European Neuropsychopharmacology (2019) 29, 76–97

www.elsevier.com/locate/euroneuro

Behavioral addictions in bipolar disorders:

A systematic review

a a, ∗∗ a a a C Varo , A Murru , E Salagre , E Jiménez , B Solé , a b ,c d ,e a L Montejo , AF Carvalho , B Stubbs , I Grande , a a , ∗ a A Martínez-Arán , E Vieta , M Reinares

a Bipolar Disorders and Depressive Unit, Hospital Clinic, Institute of Neurosciences, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain b Department of Psychiatry, University of Toronto, Toronto, ON, Canada c Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada d Physiotherapy Department, South London and Maudsley NHS Foundation Trust, Denmark Hill, London SE5 8AZ, United Kingdom e Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London, Box SE5 8AF, United Kingdom

Received 17 July 2018; received in revised form 18 September 2018; accepted 23 October 2018

KEYWORDS Abstract Bipolar disorder; Clinical and epidemiological research suggests that behavioral addictions (BA) are associated Behavioral addictions; with a wide range of psychiatric disorders. However, the relationship between BA and bipo- Comorbidity; lar disorders (BD) has not been thoroughly explored. The aim of this systematic review was Prevalence; to critically summarize and evaluate the current available evidence regarding a possible asso- Treatment ciation between BA and BD. A systematic review of major electronic databases according to PRISMA guidelines was conducted from inception to 31st December 2017. We sought quanti- tative studies data concerning prevalence of comorbidity, features and treatment related to BA-BD comorbidity. Data were narratively synthesized. Of the 1250 studies returned from the search, a total of 28 articles were included in this review. BA may be overrepresented in BD samples, and the other way around. Pathological gambling and kleptomania were the most prevalent conditions followed by compulsive buying, compulsive sexual behavior and internet addiction. BA was also associated with other mood disorders, anxiety disorders and substance use disorder. BD-BA comorbidity was related with more severe course of illness. Studies on treatment strategies for BD–BA comorbidity are rather limited; only one randomized controlled

∗ Corresponding author. E-mail addresses: [email protected] (A. Murru), [email protected] (E. Vieta). ∗∗Co-Corresponding author: Bipolar Disorders and Depressive Unit, Clinical Institute of Neurosciences, Hospital Clinic, Villarroel 170, 08036 Barcelona (Spain). https://doi.org/10.1016/j.euroneuro.2018.10.012 0924-977X/ © 2018 Elsevier B.V. and ECNP. All rights reserved. Behavioral addictions in bipolar disorders: A systematic review 77

trial that fulfilled inclusion criteria was identified. Methodological heterogeneity in terms of design and results among studies was found. BD-BA commonly co-occurs although there is a need for rigorous studies. Routine screening and adequate assessment may be helpful in BD pa- tients to identify individuals at risk for BA and to effectively manage the complex consequences associated with BA-BD comorbidity. © 2018 Elsevier B.V. and ECNP. All rights reserved.

1. Introduction addiction, tanning addiction or physical exercise addiction ( Ascher and Levounis, 2015 ) could be also considered as Bipolar disorder (BD) is a severe and chronic condition which BA. Yet, not every ICD, or impulsivity-related disorders clinical manifestations may encompass different symptom have been included within the emerging concept of BA. dimensions beyond the core expression related to alter- For example, it remains unclear whether trichotillomania, ations in mood and energy. For instance, BD patients can skin-picking disorder, pyromania or intermittent explosive present high impulsivity ( Jimenez et al., 2016 ), and in- disorder could be conceived as BA. Therefore, the current creased comorbidity with other psychiatric disorders (in- classification and diagnosis of BA are to date a matter cluding anxiety disorders, substance use disorders (SUD), of ongoing debate ( Ascher and Levounis, 2015 ) yet the attention-deficit/hyperactivity disorder and personality dis- evidence is clear that BA are associated with worse clinical orders (PD)), which can make diagnosis and management of outcomes and quality of life ( Medeiros et al., 2017 ). BD more difficult; this comorbidity is also associated with Previous clinical and epidemiological studies suggest poorer outcomes ( Grande et al., 2016; Vieta et al., 2018a ). that BA are related to a wide range of psychiatric dis- Comorbidity with SUD is associated with a worse course of orders ( Chamberlain et al., 2016; Grant et al., 2010 ). bipolar illness, as it may trigger illness onset ( Swann et al., BA has been viewed as an attempt to self-medicate or 2004 ), increase the risk of suicidal behavior ( Ostergaard et escape negative mood states ( Goldstein and Bukstein, al., 2017 ), relate to functional impairment ( Cardoso et al., 2010 ). The co-occurrence of BA-BD ( Di et al., 2010; 2015 ), poor treatment adherence ( Murru et al., 2013 ), and Sapir et al., 2013 ) could be explained through either BA a lower quality of life ( Singh et al., 2005 ). may trigger or predispose to BD or BD may predispose Over the last decade, the concept of addiction has been to BA through increased sensitivity to rewarding stimuli stretched beyond substances to include behavioral addic- or through self-treatment. Also, BA and BD could share tions (BA). There is some evidence that BA and SUD could common features such as the emotional instability and share common biological and behavioral characteristics impulsivity. However, comorbidity rates, features and ( Grant et al., 2010 ). BA are characterized by the repetitive treatment related to the association between BA and BD occurrence of impulsive and uncontrolled acts that can turn have not been thoroughly studied and, to the best of our into addictive behaviors over time, causing psychological, knowledge, no systematic review has explored this issue. social and working problems, sometimes with legal and Thus, a better understanding of the possible associations economic consequences ( Lejoyeux et al., 2000 ). Similar to between BA and BD at epidemiological, phenomenological SUD, BA affects the neural circuitry of the brain’s reward and mechanistic levels may provide clinical insights for system. Patients with BA report an urge or craving state the recognition, management, and understanding of com- prior to initiating the behavior and dysphoric state while plex patients exhibiting both bipolar spectrum disorders abstaining from the behaviors as do patients with SUD. and BA. However, unlike substance withdrawal, there are no reports Comorbid prevalence rates can be expressed in two ways: of physiological prominent or medically serious withdrawal the prevalence of psychiatric disorders, especially BD with a states from BA ( Grant et al., 2010 ). The DSM-5 ( American comorbid BA and the prevalence of BA with a comorbid BD. Psychiatric Association, 2013 ) represents a conceptual Hence, the aim of this systematic review was to critically change with the inclusion of pathological gambling (PG) consider and summarize current available evidence regard- under the term “gambling disorder” within the category of ing a possible association between BA and BD. Specifically addictions, thus defining and recognizing BA ( Demetrovics we focused on: (1) Prevalence of comorbid BD in subjects and Griffiths, 2012 ). Also, in DSM-5, criteria for “Inter- with BA, and associated features, (2) prevalence of comor- net gaming disorder” have been proposed into section III bid BA in subjects with BD, and associated features and, fi- (“emerging measures and models”) as an area that required nally, (3) specific treatments for comorbid presentations of further research before possible inclusion in future editions BD and BA. of the DSM. In previous versions of DSM, PG was included under the umbrella of impulse control disorders (ICD), a separate category from SUD. In this sense, kleptomania has 2. Experimental procedures also been hypothesized as having similarities to SUD but it is still classified as ICD. Although not included as formal diag- This systematic review was performed according to the noses in current psychiatric diagnostic systems, additional Preferred Reporting Items for Systematic Reviews and behaviors such as compulsive buying ( Black, 2007 ), inter- Meta-Analyses (PRISMA) guideline recommendations ( Moher net addiction (IA)( Ko et al., 2012 ), video/computer game et al., 2009 ). addiction ( Porter et al., 2010 ), compulsive sexual behavior, To identify studies for this review, a systematic search ( Goodman, 1992 ), food addiction, compulsive buying, work was performed using MEDLINE/PubMed/Index Medicus, 78 C. Varo et al.

