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  2. Multidimensional Assessment of Fatigue

Multidimensional Assessment of Fatigue

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Purpose

The Multidimensional Assessment of Fatigue (MAF) is a 16-item self-report measure designed to evaluate fatigue in adults with rheumatoid arthritis (RA). MAF is also used in additional adult populations including but not limited to those with systemic lupus erythematosus (SLE), multiple sclerosis (MS), ankylosing spondylitis, and various cancers.

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Instrument Details

Acronym MAF

Area of Assessment

Activities of Daily Living
Mental Health
Occupational Performance
Social Relationships
Quality of Life

Assessment Type

Patient Reported Outcomes

Cost

Free

Actual Cost

$0.00

Cost Description

If using this assessment in industry, please contact instrument authors for rights to use. Please see conditions of use: https://eprovide.mapi-trust.org/instruments/multidimensional-assessment-of-fatigue#contact_and_conditions_of_use

CDE Status

NINDS CDE status as of 5/23/19

  • Supplemental: rheumatoid arthritis (RA), osteoarthritis (OA), ankylosing spondylitis
  • Exploratory: systemic lupus, fibromyalgia, multiple sclerosis (MS), cancer, HIV

Populations

Multiple Sclerosis
Mixed Populations
Chronic Pain
Cancer
Brain Injury
Arthritis

Key Descriptions

  • 16-item, self-administered questionnaire
  • 5 dimensions: degree of impact, severity, distress, impact on activities of daily living, and timing
  • Items 1 through 14 are measured on a scale of 1 to 10
  • Items 15 and 16 have categorical responses
  • If Item 1 receives a score of 1, a score of 0 is assigned to items 2-16.
  • Scoring consists of a summation of items 1 through 3 (maximum 30), an average of items 4 through 14 (maximum 10), and conversion of item 15 to scale of 10 by multiplying by 2.5 (maximum 10)
  • The Global Fatigue Index (GFI) is calculated by adding these 3 numbers together to get a score out of 50. Item 16 is not included in calculating the GFI.

Number of Items

16

Equipment Required

  • MAF Form

Time to Administer

10 minutes

Required Training

No Training

Age Ranges

Adult

18 - 64

years

Instrument Reviewers

  • Madison Lash
  • Sara Kiyani
  • Kendal Rozaieski
  • Tim Schulte
  • Dashae Smallwood
  • Brett Piland
  • Neel Patel, OMS-3, Chicago College of Osteopathic Medicine

ICF Domain

Activity
Participation

Measurement Domain

Activities of Daily Living

Considerations

  • Patient’s literacy level
  • Cognitive status
  • Willingness of patient to participate with the measurement tool as fatigue could cause patient to not finish tool (noted to have the lowest completion rate of outcome measures < 80%).
  • Instructions can be complicated, additional explanations and supervision may be needed because if the instructions are not explained well, it is not uncommon for fatigue to be underestimated

Arthritis

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Standard Error of Measurement (SEM)

Rheumatoid Arthritis: (Nicassio et al, 2012; n=106; mean age = 56.09 (12.45) years; Mean time since RA diagnosis 10.75 (11.23) years)

  • SEM for direct effects of disease to fatigue = 0.285
  • SEM for indirect effects of disease to fatigue = 0.231

Cut-Off Scores

Ankylosing Spondylitis (Turan et al, 2007; n=68)

  • Patients with BASDAI score of ≥ 5 are accepted to have fatigue.

