Table 1 Description of the measurement domains, properties, aspects, and statistics and methods

Reliability

Internal consistency

Cronbach’s alpha or Kuder-Richardson formula (KR-20) to determine relevance

Factor analysis or principal component analysis to determine whether items form one or more than one scale

Reliability

Intraclass correlation coefficient (ICC) or Cohen’s kappa

Measurement error

Standard error of measurement (SEM)

Smallest detectable change (SDC)

Change beyond measurement error

Limits of agreement (LoA)

Minimal important change to determine the adequacy of measurement error

Validity

Content validity

Face validity

Assessment of relevance of all items for the construct, aim and target group

Assessment of important missing items

Construct validity

Structural validity

Factor analysis to confirm the number of subscales present

Hypotheses testing

Assessment of a priori hypotheses, clearly indicating both direction and magnitude of the correlation or difference

Cross-cultural validity

Assessment of adequate reflection of the performance of the items of the original instrument

Criterion validity

Correlation

Area under the receiver operator characteristics curve (AUC)

Sensitivity and specificity

Responsiveness

Assessment of a priori hypotheses focussing on the change score of an instrument in the hypotheses

Area under the receiver operator characteristic curve (AUC)