Cochrane Library and Psycinfo of all articles published up went title and abstract examination. Further 1097 articles to December 31st 2017, cross-checking the obtained refer- unrelated to the aim of this review, 55 reviews, 33 case re- ences. The systematic search was performed as follows: ports, 3 short communications, 4 letters to the editor, 2 MEDLINE/PubMed/Index Medicus string: keywords (“psy- commentaries, 1 supplement and 5 studies involving only chiatric disorder” OR “mood disorders” OR “bipolar children/adolescents were excluded. Thirty-six full text ar- disorder” OR “bipolar affective disorder” OR “manic” OR ticles were assessed for eligibility and 8 full-text articles “mania” OR “bipolar depress ∗”) AND (“behav ∗ addict ∗”OR were excluded ( DeCaria et al., 1996; Kafka and Prentky, “non-substance-related addiction” OR “impulse control” 1992; Kesebir, 2012; Soberay et al., 2014; Hollander et al., OR “internet addict ∗”OR “excessive internet use” OR 2005a; Wolfling et al., 2015; McIntyre et al., 2007; Nunes- “pathological internet use” OR “problematic internet use” Neto et al., 2018 ). In the end, 28 full text articles were OR “computer addict ∗”OR “gambl ∗”OR “eat addict ∗”OR included in the systematic review ( Black and Moyer, 1998; “food addict ∗”OR “sex ∗ addict ∗”OR “shopping addict ∗” Kausch, 2004; Hodgins et al., 2005; Petry et al., 2005; Dan- OR “compulsive buying” OR “compulsive sex behav ∗”OR non et al., 2006; Zimmerman et al., 2006; Kessler et al., “buy ∗ addict ∗”OR “work addict ∗”OR “tanning addict ∗”OR 2008; Edens and Rosenheck, 2012; Abdollahnejad et al., “physical exercise addict ∗”OR “physical activit ∗ addict ∗”). 2014; Nower et al., 2015; Raymond et al., 2003; Scanavino Cochrane library: we used the same search strategy. et al., 2013; Kim et al., 2016; Bernardi and Pallanti, 2009; Psychinfo: we used the same search strategy. Lejoyeux et al., 2002; Presta et al., 2002; Bayle et al., 2003; Dannon et al., 2004; Di et al., 2010; Sapir et al., 2013; Quilty et al., 2011; Quilty et al., 2017; Kawa et al., 2005; Kennedy

Eligibility criteria and study selection et al., 2010; Jones et al., 2015; Kesebir et al., 2012; Karakus and Tamam, 2011; Manning et al., 2017 ). Records were reviewed using the following inclusion crite- ria: (1) samples of patients diagnosed with BD presenting a comorbid diagnosis of BA, (2) samples of patients with BA presenting a comorbid diagnosis of BD, (3) mixed sam- Prevalence of comorbid BD in subjects with BA, ples (e.g., mood disorders patients) with separate outcomes and associated features for BD patients, (4) studies conducted on adult ( ≥ 18 years) individuals, (5) case-control and cohort studies, retrospec- A total of 19 studies were included in this section ( Table 1 ). tive and prospective, population or register-based, (6) sub- Among these, 11 studies were on PG ( Black and Moyer, 1998; analyses or post-hoc analyses considering comorbid BD and Kausch, 2004; Hodgins et al., 2005; Petry et al., 2005; Dan- BA of wider studies in which the original study did not pro- non et al., 2006; Zimmerman et al., 2006; Kessler et al., vide details on BD and BA comorbidity, (7) studies published 2008; Edens and Rosenheck, 2012; Abdollahnejad et al., in English language. The following exclusion criteria were 2014; Nower et al., 2015; Manning et al., 2017 ), 2 on com- applied: (1) studies concerning addictions in general, but pulsive sexual behavior ( Raymond et al., 2003; Scanavino et not specifying the type of BA, (2) studies including indi- al., 2013 ), 2 on IA ( Kim et al., 2016; Bernardi and Pallanti, viduals at high risk for BD with no validated diagnosis (i.e. 2009 ), 1 on ICD (including PG and kleptomania) ( Lejoyeux et no standardized diagnostic assessment) and (3) reports not al., 2000 ) and 3 on kleptomania ( Presta et al., 2002; Bayle published, uncompleted studies, letters to the editor, opin- et al., 2003; Dannon et al., 2004 ). ions or commentaries, reviews, case reports, and short com- munications. Pathological gambling (PG) Across the 11 studies there were 1006 people with BD. Data extraction The National Epidemiologic Survey of Alcohol and Related Conditions found that the lifetime prevalence of PG in a Using the PRISMA statement, articles were selected based sample of 43093 individuals was 0.42% ( Petry et al., 2005 ). on title and abstract. Full texts of the potentially eligi- When considering comorbidities, results confirmed high ble studies were independently assessed for eligibility by rates of alcohol use disorder (73.2%), PD (60.8%), nicotine two blind independent researchers (CV and MR). References dependence (60.4%), mood disorder (49.6%), an anxiety identified through other sources were also reviewed to iden- disorder (41.3%), and any other drug use disorder (38.1%). tify further possible studies of interest. Among patients with lifetime prevalence of any mood Extracted information included: main BA, first author, disorder, 36.9% presented a lifetime diagnosis of major year, study design, primary and secondary aim, general sam- depressive episode, 22.8% of manic episodes and 4.6% of ple size (BD patients in a BA sample and vice versa), BA as- hypomanic episodes. sessment, primary results and secondary results. It was not Data from the United Stated National Comorbidity Sur- possible to do a meta-analysis due to heterogeneity in the vey Replication revealed that in a sample of 9282 individu- outcomes/population thus we conducted a narrative syn- als, the lifetime prevalence of problem gambling was 2.3%, thesis of the available evidence. while the lifetime prevalence of PG was 0.6% ( Kessler et al., 2008 ). Among patients with PG, 96.3% of survey respon- dents also met lifetime criteria for one or more other psy- 3. Results chiatric disorders. Concerning BD, the estimated lifetime prevalence of PG among BDII was 2.9%. The global search first returned 1250 titles ( Fig. 1 ). We ex- A case–control study focusing on all veterans accessing cluded 14 duplicates articles, so that 1236 articles under- veterans’ health mental services (n = 1102846) evaluated Behavioral addictions in bipolar disorders: A systematic review 79

Fig. 1 PRISMA flow-chart of the studies considered and finally selected for review.

rates of PG diagnosis and the comorbidity among PG pa- The prevalence and diagnostic correlates of PG in psychi- tients ( Edens and Rosenheck, 2012 ). The results showed atric outpatients was evaluated in a cross-sectional study that veterans with PG (n = 2,283) were lower compared with including 1709 individuals ( Zimmerman et al., 2006 ). Results non-PG (n = 1,100,563). The results showed that the preva- showed that 2.3% (n = 40) of patients had a lifetime disor- lence of PG was 0.21%. Among PG cases, 20.5% met diagno- der of PG. Patients with PG were 4-fold more frequently sis for BD (n = 469). When PG cases were compared with diagnosed with a lifetime history of BDI, followed by panic patients without PG, a significant association was found disorder with agoraphobia, alcohol abuse/dependence, and between PG and alcohol use disorders, followed by BD other ICD than non-PG. and PD. In a recent cross-sectional study the prevalence of gam- An epidemiologic study that assessed the prevalence of bling problems across the risk continuum and its relation- PG and its comorbid psychiatric disorders in a 275 homeless ship with substance use and specific psychiatric diagnoses population of United States of America ( Nower et al., 2015 ), among 831 patients was examined ( Manning et al., 2017 ). revealed that PG patients( ≥1 symptom) (n = 127, 46%) were Results revealed that 6.3% (n = 53) of patients were classi- 3-fold more likely than non-PG patients (n = 88, 32%) to fied as problem gamblers. Also, the results suggested that meet diagnostic criteria for BD, followed by antisocial PD, drug use, borderline PD, BD, and psychotic disorder were post-traumatic stress disorder, any other mental health psy- significant predictors of PG. chiatric disorder and nicotine use. Also, the results revealed A cross-sectional study that evaluated the psychiatric co- that among PG individuals, 68% met diagnostic criteria for morbidity of 30 PG patients ( Black and Moyer, 1998 ) re- BD. vealed high rates of any lifetime SUD (64%), any lifetime 80 C. Varo et al.

)

page

),

with and

next

disorder N/A

on mood

of BD:

result(s) ∗

(

treatment alcohol associated

abstinence:lifetime

continued

( Factors stable prevalence disorders current current Secondary

No

BD:

man ∗

use

vs.

( (23%); :

PG

other

N/A)

visited

a

PG

CSB 0.04. (42.9%)

in

alcohol

vs. Alcohol alcohol PG weekly <

(64%); Drug BD:

mood

depressive

vs. (

:

was P

9)

∗

: buying married (72.4%) 0.001. Current vs.

± disorders

(40%);

SUD 12)

< 0.05.

(20%); more

$34.250, 5)

younger P ± psychiatric

(7%). 0.001.

< major

(23

: ±

or of

0.001.

:

P white < subject

of comorbidities

(48%).

