and greater accessibility to the target are characteristics that set cyberbullying apart from off line bullying (Patchin & Hinduja, 2006; Tokunaga, 2010). These differences have implications in the development of appropriate cyberbullying interventions. Cyberbullying can take place through various electronic media (Knighton et al., 2012), including: phone calls; e-mails; texting (which may include picture and/or video messages); instant messaging (e.g., Windows Live Messenger); social networking platforms (e.g., Facebook); microblogging sites (e.g., Twitter); rating sites (e.g., Hot or Not); online gaming sites and massive multiplayer online role-playing games (MMORPG); video broadcasting websites (e.g., YouTube); chat rooms; website forums / bulletin boards / “bash boards”; and dedicated websites.

Prevalence of Cyberbullying In their recent and comprehensive synthesis of existing cyberbullying literature (73 articles published in peer-reviewed academic journals), Patchin and Hinduja (2013) found that victimization rates ranged from 2.3% to 72%, with the average being 21%. Among the studies that included offending behaviours, 1.2% to 44% of teens reported cyberbullying others, an average of 15%. Overall, approximately one out of every five teenagers has been the target of cyberbullying, and one out of every six has been a cyberbully at some point in their lifetimes. A recent survey found that 23% of Canadian students from grades 4-11 have said or done something mean or cruel to someone online, while 37% reported that someone has said or done mean or cruel things to them online that made them feel badly (Steeves, 2014). The substantial variation in prevalence rates can be attributed to a number of factors, including the lack of an accepted definition of cyberbullying, the range of conceptual and operational definitions, methodological differences and the lack of reliable and valid measures of cyberbullying.

What to do about cyberbullying? There are very few interventions specifically targeting cyberbullying behaviours, and even fewer rigorous evaluations of these interventions (Cioppa, O’Neil, & Craig, 2015; Nocentini, Zambuto, & Menesini, 2015). Adolescents often refuse to seek help from an adult in fear that their technology will be taken away (Tokunaga, 2010). Research results suggest that more work needs to be done around making reporting safer and more convenient, as well as ensuring that appropriate actions are taken after a report is received. Engaging both adults and youth in this process is essential. Innovative, youth friendly solutions are needed. For example, infographicsNote 1, online games, appsNote 2, or softwareNote 3 may be an effective way of educating youth about cyberbullying and changing patterns of interaction. However, none of these innovative initiatives have been rigorously tested for effectiveness. Defending behaviour (i.e., attempting to stop bullying and provide comfort and support to victimized peers) has been found to significantly reduce bullying in schools and have a protective effect on victimized peers (Sainio et al, 2010). Defenders are most likely to be female or empathetic males (Gini et al., 2007). The effects of defending behaviour on bullying and on the adjustment of victimized students has informed a number of bullying prevention and intervention programs (e.g., KiVa: Kärnä et al., 2011; Befriending Interventions: Menesini et al., 2003), and Promoting Alternative Thinking Strategies (PATH): Domitrovich, Cortes, & Greenberg, 2007). However, recent research suggests that defenders may experience problems due to defending (Sandre & Craig, 2015). In a recent fMRI study, Sandre and Craig (2015) found that, compared to controls, defenders display greater neural responsivity in the posterior insular cortex, an area of the brain associated with emotional arousal and social pain when witnessing the victimization of peers. More research is needed regarding the risks and benefits of defending behaviours towards cyberbullying. Previous research on protective factors for bullying perpetration and victimization in general may apply to cyberbullying. For example, a positive school climate and feeling connected to school have both been found to be protective factors against bullying (Resnick et al., 1997; Williams & Guerra, 2007). Therefore, the same may be the case for cyberbullying. Fanti and colleagues (2012) found that parental/family support helped to protect youth from engaging in cyberbullying behaviours, and from being victimized online. This association was especially important for children from single-parent families who, compared to children from intact families, were more likely to be targets of cyberbullying by their peers. Social support from peers is also an important protective factor (Sainio et al, 2010).

Teasing / belittling / name-calling Exclusion: Deliberately leaving certain individuals out of online social exchanges (e.g., instant messaging or email conversations) Rumour-spreading “Flaming” or “bashing”: Verbally attacking an individual with belligerent or denigrating language (e.g., insults, bigotry, or other hostile expressions); Online harassment: Repeatedly sending offensive messages to an individual; Cyberstalking: Online harassment that includes intimidation and/or threats of harm; “Cyber‐smearing”: Creating, posting and/or distributing sensitive, private and/or embarrassing information or images (including doctored images); Impersonating someone or creating a false identity to deceive another individual (“catfishing”); Rating aspects of an individual (e.g., appearance, character) on a rating site; and Creating derogatory websites that mock, torment, and harass the intended victim. The most common type of cyberbullying behaviour reported by Canadian students is name calling (Mishna et al., 2010; Steeves, 2014; Wade & Beran, 2011). Other, much less common, forms of mean or cruel behaviour includes harassing someone during an online game, spreading rumours, posting embarrassing photos or videos of someone, making fun of someone’s race/religion/ethnicity, making fun of someone’s sexual orientation, and sexually harassing someone (Mishna et al., 2010; Steeves, 2014; Wade & Beran, 2011). A 2014 youth survey indicated that the majority (65%) of cyberbullying incidents were chronic, lasting longer than a year (PREVNet, 2014). In this same survey, 70% of youth reported that when they see abusive content online, they report it. However, when asked why they might not report, they gave the following reasons: There is no point, reporting would not help (43%); I do not want the person to find out (36%); I am afraid of the negative consequences (29%); It takes too much time (27%); Someone else will report this content (15%); and I do not know how to report (13%).

Pew Research Center has been studying online harassment for several years now. A new report on Americans’ experiences with and attitudes toward online harassment finds that 41% of U.S. adults have personally experienced some form of online harassment – and the severity of the harassment has increased since we last studied it in 2017. We spoke with Emily Vogels, a research associate at the Center focusing on internet and technology research, about the new findings. The interview has been edited for clarity and condensed. One of the big takeaways from this report – and, to me, the biggest surprise – is that, while the overall number of people facing online harassment seems to be more or less stable, the nature of the harassment has changed over time. What are some of the most significant ways in which online harassment has worsened since we first started studying it? Emily Vogels, research associate at Pew Research Center While the overall number of those facing at least one of the six problems we ask about hasn’t changed, this survey finds that the level of harassment is increasing in two key ways: People are more likely to have encountered multiple forms of harassment online, and severe encounters have become more common. When the Center began studying online harassment in 2014, we found that 35% of American adults had experienced it. That grew to 41% in 2017 and remains the same in the new survey. But the shares who have ever experienced more severe forms of harassment – such as physical threats, stalking, sexual harassment or sustained harassment – or multiple forms of harassing behaviors online have both risen substantially in the past three years. This is not the pattern we saw in prior surveys. There has been a markedly steeper rise in these measures since 2017, compared with the change between our 2014 and 2017 studies. The shares who have ever experienced more severe forms of harassment or multiple forms of harassing behaviors online have both risen substantially in the past three years. Also, when we ask people about their most recent harassment experience, they’re more likely than in the past to include these more severe behaviors and involve multiple forms of harassment. And as of 2020, 41% of online harassment targets say their most recent experience spanned multiple locations online – for example, a person being harassed on social media and by text message. Does this suggest that online harassment is, to some extent, becoming “normalized”? It is commonplace. Roughly four-in-ten American adults say they’ve personally experienced harassment online. These numbers are more staggering when we look at adults under 30 – 64% of them say they’ve faced such issues online and 48% say they’ve experienced at least one of the more severe types of harassment. In addition, previous work by the Center found that a majority of adults overall have witnessed others being harassed online. Even when online harassment hasn’t been the focus of our research, we have seen this online incivility play a role in people’s perceptions and experiences of other online phenomena, such as online dating, political discussions on social media and social media in general. The Center’s past research on harassment has shown there are some demographic differences in the kinds of problems people face online. What did this survey show in particular about men, women and harassment? Men are slightly more likely than women to encounter at least one of the six types of online harassment we asked about, but there are notable differences in the types of harassment they encounter. Men are more likely than women to be called an offensive name or be physically threatened. Women are about three times as likely as men to face sexual harassment online, and younger women are even more likely to experience this type of abuse. Another difference in the new survey is that sexual harassment of women has doubled in the past three years, while the rate of sexual harassment among men is largely the same as in 2017. Women who have been the target of online harassment also report finding their most recent harassment experiences to be more upsetting than their male counterparts. There are also differences in where men and women encountered harassment online in their most recent experience. Social media sites are the most common location regardless of gender, but a larger share of women who have been harassed say their most recent incident was on social media, compared with men who have been targeted. Men targeted in online harassment are more likely than women to have been harassed while online gaming or while using an online forum or discussion site. Beyond personal experiences, men and women express different attitudes about online harassment, with women more likely to say it’s a major problem. And prior Center work finds that a greater share of women than men value people feeling safe online over people being able to speak their minds freely. When it comes to how to address online harassment, women are more optimistic than men about a variety of potential solutions, including criminal charges for social media users who harass others online, temporary or permanent bans for users who harass others, and social media companies proactively deleting bullying or harassing posts. Interesting. To what extent do those gender differences in harassment experiences reflect differences in men’s and women’s online activities? Men are more likely to report they had these types of experiences in online forums or gaming platforms. Is that because more men than women use such platforms? It’s a bit complicated. Prior work from the Center suggests there are modest gender differences in gaming, with men being more likely than women to at least sometimes play video games. But this study didn’t ask if people played games online, so we can’t say whether the gender differences in harassment incidents tied to gaming hold when looking at just online gamers. It’s worth keeping in mind that the data on where people were harassed online is for people’s most recent incident, not every incident these folks may have encountered in the past. Prior Center findings show people may stop engaging in an activity – for example, withdrawing from a platform or deleting a social media account – if they encounter harassment. Similarly, do the age differences in those who say they have experienced harassment reflect how many, and how frequently, people of different ages are online? In other words, does the fact that far more adults under 30 report experiencing online harassment reflect younger people spending much more of their lives online than older folks? We don’t quite have enough evidence to make this causal connection, but the broad patterns are pretty clear. This survey found that adults under 30 consistently experience each of the six forms of harassment we asked about at higher rates than any other age group. The Center’s previous work does show that younger adults are more likely to use the internet and to use it almost constantly. Our research on teens in 2018 found that greater exposure to the internet puts people at a higher likelihood of encountering harassment at some point online. It’s worth noting, though, that non-internet users were not asked about their possible experiences with online harassment. So, if people stopped using the internet sometime after they were harassed online, our data wouldn’t capture their earlier harassment experience. The survey finds that 75% of targets of online harassment say their most recent experience was on social media. Has this been true since the Center began researching online harassment? Do people feel social media companies have done enough to discourage this behavior? Fully 79% of Americans think social media companies are doing an only fair to poor job when it comes to addressing online harassment or bullying. The share of online harassment targets who say their most recent harassing encounter took place on social media is growing – up 17 percentage points since 2017. The Center’s prior work reveals a variety of negative opinions Americans hold about social media companies, and when it comes to Americans’ views of how these companies handle online harassment, the pattern of criticism continues. Fully 79% of Americans think social media companies are doing an only fair to poor job when it comes to addressing online harassment or bullying on their platforms. Based on previous Center findings, American teens hold similarly negative views of social media companies’ ability to address these issues. Many Americans suggest that permanent bans for users who harass others and required identity disclosure to use these platforms would be very effective ways to combat harassment on social media. To what extent do you think that the fact 2020 was an election year accounts for the increase in the number of people who say they were harassed because of their political views? Politics was already a heated issue long before this election. According to other research from the Center, partisan antipathy has been growing for years. Americans increasingly say they find they have less in common politically with people with whom they disagree, and they see political discussions online as less respectful, less civil and angrier than political discussions in other places. There are also some striking demographic differences among those who say they’ve been harassed for their politics. Online harassment targets who are White or male – 56% and 57% of each – are particularly likely to think their harassment was a result of their political views. This is especially true for White men who say they’ve been targeted, at 61%. Other groups commonly point to other aspects of their identity as the reason they faced harassment online. For example, roughly half or more Black or Hispanic online harassment targets – 54% and 47% respectively – identify their race or ethnicity as a reason they were harassed, while only 17% of their White counterparts say the same. Bear in mind that politics isn’t the only perceived reason for harassment being on the rise. Over the past several years, rising shares of online harassment targets have said they think they were harassed because of their gender, race, ethnicity, religion or sexual orientation.

