# Dataset on comprehensive assessment & classification of upper & lower limb pain in athletes

## TL;DR

This paper presents a dataset from a scoping review on upper and lower limb pain assessment and classification in athletes.

## Contribution

The novel contribution is a comprehensive, reusable dataset capturing pain assessment practices in athletes.

## Key findings

- The dataset includes 470 articles with detailed information on pain assessment tools and classifications.
- Descriptive analysis of frequencies and counts was conducted to summarize the data.
- The dataset includes clinical guidance and multi-domain tools for pain assessment.

## Abstract

Data were charted as part of a scoping review which followed the Joanna Briggs Institute (JBI) evidence synthesis guidelines and the Preferred Reporting Items for Systematic Reviews and Meta Analysis Scoping Review extension (PRISMA-SCr) guidelines. Data was extracted from 470 articles that met the inclusion criteria for the scoping review; primary research articles of athletes where upper and/or lower limb pain since database inception.

A draft data charting tool was developed by the research team and piloted for feasibility, accuracy and agreement. The charting tool was updated accordingly before being applied to the entire data set. Data collected included citation details, research context, participant information and pain assessment and classification tools, categories, and additional relevant information.

The raw data set was filtered, and descriptive analysis of frequencies and counts were conducted.

Researchers and clinicians interested in the range and applications of different pain assessment practices in athletes may reuse this data set. Data charting was comprehensive including aspects beyond the scope of the original research that offer clinical and research potential. These include information around recommended practice, (International Olympic Committee guidance) pain classifications and definitions and the use of multi-domain pain assessment tools.