We report on the development of short forms from the Patient-Reported Outcomes Measurement Information System (PROMIS™) Sleep Disturbance (SD) and Sleep-Related Impairment (SRI) item banks. Results from post-hoc computerized adaptive testing (CAT) simulations, item discrimination parameters, item means, and clinical judgment were used to select the best-performing 8 items for SD and SRI. The final 8-item short forms provided less test information than the corresponding full banks, but correlated strongly with the longer forms. The short forms had greater measurement precision than the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) as indicated by larger test information values across the continuum of severity, despite having fewer total items, a major advantage for both research and clinical settings.

The PROMIS sleep disturbance and SRI item banks have excellent measurement properties and may prove to be useful for assessing general aspects of sleep and SRI with various groups of patients and interventions.

The Patient-Reported Outcomes Measurement Information System (PROMIS®) is an NIH Roadmap initiative devoted to developing better measurement tools for assessing constructs relevant to the clinical investigation and treatment of all diseases—constructs such as pain, fatigue, emotional distress, sleep, physical functioning, and social participation. Following creation of item banks for these constructs, our priority has been to validate them, most often in short-term observational studies. We report here on a three-month prospective observational study with depressed outpatients in the early stages of a new treatment episode (with assessments at intake, one-month follow-up, and three-month follow-up). The protocol was designed to compare the psychometric properties of the PROMIS depression item bank (administered as a computerized adaptive test, CAT) with two legacy self-report instruments: the Center for Epidemiological Studies Depression scale (CESD; Radloff, 1977) and the Patient Health Questionnaire (PHQ-9; Spitzer et al., 1999). PROMIS depression demonstrated strong convergent validity with the CESD and the PHQ-9 (with correlations in a range from .72 to .84 across all time points), as well as responsiveness to change when characterizing symptom severity in a clinical outpatient sample. Identification of patients as “recovered” varied across the measures, with the PHQ-9 being the most conservative. The use of calibrations based on models from item response theory (IRT) provides advantages for PROMIS depression both psychometrically (creating the possibility of adaptive testing, providing a broader effective range of measurement, and generating greater precision) and practically (these psychometric advantages can be achieved with fewer items—a median of 4 items administered by CAT—resulting in less patient burden).

Objective To evaluate the responsiveness to change of the PROMIS® negative affect measures (Depression, Anxiety, and Anger) using longitudinal data collected in six chronic health conditions. Study Design and Setting Individuals with major depressive disorder (MDD), back pain, chronic obstructive pulmonary disease (COPD), chronic heart failure (CHF), and cancer completed PROMIS negative affect instruments as computerized adaptive test (CAT) or as fixed-length short form (SF) at baseline and a clinically-relevant follow-up interval. Participants also completed global ratings of health. Linear mixed effects models and standardized response means (SRM) were estimated at baseline and follow-up. Results 903 individuals participated (back pain, n = 218; cancer, n = 304; CHF, n = 60; COPD, n = 125; MDD, n = 196). All three negative affect instruments improved significantly for treatments of depression and pain. Depression improved for CHF patients (anxiety and anger not administered), while anxiety improved significantly in COPD groups (stable and exacerbation). Response to treatment was not assessed in cancer. Subgroups of patients reporting better or worse health showed a corresponding positive or negative average SRM for negative affect across samples. Conclusion This study provides evidence that the PROMIS negative affect scores are sensitive to change in intervention studies in which negative affect is expected to change. These results inform the estimation of meaningful change and enable comparative effectiveness research.

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Background We report on the development and calibration of item banks for alcohol use, negative and positive consequences of alcohol use, and negative and positive expectancies regarding drinking as part of the Patient-Reported Outcomes Measurement Information System (PROMIS). Methods Comprehensive literature searches yielded an initial bank of more than 5,000 items from over 200 instruments. After qualitative item analysis (including focus groups and cognitive interviewing), 141 items were included in field testing. Items for alcohol use and consequences were written in a first-person, past-tense format with a 30-day time frame and 5 response options reflecting frequency. Items for expectancies were written in a third-person, present-tense format with no time frame specified and 5 response options reflecting intensity. The calibration sample included 1,407 respondents, 1,000 from the general population (ascertained through an internet panel) and 407 from community treatment programs participating in the National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN). Results Final banks of 37, 31, 20, 11, and 9 items (108 total items) were calibrated for alcohol use, negative consequences, positive consequences, negative expectancies, and positive expectancies, respectively, using item response theory (IRT). Seven-item static short forms were also developed from each item bank. Conclusions Test information curves showed that the PROMIS item banks provided substantial information in a broad range of severity, making them suitable for treatment, observational, and epidemiological research.

The results demonstrated the validity of PROMIS CATs, which require only 4-6 items in each domain. This efficiency makes it feasible to use a comprehensive health status profile within the substance use treatment setting, providing important prognostic information regarding abstinence and severity of drinking.

Purpose Nonspecific factors that accompany healthcare treatments, such as patients’ attitudes and expectations, are important parts of the experience of care and can influence outcomes. However, no precise, concise, and generalizable instruments to measure these factors exist. We report on the development and calibration of new item banks, titled the Healing Encounters and Attitudes Lists (HEAL), that assess nonspecific factors across a broad range of treatments and conditions. Methods The instrument development methodology of the Patient-Reported Outcomes Measurement Information System (PROMIS®) was used. Patient focus groups and clinician interviews informed our HEAL conceptual model. Literature searches of 8 databases yielded over 500 instruments and resulted in an initial item pool of several thousand items. After qualitative item analysis, including cognitive interviewing, 296 items were included in field testing. The calibration sample included 1657 respondents, 1400 obtained through an internet panel and 257 from conventional and integrative medicine clinics. Following exploratory and confirmatory factor analyses, the HEAL item banks were calibrated using item response theory (IRT). Results The final HEAL item banks were Patient-Provider Connection (57 items), Healthcare Environment (25 items), Treatment Expectancy (27 items), Positive Outlook (27 items), and Spirituality (26 items). Short forms were also developed from each item bank. A 6-item short form, Attitudes toward Complementary and Alternative Medicine (CAM) was also created. Conclusions HEAL item banks provided substantial information across a broad range of each construct. HEAL item banks showed initial evidence of predictive and concurrent validity, suggesting they are suitable for measuring nonspecific factors in treatment.