Trolls are also motivated by what psychologists call “atypical social rewards”. Generally, people are motivated by creating a positive social environment (typical, positive social rewards). But trolls show higher motivation to achieve negative social rewards, like creating social mayhem and disruption. We wondered if different types of empathy could explain such seemingly pointless, harmful behaviour.

Singer-songwriter Ed Sheeran recently announced he had quit Twitter because he was sick of internet trolls. While this high-profile example shows the effects of antisocial online behaviour, it hides an alarming statistic. In one online poll over a quarter of Americans admitted to having engaged in trolling at some point. Now new research into the personality of trolls suggests building their empathy for others could be one way to modify their behaviour. What is trolling? We define trolling as deceptive and disruptive online behaviour, which typically involves posting inflammatory and malicious comments to deliberately provoke and upset people.

Almost half the population of the planet now has access to the internet, with about one in three of those people regularly active on social media. But this increased opportunity to socialise and communicate in a virtual environment has offered new avenues for antisocial behaviour. The problem of cyberbullying has received considerable research attention. However, other online antisocial behaviours with similarly harmful outcomes have received far less consideration – one example being anonymous online trolling. Trolling behaviours typically include deliberately posting inflammatory comments and argumentative messages in an attempt to provoke, disrupt and upset others. “Trolls” may pretend to be part of the group, but their real intent is to create conflict for their own amusement. Shockingly, more than a quarter of Americans have admitted to engaging in trolling behaviour at some point. Most concerning, however, is that harassing behaviours online (such as cyberbullying and trolling) are shown to have psychological outcomes similar to those of harassment offline. These outcomes can include depression, social anxiety and low self-esteem. But while cyberbullying is a clear extension of offline bullying, there is no obvious real-world counterpart to online trolling. This can make it harder to grasp exactly why it happens. Free of ads, free to read and free to republishBecome a supporter Who are the trolls? Trollface: a sign that you should steer clear. Research has defined a typical troll as an internet user who takes on a fake identity, which they then use to cause disruption and trigger conflict among others for their own amusement. The cover of anonymity allows the troll to treat the internet as their personal playground, throwing provocative comments into forums like grenades into a crowd. Trolls remain unknown to victims and, unlike cyberbullying, their victims are unknown to them. Online organisations and government bodies have made various attempts to govern and combat trolling. These include anti-troll.org and the online group Zero Trollerance. But trolling has largely eluded most attempts to control it – as shown by the huge numbers of people who admit to having done it. Is there a trolling ‘type’? One way to try to understand why people engage in trolling is to investigate whether they are likely to show particular personality traits, such as narcissism, psychopathy, Machiavellianism and everyday sadism – known as the “dark tetrad”. These traits commonly underpin many forms of social manipulation and deception, and involve a drive for ruthless self-advancement, aggression and, most notably, a lack of empathy and severe callousness. Taking each of the tetrad in turn, narcissism is associated with feelings of superiority and ego-inflation; psychopathy is linked to impulsivity and callousness; Machiavellianism is associated with manipulation and exploitation of others; and sadism is defined as the enjoyment of inflicting pain on others. A 2014 study found that people with higher levels of sadism, psychopathy and Machiavellianism were more likely to engage in online trolling behaviour, with sadism being the strongest predictor. What’s the ultimate motivation? But research on trolling behaviours has not yet considered the direct motivating factors. So my recent research sought to understand what motivates individuals to engage in trolling behaviours. If a behaviour is rewarding, an individual is more likely to do it. Because trolling depends on interaction with others, we were interested in the social rewards experienced by those who provoke these interactions. There are two forms of social rewards: typical and atypical. Typical social rewards generally occur through reciprocal social behaviours and interactions. We experience positive (or typical) social rewards when we engage in helpful, altruistic behaviour. But in our study we explored atypical social rewards, also known as “negative social potency”. Negative social potency is measured using the Social Rewards Questionnaire, in which participants indicate their agreement with statements such as “I enjoy making someone angry” and “I enjoy embarrassing others”. These are the rewarding feelings that some people experience when creating social discord, through selfish or self-serving behaviours and interactions. Individuals who seek negative social potency are likely to enjoy inflicting psychological pain and distress on others. They may achieve this through exerting negative social influence, power and strength. Personality vs motivation We gathered a sample of 396 adults (75.9% women and 24.10% men) and asked them to complete a questionnaire to measure their levels of narcissism, psychopathy, Machiavellianism and sadism. We also assessed their orientation towards negative social potency and their engagement in trolling behaviours on Facebook. Higher levels of psychopathy and sadism tend to predict trolling behaviours, with sadism being the strongest factor. We also found that men were more likely than women to engage in Facebook trolling. But more surprising was what we found when we included negative social potency in the model. The effect of negative social potency was far stronger than the effects of psychopathy and sadism. This means that while antisocial personality traits do play a role, what really influences trolling behaviour is the social pleasure derived from knowing that others are annoyed by it. The more negative social impact the troll has, the more their behaviour is reinforced. Fighting back Sage advice. MemeCenter Happily, this discovery suggests an easy way to deal with trolls: ignore them, rather than giving them the satisfaction of an angry reaction. Individuals seeking a negative social reward may still engage in trolling. But if they don’t receive that negative social reward, then their motivation to engage in this behaviour will likely diminish.

But this increased opportunity to socialise and communicate in a virtual environment has offered new avenues for antisocial behaviour. The problem of cyberbullying has received considerable research attention. However, other online antisocial behaviours with similarly harmful outcomes have received far less consideration – one example being anonymous online trolling. Trolling behaviours typically include deliberately posting inflammatory comments and argumentative messages in an attempt to provoke, disrupt and upset others. “Trolls” may pretend to be part of the group, but their real intent is to create conflict for their own amusement. Shockingly, more than a quarter of Americans have admitted to engaging in trolling behaviour at some point. Most concerning, however, is that harassing behaviours online (such as cyberbullying and trolling) are shown to have psychological outcomes similar to those of harassment offline. These outcomes can include depression, social anxiety and low self-esteem. But while cyberbullying is a clear extension of offline bullying, there is no obvious real-world counterpart to online trolling. This can make it harder to grasp exactly why it happens.

