Details

Autor(en) / Beteiligte

• Wideman, Timothy H
• Edwards, Robert R
• Walton, David M
• Martel, Marc O
• Hudon, Anne
• Seminowicz, David A

Titel

The Multimodal Assessment Model of Pain: A Novel Framework for Further Integrating the Subjective Pain Experience Within Research and Practice

Ist Teil von

• The Clinical journal of pain, 2019-03, Vol.35 (3), p.212

Ort / Verlag

United States

Erscheinungsjahr

2019

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Pain assessment is enigmatic. Although clinicians and researchers must rely upon observations to evaluate pain, the personal experience of pain is fundamentally unobservable. This raises the question of how the inherent subjectivity of pain can and should be integrated within assessment. Current models fail to tackle key facets of this problem, such as what essential aspects of pain are overlooked when we only rely on numeric forms of assessment, and what types of assessment need to be prioritized to ensure alignment with our conceptualization of pain as a subjective experience. We present the multimodal assessment model of pain (MAP) as offering practical frameworks for navigating these challenges. This is a narrative review. MAP delineates qualitative (words, behaviors) and quantitative (self-reported measures, non-self-reported measures) assessment and regards the qualitative pain narrative as the best available root proxy for inferring pain in others. MAP offers frameworks to better address pain subjectivity by: (1) delineating separate criteria for identifying versus assessing pain. Pain is identified through narrative reports, while comprehensive assessment is used to infer why pain is reported; (2) integrating compassion-based and mechanism-based management by both validating pain reports and assessing underlying processes; (3) conceptualizing comprehensive pain assessment as both multidimensional and multimodal (listening/observing and measuring); and (4) describing how qualitative data help validate and contextualize quantitative pain measures. MAP is expected to help clinicians validate pain reports as important and legitimate, regardless of other findings, and help our field develop more comprehensive, valid, and compassionate approaches to assessing pain.