Treatment classifications and interventions for neck pain: a scoping review.

Ishaq, I; Mehta, P; Skinner, IW; Bagg, MK; Bier, J; Verhagen, AP

Treatment classifications and interventions for neck pain: a scoping review.

Ishaq, I Mehta, P

Skinner, IW Bagg, MK Bier, J Verhagen, AP

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Publisher:: ELSEVIER SCIENCE INC
Publication Type:: Journal Article
Citation:: J Clin Epidemiol, 2023, 159, pp. 1-9
Issue Date:: 2023-07

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Field	Value	Language
dc.contributor.author	Ishaq, I
dc.contributor.author	Mehta, P https://orcid.org/0000-0002-9307-9648
dc.contributor.author	Skinner, IW
dc.contributor.author	Bagg, MK
dc.contributor.author	Bier, J
dc.contributor.author	Verhagen, AP
dc.date.accessioned	2023-10-06T04:42:33Z
dc.date.available	2023-04-25
dc.date.available	2023-10-06T04:42:33Z
dc.date.issued	2023-07
dc.identifier.citation	J Clin Epidemiol, 2023, 159, pp. 1-9
dc.identifier.issn	0895-4356
dc.identifier.issn	1878-5921
dc.identifier.uri	http://hdl.handle.net/10453/172553
dc.description.abstract	OBJECTIVES: Our aim is to provide an overview of how neck pain is classified in the literature, define and group conservative interventions into 'nodes', and develop draft networks of interventions in preparation for a network meta-analysis (NMA). STUDY DESIGN AND SETTINGS: We performed a scoping review. For feasibility reasons, we searched for randomized clinical trials (RCTs) via neck pain clinical practice guidelines (CPGs) published from 2014. We used standardized data extraction forms to extract data about classification of neck pain and interventions evaluated in the included RCTs. We calculated frequencies of neck pain classifications and grouped interventions into nodes based on the definitions used in Cochrane reviews. Draft network graphs comparing interventions were constructed using the online Shiny R application CINEMA. RESULTS: We included 242 RCTs from seven CPGs, evaluating 28,581 patients. We found three different classification systems of which The Neck Pain Task Force classification was used most often. We defined and grouped all interventions into 19 discrete potential nodes. CONCLUSION: We found a wide variation in neck pain classifications and conservative interventions. Grouping the interventions was challenging and needs further evaluation before conducting a final NMA.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	ELSEVIER SCIENCE INC
dc.relation.ispartof	J Clin Epidemiol
dc.relation.isbasedon	10.1016/j.jclinepi.2023.04.010
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 11 Medical and Health Sciences
dc.subject.classification	Epidemiology
dc.subject.classification	4202 Epidemiology
dc.subject.mesh	Humans
dc.subject.mesh	Neck Pain
dc.subject.mesh	Network Meta-Analysis
dc.subject.mesh	Humans
dc.subject.mesh	Neck Pain
dc.subject.mesh	Network Meta-Analysis
dc.subject.mesh	Humans
dc.subject.mesh	Neck Pain
dc.subject.mesh	Network Meta-Analysis
dc.title	Treatment classifications and interventions for neck pain: a scoping review.
dc.type	Journal Article
utslib.citation.volume	159
utslib.location.activity	United States
utslib.for	01 Mathematical Sciences
utslib.for	11 Medical and Health Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
pubs.organisational-group	/University of Technology Sydney/Faculty of Health/Graduate School of Health
pubs.organisational-group	/University of Technology Sydney/Faculty of Health/Graduate School of Health/GSH.Physiotherapy
utslib.copyright.status	closed_access	*
dc.date.updated	2023-10-06T04:42:32Z
pubs.publication-status	Published
pubs.volume	159

Abstract:

OBJECTIVES: Our aim is to provide an overview of how neck pain is classified in the literature, define and group conservative interventions into 'nodes', and develop draft networks of interventions in preparation for a network meta-analysis (NMA). STUDY DESIGN AND SETTINGS: We performed a scoping review. For feasibility reasons, we searched for randomized clinical trials (RCTs) via neck pain clinical practice guidelines (CPGs) published from 2014. We used standardized data extraction forms to extract data about classification of neck pain and interventions evaluated in the included RCTs. We calculated frequencies of neck pain classifications and grouped interventions into nodes based on the definitions used in Cochrane reviews. Draft network graphs comparing interventions were constructed using the online Shiny R application CINEMA. RESULTS: We included 242 RCTs from seven CPGs, evaluating 28,581 patients. We found three different classification systems of which The Neck Pain Task Force classification was used most often. We defined and grouped all interventions into 19 discrete potential nodes. CONCLUSION: We found a wide variation in neck pain classifications and conservative interventions. Grouping the interventions was challenging and needs further evaluation before conducting a final NMA.

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http://hdl.handle.net/10453/172553