Table 1. A brief explanation of the key psychometric properties examined in this study.
| Psychometric property | Brief explanation |
|---|---|
| Internal consistency | Internal consistency examines how items (e.g., questions) in a measure (e.g., PCOC SAS) are associated (or correlate) with each other. Internal consistency provides an indication of the level of coherence of a measure. It also provides an indication of whether there are redundant items in a measure. From a clinical perspective, good internal consistency for measures that examine a single concept is important. This is because measures with high internal consistency may place unnecessary burden on patients, carers and staff (as the measure may have redundant questions in it). While measures with a low internal consistency may mean that a number of different concepts are being measured by the scale, and this may make it more challenging to use as part of routine clinical care. |
| Construct validity | Construct validity investigates whether a measure examines the concept (or construct) it intends to. Convergent and discriminant validity are part of construct validity. Convergent validity tests how closely items correlate. Discriminant (or divergent) validity recognises that unrelated items should have low correlations. Theory or hypothesis testing is part of examining these types of validity. This is because what we need to measure may not always be observed directly. Establishing a clear hypothesis or theory to test from the beginning is important as it helps reduce the risk of bias. If the relationship between the theory and the measure is not apparent in the results from the study, then the measure does not measure what it intends to measure (and it has poor construct validity) or the theory tested was incorrect. Reporting negative findings and reviewing the theories that were tested in research is an important part of developing outcome measures. This helps build knowledge, allows for critical appraisal of research results, and it ensures honesty in research reporting and conduct. |
| Reliability | Concerns whether a measure is able to produce reproducible and consistent results. Intra-rater (test-retest) reliability involves the same person repeating the measure. Inter-rater reliability examines agreement between different raters (e.g., a carer and a staff member). |
| Interpretability | Provides an indication of the extent to which someone (the patient, the carer, staff) can derive meaning from the numerical scores in the measure. This is important when it comes to ensuring the measure informs clinical care. |
| Acceptability | Examines how agreeable the measure is to the user (the patient, the carer, staff). Low levels of acceptability may result in a measure not being used, it being used incorrectly and missing data. |
| Sensitivity | Examines whether the measure can detect differences between groups. For example, whether the measure can detect differences between different diagnostic groups or those with advanced versus early-stage disease. |
Acknowledgment: This information has been derived from: Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. Journal of clinical epidemiology. 2007; 60(1):34–42 and Fayers PM, Machin D. Scores and measurements: validity, reliability, sensitivity. Quality of life: the assessment, analysis and interpretation of patient reported outcomes. 2nd ed. Chichester: John Wiley & Sons; 2007. pp. 77–108.