The pediatric Functional Assessment of Chronic Illness Therapy-Fatigue (PedsFACIT-F) measures fatigue in various clinical settings.
OBJECTIVE:
To verify the measurement properties of the Arabic version (PedsFACIT-F-Ar) in patients with cancer.
METHODS:
In this cross-sectional validation study, the PedsFACIT-F and the Pediatric Quality of Life Multidimensional Fatigue Scale (PedsQL-MFS) were administered to 114 participants (74 boys and 40 girls) aged 8–18. Exploratory factor analysis was used to test the structural validity of PedsFACIT-F-Ar. Its construct validity was investigated using the hypothesis testing method to predict a moderate correlation (rho 0.4) with the PedsQL-MFS domains and the total score. Its reliability was also tested.
RESULTS:
The PedsFACIT-F-Ar is a two-factor model that explains 67.38% of the total variance. It is significantly correlated with PedsQL-MFS (rho 0.84). It displayed excellent internal consistency (Cronbach’s 0.93) and test-retest reliability (ICC 0.99; 95% CI: 0.96–0.99). Bland–Altman’s analysis revealed the absence of a systematic error between the two test sessions. The standard error of measurement, minimal detectable change (MDC), and MDC% were 0.92, 2.56 points, and 2.88%, respectively, with no floor or ceiling effects.
CONCLUSIONS:
The PedsFACIT-F-Ar demonstrated excellent psychometric properties. The findings suggest the clinical usefulness of this scale.
KudubesAABektasMUgurO. Developing a scale for the assessment of fatigue in pediatric oncology patients aged 7-12 for children and parents. Asian Pacific Journal of Cancer Prevention. 2015; 15(23): 10199-10207.
2.
SiegelRLMillerKDFedewaSA, et al. Colorectal cancer statistics, 2017. CA: A Cancer Journal for Clinicians. 2017; 67(3): 177-193.
3.
WardEDeSantisCRobbinsA, et al. Childhood and adolescent cancer statistics, 2014. CA: A Cancer Journal for Clinicians. 2014; 64(2): 83-103.
4.
BelgaumiAFPathanGQSiddiquiK, et al. Incidence, clinical distribution, and patient characteristics of childhood cancer in Saudi Arabia: A population-based analysis. Pediatric Blood & Cancer. 2019; 66(6): e27684.
5.
NessKKKasteSCZhuL, et al. Skeletal, neuromuscular and fitness impairments among children with newly diagnosed acute lymphoblastic leukemia. Leukemia & Lymphoma. 2015; 56(4): 1004-1011.
6.
AntwiGOJayawardeneWLohrmannDK, et al. Physical activity and fitness among pediatric cancer survivors: a meta-analysis of observational studies. Supportive Care in Cancer. 2019; 27(9): 3183-3194.
7.
AngSHKohSSLLeeXHHT, et al. Experiences of adolescents living with cancer: A descriptive qualitative study. Journal of Child Health Care. 2018; 22(4): 532-544.
8.
BergerAMAbernethyAPAtkinsonA, et al. NCCN clinical practice guidelines cancer-related fatigue. Journal of the National Comprehensive Cancer Network: JNCCN. 2010; 8(8): 904-931.
9.
CamposMHassanBRiechelmannR, et al. Cancer-related fatigue: a practical review. Annals of Oncology. 2011; 22(6): 1273-1279.
10.
AbutahaNAl-zharaniMAl-DoaissAA, et al. Anticancer, antioxidant, and acute toxicity studies of a Saudi polyherbal formulation, PHF5. Open Chemistry. 2020; 18(1): 472-481.
11.
Al QadireMAl KhalailehM. Prevalence of symptoms and quality of life among Jordanian cancer patients. Clinical Nursing Research. 2016; 25(2): 174-191.
12.
TomlinsonDHindsPSEthierM-C, et al. Psychometric properties of instruments used to measure fatigue in children and adolescents with cancer: a systematic review. Journal of Pain and Symptom Management. 2013; 45(1): 83-91.
13.
PerezCSdas NevesLMSVacariAL, et al. Reduction in handgrip strength and electromyographic activity in women with breast cancer. Journal of Back and Musculoskeletal Rehabilitation. 2018; 31(3): 447-452.
14.
ZabitFIyigunG. A comparison of physical characteristics, functions and quality of life between breast cancer survivor women who had a mastectomy and healthy women. Journal of Back and Musculoskeletal Rehabilitation. 2019; 32(6): 937-945.
15.
InvernizziMDe SireALippiL, et al. Impact of rehabilitation on breast cancer related fatigue: a pilot study. Frontiers in Oncology. 2020; 10: 556718.
16.
HockenberryMJHindsPSBarreraP, et al. Three instruments to assess fatigue in children with cancer: the child, parent and staff perspectives. Journal of Pain and Symptom Management. 2003; 25(4): 319-328.
17.
HindsPSHockenberryMTongX, et al. Validity and reliability of a new instrument to measure cancer-related fatigue in adolescents. Journal of Pain and Symptom Management. 2007; 34(6): 607-618.
18.
