Abstract
Objectives: This article reports the cross-studies analysis of projects from the P30 Center of Excellence for Biobehavioral Approaches to Symptom Management. Although the projects investigated diverse populations, a consistent theoretical and empirical approach guided each project. Methods: Common data elements included the following measures of psychobehavioral variables: the PROMIS Short-Form Fatigue Scale, the Center of Epidemiologic Studies Depression Scale, and the Perceived Stress Scale. Plasma cytokines were measured as the shared biological data element. Results: Data were analyzed from 295 participants with fibromyalgia (n = 72), second trimester pregnancy (n = 73), sickle cell anemia (n = 60), and cardiometabolic risk (n = 91). The mean age of participants was 35.4years, and the most participants were female. Levels of symptoms were generally elevated across samples; the level of fatigue ranged from 18.9 to 24.7, depressive symptoms from 12.5 to 23.4, and perceived stress from 16.5 to 21.8. Intercorrelations among symptom measures and perceived stress were strong across the samples. However, correlations among psychobehavioral variables and cytokines were variable, indicating a separate relationship for the measures with cytokines. Conclusions: Future work in symptom science could benefit from common data elements, including biomarkers, across populations to better develop the taxonomy of symptom profiles across conditions.
| Original language | English |
|---|---|
| Pages (from-to) | 322-331 |
| Number of pages | 10 |
| Journal | Nursing Outlook |
| Volume | 62 |
| Issue number | 5 |
| DOIs | |
| State | Published - 2014 |
Bibliographical note
Publisher Copyright:© 2014 Elsevier Inc.
Funding
P30 Center of Excellence for Biobehavioral Approaches to Symptom Management (P30 NR011403, Grap principal investigator). PROMIS was funded with cooperative agreements from the National Institutes of Health (NIH) Common Fund Initiative ( U54AR057951 , U01AR052177 , U54AR057943 , U54AR057926 , U01AR057948 , U01AR052170 , U01AR057954 , U01AR052171 , U01AR052181 , U01AR057956 , U01AR052158 , U01AR057929 , U01AR057936 , U01AR052155 , U01AR057971 , U01AR057940 , U01AR057967 , and U01AR052186 ). The contents of this article uses data developed under PROMIS. These contents do not necessarily represent an endorsement by the U.S. Federal Government or PROMIS. See www.nihpromis.org for additional information on the PROMIS initiative. The authors thank Drs. Rita Pickler and Cindy Munro for their work in developing the P30 Center of Excellence.
| Funders | Funder number |
|---|---|
| National Institutes of Health (NIH) | U01AR052170, U01AR052181, U01AR052171, U54AR057943, U01AR057956, U01AR057967, U01AR052158, U01AR057954, U54AR057951, U01AR057940, U01AR052186, U01AR057971, U01AR052155, U01AR052177, U01AR057929, U54AR057926, U01AR057948, U01AR057936 |
| National Institute of Nursing Research | P30NR011403 |
Keywords
- Big data
- Depressive symptoms: P30
- Fatigue: PROMIS
ASJC Scopus subject areas
- General Nursing
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