(22.2%);

differences mood <

P

disorders (60%); (19

younger SUD

P

prevalence

(32.5 one

result(s)

:

disorder 10);

(33%);

onset

compulsive SUD

disorders 11); 0); ±

income

typical of attempts SUD (73%); (7%); disorders

0.44)

± ± elderly

casino =

Primary comorbid disorders anxiety (17%); The 44-year-old with a elderly Any vs. significant psychiatric P use (61%); mood use Age disorder (35.1 use (33 disorders (30 Prevalence Lifetime Any

assessment SOGS DSM-IV SOGS BA

I

2, BDI 8,

BD =

=

n

n BDII

diagnosis diagnosis

features.

gamblers: months):

%) 17%. 20% 2.7%; BDII 4%; 2%

6 month):

Lifetime 5, 6, 1, 0; 4, 2,

(n;

======

BD (past n Lifetime prevalence: n Elderly n younger gamblers: 8.2% (past n 2%. prevalence: n n Current Current

associated

98

=

n and

sample

gamblers: young

BA

30 37; 101

= = =

with

General size n Elderly n gamblers: n

the

subjects

of

in

examine

BD Secondary aim(s) study To factors associated with abstinence during one-year follow-up

of in

and on

with of and

the

and with

SUD

comorbid and

gamblers and

aim(s)

alcohol features

and

focus

onset

disorder of

prevalence suicidal of study

examine compare examine

subjects

main

the To psychiatric comorbidity sociodemo- graphic of PG To elderly younger regarding psychiatric comorbidity, a SUD and ideation behavior To prevalence age lifetime current disorder, mood PG Primary

prevalence

design

the

Study Cross- sectional Cross- sectional Naturalistic, 12-month follow-up longitudinal study

assessing

Moyer

(2004)

(2005)

&

Author,

al.,

studies

year Black (1998) Kausch Hodgins et First

Main (PG)

1

BA

Table Main Pathological gambling Behavioral addictions in bipolar disorders: A systematic review 81

)

page

0.05;

8.3,

n.s.;

<

n.s.); n.s.); n.s.); n.s.); n.s.) disorder

=

= 7.5–28.7, P

3.1–10, 2.4–11.3, 0.9–7.1,

= = = = =

1.74–6.26, 3.9–15.0,

next P

disorder

n.s.); =

OR

= = = P P P P P

=

( =

=

4.6, 2.6, 1.7, on

2.6,

P

5.0,

= = =

anxiety =

= male: episode

result(s)

95%CI 95%CI 95%CI

6.9–8.4,

95%CI OR OR OR

OR

dependence = OR

2.8–7.6, 3.1–8.2, 1.6–4.5, 0.8–3.6, 3.8–17.7, 0.6–3.8,

dependence vs.

episode

depressive 9.5,95%CI 14.7,95%CI 5.6, 5.2, 1.6, ======

2.8–3.5, 7.7,

(OR continued

= = = = =

0.05; 0.5; 0.05; 0.05; n.s.); n.s.;

( = =

< < < < = =

manic Female Alcohol (OR P 95%CI SUD OR nicotine (OR P 95%CI major (OR P 95%CI generalized (OR P 95%CI ∗ 95%CI OR P hypomanic (OR P 95%CI Secondary

use

in (0.42%).

(38.1%)

mood

nicotine PG

anxiety SUD alcohol

vs.

PG:

prevalence (60.4%);

(60.8%);

(49.6%); (41.3%);

with PD

result(s)

(99.58%)

Primary Comorbidity subjects (73.2%); dependence disorders disorders Non-PG

assessment AUDADIS-IV BA

PG

PG

+

+

(0.95%); PG

MDD

%) +

manic hypomanic major

(n; + + +

BD depressive disorder PG (2.92%); PG (0.85%) (36.9%); manic (22.80%); hypomanic (4.66%) PG

sample

43093

=

General size n

in

the

of

sex

examine

Secondary aim(s) study To the differences comorbid associations

of

of

of

and

and

aim(s) sample

quarters a

study in

examine

the To prevalence comorbidity PG American household group residents Primary

Epi-

design

Study National demiologic, cross- sectional

al.,

)

et

Author,

year Petry (2005) First continued

(

1

BA

Table Main 82 C. Varo et al.

)

vs.

vs. ICD PG by

page :

2.5; 3.3;

= =

ICD

1.26–6.19

Non-PG (8.2%); next (42.5%)

OR OR

(62.5%)

=

with on

vs. PG disorders,

predicted

4;

PG

: =

result(s) 95%CI

Non-PG

was

1.37–11.74. 1.30–4.76. 1.74–6.26. (10%) (40.1%); (18.3%); use

OR

mood

= = = vs. disorder

2.8;

PG

SUD continued

: =

onset (

BDI (2.7%); 95%CI Alcohol Non-PG 95%CI Panic agoraphobia: Non-PG 95%CI (20%) OR PG anxiety and Secondary

PG

2.3%;

:

more

patients patients

40,

:

: (78.4%); for

97.7%) =

patients prevalence (2.3%);

n

:

(19.2%); relatives SUD

(3.2%).

disorders

PG: with

1.669,

gambling

of gambling =

n (16.1%). prevalence

gambling

patients (13.4%); relatives

result(s)

Anxiety

relatives

relatives 96.3%

:

Depression

meet

Primary relatives (8.0%); Problematic (100%); (9.7%). (17.3%); (18.3%). patients (13.9%) Prevalence (non-PG: problem (0.6%). PG disorders Alcohol Prevalence

PG

a

+

assessment SOGS SCID module DSM-IV CIDI BA

1st

BDII 2,

5,

BDI

4,

=

2%; =

2%;

= n

n

1, n

1, 2.7%; 4.3%

%)

=

= BDII

n

BDI n

45, 72,

(n;

Non-PG:

= =

BD BDI BDII -degree: 5% 10%; 5% n n 2.9% PG:

93

1st

=

n

sample

52;

=

n

1709 9,282

= =

General size PG: -degree: n n individuals

the PG

2nd

of

other the

disorders

examine examine

Secondary aim(s) study To the comorbidity between and psychiatric disorders To the associations between temporally 1st and disorders

of PG

PG

and a

a

of the the the of

other

and

in survey

PG in

-degree

gambling

aim(s)

of

of

with 1st

sample study

examine examine examine a

the To comorbid psychiatric diagnoses cohort their relatives To prevalence in psychiatric outpatients To lifetime symptoms along psychiatric disorders sample American Primary

design

Study Cross- sectional Cross- sectional National comorbidity survey replication, cross- sectional

al., al.,

et )

et

(2006)

Author,

al.,

year Dannon (2006) Zimmerman et Kessler (2008) First continued

(

1

BA

Table Main Behavioral addictions in bipolar disorders: A systematic review 83

)

page found

2.1; PG

0.001); 0.01)

11.28–

were 2.0– 1.8–2.3; =

< < was female

1.9–2.3; next

= past-year

= =

(20.3%);

BD

=

PG

on (OR

other disorders being

for (OR

95%CI

result(s) cluster

disorders:

No 0.001);

non-PG 1.8–2.3;P 0.7–0.9;P use

0.001);

depression/anxiety <

2.8; 2.2;95%CI 2.1;95%CI 0.8; = =

<

40–74 factor

= = = =

0.001);PD 0.001); other

continued

0.01.

( < <

=

Risk alcohol (OR homelessness (OR (OR P 95%CI ages P (OR 95%CI 6.87;P 2.5;P Cluster and (64.5%); P significant Secondary

r:

:

vs.

vs.

vs.

non-PG

99%

0.01. 0.01. 0.01. (1.5%); (7.5%);

PG disorde

vs. vs.

1.54; < < < disorder psychotic

:

(10.4%); 1.19–1.65; 1.05–1.49; P P P (24%)

(16.4%) 1.25; 1.44; =

11.25–2.32;

(20.5%) = =

= =

= with

PG OR PG stress

0.21%

non-PG non-PG

PG

:

OR OR (16.4%) 1.29;

: anxiety

1,100,563,

non-PG vs. vs. 95%CI 95%CI =

= Suicidality

95%CI

PG BDI

n :

result(s) 1.23–1.93; 1.21–1.72; 1.14–1.82; 1.07–1.56;

vs. 2,283, (4.5%); (5%); (3%);

OR

= = = = disorder disorders =

1.7; 1.40; 1.25;

n 0.01. 0.001. 0.001.SUD: 0.001

(15.1%) (21.9%)

= = =

= < < <

Primary non-PG: Post-traumatic PG OR P non-PG 95%CI Panic non-PG 95%CI P (35.6%) OR P non-PG 95%CI Mood features (1.5%); 95%CI Generalized PG OR P PG:

assessment ICD NODS-SA; PGSI BA

7,

NOS =

BDII

15,

n

BD

=

NOS

BDI

n 469,

BDII %)

11% 4.5%; 3%; 6%

BD =

BDI n 8, 3, 2, 4,

(n;

= = = =

BD 20.5% PG: 20.5%; 9.6%; n Non-PG: n n n PG:

140

= non

n

sample

73;

=

67)

n

11202846

=

=

General size n Regular gamblers: (PG PG

of PG

in

the

to

of

risk

risk

examine

Secondary aim(s) study To the factors Clustering psychiatric disorders high gambler populations

of

PG

of the the of

among

mental

aim(s)

PG services

of sample

study

examine examine a

the To rate veterans receiving health To prevalence in psychiatric disorders Primary

design

Study Case-control, cross- sectional Cross- sectional

)

(2014) &

Author,

al.,

year Edens Rosenheck (2012) Abdollahnejad et First continued

(

1

BA

Table Main 84 C. Varo et al.

