Literature DB >> 31270904

Operationalization of the new Pain and Disability Drivers Management model: A modified Delphi survey of multidisciplinary pain management experts.

Yannick Tousignant-Laflamme1, Chad E Cook2, Annie Mathieu3, Florian Naye1,4, Frédéric Wellens4, Timothy Wideman5,6, Marc-Olivier Martel7, Olivier Tri-Trinh Lam4.   

Abstract

BACKGROUND: We recently proposed the Pain and Disability Drivers Management (PDDM) model, which was designed to outline comprehensive factors driving pain and disability in low back pain (LBP). Although we have hypothesized and proposed 41 elements, which make up the model's five domains, we have yet to assess the external validity of the PDDM's elements by expert consensus. RESEARCH
OBJECTIVES: This study aimed to reach consensus among experts regarding the different elements that should be included in each domain of the PDDM model. RELEVANCE: The PDDM may assist clinicians and researchers in the delivery of targeted care and ultimately enhance treatment outcomes in LBP.
METHODS: Using a modified Delphi survey, a two-round online questionnaire was administered to a group of experts in musculoskeletal pain management. Participants were asked to rate the relevance of each element proposed within the model. Participants were also invited to add and rate new elements. Consensus was defined by a greater than or equal to 75% level of agreement.
RESULTS: A total of 47 (round 1) and 33 (round 2) participants completed the survey. Following the first round, 38 of 41 of the former model elements reached consensus, and 10 new elements were proposed and later rated in the second round. Following this second round, consensus was reached for all elements (10 new + 3 from first round), generating a final model composed of 51 elements.
CONCLUSION: This expert consensus-derived list of clinical elements related to the management of LBP represents a first step in the validation of the PDDM model.
© 2019 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Delphi survey; chronic pain; disability; low back pain; pain

Mesh:

Year:  2019        PMID: 31270904     DOI: 10.1111/jep.13190

Source DB:  PubMed          Journal:  J Eval Clin Pract        ISSN: 1356-1294            Impact factor:   2.431


  4 in total

Review 1.  Back pain treatment: a new perspective.

Authors:  Anke Steinmetz
Journal:  Ther Adv Musculoskelet Dis       Date:  2022-07-04       Impact factor: 3.625

2.  Development and content validity of a rating scale for the pain and disability drivers management model.

Authors:  Florian Naye; Simon Décary; Yannick Tousignant-Laflamme
Journal:  Arch Physiother       Date:  2022-05-16

3.  Optimizing management of low back pain through the pain and disability drivers management model: A feasibility trial.

Authors:  Christian Longtin; Simon Décary; Chad E Cook; Marc O Martel; Sylvie Lafrenaye; Lisa C Carlesso; Florian Naye; Yannick Tousignant-Laflamme
Journal:  PLoS One       Date:  2021-01-20       Impact factor: 3.240

4.  Machine Learning Identifies Chronic Low Back Pain Patients from an Instrumented Trunk Bending and Return Test.

Authors:  Paul Thiry; Martin Houry; Laurent Philippe; Olivier Nocent; Fabien Buisseret; Frédéric Dierick; Rim Slama; William Bertucci; André Thévenon; Emilie Simoneau-Buessinger
Journal:  Sensors (Basel)       Date:  2022-07-03       Impact factor: 3.847

  4 in total

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