The results of this study indicate that the PROMIS-PI items constitute a psychometrically sound item bank for assessing the negative effects of pain on functioning in the range experienced by the vast majority of people who have pain. This conclusion is supported by findings concerning (1) unidimensionality, (2) item fit to the IRT model, (3) reliability of the PROMIS-PI scores across different levels of pain interference, (4) associations between PROMIS-PI scores and other measures, (5) and the independence of function of the large majority of items with respect to subgroup membership.
There are several advantages of the PROMIS-PI over traditional measures of pain interference. The item bank can be used to develop short forms for particular purposes or samples, or the items can be administered using CAT. Scores on short forms and on CAT are reported in the same metric and are directly comparable. Also, through the PROMIS Assessment Center, pain interference can be measured in context with other domains (e.g. depression, anxiety, physical function, fatigue, social health) and scores can be graphically displayed and compared with respect to national and subgroup norms. A major strength of the PROMIS-PI bank is that scores have inherent meaning; they communicate respondents' levels of a domain relative to the general population. Thus, the PROMIS PI bank advances the measurement of pain interference.
Responses to self-reported items measuring complex constructs are never strictly unidimensional. However, the results of our analyses support the conclusion that the pain interference domain, at least as measured by the PROMIS-PI item bank, is a homogenous construct. These results have conceptual as well as psychometric implications. Psychometrically, the results strongly support the use of one summary score. Conceptually, they suggest that pain interference is a relatively “narrow band” domain [45
]. The PROMIS-PI item responses exhibited high internal consistency and a single factor dominated despite inclusion of items representing multiple hypothesized pain interference subdomains. The results are consistent with EFA results from most (but not all) analyses of other measures of pain interference [14
] and consistent with the high internal consistency estimates obtained for other pain interference measures [4
The PROMIS-PI scores proved to be highly reliable in the T-score range of 50 and 80. They were less reliable in score ranges representing no pain interference to mild pain interference (e.g., scores that are >1 SD below the population mean) and in score ranges reflecting very severe pain interference (e.g., scores that are >3 SD above the population mean). However, the range of high reliability for the PROMIS-PI scores corresponds to the range reported by most individuals in our samples (see ). For instance, among the ACPA clinical sample, no individuals had a score lower than 40 and only 5 individuals (less than 1%) had PROMIS-PI score over 80.
Strong support for the validity of PROMIS-PI scores was observed in the pattern of correlations with other measures and the scores ability to discriminate among individuals with different levels and numbers of chronic conditions, disabling conditions, and general health. Pain intensity and pain interference scores had approximately 25% shared variance (rho = .487), suggesting that the pain interference and pain intensity are related, but distinct domains.
The findings concerning differential item function support the use of the PROMIS-PI items (and the interpretation of the PROMIS-PI scores) across samples that differ in educational level (no differences were found) and gender (difference found in only one item). DIF was of somewhat greater concern with respect to age (8 items were found to have statistically, age-related DIF). However, though DIF reached statistical significance, its practical impact on scores was minor. We judged this impact to be negligible, retained all items in the bank, and did not construct scoring tables that would account for these differences. Nevertheless, future studies should evaluate the impact of DIF on PROMIS-PI scores obtained using CAT. Additionally, in selecting items from the bank for short forms, we recommend giving preference to items that exhibited no statistically significant DIF.
Study Limitations and Future Research Directions
Although the findings provide preliminary support for the validity and reliability of the PROMIS-PI item bank, validation is an ongoing process, and no single study can provide all the information needed to fully understand the strengths and weaknesses of a measure. Data for the current study were obtained from large community samples that included healthy individuals as well as individuals with a number of specific health problems. Although these samples represent a large range of individuals, it would be useful to expand the evaluation of the PROMIS-PI to additional subgroups, such as persons with specific pain conditions (e.g., headache, low back pain, post-herpetic neuralgia), individuals with other health conditions who often have pain as a secondary complaint or symptom (e.g., patients with multiple sclerosis, cerebral palsy, neuromuscular disease), in ethnic/racial minority samples and in persons with lower levels of education.
In addition, although we performed a variety of analyses useful for determining the psychometric properties of the PROMIS-PI items, additional analyses would be helpful for interpreting the PROMIS PI scores. The interpretability of the PROMIS metric could be extended by estimating score differences representing meaningful category intervals (e.g., “clinically important difference”, “clinically meaningful change”). Another important step, and one seldom undertaken with health outcome measures, is to develop supportable inferences based on PROMIS-PI scores [52
]. These would include, for example, associating PROMIS-PI scores and score changes with clinical markers or “actionable” events, such as change in medication or referral to specialists.