Networks and psychopathology: opportunities, challenges and implications

Stijn Vos, de

doi:10.33612/diss.113057096

Networks and psychopathology: opportunities, challenges and implications

Stijn Vos, de

Onderzoeksoutput

1261 Downloads (Pure)

Samenvatting

Major Depressive Disorder (MDD) is een psychische aandoening die grote gevolgen heeft voor zowel patiënten als de mensen om hen heen. Naar schatting wordt de grootste bijdrage aan de wereldwijde ziektelast in de komende decennia. MDD is moeilijk te begrijpen omdat het een zeer heterogene ziekte is: patiënten met dezelfde MDD-diagnose kunnen enorm verschillende symptoomprofielen, ziekteverloop en behandelingsrespons vertonen. Bovendien zijn er nog geen betrouwbare biologische markers voor MDD gevonden.

MDD en psychiatrische stoornissen worden in het algemeen traditioneel geanalyseerd alsof het lichamelijke ziekten zijn; d.w.z. als een latente oorzaak die leidt tot de manifestatie van depressiesymptomen. Belangrijk is dat deze symptomen worden verondersteld wederzijds onafhankelijk te zijn: het gelijktijdig optreden wordt volledig verklaard door de veronderstelde onderliggende aandoening. Het gebruik van het latente variabele model om MDD weer te geven is problematisch omdat zowel het bestaan van een enkele latente oorzaak als de onafhankelijkheid van symptomen moeilijk te rechtvaardigen zijn. Het huidige proefschrift heeft als doel het gebruik van een alternatief ziektemodel van MDD te onderzoeken: het netwerkmodel. Recent zijn netwerkmodellen in toenemende mate toegepast in psychiatrisch onderzoek en vormen een interessant alternatief voor latente variabele modellen, omdat ze geen eenvoudige latente oorzaak voor MDD aannemen en ze (in)directe relaties tussen symptomen kunnen modelleren.

Dit proefschrift onderzoekt de toepassing van netwerkmodellen in psychiatrisch onderzoek op cross-sectionele en longitudinale data. Bovendien bespreken we de sterke en zwakke punten, mogelijkheden en uitdagingen van de netwerkbenadering in psychiatrisch onderzoek.

Originele taal-2	English
Kwalificatie	Doctor of Philosophy
Toekennende instantie	Rijksuniversiteit Groningen
Begeleider(s)/adviseur	de Jonge, Peter, Supervisor Wit, Ernst, Supervisor Wardenaar, Klaas, Co-supervisor Bos, Elske, Co-supervisor
Datum van toekenning	3-feb.-2020
Plaats van publicatie	[Groningen]
Uitgever	University of Groningen
Gedrukte ISBN's	978-94-034-2369-2
Elektronische ISBN's	978-94-034-2368-5
DOI's	https://doi.org/10.33612/diss.113057096
Status	Published - 2020

Toegang tot document

10.33612/diss.113057096

Title and contentsFinal publisher's version, 677 KB
Chapter 1Final publisher's version, 781 KB
Chapter 2Final publisher's version, 1,1 MB
Chapter 3Final publisher's version, 1,22 MB
Chapter 4Final publisher's version, 1,13 MB
Chapter 5Final publisher's version, 1,29 MB
Chapter 6Final publisher's version, 1,1 MB
Chapter 7Final publisher's version, 665 KB
Chapter 8Final publisher's version, 854 KB
Complete thesisFinal publisher's version, 3,33 MB
PropositionsFinal publisher's version, 394 KB

