{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/41594"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/41594","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Prevalence and correlates of cyber-victimization in a nationally representative sample of South African youth","abstract":"Cyber-victimization is defined as “the experience of aggressive behaviours while using new electronic technologies, primarily mobile phones and the internet\" (Álvarez-García et al., 2015a; Smith & Steffgen, 2013). Approximately 20 to 50% of adolescents have experienced online victimization globally (Zhu et al., 2021). This is a public health concern because cyber- victimization can harm the mental health of the victim thus leading to depressive symptoms such as anxiety, helplessness, distress, sadness, trauma symptoms, reduced self-esteem, feelings of isolation, fear of socialization, hopelessness, self-harm, or suicidal ideation (Hertz et al., 2015; Kim et al., 2022; Landoll et al., 2015; Mason et al., 2009). Research on the risk factors associated with cyber-victimization is relatively new and has some gaps and inconsistencies (Álvarez-García et al., 2015a; Zhu et al., 2021). This study will focus on analyzing the association of some demographic, psychological, educational, family factors and exposure to other forms of violence, with cyber-victimization, in a nationally representative sample of South African children. We aim to determine the lifetime prevalence and last-year prevalence (i.e., annual incidence) of cyber- victimization, as well as the association of cyber-victimization with its correlates, based on a nationally representative cross-sectional study of 15–17-year-old youth in South Africa. Method: This mini dissertation will use secondary data obtained, with permission, from the Optimus Study conducted in South Africa (Ward et al., 2018). The study drew on data from a population survey that was conducted with a sample of 15- to 17-year-old adolescents recruited nationally from schools (4 086 participants) as well as households (5 631 participants) (Ward et al., 2018). The aims of this study are as follows: To estimate the prevalence and incidence of cyber-victimization among South African youth as of 2013/2014, as well as in-person victimization. This will be achieved by reporting the relative frequencies with CI of both the lifetime and last-year prevalence, stratified by key demographic measures. We will also report the prevalence of each of the six types of cyberbullying. To measure the strength of association between cyber-victimization and potential risk/protective factors among South African youth. We will use logistic regression to estimate the association of each factor in table 1 with cyber-victimization, adjusting for the possible confounding factors listed. The associations will be expressed as odds ratios (ORs) with their 95% confidence intervals (Cis). The unadjusted odds ratios (OR) will be estimated using a univariable regression model for each correlate and adjusted OR (aOR) will be estimated using a multivariable regression model containing all correlates. To study the relationship between cyber-victimization and each of the potential consequences stratified by sex. For the factors, we will report differences in proportions, by cyber-victimization and CIs. The following correlates will be considered as consequences of cyber-victimization (table 2): Behavioral patterns (high-risky sexual behaviours, alcohol and substance misuse), educational (academic performance), and psychological (anxiety, depression, anger, and post-traumatic stress).","abstract_html":"Cyber-victimization is defined as “the experience of aggressive behaviours while using new electronic technologies, primarily mobile phones and the internet" (Álvarez-García et al., 2015a; Smith & Steffgen, 2013). Approximately 20 to 50% of adolescents have experienced online victimization globally (Zhu et al., 2021). This is a public health concern because cyber- victimization can harm the mental health of the victim thus leading to depressive symptoms such as anxiety, helplessness, distress, sadness, trauma symptoms, reduced self-esteem, feelings of isolation, fear of socialization, hopelessness, self-harm, or suicidal ideation (Hertz et al., 2015; Kim et al., 2022; Landoll et al., 2015; Mason et al., 2009). Research on the risk factors associated with cyber-victimization is relatively new and has some gaps and inconsistencies (Álvarez-García et al., 2015a; Zhu et al., 2021). This study will focus on analyzing the association of some demographic, psychological, educational, family factors and exposure to other forms of violence, with cyber-victimization, in a nationally representative sample of South African children. We aim to determine the lifetime prevalence and last-year prevalence (i.e., annual incidence) of cyber- victimization, as well as the association of cyber-victimization with its correlates, based on a nationally representative cross-sectional study of 15–17-year-old youth in South Africa. Method: This mini dissertation will use secondary data obtained, with permission, from the Optimus Study conducted in South Africa (Ward