online safety research articles

Articles on Online safety

Displaying 1 - 20 of 67 articles.

Meta has a new plan to keep kids safe online, but it’s a missed opportunity for tech giants to work together

Toby Murray , The University of Melbourne

Roblox was just banned in Turkey to ‘protect children’. What’s Australia doing?

Ausma Bernot , Griffith University and Joel Scanlan , University of Tasmania

Social media: Disinformation expert offers 3 safety tips in a time of fake news and dodgy influencers

Fabrice Lollia , Université Gustave Eiffel

Is your child’s photo on their school Facebook page? What does this mean for their privacy?

Karley Beckman , University of Wollongong and Tiffani Apps , University of Wollongong

We research online ‘misogynist radicalisation’. Here’s what parents of boys should know

Steven Roberts , Monash University and Stephanie Wescott , Monash University

Big tech companies were open to online safety regulation – why did NZ’s government scrap the idea?

Fiona Sing , University of Auckland, Waipapa Taumata Rau and Antonia Lyons , University of Auckland, Waipapa Taumata Rau

We found over 300 million young people had experienced online sexual abuse and exploitation over the course of our  meta-study

Deborah Fry , The University of Edinburgh

Australia will trial ‘age assurance’ tech to bar children from online porn. What is it and will it work?

Paul Haskell-Dowland , Edith Cowan University

Albanese government flags measures to tackle online misogyny in the battle against violence towards women

Michelle Grattan , University of Canberra

Elon Musk is mad he’s been ordered to remove Sydney church stabbing videos from X. He’d be more furious if he saw our other laws

Rob Nicholls , University of Sydney

Deepfake porn: why we need to make it a crime to create it, not just share it

Clare McGlynn , Durham University

Online child safety laws could help or hurt – 2 pediatricians explain what’s likely to work and what isn’t

Megan Moreno , University of Wisconsin-Madison and Jenny Radesky , University of Michigan

Digital trade protocol for Africa: why it matters, what’s in it and what’s still missing

Franziska Sucker , University of the Witwatersrand

What is doxing, and how can you protect yourself?

Rob Cover , RMIT University

Teens on social media need both protection and privacy – AI could help get the balance right

Afsaneh Razi , Drexel University

Canada should not fall behind on implementing safety measures for children online

Azfar Adib , Concordia University

How to protect yourself from cyber-scammers over the festive period

Rachael Medhurst , University of South Wales

Protecting kids online: A guide for parents on conversations about ‘sextortion’

Camille Mori , University of Calgary and Sheri Madigan , University of Calgary

When to give your child their first mobile phone – and how to keep them safe

Andy Phippen , Bournemouth University

The vast majority of us have no idea what the padlock icon on our internet browser is – and it’s putting us at risk

Fiona Carroll , Cardiff Metropolitan University

Related Topics

• Children online
• Cybersecurity
• Internet use
• Online abuse
• Social media

Top contributors

Researcher: Digital Literacy and Digital Wellbeing, Western Sydney University

Professor of Cyber Security Practice, Edith Cowan University

Professor of IT Ethics and Digital Rights, Bournemouth University

Senior Lecturer in Digital Cultures, SOAR Fellow., University of Sydney

PhD candidate researching children's play in digital games, The University of Melbourne

Associate Professor of Criminology, Monash University

Executive Director, Arizona State University

Associate Professor, Sociology, Athabasca University

Professor, Cyber Security, Aston University

Professor & Australian Research Council Future Fellow, Social and Global Studies Centre, RMIT University

Dean of Global Business, The Fletcher School, Tufts University

Professor, Family and Sexual Violence, RMIT University

Senior Lecturer in Education, University of Newcastle

Senior Lecturer, Journalism and Digital Communication, University of Central Lancashire

Professor of Information Technology Management, University at Albany, State University of New York

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September 18, 2023

Here’s How to Actually Keep Kids and Teens Safe Online

Controversial policy proposals such as the Kids Online Safety Act (KOSA) are making headway across the country, but there are other ways to help protect young people in the digital world

By Lauren Leffer

fotostorm/Getty Images

The Internet can be a risky place. There are endless feeds filled with posts that contain graphic sexual and violent content, glamorize eating disorders, encourage self-harm or promote discriminatory and offensive diatribes. People often share too much personal information with a too-public audience that includes cyberbullies and strangers with ill intent. And they also risk losing time: by spending hours online, they might miss out on experiences and growth opportunities that can be found elsewhere. These problems are particularly acute for children and teenagers, and new laws that attempt to protect youth from the Internet’s negative effects have their own serious downsides. Scientific American spoke with experts about the best evidence-backed ways to actually keep kids safe online.

Young people spend a huge chunk of their lives on the Internet. For most teens in the U.S., the bulk of their waking hours play out in front of network-connected screens, according to surveys from the nonprofit organization Common Sense and from the American Academy of Child and Adolescent Psychiatry . Kids younger than age 13 aren’t that far behind; they spend upward of five hours online daily.

Though the exact impacts of online activity aren’t yet well understood , it’s clear that what happens on the Internet does matter for young people’s well-being. “I don’t know that we can say ‘cause and effect’ at this point,” says Mary Alvord, a practicing psychologist who specializes in treating children and adolescents and is an adjunct associate professor at the George Washington University School of Medicine. “But we can make correlational statements,” she adds, noting that excessive time spent on social media has been associated with poor mental health among kids and teens.

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Both the U.S. Surgeon General and the American Psychological Association issued health advisories earlier this year about potential harms of online social media to youth. Each advisory is clear: online activity carries benefits and risks, and more work is needed to understand and mitigate the downsides.

In recent months lawmakers have introduced and enacted policies ostensibly aimed at doing just that. Multiple states have imposed age restrictions for certain types of online content. At the national level, the Kids Online Safety Act (KOSA) has advanced out of a Senate committee and awaits consideration on the legislative floor. But experts are divided on whether age-restriction efforts and sweeping policies such as KOSA are set to help young people or harm them.

Proponents of KOSA, including the American Psychological Association, say that the legislation could be a positive first step toward holding tech companies accountable for their impact. Conversely, critics such as the American Civil Liberties Union fear that some of its provisions will reduce online freedoms, restrict access to information and penalize vulnerable populations such as LGBTQ+ youth by leaving the moderation and definition of harmful content up to state officials, who may have their own political agendas. Earlier this month one co-sponsor of the bill, Senator Marsha Blackburn of Tennessee, appeared to imply that in her state, KOSA would be used to block minors from accessing information about transgender issues. Jamie Susskind, Senator Blackburn’s legislative director, has denied the senator was making any claims about using KOSA to censor trans content. “KOSA will not—nor was it designed to—target or censor any individual or community,” Susskind posted on X (formerly Twitter).*

But these controversial policies aren’t the only way to promote online safety. Other legislative actions that are less focused on censorship, along with clear content guidelines and better social media design, could help. Plus, digital safety researchers and psychologists agree that getting families, schools and young people themselves involved would make a big difference in keeping kids safe.

Digital privacy legislation is one alternate policy path that might shift the online landscape for the better. “If people’s data is treated with respect in ways that are transparent and accountable, actually, it turns out a whole set of safety risks get mitigated,” says social psychologist Sonia Livingstone, who researches children and online media at the London School of Economics and Political Science.

A comprehensive data privacy bill could require social media companies to disclose when user data are being collected and sold—and to obtain consent first. This would help users make better choices for themselves, Livingstone says. Limiting the data that tech platforms amass and profit from could also help block the proliferation of algorithms that emphasize increasingly extreme content in order to hold social media users’ attention. Additionally, privacy legislation could ideally enable users to request the removal of content or data they no longer want online—potentially protecting kids (and everyone else) from their own short-term choices, Alvord says.

Beyond privacy, national guidelines for social media sites could help. Livingstone and Alvord suggest that a content rating system like those used for movies, TV shows and video games might help young people avoid inappropriate content—and allow families to set firmer boundaries. Design features that let users block others and limit the audience for specific posts allow kids and teens to take the reins of their own safety—which is critical, says Pamela Wisniewski, a Vanderbilt University computer scientist, who studies human-computer interaction and adolescent online safety.

Parental controls can be appropriate for younger kids, but teens need the chance to exercise autonomy online, Wisniewski says. Such freedom lets them engage in some of the Internet’s positive aspects: civic engagement opportunities, community and educational resources, identity exploration and connections beyond one’s own social bubble. To ensure these benefits are accessible to all, youth should be directly involved formulating regulations and safety strategies, Wisniewski adds. As part of her research, she holds workshops with teens to involve them in co-designing online safety interventions. Though this program, called Teenovate, is in the early stages, some ideas have already emerged from it. Among them: social platforms could provide “nudges” that would ask users to think twice before sharing personal data and prompt would-be bad actors to reconsider personal requests or bullying behavior.

Education is another important way to reach young people. They may be digital natives, but there’s a lot for them to learn about engaging with the Internet safely. “You ask young people what they would like to learn about in school; they would love better digital literacy,” Livingstone says. “They’d love to be taught about data ecology. They’d love to understand how algorithms work.” And existing coursework should adapt to include discussions of online issues, Wisniewski adds. For instance, sex education classes could add modules about dealing with sexual solicitation online or learning safer ways to “sext.” Studies suggest that sexting, or sharing intimate information via digital devices, is practiced by 25 percent to 35 percent of teenagers.

Engaging with the ways youth use the Internet instead of dismissing them is key to improving young people’s experience—at their schools, in their families and under policies that affect them. Kids and teens are often better versed in the latest apps and platforms than their parents are. This dynamic can breed misunderstanding and judgment, and it can make open conversations about online struggles difficult, says psychologist Mitch Prinstein, who studies technology and adolescent development at the University of North Carolina at Chapel Hill. “We’ve inadvertently communicated to our kids that we don’t understand or care and [that] we’re not going to be empathic or interested in talking about their online experiences,” Prinstein explains. “What we should be doing is just the opposite: saying, ‘This seems really important, and you’re spending a lot of time on it.’”

