The Effect of Dragon Boating on the Quality of Life for Breast Cancer Survivors: A Systematic Review.
Igor Herrero-ZapirainSergio Álvarez-PardoArkaitz CastañedaAdrian Moreno-VillanuevaJuan Francisco Mielgo-AyusoPublished in: Healthcare (Basel, Switzerland) (2024)
Physical activity improves breast cancer-related symptoms in women and decreases cancer-related mortality. The main objective of this systematic review is to synthesize and analyze the evidence of the effect of dragon boating on the quality of life of female breast cancer survivors. A systematic review based on the PRISMA method was conducted using four databases (Web of Science, Scopus, Cochrane and Pubmed). The search phrase used was "Breast Cancer" AND "Dragon Boat" AND "Quality of Life". The search was conducted in June 2024. The PEDro method was used to ensure the quality of the publications. A total of 77 articles published until 2024 were selected, of which 10 met the inclusion criteria of assessing the application of dragon boating and that used a validated instrument to assess quality of life. There is no homogeneity in terms of the instrument used to measure QOL. The SF-36 was the most commonly used, followed by the FACT-B and the EORTC QLQ-C30. Five out of ten articles compared the improvement in quality of life between dragon boating and other physical activities, while 6 out of 10 analyzed the pre-post effect of dragon boat use. Dragon boating is a physical activity alternative that improves the quality of life of breast cancer survivors and reduces the symptomatology caused by the disease and its treatments. As dragon boat programs are applied over a longer period of time, the improvements in quality of life are greater. When compared with other types of physical activity, dragon boating does not show significant differences that position it as a better option for this population.
Keyphrases
- physical activity
- systematic review
- meta analyses
- body mass index
- public health
- sleep quality
- randomized controlled trial
- mental health
- pregnant women
- cardiovascular disease
- metabolic syndrome
- cardiovascular events
- adipose tissue
- young adults
- risk factors
- machine learning
- skeletal muscle
- deep learning
- patient reported outcomes
- coronary artery disease
- big data
- breast cancer risk
- childhood cancer