)

page

more

than

next

on

exhibited

result(s)

impulsivity

of

sample continued

( The traits compulsivity Secondary

BD

non-

stress 4.31;

(8.4%),

0.05. 0.05. vs.

(19.7%),

0.01. 0.001), 0.02), 0.04) = non-PG

(16%);

< < non-PG

disorders < < = =

2.59;

P P

1.07–3.38;

psychiatric P P P P (OR (6.3%).

= (7.2%),

1.14–11.48;

=

(56%)

Current

1.01–3.19;

(53.9%);

:

=

2.9; =

1.83; mood

use gamblers psychotic

PG

non-PG (OR

2.9; 2.4;

(51.6%);

PG

gamblers PG =

(59.6%);

=

= = 95%CI

(71%)

PD of

PG PD:

and OR

95%CI

drug PG Post-traumatic

use: gamblers

(OR OR OR gamblers

result(s)

(96%); 6.78–11.28; 1.14–11.48; 1.31–4.21; 1.98–9.37; 1.13–5.94; 1.03–3.25;

(58.8%);

(68%);

SUD

2.01; ======

3.6; 1.8;95%CI

non-substance PG = 0.05. 0.05 0.03),

(14%);

= =

< < =

Primary OR P disorder: (19.2%); 95%CI Antisocial PG 95%CI Any disorders: (25.5%); 95%CI Nicotine non-PG OR P low-risk moderate-risk problem Predictors diagnosis 95%CI borderline 95%CI (OR P disorder 95%CI Anxiety (71%); BD: Non-problem

assessment SOGS PGSI MICQ-S, CSBI BA

17,

7,

=

=

n

n

17.3% 21.7%

diagnosis

%) 16%; 8%

year): PG:

4, 145, 182, 2,

(n;

= = = =

BD Non-Gamblers: n Non-PG: 16%; 68% (past n Lifetime prevalence: n prevalence: n Current Lifetime

127,

88,

=

=

n

n sample

21.8%;

PG:

275 60, 837 25

= = = =

General size n (non-gamblers: n non-PG: 32%; 46.2%) n n

CSB

the

or

of

link

that

ICD

examine obsessive-

Secondary aim(s) study To data could to compulsive disorder the

of in

the

the SUD CSB

with a the the in

of of of

use

and in and of

with

aim(s) of

severity

specific study

PG examine examine examine

sample

the To differences prevalence psychiatric disorders by a American homeless To prevalence gambling problems relationship substance and psychiatric To prevalence psychiatric disorders sample subjects Primary

Epi-

design

Study National demiologic, cross- sectional Cross- sectional Cross- sectional

al.,

)

et (2017) 2003

Author,

al., al.,

year Nower (2015) Manning et Raymond et First continued

(

1

BA

Table Main Compulsive sexual behavior (CSB) Behavioral addictions in bipolar disorders: A systematic review 85

)

page

next

on

result(s)

continued

( Secondary

PIU

(7%); deficit (7%);

SUD

0.003.

social PIU 0.078 non-PIU

(46.5%),

PD =

5.43;

= BDII

3.12;

P

(5.5%); (1.2%);

1.50–8.08; 2.14–4.32; 1.54–3.09;

=

diagnosis

disorders:

use

=

(4.6%); = = = non-PIU (15%); (15%);

disorders:

(0.8%); OR

(36.1%),

PIU

Attention

OR

(28.1%);

(14%); 1.59;

: disorder

vs. disorders

disorders: (12.8%)

(7%)

=

non-PIU PG: 95%CI 95%CI 95%CI BD: PD

(7%); Mood Anxiety Alcohol (14%);generalized PIU

∗

common PD .

ICD non-PIU OR

604) (0.4%); result(s) 1.76–16.78; 1.27–1.99; 0.88–11.04;P

disorder disorder

non-PIU

= disorders = = =

3.48; 3.04; 2.19; anxiety

2968). most

(9.8%); (n 0.004. 0.001. 0.001. 0.001

= = =

=

= < < <

Primary was: mood (14.0%), (n non-PIU 95%CI Somatoform (1.7%); OR P (10.6%); OR P PIU OR P disorders: (16.5%); 95%CI P 95%CI hyperactivity symptoms anxiety anxiety borderline dysthymia obsessive-compulsive avoidant The PIU Comorbidities

assessment SCS IAT BA IAS

6, 4, 1, 30,

= = = =

n n n n

%) 7%

PIU: Manic PIU:

1,

(n;

=

BD episodes: 4.7% episodes: 1.2% 0.2% 1% Hypomanic n Non-

sample

86 6510 15

= = =

General size n n n

the

of

Secondary aim(s) study

of

IA

PIU

of CSB the

and

of among

in with

aim(s)

patients CSB

sample comorbid demographic study

examine examine examine a

the To and psychiatric disorders male with To prevalence, correlates, comorbid in Korean individuals To comorbidities and features patients Primary

Epi-

design

Study Cross- sectional National demiologic, cross- sectional Cross- sectional

&

)

al., (2013)

Author,

et

al.,

year Scanavino et Kim 2016 Bernardi Pallanti (2009) First

continued

( (IA)

use

1

BA

Table Main Problematic internet (PIU) Internet addiction 86 C. Varo et al.

Im-

Test; spec-

(1.3%);

Severity (36%);

disorder

(1.3%); Associated

ICD- confidence

ICD 0.001

=

(51%);

Minnesota

ICD- < mood Addiction

and

CI

+ otherwise

=

P

Bulimia: Compulsive

result(s)

(19%);

Gambling

ICD +

not another

MIDI

(19%);

Ratio; (45%)

ICD

0.002. 0.001. +

Internet

Disorder = <

BD: P ICD P buying: ICD-(22%); Prevalence: (73%); SUD Problem Secondary

the Odds

Disorder Use =

=

of

:

or

OR

PG

PG

BDII

PGSI

with

0.03.

body ICD

Questionnaire;

Bipolar

= 0.02 Alcohol (20%)

with version

disorder

= disorder P

=

SUD (25%); disorder (3.7%); (33%);

P

2.4);

(16.8%); (25%); The disinhibition or

patients

NOS ±

separation disorders; (2.8%)

Disorder; Panic =

16.1); Korean panic use

2.4); ICD patients Inventory

BD

± (4.9

Intermittent

Kleptomania ± disorder

II; (2.8%); 2.19);

:

The seeking (60%);

disorder

depression ± (9.5%);

result(s)

= (30%); (58.1 (4.7 Impulsiveness

18.3); 15.7);

kleptomania

BD alcohol trichotillomania obsessive-compulsive

type Control Total (29%): ± ±

(2.6 IAT Personality AUDADIS-IV

+

=

substance-use

Primary explosive (2.8%); pyromania trichotillomania (60%); anxiety (30%); dysmorphic (20%); Scale (72.1 (57.3 alcohol Sensation Kleptomania SUD alcohol (19%); disorder (14%) Obsessive-compulsive Barratt Unipolar ICD = PD

Scale; Impulse

Disorder

results; SUD

Bipolar

gambling;

Addiction

= Minnesota Screen;

assessment DSM-IV DSM-IV DSM-IV BA MIDI

= secondary

BDII

I;

and

Internet

40%

(in BDII 20%;

MICQ-S

BDI

= Gambling

type Pathological 8,

4,

%) 27% 4%; 19%; 19%

= = IAS

=

ICD;

n n

3, 1, 4, 6, primary Oaks

(n;

PG

= = = =

BD BDII n kleptomania sample) Kleptomania patients: n n n BDI the Disorder

South

without in

ratios;

=

Inventory;

Bipolar

odds

SOGS sample =

appear =

patients

Alcohol: Other

Behavior BDI

OR

107 20 11 60 29 21

not

======Scale;

General size n n Kleptomania: n n psychiatric: n Kleptomania: n are

Sexual

depressed

Disorder;

ICD-

=

the they

of

of differences;

and

ICD-

+ Compulsivity

when compare examine depressed Bipolar

Compulsive

ICD; Secondary aim(s) study To ICD in inpatients To clinical features kleptomania comorbidity =

=

BD

in Sexual of

of

significant

with

ICD studies or and

=

CSBI

of

the

the the of of with

not with

in

SUD

SCS

and

with with without with = aim(s)

abuse

or

disorders

patients original addiction;

population study n.p.