From that place of openness and curiosity, caregivers are much better positioned to help kids and teens develop resilience and healthier online habits. The online world “isn’t good or bad,” Alvord says. “It’s what we make of it, how we use it, how much we use it.” Accepting that “it’s here to stay,” she says, is the first step toward finding real and meaningful safety solutions.

*Editor’s Note (9/18/23): This paragraph was updated after posting to include a comment made on social media by Jamie Susskind, Senator Marsha Blackburn’s legislative director.

• Research article
• Open access
• Published: 05 June 2013

Internet safety education for youth: stakeholder perspectives

• Megan A Moreno 1 , 4 ,
• Katie G Egan 2 ,
• Kaitlyn Bare 1 ,
• Henry N Young 3 &
• Elizabeth D Cox 1  

BMC Public Health volume  13 , Article number:  543 ( 2013 ) Cite this article

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Internet use is nearly ubiquitous among US youth; risks to internet use include cyberbullying, privacy violations and unwanted solicitation. Internet safety education may prevent these negative consequences; however, it is unclear at what age this education should begin and what group is responsible for teaching this topic.

Surveys were distributed to key stakeholders in youth safety education including public school teachers, clinicians, parents and adolescents. Surveys assessed age at which internet safety education should begin, as well as experiences teaching and learning internet safety. Surveys of adults assessed willingness to teach internet safety. Finally, participants were asked to identify a group whose primary responsibility it should be to teach internet safety.

A total of 356 participants completed the survey (93.4% response rate), including 77 teachers, 111 clinicians, 72 parents and 96 adolescents. Stakeholders felt the optimal mean age to begin teaching internet safety was 7.2 years (SD = 2.5), range 2-15. Internet safety was regularly taught by some teachers (20.8%), few clinicians (2.6%) and many parents (40.3%). The majority of teachers, clinicians and parents were willing to teach internet safety, but all groups surveyed identified parents as having primary responsibility for teaching this topic.

Conclusions

Findings suggest agreement among key stakeholders for teaching internet safety at a young age, and for identifying parents as primary teachers of this topic. Clinicians have a unique opportunity to support parents by providing resources, guidance and support.

Peer Review reports

While the internet has provided adolescents with numerous benefits, including increased social support, academic enrichment and worldwide cross-cultural interactions, there are concomitant risks to internet use [ 1 – 8 ]. The American Academy of Pediatrics’ (AAP) recent report on children’s social media use describes specific risks such as privacy violations and cyberbullying [ 9 ]. A previous study found that one-third of adolescents had given their internet password to friends and one-fourth were unaware that content uploaded online cannot be permanently deleted [ 1 ]. Cyberbullying, or internet harassment, impacts up to a third of youth and has been linked to a variety of health concerns, some as serious as suicidal ideation [ 10 – 15 ]. In addition, adolescents frequently display personal and identifiable information about themselves on the internet. These details may include their home location, revealing photographs, or descriptions of sexual behavior and substance use [ 16 – 18 ].

Internet safety is highly salient for today’s youth as they spend up to 10 hours a day using various forms of media [ 8 , 19 , 20 ]. The ever-increasing popularity of social media, including websites such as Facebook and Twitter, have contributed to youth’s time investment in the internet [ 7 ]. The vast majority of adolescents have internet access and most report daily use [ 21 , 22 ]. Several organizations, including the AAP, have offered expert advice regarding internet safety, but an evidence-based approach to educate youth about the dangers of being online does not currently exist [ 23 ]. Further, data to guide decisions about the age at which such education should begin, and who would have primary responsibility for teaching this topic are incomplete.

An ideal approach for teaching internet safety would likely involve a person or group who could reach most children in order to provide widespread dissemination of this knowledge. An ideal candidate would also have experience teaching about the internet or related safety issues, and be willing to invest in teaching this topic. Given that most US youth and adolescents attend public school, a first possibility is public school teachers. However, it is unclear at what grades and in which school subjects this material could be integrated into existing curricula. A second possibility is child health providers such as pediatricians or family medicine physicians. The AAP social media report argues that “pediatricians are in a unique position” to provide internet safety education [ 9 ]. Several resources exist to guide pediatricians in these discussions, but it is unclear whether pediatricians are comfortable in these discussions. Previous work has suggested that pediatrician’s performance of adolescent health behavior screening and prevention counseling regarding health risk behaviors is quite low [ 24 , 25 ]. A third potential candidate is the parent of the adolescent. While adults’ use of online media such as social networking sites continues to rise, data regarding parents’ comfort or experience with teaching internet safety remains elusive [ 26 ]. While all three groups undoubtedly should play a role in online safety education, it remains unclear which group is seen as holding primary responsibility among these stakeholders.

The purpose of this study was to investigate views of key stakeholders on internet safety education, including school teachers, clinicians who see children and adolescents, parents of adolescents, and adolescents themselves. Our goals were to investigate at what age internet safety education should begin, and to identify a primary candidate to teach this topic.

This study was conducted between July 1, 2009 and August 15, 2011 and received IRB approval from the University of Wisconsin Human Subjects Committee.

Setting and subjects

Participants in this study included public school teachers, health care providers who see children and adolescents, parents of adolescents, and adolescents themselves. School teachers were recruited from a summer continuing education conference within a public school district. This district includes 4 elementary schools, one middle and one high school. Inclusion criteria limited participants to teachers who taught kindergarten through 12 th grade within that public school district. Clinicians were recruited at a yearly regional continuing medical education conference; inclusion criteria limited participants to physicians (MDs and DOs), nurse practitioners (NPs), physician assistants (PAs), and nurses, all of whose practice included pediatric patients. Parents of adolescents were identified within a large general pediatric practice that includes 8 pediatric providers. Inclusion criteria for parents were that they had a child between the ages of 11 and 18 years. Adolescents (ages 11-18 years) were identified and recruited within this same large general pediatric practice. Most parents and teens were recruited as dyads. We did not exclude parents or teens who elected to participate in the study separately because we did not compare data between parents and teens.

Data collection and recruitment

In each recruitment setting, potentially eligible participants were approached by a research assistant. After explaining the study and obtaining consent, participants completed a paper survey. Survey respondents were provided a $5 gift card as compensation.

Survey design

The goals of the survey were to understand at what age internet safety education should begin, explore the experiences of adult participants in teaching online safety or the adolescents learning about this topic, and to identify a group who has primary responsibility for teaching this topic. Thus, we included all potential survey participants in the survey design process. Surveys were designed after a review of the literature and conversations with a panel of physicians, parents and researchers. Questions were pilot-tested first with a panel and then among teachers and adolescents. In the final survey items some words were modified to make the survey clear to all groups of participants. For example, among health care provider groups the question: “For how many years have you been in practice?” was changed for teacher groups to read: “For how many years have you been teaching?” All four surveys are included as Additional files 1 , 2 , 3 and 4 .

Data sources and variables

Participants provided demographic data including gender and age. Teachers were asked to disclose the grade levels they taught, subjects taught and years of teaching experience. Clinicians were asked to provide their training background (i.e. MD, NP), field of practice (Pediatrics, Family Practice) and years in practice. Parents provided their age, gender and the ages of their children. Adolescents were asked for their age, gender and grade in school.

Age to begin teaching internet safety

Teachers, clinicians, parents and adolescents were asked to provide at what age internet safety education should begin. An “other” option was presented for write-in answers.

Candidates to teach internet safety

In order to identify potential candidates to teach internet safety, participants were asked about previous experiences teaching or learning about internet safety. Then participants were asked for their own willingness to teach this subject and to identify an ideal primary candidate to teach this topic.

Experiences teaching internet safety

To describe experiences in providing internet safety education, teachers were asked how frequently they had ever taught internet safety education. Clinicians were asked how frequently they had ever counseled patients on this topic. Answer options included regularly, sometimes, never and never but plan to do so soon. Parents were asked about how frequently they talked with their child about internet safety: regularly, sometimes, never and never but plan to do so soon (Table  1 ).

Adolescents’ experiences learning about internet safety

Adolescents were asked ways in which they had learned about internet safety. A list of answer options was developed through review of the literature and the web and then piloted with several adolescents to ensure completeness. Answer options included learning from friends, siblings, parents, teachers and clinicians as well as learning by self-teaching. A write-in “other” option was also provided. Adolescents were allowed to choose all applicable answers from this list.

Willingness to teach internet safety

Teachers were asked whether or not they supported teaching internet safety education in public schools. Health care providers were asked whether or not they supported teaching internet safety education in provider offices (yes or no).

All groups, including teachers, clinicians, parents and adolescents were asked to select a candidate group whom they felt had primary responsibility for teaching internet safety to children and adolescents. Based on a review of current groups engaged in teaching this subject, answer options included churches, community groups, health care providers, law enforcement, parents and teachers. An “other” option was presented for write-in answers.

All statistical data analyses were conducted using STATA version 11.0 (Statacorp, College Station, TX). Descriptive statistics were calculated for survey responses. ANOVA was used to compare mean age to begin teaching between teachers, clinicians, parents and adolescents. Logistic regression was used to assess whether experience teaching internet safety was associated with years of career experience.

