Sexting and Mental Health Among Young Australians Attending a Musical Festival: A Cross Sext-ional Study

Abstract

Sexting is widely prevalent among young adults; however, the impact of sexting on mental health is not fully understood. This study aimed to investigate sexting behavior among young adults (18–30 years) attending an Australian music festival and the impact of sexting on mental health. A paper survey was completed by 776 respondents. Psychological distress (Kessler 6) was classified as “distressed” or “not distressed.” Univariate and logistic regressions were used to test the associations between sexting and distress. In the past 12 months, 53.1 percent of respondents had sent a sexually explicit message, 43.1 percent had sent a sexually explicit image, 61.2 percent had received a sexually explicit message, and 55.1 percent had received a sexually explicit image. Three quarters of respondents (73.1 percent) felt that sexting could have a positive impact. No association was found between the frequency of sending and receiving sexually explicit images or messages in univariate analyses. However, the more unwanted messages/images were received in the past year, the more likely respondents were to be distressed as seen in univariate analyses. After adjusting for gender, sexual orientation, and alcohol, people who received 5 or more unsolicited messages were 2.4 times more likely to be distressed (odds ratio = 2.42, 95% confidence interval = 1.33–4.40, p = 0.004). In conclusion, this study showed that sexting is common and that the more unsolicited sexts that were received, the higher the distress level. Policymakers and program developers should be aware of the positive and negative impact of sexting.

Background

Given the rise of technology, the changing nature of sexual practices and behavior of young people has received increased attention.¹ There has been particular focus on young adults, as sexual development is a key stage where sexual expression and exploration is important.² Sexually risky behavior among youth has been linked to adverse mental health outcomes.³

The sexual practice of “sexting” is sending or receiving messages, photographs or videos of a sexual nature on any platform, for example, text, Facebook, Snapchat, or Tinder, is prevalent among young adults.⁴ Yeung et al. investigated the prevalence and attitudes toward sexting among Australian young people at a music festival.⁴ They found ∼40 percent of participants, 16–29 years of age, were engaged in the sending or receiving sexually explicit material in their lifetime. Similarly, among Australians 13 years and older, Lee et al. found that in the participants' entire lifetime 49 percent had sent a sexually explicit image/video and 67 percent had received a sexual image.⁵

Previous studies into effects of sexting on mental wellbeing have returned mixed results. A 2014 systematic review by Klettke et al. of sexting⁶ and its correlates included four studies addressing psychological distress. Two of the four studies,^7,8 both from the United States, found no correlation between sexting and depression, self-esteem, or anxiety; or was sexting a marker of poor mental health. One study by Dake et al. found a correlation between previous sexting and feelings of sadness, hopelessness, suicidal thoughts, and attempts in a population of middle and high schoolers in the United States.⁹ Conversely, Englander¹⁰ found college students who sexted were less likely to have experienced depression. Several studies have also found an association between sexting and increased risk of risky sexual behaviors, such as the use of alcohol and/or illicit drugs before sexual intercourse.^2,11 However, the implications of this risk on physical and/or mental health was not examined.

Music festivals attract a large number of attendees less than the age of 30, and attendees are an at risk population for substance abuse and risky sexual behavior,^12,13 making it an ideal context to study the relationship between sexting and mental health.

In summary, sexting is widely prevalent among young adults; however, the impact of sexting on mental health is not yet fully understood. In addition, the positive impact of sexting has not been researched widely. Therefore, this study aimed to investigate sexting behavior among young adults attending an Australian music festival and the impact of sexting on mental health.

Methods

Survey development

The survey content and design were guided by previous research,^14,15 using validated tools and members of the research team who had expertise in the areas of sexual and mental health. The survey was piloted twice with groups representative of the target demographic (n = 20) and the survey content was refined. The study was approved by Western Sydney University Human Research Ethics Committee (H11327).