ICD evaluate examine examine examine patients a

interview;

the DSM-IV;

the To prevalence in depressed inpatients To comorbidity patients kleptomania To impulsivity, sensation seeking, mood patients kleptomania, compared psychiatric patients an to alcohol dependence To prevalence psychiatric diagnoses patients kleptomania Primary

of for

depressed

Behavioral

=

applicable; =

diagnostic design

+

BA

not

extracted Interview ICD

=

Study Cross- sectional Cross- sectional Cross- sectional Cross- sectional, case-control BD

N/A

of

al., Clinical

al.,

al.,

international

et

)

disorders; (2002) et

Schedule-IV;

et

Author,

Results

al.,

= Interview;

∗

year Lejoyeux et Presta (2002) Bayle (2003) Dannon (2004) First Structured

Composite continued

=

Interview

(

=

(ICD)

Disorder

SCID

1

Impulse-control CIDI

BA

PG) =

Table Main Impulsive control disorder (including kleptomania and Kleptomania Abbreviations: Disabilities ified; ICD pulsive Index; interval Behavioral addictions in bipolar disorders: A systematic review 87 mood disorder (60%), any lifetime anxiety disorder (40%), indicated that mood disorders predicted higher compulsive any lifetime compulsive behavior (43%) (particularly, com- sexual behavior scores. pulsive buying (23%) and compulsive sexual behavior (17%)).

Among those with mood disorders, 20% reported lifetime BD Problematic internet use (PIU)/ internet addiction (IA) diagnosis. Across the 2 studies there were a total of 31 people with BD.

A retrospective cross-sectional comparison study be- A study aimed to investigate the prevalence and psychi- tween elderly PG patients (n = 37) and younger PG patients atric comorbidities of individuals diagnosed with PIU in a

(n = 98) was aimed to investigate lifetime psychiatric national cohort of 6510 Korean subjects (Kim et al., 2016). comorbidities ( Kausch, 2004 ). No differences were found The results showed that 9.3% of the sample met crite- between elderly and young PG patients. BD diagnosis was ria for problematic internet use. Individuals with problem- present in 2.7% of elderly gamblers and in 8.2% of younger atic internet use were more likely to present PG, mood gamblers without significant differences between both disorders, anxiety disorder and alcohol use disorder than groups. non-problematic internet use individuals. No differences

A naturalistic sample (n = 101) of PG patients was eval- were reported concerning BD prevalence between non- uated to determine the association between comorbidity problematic internet use (0.2%) and problematic internet in PG ( Hodgins et al., 2005 ). Results confirmed high rates use individuals (1%). of lifetime alcohol disorder (73%), lifetime mood disorders A cross-sectional study examined psychiatric comorbidi-

(61%), and lifetime SUD (48%). Among those with mood dis- ties in patients with IA (Bernardi and Pallanti, 2009). IA was orders 4% reported BDI diagnosis and 2% BD II. Additionally, found in 15 out of 50 patients. The most prevalent comorbid age at onset for mood disorders were equally likely to pre- diagnoses were any anxiety disorders (30%), any PD (28%) date or follow gambling disorders. and attention deficit and hyperactivity disorder (14%). Re-

A cross-sectional study investigating comorbid psychi- garding mood disorders, 7% of the patients with diagnosis of atric disorders focused on 52 PG patients and their families IA met diagnostic criteria for BDII. ( Dannon et al., 2006 ) reported higher prevalence of alco- Kleptomania hol addiction (19%), unipolar depression (17.3%) and any Across the 3 studies there were a total of 24 people with BD. anxiety disorder (13.46%) compared with BD (4%) among PG A cross-sectional study aimed to evaluate the clinical fea- patients. tures and psychiatric comorbidities of 20 outpatients with a A cross-sectional study that evaluated the association be- lifetime diagnosis of kleptomania ( Presta et al., 2002 ). All tween psychiatric disorders and PG in a sample of 140 reg- patients met criteria for other psychiatric disorder, espe- ular gamblers ( Abdollahnejad et al., 2014 ) showed that 73 cially mood, anxiety disorders, and any other ICD. Among patients of the sample met criteria for PG. Among PG indi- those with mood disorders, 60% reported BD. When sociode- viduals, 91% had at least one psychiatric diagnosis. Specifi- mographic and clinical features were examined, the results cally, PG patients presented significantly higher frequency showed that BDI and bulimia were significantly more likely of posttraumatic stress disorder followed by BDI, panic to occur in women with kleptomania than in men. disorder, lifetime suicidal ideation, mood disorder with A cross-sectional study assessed the prevalence of ICD (in- psychotic features, social phobia and generalized anxiety cluding kleptomania) in 107 patients meeting criteria for disorder. major depressive disorder ( Lejoyeux et al., 2002 ). Among A cross-sectional study assessed the prevalence of ICD 31 (28.9%) depressed patients with ICD, 4 (3.7%) presented (including PG) in 107 patients meeting criteria for major kleptomania. BD was found in 3 out of 4 (75%) patients with depressive disorder ( Lejoyeux et al., 2002 ). Among 28.9% kleptomania. depressed patients with ICD, 2.8% presented PG. BD was A cross-sectional study was performed on the incidence of significantly more frequent in depressed patients with ICD comorbid psychiatric conditions in a sample of 11 individuals than in depressed patients without ICD (19 vs.13%). with kleptomania ( Bayle et al., 2003 ). Among those, 73% had a mood disorder, with 27% individuals fulfilling criteria for BD. Compulsive sexual behavior Another cross-sectional study assessed 21 patients af- Across the 2 studies there were a total of 8 people with BD. fected by kleptomania and their relatives (n = 57) in order A cross-sectional study assessed the lifetime prevalence to identify possible comorbid psychiatric diagnoses ( Dannon of other psychiatric disorders in 23 patients with compulsive et al., 2004 ). Results showed that 33% of patients with klep- sexual behavior ( Raymond et al., 2003 ). Results confirmed tomania presented unipolar depression, 19% BDII, 4% BDI, high rates of lifetime any anxiety disorder (96%), any mood 14% panic disorder and 9.5% obsessive-compulsive disorder. disorder (71%) and history of SUD (71%). Among mood disor- der, 8% of the patients with compulsive sexual behavior met diagnostic criteria for BD. Prevalence of comorbid BA in subjects with BD, Another cross-sectional study examined compulsive sex- and associated features ual behavior and psychiatric diagnoses in a sample of 86 male patients with compulsive sexual behavior ( Scanavino A total of 9 studies were included in this section ( Table 2 ). et al., 2013 ). Among those, 72% presented any psychiatric Among these, 2 studies were on BA ( Di et al., 2010; Sapir et diagnosis, especially anxiety disorders (46.5%), mood disor- al., 2013 ), 5 on PG ( Quilty et al., 2011; Quilty et al., 2017; ders (36.1%), SUD (14%) and ICD (12.8%). Among those with Kawa et al., 2005; Kennedy et al., 2010; Jones et al., 2015 ), mood disorders 5.8% met diagnostic criteria for, hypomania 1 on compulsive buying ( Kesebir et al., 2012 ) and 1 on ICD episodes and 1.2% for manic episodes. A linear regression ( Karakus and Tamam, 2011 ). 88 C. Varo et al.

)

page

in

0.014)

next

0.007);

impulsivity =

comorbidity

on = scores

than II (P

(P

unemployed

axis higher

lower

result(s) : 0.007)

+ = continued

−

( higher

(P BA : BA

0.021); 0.023);

+ −

= =

BA (P (P level BA Self-directness cooperativeness than Secondary

vs. HC

vs.

106.

vs.

vs. = vs. Benign

BD

(3%) music, 0.32, n

(13%)

(1%); :

addictions

=

(17%) BD on

−

0.05)

(r : BD 0.33; 0.05)

HC

HC 0.001) 0.05).

novelty

: BD

< = <

BA

smoking

< <

:

HC

0.042. 0.001. 0.005 P P

vs. (r

P P

Harmful

scores than and and CB = < =

Harmful

52;

vs. and P P P BD

result(s)

=

(7%) addiction 0.29,

0.31;

n

0.42; 0.28,

addiction :

=

= 0.05).

cooperativeness: BD − −

higher

0.001. 0.05) 0.05).

(6%); (2%); (4%);

+

:

< = =

< < <

Primary BA PG P HC Sexual HC Work HC BD: shopping addictions (P addictions seeking: P P and (r (r addictions self-transcendence: BD(r HC(r

71, 50

200 50

size

28%; 27%

= =

= =

BDII: n n

n n

44, 43,

= =

General sample BDI: 45%; n Cy- clothymic: n HC: BDI: HC:

features.

the

two for

6; 8;

3–4 <

<

treating =

least

Criteria euthymia At months: HDRS YMRS CGI Consensus between two physicians associated

and

EAI;

SAST;

BD

assess-

BA ment SOGS; CBS; WART; IAS Behavioral Addiction Scale with

so-

and

aim(s) for

subjects

study in

/BA-

BA + compare the

Secondary of To BA ciodemographic, clinical variables, impulsivity temperamental dimensions

the the

of

comorbid

and

aim(s)

BA sample of

study

a

between

and in examine examine the BD

of To prevalence BA of To interrelation- ship BD (harmful benign addictions), and temperamental traits Primary

prevalence

design

the

Study Cross- sectional Case-control Cross- sectional Case-control

assessing

al.,

et al., Author,

et

studies

Sapir year Di (2010) (2013) First

Main

2

BA

Table Main Behavioral Addictions (BA) Behavioral addictions in bipolar disorders: A systematic review 89

)

BD

and

page

and

onset

vs.