Participants

A total of 356 participants completed the survey (93.4% response rate), including 77 teachers, 111 clinicians, 72 parents and 96 adolescents. Teachers had an average of 14.8 (SD = 8.4) years of teaching experience. The subjects that teachers taught included: health, social studies, language arts/English, special education, health and technology/computer skills. Clinicians included 68 (61.3%) physicians, 16 (14.4%) nurse practitioners, 15 (13.5%) physician assistants and 8 (7.2%) nurses. Their practice background was mainly pediatrics (61.3%) and family practice (27.9%). Clinicians’ years of experience averaged 14.5 (SD = 10.1). Parents were 81% female. Adolescents were 62.5% female and had an average age of 15.1 (SD = 2.3). Please see Table  2 for further descriptive information.

The overall mean age at which stakeholders indicated for starting to teach internet safety was 7.2 years (SD = 2.5), range 2-15. Teachers reported that the average age at which internet safety should be taught was 6.9 years (SD = 2.1), while clinicians felt the average age to start teaching this topic should be 7.3 years (SD = 2.4). Parents felt that internet safety education should begin at age 6.6 years (SD = 2.3). There were no statistically significant differences between these groups regarding age to begin teaching internet safety (p = .2). Adolescents reported that internet safety education should begin at age 8.7 years (SD = 2.4). Please see Figure  1 for a summary of recommended ages to begin internet safety education.

Age to begin teaching internet safety to youth.

Among teachers, 16 (20.8%) reported currently teaching internet safety, 51 (66.2%) had never taught it, and 4 (7.8%) had never taught it but planned to soon. The number of years teaching was not significantly associated with the likelihood to have taught internet safety.

Among clinicians, 3.6% regularly and 55% sometimes counseled patients on internet safety. One-third of clinicians (33.3%) had never counseled or taught patients about internet safety and a few clinicians (8.1%) had no experience with this but planned to begin soon. The number of years in practice was not associated with the likelihood to have taught internet safety (p = .6).

All parents reported discussing online safety with their children either sometimes (58.3%) or regularly (40.3%).

Experiences learning internet safety

Adolescents were asked to identify ways in which they had learned about online safety. Adolescents were permitted to select all options that applied. Adolescents selected people including teachers (87.5%), parents (75%), friends (41.7%), siblings (27.1%) and clinicians (11.5%). Some adolescents indicated that they had learned internet safety by being self-taught (27.5%).

Teachers uniformly reported supporting online safety education in public schools (100%). Clinicians almost uniformly supported providing online safety education in clinicians’ offices (99.1%).

All groups selected parents as the primary candidate to teach internet safety. Among teachers, 97% ranked parents as their first choice candidate, and 3% ranked teachers as first choice. Among clinicians 97% ranked parents as first choice candidate, and 3% ranked teachers as first choice. Among parents, 96% ranked themselves as first choice candidate, and 4% ranked teachers as first choice. Among adolescents, there was more variety in answers. Most adolescents (74.7%) ranked parents as first choice candidate, 13.8% ranked teachers as first choice, 5.7% ranked law enforcement as first choice, 1.5% ranked community as first choice, 3% ranked churches as first choice and 3% wrote in answers of making a movie related to online safety and making a powerpoint regarding online safety.

The results of this study illustrate several key points regarding promoting safe internet use among youth. Findings suggest general agreement among key stakeholders for teaching internet safety at a young age, and for identifying parents as primary teachers of this topic.

First, our findings regarding the suggested age to begin teaching online safety may seem younger than expected. The suggested age range of 6 to 8 years identified by participants suggests that internet safety education could begin in early grade school, around 1 st or 2 nd grade. However, given our current society’s focus on technology, it is likely that children are being introduced to computers at ever-younger ages. Data from 2010 suggests that almost 20% of 8 to 10 year olds spend time on social networking sites daily, in the past three years it seems likely that this percentage has grown [ 20 ]. Timing safety education with the onset of internet use may allow for the concomitant development of computer skills and safety skills. As with many health teachings such as nutrition or sexual behavior, providing education to children before dangers can arise is a key strategy to help youth integrate these lessons into their lives and prevent negative consequences.

Second, our findings include a general agreement among key stakeholders that parents should hold the primary responsibility for internet safety education. These findings are supported by a recent study in which teachers felt that parents should have the primary role in teaching this topic [ 27 ]. Interestingly, we found that while parents all reported that they regularly or sometimes teach internet safety, only 75% of adolescents reported hearing from parents on this topic. These conflicting findings may be due to social desirability on the part of parents reporting their teaching efforts, or that teens may underreport their parents counseling efforts as they may not recognize parent attempts to discuss these difficult topics. Previous work has found a similar disconnect between parent and pediatrician reporting of counseling on risk behaviors [ 28 ].

Finally, our findings suggest that parents are willing teachers in providing internet safety education, and that many report some experience in this area. However, while parents may be candidates to guide their children’s digital lives, some parents may feel underprepared for the task of instructing their children who have grown up as “digital natives.” Thus, health care providers and public health educators may have an unique opportunity to support parents by providing resources, guidance and support. Pediatricians who see adolescent patients have the opportunity to serve an important and perhaps familiar role. As with many other topics of health supervision including safety, nutrition and fitness, parents are the primary source of education for their children. However, in many of these health topics, clinicians and health educators are trusted sources for parents on how to talk with their children about these issues. Some child health providers may feel untrained or unprepared to answer questions about internet safety or cyberbullying given that these are relatively recent health concerns about which much remains unknown. Pediatricians can use American Academy of Pediatrics guidelines to recommend parental supervision of internet activities, decreasing or eliminating isolated screen time (ie, moving the computer to a public space), and having open discussions about the potential dangers of electronic media [ 23 ]. Pediatricians and educators can also partner with schools or other community groups, such as law enforcement, to provide consistent and reinforced messages about internet safety.

Limitations to this study include the regional focus of our data collection. Our study aimed to draw representation of populations of teachers, clinicians, parents and adolescents within our region, the excellent response rates and distribution of participants within each category support that our results are generalizable within our region. However, there are other groups who may engage in teaching internet safety that were not included in this study such as churches and community groups. Second, it is notable that our study did not provide data on what methods would be best to provide internet safety education, this is a logical next step for future study. Third, we did not specify in the context of this study whether online safety should include additional technologies such as cell phones or texting. Fourth, data was collected by self-report, thus recall bias or overestimation of experience or willingness could have impacted our findings. Based on the varied stakeholders included in this study, there was some variation in data collected from each group.

Technology is now an integral part of life, and thus, part of the health of our patients. Our findings illustrate consensus around several groups with experience and investment in working with children and adolescents that parents should have primary responsibility for teaching internet safety. Our study highlights an opportunity for pediatricians to play a collaborative role with parents, patients and teachers to address the critical topics towards improving internet safety. Given the importance of this topic for today’s youth, it is likely that collaborative efforts are needed to provide consistent education about safety in the digital world.

Authors’ information

MM is an adolescent medicine physician who conducts research on the intersection of technology and health. KE is a medical student interested in pediatrics. KB studied consumer science and is interested in ways to improve internet safety education for youth. HY is a pharmacist and researcher with interest in provision of education to patients and parents. EC is a pediatrician and researcher interested in improving health systems and communication.

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Acknowledgments

This project was supported by Award Number K12HD055894 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The funding organization had no role in the design, collection of data, analysis or interpretation on the data in this manuscript. The authors would like to acknowledge the contributions of Michael Swanson and Jay Farnsworth to this project.

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Megan A Moreno, Kaitlyn Bare & Elizabeth D Cox

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MM conceived of the study, participated in its design and coordination, participated in analysis and wrote the manuscript. KE and KB participated in data collection and helped to draft the manuscript. HY and EC participated in analysis and helped to draft the manuscript. All authors read and approved the final manuscript.

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Moreno, M.A., Egan, K.G., Bare, K. et al. Internet safety education for youth: stakeholder perspectives. BMC Public Health 13 , 543 (2013). https://doi.org/10.1186/1471-2458-13-543

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Adolescents’ Exposure to Online Risks: Gender Disparities and Vulnerabilities Related to Online Behaviors

Elena savoia.

1 Community Safety Branch of the Emergency Preparedness, Research, Evaluation, and Practice Program, Division of Policy Translation and Leadership Development, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; ude.dravrah.hpsh@namirrahn (N.W.H.); ude.dravrah.hpsh@usam (M.S.)

2 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA

Nigel Walsh Harriman

3 Operation250, Lowell, MA 01854, USA; gro.052noitarepo@etoct

Neil Shortland

4 Center for Terrorism and Security Studies, University of Massachusetts Lowell, Lowell, MA 01854, USA; ude.lmu@dnaltrohS_lieN

Associated Data

The data gathered during the course of the project are available upon request, due to research subjects’ privacy considerations, via the national public repository of data Criminal Justice Data (NACJD), hosted by the Inter-university Consortium for Political and Social Research (ICPSR; at the University of Michigan), and can be found at the following link: https://www.icpsr.umich.edu/web/NACJD/studies/37338 .

In the last decade, readily available electronic devices have created unprecedented opportunities for teens to access a wide variety of information and media–both positive and negative–on the internet. Despite the increasing number of initiatives taking place worldwide intended to assess and mitigate the online risks encountered by children and adolescents, there is still a need for a better understanding of how adolescents use the internet and their susceptibility to exposure to risks in the online space. We conducted a cross-sectional online survey of a convenience sample of 733 8th and 9th grade students in Utah. The survey contained eight questions regarding students’ exposure to three types of online risk scenarios: content risk, contact risk, and criminal risk. Independent variables included students’ online behaviors, use of social media and private messaging apps, and adult supervision of online activities. Logistic and negative binomial regression models indicated that gender, social media use, and chatting with strangers were associated with exposure to multiple risky online scenarios. Our results provide critical information to educators involved in the development of initiatives focusing on the reduction of youth online risk by identifying correlates of risky online events, allowing them to tailor their initiatives to meet the needs of potentially vulnerable populations.

