User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial.

Background: Chronic pain imposes a large burden on individuals and society. A patient-centric digital chronic pain management app called Manage My Pain (MMP) can be used to enhance communication between providers and patients and promote self-management.

Objective: The purpose of this study was to evaluate the real-world engagement of patients in urban and rural settings in Ontario, Canada with the MMP app alongside their standard of care and assess the impact of its usage on clinical outcomes of pain and related mental health.

Engagement with Manage My Pain mobile health application among patients at the Transitional Pain Service.

Objective: Mobile health platforms have become an important component of pain self-management programs and hundreds of mobile applications are commercially available for patients to monitor pain. However, few of these applications have been developed in collaboration with healthcare professionals or have been critically evaluated. Manage My Pain is a user-driven mobile health platform developed by ManagingLife in collaboration with clinician researchers.

Interpretability and Class Imbalance in Prediction Models for Pain Volatility in Manage My Pain App Users: Analysis Using Feature Selection and Majority Voting Methods.

Background: Pain volatility is an important factor in chronic pain experience and adaptation. Previously, we employed machine-learning methods to define and predict pain volatility levels from users of the Manage My Pain app. Reducing the number of features is important to help increase interpretability of such prediction models.

Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods.

Background: Measuring and predicting pain volatility (fluctuation or variability in pain scores over time) can help improve pain management. Perceptions of pain and its consequent disabling effects are often heightened under the conditions of greater uncertainty and unpredictability associated with pain volatility.

Objective: This study aimed to use data mining and machine learning methods to (1) define a new measure of pain volatility and (2) predict future pain volatility levels from users of the pain management app, Manage My Pain, based on demographic, clinical, and app use features.

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation.

Background: Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use.

Objective: The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement.

The Toronto General Hospital Transitional Pain Service: development and implementation of a multidisciplinary program to prevent chronic postsurgical pain.

Chronic postsurgical pain (CPSP), an often unanticipated result of necessary and even life-saving procedures, develops in 5-10% of patients one-year after major surgery. Substantial advances have been made in identifying patients at elevated risk of developing CPSP based on perioperative pain, opioid use, and negative affect, including depression, anxiety, pain catastrophizing, and posttraumatic stress disorder-like symptoms. The Transitional Pain Service (TPS) at Toronto General Hospital (TGH) is the first to comprehensively address the problem of CPSP at three stages: 1) preoperatively, 2) postoperatively in hospital, and 3) postoperatively in an outpatient setting for up to 6 months after surgery.