PUI Cognitive Determinants - Lisbon Addictions

PUI Cognitive DeterminantsDr Konstantinos Ioannidis

MD, MSc, MRCPsych

Cambridge and Peterborough NHS Foundation Trust UK, S3 Eating Disorders and

University of Cambridge, Department of Psychiatry, Cambridge, United Kingdom.

Cognitive Determinants

Assessment challenges

Relations to Clinical course

In brief

Determinants of problematic internet use

I

Determinants

Ex

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g P

UI'

s D

ete

rmin

ants

, Ass

ess

me

nt

and

Clin

ical

Co

urs

e-E

PA

War

saw

20

19

Biological (systemic) level

Neurobiological level

Cognitive level

Behavioral level

Psychosocial level

Clinical level

Cortisol

DHEA

Immune Cells

IL-6

Family Support

FriendshipsIntimate

relationships

Adrenal glands

PFC

Amygdala

Hippocampus

Pituitary

Hypothalamus

BR

AIN

STR

UC

TUR

E &

FU

NC

TIO

NEN

VIR

ON

MEN

TAL

SUP

PO

RT

INFL

AM

MA

TIO

N

HO

RM

ON

AL

STR

ESS

RES

PO

NSE

GEN

ES 5-HTTLPR FKBP5 BDNF NPY MAOA

Co

rtis

ol i

mp

acts

on

PFC

an

d li

mb

icb

rain

; DH

EA m

ay b

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rote

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ACTH

TNF-a

Cortisol suppressesInflammatory response

Pro

-in

flam

mat

ory

cyt

oki

nes

imp

act

on

th

e a

myg

da

la a

nd

PFC

‘L/L’ × ‘Met’ × ‘T’ etc

COST Action Priorities

-> 1. To achieve a reliable consensus-driven conceptualization of different forms of PUI

(phenomenologies, co-morbidities, brain-based mechanisms)

The neuroscience research of those disorders of repetitive urge-driven behaviours, supportsa complex neuropsychological model indicatingimpaired ‘top-down’ cortical behavioural control, which is underpinned by abnormal activationin specific components of brain circuitry which encodesaffective, cognitive and motor control of instrumental behaviour

DETERMINANTS OF PUI

Fineberg et al; European Neuropsychopharmacology; 2018;1232-1246

Problematic usage of the internet

Internet Gaming Disorder

Online Gambling

Overuse of social/streaming

media

Excessive use of pornography

Excessive online buying

Cyberchondria

Cyberbullying

Cognitive determinants of PIU – LISBON ADDICTIONS 2019



Online Gambling

Overuse of social/streaming

media

Excessive use of pornography

Excessive online buying

Cyberchondria

Cyberbullying

Internet activity

All (n = 1749) 18 ≤ Age ≤ 25 (n = 1042)

26 ≤ Age ≤ 55 (n = 592)

Age > 55 (n = 115)

General surfing 2.100 2.400 1.500 0.590

Internet gaming

0.600 0.450 0.110 0.000

MMORPG 0.000 0.000 0.710 0.000

Time wasters 0.000 0.000 0.000 0.450

Action multiplayer

0.000 0.000 0.000 0.000

Shopping 1.400 0.840 1.500 0.000

Auction websites

0.027 0.000 0.990 0.230

Gambling 0.000 0.000 0.780 0.000

Sports 0.000 0.000 0.000 0.000

Pornography 1.000 1.400 0.210 0.000

Instant Messaging

0.000 0.000 0.110 0.000

Social networking

0.460 0.000 1.300 0.000

Streaming media

0.000 0.000 0.000 1.200

Ioannidis et al; Addict Behav. 2018 Jun; 81: 157–166.



