Shortening the Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R): A Proof-of-Principle Study for Customized Computer-Based Testing

Pain Med. 2015 Dec;16(12):2344-56. doi: 10.1111/pme.12864. Epub 2015 Jul 14.

Abstract

Background: The Screener and Opioid Assessment for Patients with Pain-Revised (SOAPP-R) is a 24-item self-report instrument that was developed to aid providers in predicting aberrant medication-related behaviors among chronic pain patients. Although the SOAPP-R has garnered widespread use, certain patients may be dissuaded from taking it because of its length. Administrative barriers associated with lengthy questionnaires further limit its utility.

Objective: To investigate the extent to which two techniques for computer-based administration (curtailment and stochastic curtailment) reduce the average test length of the SOAPP-R without unduly affecting sensitivity and specificity.

Design: Retrospective study.

Setting: Pain management centers.

Subjects: Four hundred and twenty-eight chronic non-cancer pain patients.

Methods: Subjects had taken the full-length SOAPP-R and been classified by the Aberrant Drug Behavior Index (ADBI) as having engaged or not engaged in aberrant medication-related behavior. Curtailment and stochastic curtailment were applied to the data in post-hoc simulation. Sensitivity and specificity with respect to the ADBI, as well as average test length, were computed for the full-length test, curtailment, and stochastic curtailment.

Results: The full-length SOAPP-R exhibited a sensitivity of 0.745 and a specificity of 0.671 for predicting the ADBI. Curtailment reduced the average test length by 26% while exhibiting the same sensitivity and specificity as the full-length test. Stochastic curtailment reduced the average test length by as much as 65% while always exhibiting sensitivity and specificity for the ADBI within 0.035 of those of the full-length test.

Conclusions: Curtailment and stochastic curtailment have potential to improve the SOAPP-R's efficiency in computer-based administrations.

Keywords: Chronic Pain; Opioids; Respondent Burden; Risk Stratification; SOAPP-R; Substance Abuse.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Analgesics, Opioid / administration & dosage
  • Analgesics, Opioid / adverse effects*
  • Boston
  • Chronic Pain / diagnosis*
  • Chronic Pain / drug therapy*
  • Clinical Decision-Making / methods
  • Diagnosis, Computer-Assisted / methods*
  • Feasibility Studies
  • Female
  • Humans
  • Male
  • Mass Screening / methods
  • Middle Aged
  • Opioid-Related Disorders / diagnosis*
  • Opioid-Related Disorders / prevention & control*
  • Pilot Projects
  • Reproducibility of Results
  • Retrospective Studies
  • Sensitivity and Specificity
  • Software
  • Software Validation
  • Surveys and Questionnaires

Substances

  • Analgesics, Opioid