Interventions minimizing fatigue in children/adolescents with cancer: An integrative review.
Michelle Darezzo Rodrigues NunesEmiliana BomfimKarin OlsonLuis Carlos Lopes-JuniorFernanda Machado Silva-RodriguesRegina Aparecida Garcia de LimaLucila Castanheira NascimentoPublished in: Journal of child health care : for professionals working with children in the hospital and community (2018)
Fatigue is among the most common, debilitating, and distressing symptoms associated with chronic condition in pediatric population. The purpose of this study was to identify non-pharmacological fatigue interventions in children and adolescents with cancer. For this, we carried out an integrative review of the literature from January 2000 to December 2016. A comprehensive search of four databases was conducted: Cumulative Index to Nursing and Allied Health Literature, Psychology Information, Medline via PubMed, and Web of Science. Randomized controlled trial, quasi-experimental, case-control and cohort studies were included in this review. Thirteen relevant studies were included for analysis. Seven papers reported positive outcomes for exercise, exercise plus leisure activities, healing touch and acupressure. In another six papers using exercise, exercise plus psychological intervention and massage, no effectiveness was found. Effective management of fatigue in children and adolescents is important but research in this area is limited, so the results of this review should be interpreted cautiously. Future researchers are encouraged to test the effective interventions in homogenous cancer populations and in other groups where fatigue is a common concern.
Keyphrases
- physical activity
- sleep quality
- randomized controlled trial
- papillary thyroid
- high intensity
- case control
- squamous cell
- healthcare
- young adults
- systematic review
- public health
- mental health
- study protocol
- lymph node metastasis
- depressive symptoms
- childhood cancer
- squamous cell carcinoma
- adipose tissue
- clinical trial
- machine learning
- big data
- climate change
- body composition
- quality improvement
- deep learning
- network analysis
- meta analyses
- genetic diversity