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This study aims to determine the effect of watching nature videos accompanied by natural sounds (music) through virtual reality (VR) headsets on sleep quality, state anxiety, and trait anxiety levels in high-risk pregnant women. The research is designed as a single-blind, randomized controlled experimental study. Data collection tools include the Pregnant Information Form, State-Trait Anxiety Inventory (STAI), and the Pittsburgh Sleep Quality Index (PSQI). The collected data will be analyzed using SPSS 25. Data collection is planned to take place between June 2025 and December 2026.
Full description
High-risk pregnancies are a process that carries complications that can negatively affect both maternal and fetal health, increasing stress and anxiety. In such pregnancies, women are more affected by both psychological and physiological changes. Increased stress and anxiety can threaten both the mother's and fetus's health and increase the likelihood of pregnancy complications. Additionally, common sleep problems during pregnancy, especially in the third trimester, become more pronounced and can negatively impact both physiological and psychological health. This project aims to investigate the effects of virtual reality headsets with nature scenes and sounds on sleep quality and anxiety levels in women with high-risk pregnancies. The virtual reality experience aims to reduce stress, improve sleep quality, decrease anxiety, and enhance overall physiological health for the women. Recently, virtual reality used in the medical field has helped reduce stress levels in pregnant women through nature imagery and sounds, promoting relaxation and improving sleep quality. With this technology, it may be possible to alleviate the psychological challenges encountered during pregnancy, thereby improving both maternal and fetal health. Therefore, researching the effects of virtual reality technology on psychological and physiological health in high-risk pregnancies is of great importance. The study will be conducted at the Perinatology Clinic of Health Sciences University Antalya Training and Research Hospital between June 2025 and December 2026 with 68 high-risk pregnant women. A randomized controlled design will be used, and participants will be divided into two groups. The intervention group will watch videos with nature scenes and sounds for 15 minutes each evening for 5 consecutive days, using virtual reality headsets. The control group will not receive any intervention. Data collection tools will include the Pregnancy Introduction Form, Anxiety Inventories, and the Pittsburgh Sleep Quality Index, and the data will be analyzed using SPSS 25. During the study, participants' psychological health, anxiety levels, and sleep quality will be regularly evaluated. This study aims to investigate the effects of virtual reality technology on psychological health in high-risk pregnancies and whether it reduces anxiety and improves sleep quality. The results may indicate that virtual reality helps cope with psychological challenges and improve fetal health. The study will contribute to the nursing literature by exploring the effects of virtual reality headsets on anxiety and sleep quality and will aim to develop suitable approaches for women with high-risk pregnancies. Additionally, virtual reality could be an effective non-pharmacological intervention. The results could bring innovations to health service policies and clinical practices, help healthcare workers develop more effective support strategies, and improve both maternal and fetal health.
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Inclusion criteria
Pregnant women who are hospitalized due to high-risk pregnancy and have been admitted for more than 3 days,
Able to communicate verbally,
Having no hearing or visual impairments,
Citizens of the Republic of Türkiye,
Willing to participate in the study.
Exclusion criteria
Having a diagnosed psychiatric disorder,
Inability to speak Turkish.
Primary purpose
Allocation
Interventional model
Masking
68 participants in 2 patient groups
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Central trial contact
Nurcan KIRCA, Doç. Dr.; Feyzanur GÜLÇELİK, Specialist Nurse
Data sourced from clinicaltrials.gov
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