Handle.net

Permanente koppeling

Citeer dit

@phdthesis{92c4b73e5a3a45b3885e9329918776dc,

title = "Networks and psychopathology: opportunities, challenges and implications",

abstract = "Major Depressive Disorder (MDD) is a mental illness that greatly impacts patients as well as the people around them. It is estimated to become the biggest contributor to the global burden of disease in the upcoming decades. MDD is hard to understand because it is a highly heterogeneous illness: patients with the same MDD diagnosis may display vastly different symptom profiles, illness course, and responses to treatment. Furthermore, reliable biological markers for MDD have yet to be found. MDD and psychiatric disorders, in general, have traditionally been analyzed as if they are physical illnesses; i.e. as a latent cause that leads to the manifestation of depression symptoms. Importantly, these symptoms are assumed to be mutually independent: their co-occurrence is completely explained by the assumed underlying disorder. The use of the latent variable model to represent MDD is problematic because both the existence of a single latent cause and the independence of symptoms are hard to justify. The current dissertation aims to investigate the use of an alternative disease model of MDD: the network model. Recently, network models have been increasingly applied in psychiatric research, forming an interesting alternative to latent variable models, because they do not assume a single latent cause for MDD and they can model (in)direct relationships among symptoms. This thesis considers the application of network models in mental health research on cross-sectional and longitudinal study data. Moreover, we discuss the strengths, weaknesses, possibilities, and challenges of the network approach in psychiatric research.",

author = "{Vos, de}, Stijn",

year = "2020",

doi = "10.33612/diss.113057096",

language = "English",

isbn = "978-94-034-2369-2",

publisher = "University of Groningen",

school = "University of Groningen",

}

TY - BOOK

T1 - Networks and psychopathology

T2 - opportunities, challenges and implications

AU - Vos, de, Stijn

PY - 2020

Y1 - 2020

N2 - Major Depressive Disorder (MDD) is a mental illness that greatly impacts patients as well as the people around them. It is estimated to become the biggest contributor to the global burden of disease in the upcoming decades. MDD is hard to understand because it is a highly heterogeneous illness: patients with the same MDD diagnosis may display vastly different symptom profiles, illness course, and responses to treatment. Furthermore, reliable biological markers for MDD have yet to be found. MDD and psychiatric disorders, in general, have traditionally been analyzed as if they are physical illnesses; i.e. as a latent cause that leads to the manifestation of depression symptoms. Importantly, these symptoms are assumed to be mutually independent: their co-occurrence is completely explained by the assumed underlying disorder. The use of the latent variable model to represent MDD is problematic because both the existence of a single latent cause and the independence of symptoms are hard to justify. The current dissertation aims to investigate the use of an alternative disease model of MDD: the network model. Recently, network models have been increasingly applied in psychiatric research, forming an interesting alternative to latent variable models, because they do not assume a single latent cause for MDD and they can model (in)direct relationships among symptoms. This thesis considers the application of network models in mental health research on cross-sectional and longitudinal study data. Moreover, we discuss the strengths, weaknesses, possibilities, and challenges of the network approach in psychiatric research.

AB - Major Depressive Disorder (MDD) is a mental illness that greatly impacts patients as well as the people around them. It is estimated to become the biggest contributor to the global burden of disease in the upcoming decades. MDD is hard to understand because it is a highly heterogeneous illness: patients with the same MDD diagnosis may display vastly different symptom profiles, illness course, and responses to treatment. Furthermore, reliable biological markers for MDD have yet to be found. MDD and psychiatric disorders, in general, have traditionally been analyzed as if they are physical illnesses; i.e. as a latent cause that leads to the manifestation of depression symptoms. Importantly, these symptoms are assumed to be mutually independent: their co-occurrence is completely explained by the assumed underlying disorder. The use of the latent variable model to represent MDD is problematic because both the existence of a single latent cause and the independence of symptoms are hard to justify. The current dissertation aims to investigate the use of an alternative disease model of MDD: the network model. Recently, network models have been increasingly applied in psychiatric research, forming an interesting alternative to latent variable models, because they do not assume a single latent cause for MDD and they can model (in)direct relationships among symptoms. This thesis considers the application of network models in mental health research on cross-sectional and longitudinal study data. Moreover, we discuss the strengths, weaknesses, possibilities, and challenges of the network approach in psychiatric research.

U2 - 10.33612/diss.113057096

DO - 10.33612/diss.113057096

M3 - Thesis fully internal (DIV)

SN - 978-94-034-2369-2

PB - University of Groningen

CY - [Groningen]

ER -

Networks and psychopathology: opportunities, challenges and implications

Samenvatting

Toegang tot document

Handle.net

Vingerafdruk

Citeer dit