A New Method in Psychopathology Research: Network Analysis

Abstract

Though network analysis has a long history in both natural and social sciences it has emerged as a new method in psychology in recent years. Unlike medical disorders, mental disorders are not observable in laboratory. However, we can identify them by the way of observable symptoms. According to the network perspective, a disorder occurs when an external event triggers a psychological symptom. Activated symptom also interacts with other symptoms and forms a pattern of symptoms. Network approach criticizes traditional categorical diagnostic approach and focuses on symptom organization. Probably, treating the most effective symptom will accelerate recovery process and provide more effective treatment. Network analysis can be used in both cross-sectional and longitudinal studies. Psychological networks provide opportunities to investigate direction of the relationship among symptoms, comorbidity, external triggers of psychological symptoms, effectiveness of treatment, comparison of symptom pattern according to sample characteristics. Despite the utility of psychological networks, accuracy of them has been questioned and certain methods to prove accuracy of networks proposed as response. Technological progress in recent years enabled network analysis to be more eligible in psychology. R Statistics software is very useful in network analysis which is totally free and open sourced and supported by many additional packages. This review article aims is to provide information about usage of network analysis in psychology, especially in clinical research. In the first part historical and theoretical background of network analysis was introduced and in the following parts structure, validity of psychological networks and R Statistics Software which is used for conducting network analysis were explained briefly.

Keywords

• network analysis
• psychological networks
• partial correlation networks
• bayesian networks
• r statistics