Outcome measures

Respondents were asked about gender, age, rurality, relationship status, sexual orientation, study status, employment status, and sexting behaviors over the past 12 months. Sexting behaviors were categorized into four groups: sending sexually explicit messages, receiving sexually explicit messages, sending sexually explicit images, and receiving sexually explicit images. Further questions included impact of sextings on their mental health. The audit-C was used to measure alcohol intake.¹⁶ Other risky sexual behaviors were assessed based on findings in previous surveys of a similar population.^14,15

The Kessler 6 (K6), a validated psychological distress scale, was used to measure psychological distress,¹⁷ allowing for comparison with similar studies.^18–20 K6 is widely recognized, and has been used by the Australian Bureau of Statistics in the Australian National Survey of Mental Health and Wellbeing,²¹ and the U.S. National Health Interview Survey.²² Furukawa et al.²¹ evaluated K6 against other screening scales and found K6 preferable because of its brevity and consistency. Our cutoff score for psychological distress was based on data of Furukawa et al., which showed an increased chance of having or developing a serious mental health disorder for scores ≥12. Hence, we classified scores of 6–11 as “Not Distressed,” and 12–30 as “Distressed” (see Supplementary Data).

Data collection

The data collection for this study was undertaken over 4 days at a major music festival in New South Wales. Attendees within the target age group were approached, invited to complete the survey, and given a participant information sheet. The data collection was convenience sampling because of the location and time constraints of the music festival. Completion of the survey was considered as providing consent. Surveys were completed anonymously with private areas available for completion, and placed into a closed box to ensure confidentiality. No identifying data were collected. No visibly intoxicated person was invited to complete the study. No incentives were provided.

Data analysis

Data were analyzed using SPSS version 22. Pearson χ² tests were run to compare categorical variables. A value of p < 0.05 was considered statistically significant. Cronbach's alpha was calculated to determine internal consistency for the K6. Crude and adjusted odds ratios (ORs) were calculated with binary logistic regression to determine which demographic factors and sexting behaviors were associated with psychological distress, and to determine which groups received more unwanted sexts. Variables that were significant in the univariate analysis were entered into the logistic regression model.

Results

Demographics and sexting prevalence

A total of 776 respondents completed the survey. Females comprised 63.7 percent of respondents. The highest proportion (49.4 percent) of respondents were 21–24 years of age, 85.3 percent lived in urban areas, 49.0 percent were in a relationship, 89.4 percent identified as heterosexual. Of the respondents, 56.6 percent reported studying part-time or full-time, and 91.9 percent reported some level of employment.

A slight majority (53.1 percent) had sent a sexually explicit message in the past 12 months and 43.1 percent had sent a sexually explicit image. Of respondents, 61.2 percent had received a sexually explicit message and 55.1 percent had received a sexually explicit image in the past 12 months.

Sexting and demographics

Sexting behaviors were not significantly different between men and women, except that men were more likely to have received an image in the past 12 months (p = 0.004). Lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI) respondents were more likely to have sent a message (p = 0.026) or image (p ≤ 0.001) but were not more likely to receive messages or images. Respondents who were in a relationship were more likely to have sent an image (p = 0.010), with no difference in other sexting behaviors. Age, rurality, study, and employment status were not significantly correlated with sexting behaviors (Table 1).

Table 1.

