Efficacy of Structured Teaching Programme on Knowledge Regarding Endometrial Cancer and its Prevention among Middle Adulthood Women: A Research Protocol

Introduction: Globally, the incidence of Endometrial Cancer (EC) is increasing, making it one of the most prevalent gynaecological cancers in high‑income countries. Organising EC prevention and awareness programs in a timely manner is crucial, particularly in developing nations where awareness is urgently needed. Early detection is a key factor in reducing cancer mortality. Healthcare professionals have a duty to educate the public about EC and how to prevent it. Need of the study: There is currently no established method for preventing EC. However, several studies indicate that overweight and obesity pose substantial risk factors for EC. Other risk factors include weight fluctuations and weight gain in middle age. It is critical to reduce weight and maintain a healthy weight. Raising awareness among community members is therefore crucial. Aim: To evaluate the impact of a structured education program on middle‑aged women’s understanding of EC and how to prevent it. Materials and Methods: The study will use a one‑group, quasi‑experimental pretest-post‑test design and will take place at the AVBR Hospital’s OPD in the Gynaecology department, Sawangi (Meghe), Wardha, Maharashtra, India. The duration of the study will be April 2025 to September 2025. Women who visit the OPD between the ages of 40 and 65 years will be invited to participate. Informed consent will be obtained from each participant. A quantitative method will be used to assess how well the structured teaching program affects women’s knowledge of EC and its prevention. Fifty women will participate, and a structured questionnaire will be used to collect data. Section I (demographic data) will include: age, marital status, weight, height, age at menarche, age at menopause and family history of cancer. Section II will comprise an organised survey regarding EC and its prevention. Data will be organised and analysed using descriptive and inferential statistics. For statistical analysis, data will be coded and entered into an Excel spreadsheet. Descriptive statistics will summarise demographic variables using frequency, mean, standard deviation and percentages. To assess the significance of the difference in knowledge scores between the pre- and post-tests, a paired t‑test will be used. To investigate the association between knowledge levels and demographic factors, the Chi‑square test will be applied.