CoChat
Sign Up
Cited by 27Psychometric Methodologies and TestingCancer survivorship and careHealth Education and Validation

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Measuring daily fatigue using a brief scale adapted from the Patient-Reported Outcomes Measurement Information System (PROMIS®)

Christodoulou, Christopher, Schneider, Stefan, Junghaenel, Doerte U., Broderick, Joan E., Stone, Arthur A.·2014·Quality of Life Research
DOI 10.1007/s11136-013-0553-z
Open this paper in CoChat — free account

Abstract

Purpose Daily assessments can provide insight into the temporal characteristics of fatigue. They can demonstrate consistency or reveal variability, as when fatigue changes with the underlying medical condition, improves with therapy, or worsens as a medication side effect. We adapted a fatigue measure from the Patient-Reported Outcomes Measurement Information System (PROMIS(®)) for daily assessment and examined its psychometric properties in a month-long prospective study. Methods Three groups of 100 participants each were drawn from two fatigue-related clinical disorders [osteoarthritis (OA) and premenstrual syndrome/premenstrual dysphoric disorder (PMS/PMDD)], and a general population sample (GP). They completed brief daily web-based fatigue measures at home on 28 consecutive evenings. Results Compliance was high for all samples, based on the percent of participants who remained in the study (98 % for GP and OA, 95 % for PMS/PMDD). The new scale performed consistently across the groups, sensitively measuring fatigue with high reliability (>0.90) especially in the average to high fatigue level range. Supporting known-groups validity, fatigue scores were elevated in the clinical groups as compared to the GP. The scale was sensitive to change, with the PMS/PMDD sample showing a linear increase in fatigue prior to menses onset, and a sharp drop off afterward. Conclusions The scale was psychometrically sound across diverse clinical and general population samples, though less rel…