Prevalence of Sexting Behaviors in the Last 12 Months by Demographics

	Did not send messages % (n)	Sent messages % (n)	p	Did not send images % (n)	Sent images % (n)	p	Did not receive messages % (n)	Received messages % (n)	p	Did not receive images % (n)	Received images % (n)	p
Gender
Male (n = 277)	43.5 (120)	56.5 (156)	0.231	59.6 (164)	40.4 (111)	0.276	36.8 (102)	63.2 (175)	0.345	38.3 (106)	61.7 (171)	0.004
Female (n = 494)	48.0 (236)	52.0 (256)		55.6 (274)	44.4 (219)		40.3 (199)	59.7 (295)		48.5 (241)	51.1 (252)	0.004
Age, years
18–20 (n = 292)	47.9 (139)	52.1 (151)	0.123	56.9 (165)	43.1 (125)	0.801	38.0 (111)	62.0 (181)	0.939	42.6 (124)	57.4 (167)	0.586
21–24 (n = 383)	47.1 (180)	52.9 (202)		57.7 (221)	42.3 (162)		39.2 (150)	60.8 (233)		46.0 (176)	54.4 (207)
25–30 (n = 101)	36.6 (37)	63.4 (64)		54.0 (54)	46.0 (46)		39.6 (40)	60.4 (61)		47.5 (48)	52.5 (53)
Sexual orientation
Hetero (n = 681)	47.6 (323)	52.4 (355)	0.026	59.6 (404)	40.4 (274)	<0.001	40.1 (273)	59.9 (408	0.082	46.0 (313)	54.0 (367)	0.265
LGBTIQ+ (n = 81)	34.6 (28)	65.4 (53)		38.3 (31)	61.7 (50)		29.6 (24)	70.4 (57)		39.5 (32)	60.5 (49)	0.265
Relationship status
Single (n = 394)	48.7 (191)	51.3 (201)	0.168	61.6 (241)	38.4 (150)	0.010	37.1 (146)	62.9 (248)	0.261	41.5 (163)	58.5 (230)	0.053
In relationship (n = 378)	43.8 (165)	56.2 (202)		52.4 (198)	47.6 (180)		41.0 (155)	59.0 (223)		48.4 (183)	51.6 (195)	0.053
Rurality (modified Monash Model)
Urban (n = 649)	44.5 (288)	55.5 (359)	0.130	56.2 (365)	43.8 (284)	0.629	38.5 (250)	61.5 (399)	0.837	45.5 (295)	54.5 (354)	0.188
Nonurban (n = 112)	52.3 (58)	47.7 (53)		58.7 (64)	41.3 (45)		37.5 (42)	62.5 (70)		38.7 (43)	61.3 (68)	0.188
Study status
Student (n = 434)	47.2 (204)	52.8 (228)	0.575	56.8 (246)	43.2 (187)	0.805	38.2 (166)	61.8 (268)	0.634	45.5 (197)	54.5 (236)	0.836
Nonstudent (n = 333)	45.2 (150)	54.8 (182)		57.7 (191)	42.3 (140)		39.9 (133)	60.1 (200)		44.7 (149)	55.3 (184)	0.836
Employment status
Unemployed (n = 62)	51.6 (32)	48.4 (30)	0.424	55.7 (34)	44.3 (27)	0.902	46.8 (29)	53.2 (33)	0.433	54.1 (33)	45.9 (28)	0.082
Part-time (n = 398)	47.7 (189)	52.3 (207)		58.0 (231)	42.0 (167)		38.7 (154)	61.3 (244)		47.2 (188)	52.8 (210)
Full-time (n = 304)	43.9 (133)	56.1 (170)		56.6 (171)	43.4 (131)		38.2 (116)	61.8 (188)		40.8 (124)	59.2 (180)

All p-values calculated by Pearson χ² test.

Bold values indicate that p-value is significant at p < 0.05.

LGBTIQ+, lesbian, gay, bisexual, transgender/gender diverse, intersex and queer.

Distress prevalence and demographics

Of total respondents, 55.3 percent reported a K6 score of 12 and above and categorized as distressed. Women and LGBTQI respondents were more likely to be distressed (p = 0.003 and p = 0.009, respectively). Cronbach's alpha was 86 percent. Age, relationship status, rurality, study, and employment status had no significant correlation with distress (Table 2).

Table 2.

Demographics Versus Distress

	Total (N)	No distress % (n)	Distress % (n)	p
Gender
Male	272	52.6 (143)	47.4 (129)	0.003
Female	484	40.5 (196)	59.5 (288)	0.003
Age, years
18–20	287	42.2 (121)	57.8 (166)	0.199
21–24	376	47.9 (180)	52.1 (196)
25–30	98	39.8 (39)	60.2 (59)
Sexual orientation
Heterosexual	666	46.1 (307)	53.9 (359)	0.009
LGBTQI	81	30.9 (25)	69.1 (56)	0.009
Relationship status
Single	387	41.6 (161)	58.4 (226)	0.720
In a relationship	370	48.1 (178)	51.9 (192)	0.720
Rurality (modified Monash Model)
Urban	635	44.1 (280)	55.9 (355)	0.590
Nonurban	111	46.8 (52)	53.2 (59)	0.590
Study status
Student	430	44.9 (193)	55.1 (237)	0.897
Nonstudent	322	44.4 (143)	55.6 (179)	0.897
Employment status
Unemployed	61	41 (25)	59 (36)	0.152
Part-time	390	41.5 (162)	58.5 (228)
Full-time	298	48.7 (145)	51.3 (153)

All p-values calculated by Pearson χ² test.

