In Medical journal of the Islamic Republic of Iran
Background: Bipolar disorder is considered a psychiatric disease without any effective screening questionnaire to monitor and manage Iranian patients. This study aims to implement a researcher-made questionnaire in the form of educational interactive software for better management of patients with bipolar disorder and prevent further complications. Methods: The present cross-sectional study evaluated the efficacy of psychoeducational-interactive-therapeutic software for patients with bipolar disorder, which is a network-based software providing a researcher-made questionnaire in a planned manner. This software can predict the occurrence of future bipolar episodes for each patient by using artificial intelligence algorithms after the occurrence of two mood episodes as the training phase. The patients with bipolar disorder were asked to use the software for a year and their mood episodes were compared before and after using the software. We evaluate the reliability of the questionnaires in the software with internal consistency using alpha Cronbach test and test-retest analysis. Face validity and content validity were also evaluated. Results: The content validity index of the instrument was 93%, and the Cronbach's alpha coefficient of the whole questionnaire was 0.955. Also, the ICC coefficient for this questionnaire is above 0.70, and the correlation coefficient of the answers in all constructs of the questionnaire is more than 0.8. Thirty male patients with bipolar disorder who experienced four episodes of mood swings per year experienced an average of 2 mood episodes per year following the use of this software. Conclusion: Our Psychoeducational-interactive-therapeutic software is the first Persian language software based on artificial intelligence to monitor clinical symptoms in patients with bipolar disorder, which uses a standard questionnaire to predict the incidence of episodes of depression and mania in these patients.
Akbarzadeh Farzad, Ebrahimi Alireza, Akhlaghi Saeid, Rajai Zahra, Rezaei Kalat Afsaneh, Jafarzadeh Esfehani Reza, Garmehi Sima, Sangsefidy Zahra
2022
Artificial intelligence, Bipolar disorder, Educational software, Interactive software
