VALIDATION DATA

MEASUREMENT PROPERTIES
Limitations >=5 European languages (English)
Observations

Translated versions can be found on the official website: http://dash.iwh.on.ca/translations. Researchers and commercial organisations wishing to use the translated measure should contact the developers.

1. RELIABILITY
A. Internal Consistency Tested
Cronbach's (Describe)

The Cronbach’s alpha were high (0.92 and 0.94)

B. Reliability intraobserver or test-retest Tested
Continuous scores: intraclass
correlation coefficient (ICC)
Dichotomus: Cohen kappa (Describe)

Test–retest reliability was evaluated in four studies (from 5 publications): one excellent, one fair and two poor quality ratings. Intraclass correlation coefficients (ICC) ranged from 0.90 to 0.94 and thus met the cut-point for a positive rating (C>.70) and for use in individual patients.

C. Reliability interobserver or Measurement error Tested
Standard error of measurement (SEM),
smallest detectable change (SDC) or
Limits of agreement (LoA) (Describe)

MDC90: 11.0–17.2

2. VALIDITY
A. Content validity: face validity Not Tested
Expert opinion (relevance and
comprehensiveness) (Describe)
B. Construct Validity:
Structural validity
Tested
Hypotheses-testing Tested
Cross-cultural validity Tested
Brief Description

Summary of the validation study that used the QuickDASH in prospective data collection:

1 factor model High interitem correlation (Cronbach’s alpha 0.92) but factor loadings and variance not reported 2 factor model Factor 1 (function): 59 % variance, eigenvalue 6.5 Factor 2 (symptoms): 14 % variance, eigenvalue 1.55.

Later the authors chose to leave the two factor model and return to a single summative score combining Factor 1 (n = 7 items) and 2 items from Factor 2 (n = 2), with a Cronbach’s alpha of 0.925 and factor analysis findings suggesting one factor. The other two items (pins and needles, sleep) from Factor 2 were dropped based on focus group work.

C. Criterion validity Not Tested
Comparison with a 'gold standard' Continuous scores:
correlations, ROC curves Dichotomus:
Sensitivity & Specificity (Describe)