🚀 Quick Start Guide

This guide will help you start working with the supplementary materials of the “Healthy is fresh” study in less than 10 minutes.

📋 Prerequisites

Required Software

R (version 4.0 or higher) - Download here
RStudio (recommended) - Download here
Git (optional, to clone repository) - Download here

Alternative Without R

If you only want to explore materials without running analyses:

⚡ Quick Start (3 steps)

1️⃣ Get the Repository

Option A: Clone with Git

git clone https://github.com/jcmunozmora/food-perception-rural-colombia.git
cd food-perception-rural-colombia

Option B: Download ZIP

Click the green “Code” button on GitHub
Select “Download ZIP”
Extract the file on your computer

2️⃣ Configure R Environment

Open RStudio and run:

# Set working directory
setwd("path/to/food-perception-rural-colombia")

# Run automatic setup
source("setup.R")

This script:

✅ Verifies your R version
✅ Installs required packages automatically
✅ Loads libraries
✅ Verifies project structure
✅ Creates necessary folders

Estimated time: 2-3 minutes

3️⃣ Run Analysis

Option A: Full Analysis (Automatic)

# Run everything at once
run_full_analysis()

Option B: Step by Step (Manual)

# Navigate to analysis folder
setwd("Analysis_Quantitative")

# Step 1: Generate processed datasets
source("01_GenDataSet.R")

# Step 2: Generate RIEN graphs (nutritional adequacy)
source("02_Gen_Graph_RIEN.R")

# Step 3: Generate GABAS graphs (food groups)
source("03_Gen_Graph_GABAS.R")

# Step 4: Generate nutritional heatmap
source("04_Gen_Graph_Nutrients.R")

Estimated time: 2-3 minutes

📂 Repository Structure

food-perception-rural-colombia/
├── README.md                              # Main page
├── WORKSHOP.md                            # ⭐ Complete visual workshop documentation
├── QUICKSTART.md                          # This guide
├── setup.R                                # Automatic setup
├── _config.yml                            # GitHub Pages configuration
│
├── Analysis_Quantitative/                 # 📊 Quantitative analysis
│   ├── README.md                          # Detailed documentation
│   ├── 01_GenDataSet.R                    # Dataset generation
│   ├── 02_Gen_Graph_RIEN.R                # RIEN graphs
│   ├── 03_Gen_Graph_GABAS.R               # GABAS graphs
│   ├── 04_Gen_Graph_Nutrients.R           # Nutritional heatmap
│   ├── Bases de datos.xlsx                # Primary data
│   └── graphs/                            # Generated graphs
│
├── Analysis_Qualitative/                  # 📝 Qualitative analysis
│   ├── README.md                          # Documentation
│   ├── Barreras dieta saludable.xlsx      # Coded barriers
│   └── Información Sociodemografica.xlsx  # Participant info
│
├── Participatory_Workshop_Forms/          # 📋 Workshop forms
│   ├── README.md
│   ├── desayuno, almuerzo, comida, barreras.pdf
│   ├── Cuadro registro.pdf
│   └── extras.pdf
│
├── Participatory_Workshop_Evidence-Transcriptions/  # 📸 Evidence
│   ├── README.md
│   ├── Pictures/                          # Co-designed meal photos
│   └── Transcriptions/                    # Transcriptions (restricted)
│
└── Participatory_Workshops_Design/        # 🎨 Methodological design
    └── Notas para Diseño de talleres 1.docx

🎯 Common Use Cases

Use Case 1: I want to understand how the workshops functioned

📖 Read the complete visual workshop documentation

Includes:

Step-by-step process with real photographs
Examples of participant co-designed meals
Downloadable materials
Key findings and lessons learned

Use Case 2: I want to reproduce the paper’s analyses

source("setup.R")
run_full_analysis()

Review results in: Analysis_Quantitative/graphs/

Use Case 3: I just want to see results (without code)

Navigate directly to:

🎨 Visual workshop documentation with meal photos
📊 Nutritional graphs
📸 Co-designed meal photos
📄 Complete paper

Use Case 4: I want to use the forms in my own study

Review: Participatory_Workshop_Forms
Read the methodological design documentation
Adapt materials to your context
Important: Cite the original study:

Arcila-Agudelo, A.M. et al. (2026). "Healthy is fresh": A participatory study 
of meal ideals and barriers shaping food choice in rural Colombia.