Bold values indicate that p-value is significant at p < 0.05.

LGBTQI, Lesbian, gay, bisexual, transgender, queer, and intersex.

Distress versus sexting and alcohol

An association between receiving unsolicited or unwanted sexts and distress was found, but not for other sexting behaviors. Respondents who had received unsolicited or unwanted sexts in the past 12 months were more distressed and the more sexts they received the more likely they were to be distressed (p = 0.002). Respondents who consumed more than six standard alcoholic drinks in one occasion at least once a month, were less likely to be distressed than those who did not (p = 0.008) (Table 3).

Table 3.

Sexting Behavior Versus Distress

	Total	No distress % (n)	Distress % (n)	p
In the last 12 months, how often have you sent sexually explicit messages?
Never	348	46.6 (162)	53.4 (186)	0.579
Monthly or less	206	44.7 (92)	55.3 (114)
2–3 times a month	103	38.8 (40)	61.2 (63)
2–3 times a week or more	101	43.6 (44)	56.4 (57)
In the last 12 months, how often have you sent sexually explicit images?
Never	431	45.2 (195)	54.8 (236)	0.253
Monthly or less	203	47.8 (97)	52.2 (106)
2–3 times a month	68	33.8 (23)	66.2 (45)
2–3 times a week or more	56	44.6 (25)	55.4 (31)
In the last 12 months, how often have you received sexually explicit messages?
Never	293	47.1 (138)	52.9 (155)	0.237
Monthly or less	233	47.2 (110)	52.8 (123)
2–3 times a month	114	38.6 (44)	61.4 (70)
2–3 times a week or more	121	39.7 (48)	60.3 (73)
In the last 12 months, how often have you received sexually explicit images?
Never	338	45.0 (152)	55.0 (186)	0.293
Monthly or less	239	48.5 (116)	51.5 (123)
2–3 times a month	95	37.9 (36)	62.1 (59)
2–3 times a week or more	88	40.9 (36)	59.1 (52)
In the last 12 months, how often have you received unsolicited sext messages/images?
None	470	49.6 (233)	50.4 (237)	0.002
1 or 2	136	42.6 (58)	57.4 (78)
3–5	73	34.2 (25)	65.8 (48)
5–10	27	25.9 (7)	74.1 (20)
>10	40	27.5 (11)	72.5 (29)
How often do you have more than six drinks on one occasion?
Less than monthly	150	33.3 (50)	66.7 (100)	0.008
Monthly	305	47.9 (146)	52.1 (159)
More than monthly	301	46.8 (141)	53.2 (160)

All p-values calculated by Pearson χ² test.

Bold values indicate that p-value is significant at p < 0.05.

Attitudes toward sexting

Overwhelmingly respondents thought that sexting can have a positive impact (73.1 percent, n = 564). When asked if sexting behaviors had an effect on their mood, the majority reported no or positive impact. Receiving sexually explicit images was the sexting behavior most likely to be associated with reported negative impact on mood (9.6 percent, n = 41) (Table 4).

Table 4.

Sexting and Impact on Mood

	% (n)
Do you think sexting can have a positive impact?
Yes	73.1 (564)
No	9.8 (76)
Unsure	17.1 (132)
Total	100 (776)
In the last 12 months, how often has sending sexually explicit messages affected your mood?
Negative impact	4.3 (18)
No impact	51 (214)
Positive impact	44.8 (188)
Total	100 (420)
In the last 12 months, how often has sending sexually explicit images affected your mood?
Negative impact	6 (20)
No impact	46.9 (157)
Positive impact	47.2 (158)
Total	100 (335)
In the last 12 months, how often has receiving sexually explicit messages affected your mood?
Negative impact	8.4 (40)
No impact	43.9 (208)
Positive impact	47.7 (226)
Total	100 (474)
In the last 12 months, how often has receiving sexually explicit images affected your mood?
Negative impact	9.6 (41)
No impact	45.8 (196)
Positive impact	44.6 (191)
Total	100 (428)