Acknowlegement This study was funded by Public Safety Canada. Start of text box Overview of the study Using multiple surveys, this article examines cyberbullying and cybervictimization among Canadian youth and young adults aged 12 to 29. With rates of online and social media use being high among young people, there is an increased risk of online forms of bullying and victimization. This paper examines the prevalence of cyberbullying and cybervictimization among young people, with a focus on identifying the at-risk populations, behaviours related to prevalence, such as internet and smart phone usage, and the association of online victimization with other forms of victimization, such as fraud and assault. Some young people are more vulnerable to cybervictimization, including Indigenous youth, sexually diverse and non-binary youth, youth with a disability, and girls and women.  Cybervictimization increases during adolescence and remains high among young adults in their early 20s. It then tapers off in the late 20s. Increased internet usage, as well as using smart phones before bed and upon waking, are associated with an increased risk of being cyberbullied. For youth aged 12 to 17, not using devices at mealtime, having parents who often know what their teens are doing online, and having less difficulty making friends act as potential buffers against cybervictimization. Cybervictimized young adults often change their behaviour, both online—from blocking people and restricting their own access—and offline—such as carrying something for protection. Cybervictimized young adults were also more likely to have experienced other forms of victimization such as being stalked and being physically or sexually assaulted. End of text box Introduction Internet use is now woven into the fabric of Canadian society. It has become a large part of everyday life, whether it is in the context of online learning, remote working, accessing information, e-commerce, obtaining services (including healthcare), streaming entertainment, or socializing. And while nearly all Canadians use the internet to some degree, Canadians under 30 represent the first generation born into a society where internet use was already ubiquitous. As such, it may not be surprising that Canadians under the age of 30 are more likely to be advanced users of the internet, compared to older generations.Note   In addition, they often spend many hours on the internet, with this usage increasing during the COVID-19 pandemic, more so than any other age group.Note  Besides proficiency and intensity, the way in which young people interact with the internet is often different from older generations. Previous Statistics Canada research has shown that younger people are more likely than their older counterparts to use social media, more likely to use multiple social media apps, and engage in more activities on these apps.Note  This use has been related to some negative outcomes for younger people, including lost sleep and trouble concentrating.Note  Social media and online activities may also place youth and young people at increased risk of cybervictimization or cyberbullying. Numerous studies have investigated both the prevalence and impact of cybervictimization, noting that youth are often at increased risk.Note   While comparisons across studies are often difficult because of definitional differences, ages of the youth being studied, and the time frames, there is consensus on the criteria for measuring cybervictimization. These include (1) intentions to harm the victim, (2) power imbalance between the bully and victim, (3) the repeated nature of aggression, (4) use of electronic devices (including phones or computers), and (5) possible anonymity.Note  This article examines cyberbullying among youth and young adults aged 12 to 29 in Canada using four population-based surveys. The Canadian Health Survey of Children and Youth (CHSCY) collects information on cyberbullying among youth aged 12 to 17, while three surveys capture this information for adults aged 18 to 29. These surveys include the Canadian Internet Use Survey (CIUS), the General Social Survey (GSS-Cycle 34) on Victimization and the Survey of Safety in Public and Private Spaces (SSPPS). Each will be used to help paint a picture of cyberbullying of younger people in Canada.Note  Definitions and measures of cyberbullying within each of the surveys are detailed in “Cyberbullying content across four Statistics Canada surveys” text box. The study starts by discussing the prevalence of, and risk factors associated with, cyberbullying among teens aged 12 to 17. This is followed by an analysis of cyberbullying among young adults aged 18 to 29. Along with providing a profile of cyberbullying, another goal is to highlight data and knowledge gaps in this area and potential areas where future surveys and research should focus. One-quarter of teens experience cyberbullying In 2019, one in four teens (25%) aged 12 to 17 reported experiencing cyberbullying in the previous year (Chart 1). Being threatened or insulted online or by text messages was the most common form, at 16%. This was followed by being excluded from an online community (13%) and having hurtful information posted on the internet (9%).   Among those aged 12 to 17, rates of cyberbullying increased with age, rising from 20% at age 12 to 27% by age 17. This perhaps reflects an increased use of the internet, and specifically social media usage with age. The largest increase in cyberbullying prevalence related to being threatened or insulted online or by text messages (from 11% at age 12 to 19% at age 17). Data table for Chart 1  Data table for chart 1 Table summary This table displays the results of Data table for chart 1 percentage (appearing as column headers). percentage Total youth aged 12 to 17 25 Hurtful information was posted on the internet 9 Excluded from an online community 13 Threatened/insulted online or by text messages 16 Source: Statistics Canada, Canadian Health Survey on Children and Youth, 2019. Besides age, the likelihood of being victimized online varied by gender, sexual attraction, Indigenous identity and educational accommodations.  Generally, boys and girls have quite similar prevalence of cybervictimization. For instance, about 1 in 4 (24% for boys and 25% for girls) reported that they experienced any of the three forms of cybervictimization. Non-binary teens, however, experienced cybervictimization at significantly higher levels than both boys and girls. Over half (52%) of teens who reported a gender other than male or female said that they were cybervictimized in the past year. The higher prevalence among non-binary teens was seen across all types of cybervictimization. The greatest difference, however, was seen for being excluded from an online community. The proportion of non-binary teens who reported this type of cybervictimization was about three and a half times the proportion recorded for boys and girls (45% versus 12% for boys and 13% for girls). In addition, youth aged 15 to 17Note  who identified as having the same gender attraction had a significantly higher likelihood of being cyberbullied (33%), compared to their peers who were exclusively attracted to a different gender (26%). This increased risk was seen for all types of cyberbullying but was most pronounced for hurtful information being posted on the internet and being excluded from an online community. First Nations youth (off-reserve) are at greater risk of cyberbullying First NationsNote  youth living off-reserve were more likely than their non-Indigenous peers to have been cyberbullied in the past year. In particular, 34% of First Nations youth reported being bullied online, compared to 24% of non-Indigenous youth. The risk was heightened for certain types of cyberbullying, including having hurtful information posted on the internet and being threatened/insulted online or by text messages. These higher levels of cybervictimization mirror the overall higher rates of victimization for Indigenous people, which could be rooted in the long-standing legacy of colonialism resulting in discrimination and systemic racismNote  (Table 1). No significant differences were observed for Inuit and Métis youth.Note   Most racialized groups had either similar or lower prevalence rates of cyberbullying compared to non-racialized and non-Indigenous youth. For example, 16% of the South Asian youth and 18% of Filipino youth said that they had experienced cyberbullying in the past year, much lower than the 27% of non-racialized, non-Indigenous youth who reported being victimized online. In addition, those born in Canada had a higher likelihood of cyberbullying, compared to the immigrant youth population (26% versus 19%). This was seen for all forms of online victimization. The differences in risk may be due to variations in frequency of going online. Indeed, previous research has shown that immigrants are less likely to be advanced users of the internet, and are more often non-users, basic users or intermediate users.Note     Table 1 Prevalence of cyberbullying among youth aged 12 to 17, by population group, 2019 Table summary This table displays the results of Prevalence of cyberbullying among youth aged 12 to 17. The information is grouped by Population Subgroups, ages 12 to 17 (appearing as row headers), Types of cyberbullying, Hurtful information was posted on the internet, Threatened/insulted online or by text messages, Excluded from an online community and Any of the 3 types of cyberbullying, calculated using percent units of measure (appearing as column headers). Population group Types of cyberbullying Hurtful information was posted on the internet Threatened/insulted online or by text messages Excluded from an online community Any of the 3 types of cyberbullying percentage Gender Boys (ref.) 7 16 12 24 Girls 10 16 13 25 Non-binary 30Note E: Use with cautionNote * 34Note E: Use with cautionNote * 45Note E: Use with cautionNote * 52Note E: Use with cautionNote * Indigenous identity First Nations 14Note E: Use with caution 23Note * 16Note E: Use with caution 34Note * Métis 12Note E: Use with caution 20 13Note E: Use with caution 30 Inuit 14Note E: Use with caution 30Note E: Use with caution Note F: too unreliable to be published 36Note E: Use with caution Non-Indigenous (ref.) 8 16 13 24 Racialized group Black 8 16 12 24 Chinese 7 11Note * 12 22 Filipino 10 10Note * 7Note * 18Note * South Asian 5Note * 9Note * 9Note * 16Note * Not part of a racialized group (ref.) 9 18 14 27 Country of Birth Canada (ref.) 9 17 14 26 Outside Canada 5Note * 11Note * 10Note * 19Note * Gender attractionTable 1 Note 1 Same gender (ref.) 15 22 17 33 Opposite gender 9Note * 18 13Note * 26Note * Youth has an education accomodation Yes 11Note * 19Note * 15 27Note * No (ref.) 7 14 12 23 Don't know 12Note * 19Note * 15 29Note * E use with caution F too unreliable to be published Note 1 Only asked of youth aged 15 to 17. Return to note 1 referrer Note * significantly different from the reference category (ref.) (p<0.05) Return to note * referrer Source: Statistics Canada, Canadian Health Survey of Children and Youth, 2019. Higher likelihood of cyberbullying among youth with education accommodation Based on results from CHSCY, having an education accommodation, such as an Individual Education Plan (IEP), Special Education Plan (SEP) or Inclusion and Intervention Plan (IIP), places youth at increased risk of cyberbullying. Overall, 27% of youth with some type of education accommodation for learning exceptionalities or special education needs were bullied online, compared to 23% of their peers without accommodation. The risk was greatest when the cyberbullying incidents involved hurtful information being posted on the internet or being threatened or insulted online or by text messages. The increased risk of cyberbullying among those with an education accommodation peaks at age 16, with 36% of 16 year-olds with an educational accommodation reporting being cyberbullied compared with 24% of youth without an accommodation.Note  Frequent use of social media tied to higher prevalence of cyberbullying among youth Because of the potential negative impacts of cyberbullying, including the effects on mental wellbeing, it is important to understand the factors that can expose youth to online harm. One of these possible factors relates to the frequency of online activity. The CHSCY asked youth how often they go online for social networking, video/instant messaging, and online gaming. The majority (about 80%) said that went online at least weekly, with 60% saying they went on social network platforms several times a day, and just over 50% reporting that they used video or instant messenger apps at this same level of frequency. About 1 in 3 (32%) teens said that they went online for gaming at least once a day or more. In general, results from CHSCY show that more frequent social networking, instant messaging use and online gaming had a strong association with an increased risk of cybervictimization. For instance, among youth who stated that they constantly use social networking, video and instant messaging or online gaming, about one-third (34%, 36% or 30% respectively) said that they had been cyberbullied in the past year. Conversely, the proportion reporting cybervictimization drops to around 20% when social networking and video and instant messaging was used less than once a week (22%, 22%, and 24% respectively). The risk decreases even further to less than 15% when youth never utilized social networking or video and instant messaging apps (Table 2).  Table 2 Prevalence of cyberbullying among youth aged 12 to 17, by frequency of social media use and gender, 2019 Table summary This table displays the results of Prevalence of cyberbullying among youth aged 12 to 17. The information is grouped by Frequency of social media use (appearing as row headers), Proportion cyberbullied in past year, by gender, Total, Boys, Girls, Social networking , Video or instant messaging and Online Gaming , calculated using percent units of measure (appearing as column headers). Frequency of social media use Proportion cyberbullied in past year Total Boys Girls Social networking Video or instant messaging Online Gaming Social networking Video or instant messaging Online Gaming Social networking Video or instant messaging Online Gaming percentage Constantly 34Note * 36Note * 30 33Note * 32Note * 30 34Note * 38Note * 28 Several times a day 27Note * 27Note * 30 26 27 30 27Note * 27Note * 29 Once a day (ref.) 21 23 27 22 25 26 20 20 29 Weekly 27 24 24 30 27 23 21 21 27 Less than weekly 22 20 24 22 21 19Note * 21 17 29Table 2 Note † Never 12Note * 14Note * 22Note * 14Note * 15Note * 15Note * 9Note * 13Note * 24Table 2 Note † Note † significant gender difference (p < 0.05) Return to note † referrer Note * significantly different from reference category (ref.) (p < 0.05) Return to note * referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Statistics Canada, Canadian Health Survey of Children and Youth, 2019. No gender differences were found between social media, video or instant messaging use and cybervictimization.Note   For instance, for both boys and girls, the proportion who said they were cybervictimized in the past year was over 30% if they constantly checked their social networking and instant messaging applications, with the risk decreasing similarly with lower levels of use. The risk of cybervictimization increases with age, from 12 to 17, mirroring the increased frequency in the use of social networking, video and instant messaging as youth age. Going online more frequently had the same impact on the cybervictimization risk for Indigenous and non-Indigenous youth. That is, going on social media more frequently increased the risk to the same extent for both Indigenous youth and non-Indigenous youth. However, this was not the case for all youth. For instance, the risk associated with more frequent social media and gaming use was greater for non-racialized youth than it was for racialized youth. Cyberbullying is sometimes related to usage patterns of electronic devices In addition to frequency of use, usage pattern of electronic devices may also be related to risk. Among youth aged 12 to 17, three-quarters (75%) used an electronic device before falling asleep in the past week. This usage pattern rises from a low of 54% at age 12 to a high of 92% by age 17. Using electronic devices before going to sleep appears to increase the risk of being cyberbullied. About 27% of youth that used their electronic device before going to sleep were cyberbullied in the past year, compared to 19% who had not used their device before going to sleep. The increased risk was most often related to being threatened or insulted online or by text messages (18% versus 11% who had not used a device before going to sleep) (Chart 2). Data table for Chart 2  Data table for chart 2 Table summary This table displays the results of Data table for chart 2 Yes, a device was used and No, a device was not used (ref.), calculated using percentage units of measure (appearing as column headers). Yes, a device was used No, a device was not used (ref.) percentage Total youth aged 12 to 17 27Note * 19 Hurtful information was posted on the internet 10Note * 5 Threatened/insulted online or by text messages 18Note * 11 Excluded from an online community 14Note * 10 Note * significantly different from the reference category (ref.) (p<0.05) Return to note * referrer Source: Statistics Canada, Canadian Health Survey of Children and Youth, 2019. Use of electronic devices before going to sleep and risk of cybervictimization is fairly constant across age, but appears to be highest at age 15, where 31% had been cybervictimized in the past year. This proportion falls to 16% if they did not use their device before bedtime. Results suggest that parents may, in some cases, serve as protective agents, by not allowing electronic devices at the dinner table and having a greater knowledge of what their teens are doing online. For most youth (71%), parents did not allow electronic devices during the evening meal. However, 21% of youth said that their parents allowed electronic devices at the evening meal and another 7% said that their family does not eat together. The association with cybervictimization, especially being threatened or insulted online or by text messages, increases if electronic devices were allowed at dinner (18% versus 15%). However, there are no differences with respect to other types of cybervictimization. The real risk of cybervictimization is not whether a device was used, but whether the family ate together, which can be influenced by financial or other circumstances, such as work schedules or extracurricular activities.  Across all types of cybervictimization, 35% of youth who had not eaten dinner with parents reported that they had been cybervictimized in the past year, significantly greater than the 26% of youth who said that electronic devices were allowed at the evening meal, and the 23% who said that electronic devices were not allowed. This risk is strongest for ages 12 and 16. Parents’ knowledge of youth’s online activities may help lower the association with cybervictimization. Most Canadian youth who go online have some types of rules or guidelines established by their parents, which is usually more stringent for younger children and is typically relaxed as they age and gain more trust.Note  In 2019, the proportion who stated that their parents often or always know what they are doing online was quite high. In all, 63% stated this level of parental knowledge, while another 37% said that their parents never or only sometimes knew what they were doing online. Parental knowledge about online activity declines with age. At age 12, 77% of youth state that their parents often or always know what they are doing online, which drops to 51% by age 16 and to 49% by age 17. As may be expected, increased parental knowledge of teen’s online activity was associated with a lower risk of cybervictimization (Chart 3). In particular, close to a third of youth (29%) who said their parents never or only sometimes knew about their online activities reported that they had been cybervictimized. This proportion drops to 22% when parents often or always knew what their teen was doing online. A similar pattern is noted regardless of type of cybervictimization experienced. Data table for Chart 3  Data table for chart 3 Table summary This table displays the results of Data table for chart 3 Parents never or sometimes know online activity and Parents often or always know online activity (ref.), calculated using percentage units of measure (appearing as column headers). Parents never or sometimes know online activity Parents often or always know online activity (ref.) percentage Total youth aged 12 to 17 29Note * 22 Hurtful information was posted on the internet 12Note * 7 Threatened/insulted online or by text messages 20Note * 13 Excluded from an online community 15Note * 12 Note * significantly different from the reference category (ref.) (p<0.05) Return to note * referrer Source: Statistics Canada, Canadian Health Survey of Children and Youth, 2019. Youth who have difficulty making friends are most vulnerable to online victimization Based on previous research,Note  knowing more people and having more friends, especially close friends can perhaps shield youth from being victimized, and if they are victimized, having friends can perhaps offset some of the negative impacts. Therefore, it is expected that individuals who have a difficult time making friends may be at greater risk of being victims of cyberbullying, as the person or persons victimizing them may believe them to be easier targets of abuse. In general, across all youth aged 12 to 17, most do not have any difficulty making friends, based on responses from parents. Just over 80% of parents reported that their teen had no difficulty in making friends, while 15% said that their teen had some difficulty and around 4% said that they had a lot of difficulty or could not do it at all. Across individual ages, these proportions are similar. Also, boys and girls have very similar patterns of ease of making friends (parents of around 80% of both boys and girls said that they had no difficulty making friends).Note  It bears mentioning that these are parents’ reports about their child’s purported difficulty making friends and therefore may not be the most accurate. Parents may not be fully aware of how well their child develops friendships, as this information may be intentionally hidden from them. With respect to cybervictimization, teens that have greater difficulty making friends have a greater risk of being cybervictimized than their peers without any difficulty. For example, 23% of youth whose parents said they have no difficulty making friends reported that they had been victims of cyberbullying in the past year.  This proportion climbs 12 percentage points to 35% if teens had a lot of difficulty or were unable to make friends (Table 3). A similar pattern was observed regardless of the type of cyberbullying. The relationship between the ease of making friends and cyberbullying was seen across all ages, though the gap appears to be greatest at age 16. For example, almost half (44%) of 16-year-old teens who had trouble forming friendship were cyberbullied, compared with 24% who had no difficulty making friends. Girls were especially vulnerable to cyberbullying when they had trouble making friends.Note  Overall, 40% of girls whose parents said had a lot of difficulty making friends, or were unable to do so, were cybervictimized. This compares to 23% of girls who had no difficulty making friends. The corresponding difference for boys was much lower, with 28% being cyberbullied if they had trouble making friends and 23% without any difficulty.  Table 3 Prevalence of cyberbullying among youth aged 12 to 17, by ease of developing friendships, 2019 Table summary This table displays the results of Prevalence of cyberbullying among youth aged 12 to 17. The information is grouped by Cyberbullying type, age and gender (appearing as row headers), Difficulty making friends, No difficulty (ref.), Some difficulty and A lot of difficulty /Cannot make friends, calculated using percent units of measure (appearing as column headers). Cyberbullying type, age and gender Difficulty making friendsTable 3 Note 1 No difficulty (ref.) Some difficulty A lot of difficulty or Cannot make friends percentage Total youth aged 12 to 17 23 32Note * 35Note * Type of cyberbullying Hurtful information was posted on the internet 7 14Note * 15Note * Threatened/insulted online or by text messages 15 22Note * 22Note * Excluded from an online community 12 18Note * 24Note * Age 12 years 18 27Note * 29 13 years 21 32Note * 32 14 years 22 28 39 15 years 27 32 28 16 years 24 35Note * 44Note * 17 years 24 40Note * 39 Gender Boys 23 29Note * 28 Girls 23 35Note * 39Note * Note 1 Based on responses from parents. Return to note 1 referrer Note * significantly different from reference category (ref.) (p < 0.05) Return to note * referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Statistics Canada, Canadian Health Survey of Children and Youth, 2019. Young adults: Women and young adults most often the target of cybervictimization The remainder of the study examines the patterns of cybervictimization among young adults aged 18 to 29.  To understand cyberbullying among this age group, three population-based surveys were used. These complementary surveys, while differing in survey design and measurement, shed light on the nature of cyberbullying and the young people most at risk. According to the 2018 SSPPS, 25% of young people aged 18 to 29 experienced some form of cybervictimization, with the most common being receiving unwanted sexually suggestive or explicit images or messages (15%) and aggressive or threatening emails, social media or text messages (13%) (Table 4). Young women were more often the target of the online abuse, with a prevalence almost double the rate for young men (32% versus 17%). This gender difference was even more pronounced for receiving unwanted sexually suggestive or explicit material, where young women were almost three times as likely to be targeted (22% versus 8%).Note   Therefore, the main gender differences appear to be with respect to cybervictimization of a sexualized nature, as there were no differences between men and women on solely aggressive content without sexual content.Note   Table 4 Prevalence of cybervictimization among young people aged 18 to 29, by age group, gender and type of cybervictimization, 2018 Table summary This table displays the results of Prevalence of cybervictimization among young people aged 18 to 29. The information is grouped by Type of cybervictimization (appearing as row headers), Total, Men, Women, Overall, 18-21 (ref.), 22-25 and 26-29, calculated using percent units of measure (appearing as column headers). Type of cybervictimization Total Men Women Young people aged 18 to 29 18 to 21 years (ref.) 22 to 25 years 26 to 29 years Young people aged 18 to 29 18 to 21 years (ref.) 22 to 25 years 26 to 29 years Young people aged 18 to 29 18 to 21 years (ref.) 22 to 25 years 26 to 29 years percentage Total 25 31 25 19Note * 17 25 16 13Note * 32Table 4 Note † 38Table 4 Note † 34Table 4 Note † 26Table 4 Note †Note * Received any threatening or aggressive emails, social media messages or text messages where you were the only recipient 13 14 13 11 9 12 8 8 16Table 4 Note † 17 18Table 4 Note † 14 You were the target of threatening or aggressive comments spread through group emails, group text messages or postings on social media 6 6 7 6 5 7 5 4 8 6 9 7 Somone posted or distributed (or threatened to) intimate or sexually explicit videos or images of you without your consent 2 2 3 2 2 3 2 1 3 2 5 3 Someone pressured you to send, share, or post sexually suggestive or explicit images or messages 6 10 5Note * 4Note * 3 5 3 3 9Table 4 Note † 16Table 4 Note † 8Table 4 Note †Note * 6Note * Someone sent you sexually suggestive or explicit images or messages when you did not want to receive them 15 20 17 10Note * 8 13 8 5Note * 22Table 4 Note † 27Table 4 Note † 26Table 4 Note † 16Table 4 Note †Note * Note † significant gender difference for a particular group (p < 0.05) Return to note † referrer Note * significantly different from reference category (ref.) (p < 0.05) Return to note * referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Statistics Canada, Survey of Safety in Public and Private Spaces, 2018. For some types of cybervictimization, there was a significantly greater risk for young adults aged 18 to 21, as compared with young adults aged 26 to 29. For instance, about 20% of young adults aged 18 to 21 reported receiving unwanted sexually suggestive or explicit images or messeges in the last year, double the 10% of young adults aged 26 to 29 who said they also received these types of unwanted images or messages. Young adults aged 18 to 21 were also twice as likely to report being pressured to send, share or post sexually suggestive or explicit images or messages (10%) than their older counterparts (5% for ages 22 to 25 and 4% for ages 26 to 29). The relationship between cybervictimization and age is similar for both men and women, though rates are always higher for women. Both men and women have about a 12-percentage point gap between ages 18 and 21 and 26 and 29 in experiencing any of the five forms of cybervictimization in the past year (25% versus 13% for men, 38% versus 26% for women). With respect to the individual forms of cybervictimization, the largest decreases by age group related to sexual victimization, especially for women. For example, for women, there was about a 10-percentage point decline from age 18-21 to age 26-29 on being pressured to send, share or post sexually suggestive or explicit images or messages (16% to 6%) and receiving unwanted sexually suggestive or explicit images or messages (27% to 16%). Greater risk of cybervictimization among LGBTQ2 young adults Data from the SSPPS also show that LGBTQ2Note  young adults were more likely than their non-LGBTQ2 counterparts to have experienced cybervictimization (49% versus 23%).Note ,Note  Moreover, the decrease in the risk of cybervictimization across age groups is not seen among the LGBTQ2 population. That is, the proportion experiencing cybervictimization at ages 18 to 21 and late 20s is similar for LGBTQ2 adults, whereas the prevalence of cyberbullying among non-LGBTQ2 young adults declines by about half between the same ages (30% at age 18 to 21 to 18% at ages 26 to 29). Interestingly, among the LGBTQ2 population, the age group with the highest rates of cybervictimization are young adults aged 22 to 25 (at 58%).  This is a rare instance of a nonlinear age trend with respect to cybervictimization declining from age 18 to age 29.Note  First Nations young adults are more frequently the victims of cyberbullying Almost half (46%) of First Nations young people living off-reserve had experienced some form of cyberbullying in the preceding year. This was nearly double the share of non-Indigenous young adults (26%). There was no increased risk among Métis or Inuit young people.Note  Among racialized groups, the likelihood of being cyberbullied was similar to the non-racialized, non-Indigenous population. There was also no difference in risk by immigrant status.  