Use Case 5: I want to access complete transcriptions

Complete transcriptions are not publicly available for ethical reasons (re-identification risk).

To request access:

Send email to: ana.arcila@uniremington.edu.co
Subject: “Access Request - Rural Colombia Transcriptions”
Include:
- Purpose of use
- Institutional affiliation
- Ethics committee approval (if applicable)

📊 Expected Outputs

After running the analyses, you should see:

Processed Datasets

DS_Talleres_RIEN.rds / .xlsx (nutritional adequacy)
DS_Talleres_GABAS.rds / .xlsx (food groups)

RIEN Graphs

reg_Calorias.png
reg_Proteina.png
reg_CHO.png
reg_Grasas.png
reg_Fibra.png
reg_Calcio.png
reg_Hierro.png
reg_Sodio.png
ALL_Macronutrientes.png
ALL_Micronutrientes.png

GABAS Graphs

reg_GABAS.png
ALL_GABAS.png

Nutritional Heatmap

panel_b_heatmap.pdf (used in the article)
panel_b_heatmap.png

🐛 Troubleshooting

Problem: Error installing packages

Solution:

# Try manual installation
install.packages(c("tidyverse", "hrbrthemes", "readxl", 
                   "writexl", "reshape2", "ggplot2"))

Problem: “Cannot find file Bases de datos.xlsx”

Solution: Verify you’re in the correct directory:

getwd()  # Should show project folder
setwd("correct/path/to/project")

Problem: Graphs are not generated

Solution: Verify the graphs/ folder exists:

dir.create("Analysis_Quantitative/graphs", recursive = TRUE)

Problem: R version too old

Solution: Download R 4.0 or higher from: https://www.r-project.org/

📚 Additional Documentation

For more detailed information, consult:

📄 Main README - Complete study summary
📊 Quantitative Analysis README - Technical details
📝 Qualitative Analysis README - Qualitative methodology
📋 Forms README - Workshop materials
📸 Evidence README - Photos and transcriptions

💡 Useful Tips

View all available scripts

list.files("Analysis_Quantitative", pattern = "\\.R$")

View dataset structure

library(tidyverse)
ds_RIEN <- read_rds("Analysis_Quantitative/DS_Talleres_RIEN.rds")
glimpse(ds_RIEN)

Export graphs in high resolution

ggsave("my_graph.png", width = 12, height = 8, dpi = 300)

📖 How to Cite

@article{arcila2026healthy,
  title={"Healthy is fresh": A participatory study of meal ideals 
         and barriers shaping food choice in rural Colombia},
  author={Arcila, D. et al.},
  journal={[Journal Name]},
  year={2026}
}

GitHub automatically recognizes CITATION.cff to facilitate citation.

🆘 Help and Support

Frequently Asked Questions

Check the repository Issues - your question may have already been answered!

Report a Problem

Found a bug or error in the code?

Open an Issue
Describe the problem clearly
Include error messages if any

Contact

For questions about the study or data requests:

📧 Email: ana.arcila@uniremington.edu.co (Ana María Arcila-Agudelo)
📧 Alternative email: jmunozm1@eafit.edu.co (Juan Carlos Muñoz-Mora)
🌐 Web: https://jcmunozmora.github.io/food-perception-rural-colombia

⚖️ License

This project is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).

You are free to share and adapt these materials with proper attribution.

See: LICENSE.md

Ready to start! 🎉

If you have any questions, don’t hesitate to open an Issue or contact us directly.

Last updated: February 2026