Purpose The purpose of this study was to calibrate the items for the Communicative Participation Item Bank (CPIB) using Item Response Theory (IRT). One overriding objective was to examine if the IRT item parameters would be consistent across different diagnostic groups, thereby allowing creation of a disorder-generic instrument. The intended outcomes were the final item bank and a short form ready for clinical and research applications. Methods Self-report data were collected from 701 individuals representing four diagnoses: multiple sclerosis, Parkinson’s disease, amyotrophic lateral sclerosis and head and neck cancer. Participants completed the CPIB and additional self-report questionnaires. CPIB data were analyzed using the IRT Graded Response Model (GRM). Results The initial set of 94 candidate CPIB items were reduced to an item bank of 46 items demonstrating unidimensionality, local independence, good item fit, and good measurement precision. Differential item function (DIF) analyses detected no meaningful differences across diagnostic groups. A 10-item, disorder-generic short form was generated. Conclusions The CPIB provides speech-language pathologists with a unidimensional, self-report outcomes measurement instrument dedicated to the construct of communicative participation. This instrument may be useful to clinicians and researchers wanting to implement measures of communicative participation in their work.

Purpose This study evaluated psychometric properties of the Patient Health Questionnaire-9 (PHQ-9), the Center for Epidemiological Studies Depression Scale-10 (CESD-10), and the eight-item PROMIS Depression Short Form (PROMIS-D-8; 8b short form) in a sample of individuals living with multiple sclerosis (MS). Research Method Data were collected by a self-reported mailed survey of a community sample of people living with MS (n=455). Factor structure, inter-item reliability, convergent/discriminant validity and assignment to categories of depression severity were examined. Results A one factor, confirmatory factor analytic model had adequate fit for all instruments. Scores on the depression scales were more highly correlated with one another than with scores on measures of pain, sleep disturbance, and fatigue. The CESD-10 categorized about 37% of participants as having significant depressive symptoms. At least moderate depression was indicated for 24% of participants by PHQ-9. PROMIS-D-8 identified 19% of participants as having at least moderate depressive symptoms and about 7% having at least moderately-severe depression. None of the examined scales had ceiling effects, but the PROMIS-D-8 had a floor effect. Conclusions Overall, scores on all three scales demonstrated essential unidimensionality and had acceptable inter-item reliability and convergent/discriminant validity. Researchers and clinicians can choose any of these scales to measure depressive symptoms in individuals living with MS. The PHQ-9 offers validated cut off scores for diagnosing clinical depression. The PROMIS-D-8 measure minimizes the impact of somatic features on the assessment of depression and allows for flexible administration, including Computerize Adaptive Testing (CAT). The CESD-10 measures two aspects of depression, depressed mood and lack of positive affect, while still providing an interpretable total score.

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This study compared the use of the conventional multilevel model (MM) with that of the multiple membership multilevel model (MMMM) for handling multiple membership data structures. Multiple membership data structures are commonly encountered in longitudinal educational data sets in which, for example, mobile students are members of more than one higher-level unit (e.g., school). While the conventional MM requires the user either to delete mobile students' data or to ignore prior schools attended, MMMM permits inclusion of mobile students' data and models the effect of all schools attended on student outcomes. The simulation study identified underestimation of the school-level predictor coefficient, as well as underestimation of the level-two variance component with corresponding overestimation of the level-one variance when multiple membership data structures were ignored. Results are discussed along with limitations and ideas for future MMMM methodological research as well as implications for applied researchers.

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BackgroundThe minimally important difference (MID) refers to the smallest change that is sufficiently meaningful to carry implications for patients’ care. MIDs are necessary to guide the interpretation of scores. This study estimated MID for the Patient Reported Outcomes Measurement Information System (PROMIS) pain interference (PI).MethodsStudy instruments were administered to 414 people who participated in two studies that included treatment with low back pain (LBP; n=218) or depression (n=196). Participants with LBP received epidural steroid injections and participants with depression received antidepressants, psychotherapy, or both. MIDs were estimated for the changes in LBP. MIDs were included only if a priori criteria were met (ie, sample size ≥10, Spearman correlation ≥0.3 between anchor measures and PROMIS-PI scores, and effect size range =0.2–0.8). The interquartile range (IQR) of MID estimates was calculated.ResultsThe IQR ranged from 3.5 to 5.5 points. The lower bound estimate of the IQR (3.5) was greater than mean of standard error of measurement (SEM) both at time 1 (SEM =2.3) and at time 2 (SEM =2.5), indicating that the estimate of MID exceeded measurement error.ConclusionBased on our results, researchers and clinicians using PROMIS-PI can assume that change of 3.5 to 5.5 points in comparisons of mean PROMIS-PI scores of people with LBP can be considered meaningful.

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Objective Over a quarter million individuals in the US have Multiple Sclerosis (MS). Chronic pain and depression are disproportionately high in this population. The purpose of this study was to examine the relationship between chronic pain and depression in MS and to examine potentially meditational effects of anxiety, fatigue and sleep. Methods Cross-sectional data from self-reported instruments measuring multiple symptoms and quality of life indicators were used in this study. Structural equation modeling (SEM) was utilized to model direct and indirect effects of pain on depression in a sample of 1245 community dwelling individuals with MS. Pain interference, depression, fatigue and sleep disturbance were modeled as latent variables with 2 to 3 indicators each. The model controlled for age, sex, disability status (EDSS) and social support. Results A model with indirect effects of pain on depression had adequate fit and accounted for nearly 80% of the variance in depression. The effects of chronic pain on depression were almost completely mediated by fatigue, anxiety, and sleep disturbance. Higher pain was associated with greater fatigue, anxiety, and sleep disturbance, which in turn were associated with higher levels of depression. The largest mediating effect was through fatigue. Additional analyses excluded items with common content and suggested that the meditational effects observed were not attributable to content overlap across scales. Conclusions Individuals living with MS who report high levels of chronic pain and depressive symptoms may benefit from treatment approaches that can address sleep, fatigue, and anxiety.