# Mapping Insight Dimensions and Symptom Dynamics in Schizophrenia: A Data-Driven Network Approach: Cartographie des dimensions d’insight et de la dynamique symptomatique dans la schizophrénie: une approche par réseau fondée sur les données

## TL;DR

This study explores how awareness of illness and treatment relates to symptoms in schizophrenia, finding that anxiety and depression are key influencers.

## Contribution

The study introduces a data-driven network approach to map insight dimensions and symptom dynamics in schizophrenia.

## Key findings

- Greater illness awareness is linked to higher depressive symptoms.
- Anxiety and depression are the most central and influential variables in the symptom network.
- Awareness of the need for treatment is more central than illness awareness in influencing symptom dynamics.

## Abstract

Patients with schizophrenia spectrum disorders (SSD) present with cognitive, behavioral, and emotional difficulties. Affected individuals often exhibit poor insight into aspects of their illness, such as awareness of the illness itself or the need for treatment, which can hinder treatment adherence and complicate clinical outcomes. This study aimed to investigate the relationships between clinical symptoms and dimensions of insight in SSD using a network approach, which captures direct and indirect relationships among variables. We hypothesized that illness awareness would correlate negatively with positive symptoms and positively with depressive symptoms, and that positive symptoms would have the strongest influence on the network.

Data were collected from 142 individuals diagnosed with SSD. Insight was measured using the Birchwood Insight Scale (IS) across three dimensions: illness awareness, symptom re-labelling, and awareness of the need for treatment. Symptoms were evaluated using the Scale for the Assessment of Positive Symptoms, the Scale for the Assessment of Negative Symptoms, the Calgary Depression Scale and the Hamilton Anxiety Scale. Network analysis was employed to explore interconnections (edges) between variables (nodes) and identify influential variables through centrality measures (strength, betweenness, closeness).

A significant positive connection was found between illness awareness and depressive symptoms. Anxiety and depressive symptoms were identified as the most central and influential variables within the network. Treatment awareness showed greater centrality than illness awareness, indicating this dimension's potential importance in influencing symptom dynamics in a clinical profile.

Analyzing a more extensive network that includes treatment adherence and cognitive domains affected in SSD could enhance and validate the understanding of the cascading effects of symptoms and insight dimensions, allowing for more tailored treatments.

Interconnections between levels of awareness and clinical symptoms in schizophrenia and related disorders

Plain Language Summary

Schizophrenia is a complex mental illness that affect thinking, emotions, and behaviors. Many individuals with schizophrenia struggle to recognize that they are ill or their need for treatment, which complicates adherence to treatment plans. This study aimed to explore how different symptom domains of schizophrenia are connected to aspects of a person's insight into their illness.

Data was collected from 142 people diagnosed with schizophrenia spectrum disorders. Insight was measured using the Birchwood Insight Scale, which assesses three key dimensions: how aware people are of their illness, how they label or recognize their symptoms, and how aware they are of the need for treatment. Symptom domains in schizophrenia, including positive symptoms (e.g., delusions, hallucinations), negative symptoms (e.g., affect flattening, alogia), depression, and anxiety, were assessed. A network analysis analyzed the relationships between insight dimensions, symptom domains, and subdomains. In this approach, each variable is represented as a “node” in a network, and its connections are shown as “edges.” The strength of these connections can reveal which variables are most important in influencing others.

Greater awareness of one's illness was linked to greater depressive symptoms. Anxiety and depression emerged as the most influential symptoms in the network, meaning they had strong connections with other symptoms. Awareness of the need for treatment was the most influential insight dimension within the network, suggesting that understanding the need for treatment may play an essential role in managing symptoms. A larger sample, including other clinical outcome variables within the network, such as treatment adherence and functioning, could provide a better understanding of how symptoms interact and lead to various clinical outcomes.