1. Introduction

In the last decade, readily available electronic devices such as computers, tablets, and smartphones have created unprecedented opportunities for teens to communicate, connect, share, and access a wide variety of information and media on the internet [ 1 , 2 ]. A 2018 survey reported that nearly all U.S. teens (95%) have access to a smartphone and 45% are “almost constantly” on the internet. Information and communication technologies are playing a key role in fulfilling adolescents’ emotional and communication needs [ 3 ], and the instrumental and social functions of such technologies are having a critical impact on teens’ interactions with parents, peers, and social groups [ 4 ]. Digital communication can both strengthen and strain teen-parent relationships. Mobile phones provide a permanent channel of communication between parents and teenagers, thereby offering opportunities to intensify parental supervision and control [ 5 , 6 , 7 ]. However, the same technology is also facilitating the process by which teens connect with peers and with individuals in an independent manner free from parental surveillance.

Despite the increasing number of initiatives taking place worldwide intended to assess and mitigate the online risks encountered by children and adolescents, there is still a need for a better understanding of how adolescents use the internet and what consequences they may face [ 2 , 8 ]. For example, it is important to expand the existing research into the role adults play in being a protective factor to the risks and threats presented to youth online. Existing research focusing on the mediation rules and strategies of parents has found that restrictions of online peer-to-peer interaction are effective, though the most common of strategies done by parents have been found to show no significant impact [ 9 ]. Alas, the current understanding of how young people experience communication technologies, how they perceive opportunities for risks over the internet, and how social media shapes their interactions is developing but admittedly incomplete.

1.1. Adolescents’ Exposure to Risky Online Situations

Risky online situations that adolescents may encounter have been classified into three groups: (1) “content risk,” referring to user exposure to possible harmful contents, (2) “contact risk,” referring to user activities and communications with known or unknown individuals that carry a potential threat and (3) “commercial risk,” referring to situations in which commercial organizations attempt to exploit the user [ 10 ]. In reviews of what risks would bother fellow adolescents of their age, youth identified pornographic and violent content as being their two highest concerns (classified as content risk) [ 11 ]. As a highly interactive platform, social media facilitates more opportunities for adolescents to engage in risky behaviors and be exposed to risky online content. When online, adolescents devote much of their free time to social media, using social media platforms for an average of nearly 3 h each day [ 12 , 13 ]. Understanding the relationship between social media use and risky behaviors during adolescence is crucial given the increased propensity for risk-taking that is unique to this developmental period [ 14 , 15 ]. Several studies and reviews of existing literature provide evidence illustrating how the use of social media impacts–both positively and negatively–essential aspects of adolescents’ mental health and psychosocial development, including self-esteem, social connectedness, peer communications [ 16 , 17 , 18 ], and how social media may pose risks of cyber victimization and lurking [ 19 , 20 , 21 , 22 ]. A recent meta-analysis showed that higher levels of social media use among adolescents are associated with more frequent engagement in drug use, risky sexual acts, and violent behaviors with a small-to-medium magnitude of effect [ 23 ]. Specific examples of negative situations experienced by adolescents in the online space include: being contacted by a stranger, having either seen or received media that made them feel uncomfortable, having felt under pressure to send photos or other information about themselves, and having accidentally spent money online that they did not mean to spend [ 24 , 25 ]. As part of a three-year research effort to examine childrens’ safe use of the internet and digital technologies in Europe, researchers found that the most common of risks experienced by youth was giving out personal information, encountering violent and hateful contact being third most prevalent, and being bullied the fourth most common [ 26 ]. While all these situations have been widely documented, little is known about which individual-level online behaviors and which social media and communication platforms are most likely associated with negative and risky situations.

A range of work has sought to understand the risk factors associated with encountering harmful material online. For example, Suler identifies the role that the experience of being “online” plays in creating a risk-shift in individuals (referred to as the online disinhibition effect) [ 27 ]. Other field research has explored the base-level predictors that someone (especially a young person) will be on a social networking site and thus exposed to risk. This work equally identifies the avenues to practically manage online risks to children–via the industry providers, parents, and the children themselves. Wider meta-analyses have sought to identify the prevalence of risk; for example, noting that one in five youth had experienced unwanted exposure to sexually explicit material while online and one in nine youth experience online sexual solicitation [ 28 ]. Taken together, such work emphasizes the risk of being online in general, the nature of “being online” which increases the likelihood of risky behavior, and even the immensely high prevalence of risky experiences that are encountered by those (especially young children) who go online. While crucially important, the issue with such work is that it often draws a homogenous, and indeed static, perception of internet users, meaning that exposure to risks is held equal across all individuals, irrespective of the distinct qualities of the user themselves. This, from a theoretical standpoint is at odds with the general view of risky behavior; even that which occurs offline. For example, it is noted that the demographic factors of the user are related to the likelihood that they will be exposed to violent extremist material (even unsolicited) [ 29 ]. What this means then, and in line with an interactionist perspective of risky online behavior, is that factors associated with the individual, and indeed their internet tendencies, will play an important role in the nature of the risk that they are exposed to. This proposition makes intuitive sense, given that it is known that when it comes to the negative effects of harmful media, susceptibility stems from three discrete sources; dispositional, developmental, and social susceptibility. Thus in order to fully conceptualize the risks of being “online”, we must disaggregate both the nature of risks that individuals are exposed to, and the differential effect such harmful material may have on them [ 30 , 31 , 32 ]. This interactionist and disaggregated view of risk exposure online for young individuals is currently not fully explored but is critical in understanding how best to prevent harmful outcomes of being online.

1.2. Current Study

This study was conducted in a practice context where a group of schools decided to participate in an educational initiative designed to reduce hate and enhance tolerance towards diversity. Prior to the implementation of this educational initiative, a survey was conducted to understand students’ behaviors and attitudes, exposure to hate messages, and exposure to risky situations online. The analysis we present in this manuscript includes a subset of the survey questions focused on online behaviors and exposure to risky situations. This analysis was descriptive in its intent-we sought to describe predictors of adolescents’ exposure to online risks in the sampled population with no intention of deriving conclusions regarding the general population of 8th and 9th graders in the selected schools’ districts, the state of Utah, or the USA. The study was guided by the following research questions: What demographic characteristics are associated with exposure to online risks? How is the use of social media and private messaging apps associated with exposure to online risks? To what extent is adult supervision of adolescents’ online activities a protective factor towards exposure to online risks?

2. Materials and Methods

2.1. study design.

We implemented a cross-sectional study design by the use of an online survey, in four schools in Utah (USA), gathering data from students in 8th and 9th grade in April 2018. The consent process contained two stages-one month before the start of data collection, parents were provided the study goals and opt-out forms. Students whose parents opted out were not invited to take the survey. We then obtained consent from the remaining students at the beginning of the survey. Data were collected using the online survey platform Qualtrics. The survey link was shared with the students by their teachers during class time–the survey took roughly twenty minutes to complete. We opted for a short survey to avoid disruption of learning activities as requested by the teachers. The study protocol and instruments were approved by the Harvard T.H. Chan School of Public Health Institutional Review Board (IRB16-1757; 24 January 2017) as well as by the ethical committee of the school district where the study was implemented. The Helsinki ethics protocols were followed throughout the course of this study [ 33 ]. A copy of the survey instrument can be found in the Supplementary Material .

2.2. Dependent Variables

To measure exposure to online risks, respondents were asked if they had ever experienced any of the following eight situations: (1) Bullying or harassment by friends or acquaintances, (2) Getting involved in unwanted conversations in a chat room, social networking site, or on email, (3) Coming across sexual images or content, (4) Coming across images of violence, (5) Someone trying to sell me drugs or alcohol, (6) Someone using my photos in an inappropriate way, (7) A stranger trying to meet with me, (8) Coming across hate groups trying to convince me of their views. Some of these situations can be classified as content risk (q3 and q4), some others as contact risk (q1, q2, q6, q7, and q8), and one as criminal risk (q7). This dependent variable was studied in two ways: (1) using each of the eight situations as an outcome, (2) using the number of situations a student encountered as the outcome. We also created a dichotomous variable where 0 = no situations encountered and 1 = any number of situations encountered, to further study and confirm the relationship found in the previous analysis.

2.3. Independent Variables

Independent variables included demographics (race, gender, and age), in addition to academic performance, use of social media and private messaging apps, and adult supervision. Academic performance was measured by frequency of grade type (A, A−/B+, B, B−/C+, and C or lower). Use of social media was measured by asking respondents which social media tool (i.e., YouTube, Snapchat, Instagram, etc.) they use and how frequently they use it, with answer options ranging from 1 (never) to 6 (all the time). A summative social media use score was created by dichotomizing the use of each social media platform used by the respondent into a dichotomous variable (1 = daily use or higher, 0 = less than daily use) and summing the attributed value across all fifteen platforms. Respondents were also asked if they used any private messaging apps, including Kik, Telegram, or WhatsApp, and if they used such apps more frequently than texting.

To further understand social media use and online behaviors, respondents were asked how many of their social media followers they knew in person, and how frequently they chatted with strangers while on social media. A similar question was asked about their friends’ behaviors, under the assumption that they would be less likely to misreport friends’ habits compared to their own. Additional questions focused on behaviors such as sharing personal information while on social media or chatting with strangers while playing online video games. Finally, using items adapted from existing research, respondents were asked about adult supervision, in particular, if their parents supervised their online activities, if anyone had ever talked to them about online safety, and if they had a trusted adult to ask for help in case they encountered an uncomfortable situation online [ 34 ].

