Bullying Victimization among In-School Adolescents in Ghana: Analysis of Prevalence and Correlates from the Global School-Based Health Survey
Bibliographic record
Abstract
(1) Background: Although bullying victimization is a phenomenon that is increasingly being recognized as a public health and mental health concern in many countries, research attention on this aspect of youth violence in low- and middle-income countries, especially sub-Saharan Africa, is minimal. The current study examined the national prevalence of bullying victimization and its correlates among in-school adolescents in Ghana. (2) Methods: A sample of 1342 in-school adolescents in Ghana (55.2% males; 44.8% females) aged 12–18 was drawn from the 2012 Global School-based Health Survey (GSHS) for the analysis. Self-reported bullying victimization “during the last 30 days, on how many days were you bullied?” was used as the central criterion variable. Three-level analyses using descriptive, Pearson chi-square, and binary logistic regression were performed. Results of the regression analysis were presented as adjusted odds ratios (aOR) at 95% confidence intervals (CIs), with a statistical significance pegged at p < 0.05. (3) Results: Bullying victimization was prevalent among 41.3% of the in-school adolescents. Pattern of results indicates that adolescents in SHS 3 [aOR = 0.34, 95% CI = 0.25, 0.47] and SHS 4 [aOR = 0.30, 95% CI = 0.21, 0.44] were less likely to be victims of bullying. Adolescents who had sustained injury [aOR = 2.11, 95% CI = 1.63, 2.73] were more likely to be bullied compared to those who had not sustained any injury. The odds of bullying victimization were higher among adolescents who had engaged in physical fight [aOR = 1.90, 95% CI = 1.42, 2.25] and those who had been physically attacked [aOR = 1.73, 95% CI = 1.32, 2.27]. Similarly, adolescents who felt lonely were more likely to report being bullied [aOR = 1.50, 95% CI = 1.08, 2.08] as against those who did not feel lonely. Additionally, adolescents with a history of suicide attempts were more likely to be bullied [aOR = 1.63, 95% CI = 1.11, 2.38] and those who used marijuana had higher odds of bullying victimization [aOR = 3.36, 95% CI = 1.10, 10.24]. (4) Conclusions: Current findings require the need for policy makers and school authorities in Ghana to design and implement policies and anti-bullying interventions (e.g., Social Emotional Learning (SEL), Emotive Behavioral Education (REBE), Marijuana Cessation Therapy (MCT)) focused on addressing behavioral issues, mental health and substance abuse among in-school adolescents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".