Analyzing the data requires multiple approaches. Quantitative analysis involves using descriptive statistics to summarize bullying incident rates, locations, and changes over time, as well as inferential statistics to examine relationships between variables, such as the impact of the curriculum on bullying rates across different grades or schools. Disaggregating data by subgroups enables the identification of disparities and the targeted delivery of interventions. Qualitative analysis employs thematic analysis to identify recurring patterns and themes in interview and focus group data, using coding frameworks to ensure reliability and transparency. Visual and mapping data can further contextualize findings by highlighting spatial patterns of bullying incidents. In mixed-methods analysis, an explanatory sequential design can be used: quantitative survey results are analyzed first, followed by qualitative findings that explain or elaborate on observed patterns. Triangulating data from multiple sources validates findings and provides a comprehensive view. Action research analysis involves reflecting on cycles of action and feedback, utilizing both quantitative and qualitative data to assess the effectiveness of interventions and inform subsequent steps. Stakeholders are engaged in interpreting the results and developing recommendations (Hall, 2017; Marsh, 2018; Brion-Meisels, 2022)