Related Experiment Video
Updated: Jul 11, 2025

Chuzhen Therapy as a Non-Invasive Traditional Chinese Therapy for Neck Pain
Published on: June 6, 2025
Clinical validation of grouping conservative treatments in neck pain for use in a network meta-analysis: a Delphi
Iqra Ishaq1, Ian W Skinner2, Poonam Mehta1
1Graduate School of Health, Discipline of Physiotherapy, University of Technology Sydney, 100 Broadway, Ultimo, 2007, Australia.
Background:
A network meta-analysis aims to help clinicians make clinical decisions on the most effective treatment for a certain condition. Neck pain is multifactorial, with various classification systems and treatment options. Classifying patients and grouping interventions in clinically relevant treatment nodes for a NMA is essential, but this process is poorly defined.
Objective:
Our aim is to obtain consensus among experts on neck pain classifications and the grouping of interventions into nodes for a future network meta-analysis.
Design:
A Delphi consensus study involving neck pain experts worldwide.
Methods:
We invited authors of neck pain clinical practice guidelines published from 2014 onwards. The Delphi baseline questionnaire was developed based on the findings of a scoping review, including four items on classifications and 19 nodes. Participants were asked to record their level of agreement on a seven-point Likert scale or using Yes/No/Not sure answer options for the various statements. We used descriptive analysis to summarise the responses on each statement with content analysis of the free-text comments.
Results:
In total, 18/80 experts (22.5%) agreed to participate in one or more Delphi rounds. We needed three rounds to reach consensus for two classification of neck pain: one based on aetiology and one on duration. In addition, we also reached consensus on the grouping of interventions, including a definition of each node, with the number of nodes reduced to 17.
Conclusion:
With this consensus we clinically validated two neck pain classifications and grouped conservative treatments into 17 well-defined and clinically relevant nodes.