PG

mood

PG 95%

next 0.001]; 0.02] [problem

0.04).

8.85) < = on

0.33; =

P P ± P

1.96; vs. =

MDD

preceded

r analyses

problem

= gambling gambling

association association:

life: 3.75; result(s)

gambling (OR (22.94

Longitudinal with 11.65); 13.32) 13.47); no

continued

of

( Comorbidities: ± ± ±

disorder disorder disorder

1.02-

0.01.

PG. =

<

Mood of disorder gambling CI Quality gambling non-problem (31.47 [problem (29.69 non-problem (35.29 Concurrent mood P mood revealed Secondary

:

:

:

: vs. PG

(20%); (12%);

(0%); (13%);

7%

BD

MDD (26%)

0.01.

disorders =

BD;

P women women

0.05 men

women women

12.4%

12.5% 4%

:

>

disorder vs. vs.

P

vs. vs. abuse/dependence Eating

vs.

BDI

result(s) abuse/dependence (15%);

of

(5%) (32%) (19%) (1%)

0.01. 0.001. 0.03. 0.001

= < = <

Primary Onset women men P Alcohol men P Cannabis men P men P Prevalence: (33/275) (36/304); Prevalence: depressive

90 6, 21,

BD

BD: BD:

size

BDII: = =

=

n n n

121 275 304 227, 77, 138 137 100,

======

General sample Women: n n n (BDI: n 74.6%; n 25.3%) disorder: n n (BDI: n 80.29%; BDII: 15.33%; NOS: 4.38%) Depressive Men: MDD:

for

Criteria euthymia N/A N/A N/A

TAG LIFE

assess-

BA ment DIGS CPGI; SOGS; CPGI;

of

PG

sex

of

aim(s) life

onset

of

study disorder

problem mood

examine examine the

Secondary of To differences, temporal relationship between mood and gambling, comorbidities, quality To association and disorder

the the of of

in

onset,

men

differ

aim(s)

sample

BD number

of

of study

a and

BD or

women

in examine examine examine

the suicide mood age

of To whether and with in course illness, of attempts, comorbidity rates symptom presentation To prevalence problem gambling MDD To prevalence PG of disorder patients Primary

design

Study Cross- sectional Cross- sectional Cross- sectional; longitudinal

al.,

)

2010 2011

et

Author,

al., al.,

year Kawa 2005 Kennedy et Quilty et First

continued

(

2

BA

Table Main Pathological gambling (PG) /Problem gambling 90 C. Varo et al.

)

page

next

on

result(s)

continued

( Secondary

or

at

of age

a with

at

severe 0.002)

0.02), Risk

0.94; : low

desire

=

or =

social behavior.

=

gamble

gambling

P or gambling:

were

Moderate ideation

copes the

to

cycling and no younger (OR the

3.44;

BD PG:

89.45%.

differences;

=

and of not

disorder

enhancement

no gambling

Moderate suicidal rapid motivations problem Desire

onset

affect

gambling

(OR 658,

affect

result(s)

1.21–9.73;P 1.29–5.34; 0.90–0.98; or

10.55%;

of of period

predicted

for =

2.63;

= = =

line: n

= 0.008), 67,

gamble, severe illness

= =

Primary or n risk: factor problem history attempt 95%CI history (OR 95%CI P at 95%CI Affect to behavior. predicted Gambling base 30-day negative depressive reasons positive Distibution

635 size

BDII:

BD: (BDI:

6.6%)

=

n 15 15 14, 1,

= = = =

General sample disorder: n n n 93.3%; n BD: Depressive

for

Criteria euthymia N/A N/A

RFG

assess-

BA ment PGSI SOGS;

aim(s)

study

the

Secondary of

of

the the and

with

and

in

aim(s)

sample

desire

study

patients a

in examine examine

gamble the BD

mood

of To prevalence distribution PG of association between affect, to gambling behavior individuals a disorder Primary To

design

Study Cross- sectional Longitudinal

al.,

)

2017 et

Author,

al.,

year Jones 2015 Quilty et First continued

(

2

BA

Table Main Behavioral addictions in bipolar disorders: A systematic review 91

vs.

vs. First

Major

Scale;

of Rating

0.01),

higher

(62.5%)

=

0.1) Scale.

Severity < scores

more

± Working:

±

(75%)

(P suicide

0.009. MDD

0.01. 0.002.

CB

± 0.002.

Buying

remission: CB-(43.4%);

0.03), questionnaire;

= co-morbidity:

= =

(1.5 ICD- = Rating

vs. (75%)

Hamilton

0.007. CB CB-(32.6);

P

= P P II

CB-(15.4); CB-(21.8);

P

± 0.025.

CB-(52%);

scores: scores 0.024), vs. ± = full

(11.8%); =

(P comorbidity =

vs. P =

onset: CB

± vs. vs.

0.2)

than

impulsivity episodes

episodes: CB

vs. p previous

Premenstrual Axis Cyclothymic Irritable

Mania

result(s)

0.2); 0.1); (P

±

follow-up; HRSD CB of mania: of

gambling

± ±

Compulsive

higher

(75%) (2.3 (100%) (162.5%) (17.3) (23.2) = 0.035) Young

higher

for

0.035. 0.001. 0.045. 0.029. 0.045 +

CB-(32.6%);

± ± ± ± ± ±

episode:

= =

= = = = =

CBS control; interval

CB-(2.4%); CB P syndrome: vs.CB-(32.6%); Postpartum vs. episode CB-(41.3%); of CB-(2.2 Number CB CB-(0.9 Inter-episode CB P CB P temperament CB P temperament CB P ICD alcohol/SUD number attempts depressive and (P Female:

Secondary

YMRS

Reason

ICD;

=

1;

Healthy

Test; 1; PG

8;

=

=

RFG = n

8; =

longitudinal n without HC

Risk n

behavior

=

Intermittent n

picking (0%)

BD

The

ratios; 9;

=

=

- HC

27.4%

= skin

exercise sexual

n CB

disorder

Addiction LIFE odds Inventory;

result(s)

CB (8%); =

kleptomania CB;

ICD; OR BD Work 13; 4; 0)

=

= = =

with

Primary CB: (pathologic n explosive trichotillomania n compulsive compulsive n Prevalence: Addiction

BD

WART without

=

124

100

100; size specified;

+

BD

=

= =

=

n Exercise CB

n n

-

=

BA; ICD General sample HC: BDI: BD: Gambling;

EAI

of otherwise

ICD;

for 12, 8

Not

without < <

Studies; = with

BD

BD

NOS Criteria euthymia HDRS N/A YMRS Assessment

=

−=

+ Genetic

BA

for ICD

BA;

assess-

Temporal

= assessment;

BA ment CBS MIDI

with

TAG Interview not

disorders; BD

=

=

the on

aim(s)

+

and CB-

clinical

N/A

Screen;

BA

study of

/ICD-

and I; Diagnostic

+

+ examine examine = the

Secondary of To differences between CB To ICD sociodemo- graphic, variables levels impulsivity/ sensation seeking type

impulse-control

DIGS Interview; Gambling

= to

in

the the

of

of

ICD Oaks it

and

ICD

aim(s) Disorder

study Disorder

Problem; BD

HC

South

Scale;

in examine examine the

=

Bipolar

of To frequency CB compare with To prevalence lifetime BDI Primary

=

Canadian SOGS

Impulsive

BDI

=

Addiction

design

Test;

CPGI

Study Cross- sectional Case-control Cross- sectional Disorder; Minnesota

Internet

=

=

Screening

&

)

IAS

2012 MIDI

Impression;

Bipolar

Author,

=

al.,

BD year Kesebir et Karakus Tamam, 2011 First

Addiction Global

continued

disorder; (

Depression;

PG (CB)

Sexual

2 for Clinical

BA

=

klepto-

=

Table Main Compulsive buying ICD (including CB, mania, and compulsive sexual behavior) Abbreviations: CGI Scale depressive SAST 92 C. Varo et al.