Ankylosing Spondylitis (Dernis-Labous et al, 2003; n=639)

  • Patients with VAS >50 are accepted to have fatigue

Test/Retest Reliability

Ankylosing Spondylitis (Bahouq et al, 2012; n=110)

  • Excellent test-retest reliability (ICC=0.98)

Internal Consistency

Ankylosing Spondylitis (Bahouq et al, 2012; n=110)

  • Excellent internal consistency (Cronbach's alpha = .991)

Construct Validity

Convergent Validity

Ankylosing Spondylitis

Turan et al, 2007; n=68

  • Excellent convergent validity between MAF and BASDAI (r=0.692)
  • Excellent convergent validity between MAF and BASFI (r=0.712)

Bahouq et al, 2012; n=110

  • Adequate convergent validity between MAF and axial (r=0.34) and peripheral (r=0.32) visual analogical scale
  • Excellent convergent validity between MAF and BASDAI (r=0.77)
  • Excellent convergent validity between MAF and BASFI (r=0.64)

Dernis-Labous et al, 2003; n=639

  • Adequate convergent validity between VAS fatigure and VAS axial pain (r=0.58)
  • Adequate convergent validity between VAS fatigue and BASFI (r=0.57)
  • Adequate convergent validity between VAS fatigue and VAS global assessment pain (r=0.47)

Nicassio et al, 2012; n=106

  • Adequate convergent validity between MAF and PSQI daily disturbances (r = 0.531)
  • Adequate convergent validity between MAF and RADAR disease activity (r = 0.401)
  • Adequate convergent validity between MAF and PSQI sleep quality (r = 0.447)

Divergent Validity

Turan et al, 2007; n=68

  • Adequate divergent validity between MAF and hemoglobin (r= -0.384)

Nicassio et al, 2012; n=106

  • Excellent divergent validity between MAF and SF-36 vitality subscale (r = -0.787)

Chronic Pain

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Internal Consistency

Fibromyalgia: (Dailey et al, 2016; n=94 women; mean age = 49.2 (11.0) years; mean BMI = 33.8 (7.3))

  • Excellent internal consistency (Cronbach’s alpha = .93)

Construct Validity

Convergent Validity

Fibromyalgia: (Dailey et al, 2016; n=94 women; mean age = 49.2 (11.0) years; mean BMI = 33.8 (7.3))

  • Adequate convergent validity between MAF and Visual Analog Scale (r=0.80)

Multiple Sclerosis

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Internal Consistency

Multiple Sclerosis:

(Schwartz et al, 1996; n = 139; Mean Age = 43.06 (8.94) years; Mean Time Post diagnosis = 8.22 (6.69) years)

  • Excellent internal consistency (Cronbach’s alpha = .93)

Cancer

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Test/Retest Reliability

Cancer:

Meek et al, 2000; n = 212; mean age = 56.6 (13.6) years

  •  Excellent internal consistency coefficient Alpha (.88), stability (.87), completion rate (79.5%)

Internal Consistency

Cancer:

Meek et al, 2000; n = 212; mean age = 56.6 (13.6) years

  • Excellent internal consistency: Cronbach’s Alpha = .93)

Responsiveness

Cancer:

Meek et al, 2000; n = 212; mean age = 56.6 (13.6) years

  • Statistically significant changes for high score (SD), 22.8 (10.2) and low score (SD), 20.3 (9.2) for fatigue rating (p = 0.001)

Mixed Populations

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Minimally Clinically Important Difference (MCID)

Systemic Lupus Erythematosus (SLE): (Goligher et al, 2008; n = 80; mean age = 47.8 (12.5) years)

  • Normalized Scaling:11.5 (95% Confidence Interval: 6.4,16.7)
  • Standardized: 0.45 (95% Confidence Interval: 0.25, 0.61)
    • Obtained by taking MCID divided by standard deviation of patient scores
  • Original Scaling: 5.0 (95% Confidence Interval: 2.8, 7.2)

Internal Consistency

Human Immunodeficiency Virus (HIV): (Grady, et al 1998; n = 50; Mean Age = 39.2 (6.8) years)

  • Excellent internal consistency (Cronbach’s alpha = .93)

 

Pregnancy: (Mortazavi et al, 2019; n = 582; Mean age 27.2 (5.5) years; Mean gestational age 23.24 (10) weeks)

  • Excellent internal consistency (Cronbach’s alpha = 0.957)

Construct Validity

Pregnancy: (Mortazavi et al, 2019; n = 582; Mean age 27.2 (5.5) years; Mean gestational age 23.24 (10) weeks)

  • Moderate divergent validity between MAF and WHO-5 (r = -0.35)

Brain Injury

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Cut-Off Scores

Traumatic Brain Injury (TBI): (Englander et al, 2010; n = 119; Mean age = 40 (12) years)

  • Score of 27 was used as a cut-off score for the presence of fatigue.