2.4. Statistical Analyses

Simple and multiple logistic regression models were used to study how the independent variables were associated with the occurrence of each of the 8 situations identified as online risks. A Box-Tidwell procedure was used to confirm that aggregate social media use had a linear relationship to the log odds of each of the 8 dependent variables. Independent variables were included in the multiple models when a statistically significant association was found in the simple models ( p -value < 0.05). Gender, race, and age were included regardless of their significance in the final models because of theoretical relevance. Hosmer-Lemeshow tests were used to assess the goodness of fit of the multiple logistic regression models [ 35 ]. For the second dependent variable related to the number of situations the respondents experienced, a negative binomial regression model was fitted to the counts of the risky online situations. Pearson’s chi-squared test of dispersion was used to assess the goodness of fit for the negative binomial model. We compared the fit of the negative binomial regression model to Poisson, zero-inflated Poisson, and zero-inflated negative binomial models using the Bayesian information criterion (BIC) to determine whether any of those distributional forms was more appropriate for this sample. For both logistic and negative binomial regressions, model misspecification was assessed using Pregibon’s goodness-of-link test [ 36 ]. For models where the goodness-of-fit test failed, we tried to modify the set of covariates in the model to achieve a better fit as feasible. Data analysis was performed using Stata Statistical Software Release 15.1 (StataCorp LLC, College Station, TX, USA).

The response rate to the survey was 86% (767/897). This paper is based on the analysis of the data obtained from 733 students of which we had complete data. Below we provide the sample characteristics based on demographics and academic performance, and descriptive statistics for social media use, private messaging use, online behaviors, adult supervision of online activities, and risky online situations experienced by the respondents. We then present the results of the multiple logistic regression models for the dependent variables (each of the eight risky situations and exposure to at least one situation). Finally, we present the results of the negative binomial regression model for the count of different risky online scenarios.

3.1. Sample Characteristics and Descriptive Statistics

Detailed descriptive statistics for the sample can be found in Table 1 . We gathered data from a convenience sample of 733 individuals, the majority of whom were male (51%). Major categories of race were: White (39%), Hispanic (21%), and mixed-race (10%). The sample included students aged 14 (41%), 15 (58%), and 16 (1%). Regarding academic performance, most students reported receiving grades ranging between A– and B+ (41%).

Students’ Online Behaviors.

3.1.1. Social Media Use and Online Behaviors

Detailed descriptive statistics for the sample can be found in Table 1 . Most participants reported using more than one social media platform daily (85%), and 50% reported using three or more social media platforms daily. Only 14% of students had met all of their social media followers in person, the majority of them (62%) reported that they had chatted with strangers on social media, and 62% reported they believe their friends did so as well. Thirty-one percent of respondents indicated they had shared personal information, such as their school or town name when posting on social media. Eleven percent of students used private messaging apps more than texting, and use was distributed as follows: WhatsApp (9%), followed by Kik (5%), and Telegram (1%). The majority of participants played video games online (78%), and 51% reported that they chatted with someone they did not know while gaming. Regarding parents’ supervision, the majority (52%) of students reported that their parents did not install parental controls on their computers or other devices. The majority (69%) of students reported they had a trusted adult they could ask for help if they experienced an online situation that made them feel uncomfortable. Finally, 95% of respondents reported that someone had spoken to them about online safety.

3.1.2. Risky Online Situations

Table 2 presents the detailed summary measures of each risky online event and the count of risky online events.

Risky Online Situations.

The most frequently reported situation was coming across images of violence (32%), followed by coming across sexual images or content (31%), and bullying by friends or acquaintances (29%). Twenty-six percent of respondents indicated they had been in an unwanted conversation in a chat room, social networking site, or on email. Seventeen percent of students reported experiencing a situation in which they encountered a stranger online who wanted to meet with them, and 14% of students reported coming across hate groups trying to convince them of their views. Fourteen percent of students indicated that someone had tried to sell them drugs or alcohol online. Only six percent of students reported someone inappropriately using their photos. Overall, the distribution of the counts of risky online situations was skewed to the right with subjects reporting a mean of 1.7 events (SD = 2) and a median of 1 (range = 0–8). Forty percent of the subjects did not report experiencing any of the risky online situations listed in the survey.

3.2. Logistic Regression Models

Table 3 presents the results for the multiple logistic regression models for each risky online event. Simple logistic regression models were performed for each of the dichotomous dependent variables. Box-Tidwell test results confirmed that our summative measure of overall social media use was linear to the log odds of each outcome ( p > 0.05). Detailed results for the simple models can be found in the Supplementary Material . The overall LR chi-square test statistics for the eight multiple models exploring the association between the independent variables and each of the eight online situations were significant (χ 2 , p < 0.01). Hosmer-Lemeshow Goodness of Fit test results confirmed that all models were a good fit for the data. Pregibon’s link test did not indicate any model misspecification (ŷ p < 0.05, ŷ 2   p > 0.05), except for the dependent variable “someone trying to sell me drugs or alcohol”. Below we provide a summary of key results for each situation and the counts of situations experienced.

Multiple Logistic Regression Models.

* p < 0.05, ** p < 0.01. OS 1, bullying or harassment by friends or acquaintances; OS 2, getting involved in unwanted conversations in a chat room, social networking site or on email; OS 3, coming across sexual images or content; OS 4, coming across images of violence; OS 5, someone trying to sell me drugs or alcohol; OS 6, someone using my photos in an inappropriate way; OS 7, a stranger trying to meet with me; OS 8, coming across hate groups trying to convince me of their views. a Two respondents differentially classified their video game use by stating they had never played video games, and yet they had chatted with strangers online. To ensure the validity of our analysis, we re-constructed the model for question 7-a stranger trying to meet with you, without these two respondents included, and found no change in significance to the reported results. Pairwise marginal linear predictors were only computed on categorical predictors with 3+ categories that had significant Chi-Squared tests. Blanks cells for continuous, dichotomous, and categorical predictors with 3+ categories indicate that this variable was not significant in the simple models and thus not included in the multiple model. Blank cells for pairwise comparison of marginal linear predictors indicate that this categorical predictor with 3+ categories did not have a significant Chi-Squared test value. 3.2.2. Online Contact Risk.

3.2.1. Online Content Risk

Two of the eight risky online situations we investigated referred to exposure to harmful contents (content risk): (1) coming across sexual images or content and (2) coming across images of violence. Gender was predictive of exposure to both of these risks. Compared to males, females had twice the odds of coming across sexual images or content (OR = 2, 95% CI 1.4–2.9) and 1.9 times the odds of coming across images of violence (OR = 1.9, 95% CI 1.3–2.7). Chatting with a stranger while online was also a predictor for both of these content risks. Respondents who reported this behavior had 70% increased odds of coming across sexual content (OR = 1.7, 95% CI 1.1–2.5) and images of violence (OR = 1.7, 95% CI 1.1–2.6). Race was the only other variable that predictive of exposure to sexual images; white students had 50% increased odds of coming across this content compared to non-white students (OR = 1.5, 95% CI 1–2.1).

Regarding the other content risk, age, academic performance, and social media use predicted coming across images of violence. Students aged 15 and older had 70% increased odds of coming across images of violence (OR = 1.7, 95% CI 1.2–2.4). Students who received grades of B or lower had 60% increased odds of coming across images of violence, compared to those who had grades of B+ or higher (OR = 1.6, 95% CI 1.1–2.3). Finally, the odds of coming across images of violence increased by 24% with each additional social media platform used by the respondent daily (OR = 1.24, 95% CI 1.08–1.42).

3.2.2. Online Contact Risk

Five out of the eight online risky situations we investigated referred to interactions with someone online that lead to a risky outcome (contact risk situations): (1) bullying and harassment by friends or acquaintances, (2) getting involved in unwanted conversations, (3) someone using the respondent’s photos in an inappropriate way, (4) a stranger trying to meet with them, and (5) coming across hate groups trying to convince the respondent of their views. Chatting with a stranger while online was a predictor for all of the five contact risks. Respondents who reported this behavior had increased odds of exposure to the five contact risk situations. These increased odds ranged from 80% for having experienced unwanted conversations (OR = 1.8, 95% C.I. 1.2–2.9), and for coming across hate groups (OR = 1.8, 95% C.I. 1–3.2) to 350% for having had someone inappropriately use the respondent’s photos (OR = 4.5, 95% C.I. 1.5–13.3). Gender was associated with two of the five situations, with females having 70% increased odds of experiencing bullying or harassment while online (OR = 1.7, 95% 1.2–2.4) and 100% increased odds of engaging in unwanted conversations (OR = 2, 95% C.I 1.4–2.9). The number of social media platforms used by the respondent was associated with experiencing bullying or harassment in the online space, the odds of experiencing bullying or harassment increased by 14% with each additional social media platform used by the respondent daily (OR = 1.14, 95% CI 1.01–1.28). Finally, the use of the private messaging app Kik was associated with 210% increased odds of having someone inappropriately use the respondent’s photos (OR = 3.1, 95% CI 1.1–9.2), however, this association should be explored in a larger sample, as only 37 students in our sample used Kik.

3.2.3. Criminal Risk

One of the eight situations we investigated referred to criminal risk: someone trying to sell the respondent drugs or alcohol. None of the independent variables resulted to be a significant predictor of this situation.

3.3. Negative Binomial Model for Number of Types of Risky Online Situations

Table 4 displays the results of the negative binomial model for the number of types of risky online situations. The final negative binomial regression model had a Pearson’s chi-square of 739.8 (df = 693, p = 0.11) indicating the model accounted for any overdispersion in the data well. Pregibon’s link test did not indicate any model misspecification (ŷ p < 0.01, ŷ 2   p = 0.36). The model included the following factors: age, gender, race, social media use, chatting with strangers on social media, the respondent’s friends’ habit of chatting with strangers on social media, parents’ supervision of online activities, if anyone had ever talked to them about online safety and if they have a trusted adult to ask for help with risky online situations. The negative binomial model had a BIC of 2445.6 which was favorable when compared to the BIC from a Poisson (BIC = 2646.4), zero-inflated Poisson (BIC = 2487.5), and zero-inflated negative binomial (BIC = 2460.7) models with similar predictors.