Behavioral addition (BA) 15% (n = 27) were rated as being at moderate or severe risk Across the 2 studies there were a total of 208 people with compared with 10% (n = 40) of those with BDI. Results also BD. showed that clinical variables associated with the presence A cross-sectional study examined the prevalence of BA of moderate and severe risk of problem gambling were hav- in a sample of 158 euthymic bipolar patients compared ing history of suicidal ideation or attempt, history of rapid with 200 healthy controls (HC) ( Di et al., 2010 ). Clinical cycling, and younger age at illness onset. variables, level of impulsivity and temperamental dimen- A cross-sectional and longitudinal study focused on eval- sions were also compared between BD with and without BA. uating the prevalence and the association of PG in a sample Results showed that bipolar patients presented higher BA of outpatients with diagnosis of depressive spectrum disor- comorbidity rates compared to HC (33% vs. 13%). Among pa- der, (n = 138) and BD (n = 137) ( Quilty et al., 2011 ). The tients with BD, compulsive buying (17%) was more frequent prevalence rate of PG evaluated with conservative crite- followed by work addiction (13%), PG (7%), compulsive sex- ria was 7% in patients with depressive spectrum disorder ual behavior (3%) and exercise addiction (4%). Furthermore, and 4% in BD, without significant differences between both BD patients with BA were more likely to present axis II groups. Despite the concurrent association between PG and comorbidity than BD patients without BA. When tempera- mood disorder symptoms (r = 0.33; p < 0.01), over past 5 ment was analysed, the results revealed significantly lower years no longitudinal association was found between both self-directness and cooperativeness scores and significantly pathologies. higher impulsivity levels in patients with BA with respect to The prospective associations between affect, desire to those without BA. gamble, and gambling behavior in individuals diagnosed Another study compared 50 BD type I with 50 HC con- with a mood disorder were evaluated ( Quilty et al., 2017 ). cerning BA ( Sapir et al., 2013 ). BA were divided into two Thirty patients with a lifetime diagnosis of unipolar depres- categories: harmful addictions (alcohol, drugs, cigarettes sive disorder (n = 15) or BD (n = 15) who met criteria for and gambling), and benign addictions (chocolate, caffeine, current and lifetime PG were enrolled in this study. Re- exercise, shopping, internet, love relationships, music and sults revealed similar gambling motivations across groups at work). Post-hoc comparisons revealed significant differ- baseline. However, during the 30-day period BD participants ences between BD patients and HC in several individual were significantly more likely to use gambling to cope with BA. BD showed higher scores on two benign BA (music and negative affect (46% vs. 22%) while participants with de- shopping) and smoking. Personality traits were also studied; pressive disorder were significantly more likely to endorse the results showed that, in both groups, novelty-seeking gambling for social reasons (8% vs. 3%) and for enhancing was positively associated with harmful addictions while the emergence of positive affect(69% vs. 51%). Regression cooperativeness was negatively associated with harmful analysis revealed mood-related variables such as high lev- addictions. els of sadness and arousal predicted an increased desire to gamble and therefore gambling behaviors. Pathological gambling / problem gambling Across the 5 studies there were a total of 1302 people with Compulsive buying BD. Across the 2 studies there were a total of 109 people with An exploratory cross-sectional study examined whether BD men and women with BD differed in comorbidity rates ( Kawa Outpatients with BD were assessed for the frequency of et al., 2005 ). Among 90 men with BD, 5% met criteria diag- compulsive buying in a cross-sectional study ( Kesebir et al., nosis for PG, none of the 121 women met criteria diagnosis 2012 ) that included 100 BD patients and 100 HC. Compul- for PG. sive buying was more prevalent in BD patients (8%) than in Another study aimed to investigate the frequency of HC (0%). Premenstrual syndrome was significantly more fre- problem gambling, clinical features and comorbidities in a quent in compulsive buying BD patients, as well as postpar- sample of 275 patients with major depressive disorder and tum onset than BD patients without compulsive buying. The 304 patients with BD ( Kennedy et al., 2010 ). The results former group presented statistically more frequent manic showed that prevalence of problem gambling did not sig- onset of illness, and lower episode severity prior to pro- nificantly differ between major depressive disorder (12.5%) phylactic treatment. Additionally, axis II comorbidity rates and BD (12.3%) groups. Regarding mood symptom severity, were increased among compulsive buying BD patients. When patients with major depressive disorder and BD meeting cri- temperament scores were analyzed, cyclothymic and irrita- teria for problem gambling scored significantly higher on de- ble temperament scores were significantly more prevalent pressive symptoms compared with non-problem gambling. in compulsive buying BD than in non-comorbid BD patients. BD patients with comorbid specific phobia, alcohol depen- In a cross-sectional study, the prevalence of lifetime dence, and SUD had significantly an increased risk of expe- compulsive buying and other ICD such as PG, kleptomania riencing problem gambling. and compulsive sexual behavior was examined within a A cross-sectional study examined the prevalence of prob- sample of 124 euthymic BDI ( Karakus and Tamam, 2011 ). lem gambling in 635 patients with BD, with a particular Results revealed that among bipolar patients with an ICD focus on differences between BDI and BDII ( Jones et al., (n = 34, 27.4%) the prevalence of compulsive buying was 2015 ). Additionally, the associations between problem gam- higher (7.3%) compared with PG (3.2%), kleptomania (0.8%) bling and lifetime clinical variables in BD were analyzed. and compulsive sexual behavior (0%) in this group of psychi- The results revealed that moderate to severe problem gam- atric patients. Regarding clinical variables, results showed bling was four times higher in BD than in the general popu- that BD patients with ICD compared with BD patients lation (11% and 3% respectively). Among patients with BDII, without them presented higher rates of comorbidity with Behavioral addictions in bipolar disorders: A systematic review 93 alcohol or any other SUD, higher number of previous suicidal of bipolar patients with kleptomania must be interpreted attempts, more depressive episodes, and higher level of with caution because could be causing by the small sample impulsivity. size of patients with kleptomania (n = 4) that appeared in the study by Lejotyeux and colleagues. Another BA, com- pulsive buying and compulsive sexual behavior seem also Specific treatments for comorbid BD and BA prevalent. Regarding the former, overspending can also be problems for BD compared to other disorders ( Blanco et One study fulfilled the inclusion criteria ( McElroy et al., al., 2008 ). Different studies found that compulsive buying 2008 ). This randomized placebo-controlled trial study eval- scores in bipolar patients were higher than those in HC ( Di uated the efficacy and safety of olanzapine in the treat- et al., 2010; Kesebir et al., 2012 ). In addition, it has been ment of PG. The sample consisted in 42 outpatients with described that up to 7–8% of individuals fulfilled compulsive PG out of which 21 received olanzapine and 21 received buying criteria in samples of individuals with BD ( Kesebir et placebo during 12 weeks. Among the sample, 19% had al., 2012; Karakus and Tamam, 2011 ), a percentage that is a BD diagnosis (n = 2 olanzapine; n = 6 placebo). The re- higher than that reported in the general population (3.1%) sults showed that olanzapine and placebo were associ- ( Mueller et al., 2009 ). Concerning compulsive sexual behav- ated with a similar rate of reduction in the total scores ior, its prevalence among BD patients was low (overall 4–8%) on the Yale-Brown Obsessive Compulsive Scale, as well compared with other diagnostic categories studied, as any as in gambling episodes/week, hours gambled/week, and other mood, anxiety disorders and SUD ( Raymond et al., in the Clinical Global Impressions-Severity of Illness scale 2003; Scanavino et al., 2013 ). Regarding IA, it is still not scores. clear whether it constitutes a BA per se or if it simply chan- nels BA, routing patients to compulsive online pornography viewing, compulsive online shopping, or internet gaming 4. Discussion disorder ( Chamberlain et al., 2016 ). The prevalence’s rate of comorbidity between BD from problematic internet to IA To our knowledge, this is the first systematic review specif- among BD was 1–7% ( Kim et al., 2016; Bernardi and Pallanti, ically aimed to examine the relationship between BA and 2009 ). As aforementioned with kleptomania, results about BD. BD-BA co-occurrence seems to be high, PG being the some BA such as, compulsive sexual behavior and problem most common among this group of patients, followed by internet use must be interpreted with caution since the kleptomania, compulsive buying, compulsive sexual behav- numbers of studies is small as well as the sample of patients ior and, finally, IA. We did not find results concerning BD with BD; hence it is difficult to draw firm conclusions about and others BA. Overall, our results suggest that, compared their relationship. It is worth mentioning that diagnostic re- to patients without BA, bipolar patients with concurrent BA liability of most BA is poor, with the exception of PG. present a worse prognosis and more severe course of illness, Beyond the overall worsening effect of comorbid BA in higher rates of axis I comorbidity, suicidal ideation and be- BD, another critical aspect that needs to be further inves- havior, early age at onset and higher levels of impulsivity. tigated is the directional relation between the two disor- No treatments are currently approved for BA-BD comorbid- ders, BA has