Algorithm-informed Decision-making to Advance Pain Treatment

Summary

Researchers are exploring how certain personal factors, such as symptoms, health history, and lifestyle, may help predict which treatments will work best for someone.

The purpose of this study is to evaluate how well a study algorithm chooses the best treatments for a patient when considering their unique pain characteristics.

Conditions

• Chronic Low-back Pain

Interventions

DEVICE

Algorithmically informed randomization (taking into account phenotypes)

After Phenotypic data is collected from participants, the algorithm will use that data to "rank" the likelihood of success of different treatments for an individual; it will then,randomize participants based on two patterns of assignment. And at visit 3, it will re-randomize those participants who wish to add an additional treatment modality or transfer from one modality to another.

BEHAVIORAL

Physical Therapy (PT) and Exercise

A high-contact intervention (10 in-person sessions) involving individualized programs tailored to participant needs and guided by physical therapy best-practice guidelines. Treatment emphasizes home exercise, progressive low-intensity conditioning, and functional endurance.

BEHAVIORAL

Cognitive-Behavioral Therapy for Pain (PRISM-CBT)

A moderate-contact telehealth intervention (8 virtual sessions) integrating standard CBT techniques with positive activity modules to enhance engagement, mood, and self-efficacy. Weekly modules focus on pacing, cognitive reframing, relaxation, gratitude, and acts of kindness.

BEHAVIORAL

mHealth Acupressure Self-Management:

A low-contact, self-guided intervention delivered via the MeTime mobile application, supported by brief staff instruction. Participants practice daily self-acupressure at ten standardized points for approximately 30 minutes per day, stimulating key acupoints associated with pain modulation.

DRUG

Duloxetine

This is a serotonin-norepinephrine reuptake inhibitor (SNRI) FDA-approved for chronic pain. A low-contact pharmacologic intervention consisting of an 8-week dose escalation of 60 mg duloxetine, followed by taper as indicated. Participants initiate medication at home after a standardized orientation, with remote safety and adherence check-ins.

Sponsors & Collaborators

• National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

  collaborator NIH

• University of Michigan

  lead OTHER

Principal Investigators

• Afton Hassett, PsyD · University of Michigan

• Daniel Clauw, MD · University of Michigan

Study Design

Allocation

RANDOMIZED

Purpose

HEALTH_SERVICES_RESEARCH

Masking

QUADRUPLE

Model

SEQUENTIAL

Eligibility

Min Age

25 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-07-31

Primary Completion

2030-02-28

Completion

2030-07-31

FDA Device

Yes

Countries

• United States

Study Locations