Table 5 Prevalence of cybervictimization among young people aged 18 to 29, by selected characteristics, 2018 Table summary This table displays the results of Prevalence of cybervictimization among young people aged 18 to 29. The information is grouped by Selected characteristics (appearing as row headers), Percent (appearing as column headers). Selected characteristics percentage Total 25 Gender Men (ref.) 17 Women 32Note * Racialized population Black 23 Chinese 19 Filipino 16 South Asian 18 Non-racialized (ref.) 27 Immigrant status Immigrant (ref.) 20 Canadian-born 27 Indigenous identity First Nations 46Note * Métis 31 Inuit 13 Non-Indigenous (ref.) 26 Disability No 17Note * Yes (ref.) 39 Sexual/gender diversity LGBTQ2 (ref.) 49 Non-LGBTQ2 23Note * Note * significantly different from reference category (ref.) (p < 0.05) Return to note * referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Statistics Canada, Survey of Safety in Public and Private Spaces, 2018. Young adults with a disability are more often targeted Young adults aged 18 to 29 with a disabilityNote  were significantly more likely to report that they were cybervictimized in the past year. Across all forms of cybervictimization measured in the SSPPS, 39% of young adults with a disability reported having experienced cyberbullying in the past year, compared with 17% of the nondisabled young adult population (Table 5).Note  The SSPPS also allows for the examination of gender differences among young men and women with a disability. Almost half (46%) of women with a disability had experienced cybervictimization in the past year, much higher than the 22% of women without a disability. The difference for men was less marked. In 2018, 27% of men with a disability were targeted online, compared to 14% of other young men. The severity of the disability also appears to heighten risk. Based on the SSPPS, 56% of young adults with a severe to very severe disability stated that they had been cybervictimized in the past year, while 46% with moderate disability and 34% of those with a mild disability stated the same. This compares to 17% of young adults without a disability that experienced cybervictimization in the past year.Note  Frequent smart phone use is related to cybervictimization Being continually connected to the Internet is common among young adults aged 18 to 29, though this may place them at increased risk. Over half (55%) checked their smart phone at least every 15 to 30 minutes, with another one-third (30%) checking their smart phone at least once per hour on a typical day. Heavy cell phone use, defined as checking at least every 5 minutes, was the least common, with 15% of youth falling into this category. However, heavy use was more prevalent in the younger age groups. In 2018, 17% of young adults aged 18 to 20 were heavy users, falling to 11% among those aged 27 to 29. The majority, around three quarters, of young adults between the ages of 18 and 29 also stated that the last thing they do before going to sleep is check their phones, and a similar percentage stated that they do this again first thing upon waking up. The rates of checking before bed and upon waking are very similar regardless of gender and age. About 4 out of 5 (82%) young adults aged 18 to 20 checked their phones when waking up, and 71% of young adults aged 27 to 29 did the same. This difference, however, was not statistically significant. A pattern, albeit weak, emerges showing that more frequent smart phone use is associated with more online victimization. Based on data from the CIUS, 15% of young adults who used their smart phone at least every 5 minutes said that they had been cybervictimized in the past year. This was double (statistically significant at the p < 0.10 level) the rate of young adults who checked their phone less often (7%)Note . There were no significant differences on whether one used the smart phone before going to bed or after waking up and cybervictimization in the past year. While a direct comparison cannot be made with the data from the CHSCY on ages 12 to 17 presented earlier, it is interesting to note that among 12-to-17-year-olds there was a significant association between using one’s electronic device at bedtime and risk of cybervictimization, with a higher risk noted especially for teens age 12 and age 15. Using protective measures online is more common among younger women Being victimized online can also lead people to pull back from social media and other online activities. For example, information from the SSPPS shows that about 22% of young adults aged 18 to 29 said that in the past year, they blocked people on the internet because of harassment, while 13% said they restricted their access to the internet to protect themselves from harassment. A further 3% deleted their online account because of harassment. Young women were twice as likely as young men to block people because of harassment (31% versus 13%) and to restrict their own access (17% versus 10%) (Chart 4). These gender differences may be driven by the higher overall cybervictimization rates for women.Note  Data table for Chart 4  Data table for chart 4 Table summary This table displays the results of Data table for chart 4 Men, Women, Young people aged 18 to 29, 18 to 21 years, 22 to 25 years and 26 to 29 years, calculated using percentage units of measure (appearing as column headers). Men Women Young people aged 18 to 29 18 to 21 years 22 to 25 years 26 to 29 years Young people aged 18 to 29 18 to 21 years 22 to 25 years 26 to 29 years percentage Blocked people because of harassment 13Note * 15Note * 13Note * 11Note * 31 35 33 27 Restricted own access to protect self 10Note * 7Note * 10Note * 11 17 14 20 17 Deleted online account because of harassment 3 2 3 2 4 4 5 4 Note * significant difference (p < 0.05) between men and women for a particular age group. Return to note * referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Statistics Canada, Survey of Safety in Public and Private Spaces (SSPPS), 2018. Limiting online activities as a response to cybervictimization is not surprising. Results from the GSS show a strong association between being victimized online and taking other precautions for one’s safety beyond unplugging from the internet. For example, when asked if they do certain things routinely to make themselves safer from crime, young adults aged 18 to 29 who had been cybervictimized in the past year were much more likely to say that they carry something for defense, such as a whistle, a knife or pepper spray, compared with young adults who had not experienced online victimization (12% versus 3%).  Cybervictimization associated with other forms of victimization among young people There is often a strong association between different types of in-person victimization.Note  This is also the case for cybervictimization.  Young adults who have been cybervictimized were more likely to be victims of fraud, more likely to have been stalked and also more likely to have been physically or sexually assaulted in the past year. Data from the GSS showed a connection between cybervictimization and risk of fraud. For example, 17% of young adults who had been cybervictimized in the past year said that they had also been a victim of fraud in the past year, more than four times higher than young adults who had not experienced cybervictimization (4%).Note  Cybervictimization is also highly correlated with other forms of victimization and behaviour. For instance, information from the SSPPS shows that young adults who have experienced unwanted behaviours in public that made them feel unsafe or uncomfortable had also been victims of online harassment and bullying in the past year.Note  About 45% of young adults who had experienced such behaviours had been cybervictimized in the past year, compared with 11% who had not experienced such behaviours (Table 6). The relationship between online victimization and unwanted behaviours in public appears to be similar for men and women. In particular, 41% of men and 46% of women who had experienced unwanted behaviours in public had also been cybervictimized. This compares to around 10% of men and women who had not experienced such incidents.Note  Cybervictimization may manifest itself in real-world public encounters because victims of online abuse may be highly sensitized to possibly unsafe or uncomfortable situations in public, especially in instances where the identity of the online abuser is not known. For all they know, the person making them feel unsafe or uncomfortable in public might be the very same person harassing them online.  Table 6 Prevalence of cybervictimization among young people aged 18 to 29, by experiences of in-person victimization in the past 12 months and gender, 2018 Table summary This table displays the results of Prevalence of cybervictimization among young people aged 18 to 29. The information is grouped by Gender (appearing as row headers), Felt unsafe or uncomfortable in public, Stalked and Experienced physical/sexual assault (appearing as column headers). Gender Felt unsafe or uncomfortable in publicTable 6 Note 1 StalkedTable 6 Note 2 Experienced physical/sexual assault Table 6 Note 3 Yes (ref.) No Yes (ref.) No None (ref.) One incident Two or more incidents percentage Total young people aged 18 to 29 45 10Note * 67 22Note * 21 54Note * 64Note * Men 41 10Note * 57 16Note * 15 44Note * 54Note * Women 46 11Note * 72 29Note * 27 62Note * 70Note * Note * significantly different from reference category (ref.) (p < 0.05) Return to note * referrer Note 1 Respondents were asked: Thinking about time you spent in public spaces in the past 12 months, how many times has anyone made you feel unsafe or uncomfortable by doing any of the following? Making unwanted physical contact, such as hugs or shoulder rubs or getting too close to you in a sexual manner. Indecently exposing themselves to you or inappropriately displaying any body parts to you in a sexual manner. Making unwanted comments that you do not look or act like a [man/woman/man or woman] is supposed to look or act. Making unwanted comments about your sexual orientation or assumed sexual orientation. Giving you unwanted sexual attention, such as inappropriate comments, whistles, calls, suggestive looks, gestures, or body language. Return to note 1 referrer Note 2 Respondents were asked: In the past 12 months, have you been stalked, that is, have you been the subject of repeated and unwanted attention, by someone other than a current or former spouse, common-law partner or dating partner. Return to note 2 referrer Note 3 Respondents are asked if the following incidents happened to them in the past 12 months (excluding acts committed by a current or previous spouse, common-law partner or dating partner): a. been attacked, b. anyone threatened to hit or attack you or threatened you with a weapon, c. has someone touch them in a sexual way against their will, d. has someone forced or attempted to force them into unwanted sexual activity by threatening them, holding them down or hurting them in some way, e. has anyone subjected you to a sexual activity to which you were not able to consent, that is, were you drugged, intoxicated, manipulated or forced in other ways than physically. Respondents are then asked if these things happened in one incident or more than one incident. Return to note 3 referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Statistics Canada, Survey of Safety in Public and Private Spaces, 2018. According to the SSPPS, young adults who have been stalked in the past year have also been victims of online bullying and harassment in the past year.Note   For instance, 67% of young adults who stated that they had been stalked in the past year also stated that they had been cybervictimized in the past 12 months, three times higher than young adults who had not been stalked in the past year (22%). The relationship is similar for both men and women, with over 72% of women and 57% of men who had been stalked also stating that they had been cybervictimized. Being a victim of stalking is more prevalent among women in general, as 32% of women stated they had been stalked, significantly greater than the 17% of men who stated that they had been stalked.Note  A connection between online victimization and physical and sexual assaults also exists.Note  Overall, among victims of physical and sexual assault, the proportion that said they were also cybervictimized was very high. In 2018, 54% of physical or sexual assault victims reported being cybervictimized, climbing to 64% if young people had experienced two or more incidents of physical or sexual assault. The strong association is present for both young adult men and women, with consistently higher prevalence for women regardless of number of physical or sexual assaults. Perpetrators of online victimization are most often men and known to the victim An important area of research on cybervictimization that is often lacking relates to the gender of the offender and the relationship between the offender and the victim. Using the SSPPS, it is possible to understand the characteristics of the perpetrator in cybervictimization incidents (Chart 5). About two-thirds (64%) of young adults who had been cybervictimized stated that a man (or men) was responsible, while 19% said it was a woman (or women), 4% said that it was both, and 13% did not know the gender of their online attacker. This general pattern was similar regardless of gender of the victim, though for women victims, the perpetrator was much more likely to be a man (or men). For instance, 73% of women who had been victimized stated that their offender(s) was (were) a man/men, while 13% stated that it was a woman or women. In contrast, 45% of men said that it was a man (or men) that was responsible, while 31% stated that their offender(s) was a woman or women. At the same time, 19% of men and 11% of women did not know the gender of their online offender.Note  Data table for Chart 5  Data table for chart 5 Table summary This table displays the results of Data table for chart 5 Total, Gender of victim, Male victim (ref.) and Female victim, calculated using percentage units of measure (appearing as column headers). Total Gender of victim Male victim (ref.) Female victim percentage Male offender 64 45 73Note * Female offender 19 31 13Note * Both male and female offenders 4 6 3 Don’t know 13 19 11 Note * significantly different from reference category (ref.) (p < 0.05) Return to note * referrer Note: Due to sample size limitations, the non-binary category is not releasable. Source: Survey of Safety in Public and Private Spaces (SSPPS), 2018. The SSPPS also has information on the relationship of the offender and victim for the most serious incident of inappropriate online behaviour (combining single and multiple offender incidents). The most common offenders, at 55%, were offenders known to the victim, including friends, neighbours, acquaintances, teachers, professors, managers, co-workers, and classmates, as well as family members or current or former partners including spouses, common-law partners or dating partners. Meanwhile, 45% were offenders who were not known to the victim, including strangers or persons known by sight only. Thus, results show that the perpetrator was known to the victim in more than 50% of cases, regardless of the gender of the victim. Based on the SSPPS, 53% of men victims and 56% of women victims knew the person victimizing them online.  Conclusion Internet and smart phone use among youth and young adults in Canada is at a very high level, particularly since the pandemic. It is a tether to the outside world, allowing communication with one another, expanding knowledge, and being entertained. It is this importance and pervasiveness that makes it particularly challenging when there are risks of online victimization. A goal of this study was to highlight the current state of cybervictimization among Canadian youth and young adults aged 12 to 29. Four separate surveys were used to paint a picture of who is most at risk of cybervictimization, how online and offline behaviours may contribute to this association, and the association with other forms of victimization. Based on the analysis of the data, there are five key messages related to cybervictimization of youth and young adults: Not all youth and young adults experience cybervictimization equally.  Those that are most vulnerable to online harm were youth aged 15 -17 with same-gender attraction or, more broadly, LGBTQ2 young adults aged 18-29, youth and young adults with a disability, Indigenous youth, and young adult women when the cybervictimization measures were more of a sexual nature. Cybervictimization increases during adolescence and remains high among young adults in their early 20s. The risk drops somewhat as young adults approach age 30. This age pattern was found using two surveys that allowed for prevalence estimates by smaller age groupings (CHSCY and SSPPS). The prevalence estimates were not completely comparable across ages 12 to 29, but the pattern remained. Greater internet use, as well as using devices at bedtime and upon waking up was associated with being cybervictimized. Potential buffers of this connection especially for the teenage population (ages 12-17) were not using devices at mealtime, having parents who often know what their teens were doing online, and having less difficulty making friends. Taking action to make themselves safer was seen for youth and young adults who have been cybervictimized. This included blocking people online, restricting their own internet access, and carrying something for protection when offline. Experiencing other forms of victimization was more common among those who were cybervictimized. This includes being stalked and being physically or sexually assaulted, and experiencing other types of unwanted behaviours in public. The benefits of the internet for the youth and young adult population are numerous, however, as this study has illustrated, there are certain risks associated with the anonymity and widespread exposure to many unknown factors while online. Knowing the socio-demographic factors and internet use patterns associated with cybervictimization can help tailor interventions to better prevent and respond to cybervictimization. Future analytical work should continue to better understand online victimization faced by youth and young adults. Darcy Hango is a senior researcher with Insights on Canadian Society at Statistics Canada. Start of text box Data sources, methods and definitions Four surveys are used in this paper: (1) Canadian Health Survey on Children and Youth (CHSCY), 2019; (2) Canadian Internet Use Survey (CIUS),2018-2019; (3) General Social Survey GSS on Victimization (cycle 34): 2019-2020, and (4) Survey of Safety in Public and Private Spaces (SSPPS): 2018. The analysis is split into 2 separate broad age groups: ages 12 to 17 is examined using the CHSCY, and ages 18 to 29 is examined using the CIUS, the GSS, and the SSPPS. There remain data gaps in cybervictimization. For instance, there is a need for more information on the perpetrators of cybervictimization. This may involve adding more follow-up questions on existing surveys, whether it is CHSCY or victimization surveys. Moreover, information on specific types of social media platforms, such as social networking sites, image-based sites and discussion forums would be helpful to pinpoint which applications are seeing the most incidents of cyberbullying. As internet use and potential harm is not restricted to people aged 12 and older, it would be critical to understand the prevalence and nature of cybervictimization for the youngest Canadians, those under the age of 12, recognizing that survey adaptation and ethical considerations would need to be considered. Lastly, certain population subgroups are more at risk of cybervictimization than others and the research for this study revealed that an inadequate sample size for some groups, such as Indigenous youth and young adults, as well as sexually and gender diverse youth and young adults, limits the ability to understand the dimensions of the issue for these populations. As such, it is necessary to consider oversampling certain groups to produce meaningful cybervictimization estimates. An additional concern, overarching many of the above issues, is the “digital divide”, particularly affecting communities in rural areas and the north. Recent statistics reveal that in 2017, 99% of Canadians had access to long term evolution (LTE) networks, though this was true for only about 63% of Northern residents.Note  The disparity in connectivity may have an adverse impact especially for the Indigenous population in terms of not only Indigenous youths’ underrepresentation in Canadian data on cyberbullying, but also digital literacy initiatives in Northern or in First Nations and Inuit communities. End of text box                                 Start of text box Cyberbullying content across four Statistics Canada surveys 1. Canadian Health Survey on Children and Youth (CHSCY), youth aged 12 to 17 years, 2019 (data collection period between February and August 2019) During the past 12 months, how often did the following things happen to you? Someone posted hurtful information about you on the Internet Someone threatened or insulted you through email, instant messaging, text messaging or an online game Someone purposefully excluded you from an online community 2. Canadian Internet Use Survey (CIUS), people aged 15 years and older, 2018-2019 (data collection period between November 2018 and March 2019) Universe: Internet users in the past 3 months During the past 12 months, have you felt that you were a victim of any of the following incidents on the Internet? Did you experience? Bullying, harassment, discrimination Misuse of personal pictures, videos or other content Other incident 3. General Social Survey GSS on Victimization (cycle 34), people aged 15 years and older, 2019-2020 (data collection period between April 2019 and March 2020) Universe: Internet users in the past 12 months In the past 5 years, have you experienced any of the following types of cyber-stalking or cyber-bullying? This can be narrowed down to past year by the following question: “You indicated that you experienced some type of cyber-stalking or cyber-bullying in the past 5 years. Did any occur in the past 12 months?” You received threatening or aggressive emails or instant messages where you were the only recipient You were the target of threatening or aggressive comments spread through group emails, instant messages or postings on Internet sites Someone sent out or posted pictures that embarrassed you or made you feel threatened Someone used your identity to send out or post embarrassing or threatening information Any other type 4. Survey of Safety in Public and Private Spaces (SSPPS), people aged 15 years and older, 2018 (data collection period between April and December 2018) Universe: Internet users in the past 12 months Indicate how many times in the past 12 months you have experienced each of the following behaviours while online. You received any threatening or aggressive emails, social media messages, or text messages where you were the only recipient You were the target of threatening or aggressive comments spread through group emails, group text messages or postings on social media Someone posted or distributed, or threatened to post or distribute, intimate or sexually explicit videos or images of you without your consent Someone pressured you to send, share, or post sexually suggestive or explicit images or messages Someone sent you sexually suggestive or explicit images or messages when you did not want to receive them End of text box Notes Note Internet-use Typology of Canadians: Online Activities and Digital Skills Return to note  referrer Note See Bilodeau, Kehler, and Minnema 2021 Return to note  referrer Note Canadians’ assessments of social media in their lives Return to note  referrer Note Other concerns as a result of increased internet and/or smart phone usage such as lack of sleep and anxiety are important but are left for other research. A recent example is an article by Schimmele et al 2021. Return to note  referrer Note Because there are already very comprehensive reviews of the prevalence and consequences of cybervictimization in Canada and abroad this is not gone into detail here. Readers should consult Zych et al 2019 ; Field 2018 for reviews, and Kim et al 2017; Hango 2016; and Holfeld and Leadbeater 2015 for examples of recent research using Canadian data. Return to note  referrer Note See Field, 2018 Return to note  referrer Note All differences are significant at p <0.05 level, unless otherwise noted. Return to note  referrer Note Questions on sexual attraction were only asked for youth aged 15 to 17. Return to note  referrer Note The Indigenous population covered in this paper are from all provinces and territories. In both the CHSCY and the SSPPS samples were selected from across Canada. The samples do not include youth and young adults living on First Nations reserves and other Aboriginal settlements. Return to note  referrer Note See Perreault 2022 for recent research focused on exploring victimization trends among the Indigenous population in Canada. Return to note  referrer Note The sample size for Inuit youth was too small to detect significant differences between groups. Return to note  referrer Note Wavrock, Schellenberg, and Schimmele 2021. Return to note  referrer Note The analysis by age is not shown but is available upon request. Return to note  referrer Note Sample size was not sufficient to conduct analyses in this section separately for the gender diverse population. Return to note  referrer Note See MediaSmarts 2022. Return to note  referrer Note See for example, research by Bollmer et al 2005 and Kendrick et al 2012. Return to note  referrer Note Due to sample size limitations, analysis does not include gender diverse youth. Return to note  referrer Note Due to sample size limitations, analysis does not include gender diverse youth. Return to note  referrer Note Due to sample size limitations, analysis does not include gender diverse young adults. Return to note  referrer Note Among ages 12 to 17, there were no differences between boys and girls on cybervictimization because none of the measures explicitly asked whether the bullying was of a sexual nature. Some additional analysis on the SSPPS on ages 15 to 17 (available upon request), showed that teen girls did report a significantly higher probability than teen boys of experiencing the three cybervictimization forms that explicitly tapped into the sexualized nature of the abuse. There were no gender differences on the two measures that only asked about aggressive cybervictimization. Return to note  referrer Note Based on the SSPPS derived variable of ‘LGBTQ2’, which uses responses to sex at birth, gender, and sexual orientation. Return to note  referrer Note This aligns with other research on violent victimization among the LGBTQ population. See Jaffray 2020; Cotter and Savage 2019. Return to note  referrer Note In the GSS, LGBTQ2 young adults also reported a significantly higher probability of experiencing cybervictimization in the form of pictures that embarrassed or threatened them (4.4% versus 1%). Return to note  referrer Note These estimates are not presented in a table but are available upon request. Return to note  referrer Note The sample size for Inuit young adults was too small to detect significant differences between groups. Return to note  referrer Note A person is defined as having a disability if he or she has one or more of the following types of disability: seeing, hearing, mobility, flexibility, dexterity, pain-related, learning, developmental, memory, mental health-related. Return to note  referrer Note In the GSS, a larger share of young adults with a disability also reported being cybervictimized via aggressive comments through email (4.3% versus 1.1%), and in CIUS, on any of the 3 types of cybervictimization measures (18.1% versus 7%). Return to note  referrer Note These results are not in a table and are available upon request. Based on the global severity score, severity classes were established. Severity scores increase with the number of disability types, the level of difficulty associated with the disability and the frequency of the activity limitation. The name assigned to each class is simply intended to facilitate use of the severity score. It is not a label or judgement concerning the person’s level of disability. The classes should be interpreted as follows: people in class 1 have a less severe disability than people in class 2; the latter have a less severe disability than people in class 3; and so on. For more information on severity scores and classes, please refer to the Canadian Survey on Disability (CSD), 2017: Concepts and Methods Guide. Return to note  referrer Note These proportions are not statistically different from each other due to high sampling variability. Return to note  referrer Note Recall that data from the SSPPS showed that 32% of young women said they were cybervictimized in the past year, compared with 17% of young men. Return to note  referrer Note See examples of some research that examines links between different types of victimization for example see Finkelhor et. al 2011; Turner et. al 2016; Waasdorp and Bradshaw 2015. Return to note  referrer Note Fraud in this case refers to having one’s personal information or account details used to obtain money or buy goods and services, having one’s personal information or account details used to create or access an account, apply for benefits, services or documents, and having been tricked or deceived out of money or goods either in person, by telephone or online. Return to note  referrer Note Respondents were asked: Thinking about time you spent in public spaces in the past 12 months, how many times has anyone made you feel unsafe or uncomfortable by doing any of the following? a. Making unwanted physical contact, such as hugs or shoulder rubs or getting too close to you in a sexual manner, b. Indecently exposing themselves to you or inappropriately displaying any body parts to you in a sexual manner, c. Making unwanted comments that you do not look or act like a (man/woman) is supposed to look or act, d. Making unwanted comments about your sexual orientation or assumed sexual orientation, or e. Giving you unwanted sexual attention, such as inappropriate comments, whistles, calls, suggestive looks, gestures, or body language. Return to note  referrer Note Due to sample size limitations, analysis does not include gender diverse young adults. Return to note  referrer Note Respondents were asked: In the past 12 months, have you been stalked, that is, have you been the subject of repeated and unwanted attention, by someone other than a current or former spouse, common-law partner or dating partner. Return to note  referrer Note These results are not shown in a table but are available upon request. Return to note  referrer Note In the SSPPS, respondents were asked if the following things happened to them in the past 12 months (excluding acts committed by a current or previous spouse, common-law partner or dating partner): a. been attacked, b. anyone threatened to hit or attack them or threatened them with a weapon, c. has someone touch them in a sexual way against their will, d. has someone forced or attempted to force them into unwanted sexual activity by threatening them, holding them down or hurting them in some way, e. has anyone subjected them to a sexual activity to which they were not able to consent, that is, were they drugged, intoxicated, manipulated or forced in other ways than physically. Respondents are then asked if these things happened in one incident or more than one incident. Return to note  referrer Note Due to sample size limitations, analysis does not include non-binary young adults. Return to note  referrer Note See CRTC Communications Monitoring Report, 2019. Return to note  referrer Related information Related Articles Bullying victimization among sexually and gender diverse youth in Canada Social Media Use, Connections and Relationships in Canadian Adolescents Findings from the 2018 Health Behaviour in School-aged Children (HBSC) Study Data sources Canadian Health Survey on Children and Youth Survey of Safety in Public and Private Spaces General Social Survey - Canadians' Safety Canadian Internet Use Survey Bibliographic references References How to cite this article  More information ISSN: 2291-0840 Note of appreciation Canada owes the success of its statistical system to a long-standing partnership between Statistics Canada, the citizens of Canada, its businesses, governments and other institutions. Accurate and timely statistical information could not be produced without their continued co-operation and goodwill. Standards of service to the public Statistics Canada is committed to serving its clients in a prompt, reliable and courteous manner. To this end, the Agency has developed standards of service which its employees observe in serving its clients. Copyright Published by authority of the Minister responsible for Statistics Canada. © His Majesty the King in Right of Canada as represented by the Minister of Industry, 2023 Use of this publication is governed by the Statistics Canada Open Licence Agreement. Catalogue no. 75-006-x Frequency: Occasional Ottawa Related infographics Cyberbullying among youth in Canada Cybervictimization among young adults in Canada Date modified: 2023-03-15

