The Effect of Artificial Intelligence Supported and Nurse-Led Online Breastfeeding Counseling

Официальное название

The Effect of Artificial Intelligence Supported and Nurse-Led Online Breastfeeding Counseling on Mothers' Breastfeeding Competence: A Randomized Controlled Study

Обзор

Breastfeeding is the gold standard in infant nutrition in the first 12 months of life (1). Breastfeeding self-efficacy perception is one of the most important factors affecting mothers\' breastfeeding duration and success in the postpartum period (2,3).Although AI has traditionally been the domain of powerful mainframes and data centers, new approaches have the capacity to put the power of AI directly into the hands of patients (4).Therefore, considering the importance of breastfeeding education and counseling, this study will determine the effect of training and use of a mobile application-supported artificial intelligence tool and nurse-led online breastfeeding counseling on mothers; breastfeeding self-efficacy perception, breastfeeding success, infant feeding attitude and postpartum depression levels. Thus, the effectiveness of the artificial intelligence tool and nurse-led breastfeeding counseling will be compared.

Подробное описание

Breastfeeding positively affects mother-infant bonding (5). Breast milk is the healthiest food source for the nutrition and development of the newborn (6). Mortality and morbidity rates from infectious diseases are lower in breastfed babies (4). It is stated that breastfeeding provides protection against postpartum bleeding, postpartum depression, ovarian and breast cancer, heart disease and type 2 diabetes (3). The rate of exclusive breastfeeding in the first 6 months in the world is 43% (2). Although breastfeeding is a common practice in Turkey, the rate of babies exclusively breastfed is 45% in the first three months, 4-5. 6-8% to 14% per month. It was determined that it decreased to 4% per month (7).

Continuing breastfeeding effectively and breastfeeding success strengthens the bond between mother and baby (4). Breastfeeding self-efficacy is associated with positive breastfeeding outcomes (5). However, it has been determined that there is a positive relationship between breastfeeding self-efficacy and breastfeeding success (8). In a study conducted with mothers whose babies were followed in the neonatal intensive care unit, it was determined that there was a positive relationship between the mothers; breastfeeding success and breastfeeding self-efficacy (Y5).

Studies have determined that mothers; attitudes towards breastfeeding their babies have a significant impact on their baby's feeding behavior (5-7). When mothers develop a positive attitude towards infant nutrition, the time to start breastfeeding and the transition to breastfeeding and complementary feeding can be positively affected (6-8). However, mothers; attitudes towards breastfeeding are affected by the mothers; mood. In a study, it was determined that there was a relationship between the mother's mood and breastfeeding attitude (8). In a different study, it was found that there was a negative relationship between the mother's anxiety level and breastfeeding success (5). However, postpartum depression can occur in the postpartum period (4). Mothers with depressive symptoms experience more anxiety about breastfeeding their babies (8). It has been reported that mothers who are stressed and anxious about taking care of the baby also worry about breastfeeding, and the breastfeeding rate is lower in these mothers (8). While the mother's inability to breastfeed her baby may be a risk factor for depression, the mother may stop breastfeeding depending on the development of depression (6-8).

Nowadays, the use of artificial intelligence has become inevitable to improve the quality of nursing care (8-10). Chat-Generative Pre-Trained Transformer (Chat-GPT) (9), a system developed by Open AI (AI), extracts a wealth of information from a variety of online sources, including books, articles, and websites, and through human-like feedback It improves text creation abilities (7). It uses deep learning, which simulates human learning, to produce human-like answers to questions. Deep learning refers to the use of multiple layers of filters, each of which provides an output score that serves as input for the next layer (9). Providing education to health professionals, especially nurses, on health-related issues, including breastfeeding, is an important part of nurses; professional roes (9).

The aim of this study is to determine the effect of artificial intelligence-supported and nurse-led online breastfeeding counseling on mothers; breastfeeding competencies.

Вмешательства

• Другое 1) Artificial intelligence supported working group
  Pregnant women will be a personal information form, breastfeeding diagnosis and evaluation scale, postnatal breastfeeding self-efficacy scale, Lowa infant nutrition attitude scale and Edinburgh postpartum depression scale. Pregnant women in the artificial intelligence-supported study group were aged 32-37. Starting from the first week of pregnancy, a mobile breastfeeding consultancy application supported by IOS and Android will be installed on smart phones. Pregnant women will be expected to use
• Другое Online breastfeeding counseling group led by a nurse
  The forms that will be applied to pregnant women in all three groups at the first meeting will also be applied to this group. 32-37 in the nurse-led online breastfeeding counseling group. Primiparous pregnant women at the gestational age will be offered 1.5 hours of breastfeeding counseling by one of the researchers, between the 32nd and 37th weeks of pregnancy, with the participation of small groups of five pregnant women in each interactive session. Pregnant women in this group will receive on

Первичные конечные точки

• mothers' breastfeeding self-efficacy perception [Срок оценки: Measurements will be completed by 12 months]

Вторичные конечные точки (1)

• mothers' breastfeeding success [Срок оценки: Measurements will be completed by 12 months]

Критерии участия

Критерии включения

• The pregnant woman is willing to participate in the research,
• The pregnant woman must have an informed written voluntary consent form,
• The pregnant woman is over 18 years of age,
• The pregnant woman speaks and understands Turkish,
• Having the pregnant woman\'s first baby (primiparous),
• The pregnant woman is planning to give birth in the hospital where she came for pregnancy check-up,
• The pregnant woman must have received breastfeeding training at the family health center to which she is affiliated.
• The baby does not have a disease that would prevent sucking (cleft palate, cleft lip, etc.),
• The baby is born older than the 37th week of pregnancy,
• The baby\'s birth weight is 2500 g and above, and the APGAR score is 7 and above at the 5th minute.

Критерии исключения

• The pregnant woman has mental retardation that affects her ability to understand and comprehend,
• Multiple pregnancy,
• The pregnant woman has gestational disorders such as preeclampsia, eclampsia and a history of gestational diabetes,
• The pregnant woman has a diagnosed psychiatric disorder,
• The pregnant woman receives support from a private breastfeeding consultant,
• Taking the baby to the neonatal intensive care unit after birth,
• The baby is born before the 37th week of pregnancy,
• Loss of communication with pregnant women who were contacted before birth, after birth,
• Pregnant women who do not use smartphones,
• Pregnant women who have an application installed on their phones but have never used the application until the birth,
• Pregnant women who were given an educational booklet but did not look at the booklet until the birth,
• Pregnant women who do not attend the 1.5-hour training or who have to leave the training halfway will be excluded.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Последовательный дизайн

Маскирование

Простое слепое

Основная цель

Поддерживающая терапия

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Идентификаторы

NCT: NCT06569017 · 17993095

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