Copyright
©The Author(s) 2016.
World J Psychiatr. Mar 22, 2016; 6(1): 143-176
Published online Mar 22, 2016. doi: 10.5498/wjp.v6.i1.143
Published online Mar 22, 2016. doi: 10.5498/wjp.v6.i1.143
Study | Aims | Sample and design | Treatment approach | Instruments | Results |
Atmaca[28] | To describe a case of problematic Internet use successfully treated with an SSRI-antipsychotic combination | Case report | SSRI-antipsychotic combination: Citalopram 20 mg/d increased to 40 mg/d within 1 wk, continued for 6 wk; then quetiapine (50 mg/d) added and increased to 200 mg/d within 4 d | SCID-IV to assess Axis I psychiatric comorbidity[29] | Y-BOCS score decreased from 21 to 7 after treatment |
n = 1 male 23-yr old single 4th year medical student | YBOCS[30,31] | Nonessential Internet use decreased from 27 to 7 h/wk; essential Internet use decreased from 4.5 to 3 h/wk | |||
Improvement maintained at 4 mo follow-up with the same medication | |||||
Bernardi et al[32] | To describe a clinical study of individuals with Internet addiction, comorbidities and dissociative symptoms | n = 50 adult outpatients self-referred for internet overuse in Italy (age M = 23.3, SD = 1.8 yr) | N/A | Youngs Internet Addiction Scale IAS[33] | Clinical diagnoses included 14% ADHD, 7% hypomania, 15% generalized anxiety disorder, 15% social anxiety disorder; 7% dysthymia, 7% obsessive compulsive personality disorder, 14% borderline personality disorder, and 7% avoidant personality disorder, 2% binge eating disorder |
9 women and 6 men scored ≥ 70 on Internet Addiction Scale; 19 with “possible Internet addiction” (scoring 40-69 on IAT) | Clinical interview | ||||
DES[34] | |||||
CGI[35] | |||||
Sheehan Disability Scale[36] | |||||
Structured Clinical Interviews for DSM-IV (SCID I and II)[37,38] | IAD associated with higher perception of family disability and higher Yale-Brown Obsessive Compulsive Severity score | ||||
Hamilton Rating Scale for Depression[39] | Scores for the Dissociative Experience Scale were higher than expected and related to higher obsessive compulsive scores, hours per week on the Internet, and perception of family disability | ||||
Hamilton Rating Scale for Anxiety[40] | |||||
Liebowitz Social Anxiety Scale[41] | |||||
YBOCS[30] | |||||
CAARS:S[42] | |||||
Beutel et al[43] | To present the assessment and clinical characterisation of individuals seeking help for computer and Internet addiction via a telephone hotline | N = 346 phone consultations (85.8% relatives, 14.2% persons affected) | Telephone consultations | Skala zum Computerspielverhalten [CSV-S (Scale for the Assessment of Pathological Computer Gaming)][44] | Consultation mainly sought by relatives (86% mothers) |
48% reported achievement failure and social isolation, lack of control (38%), family conflicts (33%) | |||||
n = 131 patients (M = 21.9, SD = 6.6, range 13-47 yr, 96.2% male) | First diagnostic interview with expert clinicians | Symptom-Checklist SCL-90-R[45] | 96% of patients (n = 131) met criteria for pathological computer gaming | ||
Specialised clinic for behavioural addictions in Germany | |||||
Bipeta et al[46] | To compare control subjects with or without Internet addiction with patients with pure obsessive compulsive disorder with or without Internet addiction | n = 34 control subjects with or without Internet addiction (age M = 26.9, SD = 6.6 yr) | OCD patients treated for 1 year with standard pharmacological treatment for OCD (TAU), received clonazepam, tapered off in three weeks, and an SSRI or clomipramine | Youngs Diagnostic Questionnaire[47] | 11 OCD patients (28.95%) diagnosed with IA compared to 3 control subjects |
