Risk Survey Experiment

A web-based risk survey experiment for behavioral research.

Quick Start

1. Install dependencies:

   npm install

2. Set up environment:

   • Create .env file with your MongoDB connection string:

   MONGODB_URI=your_mongodb_connection_string
   

3. Run the experiment:

   node server.js

   • Open http://localhost:3000 in your browser

Indifference Point (IP) Study

A two-phase study: (1) calibrate each participant's indifference point for 18 lotteries; (2) test whether visual size shifts that point.

• Run IP study: Open http://localhost:3000?study=ip in your browser.
• Phase 1: 126 trials (18 lotteries × 7 safe levels), no size manipulation. At the end, 18 indifference points are computed and shown (with optional CSV download). Option to Continue to Phase 2.
• Phase 2: 84 trials total: 72 core (18 lotteries × 4 size conditions) with safe = participant's Phase 1 IP, plus 12 dummy trials (dominant risky choices, interleaved for engagement). Trial order randomized. Data (Phase 1 + Phase 2) saved together; dummy trials have trial_id prefix dummy_ for analysis.
• Files: public/config_ip_study.json, public/ip_phase1_trials.csv, public/ip_phase2_template.csv, public/ip_phase2_dummy_trials.csv.

Trial Generation

Generate new trial configurations:

python generate_trials.py

Data Structure

The experiment saves 15 fields per trial:

• participant_id, trial_number, bar_size_condition
• choice (risk/safe/timeout), confidence (0-100 or NaN)
• risk_probability, risk_reward, safe_probability, safe_reward
• risk_position, safe_position, ev (same/safe/risky)
• bar_choice_time, confidence_choice_time, trial_id

Files

• server.js - Express server with MongoDB integration
• public/js/experiment.js - Main experiment logic
• public/css/styles.css - Styling
• public/config.json - Experiment configuration
• public/full_trials.csv - Trial data
• generate_trials.py - Trial generation script