Qigong in cancer care: a systematic review and construct analysis of effective Qigong therapy



This review (a) assesses the strength of evidence addressing Qigong therapy in supportive cancer care and (b) provides insights for definition of effective Qigong therapy in supportive cancer care.


This mixed-methods study includes (a) a systematic review of randomized clinical trials (RCTs) following PRISMA guidelines and (b) a constant-comparative qualitative analysis of effective intervention protocols.


Eleven published randomized clinical trials were reviewed. A total of 831 individuals were studied. Geographic settings include the USA, Australia, China, Hong Kong, and Malaysia. Qigong therapy was found to have positive effects on the cancer-specific QOL, fatigue, immune function, and cortisol levels of individuals with cancer. Qigong therapy protocols varied supporting a plurality of styles. Qualitative analyses identified common programming constructs. Content constructs included exercise (gentle, integrated, repetitious, flowing, weight-bearing movements), breath regulation, mindfulness and meditation, energy cultivation including self-massage, and emphasis on relaxation. Logistic constructs included delivery by qualified instructors, home practice, and accommodation for impaired activity tolerance.


There is global interest and a growing body of research providing evidence of therapeutic effect of Qigong therapy in supportive cancer care. While Qigong therapy protocols vary in style, construct commonalities do exist. Knowledge of the common constructs among effective programs revealed in this research may be used to guide future research intervention protocol and community programming design and development.

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Klein, P.J., Schneider, R. & Rhoads, C.J. Qigong in cancer care: a systematic review and construct analysis of effective Qigong therapy. Support Care Cancer 24, 3209–3222 (2016). https://doi.org/10.1007/s00520-016-3201-7

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  • Cancer
  • Qigong
  • Tai chi
  • Review
  • Qualitative
  • Construct analysis
  • Content analysis