Understanding linkages between self-reliance and mental health among forcibly displaced women in Colombia
**** Due to privacy concerns, Dataset and do.file to be provided upon reasonable request*** ⸻
Problem Statement / Background
Despite global efforts to promote self-reliance among displaced populations, the mental health implications of household-level self-reliance are not well understood, particularly for women in Latin America. This study investigates how economic self-reliance relates to depressive symptoms and resilience among forcibly displaced women in Colombia.
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Methods Used • Design: Cross-sectional analysis using baseline data from a pilot RCT of the HIAS Entrepreneurship School with a Gender Lens. • Participants: 348 forcibly displaced Colombian and Venezuelan women. • Measures: • Self-Reliance Index (SRI) • Patient Health Questionnaire-9 (PHQ-9) for depression • Brief Resilient Coping Scale (BRCS) for resilience • Analysis: Multivariate linear regression with robust standard errors using Stata 16.
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Key Findings • Self-reliance was significantly associated with lower depressive symptoms, especially in domains related to food security, financial resources, and debt. • Resilience was not significantly associated with overall self-reliance. • Feeling controlled by others was a strong predictor of increased depressive symptoms, while community support was associated with higher resilience.
How to Run the Code (Stata) 1. Software Required • Stata 16 or higher (recommended due to robust standard error handling and compatibility with newer syntax)
2. Data Preparation
• Ensure that the baseline dataset used in the study (e.g., baseline_data.dta) is placed in the same working directory as the .do file.
• If data is deidentified and available, place it in the /data folder or update the use path in the .do file accordingly.
3. Running the Script
• Open Stata.
• Set your working directory where the .do file is saved using: cd "path_to_your_project_directory"
Run the script:do "HIAS - Baseline data.do"
4. Expected Output
• The code will produce descriptive statistics, regression models for PHQ-9 and BRCS scores, and robustness checks using robust standard errors.
• Key results are printed to the Stata Results window and may be saved to .log or .csv files depending on final lines in the script.
5. Dependencies
• Ensure any user-written commands (e.g., esttab, outreg2, coefplot) are installed using:ssc install [command_name]