Thread by @NC_Jacobson

Join me tomorrow at #TIPS2022 for a discussion of Time-Varying Network Dynamics of Major Depressive Disorder

#NetworkScience

Preprint:
psyarxiv.com/pf4kc/

A 🧵for those who can't make it

1/19

Preview: as a field we're making a lot of assumptions that probably aren't right and are kind of a big deal.

2/19

1st assumption:

Specifically:
Changes in MDD are gradual
Symptoms occur "most of the day nearly every day" in major depressive episodes

3/19

Here's what MDD symptoms can actually look like in persons who meet criteria for MDD.

75% of the variation in symptoms occurs within days rather than across days or weeks.

❌Assumption 1 is wrong

MDD symptoms don't change slowly - they change quickly

4/19

2nd Assumption: MDD is a monolithic entity

Only symptom severity matters, the symptoms themselves are interchangeable

5/19

Rather than being some top-down latent process,

When you investigate it MDD symptoms they predict one another over time & do so differently for different people

❌Assumption 2 is wrong

MDD symptoms can function as a network, predicting one another, w/ heterogeneity

6/19

Assumption 3: The MDD network dynamics don't change

The relationships between MDD symptoms are fixed (i.e. anhedonia always has a positive linear relationship to later concentration difficulties for this person)

7/19

So based on prior work, we don't know much about whether MDD symptom dynamics evolve or change across time.

Let's dive in.

8/19

The data from this study were collected as part of an R01, where participants (N = 105 so far) completed measures of their depression sxs 270 times (3x per day for 90 days)

We'll focus on a few participants to dive in detail.

9/19

We ran person-specific (i.e. N = 1) time-varying vector autoregressive models using generalized additive models.

Each change in PHQ symptom is used to predict the changes in each PHQ symptom at the next measurement occasion, & relationships can change over time

10/19

Let's look at the symptom network of participant 1

The symptom changes pretty dramatically over time - concentration goes from having virtually no influence to the most influential in the network

11/19

Participant 2's network is pretty stable for a while until motor symptoms go from essentially carrying no influence to being the most influential symptom in the network

12/19

Participant 3 experiences big changes in how much motor issues influence other MDD symptoms.

13/19

Okay, but what about the whole sample?

86% of participants had their most influential symptom change

ALSO:
*MOST* participants had their most influential symptom change to their least influential symptom at some point in the study.

14/19

So what does this mean for our assumption 3?

It's also wrong ❌

Most people experience dramatic changes in MDD symptom networks across time

15/19

What are the implications of all of this?

MDD is a person-specific and everchanging symptom

This has big implications towards treatments if we try to target these influential symptoms.

16/19

Changes in MDD symptom dynamics change so drastically and so rapidly that targeting central MDD symptoms may be like playing a game of Whac-A-Mole.

The only way to win is to be adapt quickly.

17/19

Probably the only way to meet these rapid symptom network changes is using digital interventions -- traditional interventions are just too slow.

18/19

Thanks to our participants, everyone on the team that has led this work, and all who have inspired this work, including @bringmann_laura, @EikoFried, @aaronjfisher, @BorsboomDenny, & @SachaEpskamp.

19/19