ORs for distress

Table 5 provides the multivariate model of distress based on the variables of receiving unsolicited sexts, gender, sexual orientation, and binge drinking behavior. Receiving unsolicited sext messages was a significant predictor of distress, after adjusting for gender, sexual orientation, and alcohol intake. Respondents who had received between three and five unsolicited sext messages in the previous 12 months were twice as likely to be distressed (OR = 2.06, 95% confidence interval [CI] = 1.20–3.56, p = 0.010). Respondents who had received more than five unsolicited sexts in the past 12 months had 2.4 times the odds of being distressed (OR = 2.42, 95% CI = 1.33–4.40, p = 0.004). LGBTQI respondents had 1.8 higher odds of being distressed compared with heterosexuals (OR = 1.82, 95% CI = 1.07–3.12, p = 0.028). Women had higher odds of being distressed compared with men (OR = 1.46, 95% CI = 1.05–2.02, p = 0.021). Drinking more than six drinks on one occasion was predictive for reduced distress, with participants who drank that amount monthly (OR = 0.56, 95% CI = 0.37–0.86, p = 0.008) or weekly (OR = 0.60, 95% CI = 0.39–0.91, p = 0.017) having a lower likelihood of being distressed than those who binge drank rarely or never.

Table 5.

Crude and Adjusted Odds Ratios of Receiving Unwanted Messages/Images Gender, Sexual Orientation, and Alcohol Intake with Psychological Distress (N = 722)

	OR (crude)	95% CI	p	OR (adjusted)	95% CI	p
Receiving unsolicited messages/images
None	1.000			1.000	—	—
1–2	1.322	0.900–1.943	0.155	1.327	0.889–1.980	0.166
3–5	1.888	1.127–3.163	0.016	2.062	1.193–3.564	0.010
5+	2.676	1.514–4.731	0.001	2.417	1.329–4.397	0.004
Gender
Male	1.000	.	.	1.000
Female	1.629	1.208–2197	0.001	1.463	1.060–2.019	0.021
Sexual orientation
Heterosexual	1.000			1.000
LGBTIQ+	1.916	1.167–3.144	0.010	1.822	1.066–3.117	0.028
More than six drinks on one occasion
Never/less than monthly	1.000			1.000
Monthly	0.545	0.362–0.818	0.003	0.563	0.369–0.860	0.008
Weekly or more	0.567	0.377–0.853	0.006	0.596	0.390–0.913	0.017

Bold values indicate that p-value is significant at p < 0.05.

CI, confidence interval; OR, odds ratio.

Discussion

This study explored sexting behavior among music festival attendees and its impact on young adult mental health. An association between receiving unsolicited or unwanted sexts and distress was found, but not for other sexting behaviors. Furthermore, receiving unsolicited sexts was associated with distress even after adjusting for gender, sexual orientation, and alcohol intake. Other key findings were that sexting is common and a majority of participants reported that sending or receiving sexually explicit messages had no impact or a positive impact on their mood.

Univariate analyses demonstrated that the frequency of sending or receiving sexually explicit messages or images was not associated with distress. These findings contribute to the mixed results that have been found in the literature⁶ and are consistent with some of the wider international research on the interaction between sexting and mental health.^6,8,11 Of importance, recent 2019 research has indicated that coerced/pressured sexting is associated with psychological distress.²³ In the absence of a coercion measure in our study, our findings need to be interpreted with care. It is also possible that festival patrons are not representative of the general young adult population and differ from the convenience sample by Klettke et al. who recruited participants through social media and university campus and e-mail distributions. The prevalence of sexting in younger age groups (e.g., 13- to 17-year-olds) and its impact on mental health is a potential area for future research, especially given the impact of factors such as sexual identity on mental health,²⁴ and the increasing prevalence of serious mental illness in young people.^25,26