et al., 2018). The study drew on data from a population survey that was conducted with a sample of 15- to 17-year-old adolescents recruited nationally from schools (4 086 participants) as well as households (5 631 participants) (Ward et al., 2018). The aims of this study are as follows: To estimate the prevalence and incidence of cyber-victimization among South African youth as of 2013/2014, as well as in-person victimization. This will be achieved by reporting the relative frequencies with CI of both the lifetime and last-year prevalence, stratified by key demographic measures. We will also report the prevalence of each of the six types of cyberbullying. To measure the strength of association between cyber-victimization and potential risk/protective factors among South African youth. We will use logistic regression to estimate the association of each factor in table 1 with cyber-victimization, adjusting for the possible confounding factors listed. The associations will be expressed as odds ratios (ORs) with their 95% confidence intervals (Cis). The unadjusted odds ratios (OR) will be estimated using a univariable regression model for each correlate and adjusted OR (aOR) will be estimated using a multivariable regression model containing all correlates. To study the relationship between cyber-victimization and each of the potential consequences stratified by sex. For the factors, we will report differences in proportions, by cyber-victimization and CIs. The following correlates will be considered as consequences of cyber-victimization (table 2): Behavioral patterns (high-risky sexual behaviours, alcohol and substance misuse), educational (academic performance), and psychological (anxiety, depression, anger, and post-traumatic stress).","abstract_has_math":false,"creators":["Hlatshwayo, Lerato"],"institution":"Department of Public Health and Family Medicine","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Kassanjee, Reshma","Ward, Catherine"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-22T22:22:44Z","subjects":["Cyber-victimization"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/41594","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Kassanjee, Reshma","Ward, Catherine"]},{"key":"dc:creator","label":"Author","values":["Hlatshwayo, Lerato"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-08-18T07:19:35Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-08-18T07:19:35Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Public Health and Family Medicine"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Thesis / Dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters","MPH"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cyber-victimization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/41594"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Cyber-victimization is defined as “the experience of aggressive behaviours while using new electronic technologies, primarily mobile phones and the internet\" (Álvarez-García et al., 2015a; Smith & Steffgen, 2013). Approximately 20 to 50% of adolescents have experienced online victimization globally (Zhu et al., 2021). This is a public health concern because cyber- victimization can harm the mental health of the victim thus leading to depressive symptoms such as anxiety, helplessness, distress, sadness, trauma symptoms, reduced self-esteem, feelings of isolation, fear of socialization, hopelessness, self-harm, or suicidal ideation (Hertz et al., 2015; Kim et al., 2022; Landoll et al., 2015; Mason et al., 2009). Research on the risk factors associated with cyber-victimization is relatively new and has some gaps and inconsistencies (Álvarez-García et al., 2015a; Zhu et al., 2021). This study will focus on analyzing the association of some demographic, psychological, educational, family factors and exposure to other forms of violence, with cyber-victimization, in a nationally representative sample of South African children. We aim to determine the lifetime prevalence and last-year prevalence (i.e., annual incidence) of cyber- victimization, as well as the association of cyber-victimization with its correlates, based on a nationally representative cross-sectional study of 15–17-year-old youth in South Africa. Method: This mini dissertation will use secondary data obtained, with permission, from the Optimus Study conducted in South Africa (Ward et al., 2018). The study drew on data from a population survey that was conducted with a sample of 15- to 17-year-old adolescents recruited nationally from schools (4 086 participants) as well as households (5 631 participants) (Ward et al., 2018). The aims of this study are as follows: To estimate the prevalence and incidence of cyber-victimization among South African youth as of 2013/2014, as well as in-person victimization. This will be achieved by reporting the relative frequencies with CI of both the lifetime and last-year prevalence, stratified by key demographic measures. We will also report the prevalence of each of the six types of cyberbullying. To measure the strength of association between cyber-victimization and potential risk/protective factors among South African youth. We will use logistic