Objective: To examine the interrater reliability and agreement of a pain mechanisms-based classification for patients with nonspecific neck pain (NSNP).

Methods: Design - Observational, cross-sectional reliability study with a simultaneous examiner design.

Setting: University hospital-based outpatient physical therapy clinic.

Participants: A random sample of 48 patients, aged between 18 and 75 years old, with a primary complaint of neck pain was included.

Interventions: Subjects underwent a standardized subjective and clinical examination, performed by 1 experienced physical therapist. Two assessors independently classified the participants' NSNP on 3 main outcome measures.

Main Outcome Measures: The Cohen kappa, percent agreement, and 95% confidence intervals (CIs) were calculated to determine the interrater reliability for (1) the predominant pain mechanism; (2) the predominant pain pattern; and (3) the predominant dysfunction pattern (DP).

Results: There was almost perfect agreement between the 2 physical therapists' judgements on the predominant pain mechanism, kappa=.84 (95% CI, .65-1.00), p<.001. There was substantial agreement between the raters' judgements on the predominant pain pattern and predominant DP with respectively kappa=.61 (95% CI, .42-.80); and kappa=.62 (95% CI, .44-.79), p<.001.

Conclusion(s): The proposed classification exhibits substantial to almost perfect interrater reliability. Further validity testing in larger neck pain populations is required before the information is used in clinical settings.

Clinical Trial Registration Number: NCT03147508 (https://clinicaltrials.gov/ct2/show/NCT03147508).

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823704PMC
http://dx.doi.org/10.1016/j.bjpt.2018.10.008DOI Listing

Publication Analysis

Top Keywords

interrater reliability
12
neck pain
12
predominant pain
12
pain
8
pain mechanisms-based
8
mechanisms-based classification
8
classification patients
8
patients nonspecific
8
nonspecific neck
8
pain mechanism
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!