Teen girls who suffered sexual abuse may face more online victimization, exploitation

Teen girls who experienced sexual abuse were more likely than their peers to be cyberbullied, according to a study published in Nature Human Behavior.

These girls also logged higher usage of pornography and social media, which led to being sexually solicited online and engaging in more sexual activity 2 years later.

“There are some problems with prior internet research given that all prior studies relied on kids' self-reported internet activity,” Jennie G. Noll, PhD, professor of human development and family studies and director of the Child Maltreatment Solutions Network at Penn State University in State College, Pennsylvania, said in a university press release.

“Asking kids about how much time they spend online, or on social media, or if they ever view pornography could provide inaccurate data given that kids may not know exactly how much time they spend in certain activities or may not want to admit that they view adult content. Our team sought to raise the rigor of research by actually observing what kids are doing,” Noll continued.

Noll said that previous research has found conflicting results about whether the internet can impact teen development, with some finding little to no harm with the opportunity for socializing being beneficial, and others finding links to depression, less sleep and poorer school performance.

The observational study assessed 2 years of URL activity and offline psychosocial factors of 460 consenting girls aged 12 to 16 years. Of these, 156 experienced substantial sexual abuse, and 304 in a comparison group did not. The comparison group was further broken down into girls who were the same ethnicities and from the same neighborhoods and income-levels as those who were abused, as well as girls who were “census matched” to the sociodemographics of the study’s region.

The researchers did not make all data publicly available due to containing “extremely sensitive information that could compromise research participant privacy and confidentiality.”

They analyzed data using latent profile analysis to sort participants into one of three groups: a low-risk group of those with low internet use and little substance abuse but high levels of protective factors; a moderate-risk group of those with moderately high levels of internet use but low or middle levels of other risk factors; and a high-risk group of those with frequent internet use who viewed more pornography, reported higher levels of substance abuse and experienced low levels of support and self-esteem.

Noll said that girls who had been sexually abused were most likely to fit the high-risk profile.

“Girls in this profile were the ones who were more likely to view pornography, be cyberbullied and be sexually solicited online,” Noll said. “Compared to the census-matched group, sexually abused girls were also more likely to meet strangers offline where the encounter ended up in sexual assault or attempted assault."

Girls who experienced child sexual abuse did not use more pornography than comparisons but were at increased odds of being cyberbullied (OR=2.84; 95% CI,1.67-4.81).

“These females were also more likely to be represented in a high-risk latent profile characterized by heightened URL activity coupled with problematic psychosocial factors, which showed increased odds of being cyberbullied, receiving online sexual solicitations and heightened sexual activity. While Internet activity alone may not confer risk, results indicate a subset of teens who have experienced [child sexual abuse] for whom both online and offline factors contribute to problematic outcomes,” the researchers wrote in the study.

In the press release, Noll added that there appeared to be “something lingering and lasting regarding the traumatic sexualization that can accompany childhood sexual abuse that sets the stage for victimization that is unique to the rise of the internet,” and suggested the study might assist in developing recovery treatments.

“These at-risk teens have very distinct internet usage patterns, suggesting an opportunity to use machine learning techniques that would recognize at-risk kids based on the URLs they visit and then deliver targeted prevention messaged directly to their newsfeeds and the apps they use,” Noll said. “We're smart enough to use such algorithms for target marketing and to sell consumers all kinds of goods, so why not employ these same technologies to use the internet for good and to keep kids safe?"

Reference:

At risk teens may face increased online threats. https://eurekalert.org/news-releases/930481. Published Oct. 4, 2021. Accessed Oct. 5, 2021.

Noll JG, et al. Nat Human Behav. 2021;doi:10.1038/s41562-021-01187-5.