regression to estimate the association of each factor in table 1 with cyber-victimization, adjusting for the possible confounding factors listed. The associations will be expressed as odds ratios (ORs) with their 95% confidence intervals (Cis). The unadjusted odds ratios (OR) will be estimated using a univariable regression model for each correlate and adjusted OR (aOR) will be estimated using a multivariable regression model containing all correlates. To study the relationship between cyber-victimization and each of the potential consequences stratified by sex. For the factors, we will report differences in proportions, by cyber-victimization and CIs. The following correlates will be considered as consequences of cyber-victimization (table 2): Behavioral patterns (high-risky sexual behaviours, alcohol and substance misuse), educational (academic performance), and psychological (anxiety, depression, anger, and post-traumatic stress)."]},{"key":"dc:title","label":"Title","values":["Prevalence and correlates of cyber-victimization in a nationally representative sample of South African youth"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kassanjee, Reshma","Ward, Catherine"],"dc:creator":["Hlatshwayo, Lerato"],"dc:date.accessioned":["2025-08-18T07:19:35Z"],"dc:date.available":["2025-08-18T07:19:35Z"],"dc:date.issued":["2025"],"dc:description.abstract":["Cyber-victimization is defined as “the experience of aggressive behaviours while using new electronic technologies, primarily mobile phones and the internet\" (Álvarez-García et al., 2015a; Smith & Steffgen, 2013). Approximately 20 to 50% of adolescents have experienced online victimization globally (Zhu et al., 2021). This is a public health concern because cyber- victimization can harm the mental health of the victim thus leading to depressive symptoms such as anxiety, helplessness, distress, sadness, trauma symptoms, reduced self-esteem, feelings of isolation, fear of socialization, hopelessness, self-harm, or suicidal ideation (Hertz et al., 2015; Kim et al., 2022; Landoll et al., 2015; Mason et al., 2009). Research on the risk factors associated with cyber-victimization is relatively new and has some gaps and inconsistencies (Álvarez-García et al., 2015a; Zhu et al., 2021). This study will focus on analyzing the association of some demographic, psychological, educational, family factors and exposure to other forms of violence, with cyber-victimization, in a nationally representative sample of South African children. We aim to determine the lifetime prevalence and last-year prevalence (i.e., annual incidence) of cyber- victimization, as well as the association of cyber-victimization with its correlates, based on a nationally representative cross-sectional study of 15–17-year-old youth in South Africa. Method: This mini dissertation will use secondary data obtained, with permission, from the Optimus Study conducted in South Africa (Ward et al., 2018). The study drew on data from a population survey that was conducted with a sample of 15- to 17-year-old adolescents recruited nationally from schools (4 086 participants) as well as households (5 631 participants) (Ward et al., 2018). The aims of this study are as follows: To estimate the prevalence and incidence of cyber-victimization among South African youth as of 2013/2014, as well as in-person victimization. This will be achieved by reporting the relative frequencies with CI of both the lifetime and last-year prevalence, stratified by key demographic measures. We will also report the prevalence of each of the six types of cyberbullying. To measure the strength of association between cyber-victimization and potential risk/protective factors among South African youth. We will use logistic regression to estimate the association of each factor in table 1 with cyber-victimization, adjusting for the possible confounding factors listed. The associations will be expressed as odds ratios (ORs) with their 95% confidence intervals (Cis). The unadjusted odds ratios (OR) will be estimated using a univariable regression model for each correlate and adjusted OR (aOR) will be estimated using a multivariable regression model containing all correlates. To study the relationship between cyber-victimization and each of the potential consequences stratified by sex. For the factors, we will report differences in proportions, by cyber-victimization and CIs. The following correlates will be considered as consequences of cyber-victimization (table 2): Behavioral patterns (high-risky sexual behaviours, alcohol and substance misuse), educational (academic performance), and psychological (anxiety, depression, anger, and post-traumatic stress)."],"dc:identifier.uri":["http://hdl.handle.net/11427/41594"],"dc:language.iso":["en"],"dc:publisher.department":["Department of Public Health and Family Medicine"],"dc:publisher.institution":["University of Cape Town"],"dc:subject":["Cyber-victimization"],"dc:title":["Prevalence and correlates of cyber-victimization in a nationally representative sample of South African youth"],"dc:type":["Thesis / Dissertation"],"dc:type.qualificationlevel":["Masters","MPH"]},"updated_at":"2026-07-22T22:22:44Z"}