L. Boschloo, Netherlands

VU University Department of Clinical, Neuro and Developmental Psychology

Presenter Of 2 Presentations

LIVE - Symposium: Network Analysis for Personalisation of Treatment: Understanding Links Among Symptoms, Risk Factors and Functioning (ID 639) No Topic Needed
LIVE - Symposium: Network Analysis for Personalisation of Treatment: Understanding Links Among Symptoms, Risk Factors and Functioning (ID 639) No Topic Needed

S0170 - Symptom-specific Assessment of Treatment Efficacy: The Potential of Network Estimation Techniques

Session Icon
Live
Date
Tue, 13.04.2021
Session Time
17:30 - 19:00
Room
Channel 1
Lecture Time
17:47 - 18:04

ABSTRACT

Abstract Body

Introduction

Most studies on the efficacy of psychiatric treatments consider overall scale scores as outcome measures. A focus on individual symptoms would, however, result in a more precise assessment of treatment efficacy and has potential in improving our understanding of the working mechanisms of treatment. Such an approach may also help in improving the identification of patients who are -based on their pretreatment symptomatology- the most likely to benefit from a particular treatment.

Objectives

To show the potential of network estimation techniques in a) unraveling the diverse symptom-specific responses to various depression treatments and b) improving the identification of patients who are the most likely to benefit from these treatments.

Methods

First, we combined patient-level data of multiple trials considering various depression treatments, such as antidepressant medication and (internet-based) cognitive-behavioral therapy. Network estimation techniques were used to determine the complex patterns in which symptom-specific responses to treatment were related.

Results

Individual clinical symptoms differed substantially in their responses to treatment and these symptom-specific responses were related in a complex manner. Patients suffering from symptoms that were directly affected by a particular treatment were -by definition- the most likely to benefit from that treatment.

Conclusions

Network estimation techniques were able to unravel the diverse symptom-specific responses to treatment and could help in improving our understanding of the chain of events leading to a clinical response. Information from the networks could also help in improving the identification of patients who were the most likely to benefit from a particular treatment.

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