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    Öğe
    Assessing Artificial Intelligence-Generated Patient Educational Material on Gestational Diabetes Mellitus Content and Quality Evaluation
    (Lippincott Williams & Wilkins, 2025) Aypar Akbag, Nuran Nur
    Purpose: This study aims to evaluate the content and quality of patient educational materials on gestational diabetes mellitus (GDM) generated by ChatGPT and Gemini. Background: The sources of knowledge are crucial in the effective management of disease. Artificial intelligence (AI) platforms could become a primary source of patient education materials in the near future. Methods: A descriptive research design was employed. Frequently asked questions related to GDM were extracted from patient education sections of existing guidelines. These questions were then submitted to both ChatGPT and Gemini. The responses provided by these platforms were used to create educational material aimed at pregnant women diagnosed with GDM. The content was reviewed by a panel of 11 experts. The Patient Education Materials Assessment Tool for Printed Materials (PEMAT-P) was employed to evaluate the content's effectiveness and clarity, and the readability was assessed through the Ate & scedil;man Readability Formula and the Gunning Fog Index. Results: A total of 32 questions regarding GDM were directed to the AI platforms. The resulting educational materials had a readability score of 77.8 based on the Ate & scedil;man scale and 16.25 according to the Gunning Fog Index. The experts rated the material as highly comprehensible, with an average PEMAT-P understandability score of 91.36% (range: 86.66%-93.75%) and an actionability score of 89.67% (range: 80%-100%). Conclusion: The GDM educational materials generated by ChatGPT and Gemini exhibit a high level of readability, making them easy to understand. Moreover, the material was deemed comprehensible and actionable for pregnant women with GDM. Implications for practice and research: Although AI-generated patient educational materials show great potential, further experimental research is necessary to assess their long-term effectiveness.
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    Öğe
    The relationship between fear of childbirth and birth self-efficacy in low and high-risk pregnant women
    (Bmc, 2025) Cicek, Ozlem; Aypar Akbag, Nuran Nur; Durmazoglu, Gamze; Ozturk, Cigdem
    BackgroundFear of childbirth (FOC) is the most important feeling pregnant women experience about childbirth. It is also known that the fear of childbirth is affected by many factors. This study investigated the relationship between Fear of childbirth (FOC) and childbirth self-efficacy in low and high-risk pregnant women.MethodsThe research was designed in descriptive and correlational type. This study among 115 low-risk and 135 high-risk pregnant women who were recorded using a purposeful sampling.ResultsThe total W-DEQ-A values of high-risk pregnant women are substantially higher. It was determined that both groups had a moderate FOC. The W-DEQ-A and CBSEI-32 mean scores of low-risk pregnant women were significantly related. Their mean W-DEQ-A scores were negatively correlated with outcome expectancy sub-dimension (OE) scores and positively correlated with self-efficacy expectancy sub-dimension (EE) values.ConclusionThis is the first study to examine the relationship between FOC and childbirth self-efficacy in low and high-risk pregnant women. It is recommended that health professionals evaluate all pregnant women in terms of FOC and their childbirth self-efficacy for vaginal delivery.