LaiJ-SStuckyBDThissenD, et al. Development and psychometric properties of the PROMIS® pediatric fatigue item banks. Quality of Life Research. 2013; 22(9): 2417-2427.
19.
VarniJWBurwinkleTMKatzER, et al. The PedsQL™ in pediatric cancer: reliability and validity of the pediatric quality of life inventory™ generic core scales, multidimensional fatigue scale, and cancer module. Cancer. 2002; 94(7): 2090-2106.
20.
SchwartzJEJandorfLKruppLB. The measurement of fatigue: a new instrument. Journal of Psychosomatic Research. 1993; 37(7): 753-762.
21.
LaiJ-SCellaDKupstMJ, et al. Measuring fatigue for children with cancer: development and validation of the pediatric Functional Assessment of Chronic Illness Therapy-Fatigue (pedsFACIT-F). Journal of Pediatric Hematology/Oncology. 2007; 29(7): 471-479.
22.
AlhelihEBakerO. Psychometric Properties of a Developed Arabic Instrument to measure Cancer Treatment-Related Fatigue in Saudi Children. Madridge J Nurs. 2018; 3(1): 107-112.
23.
CrichtonAKnightSOakleyE, et al. Fatigue in child chronic health conditions: a systematic review of assessment instruments. Pediatrics. 2015; 135(4): e1015-e1031.
24.
HairJFBlackWCBabinBJ, et al. Multivariate data analysis: Pearson new international edition. Essex: Pearson Education Limited. 2014; 1(2).
25.
ThorndikeRM. Book review: psychometric theory by Jum Nunnally and Ira Bernstein New York: McGraw-hill, 1994, xxiv+ 752 pp. Applied Psychological Measurement. 1995; 19(3): 303-305.
26.
Association GAotWM. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. The Journal of the American College of Dentists. 2014; 81(3): 14-18.
27.
TerweeCBBotSDde BoerMR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology. 2007; 60(1): 34-42.
28.
Al-GamalELongT. The psychometric properties of an Arabic version of the PedsQL multidimensional fatigue scale tested for children with cancer. Comprehensive Child and Adolescent Nursing. 2017; 40(3): 188-199.
29.
WarnerRM. Applied statistics: From bivariate through multivariate techniques. Sage Publications; 2012.
30.
O’connorBP. SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers. 2000; 32(3): 396-402.
31.
MunroBH. Statistical methods for health care research. Vol. 1. Lippincott Williams & Wilkins; 2005.
32.
KooTKLiMY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine. 2016; 15(2): 155-163.
33.
GiavarinaD. Understanding bland altman analysis. Biochemia Medica. 2015; 25(2): 141-151.
34.
LexellJEDownhamDY. How to assess the reliability of measurements in rehabilitation. American Journal of Physical Medicine & Rehabilitation. 2005; 84(9): 719-723.
35.
DevoogdtNDe GroefAHendrickxA, et al. Lymphoedema functioning, disability and health questionnaire for lower limb lymphoedema (Lymph-ICF-LL): Reliability and validity. Physical Therapy. 2014; 94(5): 705-721.
36.
DownhamDYHolmbäckAMLexellJ. 9 Reliability of measurements in medical research and clinical practice. Studies in Multidisciplinarity. 2005; 3: 147-163.
37.
SmidtNvan der WindtDAAssendelftWJ, et al. Interobserver reproducibility of the assessment of severity of complaints, grip strength, and pressure pain threshold in patients with lateral epicondylitis. Archives of Physical Medicine and Rehabilitation. 2002; 83(8): 1145-1150.
38.
AndresenEM. Criteria for assessing the tools of disability outcomes research. Archives of Physical Medicine and Rehabilitation. 2000; 81: S15-S20.
39.
LohrKN. Assessing health status and quality-of-life instruments: attributes and review criteria. Quality of Life Research. 2002; 11(3): 193-205.
40.
AryDJacobsLRazaviehA, et al. Introduction to research in education. Belmont, CA: Wadsworth Thomson Learning Inc.; 2006.
41.
McCabeM. Fatigue in children with long-term conditions: an evolutionary concept analysis. Journal of Advanced Nursing. 2009; 65(8): 1735-1745.
42.
ter WolbeekMvan DoornenLJKavelaarsA, et al. Predictors of persistent and new-onset fatigue in adolescent girls. Pediatrics. 2008; 121(3): e449-e457.
43.
de VetHCTerweeCBKnolDL, et al. When to use agreement versus reliability measures. Journal of Clinical Epidemiology. 2006; 59(10): 1033-1039.
44.
FernandesKPTeixeiraBSArnoldBJ, et al. Cross-cultural adaptation and validation of the universal Portuguese-version of the Pediatric Functional Assessment of Chronic Illness Therapy-Fatigue (pedsFACIT-F). Jornal de Pediatria. 2020; 96: 456-463.
45.
MahdaviMEPourbakhtAParandA, et al. Test-retest reliability and minimal detectable change of randomized dichotic digits in learning-disabled children: implications for dichotic listening training. Journal of the American Academy of Audiology. 2018; 29(03): 223-232.