Obsessive Compulsive and

Related Disorders

Behavioral Addiction

Impulse Control Disorders

Compulsivity - Impulsivity




Ioannidis K et al; J Psychiatr Res. 2016 Dec;


Latent traits of impulsivity and compulsivity

Chamberlain et al; Psychol Med. 2018 Apr;48(5):810-821


Personality traits

Low self directedness(Montag et al 2010)

ImpulsivityIoannidis et al 2016

Chamberlain et al 2017)

CompulsivityIoannidis et al 2016 Chamberlain et al

2017)

Neurotiscism

(Montag et al 2010)


Goldstein and Volkow; Nat Rev Neurosci. 2011 Oct 20;12(11):652-69

Everitt and Robbins; Nat Neurosci. 2005 Nov;8(11):1481-9

Bechara; Nat Neurosci. 2005 Nov;8(11):1458-63. Addictive substances can trigger bottom-up, involuntary signalsoriginating from the amygdala that modulate, bias or even hijack the goal-driven cognitive resources that are needed for the normal operation of the reflective system


Theory:Person-Affect-Cognition-Execution (I-PACE) model

Reductions in executive functioning and inhibitory controlcontribute to engagement in online behaviours,leading to gratification, and ultimately contributingto the emergence and persistence of an internet-use disorder

Brand M et al; Neurosci Biobehav Rev. 2016;71:252–66.



Behavioral AddictionObsessive Compulsive and Related Disorders

Impulse Control Disorders

Deficits in: Motor inhibitionAttentional inhibitionDecision making(…)

Deficits in: Visual memoryVerbal memoryExecutive functionProcessing speed(…)

Deficits in: Cognitive flexibilityExecutive functionDecision makingCortical inhibition(…)

Compulsivity - Impulsivity


SCR

EEN

ING

TITLE CHECKn = 138

Insufficient data from paper/no response from authors

n =12

Out of scopen = 11

Not enough studies in domain examined

n = 25

FULL

TEX

TS

ASS

ESSE

D F

OR

EL

IGIB

ILIT

Y

SUB

GR

OU

P

AN

ALY

SES

PUBMED SEARCHn = 2908

ABSTRACT CHECKn = 77

Irrelevant titlen = 2770

Irrelevant abstractn = 61

FULL TEXT CHECKn = 90

Further papers identified by manual search of references

n = 13

FINAL SETn = 40

SSRTn = 5

STROOPn = 16

DECISION MAKING

n = 7

GO/NO-GOn = 14

DISCOUNTING

n = 4

WORKING MEMORY

n = 4

Removal of duplicates n =2

GO/NO-GO TASK 0.51 (0.26-0.75)

STOP-SIGNAL TASK 0.42 (0.17-0.66)

Summary of forest plots for various cognitive domains of problematic internet use participants versus controls; effect sizes are Hedge’s g; positive values indicate PIU performed worse than controls

STROOP ATTENTIONAL INHIBITION 0.53 (0.19-0.87)

DECISION MAKING 0.49 (0.29-0.70)

WORKING MEMORY 0.51 (0.20-0.82)

0 0.2 0.4 0.6 0.8-0.2-0.4-0.6


Tasks excluded

Internet game

shifting

Dot probe

Internet GNG

Emotional STROOP

Internet STROOP

Directed Forgetting

Stroop Match-to-

Sample Risk task

Auditory Odd ball

Implicit Association

task

Sustained attention

Verbal Fluency

Cups Task

Flanker Task


Meta-analysis funnels plots by cognitive domain; ‘z’ and ‘p’ values reported from Regression Test for Funnel Plot Asymmetry (mixed-effects meta-regression model).Evidence of publication bias identified in the domains of Discounting and working memory. Trim and fill method was used although effect size changed only for workingmemory (as indicated by the blue dotted line [non-corrected effect size 0.51])


Moderation analysis

Age, gender, presence of co-morbidities, whether or not gaming was the predominant online activity, and geographical area were not significant moderating factors in any of the cognitive domains examined (all p>0.05 non-corrected).

Quality of study was a significant moderating variable in SST (p = 0.032) with all higher quality studies reporting smaller and non-statistically significant effects


Cognition in PUI –meta-analysis

This is the first study to amass all available information from case-control studies of cognitiveperformance in people with problematic internet use

PUI was associated with significant cognitive deficits in: attentional inhibition motor inhibition decision-making and working memory

supporting recent conceptualizations of PUI that implicate cognitive dysfunctionin its pathophysiology

Ioannidis et al; Br J Psychiatry. 2019 Feb 20:1-8. doi: 10.1192/bjp.2019.3


The impact of comorbidimpulsive/compulsive disorders in PUI

PUI was associated with significant cognitive deficits in: Response inhibition decision-makingOnly those with comorbid disorders

Chamberlain et al.; J Behav Addict. 2018 Jun; 7(2): 269–275.


