Uterine involution, the process by which the uterus returns to its pre-pregnancy size during the postpartum period, can cause severe cramp-like pain in postpartum women. Although pharmacological methods are common for managing this pain in the literature, their side effects limit their use in this population. This project aims to fill a significant gap in the literature by combining guided imagery, a non-pharmacological technique, with evolving artificial intelligence (AI) technologies. While the effectiveness of guided imagery in cesarean and labor pain is well-known, its impact on pain and physiological parameters during uterine involution-specifically through AI-supported visualization-will be evaluated for the first time within the scope of this study. The primary research question of the project is: "Do guided imagery and AI-supported video applications have a healing effect on the pain levels and vital signs of postpartum women during the evaluation of uterine involution?" This research is a three-arm, randomized controlled experimental study to be conducted at Istanbul Atlas University Hospital. The sample size of the study was determined using the G\*Power 3.1 program. As a result of the a priori power analysis performed by selecting the "ANOVA: Fixed effects, omnibus, one-way" statistical test under the "F tests" family, the significance level was set at α = 0.05, the statistical power (1-β) at 0.80, and the effect size (f) at 0.25 (medium effect). The analysis indicated a total sample size of 159 participants for the three groups, with 53 participants required in each group. To account for potential sample attrition, a 10% addition was made to each group, resulting in a planned study with 59 participants per group and a total of 177 participants. "Guided Imagery" and "AI-Supported Video" applications will be utilized as intervention methods. In the guided imagery group, an expert-approved original audio script titled "The Emotional Journey of Mother and Baby" will be played to the women via over-ear headphones during the uterine involution assessment. In the AI-supported video group, a video generated with AI prompts based on the same script will be shown using virtual reality (VR) goggles during the assessment. This will allow for a comparative analysis of the effects of visual and auditory stimuli on pain during the uterine involution evaluation. Participants' pain levels will be measured using the VAS scale, and physiological data (pulse, blood pressure, SpO₂) will be recorded by monitoring at the 60th, 120th, and 180th seconds of the involution process. Considering the moderating effect of anxiety on pain threshold and vital signs, the 'Postpartum Specific Anxiety Scale' will be administered to all participants before the intervention. Data will be analyzed using ANOVA and Kruskal-Wallis tests in the SPSS 23 program.
Age range
18 Years
Sex
FEMALE
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Uterus involution pain
Timeframe: first one hour after birth