Negative Binomial Model for Counts of Types of Risky Online Situations.

* p < 0.05, ** p < 0.01.

In the negative binomial model, females had 1.5 times the incidence rate of experiencing different types of risky online situations compared to males (IRR = 1.5, 95% CI 1.3–1.9). Social media usage was also a significant predictor with each additional social media platform used daily associated with an 8% increase in the incidence rate of experiencing different types of risky online scenarios (IRR = 1.08, 95% CI 1.01–1.15). Students who chatted with strangers on social media had 1.6 times the incidence of experiencing different types of risky online scenarios than those who did not (IRR = 1.6, 95% CI 1.3–2.0). Lastly, the frequency in which the respondent’s friends chatted with strangers on social media was a significant predictor (χ 2 (df) = 14.6(3), p = 0.002). This was driven by significantly higher incidence rates of experiencing different types of risky online scenarios for students whose friends “sometimes” or “often” chatted with strangers on social media compared to students who did not know if their friends chatted with strangers with an IRR of 1.5 (95% CI 1.2–1.9) and 1.6 (95% CI 1.2–2.1), respectively.

Similar results were obtained in logistic regression models for our dichotomized variable for exposure to any risky online situation (see Table 3 ). Results from these analyses similarly indicated that gender (OR = 2.0, 95% CI 1.4–2.7), social media use (OR = 1.16, 95% CI 1.01–1.32), chatting with strangers online (OR = 2.3, 95% CI 1.6–3.4), and friends chatting with strangers online (χ 2 (df) = 11.8(3), p = 0.008) was significantly associated with exposure to risky events online.

4. Discussion

The goal of this study was to explore the individual-level characteristics associated with adolescents’ exposure to online risks, with a specific focus on demographic characteristics, various online behaviors, including use of social media and private messaging apps, and the role of adult supervision of adolescents’ online activities as a protective factor towards exposure to online risks. Findings from our study suggest how some children’s characteristics and behaviors are associated with the likelihood of encountering risky or uncomfortable situations when on the internet. Specifically, the type and duration of social media activity were strongly associated with exposure to some forms of online risk even if a temporal and causal association could not be investigated due to the cross-sectional study design. There was little evidence of parental supervision as a protective factor.

One particularly interesting result from our study is the existence of gender disparities in the exposure to online risks, with girls being more likely than boys to encounter specific risky situations in the online space. The role of gender is inevitably complex and multifaceted, but our data show that such disparities seem to be independent of other online behaviors such as the amount of time spent online or type of social media platform being used, suggesting that social factors may play a role including the potential for girls being the target of harassment, violence and sexual abuse. Our results should be consumed with the results from other studies in mind-specifically those that explore the social context that may give rise to these gender disparities in online risk. While some extant research has identified protective population-level factors against online risks, such as a country’s level of Internet diffusion, it is also vital to recognize studies that demonstrate online gender disparities in risk also occur in settings where offline exposure to risk and violence is gendered as well [ 37 , 38 , 39 , 40 ]. Future research should continue to investigate how societal factors may influence gender differences in online exposure to harmful material.

4.1. Implications for Policy Making

At the global level, we are increasingly focused on the harm caused by material accessed on the internet. Policymakers, academics, politicians, mental health, and medical professionals seek to understand the processes that govern the relationship between internet use and risk. Overall, the theoretical importance of this paper and its policy implications are related to its focus on the role of the individual, their behaviors, and characteristics, as a correlate to exposure to risky online events. While the majority of extant research has investigated the effect of the internet on the individual, such as the induced feeling of anonymity [ 27 ], researchers are increasingly exploring the role of the user on the likelihood that they engage in or are exposed to risky material online [ 30 , 41 ]. This research reinforces this interactionist perspective of online risk in that exposure to online risk is the result of an interaction between the nature of “being online” with the pre-existing characteristics, behaviors, and personality of the user.

Our findings also support the idea of differential risk in that while certain characteristics have a domain-general relationship with risk, others are associated with risk in a refined (or domain-specific) manner. For example, while being female is associated with the risks of being exposed to bullying, violent and sexual images, unwanted conversations, and at least one risky event, our data suggest that using the private messaging app Kik is associated with an individual’s photos being used inappropriately. However, we note that the use of Kik should be further investigated in larger studies due to the small number of individuals using this platform in our sample.

From a theoretical perspective, our results suggest the need to better differentiate the relationship between characteristics, and or social media use and the specific type of risk that someone may encounter. From a behaviorist standpoint, extant literature has shown that broad patterns of behavior reflect different fundamental incentives to human action [ 42 , 43 ]. This means that when it comes to online risky situations, including criminal activity, future research should aim to investigate the underlying incentives that guide both youth engagement with certain forms of online behavior and the certain risks that may stem from this. It is critical that forms of online intervention begin to think not just about domain-general aspects of prevention that can be equally beneficial to all (e.g., online safety, online disinhibition, parental rule or regulation), but also domain-specific forms of intervention that may need to be targeted towards certain types of risk that certain sub-groups of young internet users are more likely to be exposed to. These domain-specific forms of intervention must then include not only the specific online domain that individuals may be using (e.g., Kik) and the unique risks that this poses to these groups, but also the deeper psychological phenomena that are driving the online behavior.

The question of coping is important, as well as part of a wider shift from a technologically determinist discourse (of what the internet “does” to children) in favor of recognizing the importance of building children’s digital resilience. Encountering risk could in itself also represent an opportunity–to become more resilient, more digitally literate, and less vulnerable to online risks [ 44 ]. Sustained efforts are required from a variety of stakeholders, including families, schools, and technology industries to effectively safeguard children online in a dynamic technological and social media landscape. Thus, it is important to identify vulnerabilities that expose some children to higher risks so as to focus prevention efforts on those who will most benefit from them.

Future research should continue to investigate how societal factors may explain gender differences and other individual level-characteristics in online exposure to harmful material. We also recommend that future research attempt to understand how parents can reduce children’s vulnerabilities, whose role and supervision was not demonstrated as effective in our study.

4.2. Implications for Educational Initiatives

Educational initiatives should be tasked with developing programming for youth to address the underlying factors associated with online threats. These initiatives should be designed to develop the critical capability in children to recognize and mitigate the risks encountered by also learning how to self-regulate their behavior and seek help when needed. Children learning how to identify and interpret the impact and potential repercussions of various online behaviors can be influential in the overall safeguarding of youth online; among these potential risks, our study highlighted those posed by chatting with strangers, excessive use of social media platforms, and private messaging apps, and the development of both the technical and emotional competence to self-regulate online behaviors and deal with uncomfortable situations.

Initiatives that build knowledge and awareness about online risks are necessary, as is better awareness of existing disparities in exposure to risks. What this research can lend to the building and framing of educational internet safety initiatives is how to talk about and approach particular risks with students. Each risk online should be approached and discussed uniquely and based on individual risks, avoiding “one-size-fits-all” narratives that assume that all risks and the nature of such risks are the same for every internet user. Internet safety programs, such as those that are most prevalent in the education space like I-SAFE, Common Sense Media, and Netsmartz, could benefit from these findings in their efforts to avoid the use of “one-size-fits-all” approaches. In a multi-year study that evaluated internet safety education programs-such as those above-and their curriculum, researchers identified (among many other findings) that the most effective internet safety education programs need to have different strategies for different internet safety topics [ 45 ]. There is a great need to understand the risk factors and elements that might impact what risks and threats youth may be exposed to on different parts of the internet. Similarly, with many topics within internet safety being complex, the more explicit and clear educational programs can be when talking about risks and where youth might encounter them, the more beneficial it is to the educational goals.

Our findings show that the risks associated with certain online messaging apps are not all-encompassing, but rather narrowly associated with the inappropriate use of ones photos. Furthermore, chatting with strangers on social media has an array of potential associated risks. Understanding this connection and the association of certain platforms, actions, and risks can help inform education programming to give a more direct educational lesson to students to help with improving their self-regulated behaviors, necessary skills, and understanding of the potential risks around them.

Educational organizations and schools should consider our findings when building lessons and their content; learning examples and worksheets can better reflect certain risks and their association with certain behaviors. Additionally, our results should inform the way targeted programming for those who may be disproportionately exposed to risks online should be handled. Our data show that gender is associated with exposure to risky or uncomfortable situations, therefore calling on prevention programs to address these concerns with catered content. Simple changes to existing curricula might include the changing of the subject in particular examples to reflect a more accurate depiction of the research above, or more large-scale changes might be to offer further educational programming for those populations that are shown to be at higher risk of certain exposures.

4.3. Study Limitations

In considering the findings of this study, several limitations are acknowledged. Since our data were cross-sectional, we lack information on the temporal ordering of our variables, and we cannot assume causality. As a non-random convenience sample, it is important to acknowledge that these results are not necessarily generalizable outside of the sample, and that selection bias may have also influenced our reported results. Furthermore, as some of the exposures and outcomes could be perceived as negative, there is potential for social desirability bias to influence students’ responses. Our study sought to explore associations between risky online events and various behaviors online, demographic characteristics, and parental activities. It was not our intent to create an index to measure an underlying construct of online safety, and as such, no psychometric properties are reported. To our knowledge, there is no extant screening tool for exposure to online risk that has been psychometrically evaluated–future research should aim to address this gap.