A significant relationship between receiving unsolicited sext messages and distress was found. It is acknowledged that it may not be the sexting practices per se, but the degree to which these practices are consensual that matters. Current literature places focus on the nonconsensual redistribution of sexts by receivers or third parties. Klettke et al. in their 2019 article²³ found that receiving unsolicited sexual images or sending them under coercion was correlated with symptoms of distress, anxiety, or stress, concurring with our findings. A qualitative study by Burkett found that receiving unsolicited sexts were threatening and induced a sense of risk and danger in the recipient, and found the motivation of senders to be a sense of normalization of this behavior.²⁷ Reyns et al.²⁸ found that sexting is a risk factor for online sexual harassment, including receiving unsolicited messages. A systematic review of unsolicited and nonconsensual sexting by Krieger²⁹ identified that current literature is focused on exploring other risky sexual behaviors as predictors of unsolicited sexting and attitudes toward nonconsensual sexting.³⁰ Livingston et al. found among an adolescent population 11 percent had received unsolicited sexts.³¹ One in five of that subgroup were bothered by receiving unsolicited sexts. The higher prevalence of receiving unsolicited sexts in our sample could be because of the older population.

Sexting seems to be common. Our study found that 53.1 percent of respondents had sent a sexually explicit message, similar rates were found in a university population in the United States at 67.4 percent.³² This study by Dir et al. found men received sexually explicit images more frequently, as did our study (61.7 percent of all male respondents). Their article showed those in a relationship sent more sexually explicit texts than single respondents, as did our article.

A proportion of respondents believed that sexting behaviors had a negative effect on their mood. Further studies may focus on the reasons for these negative attitudes toward sexting, and whether these attitudes are associated with specific sexting behaviors or experiences (e.g., sharing of images without consent). The overall positive attitude toward sexting is consistent with previous research. Yeung et al. explored attitudes toward sexting among people 16–25 years of age, finding sexting to be a “common and normalised aspect of sexual development.”⁴ Furthermore, Burkett's qualitative study found sexting to be a positive experience in relationships compared with casual sexual encounters.²⁷ Hence, these attitudes toward sexting can be considered representative of the target population but we acknowledge that this can be moderated by other factors including consent and coercion. This study expanded on the current literature findings concludes that festival patrons perceived sexting to have a neutral or positive impact on mood.

Limitations

One limitation of this study was the inability to show causal effects because of the cross-sectional study design; therefore, further research involving a longitudinal study examining the relationship between sexting and mental health over time is required.

As stated previously, the lack of a coercion measure is also recognized as a study limitation. If the study would have measured coercion factors, it could mean that sexting under coercion may have lead to different study results. A 2018 meta-analyses among youth showed that the prevalence of forwarding a sext without consent was 12.0 percent (95% CI = 8.4–15.6), and the prevalence of having a sext forwarded without consent was 8.4 percent (95% CI = 4.7–12.0).³³ It could therefore be that among those who were coerced or had not consented to the sexting activities could have experienced higher psychological distress. We recommend that future studies include coercion measures.

In addition, music festival attendees may not be representative of the general 18- to 30-year-old population. However, the demographics of the population sampled were similar to previous studies undertaken at the same music festival and show consistency across this population.^15,34 Our population mostly comprised people living in urban areas, consistent with ABS statistics showing a higher representation of people 20–44 years of age living in capital cities.³⁵

Another limitation was that attendees were invited to complete the survey based on a convenience sampling method. Thus, the study may have some sampling error. This recruitment method was selected because it gave access to a high-risk group of young adults. However, the frequency of sexting within our study is comparable with previous studies on sexting, as another Australian music festival study⁴ found that 40 percent respondents had ever sent or received a sext and a Spanish study found that 36.1 percent had ever sent a sext.³⁶

Finally, information bias may be evident because of self-reporting and the respondents' tendency to provide more socially acceptable answers. This was minimized by providing private areas to facilitate confidential completion of the survey.

Impact

Our findings tentatively point toward a need for a change in the approach toward harm minimization in relation to sexting. Wolak and Fiklehor³⁷ characterized sexting practices as falling into two groups, “aggravated” and “experimental.” Taking a similar approach in an educational context may be useful to help young people identify when they are being pressured into or exposed to potentially harmful sexting activities, and identify when their own actions (such as sending unsolicited sexts) can have harmful effects. Hayes and Drageiweicz³⁸ in their examination of the sending of unsolicited “dick pics” drew a thematic connection between sending unsolicited sexts and the crime of indecent exposure in Australian law.³⁹ In light of the harm we have identified, a debate or consideration of legal reform in regard to unsolicited sexting may be warranted. Further exploration of the impact of unsolicited and nonconsensual sexts on other outcomes, such as study and work productivity, or health outcomes is warranted.

