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An Investigation of the Impact of Virtual Reality on Alleviating Anxiety in Patients with Breast Cancer Undergoing Radiotherapy: A Randomized Controlled Trial

Jaeyong Shin, Jee-Suk Chang, Jin Sung Kim, Ji-Ye-On An, S. Chung, So-Yeon Yoon, Yong Bae Kim

International Journal of Radiation Oncology, Biology, Physics, 2023

23 citations

Abstract

PURPOSE

To evaluate the anxiety-reducing effects of virtual reality on breast cancer patients undergoing adjuvant radiation therapy (RT).

METHODS AND MATERIALS

This randomized controlled trial was conducted among breast cancer patients receiving RT at a single institution. Of 196 enrolled and randomized, 97 were assigned to a virtual reality (VR) explanation group (intervention) and 99 were assigned to the standard-of-care group (control). Anxiety levels were measured using the Amsterdam Preoperative Anxiety and Information Scale (APAIS) as the primary endpoint, and State-Trait Anxiety Inventory (STAI) and Linear Analogue Scale Assessment (LASA) as secondary endpoints. Knowledge of the RT procedure, patient satisfaction, and time spent for counseling were also assessed.

RESULTS

Intervention significantly reduced patient anxiety immediately, not only on the primary endpoint, APAIS, but also on the STAI and LASA anxiety scales. Specifically, in the intervention group, there were immediate reductions of 26.0%, 16.1%, and 55.8% for APAIS, STAI, and LASA, respectively, while in the control group, the respective reductions were 8.1%, 8.5%, and 13.7%. Among the three anxiety scales, long-term anxiety reduction was observed only when anxiety was measured by LASA. Subgroup analyses showed that its effect on anxiety did not differ based on the physician, baseline anxiety level, use of hormone therapy or health literacy. The intervention also significantly improved knowledge of the RT…

How strong is the evidence?

Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.

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