Skip to main content


Log in

Self-reported fatigue: one dimension or more? Lessons from the Functional Assessment of Chronic Illness Therapy—Fatigue (FACIT-F) questionnaire

  • Original Article
  • Published:
Supportive Care in Cancer Aims and scope Submit manuscript


Across two general population (total n = 1,878) and two cancer (total n = 3,140) samples, we evaluated the dimensionality of self-reported fatigue as measured by the Functional Assessment of Chronic Illness Therapy—Fatigue (FACIT-F) instrument. After evaluating dimensionality of the FACIT-F, we compared the conceptually distinct fatigue experience versus fatigue impact scores in each sample. Confirmatory factor analysis of the 13-item scale showed very good fit to a single dimension (“unidimensional”) model for each sample (comparative fit index range = 0.92–0.97). Using a bifactor model to compare the loading of each item with the general fatigue factor versus the identified sub-domain (experience or impact), we found the item-general loading to be higher than that of the item-sub-domain factor in 52 of 52 comparisons (13 items; four samples). When scored separately, experience and impact scores were correlated highly (range = 0.80–0.88), yet their difference relative to one another was significant (p < 0.001). Consistently across samples, experience scores were systematically higher (more endorsement) than impact scores, by a margin of 0.21–0.46 SD units. This suggests that the fatigue experience and the impact of fatigue upon function are reported along a single dimensional continuum, but that experience is more likely than impact upon function to be endorsed at lower levels of fatigue. Fatigue as an outcome or trial endpoint can be expressed as a single number, and the experience of the symptom is more likely to be endorsed at mild levels of fatigue, presumably before the symptom exerts an adverse impact upon function.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others


  1. Demetri GD, Kris M, Wade J, Degos L, Cella D (1998) Quality-of-life benefit in chemotherapy patients treated with epoetin alfa is independent of disease response or tumor type: results from a prospective community oncology study. Procrit Study Group. J Clin Oncol 16:3412–3425

    PubMed  CAS  Google Scholar 

  2. Yellen SB, Cella DF, Webster K, Blendowski C, Kaplan E (1997) Measuring fatigue and other anemia-related symptoms with the Functional Assessment of Cancer Therapy (FACT) measurement system. J Pain Symptom Manage 13:63–74

    Article  PubMed  CAS  Google Scholar 

  3. Cella D, Lai JS, Chang CH, Peterman A, Slavin M (2002) Fatigue in cancer patients compared with fatigue in the general United States population. Cancer 94:528–538

    Article  PubMed  Google Scholar 

  4. Lai JS, Crane PK, Cella D (2006) Factor analysis techniques for assessing sufficient unidimensionality of cancer related fatigue. Qual Life Res 15:1179–1190

    Article  PubMed  Google Scholar 

  5. Cella D, Zagari MJ, Vandoros C, Gagnon DD, Hurtz HJ, Nortier JW (2003) Epoetin alfa treatment results in clinically significant improvements in quality of life in anemic cancer patients when referenced to the general population. J Clin Oncol 21:366–373

    Article  PubMed  Google Scholar 

  6. Cella D, Yount S, Sorensen M, Chartash E, Sengupta N, Grober J (2005) Validation of the Functional Assessment of Chronic Illness Therapy Fatigue Scale relative to other instrumentation in patients with rheumatoid arthritis. J Rheumatol 32:811–819

    PubMed  Google Scholar 

  7. Cella D, Yount S, Rothrock N, Gershon R, Cook K, Reeve B, Ader D, Fries JF, Bruce B, Rose M (2007) The Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH roadmap cooperative group during its first two years. Med Care 45:S3–S11

    Article  PubMed  Google Scholar 

  8. Lai JS, Cella D, Choi S, Teresi JA, Hays RD, Stone AA (2008) Developing a fatigue item bank for the Patient-Reported Outcomes Measurement Information System (PROMIS FIB version 1). Presented at the Meeting of the Survey Methods in Multicultural, Multinational, and Multiregional Contexts (3MC), Berlin, Germany.

  9. Hu LT, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling 6:1–55

    Article  Google Scholar 

  10. Reeve BB, Hays RD, Bjorner JB, Cook KF, Crane PK, Teresi JA, Thissen D, Revicki DA, Weiss DJ, Hambleton RK, Liu H, Gershon R, Reise SP, Lai JS, Cella D (2007) Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Med Care 45:S22–S31

    Article  PubMed  Google Scholar 

  11. Gibbons R, Hedeker D (1992) Full-information item bi-factor analysis. Psychometrika 57:423–436

    Article  Google Scholar 

  12. McDonald RP (1999) Test theory: a unified treatment. Lawrence Earlbaum, Mahwah

    Google Scholar 

  13. Muthen LK, Muthen BO (2004) MPlus: statistical analysis with latent variables. Muthen & Muthen, Los Angeles

    Google Scholar 

  14. S. A. S. Institute Inc. (2003) SAS/STAT, Version 9.1.

  15. Chen FF, West SG, Sousa KH (2006) A comparison of bifactor and second-order models of quality of life. Multivariate Behav Res 41:189–225

    Article  Google Scholar 

  16. Cella D, Gershon R, Lai JS, Choi S (2007) The future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment. Qual Life Res 16:133–141

    Article  PubMed  Google Scholar 

Download references

Conflict of interest statement


Author information

Authors and Affiliations


Corresponding author

Correspondence to David Cella.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cella, D., Lai, JS. & Stone, A. Self-reported fatigue: one dimension or more? Lessons from the Functional Assessment of Chronic Illness Therapy—Fatigue (FACIT-F) questionnaire. Support Care Cancer 19, 1441–1450 (2011).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: