Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
Health and Quality of Life Outcomes
Published in: Health and Quality of Life Outcomes 1/2013

Open Access 01-12-2013 | Research

Psychometric properties of the Fatigue Severity Scale in obese patients

Authors: Franco M Impellizzeri, Fiorenza Agosti, Alessandra De Col, Alessandro Sartorio

Published in: Health and Quality of Life Outcomes | Issue 1/2013

Login to get access

Abstract

Background

The aim of this study was to examine the psychometric properties of the Fatigue Severity Scale (FSS) to verify whether this instrument is a valid tool to measure fatigue in obese patients, and to examine the prevalence of fatigue in obese patients.

Methods

Before and after a three-week residential multidisciplinary integrated weight reduction program, 220 patients were asked to fill in the questionnaires: FSS, Profile of Mood States (Fatigue-Inertia subscale, POMS-Fatigue, and Vigor-Activity subscale, POMS-Vigor), and the Obesity-Related Well-Being (ORWELL-97). A subsample of 50 patients completed the questionnaire within two days.

Results

The prevalence of fatigue using a cut-off value of 4 for the FSS score was 59%. Correlations were found between FSS and POMS-Fatigue and -Vigor scores (r = 0.58 and 0.53, respectively). A relation was also found between FSS and ORWELL97 (r = 0.52, 0.42 to 0.61). From the factorial analysis only 1 factor was extracted explaining 63% of variance, with factor loading values ranging from 0.71 (item 7) to 0.87 (item 6). Intraclass Correlation Coefficient was 0.89 (0.82 to 0.94), while the agreement as measured using the Standard Error of Measurement was 0.43 (0.36 to 0.54) corresponding to 13% (11 to 17%). Cronbach’s alpha values ranged from 0.94 to 0.93. The internal responsiveness of FSS was comparable to the ORWELL97 (Standardized Response Mean = 0.50 and 0.44, respectively).

Conclusions

Fatigue is an important and frequent symptom in obese patients and therefore should be routinely assessed in both research and clinical practice. This can be achieved using the FSS, which is a short, simple, valid and reliable tool for assessing and quantifying fatigue in obese patients.
Appendix
Available only for authorised users
Literature
1.
Chen MK: The epidemiology of self-perceived fatigue among adults. Prev Med 1986,15(1):74–81. 10.1016/0091-7435(86)90037-XPubMedCrossRef
2.
Chaudhuri A, Behan PO: Fatigue in neurological disorders. Lancet 2004,363(9413):978–988. 10.1016/S0140-6736(04)15794-2PubMedCrossRef
3.
Valko PO, Bassetti CL, Bloch KE, Held U, Baumann CR: Validation of the fatigue severity scale in a Swiss cohort. Sleep 2008,31(11):1601–1607.PubMedCentralPubMed
4.
Varni JW, Limbers CA, Bryant WP, Wilson DP: The PedsQL multidimensional fatigue scale in pediatric obesity: feasibility, reliability and validity. International journal of pediatric obesity: IJPO: an official journal of the International Association for the Study of Obesity 2010,5(1):34–42. 10.3109/17477160903111706CrossRef
5.
Resnick HE, Carter EA, Aloia M, Phillips B: Cross-sectional relationship of reported fatigue to obesity, diet, and physical activity: results from the third national health and nutrition examination survey. Journal of clinical sleep medicine: JCSM: official publication of the American Academy of Sleep Medicine 2006,2(2):163–169.
6.
Lim W, Hong S, Nelesen R, Dimsdale JE: The association of obesity, cytokine levels, and depressive symptoms with diverse measures of fatigue in healthy subjects. Arch Intern Med 2005,165(8):910–915. 10.1001/archinte.165.8.910PubMedCrossRef
7.
Lee YJ, Cho WJ, Kim JK, Lee DC: Effects of coenzyme Q10 on arterial stiffness, metabolic parameters, and fatigue in obese subjects: a double-blind randomized controlled study. J Med Food 2011,14(4):386–390. 10.1089/jmf.2010.1202PubMedCrossRef
8.
Sartorio A, Fontana P, Trecate L, Lafortuna CL: Short-term changes of fatigability and muscle performance in severe obese patients after an integrated body mass reduction program. Diabetes Nutr Metab 2003,16(2):88–93.PubMed
9.
Hjollund NH, Andersen JH, Bech P: Assessment of fatigue in chronic disease: a bibliographic study of fatigue measurement scales. Health Qual Life Outcomes 2007, 5: 12. 10.1186/1477-7525-5-12PubMedCentralPubMedCrossRef
10.
Elbers RG, Rietberg MB, van Wegen EE, Verhoef J, Kramer SF, Terwee CB, Kwakkel G: Self-report fatigue questionnaires in multiple sclerosis, Parkinson's disease and stroke: a systematic review of measurement properties. Qual Life Res 2012,21(6):925–944. 10.1007/s11136-011-0009-2PubMedCentralPubMedCrossRef
11.
Grieve FG, Harris DS, Fairbanks SD: Extending the Fatigue Severity Scale to an obese population. Eating and weight disorders: EWD 2000,5(3):161–165.PubMed
12.
Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD: The fatigue severity scale, Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 1989,46(10):1121–1123. 10.1001/archneur.1989.00520460115022PubMedCrossRef
13.
Guillemin F, Bombardier C, Beaton D: Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol 1993,46(12):1417–1432. 10.1016/0895-4356(93)90142-NPubMedCrossRef
14.
McNair DM, Lorr M, Droppleman LF: Profile of Mood States Manual. San Diego: Industrial and Educational Testing Service; 1971.
15.
Mannucci E, Ricca V, Barciulli E, Di Bernardo M, Travaglini R, Cabras PL, Rotella CM: Quality of life and overweight: the obesity related well-being (Orwell 97) questionnaire. Addict Behav 1999,24(3):345–357. 10.1016/S0306-4603(98)00055-0PubMedCrossRef
16.
Mannucci E, Petroni ML, Villanova N, Rotella CM, Apolone G, Marchesini G: Clinical and psychological correlates of health-related quality of life in obese patients. Health Qual Life Outcomes 2010, 8: 90. 10.1186/1477-7525-8-90PubMedCentralPubMedCrossRef
17.
Floyd FJ, Widaman KF: Factor analysis in the development and refinement of clinical assessment instruments. Psychol Assess 1995, 7: 286–299.CrossRef
18.
de Vet HC, Terwee CB, Knol DL, Bouter LM: When to use agreement versus reliability measures. J Clin Epidemiol 2006,59(10):1033–1039. 10.1016/j.jclinepi.2005.10.015PubMedCrossRef
19.
de Vet HC, Bouter LM, Bezemer PD, Beurskens AJ: Reproducibility and responsiveness of evaluative outcome measures, Theoretical considerations illustrated by an empirical example. Int J Technol Assess Health Care 2001,17(4):479–487.PubMed
20.
Terwee CB, Dekker FW, Wiersinga WM, Prummel MF, Bossuyt PM: On assessing responsiveness of health-related quality of life instruments: guidelines for instrument evaluation. Qual Life Res 2003,12(4):349–362. 10.1023/A:1023499322593PubMedCrossRef
21.
Wright JG, Young NL: A comparison of different indices of responsiveness. J Clin Epidemiol 1997,50(3):239–246. 10.1016/S0895-4356(96)00373-3PubMedCrossRef
