Refugee_study

Coping Strategies and Resilience Among Displaced Youth in Bidibidi Settlement

*Data provided upon reasonable request

🧩 Problem Statement / Background

Displaced youth in refugee settlements face immense psychological stressors. This study investigates how different coping mechanisms—problem-focused, emotion-focused, social support, and spiritual practices—predict resilience among adolescents and young adults in Bidibidi, Uganda. The goal is to identify actionable psychosocial levers for improving mental health in protracted displacement contexts.

⸻

🛠️ Methods Used • Tool: R (v4.4.1) • Packages: MASS, brant, car, ordinal, ggplot2, sjPlot, among others • Statistical Models: • Proportional-odds ordinal logistic regression • Brant test for proportionality assumption • QR decomposition for rank diagnostics • Variance Inflation Factor (VIF) for multicollinearity • Data Management: • Row-wise total scoring of five validated scales • Categorical recoding for demographics • Sample restricted to 108 participants with complete cases

⸻

📈 Key Findings • Strongest predictors of resilience: • Social Support Coping (OR = 1.44; p < 0.001) • Spiritual Practices (OR = 1.15; p = 0.005) • Non-significant predictors: • Emotion-Focused Coping • Problem-Focused Coping (positive trend) • Vulnerability flag: • Youth aged 25+ had significantly lower resilience (OR = 0.15; p = 0.003)

Visuals: • 📊 Figure 1: Forest plot of ORs and 95% CIs

•	📈 Figure 2: Calibration plot showing excellent model reliability across all risk deciles

▶️ How to Run the Code (R) 1. Software Requirement: • R version 4.4.1 or higher • RStudio (recommended for IDE) 2. Install Required Packages (once): install.packages(c("MASS", "car", "brant", "ordinal", "ggplot2", "sjPlot"))

3.	Open & Run
•	Open PCMR.Rmd in RStudio
•	Click “Knit” to produce a full HTML report, or run chunks manually
•	Ensure the dataset (likely named df2 or similar) is loaded correctly
4.	Expected Outputs:
•	Regression tables for ordinal logistic model
•	Diagnostic results (Brant test, VIF)
•	Descriptive summaries of all scales
•	Forest and calibration plots for model interpretability
5.	Data Notes:
•	Data was cleaned and preprocessed in R
•	All participants had complete scores on 5 coping/resilience scales
•	Demographics recoded for analytic clarity (e.g., Age: 18–24 vs. 25+)