Overview

Integrity signals

Registry

Crossref · 10.1007/s11136-013-0553-z

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Show all 2 references

Research works printed but not linked: 41

  1. Ranjith, G. (2005). Epidemiology of chronic fatigue syndrome. Occupational Medicine, 55(1), 13–19. · DOI
  2. Ricci, J. A., Chee, E., Lorandeau, A. L., & Berger, J. (2007). Fatigue in the U.S. workforce: prevalence and implications for lost productive work time. Journal of Occupational and Environmental Medicine, 49(1), 1–10. · DOI
  3. DeLuca, J. (Ed.). (2005). Fatigue as a window to the brain. Cambridge, MA: MIT Press.
  4. Christodoulou, C. (2012). Approaches to the measurement of fatigue. In G. Matthews, P. A. Desmond, C. Neubauer, & P. A. Hancock (Eds.), The handbook of operator fatigue. Burlington, VT: Ashgate Publishing.
  5. Christodoulou, C. (2005). The assessment and measurement of fatigue. In J. DeLuca (Ed.), Fatigue as a window to the brain (pp. 19–35). New York: MIT Press. · DOI
  6. Chalder, T., Berelowitz, G., Pawlikowska, T., Watts, L., Wessely, S., Wright, D., et al. (1993). Development of a fatigue scale. Journal of Psychosomatic Research, 37(2), 147–153. · DOI · Paper page
  7. Lai, J. S., Cella, D., Choi, S., Junghaenel, D. U., Christodoulou, C., Gershon, R., et al. (2011). How item banks and their application can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Archives of Physical Medicine and Rehabilitation, 92(10 Suppl), S20–S27.
  8. Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194. · DOI · Paper page
  9. Broderick, J. E., Schneider, S., Schwartz, J. E., & Stone, A. A. (2010). Interference with activities due to pain and fatigue: Accuracy of ratings across different reporting periods. Quality of Life Research, 19(8), 1163–1170. · DOI
  10. Broderick, J. E., Schwartz, J. E., Vikingstad, G., Pribbernow, M., Grossman, S., & Stone, A. A. (2008). The accuracy of pain and fatigue items across different reporting periods. Pain, 139(1), 146–157. · DOI
  11. Friedberg, F., & Sohl, S. J. (2008). Memory for fatigue in chronic fatigue syndrome: the relation between weekly recall and momentary ratings. International Society of Behavioral Medicine, 15(1), 29–33. · DOI
  12. Schneider, S., Choi, S. W., Junghaenel, D. U., Schwartz, J. E., & Stone, A. A. (2013). Psychometric characteristics of daily diaries for the Patient-Reported Outcomes Measurement Information System (PROMIS(R)): a preliminary investigation. Quality of Life Research, 22(7), 1859–1869. · DOI · Paper page
  13. Schneider, S., Junghaenel, D. U., Keefe, F. J., Schwartz, J. E., Stone, A. A., & Broderick, J. E. (2012). Individual differences in the day-to-day variability of pain, fatigue, and well-being in patients with rheumatic disease: associations with psychological variables. Pain, 153(4), 813–822. · DOI
  14. Watson, T., & Mock, V. (2004). Exercise as an intervention for cancer-related fatigue. Physical Therapy, 84(8), 736–743. · DOI
  15. Wolfe, F., Hawley, D. J., & Wilson, K. (1996). The prevalence and meaning of fatigue in rheumatic disease. Journal of Rheumatology, 23(8), 1407–1417.
  16. Zautra, A. J., Fasman, R., Parish, B. P., & Davis, M. C. (2007). Daily fatigue in women with osteoarthritis, rheumatoid arthritis, and fibromyalgia. Pain, 128(1–2), 128–135. · DOI · Paper page
  17. Power, J. D., Badley, E. M., French, M. R., Wall, A. J., & Hawker, G. A. (2008). Fatigue in osteoarthritis: a qualitative study. BMC Musculoskeletal Disorders, 9, 63. · DOI
  18. Mortola, J. F. (1992). Issues in the diagnosis and research of premenstrual syndrome. Clinical Obstetrics and Gynecology, 35(3), 587–598. · DOI
  19. Dickerson, L. M., Mazyck, P. J., & Hunter, M. H. (2003). Premenstrual syndrome. American Family Physician, 67(8), 1743–1752.
  20. Tschudin, S., Bertea, P. C., & Zemp, E. (2010). Prevalence and predictors of premenstrual syndrome and premenstrual dysphoric disorder in a population-based sample. Archives of Women’s Mental Health, 13(6), 485–494. · DOI
  21. Bolen, J., Schieb, L., Hootman, J. M., Helmick, C. G., Theis, K., Murphy, L. B., et al. (2010). Differences in the prevalence and severity of arthritis among racial/ethnic groups in the United States, National Health Interview Survey, 2002, 2003, and 2006. Preventing Chronic Disease, 7(3), A64.
  22. Christodoulou, C., Junghaenel, D. U., DeWalt, D. A., Rothrock, N., & Stone, A. A. (2008). Cognitive interviewing in the evaluation of fatigue items: Results from the Patient-Reported Outcomes Measurement Information System (PROMIS). Quality of Life Research, 17(10), 1239–1246. · DOI
  23. Riley, W. T., Rothrock, N., Bruce, B., Christodoulou, C., Cook, K., Hahn, E. A., et al. (2010). Patient-Reported Outcomes Measurement Information System (PROMIS) domain names and definitions revisions: further evaluation of content validity in IRT-derived item banks. Quality of Life Research, 19(9), 1311–1321. · DOI
  24. Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45(5 Suppl 1), S22–S31. · DOI
  25. Junghaenel, D. U., Christodoulou, C., Lai, J. S., & Stone, A. A. (2011). Demographic correlates of fatigue in the US general population: results from the Patient-Reported Outcomes Measurement Information System (PROMIS) initiative. Journal of Psychosomatic Research, 71(3), 117–123. · DOI
  26. Rothrock, N. E., Hays, R. D., Spritzer, K., Yount, S. E., Riley, W., & Cella, D. (2010). Relative to the general US population, chronic diseases are associated with poorer health-related quality of life as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS). Journal of Clinical Epidemiology, 63(11), 1195–1204. · DOI
  27. Cook, K. F., Bamer, A. M., Amtmann, D., Molton, I. R., & Jensen, M. P. (2012). Six patient-reported outcome measurement information system short form measures have negligible age- or diagnosis-related differential item functioning in individuals with disabilities. Archives of Physical Medicine and Rehabilitation, 93(7), 1289–1291. · DOI
  28. Samejima, F. (1970). Estimation of latent ability using a response pattern of graded scores. Psychometrika, 35, 139. · DOI
  29. Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks—Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45(5), S22–S31. · DOI
  30. Muthén, L. K., & Muthén, B. O. (2010). Mplus user’s guide (6th ed.). Los Angeles, CA: Muthén & Muthén.
  31. Crane, P. K., Gibbons, L. E., Ocepek-Welikson, K., Cook, K., Cella, D., Narasimhalu, K., et al. (2007). A comparison of three sets of criteria for determining the presence of differential item functioning using ordinal logistic regression. Quality of Life Research, 16, 69–84. · DOI
  32. Choi, S. W., Gibbons, L. E., & Crane, P. K. (2011). lordif: An R package for detecting differential item functioning using iterative hybrid ordinal logistic regression/item response theory and Monte Carlo simulations. Journal of Statistical Software, 39(8), 1–30.
  33. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
  34. Baker, F. B. (2001). The basics of item response theory. College Park: ERIC Clearinghouse on Assessment and Evaluation.
  35. Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press. · DOI · Paper page
  36. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. · DOI · Paper page
  37. Piasecki, T. M., Hufford, M. R., Solhan, M., & Trull, T. J. (2007). Assessing clients in their natural environments with electronic diaries: rationale, benefits, limitations, and barriers. Psychological Assessment, 19(1), 25–43. · DOI
  38. Gilbert, D. G., McClernon, F. J., Rabinovich, N. E., Plath, L. C., Jensen, R. A., & Meliska, C. J. (1998). Effects of smoking abstinence on mood and craving in men: Influences of negative-affect-related personality traits, habitual nicotine intake and repeated measurements. Personality and Individual Differences, 25(3), 399–423. · DOI · Paper page
  39. Sharpe, J. P., & Gilbert, D. G. (1998). Effects of repeated administration of the Beck Depression Inventory and other measures of negative mood states. Personality and Individual Differences, 24(4), 457–463. · DOI
  40. Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1–32. · DOI · Paper page
  41. Harris, K. M., Schonlau, M., & Lurie, N. (2009). Surveying a nationally representative internet-based panel to obtain timely estimates of influenza vaccination rates. Vaccine, 27(6), 815–818. · DOI