22.
Norman GR, Wyrwich KW, Patrick DL: The mathematical relationship among different forms of responsiveness coefficients. Qual Life Res 2007,16(5):815–822. 10.1007/s11136-007-9180-xPubMedCrossRef
23.
Cohen J: Statistical power analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum; 1988.
24.
Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, Bouter LM, de Vet HC: The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol 2010,63(7):737–745. 10.1016/j.jclinepi.2010.02.006PubMedCrossRef
25.
Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, Bouter LM, de Vet HC: Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007,60(1):34–42. 10.1016/j.jclinepi.2006.03.012PubMedCrossRef
26.
Scientific Advisor Committee: Medical Outcomes Trust. Assessing health status and quality-of-life instruments: attributes and review criteria. Qual Life Res 2002,11(3):193–205. 10.1023/A:1015291021312CrossRef
27.
Ary D, Cheser Jacobs L, Razavieh A, Sorensen C: Introduction to Research in Education. Belmont, CA: Wadsworth; 2006.
28.
Ferentinos P, Kontaxakis V, Havaki-Kontaxaki B, Dikeos D, Lykouras L: Psychometric evaluation of the Fatigue Severity Scale in patients with major depression. Qual Life Res 2011,20(3):457–465. 10.1007/s11136-010-9769-3PubMedCrossRef
29.
Lerdal A, Kottorp A, Gay C, Aouizerat BE, Portillo CJ, Lee KA: A 7-item version of the fatigue severity scale has better psychometric properties among HIV-infected adults: an application of a Rasch model. Qual Life Res 2011,20(9):1447–1456. 10.1007/s11136-011-9877-8PubMedCrossRef
30.
Lerdal A, Kottorp A: Psychometric properties of the Fatigue Severity Scale-Rasch analyses of individual responses in a Norwegian stroke cohort. Int J Nurs Stud 2011,48(10):1258–1265. 10.1016/j.ijnurstu.2011.02.019PubMedCrossRef
31.
Lerdal A, Johansson S, Kottorp A, von Koch L: Psychometric properties of the Fatigue Severity Scale: Rasch analyses of responses in a Norwegian and a Swedish MS cohort. Mult Scler 2010,16(6):733–741. 10.1177/1352458510370792PubMedCrossRef
32.
Friedman JH, Brown RG, Comella C, Garber CE, Krupp LB, Lou JS, Marsh L, Nail L, Shulman L, Taylor CB: Fatigue in Parkinson's disease: a review. Movement disorders: official journal of the Movement Disorder Society 2007,22(3):297–308. 10.1002/mds.21240CrossRef
33.
Branas P, Jordan R, Fry-Smith A, Burls A, Hyde C: Treatments for fatigue in multiple sclerosis: a rapid and systematic review. Health Technol Assess 2000,4(27):1–61.PubMed
34.
Group WHOQOL: Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychol Med 1998, 28: 551–558.CrossRef
35.
Newman S: Commentary on Supplement 44: G, ICF core sets for chronic conditions. J Rehabil Med 2004,36(4):186–188. 10.1080/16501970410017413PubMedCrossRef
36.
Boonen A, Stucki G, Maksymowych W, Rat AC, Escorpizo R, Boers M: The OMERACT-ICF Reference Group: integrating the ICF into the OMERACT process: opportunities and challenges. J Rheumatol 2009,36(9):2057–2060. 10.3899/jrheum.090357PubMedCrossRef
37.
Stucki A, Daansen P, Fuessl M, Cieza A, Huber E, Atkinson R, Kostanjsek N, Stucki G, Ruof J: ICF Core Sets for obesity. J Rehabil Med 2004, 44 Suppl: 107–113.PubMedCrossRef
38.
Lucia A, Earnest C, Perez M: Cancer-related fatigue: can exercise physiology assist oncologists? Lancet Oncol 2003,4(10):616–625. 10.1016/S1470-2045(03)01221-XPubMedCrossRef
Metadata
Title
Psychometric properties of the Fatigue Severity Scale in obese patients
Authors
Franco M Impellizzeri
Fiorenza Agosti
Alessandra De Col
Alessandro Sartorio
Publication date
01-12-2013
Publisher
BioMed Central
Published in
Health and Quality of Life Outcomes / Issue 1/2013
Electronic ISSN: 1477-7525
DOI
https://doi.org/10.1186/1477-7525-11-32

Other articles of this Issue 1/2013

Health and Quality of Life Outcomes 1/2013 Go to the issue

Research

Chronic myeloid leukemia (CML): association of treatment satisfaction, negative medication experience and treatment restrictions with health outcomes, from the patient’s perspective

Research

Development and initial validation of a traditional Chinese medicine symptom-specific outcome measure: a Zheng-related atopic dermatitis symptom questionnaire (ZRADSQ)

Research

Validation of the mothers object relations scales in 2–4 year old children and comparison with the child–parent relationship scale

Research

Health related quality of life and mental distress after PCI: restoring a state of equilibrium

Research

Evaluation of the Irritable Bowel Syndrome Quality of Life (IBS-QOL) questionnaire in diarrheal-predominant irritable bowel syndrome patients

Research

Patient-reported outcomes among patients using exenatide twice daily or insulin in clinical practice in six European countries: the CHOICE prospective observational study