n = 38 patients with obsessive compulsive disorder with or without Internet addiction (age M = 27.0, SD = 6.1 yr) | IA OCD group: 5 received 150-200 mg fluvoxamine/d, 4 received 150-200 mg sertraline/d, 1 received 60 mg fluoxetine/d, 1 received 200 mg clomipramine/d | IAT[48] | OCD group, no difference in OCD scores btw IA/OCD and non-IA/OCD groups | ||
Non-IA OCD group: 8 received 150-300 mg fluvoxamine/d, 5 received 100-200 mg sertraline/d, 11 received 40-80 mg fluoxetine/d, 3 received 150-200 mg clomipramine/d | Diagnostic and Statistical Manual of Mental Disorders, DSM-IV (psychiatric interview)[12] | IA scores higher in IA/OCD group | |||
BIS-11[49] | Treatment improved test scores | ||||
YBOCS[30] | At 12 mo, 2/11 patients with OCD fulfilled IA criteria | ||||
Claes et al[50] | To investigate the association among CB, CIU, and reactive/regulative temperament in patients with ED | n = 60 female patients with eating disorders in the Netherlands (38.3% with Anorexia nervosa, 6.7% with Anorexia binging-purging type, 26.7% with bulimia nervosa, and 28.3% with Eating Disorder not otherwise specified; age range 15-57 yr, mean age = 27.8, SD = 9.8 yr) | N/A | DSM-IV, standardised clinical interview[51] | Positive association btw CB and CIU, emotional lability, excitement seeking, lack of effortful control (lack of inhibitory and lack of activation control) |
EDI-2[52,53] | 11.7% of CB patients with IA | ||||
CBS[54] | No significant differences between ED subtypes regarding CIU | ||||
Dutch Compulsive Internet Use Scale[55] | |||||
BIS/BAS scales[56,57] | |||||
DAPP[58,59] | |||||
Adult Temperament Questionnaire-Short Form[60,61] | |||||
Cruzado Díaz et al[62] | To describe clinical and epidemiological characteristics of inpatients in a clinical centre in Perú between 2001-2006 | n = 30 patients with “IA“ 90% devoted themselves to online games) in Perú | N/A | Reviewed 30 clinical registers through FEIA[63], a semi-structured instrument for psychiatric evaluation applied to clinical histories | Patient characteristics: |
Young age (18.3 ± 3.8 yr old) | |||||
All single males from 13 to 28 yr old (M = 18.3, SD = 3.8), 63.3% with secondary education completed and 66.7% dropped out | Patients completed a brief survey through an interview regarding information about their Internet use and online behaviours | Extensive daily Internet use (50% remained online for more than 6 h/d) | |||
Descriptive, retrospective and transversal study | Primary Internet use: Online gaming (43.3% excessive gaming and 6.7% excessive gambling) | ||||
Comorbidities (DSM-IV): High frequency of psychopathic behaviours (antisocial personality traits: 40%), 56.7% affective disorders (30% major depression and 26.7% dysthymia), 26.7% other addictions (13.3% gambling, 10% alcohol, 10% marihuana, 6.7% nicotine and 3.3% cocaine), 16.7% antisocial disorders (13.3% ADHD, social phobia 10% and 3.3% dysmorphic corporal disorder) | |||||
DellOsso et al[20] | To assess the safety and efficacy of escitalopram in IC-IUD using a double-blind placebo-controlled trial | n = 19 adult subjects (12 men, mean age = 38.5, SD = 12.0 yr) with IC-IUD (as primary disorder) | Escitalopram started at 10 mg/d, increased and maintained at 20 mg/d for 10 wk | Structured Clinical Interview for DSM-IV Axis I[64] | Following double-blind phase, there were no significant differences in weekly non-essential Internet use and overall clinical response between treatment and placebo group |
19 wk prospective trial with 2 consecutive phases: 10 wk treatment phase (n = 17, 11 men, mean age = 37.5, SD = 12.0 yr = and 9 wk randomised double-blind placebo controlled trial (n = 14, 10 men, mean age = 40.0, SD = 11.5 yr) | Subsequently, participants randomly assigned to placebo or escitalopram for 9 wk | Time spent in non-essential Internet use (hours/wk) | |||
CGI-I[35] | Side effects: Fatigue and sexual side effects in treatment, but not placebo group | ||||
BIS[49] | |||||
IC-IUD version of YBOCS[30] | |||||
Du et al[65] | To evaluate the therapeutic effectiveness of group CBT for Internet addiction in adolescents | n = 56 adolescents with IA (age range 12-17 yr) | Group cognitive behavioural therapy: | Beards Diagnostic Questionnaire for Internet addiction[66] | Internet use decreased in both groups |
n = 32 active treatment group (28 male, mean age = 15.4, SD = 1.7 yr) | Active treatment group: 8 1.5-2 h sessions of multimodal school-based group CBT with 6-10 students/group run by two child and adolescent psychiatrists (topics: Control, communication, Internet awareness, cessation techniques); group CB parent training; psychoeducation delivered to teachers | Internet Overuse Self-Rating Scale[67,68] | Only treatment group had improved time management skills and better emotional, cognitive and behavioural symptoms | ||
Time Management Disposition Scale[69] | |||||
Strength and Difficulties Questionnaire (Chinese edition)[70] | |||||
n = 24 clinical control group (17 male, mean age = 16.6, SD = 1.2 yr) | Clinical control group: No intervention | SCARED[71] | |||
Dufour et al[72] | To describe the sociodemographic characteristics of Internet addicts in a CDR, and to document their problems associated with other dependencies (alcohol, drugs, game practices), self-esteem, depression and anxiety | n = 57 Internet addiction treatment seekers (88.4% males, 11.6% females; age range = 18-62 yr (M = 30.5, SD = 11.8 yr). | N/A | IAT[48,73] | 88% of Internet addicts were male, with a mean age of 30, living with their parents with low income |
Canada | Becks Anxiety inventory[74] | M = 65 h of Internet use per week: 57.8% MMORPGs, 35,1% video streaming, and 29.8% chat rooms | |||
Becks Depression inventory[75] | Rosenberg test: 66.6% weak and very weak self-esteem; Depression in only 3.5% and anxiety in 7.5% | ||||
DÉBA-Alcohol/Drugs/Gaming[76] | 45.6% received pharmacological treatment for mental disorders (psychotropic) and 33.3% had a chronic physical problem | ||||
Self-esteem[77] | |||||
Duven et al[78] | To investigate whether an enhanced motivational attention or tolerance effects are reported by patients with IGD | n = 27 male clinical sample from specialised behavioural addiction centre in Germany (n = 14 with IGD, n = 13 casual computer gamers) | N/A | AICA-S[44] | Attenuated P300 for patients with IGD in response to rewards relative to a control group |
Semi-natural EEG designed with participants playing a computer game during the recording of event-related potentials to assess reward processing | SCL-90-R[45] | Prolonged N100 latency and increased N100 amplitude, suggesting tolerance during computer game play, and gaming reward attention uses more cognitive capacity in patients | |||
Floros et al[79] | To assess the comorbidity of IAD with other mental disorders in a clinical sample | n = 50 clinical sample of college students presenting for treatment of IAD in Greece (39 males, mean age = 21.0, SD = 3.2 yr; 11 females, mean age = 22.6, SD = 4.5 yr) | N/A | OCS[80] | 25/50 presented with comorbidity of another Axis I disorder (10% with major depression, 5% with dysthymia and psychotic disorders, respectively), and 38% (19/50) with a concurrent Axis II personality disorder (22% with narcissistic, and 10% with borderline disorder) |
DSQ[81] | |||||
ZKPQ[82,83] | |||||
SCL-90[84,85] | |||||
Cross-sectional study | The majority of Axis I disorders (51.85%) were reported before IAD onset, 33.3% after onset | ||||