5. Conclusions

Our results provide critical information to practitioners involved in the development of educational initiatives by suggesting the need to identify individual-level characteristics and behaviors that are associated with exposure to online risks in the population targeted by their programs, so to allow them to tailor their initiatives to meet the needs of those more likely to encounter online risks. The results presented in this manuscript also provide a platform for future longitudinal research to further investigate the magnitude of risk associated with these behaviors. Our results should be interpreted under the growing understanding that exposure to risky material online should be understood as a matter of if, not when, and as such, we recommend that future research should investigate how individuals engage with risky online content and the psychological processes which may influence exposure. With the continued increase of youth internet use, the need for reflective, impactful internet safety education is becoming more crucial. Schools are the main means by which a society can address digital safety and citizenship issues for all children within a structured learning environment. To achieve optimal success in this area, it requires teacher training and curriculum materials that are age and gender-appropriate as well as further research on the factors associated with online vulnerability.

Acknowledgments

The authors of this manuscript would like to acknowledge the work of Marcia A. Testa and Valentina Baccolini on the initial stages of data analysis and manuscript development.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/ijerph18115786/s1 . The questionnaire used for data collection is included as a supplementary file. Supplementary Material A: Survey Instrument, Supplementary Material B: Simple Logistic Regression Models.

Author Contributions

Conceptualization, E.S. and N.S.; methodology, N.W.H. and M.S.; formal analysis, N.W.H. and M.S.; writing—original draft preparation, E.S., N.W.H., M.S., T.C., and N.S.; writing—review and editing, E.S., N.W.H., T.C., and N.S. All authors have read and agreed to the published version of the manuscript.

Research reported in this publication was supported by the National Institute of Justice under award number 2016-ZA-BX-K001 Evaluation of the Peer to Peer (P2P): Challenging Extremism Initiative and award number 2018–2A-CX-0002 Operation250: An Evaluation of a Primary Prevention Campaign focused on Online Safety and Risk Assessment. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Justice.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Harvard T.H. Chan School of Public Health Institutional Review Board (IRB16-1757; 24 January 2017).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interests.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Related Information:

Internet safety research.

• Youth Perspectives on Online Safety, 2023  (August 2024)
• Cox Mobile Survey  - (Feb 26, 2024 )
• Bark's Annual Report: 2022 Research on Kids and Technology
• Overuse of devices and social media top parent concerns (C.S. Motts Children's Hospital, August 21, 2023)
• AFRAID, UNCERTAIN, AND OVERWHELMED: A Survey of Parents on Online Sexual Exploitation of Children
• Online Grooming: Examining risky encounters amid everyday digital socialization (Thorn, April 2022)
• Annual Report: 2021 Research on Kids and Technology | Bark
• Managing the Narrative Young People’s Use of Online Safety Tools (Family Online Safety Institute, November 2021)
• Tools for Today’s Digital Parents The role of parental controls in the digital lives of American parents and children . (Family Online Safety Institute, November 2020)
• Essential Facts About the Video Game Industry (Entertainment Software Association, 2020) 
• Association of Screen Time and Depression in Adolescence   (JAMA Pediatrics. Published online July 15, 2019)
• Online Safety Across the Generations - Executive Summary (Family Online Safety Institute, 2018)
• Global Kids Online: Research Synthesis 2015-2016
• Keeping Up with Generation App: NCSA Parent/Teen Online Safety Survey - National Cyber Security Alliance (June 2016)
• C.S. Mott Children's Hospital National Poll on Children's Health (2014).
• 2014 Teen Internet Safety Survey (Cox Communications, 2014)
• Youth Internet Safety: Risks, Responses, and Research Recommendations (Center for Technology Innovation at Brookings, October 2014)
• In Their Own Words:What Bothers Children Online? (EU Kids Online, February 2013)
• Anonymity, Privacy, and Security Online (Pew Internet & American Life Project, September 2013)
• Study of Self - Generated Sexually Explicit Images & Videos (International Watch Foundation, 2012)
• McAfee and NCSA Cyber Security Study (November, 2011)
• Who Needs Parental Controls?: A Survey Of Awareness, Attitudes, And Use Of Online Parental Controls (Hart Research Associates, Family Online Safety Institute, September 2011)
• Teens and Mobile Phones: Exploring Safety Issues as Mobile Phones Become the Communications Hub for American Teens (Pew Internet & American Life Project, November 9, 2010)
• Adolescence, Mobile Technology & Culture (Pew Internet & American Life Project, November 8, 2010)
• Use of Social Networking Sites in Online Sex Crimes Against Minors: An Examination of National Incidence and Means of Utilization(http://www.jahonline.org/article/S1054-139X (Journal of Adolescent Health, Volume 47, Issue 2, Pages 183-190, August 2010)
• Millennials will make online sharing in networks a lifelong habit (Pew Internet & American Life Project, July 9, 2010)
• The Secret Lives of Online Teens (McAffee, June 24, 2010)
• Teens and Mobile Phones (Pew Internet & American Life Project, April 20, 2010)
• Generation M2: Media in the Lives of 8- to 18-Year-Olds (A Kaiser Family Foundation Study, January 2010).
• Sex & Tech: Results from a Survey of Teens and Young Adults (The National Campaign to Prevent Teen and Unplanned Pregnancy with CosmoGirl.com, January, 2009)
• Enhancing Child Safety and Online Technologies: Final Report of the Internet Safety Technical Task Force to the Multi-State Working Group on Social Networking of State Attorneys General of the United States (Internet Safety Technical Task Force, Berkman Center for Internet & Society at Harvard University, December, 2008).
• 2008 National Cyberethics, Cybersafety, and Cybersecurity Baseline Study (Davina Ptuitt-Mentle, Ph.D., Educational Technology, Policy, Research and Outreach, October, 2008)
• Teens Viewing Drug and Alcohol-Related Videos Online (Custom Study for the Office of National Drug Control Policy, Nielson Online, October, 2008)
• Study of the Internet and Youth "At Risk Behaviors" (Rochester Institute of Technology, September, 2008)
• Cox Communications Teen Internet Safety Survey, Wave II--in Partnership with the National Center for Missing and Exploited Children and John Walsh (2007)

• Our Mission

Getting Kids to Take Online Safety Seriously

When you ask students to think through their own scenarios about online safety, they’re more likely to look out for themselves and others.

The top-line statistics about online safety for kids are troubling: According to a 2019 study by the Center for Cyber Safety and Education, 40 percent of kids in grades 4-8 reported that they connected or chatted online with a stranger. Meanwhile, the Journal of Adolescent Health reports that approximately one in five youth experience unwanted online exposure to sexually explicit material. And the risks just come from strangers: Pew Research Center reports that 59 percent of kids have been bullied or harassed online.

ISTE standards for students don’t quite seem up to the task. While they touch on cyberbullying and data privacy and acknowledge that being a “digital citizen” means learning about the responsibilities and behaviors for interacting in this space, they don’t say a word about access to and sharing of inappropriate and explicit content—including the risk of kids making a naive but devastating misstep themselves.

That’s a big gap. The easy solution would be cut-to-the-chase lectures that treat cyber safety as a standalone topic, but lectures often fail to make meaningful connections with students. In our years of teaching cyber safety to kids, we’ve arrived at what we think is a better approach—one in which cyber safety instruction is woven into subjects such as language arts, social studies, math, PE, and electives like STEAM, health, or theater.

We’ve seen it again and again in our classes: When cyber safety is contextualized and personalized and provides students with an opportunity to create, apply, or synthesize higher-level ideas in their subject-specific areas, the learning is far more profound. Moreover, with a cross-curricular approach, students become more empowered digital citizens who want to share their stories, research the facts, and inform their peers.

Make use of compelling, relevant narratives

Narrative is relevant in most subjects, but we’ve discovered that in the context of ELA, sharing cyber safety narratives with an element of suspense gains students’ attention, gets them thinking critically, and gives them ideas for their own narratives. Start with short, narrative videos such as those from Storybooth , a site that animates real-life stories submitted by 7th-12th graders, including testimonies relevant to cyber safety. BrainPop , which is aimed at elementary teachers and students, also has cyber safety videos.

After watching a video, ask your students to pick a related prompt. For example, if you’ve just watched a video on private and personal information, offer these:

• Explain why it can be risky to share information online.
• What steps would you take to prevent your private information from being shared?
• Create a T-chart of safe and unsafe information to share online.

Then they can write a response to the prompt and then turn and talk to a peer or share their responses in a whole group, e.g., “This reminds me of…” or “I wonder what would happen if…”

Or have your students write real or imagined narratives around topics of cyber safety. Start with story prompts such as, “A friend tells you that they are planning to meet up with someone they met through social media and wants you to come along. How do you respond?”

We have students work collaboratively on different story prompts related to cyber safety, then use a jigsaw approach where each group rotates to a completed story prompt with sticky notes to ask questions, share “a-ha” moments, and give peers feedback.

Storytelling with avatars and comics

Comics can both inspire and educate kids . Consider having your students create virtual avatars and comic strips with a tool like Pixton . They can create representations of themselves, classmates, peers, family members, or teachers who will play a role in the narratives they create (with permission, of course, from the represented people—yet another opportunity to model consideration and consent).

For example, kids could envision a scenario in which a high schooler meets someone they think is a peer online, agrees to meet them in person, realizes the gravity of the situation, and flees, and then depict that entire storyline in a comic strip format. The same thing can be done with scenarios related to sharing photos or a bank account number.

With digital comics, students can change backgrounds to build settings, vary facial expressions and body posture of their avatars, and learn technical skills like camera zoom to edit. Digital comics can launch discussions about other important topics, too, like the importance of nonverbal communication and how to support their peers when warning signs of cyber safety arise.

Practice problem-solving with scenarios

When students act out scenarios, they explore possible solutions to complicated problems with their peers. Pose scenarios and ask cooperative groups to act them out. Here's an example:

A group of classmates asks for your help to create a website about a teacher at your school. They want to include inappropriate pictures, images, and comments about her. What do you do? 

