⚠ Site under construction. Content is still being reviewed — some details, links, and PDFs may be inaccurate, incomplete, or temporarily unavailable. Last updated May 2026.

// live experiments & field materials

Experiments

All studies are built and deployed by me end-to-end.

oTree · Prolific · UK + AU samples

Approach

How I run studies

I treat experimental infrastructure as a first-class research output. Every study below was designed, coded, piloted, and analysed by me — typically using oTree for the experiment, Prolific for the participant pool, and R / Stata for analysis. The links open the actual HTML pages participants see (rendered as static previews from the experiment source).

Currently in the Field

AIT Life-Year Study — v1.3

Anticipated Information Trade-offs · Wave 3

Active on Prolific

Anticipatory Utility & Health Outcome Trade-Offs

Participants are placed in a simulated GP consultation and must choose between a certain life-year outcome (Standard Care) and a risky treatment (50/50 between a 5-year gain and a 5-year loss). A second between-subject factor varies whether the treatment outcome is revealed immediately or after a six-month delay. The design lets us separately identify hope (anticipation of the gain) and dread (anticipation of the loss) components of anticipatory utility, and how they interact with delay.

Platform: Prolific UK  ·  Engine: oTree v5 (Python)  ·  N per wave: ≈ 200  ·  Design: 2 × 2 between-subject (delay × emotion order)  ·  Ethics: UoM HREC-approved

Click any task below to view the actual experiment page:

Consent Prolific ID GP Consultation Primary Comprehension Choice Elicitation Mock Comprehension Mock Transition No-consent Exit

Recently Completed

AIT Life-Year Study — earlier waves

Waves 1 & 2 · 2024–2025

Data analysed

Pilot & Calibration Studies

Earlier waves established comprehension benchmarks, calibrated the WTP/WTA bisection procedure, and tested the GP consultation framing. Data from these waves informs the design choices in v1.3.

Status: Closed  ·  Output: Internal pilots, working paper in preparation
Pilot report (coming soon) Pre-registration (OSF)

Behind the Scenes

Tech Stack

I treat experiment code as production software: version-controlled, ethics-cleared, instrumented for behavioural telemetry (response times, revisions, slider trajectories), and reproducible from raw data to final tables.

Experiment Engine

  • oTree v5
  • Custom JS / CSS
  • Bisection / staircase procedures
  • Attention & comprehension checks

Deployment

  • Prolific (UK / AU)
  • Heroku
  • Server-side data logging

Analysis

  • R (tidyverse, lme4)
  • Stata
  • Python (pandas)
  • Reproducible pipelines

Quality

  • Pre-registration (OSF)
  • Power calculations
  • Simulated data stress tests
  • Manual pilot checklists