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sing social media strategically:   When using social media for a specific purpose it is always a good idea to consider your strategy. The following are good things to consider when using digital tools for learning:  Put the purpose first – you should always consider what you are hoping to achieve before using any digital tool, considering this will help you to choose the best tool for the job.   Look at what is out there – there are many online tools that could potentially help you with your learning and these aren’t limited to social media networks such as Facebook or Twitter.  What are other people doing? – It is always useful to consider how other people have used these tools for education. You could have a key figure in your field in mind and research their methods. Other professionals can often be willing to share their practices if you reach out on social media.   Get organised – it is always useful to plan your online strategy – perhaps using the above bullets as a template to consider your social media use. Having a plan usually makes it easier to consider your next steps and analyse results of your findings.  Review how you use social media / digital tools – technology is always changing, as will your needs throughout your studies and professional career, therefore you should regularly review how you intend to interact with online materials.  How can different social media sites enhance learning?  Here are some ideas that you could think about:  X (Twitter) Threads:  Keep up to date with live discussions from around the world following events such as major news or updates in industry.  To promote a project e.g. blog or to gather information by posting the link to an online survey for data collection.  An opportunity to be part of the conversation within a professional industry.  LinkedIn:  Reach out and connect with industry experts and their networks via company pages.  Promoting yourself and your professional/academic achievements – this information can also be seen by employers.  Joining groups of discussion – initially to observe, and later to contribute   Facebook:  Connecting with your peers and coordinating study using closed groups  Finding out what’s going on at your institution through relevant pages.  Pinterest:   Gathering ideas, particularly if you’re a visual learner.  Storyboarding ideas.  Developing a portfolio.  Creating a visual reading list.  How does it enhance communication? Tools for example like Whatsapp, Discord and Messenger can be useful when using together in groups to maintain a direct line of communication and organise roles and activities.