Discussion

These neurocognitive results support the existenceof underlying fronto-striatal dysfunction in PUI

These findings also suggest a common neurobiologicalvulnerability across PUI behaviors,including gaming.


Genetic influence in PUI

Genetic influence in PUI

Dopamine receptor gene (DRD2) (Han et al., 2007),Catecholamine-O-methyltransferase gene (COMT) (Han et al., 2007), Serotonin transporter gene (5HTTLPR/ SLC6A4) (Lee et al., 2008),Nicotine acetylcholine receptor gene (CHRNA4) (Jeong et al., 2017, Montag et al., 2012) Neurotrophic tyrosine kinase type 3 receptor gene (NTRK3) (Ki et al., 2016a).


Genetic influenceson cognition in PUIIoannidis et al.; CNS Specs


DRD2, COMT(?), 5HTTLPR/ SLC6A4, CHRNA4, NTRK3


+ Compulsivity


+ Compulsivity


Online Gambling

Overuse of

social/streaming media

Excessive use of pornogr

aphy

online

buying

Cyberchondria

Cyberbullying

Social / family influence in PUI

Familial influences may contribute to the increased or decreased likelihood of an adolescent developing problem gaming. In a review of 14 recent studies, relevant family-related variables included:

(a) parent status (e.g., socioeconomic status and mental health),(b) parent–child relationship (e.g., warmth, conflict, and abuse), (c) parental influence on gaming (e.g., supervision of gaming, modeling, and attitudes toward gaming), (d) family environment (e.g., household composition)

Schneider et al; Family factors in adolescent problematic Internet gaming: a systematic reviewJ. Behav. Addict., 6 (2017), pp. 321-333



+ Compulsivity


Online Gambling

Overuse of

social/streaming media

Excessive use of pornogr

aphy

online

buying

Cyberchondria

Cyberbullying

Assessment of problematic internet use

II

Exploring PUI's Determinants, Assessment and Clinical Course - EPA Warsaw 2019

?

Young’s internet

addiction test (Young 1998)

Chen Internet Addiction

Scale (CIAS) Chen et al.,

2003

Compulsive Internet Use Scale (CIUS) Meerkerk et

al., 2009

Computer and Internet Use

(CIU) Pratarelli,

Browne, & Johnson, 1999

Internet Addiction Scale (IAS) Nichols &

Nicki, 2004

Generalized Problematic Internet UseScale (GPIUS)Caplan, 2002

Internet Addiction

Questionnaire (IAQ) Wang, 2001

Diagnostic Criteria of Internet

Addiction(DC-IA)

Ko et al., 2005a

Problematicinternet use

Questionnaire; PIU-Q

Demetrovics, 2008


Links of cognitive findings with Clinical course of problematic internet use

III

Natural history of PUI

The 28-year-old boiler repairman suffered a cardiac arrest following a 50-hour internet gaming binge during which he neither ate nor slept.


Ho RC et al; IA and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry. 2014;14:183Carli V; Psychopathology. 2013;46(1):1-13.

alcohol abuse (OR = 3.05, 95% CI = 2.14-4.37, z = 6.12, P < 0.001),

attention deficit and hyperactivity (OR = 2.85, 95% CI = 2.15-3.77, z = 7.27, P < 0.001),

depression (OR = 2.77, 95% CI = 2.04-3.75, z = 6.55, P < 0.001)

anxiety (OR = 2.70, 95% CI = 1.46-4.97, z = 3.18, P = 0.001)

http://picayune.uclick.com/comics/ga/2017/ga171114.gifhttp://www.italoeuropeo.co.uk/2015/10/22/italian-science-in-uk/

PUI Cognitive Determinants - Lisbon Addictions

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