# Music Listening for Chronic Pain: A Systematic Review This project is a meta-analysis examining whether music listening can reduce pain intensity in individuals with chronic pain. The work involved systematic data extraction, standardisation across heterogeneous studies, and rigorous statistical analysis. ## The challenge Synthesising evidence from diverse studies presents several methodological hurdles: different pain scales (0–10 vs 0–100), missing descriptive statistics, and multi-arm trials with shared control groups. Each required careful handling to produce valid, comparable effect sizes. ## Methods - **Pain scale normalisation**: Visual Analog Scale scores on 0–100 were converted to 0–10 - **Multi-arm correction**: Studies with multiple experimental arms used the split shared control approach, preserving intervention-specific information whilst avoiding double-counting controls - **Effect sizes**: Standardised mean differences (SMDs) calculated from change scores, pooled using a random-effects model - **Heterogeneity**: Assessed via Cochran's Q and I² statistics - **Publication bias**: Evaluated with funnel plots, Egger's test, and fail-safe N ## Tools - **Python** (pandas, Jupyter) for data cleaning and effect size calculation - **Jamovi** (MAJOR module) for meta-analytic validation - **RevMan / R** (metafor) for final pooled analyses [See Project in GitHub](https://github.com/andreu-oliver/therapeutic-Use-of-Music-Listening-for-Individuals-with-Chronic-Pain-A-Systematic-Review)