Conclusions

In conclusion, this study showed that sexting is common and that the more unsolicited sexts that were received, the higher the distress level. The majority of festival attendees 18–30 years of age also reported that sending or receiving sexually explicit images or messages had no impact or a positive impact on their mood. The results of this study contribute to the body of knowledge regarding the impact of sexting on psychological distress and further research could explore the impact of unsolicited sexting and include coercion measures. Policymakers and program developers should be aware of the positive and negative impact of sexting.

Footnotes

Acknowledgments

The study group thanks the Positive Adolescent Sexual Health-North Coast Youth Sexual Health Consortium (PASH) for facilitating data collection.

Availability of Data and Materials

The data collected and analyzed during the study are not publicly available because of ethics considerations and data being used for further research.

Author Disclosure Statement

No competing financial interests exist.

Supplementary Material

References

Siegle

. Cyberbullying and sexting: technology abuses of the 21st century. Technology, 2010; 32:14–17.

Ybarra

, Mitchell

. “Sexting” and its relation to sexual activity and sexual risk behavior in a national survey of adolescents. Journal of Adolescent Health, 2014; 55:757–764.

Ramrakhta

, Caspi

, Dickson

, et al. Psychiatric disorders and risky sexual behaviour in young adulthood: cross sectional study in birth cohort. British Medical Journal, 2000; 321:263–266.

Yeung

, Horyniak

, Vella

, et al. Prevalence, correlates and attitudes towards sexting among young people in Melbourne, Australia. Sexual Health, 2014; 11:332–339.

Lee

, Crofts

, McGovern

, et al. Sexting among young people: perception and practices. Trends & Issues in Crime and Criminal Justice, 2015; 508.

Klettke

, Hallford

, Mello

. Sexting prevalence and correlates: a systematic literature review. Clinical Psychology Review, 2013; 34:44–53.

Hudson

. (2011) Factors affecting sexting behaviors among selected undergraduate students. Carbondale, IL: Southern Illinois Carbondale University.

Gordon-Messer

, Bauermeister

, Grodzinski

, et al. Sexting among young adults. Journal of Adolescent Health, 2013; 52:301–306.

Dake

, Price

, Maziarz

, et al. Prevalence and correlates of sexting behavior in adolescents. American Journal of Sexual Education, 2012; 7:1–15.

10.

Englander

. Low risk associated with most teenage sexting: a study of 617 18-year-olds [Internet]. 2012. http://webhost.bridgew.edu/marc/SEXTING%20AND%20COERCION%20report.pdf (accessed July 20, 2019).

11.

Temple

, Paul

, van den Berg

, et al. Teen sexting and its association with sexual behaviors. Archives of Pediatrics and Adolescent Medicine, 2012; 166:828–833.

12.

Jenkinson

, Bowring

, Dietze

, et al. Young risk takers: alcohol, illicit drugs, and sexual practices among a sample of music festival attendees. Journal of Sexually Transmitted Diseases, 2014; 2014:1–6.

13.

Fox

, Smith

, Yale

, et al. Drugs of abuse and novel psychoactive substances at outdoor music festivals in Colorado. Substance Use & Misuse, 2017; 53:1203–1211.

14.

Hall

, Brieger

, De Silva

, et al. Errors and predictors of confidence in condom use amongst young Australians attending a music festival. Journal of Sexually Transmitted Diseases, 2016:1–9.

15.

Day

, Criss

, Griffiths

, et al. Music festival attendees' illicit drug use, knowledge and practices regarding drug content and purity: a cross-sectional survey. Harm Reduction Journal, 2018; 15:1–8.

16.

Tam

, Knight

, Liaw

. Alcohol screening and brief interventions in primary care—evidence and a pragmatic practice-based approach. Australian Family Physician [Serial Online], 2016; 45:767–777.

17.

Kessler

, Barker

, Colpe

, et al. Screening for serious mental illness in the general population. Archives of General Psychiatry, 2003; 60:184–189.

18.

Schneider

, Richters

, Butler

, et al. Psychological distress and experience of sexual and physical assault among Australian prisoners. Criminal Behaviour and Mental Health, 2011; 21:333–349.

19.