been viewed as an attempt to self-medicate ity; we identified only one randomized controlled trial that or escape negative mood states ( Goldstein and Bukstein, has sought to address this issue in people with BD. Addition- 2010 ). The increased prevalence of BD in BA populations ally, methodological heterogeneity in terms of design among ( Di et al., 2010; Sapir et al., 2013 ) points to the possibil- studies was found. ity that either BA may trigger or predispose to BD or BD Clinical and epidemiological research revealed high may predispose to BA through increased sensitivity to re- rates of comorbidity between BA and psychiatric disorders warding stimuli or through self-treatment. Since, a trend to- ( Chamberlain et al., 2016; Grant et al., 2010 ). The most wards mood elevation and symptoms of hypomania, as well prevalent seems to be mood disorders, anxiety disorders, as an orientation towards reward-based behaviors, might SUD and PD. Yet, results globally point at a higher occur- drive to develop a BA by enhancing its enjoyment and ex- rence of BA-BD comorbidity compared with the general pop- citement. On the contrary, depressive symptoms could pro- ulation. The prevalence of BD patients in BA samples ranges vide an impetus to console or comfort oneself through BA. from 1% to 68% ( Kim et al., 2016; Lejoyeux et al., 2002 ) In this sense, the relatively strong associations between BD and the prevalence of BA in BD samples tend to vary from and PG may be explained by the fact that the characteristic 3% to 33% ( Karakus and Tamam, 2011; Di et al., 2010 ). In- mood disturbances of BD could be playing a powerful role in dividuals with BA present a higher risk to be diagnosed as the development and maintenance of gambling problems in BD, esteemed with OR ranging from 1.5 to 4 ( Zimmerman this population ( Jones et al., 2015 ). Actually, various forms et al., 2006; Abdollahnejad et al., 2014 ). Together with the of mood disturbance are associated with divergent moti- fact that there are many studies with small sample size, vations that might represent distinct pathways into gam- the variability in the assessment of BA, may partially ac- bling behavior ( Lloyd et al., 2010 ), participants with BD count for the heterogeneity in our results. Another possi- were likely to endorse gambling to cope with negative affect ble explanation could be that the number of studies found ( Quilty et al., 2017 ). Urge of BA are often associated with for BA are very widely different. For instance, PG preva- arousal and restlessness that resemble the elevated mood lence in BD ranges from 2% to 68%, approximately ( Edens or with tension and anxiety, similar to that which can occur and Rosenheck, 2012; Kausch, 2004 ), kleptomania from 4% in depressive or mixed states ( Cunningham-Williams et al., to 75% ( Lejoyeux et al., 2002; Dannon et al., 2004 ). How- 1998 ). In this sense, BA-BD comorbidity may pose as a dif- ever, it is worth mentioning that the highest percentage ferential diagnostic challenge, and has to be ruled out in the 94 C. Varo et al. assessment of possible acute depressive-mixed recurrences interviewing, and cognitive behavioral therapies, so that in BD. they could be taken into consideration in the treatment of An early BD onset ( Jones et al., 2015; Kausch, 2004; comorbid BA-BD too ( Kennedy et al., 2010 ). Kessler et al., 2008 ), and being male ( Kawa et al., 2005; Our results need to be interpreted in the light of sev- Kennedy et al., 2010; Manning et al., 2017 ) could be associ- eral limitations. First, many of the methodological limita- ated with risk factors for BD and BA. So, the implementation tions of the studies may impact on our results, preventing of early intervention strategies may help to change the out- us from drawing firm conclusions. Thus, the fact that many come of the illness and avert potentially irreversible harm studies included small sample sizes and restricted assess- to patients with BD, as early phases may be more responsive ments limit the generalizability of the findings. Taken to- to treatment ( Vieta et al., 2018b ). gether, this point out to an overall poor quality in the evi- When personality traits were analyzed among BD with co- dence so far, produced on this specific population, and calls morbid BA, self-directness and cooperativeness scores were for more methodological sound studies, with more homoge- significantly lower and impulsivity levels significantly higher nous population. Moreover, due to the cross-sectional de- compared with BD patients without comorbid BA ( Kesebir sign of most studies, the directionality of the association et al., 2012; Di et al., 2010; Sapir et al., 2013; Karakus between BA and BD could not be established. Although the and Tamam, 2011 ). Taking these results together, impul- presence of manic episodes has been defined as an exclusion sivity, poor modulation of motivation, poor modulation of criterion of PG ( American Psychiatric Association, 2013 ), we response to rewarding stimuli, combined with susceptibil- found a large variability in the definition of euthymia, when ity to behavioral sensitization are other mechanisms that reported, and most of the studies did not provide this infor- would reinforce a neurocognitive link between BD and BA mation. Regarding BA, we found differences in the number ( Swann, 2010 ). Additionally, impulsivity may be associated of studies found for each BA, nomenclature, definitions, and with greater likelihood of severe suicidal behavior in BD operational criteria about what constitutes BA, as well as ( Swann et al., 2004; Jimenez et al., 2016 ). Interactions be- screening instruments used. tween impulsivity and other risk factors for suicide, includ- Future research in the young field of BA and BA-BD co- ing BA, require further investigation. morbidity should focus on narrowing diagnostic criteria for Undoubtedly, even lower evidence on potential treat- BA, improving their diagnostic reliability. Consequently, as- ments for BD-BA comorbidity exists. To ensure the internal sessment should be created and validated in order to al- valid of the findings, many randomized controlled trials ex- low quantitative, dimensional measurements and possible clude patients with multiple comorbird condition. The only symptomatic domains. Once stable BA populations could be trial on treatment that fulfilled inclusion criteria was neg- detected, causal relationships between BA and BD could be ative, olanzapine did not showed a significant improvement investigated, outlining possible risk factors and the neuro- over the placebo group respect to reduction in gambling biological underpinnings for BA-BD comorbidities. behavior and urges ( McElroy et al., 2008 ). Although the few available literature suggest that mood stabilizers could be an effective treatment approach for BD-BA( Di et al., 2014 ), Conclusions most data is based on case reports with lithium( Moskowitz, 1980; Rocha and Rocha, 1992 ), tomiramate ( Nicolato et al., So far, literature on BA and BD comorbidity suggest the ex- 2007 ) or a single case with carbamazepine( Haller and Hin- istence of an increased co-occurrence of these conditions. terhuber, 1994 ). In a small randomized control trial, lithium Our findings highlight the need to undertake systematic was found to be effective in reducing gambling behavior and routine screening and comprehensive assessment of and effective instability in BD-PG ( Hollander et al., 2005b ); possible co-occurring BA in BD, given the potential negative however, this study was excluded from our results as BD impact that BA may bring directly on bipolar illness and, diagnostic was assessed by a screening tool. No pharmaco- more in general, to the impairment in the social, relational, logic or psychological treatments are currently approved for economic and quality of life of patients suffering from BA ( Hollander et al., 2005a; Nicolato et al., 2007; McElroy these conditions. Shared neurobiological underpinnings can et al., 2008 ). For this reason, the management of comorbid be hypothesized in high levels of impulsivity and emotional BA-BD patients was addressed at symptom dimensions. The instability, but have to be ascertained and fully understood. clinical management of BD-BA comorbidity should priori- A better assessment and understanding of the relationship tize affective instability and ensure mood regulation first between BA and BD in future research should contribute to then treats the BA symptoms if still necessary ( Di et al., the improved identification of BD individuals at risk of BA. 2014 ). There are identifiable risk factors that influence the Comorbid BA-BD patients should also be assessed in their course of BD, some of them potentially modifiable ( Vieta potentially differential treatment response. Forthcoming et al., 2018c ). Adjunctive psychological interventions that research will possibly help identifying novel targets for have shown to prevent relapses (e.g., psychoeducation, treatment and, ultimately, improve the outcome of both family intervention, cognitive-behavioral therapy and in- conditions. terpersonal and social rhythm therapy) and to improve mood-regulation in BD ( Reinares et al., 2014 ) should be considered. Presumably, this kind of interventions might be Conflict of interests beneficial at least to mitigate the potential impact of BD on BA. Although no specific evidence on BA-BD comorbidity Dr. Martinez-Aran has served as speaker or advisor for the exists, successful therapeutic interventions for BA include following companies: Bristol-Myers Squibb, Otsuka, Lund- approaches based on the 12-step model, motivational beck and Pfizer. Behavioral addictions in bipolar disorders: A systematic review 95

Dr. Vieta has received grants, CME-related honoraria, Ascher, M. , Levounis, P. , 2015. The Behavioral Addictions. American or consulting fees from AB-Biotics, Actavis, Alexza, Almi- Psychiatric Association ed, Washington, London . rall, Allergan, AstraZeneca, Bristol-Myers Squibb, Cephalon, Bayle, F. J . , Caci, H. , Millet, B. , Richa, S. , Olie, J.P. , 2003. Psy- Dainippon Sumitomo Pharma, Eli Lilly, Ferrer, Forest chopathology and comorbidity of psychiatric disorders in pa-

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