Cited by

Sorted by citations

See all 27

Metadata

Authors
Christodoulou, C., Schneider, S., Junghaenel, D. U., Broderick, J. E., & Stone, A. A.
Affiliations
Stony Brook University (US)
Corresponding author
Christodoulou, Christopher
ORCID
Venue
Quality of Life Research
Publisher
Springer Science and Business Media LLC
Published
2013-10-17
Volume
23
Issue
4
Pages
1245-1253
ISSN
  • 0962-9343 (ISSN-L)
  • 1573-2649
DOI
10.1007/s11136-013-0553-z
OpenAlex
W1983856695
Cited by
27
References
2
Citations by year
2026: 1 · 2025: 4 · 2024: 2 · 2023: 2 · 2022: 3 · 2021: 1 · 2020: 3 · 2019: 3 · 2017: 1 · 2016: 2 · 2015: 4 · 2014: 1
FWCI
3.18
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
  • Quality of Life Research (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institute for Health and Care Research
  • Institut National de la Santé et de la Recherche Médicale
  • National Institutes of Health
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases (U01AR057948)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Health Sciences › Medicine › Oncology › Cancer survivorship and care
  • Health Sciences › Nursing › Research and Theory › Health Education and Validation
Keywords
fatigue measurement, PROMIS, scale adaptation, psychometric properties, reliability statistics, known-groups validity, sensitivity to change, osteoarthritis, premenstrual syndrome, premenstrual dysphoric disorder
MeSH terms
Adult, Factor Analysis, Statistical, Fatigue, Female, Humans, Information Systems, Male, Middle Aged, Osteoarthritis, Premenstrual Syndrome, Prospective Studies, Psychometrics, Quality of Life, Surveys and Questionnaires, Mental Recall, Socioeconomic Factors, Reproducibility of Results, Self Report, Patient Outcome Assessment

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review