With practice and trust, your students will likely want to write their own scenarios. Whether you teach health, theater, or creative writing, having kids write a script for a cyber safety situation can bring new energy into your classroom.

Integrate research

When students research facts about cyber safety issues, they build their critical thinking and media literacy skills and gain a clearer understanding of what cyber safety is and what affects it, both in terms of outside influences and their own behavior.

For example, in a social studies class, ask them to consider this scenario: “Your friend tags you in a picture at the beach on Instagram. Other users have begun to make comments that make you feel uncomfortable and don’t seem appropriate to post online. You’re worried that your mom will see it. What should you do?”

As part of the assignment, have students look at legislation related to cyber safety to understand the legal ramifications of bad (and sometimes illegal) behavior; advise them to add links and resources they’ve discovered. Using an online collaboration board such as Padlet, Jamboard, or with Nearpod or Pear Deck, you can also do “think-pair-share” activities rooted in online research.

Relevant research works in math, too, and the objectivity of numbers provides a nice counterbalance to personal narratives. A good infographic, for example, can prompt questions and robust discussion. Because infographics are data-rich, they can reinforce understanding of statistics and probability and help develop quantitative literacy.

Students can also create surveys using Google Forms and collect data from their peers about a cyber safety topic of their choice—they are often more interested in crunching numbers when working with a data set they’ve created or contributed to and care about. Once students have collected and analyzed their data, they can create a Canva infographic of their own, which can also be used for a “notice and wonder” conversation that they lead.

Cyber safety instruction helps students see the connections between good citizenship overall and digital citizenship . Students need to understand the facts, cause and effect, personal responsibility, and the importance of both etiquette and context. Most of all, they need to understand that the lessons of compassion they learn throughout their school years extend into the digital world. One of the best ways to be compassionate towards others (and themselves!) is to be safe online. 

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https://www.nist.gov/news-events/news/2024/08/us-ai-safety-institute-signs-agreements-regarding-ai-safety-research

U.S. AI Safety Institute Signs Agreements Regarding AI Safety Research, Testing and Evaluation With Anthropic and OpenAI

These first-of-their-kind agreements between the u.s. government and industry will help advance safe and trustworthy ai innovation for all..

GAITHERSBURG, Md. — Today, the U.S. Artificial Intelligence Safety Institute at the U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) announced agreements that enable formal collaboration on AI safety research, testing and evaluation with both Anthropic and OpenAI.

Each company’s Memorandum of Understanding establishes the framework for the U.S. AI Safety Institute to receive access to major new models from each company prior to and following their public release. The agreements will enable collaborative research on how to evaluate capabilities and safety risks, as well as methods to mitigate those risks. 

“Safety is essential to fueling breakthrough technological innovation. With these agreements in place, we look forward to beginning our technical collaborations with Anthropic and OpenAI to advance the science of AI safety,” said Elizabeth Kelly, director of the U.S. AI Safety Institute. “These agreements are just the start, but they are an important milestone as we work to help responsibly steward the future of AI.”

Additionally, the U.S. AI Safety Institute plans to provide feedback to Anthropic and OpenAI on potential safety improvements to their models, in close collaboration with its partners at the U.K. AI Safety Institute. 

The U.S. AI Safety Institute builds on NIST’s more than 120-year legacy of advancing measurement science, technology, standards and related tools. Evaluations under these agreements will further NIST’s work on AI by facilitating deep collaboration and exploratory research on advanced AI systems across a range of risk areas.

Evaluations conducted pursuant to these agreements will help advance the safe, secure and trustworthy development and use of AI by building on the Biden-Harris administration’s Executive Order on AI and the voluntary commitments made to the administration by leading AI model developers.

About the U.S. AI Safety Institute

The U.S. AI Safety Institute , located within the Department of Commerce at the National Institute of Standards and Technology (NIST), was established following the Biden-Harris administration’s 2023 Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence to advance the science of AI safety and address the risks posed by advanced AI systems. It is tasked with developing the testing, evaluations and guidelines that will help accelerate safe AI innovation here in the United States and around the world. 

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OpenAI, Still Haunted by Its Chaotic Past, Is Trying to Grow Up

The maker of ChatGPT is struggling to transform itself into a profit-driven company while satisfying worries about the safety of artificial intelligence.

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By Cade Metz and Mike Isaac

Reporting from San Francisco

OpenAI, the often troubled standard-bearer of the tech industry’s push into artificial intelligence, is making substantial changes to its management team, and even how it is organized, as it courts investments from some of the wealthiest companies in the world.

Over the past several months, OpenAI, the maker of the online chatbot ChatGPT, has hired a who’s who of tech executives, disinformation experts and A.I. safety researchers. It has also added seven board members — including a four-star Army general who ran the National Security Agency — while revamping efforts to ensure that its A.I. technologies do not cause serious harm.

OpenAI is also in talks with investors such as Microsoft, Apple, Nvidia and the investment firm Thrive for a deal that would value it at $100 billion . And the company is considering changes to its corporate structure that would make it easier to attract investors.

The San Francisco start-up, after years of public conflict between management and some of its top researchers, is trying to look more like a no-nonsense company ready to lead the tech industry’s march into artificial intelligence. OpenAI is also trying to push last year’s high-profile fight over the management of Sam Altman , its chief executive, into the background.

But interviews with more than 20 current and former OpenAI employees and board members show that the transition has been difficult. Early employees continue to leave, even as new workers and new executives pour in. And rapid growth hasn’t resolved a fundamental question of what OpenAI is supposed to be: Is it a cutting-edge A.I. lab created for the benefit of humanity, or an aspiring industry giant dedicated to profits?

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• Small Business

Funding Your Dreams: Low-Cost Business Ideas for Every Aspiring Entrepreneur

Published on Sept. 2, 2024

By: Steve Strauss

• Today's digital world drastically reduces start-up costs, making entrepreneurship accessible to almost anyone.
• Even traditional businesses can now thrive with minimal overhead by leveraging home offices and affordable marketing tools.
• Low-cost business options range from online roles like virtual assistants to hands-on services, like pet-sitting and handyman work.

While being your own boss has long been a dream for many people, it was not so easy not so long ago. Even just a generation ago, online businesses were not really a thing, and as such, if you wanted to become an entrepreneur, you likely had to start some sort of brick-and-mortar business.

But not today.

The internet changed many things, but one of the best parts of the online digital revolution is that starting a business is easier, faster, and way less expensive than ever before. Gone are the days of renting an expensive office or storefront, hiring staff, paying for overhead, and so on.

Just about anyone can start an affordable business -- often for even under, say, $500. Here are seven examples -- a mix of online and offline businesses. Even offline, physical businesses are cheaper and easier to start nowadays because people can much more easily work out of their homes and marketing can be very inexpensive, or even, as in the case of social media, free.

1. Virtual assistant

Why a business credit card could transform your small business.

These business credit cards that offer a convenient and efficient way to separate personal and business expenses, simplifying accounting and tax reporting.

Additionally, business cards can provide valuable perks such as rewards points, cashback, and expense tracking tools, enhancing financial management and the potential to help save money in the long run.

• Administrative help
• Email management
• Conducting research
• Content creation
• And much more

The demand for VAs is growing, particularly among businesses that need help with day-to-day tasks but are not ready to hire full-time staff. Starting this business requires little more than a computer, internet access, and some apps and software.

2. Social media management

Along the same lines, while we all know that having a social media presence is vital in today's always-on, too-connected world, many people, small businesses especially, can't keep up with it. Either they don't have the content creation chops, or the technical know-how, time, or interest to manage their social media.

That's where you come in.

You can offer services like content creation, post scheduling, and performance analysis. The email marketing company Vertical Response found in a survey that 43% of small businesses spend about six hours a week on social media management. Get yourself a few clients, and you will have a full schedule (and a fat bank account!)

3. Online coaching or teaching

Coaches are all the rage these days. Whether it is selling a course or one-on-one coaching packages, online coaches sell and teach everything from yoga and weight loss to money management and online marketing. Simply set up a website, market yourself with some pay-per-click ads, and away you go.

Similarly, tutoring and teaching online has also exploded in recent years. My own daughter spent the year after college teaching Chinese kids how to speak English via the internet. She made bank (although sleep was not part of that bank, as she had to wake up at 3:00 a.m. to fit their schedule). Online tutoring platforms can be found with a simple Google search.

Now let's pivot and look at a couple of offline businesses you could also start on the cheap.

4. Pet sitting

We all love our pets, that's for sure (although I am sorry to report that our goldendoodle Hazel is, statistically speaking, the very best dog in the world). And as pet ownership continues to grow, so does the need for reliable pet care services.

If you love animals, pet sitting can be a rewarding and flexible business. Apps like Rover allow you to advertise your business and it handles the administrative side of things. Your responsibilities may include feeding, walking, grooming, and playing with pets while their owners are out of town or at work. The start-up costs are low, typically limited to basic supplies and insurance.

6. House and office cleaning

Starting a house or commercial office cleaning business can be a lucrative and affordable option. This business requires minimal initial investment and skill, just some cleaning supplies and basic equipment. Undercut the competition with your prices and you are in business (literally).

7. Handyperson

Finally, if you are good at fixing things, this old standby remains a very viable option. From home repairs to painting, plumbing, and electrical work, there is no shortage of things around the house for a handyperson to fix. Start-up costs are minimal, and advertising on sites like Craigslist is very cheap, often free.

So there you have it. Entrepreneurship on a dime is within your grasp. Whether it is managing social media or providing cleaning services, starting small and cheap really is quite possible.

Our Research Expert

Steve Strauss is the president of a boutique content company, The Strauss Group, and is a bestselling small business author and columnist. He can be reached at www.MrAllBiz.com, or at [email protected] .

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