# Single Session Pain Catastrophizing Class: Efficacy & Mechanisms for Reducing Opioid Use Among Chronic Pain Patients

> **NIH NIH K23** · STANFORD UNIVERSITY · 2023 · $159,219

## Abstract

PROJECT SUMMARY/ABSTRACT
 The opioid epidemic is a serious national crisis that affects public health as well as social and economic
welfare, with increasing and alarming mortality rates in the United States. Consequently, there is an urgent
need for effective and efficient interventions to address opioid use to prevent the risk of opioid misuse and
better address it once it is established. One of the greatest predictors for increased opioid use among patients
with chronic pain is pain catastrophizing (PC), defined as persistent negative cognitive and emotional
responses to actual or anticipated pain. Untreated PC can lead to increased opioid use and facilitate the risk
for misuse and overuse of medications, particularly when surgery and pharmacologics are the focal medical
care plan. Despite critical need, there are no targeted interventions that efficiently address the key
psychological factors that can amplify both pain, need for opioids, and increased risk for misuse. In this
mentored career development award (K23), Dr. Ziadni will attempt to address this urgent need for efficient and
effective solutions. Our group has developed a 2-hour targeted, single-session pain catastrophizing class (PC-
class), rooted in cognitive-behavior therapy (CBT) approaches, aimed at reducing opioid use by reducing pain
catastrophizing in chronic pain. This targeted, brief treatment obviates many of the existing barriers and
burdens to usual comprehensive pain-CBT, such as the time required to attend 8 sessions, insurance
coverage, travel costs, lack of skilled clinicians, patient attrition, and copayments. Dr. Ziadni proposes to
implement a randomized controlled trial comparing the PC-class to a health education control class. In Aim 1,
Dr. Ziadni will determine the efficacy of the PC class in reducing opioid use among patients with mixed-etiology
pain conditions. For Aim 2, she will collect daily data that will allow the conduct of analyses on the daily
experience of catastrophizing and how it relates to opioid use, as well as its dynamic response to treatment.
She will use this daily data to characterize the mechanistic influence of catastrophizing on opioid use both on
the daily-level and prospectively. Patient outcomes will be longitudinally tracked at 1, 3, 6, and 12 months after
the intervention session. This project aims to identify patients who achieve a meaningful reduction in opioid
use, which will enable better characterization of treatment responders and refining opioid reduction strategies.
Throughout the award period, Dr. Ziadni will obtain new skills and expertise in the mechanistic science of
opioid use, the conduct of randomized controlled trials, and the neurobiological mechanisms of pain, opioids
and addiction. To accomplish the proposed research and training, Dr. Ziadni has assembled a multi-
disciplinary team of world-class mentors who are committed to her success. This training will build on Dr.
Ziadni’s background in clinical psychology a...

## Key facts

- **NIH application ID:** 10609487
- **Project number:** 5K23DA047473-05
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Maisa Ziadni
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $159,219
- **Award type:** 5
- **Project period:** 2019-05-15 → 2024-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10609487

## Citation

> US National Institutes of Health, RePORTER application 10609487, Single Session Pain Catastrophizing Class: Efficacy & Mechanisms for Reducing Opioid Use Among Chronic Pain Patients (5K23DA047473-05). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10609487. Licensed CC0.

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