Development of a mobile monitoring program for anxiety and depression in pregnancy and evaluation of 3-month results.

Background: The aims of this study were to develop a mobile mental health application (app) to scan the symptoms of anxiety, depression, and related factors during pregnancy; examine the effect of the app on pregnant women; and determine the factors related to using such an app.

Methods: A software platform called Perinatal Anxiety Depression Monitoring Platform (PADIP) was developed. This study included 320 pregnant women: 160 in the PADIP group and 160 in the control group.

The Impact of the COVID-19 Pandemic on the Interest in Antidepressants: An Analysis of Worldwide Internet Searches With Google Trends Data.

Objective: It is known that in the digital age we live in, people try to get information on many medical issues through Internet searches. Especially as a result of the COVID-19 pandemic triggering mental problems and health professionals' stay-at-home warnings, it has become difficult for individuals to receive psychiatric help, and this has encouraged accessing information about mental problems and their treatments through Internet searches. In this context, infodemiologic research, especially with Google Trends (GT; Google LLC, Mountain View, California, United States), has become very popular in recent years.

Detection of depression and anxiety in the perinatal period using Marine Predators Algorithm and kNN.

Undiagnosed prenatal anxiety and depression have the potential to worsen and have an adverse effect on both the mother and the infant. Although the diagnosis is made by specialist doctors, it is unclear which parameters are more effective. Especially in medicine, it is crucial to diagnose disease with high accuracy.