Research

This study demonstrates how machine learning models trained on real-world data from the Manage My Pain app can predict which people living with chronic pain are likely to experience meaningful improvements in daily functioning. Using one month of self-reported pain, function, and engagement data from over 6,000 users, the models accurately forecast functional improvement in the following month.

Using one month of self-reported information collected by patients of the Transitional Pain Service using the Manage My Pain app, a machine learning model predicted patient improvement in pain interference with a 79% accuracy.

Describes the development of ManagingLife's scalable, digital self-guided intervention to address postsurgical pain and opioid use.

Description of how Alberta Health Services will test Manage My Pain with patients having elective surgery in Calgary, Alberta

A real-world multi-site study found that the use of Manage My Pain by patients with chronic pain is associated with engagement and improvements in self-reported anxiety and pain catastrophizing.

Manage My Pain was found acceptable by a majority of patients at an academic pain management program with rates of user registration and retention favorable compared to those reported by other applications.

Simplifies the prediction model in the previous machine learning paper to make it easier to apply clinically

Applies machine learning (supervised learning) to predict chronic pain outcomes 6 months in the future using 1 month of app data

Defines a new type of pain outcome measure and lays the foundation for an upcoming machine learning paper

Highlights the value of Manage My Pain to researchers conducting a randomized controlled trial for fibromyalgia patients at the Toronto General Hospital

Describes interim findings from patients at a post-surgical pain management clinic at the Toronto General Hospital who use Manage My Pain

Describes the partnership with Toronto General Hospital to develop key features in Manage My Pain (e.g. Daily Reflection, reports, portal, alerts) and explains how institutional concerns were addressed (e.g. consent, security, privacy)

Applies machine learning (unsupervised learning) to answer the question, "Who uses Manage My Pain?" - the first publication applying machine learning on a large chronic pain patient data-set

Highlights the psychological benefits of using Manage My Pain at a post-surgical pain management clinic at the Toronto General Hospital

Describes how Manage My Pain is used at a post-surgical pain management clinic at the Toronto General Hospital