he conversation map is a living, breathing representation of Social Media and will evolve as services and conversation channels emerge, fuse, and dissipate. If a conversation takes place online and you’re not there to hear or see it, did it actually happen? Indeed. Conversations are taking place with or without you and this map will help you visualize the potential extent and pervasiveness of the online conversations that can impact and influence your business and brand. As a communications or service professional, you’ll find yourself at the center of the prism – whether you’re observing, listening or participating. This visual map is the ideal complement to The Essential Guide to Social Media and the Social Media Manifesto, which will help you better understand how to listen and in turn, participate transparently, sincerely, and effectively. As conversations are increasingly distributed, everything begins with listening and observing. Doing so, will help you identify exactly where relevant discussions are taking place, as well as their scale and frequency. This dialog can be charted into a targeted social map that’s unique to your brand. In the example below, I created a Social Map using MindJet to represent the communities where I either need to or currently contribute based on my initial research.

Open accessTips and Tools29 January 2021 Share on Sharing Notes Is Encouraged: Annotating and Cocreating with Hypothes.is and Google DocsAuthors: Carlos C. Goller ccgoller@ncsu.edu, Micah Vandegrift, Will Cross, Davida S. SmythAuthors Info & Affiliationshttps://doi.org/10.1128/jmbe.v22i1.2135 101,598MetricsTotal Citations10Total Downloads1,598View all metrics CitePDF/EPUBContents JMBE Volume 22, Number 130 April 2021ABSTRACTINTRODUCTIONPROCEDURECONCLUSIONACKNOWLEDGMENTSSupplemental MaterialREFERENCESInformation & ContributorsMetrics & CitationsReferencesFiguresTablesMediaShareABSTRACTEffectively analyzing literature can be challenging for those unfamiliar with studies from rapidly evolving research fields. Previous studies have shown that incorporating primary literature promotes scientific literacy and critical thinking skills. We’ve used collaborative note-taking and annotation of peer-reviewed articles to increase student engagement with course content and primary literature. Participants annotate articles using the web-annotation tool Hypothes.is and have access to comments from their peers. Groups are then assigned to summarize the annotations and findings, posting a synthesis for the course’s Hypothes.is group. In parallel, students contribute to common notes. The instructor generates a weekly video discussing the student notes. The goal of these activities is to foster an environment of open annotation and co-creation of knowledge to aid in studying for deeper learning. Compiled notes can be used to create an open educational resource (OER). The OER provides an entry point for future students and the public. Based on the evaluation of annotations, notes, and assessments, we conclude that these activities encourage student engagement and achievement of learning outcomes while raising awareness of the importance of open and collaborative practices.INTRODUCTIONReading primary literature can be challenging for those unfamiliar with terminology or methodology (1–3). Often, students highlight long passages or read over unfamiliar jargon without fully comprehending the significance and details of a study. Several approaches have been described to promote the critical reading and analysis of primary literature (4–9). While these methods provide structure, students often read and analyze in isolation, as the methods do not facilitate virtual and open peer collaboration. Additionally, note-taking is a skill that is not commonly taught or emphasized in science courses (10). To create an inclusive and empowering environment of cocreation of knowledge, we’ve infused an upper-division metagenomics course with activities to reduce the anxiety of reading primary literature and note-taking and promote collective and collaborative constructivism.Many tools are available that allow collaborative work on electronic documents. Google Docs, Sheets, and Slides can be used to enable participants to contribute. There are also resources to annotate web pages. One such tool often used in the humanities is Hypothes.is (11–14); it is free, open source, and easy to use in classroom settings, including online courses. Initiatives such as Science in the Classroom (https://www.scienceintheclassroom.org/) have led to studies highlighting the use of annotation as a pedagogical tool (15–17).Student collaborative notes and summaries can be used to create an Open Educational Resource (OER). Furthermore, student-created OERs can foster a sense of ownership as class participants work toward creating a common resource that will serve them and a wider audience beyond the course (18).PROCEDUREWe introduced the use of Hypothes.is and collaborative notes in the fall of 2019 in an 8-week upper-division undergraduate and graduate student Metagenomics course (19). The course has weekly lectures of 1 hour 50 minutes and 5-hour labs with a course-based research project that relies heavily on the assigned readings. There were 15 students enrolled in the course: 4 undergraduates and 11 graduate students. The study was approved by the NCSU IRB (#20309).Students annotate articles using Hypothes.is (https://web.hypothes.is/) and have access to all comments. Hypothes. is a free open-source software package that allows users to highlight and annotate websites and text. Students are required to submit at least 10 meaningful annotations before the in-class discussion (see Appendix 1). A week after the discussion, groups of three or four students assigned to summarize the article post a brief synopsis on the class’s Hypothes.is group (Fig. 1 and Appendix 1).FIGURE 1.FIGURE 1. “Sharing Notes is Encouraged” workflow. Students annotate and cocreate notes to produce an OER for studying and future course participants. Students use Hypothes.is to annotate primary literature as homework assignments, following set guidelines (for details see Appendix 1), and groups are tasked with creating shared summaries for the class to view within a Hypothes.is group. Students contribute to shared notes both during and outside of the class session. The instructor then uses the notes to produce weekly recaps to provide feedback and encouragement. Student contributions are then compiled to create a final OER, containing all notes and annotations generated over the course of the semester in a publicly viewable dynamic resource (for a sample OER, go to go.nscu.edu/bitmetagenomics) and click on “Meta Book”). PB, Pressbooks.For collective notes, students have access to a Google Doc with the learning outcomes for each class session. Students are encouraged to contribute by providing definitions, examples, and links to additional resources. Notes are not graded but are lightly edited by the instructor for accuracy. Peers can provide constructive feedback and correct, remedy, or amend misconceptions and inaccuracies. Each week the instructor generates a video reviewing the notes and administers individual quizzes based on the content of the class notes.Students are informed that, with their consent, their notes and annotations can be used to create an OER that would benefit them and others beyond the course. An example of a student-generated OER is available at go.ncsu.edu/bitmetagenomics.Materials and preparationInstructors create a private course Hypothes.is “group” and share the link with students via their Learning Management System (LMS) or e-mail. Students require free Hypothes.is accounts. If using the Google Chrome browser, there is a useful Hypothes.is extension. Helpful tutorials for using Hypothes.is in education can be found on the website: https://web.hypothes.is/education/. If Google Docs are to be used for shared class notes, the instructor needs to make the document editable by participants. The creation of a short link that is easy to remember may be helpful. The instructor should provide guidelines for annotation (types of annotations including asking questions, clarifying or linking to resources, and examples of tags used by others), expectations for the number of individual annotations, and grading rubrics (Appendix 1). Frequently presenting or projecting the progress of the class notes encourages participation. The instructor can read and discuss the class notes in a short (6- to 15-min) weekly screencast video posted on an unlisted YouTube playlist (e.g., https://go.ncsu.edu/metanotes19).Students that contribute to class notes can produce a final web-based Pressbooks OER. Pressbooks is an affordable ($20 to $100/eBook) and easy-to-use online eBook creation platform used by universities and the OER community [e.g., Granite State College OERs (https://granite.pressbooks.pub/) and BC Open Textbooks (https://opentextbc.ca/pressbooks/)].Modifications and extensionsThe Hypothes.is annotation and group summaries assignment has been adapted for other lab-based courses. For example, for an undergraduate and graduate student 8-week Yeast Metabolic Engineering lab module (20), we have modified the assignment guidelines to allow students to complete the minimum number of meaningful annotations after the in-person discussion of articles. This extension resulted in several participants returning to the papers weeks later to provide additional information. Guidelines can be modified to increase the minimum number of annotations, have students ask and respond to each other, find related studies, or alter the due dates (e.g., until after in-class discussion). The rubric for group summaries can be modified for different course learning outcomes (e.g., data analysis). An example of an annotated paper can be shared with students; for example, a microbiome study from Science in the Classroom can help students learn to annotate using different tags/elements (https://www.scienceintheclassroom.org/research-papers/whats-normal-scoop-poop).Instructors can choose to encourage all participants to contribute to class notes by making the assignment credit-bearing. Instead of weekly screencast videos, alternatives include an audio file, podcast, or e-mail announcement. Other OER platforms exist, and some faculty may decide to use WordPress or GoogleSites to create publicly accessible sites to publish the collective contributions of participants. Data privacy and consent cannot be overlooked: talk to your students about posting their names on publicly facing sites, after asking for their consent in writing. Instructors are encouraged to contact other faculty to collaborate on topic-specific OERs.CONCLUSIONStudents annotate and produce summaries and collaborative notes following the guidelines. Analysis of the annotations and quiz grades suggests that participants are engaging with the articles (Fig. 2) and able to summarize the findings of the studies (Appendix 2). Annotations of student-selected papers by groups indicate students continue to use rich annotations. Participants contribute to a Google Doc and view weekly video summaries.FIGURE 2.FIGURE 2. Students annotated assigned papers frequently and began using descriptive “tags.” (A) Students used the Hypothes.is tool to annotate reading assignments and tag keywords or phrases. Some students responded to other comments and included links and other resources. (B) All students’ (n = 15) annotated readings.We note that, while students unfamiliar with Hypothes.is require a demonstration, having seen the demonstration, participants are capable of providing productive comments about the studies. For all the articles we’ve included as reading, students have contributed definitions, links to additional resources, and even responses to questions posed by peers. We advise that instructors highlight the benefits of collaborative annotation and critical note-taking. Our study demonstrates the impact of creating a scholarly community to promote learning and how it can encourage participation and ownership of an OER project. Our implementation demonstrated that all students made annotations and contributed their thoughts and ideas to the shared notes document. These efforts helped constitute a student-derived OER that could serve not only these students beyond the course but others as well.ACKNOWLEDGMENTSThe NCSU OPEN Incubator Program (summer 2019) provided training and inspired us to use Hypothes.is in this course and beyond. We are grateful for funding from the National Science Foundation (NSF) and to the PALM network for providing mentorship and access to active learning resources. The NCSU Biotechnology Program (BIT) provided the resources to offer the Metagenomics and Yeast Metabolic Engineering courses in which these activities were implemented. C.C.G. is also supported by an NIH Innovative Program to Enhance Research Training (IPERT) grant, “Molecular Biotechnology Laboratory Education Modules (MBLEMs)” 1R25GM130528-01A1. We thank the students in the fall 2019 BIT 477/577 Metagenomics course for their patience, commitment, feedback, and energy. This study has been reviewed by the Institutional Review Board at North Carolina State University and approved under protocol number #20309. We do not have any conflicts of interest to declare.Supplemental MaterialFile (jmbe00006-21_supp_1_seq2.pdf)Download1000.11 KBASM does not own the copyrights to Supplemental Material that may be linked to, or accessed through, an article. The authors have granted ASM a non-exclusive, world-wide license to publish the Supplemental Material files. Please contact the corresponding author directly for reuse.REFERENCES1.Rawlings JS. 2019. Primary literature in the undergraduate immunology curriculum: strategies, challenges, and opportunities. Front Immunol 10:1857.Go to CitationViewPubMedWeb of ScienceGoogle Scholar2.Nelms AA, Segura-Totten M. 2019. Expert–novice comparison reveals pedagogical implications for students’ analysis of primary literature. 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Analysis of student engagement in an online annotation system in the context of a flipped introductory physics class. Phys Rev Phys Educ Res 12:e020143.Go to CitationViewGoogle Scholar17.Sahota M, Leung B, Dowdell S, Velan GM. 2016. Learning pathology using collaborative vs. individual annotation of whole slide images: a mixed methods trial. BMC Med Educ 16:311.Go to CitationViewPubMedWeb of ScienceGoogle Scholar18.Yaeger J, Wolfe T. 2018. Creating the ripple effect: applying student-generated OER to increase engagement in distance education and enhance the OER community. Digital Universities 1/2.Go to CitationGoogle Scholar19.Goller CC, Ott LE. 2020. Evolution of an 8-week upper-division metagenomics course: diagramming a learning path from observational to quantitative microbiome analysis. Biochem Mol Biol Educ 48:391–403.Go to CitationViewPubMedWeb of ScienceGoogle Scholar20.Gordy CL, Goller CC. 2020. Using metabolic engineering to connect molecular biology techniques to societal challenges. Front Microbiol.Go to CitationViewPubMedWeb of ScienceGoogle ScholarInformation & ContributorsInformationContributorsInformationPublished In Journal of Microbiology & Biology EducationVolume 22 • Number 1 • 30 April 2021eLocator: 10.1128/jmbe.v22i1.2135PubMed: 33584941Copyright© 2021 Goller et al. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license.HistoryReceived: 12 April 2020Accepted: 28 November 2020Published online: 29 January 2021TopicsAnnotation Tools and PipelinesGenome AnnotationGenome Assembly and AnnotationMicrobial GenomicsMicrobial Physiology and GeneticsMicrobiome ResearchDownload PDFContributorsExpand AllAuthorsCarlos C. Goller ccgoller@ncsu.eduDepartment of Biological Sciences and Biotechnology Program (BIT), North Carolina State University, Raleigh, NC 27695View all articles by this authorMicah VandegriftNC State University Libraries, Raleigh, NC 27695View all articles by this authorWill CrossNC State University Libraries, Raleigh, NC 27695View all articles by this authorDavida S. SmythEugene Lang College of Liberal Arts at The New School, New York City, NY 10011View all articles by this authorMetrics & CitationsMetricsCitationsMetrics Article MetricsView all metricsDownloadsCitationsNo data available.0204060Jan 2022Jan 2023Jan 2024Jan 20251,59810TotalFirst 90 Days6 Months12 MonthsTotal number of downloads and citations Note: For recently published articles, the TOTAL download count will appear as zero until a new month starts. There is a 3- to 4-day delay in article usage, so article usage will not appear immediately after publication. Citation counts come from the Crossref Cited by service. 11030Smart Citations11030Citing PublicationsSupportingMentioningContrastingView CitationsSee how this article has been cited at scite.aiscite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made. Citations Citation text copied Copy Goller CC, Vandegrift M, Cross W, Smyth DS. 2021. Sharing Notes Is Encouraged: Annotating and Cocreating with Hypothes.is and Google Docs. J Microbiol Biol Educ. 22:10.1128/jmbe.v22i1.2135. https://doi.org/10.1128/jmbe.v22i1.2135 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download. Format RIS (ProCite, Reference Manager)EndNoteBibTexMedlarsRefWorks Direct import $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View OptionsFiguresOpen all in viewerFIGURE 1. “Sharing Notes is Encouraged” workflow. Students annotate and cocreate notes to produce an OER for studying and future course participants. Students use Hypothes.is to annotate primary literature as homework assignments, following set guidelines (for details see Appendix 1), and groups are tasked with creating shared summaries for the class to view within a Hypothes.is group. Students contribute to shared notes both during and outside of the class session. The instructor then uses the notes to produce weekly recaps to provide feedback and encouragement. Student contributions are then compiled to create a final OER, containing all notes and annotations generated over the course of the semester in a publicly viewable dynamic resource (for a sample OER, go to go.nscu.edu/bitmetagenomics) and click on “Meta Book”). PB, Pressbooks.Go to FigureOpen in ViewerFIGURE 2. Students annotated assigned papers frequently and began using descriptive “tags.” (A) Students used the Hypothes.is tool to annotate reading assignments and tag keywords or phrases. Some students responded to other comments and included links and other resources. (B) All students’ (n = 15) annotated readings.Go to FigureOpen in ViewerTablesMediaShareShareShare the article linkhttps://journals.asm.org/doi/10.1128/jmbe.v22i1.2135Copy LinkCopied!Copying failed.Share with emailEmail a colleagueShare on social mediaFacebookX (formerly Twitter)LinkedInWeChatBlueskyReferencesReferencesREFERENCES1.Rawlings JS. 2019. Primary literature in the undergraduate immunology curriculum: strategies, challenges, and opportunities. Front Immunol 10:1857.Go to CitationViewPubMedWeb of ScienceGoogle Scholar2.Nelms AA, Segura-Totten M. 2019. Expert–novice comparison reveals pedagogical implications for students’ analysis of primary literature. CBE Life Sci Educ 18:ar56.Go to CitationViewPubMedWeb of ScienceGoogle Scholar3.Abdullah C, Parris J, Lie R, Guzdar A, Tour E. 2015. Critical analysis of primary literature in a master’s-level class: effects on self-efficacy and science-process skills. CBE Life Sci Educ 14:ar34.Go to CitationViewPubMedWeb of ScienceGoogle Scholar4.Liao MK. 2017. A simple activity to enhance the learning experience of reading primary literature. J Microbiol Biol Educ 18.Go to CitationViewPubMedGoogle Scholar5.Hoskins SG, Lopatto D, Stevens LM. 2011. The C.R.E.A.T.E. approach to primary literature shifts undergraduates’ self-assessed ability to read and analyze journal articles, attitudes about science, and epistemological beliefs. CBE Life Sci Educ 10:368–378.Go to CitationViewPubMedWeb of ScienceGoogle Scholar6.Gottesman AJ, Hoskins SG. 2013. CREATE cornerstone: introduction to scientific thinking, a new course for stem-interested freshmen demystifies scientific thinking through analysis of scientific literature. CBE Life Sci Educ 12:59–72.Go to CitationViewPubMedWeb of ScienceGoogle Scholar7.Carmichael JS, Allison LA. 2019. Using “research boxes” to enhance understanding of primary literature and the process of science. J Microbiol Biol Educ 20(2).Go to CitationViewPubMedGoogle Scholar8.Round JE, Campbell AM. 2013. Figure facts: encouraging undergraduates to take a data-centered approach to reading primary literature. CBE Life Sci Educ 12:39–46.Go to CitationViewPubMedWeb of ScienceGoogle Scholar9.Lo SM, Luu TB, Tran J. 2020. A modified CREATE intervention improves student cognitive and affective outcomes in an upper-division genetics course. J Microbiol Biol Educ 21(1).Go to CitationViewPubMedGoogle Scholar10.Morehead K, Dunlosky J, Rawson KA, Blasiman R, Hollis RB. 2019. Note-taking habits of 21st-century college students: implications for student learning, memory, and achievement. Memory 27:807–819.Go to CitationViewPubMedWeb of ScienceGoogle Scholar11.Kennedy M. 2016. Open annotation and close reading the Victorian text: using hypothes.is with students. J Vic Cult 21:550–558.Go to CitationViewGoogle Scholar12.Shrout AH. 2016. Hypothes.is. J Am Hist 103:870–871.Go to CitationViewGoogle Scholar13.Perkel JM. 2015. Annotating the scholarly web. Nat News 528:153.Go to CitationViewWeb of ScienceGoogle Scholar14.Kalir JH, Dean J. 2018. Web annotation as conversation and interruption. Media Pract Educ 19:18–29.Go to CitationViewGoogle Scholar15.Kararo M, McCartney M. 2019. Annotated primary scientific literature: a pedagogical tool for undergraduate courses. PLOS Biol 17:e3000103.Go to CitationView Updates PubMedWeb of ScienceGoogle Scholar16.Miller K, Zyto S, Karger D, Yoo J, Mazur E. 2016. Analysis of student engagement in an online annotation system in the context of a flipped introductory physics class. Phys Rev Phys Educ Res 12:e020143.Go to CitationViewGoogle Scholar17.Sahota M, Leung B, Dowdell S, Velan GM. 2016. Learning pathology using collaborative vs. individual annotation of whole slide images: a mixed methods trial. BMC Med Educ 16:311.Go to CitationViewPubMedWeb of ScienceGoogle Scholar18.Yaeger J, Wolfe T. 2018. Creating the ripple effect: applying student-generated OER to increase engagement in distance education and enhance the OER community. Digital Universities 1/2.Go to CitationGoogle Scholar19.Goller CC, Ott LE. 2020. Evolution of an 8-week upper-division metagenomics course: diagramming a learning path from observational to quantitative microbiome analysis. Biochem Mol Biol Educ 48:391–403.Go to CitationViewPubMedWeb of ScienceGoogle Scholar20.Gordy CL, Goller CC. 2020. Using metabolic engineering to connect molecular biology techniques to societal challenges. Front Microbiol.Go to CitationViewPubMedWeb of ScienceGoogle Scholar Advertisement

