341: PainPal+: Leveraging personalized mHealth to Improve Outcomes in Chronic Pain Management

Topic: Clinical Science
Subtopic: Pain category (ICD-11), Chronic primary musculoskeletal pain, Digital Health Technologies , Treatment/management

Background and Aims: Chronic pain affects 27.5% of adults, with 10% newly diagnosed annually [1, 2]. Despite its widespread impact,
chronic pain remains notoriously difficult to manage, particularly outside of clinical settings where ongoing support
is often lacking. While non-pharmacological treatments like Cognitive Behavioural Therapy (CBT) show promise,
access is limited [2]. Many mHealth apps fill this gap but lack clinical validation [4, 3, 2]. PainPal+ addresses this via
AI-powered tracking and chatbot support. Study aims: To evaluate PainPal+’s (1) utility in delivering algorithm-
driven self-management suggestions and (2) AI chatbot effectiveness in supporting behavior change and
symptom tracking.

Methods: PainPal+ was developed in collaboration with clinicians and evaluated through a structured
approach. This pilot study evaluated PainPal+ over four weeks. We recruited 30 participants (aged 21–65) with
chronic pain online. Prior to app use, participants completed self-reported clinical outcome surveys regarding pain intensity, pain interference, and psychological well-being. Upon completion, participants downloaded the PainPal+ application and used it over four weeks. The app
collected active data (user-reported pain diaries, exercises) and passive data (including movement and usage
patterns, contingent on participant permission). After the trial, participants completed a follow-up survey assessing the same clinical measures and a usability assessment.

Results: A total of 30 users were onboarded with 21 remaining active during the core evaluation period. Users completed
an average of 2.67 sessions with average engagement time per user was nearly 25 minutes, and, indicating
sustained interaction. Statistically significant reductions were observed in current pain intensity, which decreased
by an average of 2.08 points (p = 0.0153), and in average weekly pain intensity, which saw an even drop of 2.49
points (p = 0.0011). Similarly, pain distress and interference both declined significantly—by 1.74 points (p = 0.0475)
and 2.40 points (p = 0.0015) respectively.

Conclusions: The evaluation of Painpal+ demonstrated strong feasibility and clinically relevant benefits. User engagement was
sustained, with average use approaching 25 minutes across 2.67 sessions, and 70% of participants remaining
active during the core study period. Statistically significant reductions were observed in current and average
weekly pain intensity, as well as pain distress and interference, indicating measurable symptom improvement.
These results suggest the digital intervention is both acceptable to patients and potentially effective in supporting
pain management. Further investigation in larger, controlled samples is warranted to validate and extend these
preliminary findings.

References: 1. Zhao, P., Yoo, I., Lancey, R., & Smith, K. (2019). Mobile applications for pain management: An app analysis
for clinical usage. BMC Medical Informatics and Decision Making, 19(1), 106.
https://doi.org/10.1186/s12911-019-0827-7
2. Alexander, J. C., & Joshi, G. P. (2016). Smartphone applications for chronic pain management: A critical
appraisal. Journal of Pain Research, 9, 731–734. https://doi.org/10.2147/JPR.S119966
3. Koumpouros, Y., & Georgoulas, A. (2023). Pain management mobile applications: A systematic review of
commercial and research efforts. Sensors, 23(15), 6965.
4. Lalloo, C., Jibb, L. A., Rivera, J., Agarwal, A., & Stinson, J. N. (2015). “There’s a pain app for that”: Review of
patient-targeted smartphone applications for pain management. The Clinical Journal of Pain, 31(6),
557–563.

Presenting Author: Fong-Ling Loy
Submitting Author: Fong-Ling Loy

Senior Author: Su-Yin Yang

IASP 2026 Global Year theme of Neuropathic Pain: No

• Su-Yin Yang: Doctor of Philosophy in Health Psychology - Woodlands Hospital
• Brian Premchand: PhD - Universal Health Pte Ltd
• Wee Onn Lim: MA (Clinical Psychology) - Woodlands Hospital
• Neeraj Kothari: BE (Engg) - Universal Health Pte Ltd
• Isabelle Tay: PhD - Universal Health Pte Ltd
• Kwong-Ming Leong - Tan Tock Seng Hospital
• Fong-Ling Loy: MSci(Med) Pain Management - The Practice Matters Pte Ltd