Edwards

, Black

, Dhingra

, et al. Physical and sexual intimate partner violence and reported serious psychological distress in the 2007 BRFSS. International Journal of Public Health, 2009; 54(S1):37–42.

20.

Sunderland

, Slade

, Stewart

, et al. Estimating the prevalence of DSM-IV Mental Illness in the Australian General Population using the Kessler Psychological Distress Scale. Australian & New Zealand Journal of Psychiatry, 2011; 45:880–889.

21.

Furukawa

, Kessler

, Slade

, et al. The performance of the K6 and K10 screening scales for psychological distress in the Australian National Survey of Mental Health and Well-Being. Psychological Medicine [Serial Online], 2003; 33:357–362.

22.

Kesseler

, Andrews

, Colpe

, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine [Serial Online], 2002; 32:959–976.

23.

Klettke

, Hallford

, Clancy

, et al. Sexting and psychological distress: the role of unwanted and coerced sexts. Cyberpsychology, Behavior, and Social Networking, 2019; 22:237–242.

24.

Ahern

, Mechling

. Sexting: serious problems for youth. Journal of Psychosocial Nursing and Mental Health Services, 2013; 51:22–30.

25.

Youth Mental Health Report. Mission Australia. 2017. https://blackdoginstitute.org.au/docs/default-source/research/evidence-and-policy-section/2017-youth-mental-health-report_mission-australia-and-black-dog-institute.pdf?sfvrsn=6 (accessed July 20, 2019)

26.

Lawrence

, Johnson

, Hafekost

, et al. The mental health of children and adolescents. Report on the Second Australian Child and Adolescent Survey of Mental Health and Wellbeing. Department of Health, Canberra, 2015.

27.

Burkett

. Sex(t) talk: a qualitative analysis of young adults' negotiations of the pleasures and perils of sexting. Sexuality & Culture, 2015; 19:835–863.

28.

Reyns

, Burek

, Henson

, et al. The unintended consequences of digital technology: exploring the relationship between sexting and cybervictimization. Journal of Crime and Justice, 2013; 36:1–17.

29.

Krieger

. Unpacking ‘sexting’: a systematic review of non consensual sexting in legal, educational, and psychological literatures. Trauma, Violence and Abuse, 2017; 18:593–601.

30.

Salter

, Crofts

, Lee

. Beyond criminalisation and responsibilisation: sexting, gender and young people. Current Issues in Criminal Justice, 2013; 24:301–316.

31.

Livingstone

, Haddon

, Görzig

, et al. Risks and safety for children on the internet: the UK report [Internet]. Eprints.lse.ac.]uk. 2010 [cited October 1, 2018]. http://eprints.lse.ac.uk/33730/1/EU_Kids_Online_Report_April2014.pdf (accessed July 20, 2019).

32.

Dir

, Coskunpinar

, Steiner

, et al. Understanding differences in sexting behaviors across gender, relationship status, and sexual identity, and the role of expectancies in sexting. Cyberpsychology, Behavior, and Social Networking, 2013; 16:568–574.

33.

Madigan

, Ly

, Rash

, et al. Prevalence of multiple forms of sexting behavior among youth: a systematic review and meta-analysis. JAMA Pediatrics, 2018; 172:327–335.

34.

Fernando

, Buckland

, Melwani

, et al. Perceived driving safety and estimated blood alcohol concentration (BAC) the morning after drinking amongst young Australians attending a music festival: a cross-sectional survey. Substance Abuse Treatment, Prevention, and Policy, 2018; 13:25.

35.

Australian Bureau of Statistics (2016). Population by age and sex, regions of Australia. Canberra, Australia: Australian Bureau of Statistics.

36.

Gámez-Guadix

, de Santisteban

, Resett

. Sexting among Spanish adolescents: prevalence and personality profiles. Psicothema, 2017; 29:29–34.

37.

Wolak

, Fikelhor

(2011). Sexting: a typology. Durham, NC: Crimes Against Children Research Centre.

38.

Hayes

, Dragiewicz

. Unsolicited dick pics: Erotica, exhibitionism or entitlement?. Women's Studies International Forum, 2018; 71:114–120.

39.

Summary Offences Act. NSW, Australia 1988.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB