹ and are more likely to have undiagnosed HIV infection.⁴⁰ It also underlines the importance of providing MSM-inclusive STI testing facilities within more generic services including community-based sexual health and GP services, as these may be more acceptable to younger men.⁴¹ Men who used the gay scene more frequently and those who perceived themselves to be ‘out’ were also more likely to report regular STI testing. This is consistent with the finding of Mustanski et al.¹⁹ that whilst ‘connectedness’ to the gay scene carries elevated potential exposure to sexual contacts at high risk of STIs including HIV, it is also associated with improved access to MSM-specific health improvement and testing services. Moreover, this is consistent with ideas of improved sexual health literacy and community capital for scene-users, since historically the commercial gay scene has been a hub for both sexual health intervention delivery and the promotion of sexual health norms.

Employment status was also associated with regularity of STI testing, with those on long-term sickness absence or their carers less likely to test regularly than students, retired, unemployed or employed participants. Vulnerability has previously been identified as a risk factor for STI acquisition and infrequent HIV testing.^21,42,43 It is likely that poorer sexual health among these vulnerable groups is shaped by wider social determinants of health.⁴⁴ For example, young MSM suffer more from victimisation via bullying,⁴⁵ homelessness and social stigma than their heterosexual counterparts. The clustering of these co-occurring epidemics or ‘syndemics’ of risk factors⁴⁶ is increasingly recognised in studies on MSM^19,47 and indicates the importance of examining the heterogeneity of the MSM population and therein, the centrality of intersectionality⁴⁸ (whereby multiple social vulnerabilities impact upon one another, for example, age and ethnicity) in contributing to the amplification of inequalities within sexual health.⁴⁷

Although having a greater number of sexual partners was associated with reporting regular STI testing, the relationship with CAI partners was less clear, suggesting a disconnect between levels of risk and testing. This is consistent with the notion that those syndemics placing men at elevated risk may also mitigate against access to testing and prevention services.⁴⁹ Study participants with HIV were more likely to regularly test for STI, consistent with significant improvements in routine sexual health screening in clinics. Finally, regular HIV testing was highly related to regular STI testing, which is fairly unsurprising given the move to screen MSM for all STIs when presenting for either an HIV or STI test. However, it is also suggestive that, once men are linked into services, regular STI and HIV testing becomes normative, at least for some.

Limitations

Recruiting participants from social media advertising meant it was neither possible to calculate an accurate response rate, nor exclude duplicate responses from men accessing the survey using different sites or profiles. Generous free advertising and procedural difficulties meant we were also unable to track the total number of message blasts/banner impressions reaching unique users during the survey period. Social network users are younger than the general population,²³ whilst economically disadvantaged men unable to afford the relative expense of a smartphone or private Internet necessary to access sociosexual networking sites, along with technologically challenged, illiterate and (potentially) learning disabled MSM, were also likely underrepresented. Whilst the self-reported nature of this study imbues inherent generic limitations, including recall accuracy, veracity and social desirability, our principle dependent variable also fails to take into account the duration of regular STI testing. Thus we are unable to distinguish those whose regular testing is a longstanding behaviour from those for whom this is a relatively recent development. Although the strong association between regular STI and HIV testing could reflect redundancy of the latter variable as a predictor, this finding remains meaningful in terms of health promotion, and so was included in the analysis. Despite these limitations, a large, demographically varied sample was recruited with sample sizes comparable to those of previous commercial gay scene surveys.¹² Indeed, in recruiting a sample who largely eschewed the commercial gay scene, this study adds knowledge of an important group of MSM previously excluded from contemporary research and questions the representativeness of data collected solely within commercial venues.

Implications

Along with demonstrating sub-optimal levels of regular STI screening amongst MSM, this study has identified various sub-groups of MSM who are less likely to regularly screen for STIs. However, a common theme among these characteristics was men’s vulnerability, stemming from a complex interplay of social, health and behavioural factors that each contribute to the higher rates of STI observed amongst MSM. Successful reduction of STI transmission amongst MSM will necessitate a comprehensive range of approaches^21,50 to address these interrelated factors. In particular, new technologies, such as self-sampling and home-testing for STIs/HIV, promise to reduce a host of clinic-related testing barriers⁵¹ and appear acceptable to MSM.⁵² However, the potential for loss-to-follow-up for positive diagnoses, and a potential lack of continuity of care therein, must be addressed. In concert, our results are useful to guide future prevention interventions delivered via social media sites and also suggest ways in which access to and engagement with testing services might be improved.

Footnotes

Acknowledgements

JF and PF designed the SMMASH study. JF coordinated data collection and data screening. RA and JF performed and wrote up the analyses. LG, DC and JF wrote the manuscript with input from all authors. All authors commented on multiple drafts of the script. The authors thank all the men who took part in this study, and both Gaydar and Grindr for providing some generous free participant recruitment advertising to support the SMMASH study.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The SMMASH study was funded by NHS Lanarkshire Blood Bourne Viruses and Glasgow Caledonian University (GCU)_. GCU funds JF, RA and PF. LG was self-funded for this project. NHS Lothian and NHS Borders fund DC.

Ethics

Ethical approval was granted by Glasgow Caledonian University School of Health and Life Sciences Ethics Subcommittee (HLS id: B11/59)

Key Message

Regular STI testing amongst MSM falls short of recommended guidelines despite on-going behavioural risk. Various sub-groups of MSM are less likely to regularly screen for STIs, characterised by a complex interplay of social, health and behavioural factors.

Prior publication

The demographic characteristics of the sample and prevalence of STI testing for HIV negative/untested participants only have been submitted elsewhere (Frankis J, Young I, Lorimer K, et al. Towards preparedness for PrEP. PrEP awareness and acceptability amongst MSM at high risk of HIV transmission who use sociosexual media in four Celtic nations – Scotland, Wales, Northern Ireland and the Republic of Ireland: an online survey. STI 2016; doi:10.1136/sextrans-2015-052101. This paper includes the HIV negative/untested SMMASH participants only.) The substantive issues within this paper (regularity of STI testing) have not been published elsewhere. We confirm that the remaining results presented in this paper have not been published previously in whole or part, except in abstract format.

References

Beyrer

. Strategies to manage the HIV epidemic in gay, bisexual, and other men who have sex with men. Curr Opin Infect Dis 2014; 27: 1–8.

Mercer

Tanton

Prah

. Changes in sexual attitudes and lifestyles in Britain through the life course and over time: findings from the National Surveys of Sexual Attitudes and Lifestyles (Natsal). Lancet 2013; 382: 1781–1794.

Public Health England. Sexually transmitted infections and chlamydia screening in England, 2014 [Internet]. Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/437433/hpr2215_STI_NCSP_v6.pdf (2014, accessed 26 February 2016).

Aghaizu

Brown

Nardone

. HIV in the United Kingdom 2013 Report: Data to end 2012, London: Public Health England, 2013.

Health Protection Scotland. Genital herpes simplex, genital chlamydia and gonorrhoea infection in Scotland: laboratory diagnoses 2005 – 2014. HPS Weekly Rep 2015; 49: 213–227.

Hughes

Alexander

Simms

. Lymphogranuloma venereum diagnoses among men who have sex with men in the U.K.: interpreting a cross-sectional study using an epidemic phase-specific framework. Sex Transm Infect 2013; 89: 542–547.

Public Health England. Hepatitis C in the UK 2014 Report. London: Public Health England. Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/337115/HCV_in_the_UK_2014_24_July.pdf (2014, accessed 26 February 2016).

Simms I, Wallace L, Thomas DR, et al. Recent outbreaks of infectious syphilis, United Kingdom, January 2012 to April 2014. Euro Surveill 2014; 19(24): pii: 20833.

Simms I, Field N, Jenkins C, et al. Intensified shigellosis epidemic associated with sexual transmission in men who have sex with men – Shigella flexneri and S. sonnei in England, 2004 to end of February 2015. Euro Surveill 2015; 20(15): pii: 21097.

10.

Gilbart

Simms

Jenkins

. Sex, drugs and smart ‘phone applications: findings from semi-structured interviews with men who have sex with men diagnosed with Shigella flexneri 3a in England and Wales. Sex Transm Infect 2015; 91: 598–602.

11.

Malek

Mitchell

Furegato

. Contribution of transmission in HIV-positive men who have sex with men to evolving epidemics of sexually transmitted infections in England: an analysis using multiple data sources, 2009–2013. Euro surveill 2015; 20(15): pii 21093.

12.

Knussen

Flowers

McDaid

. HIV-related sexual risk behaviour between 1996 and 2008, according to age, among MSM (Scotland). Sex Transm Infect 2011; 87: 257–259.

13.

Lattimore

Thornton

Delpech

. Changing patterns of sexual risk behaviour among London Gay Men: 1998-2008. Sex Transm Dis 2011; 38: 221–229.

14.

Pragmatic open-label randomised trial of preexposure prophylaxis: the PROUD study. In: Conference on retroviruses and opportunistic infections 2015; 2015 Feb 23–26, 2015. 22LB; Seattle, WA, USA.

15.

On demand PrEP with oral TDF-FTC in MSM: results of the ANRS Ipergay trial. In: Conference on retroviruses and opportunistic infections 2015; 2015 Feb 23–26, 2015. 23LB; Seattle, WA, USA.

16.

Lorimer

Kidd

Lawrence

. Systematic review of reviews of behavioral HIV prevention interventions among men who have sex with men. AIDS Care 2012; 25: 1–18.

17.

Johnson

Diaz

Flanders

. Behavioral interventions to reduce risk for sexual transmission of HIV among men who have sex with men. Cochrane Database Syst Rev 2008(3): 1–71.

18.

McDaid

Hart

. Contact with HIV prevention services highest in gay and bisexual men at greatest risk: cross-sectional survey in Scotland. BMC Public Health 2010; 10: 1–10.

19.

Mustanski

Newcomb

Du Bois

. HIV in young men who have sex with men: a review of epidemiology, risk and protective factors, and interventions. J Sex Res 2011; 48: 218–253.

20.

Sullivan

Peterson

Rosenberg

. Understanding racial HIV/STI disparities in black and white men who have sex with men: a multilevel approach. PloS One 2014; 9: e90514.

21.

Coia

Milne

McAdams

. HIV Prevention needs assessment of men who have sex with men, Edinburgh: Scottish Government, 2014.

22.

Santos

Beck

Wilson

. Homophobia and access to HIV services among young men who have sex with men (YMSM). J Int AIDS Soc 2012; 15: 190.

23.

Office for National Statistics. Social networking: The UK as a leader in Europe. Secondary Social networking: The UK as a leader in Europe, June 2013, www.ons.gov.uk/ons/rel/rdit2/internet-access—households-and-individuals/social-networking–the-uk-as-a-leader-in-europe/sty-social-networking-2012.html (accessed 26 February 2016).

24.

Harris Interactive. Gays, Lesbians and Bisexuals Lead in Usage of Online Social Networks. http://www.marketresearchworld.net/content/view/1067/77/ (2007, accessed 26 February 2016).

25.

Young

Szekeres

Coates

. The relationship between online social networking and sexual risk behaviors among men who have sex with men (MSM). PloS One 2013; 8: e62271.

26.

Rosser

Oakes

Konstan

. Reducing HIV Risk Behaviour of MSM through persuasive computing: results of the Men’s INTernet Study (MINTS-II). AIDS 2010; 24: 2099–2107.

27.

Saxton

Dickson

Hughes

. Who is omitted from repeated offline HIV behavioural surveillance among MSM? Implications for interpreting trends. AIDS Behav 2013; 17: 3133–3144.

28.

Liau

Millett

Marks

. Meta-analytic examination of online sex-seeking and sexual risk behavior among men who have sex with men. Sex Transm Dis 2006; 33: 576–584.

29.

Lewnard

Berrang-Ford

. Internet-based partner selection and risk for unprotected anal intercourse in sexual encounters among men who have sex with men: a meta-analysis of observational studies. Sex Transm Infect 2014; 90: 290–296.

30.

Beymer

Weiss

Bolan

. Sex on demand: geosocial networking phone apps and risk of sexually transmitted infections among a cross-sectional sample of men who have sex with men in Los Angeles county. Sex Transm Infect 2014; 90: 568–572.

31.

Lehmiller

Ioerger

. Social networking smartphone applications and sexual health outcomes among men who have sex with men. PloS One 2014; 9: e86603.

32.

Phillips

Cambiano

Nakagawa

. Increased HIV incidence in men who have sex with men despite high levels of ART-induced viral suppression: analysis of an extensively documented epidemic. PloS One 2013; 8: e55312.

33.

Young

Flowers

McDaid

. Barriers to uptake and use of pre-exposure prophylaxis (PrEP) among communities most affected by HIV in the UK: findings from a qualitative study in Scotland. BMJ Open 2014; 4: e005717.

34.

Young

Flowers

McDaid

. Key factors in the acceptability of Treatment as Prevention (TasP) in Scotland: a qualitative study with communities affected by HIV. Sex Transm Infect 2015; 91: 269–274.

35.

Buchbinder

Glidden

Liu

. HIV pre-exposure prophylaxis in men who have sex with men and transgender women: a secondary analysis of a phase 3 randomised controlled efficacy trial. Lancet Infect Dis 2014; 14: 468–475.

36.

McDaid

Knussen

. Sexually transmitted infection testing and self-reported diagnoses among a community sample of men who have sex with men in Scotland. Sex Transm Infect 2013; 89: 223–230.

37.

Clutterbuck

Flowers

Barber

. United Kingdom National Guideline on Safer Sex Advice in the GUM Consultation, London: Clinical Effectiveness Group, British Association of Sexual Health and HIV, 2011.

38.

Ross JR, Brady M, Clutterbuck D, et al. Recommendations for testing for sexually transmitted infections in men who have sex with men. In: BASHH workshop on STI and HIV screening for men who have sex with men (MSM) (published online) UK, 2015, 2015.

39.

Mcfarlane

Bull

Reitneijer

. The internet as a newly emerging risk environment for sexually transmitted diseases. JAMA 2000; 284: 443–446.

40.

Mackellar

Hou

Whalen

. Reasons for not HIV testing, testing intentions, and potential use of an over-the-counter rapid HIV test in an internet sample of men who have sex with men who have never tested for HIV. Sex Transm Dis 2011; 38: 419–428.

41.

Forbes

West

Byrne

. Unintended consequences: A lost opportunity to test men who have sex with men attending contraception and sexual health clinics. HIV Med 2014; 15: 30.

42.

McKirnan

Du Bois

Alvy

. Health care access and health behaviours among men who have sex with men: the cost of health disparities. Health Educ Behav 2013; 40: 32–41.

43.

Mayer

Wang

Koblin

. Concomitant socioeconomic, behavioral, and biological factors associated with the disproportionate HIV infection burden among Black men who have sex with men in 6 US cities. PloS One 2014; 9: e87298.

44.

Dahlgren

Whitehead

. Policies and strategies to promote social equity in health, Stockholm: Institute for Future Studies, 1991.

45.

Uhrig SCN. An evaluation of poverty and sexual orientation in the UK. Institute for Social and Economic Research, University of Essex, 2013.

46.

Singer

Clair

. Syndemics and public health: reconceptualizing disease in bio-social context. Med Anthropol Quart 2003; 17: 423–441.

47.

Santos

Beck

. Syndemic conditions associated with increased HIV risk in a global sample of men who have sex with men. Sex Transm Infect 2014; 90: 250–253.

48.

Cole

. Intersectionality and research in psychology. Am Psychol 2009; 64: 170–180.

49.

Mimiaga

O'Cleirigh

Biello

. The effect of psychosocial syndemic production on 4-year HIV incidence and risk behavior in a large cohort of sexually active men who have sex with men. J Acquir Imm Def Syndr 2015; 68: 329–336.

50.

Public Health England. Strategic framework to promote the health and wellbeing of gay, bisexual and other men who have sex with men (Draft document), London: Public Health England, 2014.

51.

Flowers

Knussen

. Has testing been normalized? An analysis of changes in barriers to HIV testing among men who have sex with men between 2000 and 2010 in Scotland, UK. HIV Med 2013; 14: 92–98.

52.

Fisher

Wayal

Smith

. Home sampling for sexually transmitted infections and HIV in men who have sex with men: a prospective observational study. PloS One 2015; 10: e0120810.

Regular STI testing amongst men who have sex with men and use social media is suboptimal – a cross-sectional study

Abstract

Keywords

Introduction

Methods

Study design and population

Statistical analysis

Results

Univariate associations between independent variables and regular STI testing in the previous 12 months

Multivariable logistic regression analysis predicting regular STI testing in the previous 12 months from socio-demographics and sexual health related variables

Discussion

Limitations

Implications

Footnotes

Acknowledgements

Declaration of conflicting interests

Funding

Ethics

Key Message

Prior publication

References