Distress as a bridge to suicidality in schizophrenia spectrum disorders: a network-based intervention simulation...

Area of Science:

• Psychiatry
• Computational Psychiatry
• Network Science

Background:

• Schizophrenia spectrum disorders (SSD) have a significantly increased risk of suicide.
• The precise mechanisms linking psychopathology to suicidality in SSD are not fully understood.
• Network models offer a framework to study symptom interrelations and identify intervention targets.

Purpose of the Study:

• To develop a network-based simulation framework using the Positive and Negative Syndrome Scale (PANSS) for schizophrenia.
• To identify symptom domains most associated with suicidality in SSD.
• To evaluate the impact of modulating specific symptoms on suicidal ideation.

Main Methods:

• Developed a network-based simulation framework utilizing PANSS data.
• Analyzed symptom networks to identify key symptom domains and bridge symptoms.
• Conducted simulation-based modulation of symptom domains to assess effects on suicidality.

Main Results:

• Reproduced a five-domain PANSS structure: Positive, Negative, Cognitive Impairment, Impulsive-Hostile, and Distress.
• Distress symptoms (anxiety, depression, guilt, tension) were most consistently linked to suicidality.
• Modulating the Distress domain in simulations reduced network connectivity and predicted suicidal ideation.

Conclusions:

• Affective distress is a critical symptom pathway associated with suicide risk in SSD.
• Network-informed digital simulations can aid in prioritizing symptom targets for intervention.
• Further research, including RCTs, is needed to confirm if targeting distress reduces suicidality.