Bibliography

Bahouq, Hanane, Samira Rostom, Rachid Bahiri, Jinane Hakkou, Nawal Aissaoui, and Najia        Hajjaj-Hassouni. “Psychometric Evaluation of the Arabic Version of the Multidimensional Assessment of Fatigue Scale (MAF) for Use in Patients with Ankylosing Spondylitis.” Rheumatology International 32, no. 12 (December 1,2012):3969–76. https://doi.org/10.1007/s00296-011-2306-z.

Dailey DL, Frey Law LA, Vance CG, et al. Perceived function and physical performance are associated with pain and fatigue in women with fibromyalgia. Arthritis Res Ther. 2016;18:68. Published 2016 Mar 16. doi:10.1186/s13075-016-0954-9

Dernis-Labous, E. “Assessment of Fatigue in the Management of Patients with Ankylosing Spondylitis.” Rheumatology 42, no. 12 (June 27, 2003): 1523–28. https://doi.org/10.1093/rheumatology/keg421.

Jeffrey Englander, Tamara Bushnik, Jean Oggins & Laurence Katznelson (2010) Fatigue after traumatic brain injury: Association with neuroendocrine, sleep, depression and other factors, Brain Injury, 24:12, 1379-1388, DOI: 10.3109/02699052.2010.523041

Goligher E, Pouchot J, Brant R, Kherani RB, Aviña-Zubieta JA, Lacaille D, et al. Minimal clinically important difference for 7 measures of fatigue in patients with systemic lupus erythematosus. J Rheumatol 2008;35:635–42.

Grady C, Anderson R, Chase, GA. Fatigue in HIV-infected men receiving investigational interleukin-2. Nurs Res, 1998. 47(4): 227-34. Meek PM, et al. Psychometric testing of fatigue instruments for use with cancer patients. Nurs Res, 2000. 49(4): 181-190.

Meek, P. M., L. M. Nail, A. Barsevick, A. L. Schwartz, S. Stephen, K. Whitmer, S. L. Beck, L. S. Jones, and B. L. Walker. “Psychometric Testing of Fatigue Instruments for Use with Cancer Patients.” Nursing Research 49, no. 4 (August 2000): 181–90.

Mortazavi F, Borzoee F. Fatigue in Pregnancy: The validity and reliability of the Farsi Multidimensional Assessment of Fatigue scale. Sultan Qaboos Univ Med J. 2019;19(1):e44-e50. doi:10.18295/squmj.2019.19.01.009

Nicassio, Perry M., Sarah R. Ormseth, Mara K. Custodio, Michael R. Irwin, Richard Olmstead, and Michael H. Weisman. “A Multidimensional Model of Fatigue in Patients with Rheumatoid Arthritis.” The Journal of Rheumatology 39, no. 9 (September 2012): 1807–13. https://doi.org/10.3899/jrheum.111068.

Schwartz, Carolyn E., Linda Coulthard-Morris, and Qi Zeng. “Psychosocial Correlates of Fatigue in Multiple Sclerosis.” Archives of Physical Medicine and Rehabilitation 77, no. 2 (February 1, 1996): 165–70. https://doi.org/10.1016/S0003-9993(96)90162-8.

Turan, Y., Duruöz, M.T., Bal, S. et al. Rheumatol Int (2007) 27: 847. https://doi.org/10.1007/s00296-007-0313-x

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