Key Initiatives Primary items under Key Initiatives Artificial Intelligence Computational Thinking Digital Citizenship Edtech Selection Global Collaborations STEAM in Education Teacher Preparation ISTE Standards Primary items under ISTE Standards Students Educators Education Leaders Coaches Faculty Secondary items under ISTE Standards IMPLEMENTATION Essential Conditions Adopting the Standards Learning Library Primary items under Learning Library Books Blog Posts Topic Guides Podcasts Webinars Journals Professional Development Primary items under Professional Development ISTE U Certifications School Partners Events Primary items under Events ISTELive 26 ASCD Annual Conference 26 Edtech Providers Primary items under Edtech Providers ISTE Seal EdTech Index Solutions Network Sponsorship & Advertising Toggle open Toggle closed Log In Become a Member Key Initiatives Artificial Intelligence Computational Thinking Digital Citizenship Edtech Selection Global Collaborations STEAM in Education Teacher Preparation ISTE Standards Students Educators Education Leaders Coaches Faculty IMPLEMENTATION Essential Conditions Adopting the Standards Learning Library Books Blog Posts Topic Guides Podcasts Webinars Journals Professional Development ISTE U Certifications School Partners Events ISTELive 26 ASCD Annual Conference 26 Edtech Providers ISTE Seal EdTech Index Solutions Network Sponsorship & Advertising Homepage ASCD EdSurge Digital Citizenship in Education Bring Digital Citizenship to the Classroom in Meaningful Ways Teaching digital citizenship has never been more important. Prepare students to stay safe, solve problems and become a force for good. Teaching digital well-being doesn’t mean providing students with a list of “don’ts.” It’s about the do’s – modeling and practicing skills that help young people become thoughtful, empathetic digital citizens who know how to use technology to learn and solve problems in their digital and physical communities.  The digital citizenship competencies, developed by the ISTE-led DigCit Coalition in conjunction with coalition partners, shift the conversation from don’ts to do’s.

Defining digital citizenshipAs a first step in reducing some of the existing term confusion and improving the focus and evaluation of educational efforts, we recommend distinguishing digital citizenship education from digital literacy education (Internet and computer technical skills). Many in the field already use the term ‘digital literacy’ to refer to computer and Internet-based skills such as knowing good search strategies, understanding and using privacy settings, practicing identity theft protection behaviors, creating safe passwords, correctly citing online information, and avoiding spam and e-scams (Koltay, 2011; Sonck et al., 2011). Digital literacy requires a very specific set of educator knowledge and teaching skills compared to other goals currently under the digital citizenship umbrella.A second recommendation is to focus digital citizenship education on helping youth build and practice specific online social skills versus admonitions against problem behaviors like cyberbullying and sexting. Cyberbullying and sexting have complex causal roots in adolescent identity-formation, peer struggles, self-esteem, romantic exploration, and sexual decision-making (Hinduja and Patchin, 2010; Jones et al., 2013; Lenhart et al., 2008; Mitchell et al., 2012; Raskauskas and Stoltz, 2007; Sumter et al., 2012; Ybarra et al., 2012). Reducing these problems likely requires evidence-based bullying prevention and relationship and sexual education programs (Jones et al., 2014b; Nation et al., 2003; National Institutes of Health, 2004; Pentz, 2003).By separating it from digital literacy education and cyberbullying prevention, digital citizenship education can instead be focused on using Internet resources to have youth (1) practice respectful and tolerant behaviors toward others and (2) increase civic engagement activities. As we describe below, this definition of digital citizenship more closely aligns with direction of general youth citizenship education and could provide a useful roadmap for programs interested in increasing positive online youth citizenship behaviors. There is a growing appreciation that the Internet can provide important opportunities for youth to exercise positive social skills and engage with their community in ways that may have positive outcomes for offline civic engagement (Flanagan and Gallay, 1995; Kahne and Sporte, 2008; Sherrod et al., 2002; Zaff et al., 2008).

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AbstractUsing digital media is complicated. Invasions of privacy, increasing dataveillance, digital-by-default commercial and civic transactions and the erosion of the democratic sphere are just some of the complex issues in modern societies. Existential questions associated with digital life challenge the individual to come to terms with who they are, as well as their social interactions and realities. In this article, we identify three contemporary normative responses to these complex issues –digital citizenship, digital rights and digital literacy. These three terms capture epistemological and ontological frames that theorise and enact (both in policy and everyday social interactions) how individuals learn to live in digitally mediated societies. The article explores the effectiveness of each in addressing the philosophical, ethical and practical issues raised by datafication, and the limitations of

Just as in the real world, the online world has had to create structure to protect those using these digital devices from harm

Digital citizenship in schools : nine elements all students should know by Ribble, Mike Publication date 2015 Topics Computer literacy -- Study and teaching -- United States, Internet literacy, Education, Elementary -- United States -- Data processing, Education, Secondary -- United States -- Data processing Publisher Eugene, Oregon : International Society for Technology in Education Collection internetarchivebooks; nationaluniversity; inlibrary; printdisabled Contributor Internet Archive Language English Item Size 474.9M x, 212 pages : 28 cmIncludes bibliographical references and indexSection I. Understanding digital citizenship -- chapter 1. A brief history of digital citizenship -- chapter 2. The nine elements of digital citizenship -- Section II. Digital citizenship in schools -- chapter 3. Creating a digital citizenship program -- chapter 4. Professional development activities in digital citizenship -- Section III. Digital citizenship in the classroom -- chapter 5. Teaching digital citizenship to students -- chapter 6. Foundational lessons in digital citizenship -- chapter 7. Guided lessons in digital citizenship -- Conclusion Access-restricted-item true Addeddate 2023-07-18 11:33:13 Autocrop_version 0.0.15_books-20220331-0.2 Bookplateleaf 0002 Boxid IA41026906 Camera USB PTP Class Camera Col_number COL-2513 Collection_set printdisabled External-identifier urn:lcp:digitalcitizensh0000ribb_x4u3:epub:925c17a4-eb03-466d-9236-c990d53eee2f urn:lcp:digitalcitizensh0000ribb_x4u3:lcpdf:24304311-9320-40ce-8f6d-da51036f64ec urn:oclc:record:1391393133 Foldoutcount 0