Previous studies have shown that more than 30%-50% of people with cancer, chronic non-communicable diseases, infectious diseases, or mental disorders had an average of seven or more psychological and somatic symptoms at the same time. These symptoms may take a toll on e.g. PLWH (persons living with HIV), leading to low levels of medication adherence and poor quality of life. Consequently, multimorbidity (co-existence of two or more chronic conditions, including physical communicable/non-communicable diseases and mental health conditions) is a growing public health challenge.
However, there is a dearth of evidence on how psychological and somatic symptoms interacted with each other and how those relationships change over time. The complexity of treating people with multiple co-occurrence symptoms is especially high as it involves uncertainty in relationships among multiple symptoms. In addition, symptom phenotype is rarely the result of one single disease or an abnormality in a single effector gene product, but rather represents a complex network of pathobiological processes.
In recent years, owing to the appearance of a new paradigm of data-intensive medicine, new inferencing techniques (such as regular lattices, metapopulation model, small-world networks, and temporal networks) focusing on the interconnectedness of symptoms are becoming popular. Based on complex network theory, mapping symptom networks among co-occurrence of psychological and somatic symptoms enables us to visualize and explore internal network structures of disease phenotypes, which in turn, may help researchers not only to identify the interactions between symptoms but also lead to the development of more precise and individualized interventions.
This Research Topic aims to provide a platform for the research community to disseminate the most promising breakthroughs. Colleagues are invited to make contributions in the area of network science and symptom network to provide new evidence for understanding the interactions among co-occurrence of psychological and somatic symptoms.
We would like submissions of original research, systematic review, review, mini review, policy and practice, reviews, hypothesis and theory, perspective, clinical trial, and conceptual analysis in the following subtopics, but are not limited to:
• Building and analysing symptom networks based on clinical real-world data (e.g. symptoms, diseases, and phenotypic data);
• Provision and optimization of complex treatments and care based on symptom networks;
• New experiments and longitudinal study that provide mechanism analysis based on symptom networks;
• Statistical models and tools for mapping symptom networks among co-occurrence of psychological and somatic symptoms;
• Systematic reviews of recent breakthroughs in symptom networks.
Previous studies have shown that more than 30%-50% of people with cancer, chronic non-communicable diseases, infectious diseases, or mental disorders had an average of seven or more psychological and somatic symptoms at the same time. These symptoms may take a toll on e.g. PLWH (persons living with HIV), leading to low levels of medication adherence and poor quality of life. Consequently, multimorbidity (co-existence of two or more chronic conditions, including physical communicable/non-communicable diseases and mental health conditions) is a growing public health challenge.
However, there is a dearth of evidence on how psychological and somatic symptoms interacted with each other and how those relationships change over time. The complexity of treating people with multiple co-occurrence symptoms is especially high as it involves uncertainty in relationships among multiple symptoms. In addition, symptom phenotype is rarely the result of one single disease or an abnormality in a single effector gene product, but rather represents a complex network of pathobiological processes.
In recent years, owing to the appearance of a new paradigm of data-intensive medicine, new inferencing techniques (such as regular lattices, metapopulation model, small-world networks, and temporal networks) focusing on the interconnectedness of symptoms are becoming popular. Based on complex network theory, mapping symptom networks among co-occurrence of psychological and somatic symptoms enables us to visualize and explore internal network structures of disease phenotypes, which in turn, may help researchers not only to identify the interactions between symptoms but also lead to the development of more precise and individualized interventions.
This Research Topic aims to provide a platform for the research community to disseminate the most promising breakthroughs. Colleagues are invited to make contributions in the area of network science and symptom network to provide new evidence for understanding the interactions among co-occurrence of psychological and somatic symptoms.
We would like submissions of original research, systematic review, review, mini review, policy and practice, reviews, hypothesis and theory, perspective, clinical trial, and conceptual analysis in the following subtopics, but are not limited to:
• Building and analysing symptom networks based on clinical real-world data (e.g. symptoms, diseases, and phenotypic data);
• Provision and optimization of complex treatments and care based on symptom networks;
• New experiments and longitudinal study that provide mechanism analysis based on symptom networks;
• Statistical models and tools for mapping symptom networks among co-occurrence of psychological and somatic symptoms;
• Systematic reviews of recent breakthroughs in symptom networks.