Ge et al[86] | To investigate the association between P300 event-related potential and IAD | n = 41 IAD subjects (21 males, age M = 32.5, SD = 3.2 yr) | CBT | Standard auditory oddball task using American Nicolet BRAVO Instrument | IA individuals had longer P300 latencies, but similar P300 amplitudes compared to controls |
n = 48 volunteers (25 males, age M = 31.3, SD = 10.5 yr) | Following treatment, P300 latencies decreased significantly, suggesting cognitive function deficits associated with IAD can be ameliorated with CBT | ||||
Experimental task | |||||
Han and Renshaw[21] | To test whether bupropion treatment reduces the severity of EOP and MDD | n = 50 male subjects with EOP and MDD (aged 13-45 yr) | Random allocation to either bupropion and EDU group or placebo and EDU group | Structured Clinical Interview for DSM-IV[64] | During active treatment period, Internet addiction, gaming, and depression decreased relative to placebo group |
n = 25 treatment group (mean age = 21.2, SD = 8.0 yr, range = 13-42) | 12-wk treatment (8 wk active treatment phase and 4-wk post treatment follow-up period) | Youngs Internet Addiction Scale[87,88] | During follow-up, bupropion-associated reductions in gaming persisted, while depressive symptoms recurred | ||
n = 25 placebo group (mean age = 19.1, SD = 6.2 yr, range = 13-39) | |||||
Randomised controlled double-blind clinical trial | 150 mg/d Bupropion SR given and increased to 300 mg/d during first week | Becks Depression Inventory[89] | |||
Han et al[24] | To test the effects of bupropion sustained release treatment on brain activity for Internet video game addicts | n = 11 IAG (IAG; mean age = 21.5, SD = 5.6 yr; mean craving score = 5.5, SD = 1.0; mean playing time = 6.5, SD = 2.5 h/d; mean YIAS score = 71.2, SD = 9.4) | Placebo group started with one pill and then raised to two pills | Structured Clinical Interview for DSM-IV[64] | Bupropion sustained release treatment works for IAG in a similar way as it works for patients with substance dependence |
n = 8 HC (HC; mean age = 11.8, SD = 2.1 yr; mean craving score = 3.9, SD = 1.1; mean Internet use = 1.9, SD = 0.6 h/d; mean YIAS score = 27.1, SD = 5.3) in South Korea | Buproprion sustained release treatment: 6 wk | Beck Depression Inventory[89] | During exposure to game cues, IAG had more brain activation in left occipital lobe cuneus, left dorsolateral prefrontal cortex, left parahippocampal gyrus relative to HC | ||
Youngs Internet Addiction Scale[87] | |||||
Experimental design | Participants underwent 6 wk of bupropion sustained release treatment (150 mg/d for first week, 300 mg/d afterwards) | Craving for Internet video game play: 7-point visual analogue scale | After treatment, craving, play time, cue-induced brain activity decreased in IAG | ||
Brain activity measured at baseline and after treatment using 1.5 Tesla Espree fMRI scanner | |||||
Han et al[22] | To assess the effect of methylphenidate on Internet video game play in children with ADHD | n = 62 children (52 males, mean age = 9.3, SD = 2.2 yr, range = 8.12), drug-naïve, diagnosed with ADHD, and Internet video game players in South Korea | Treatment with Concerta (OROS methylphenidate HCI, South Korea) | YIAS-K[87,88] | Following treatment, Internet addiction and Internet use decreased |
Initial dosage: 18 mg/d, and maintenance dosage individually adjusted based on changes in clinical symptoms and weight | Korean DuPaul's ADHD Rating Scale[90,91] | ||||
Changes in IA between baseline and treatment completion correlated with changes in ADHD, and omission errors from the Visual Continuous Performance Test | |||||
Visual Continuous Performance Test using the Computerised Neurocognitive Function Test[92] | |||||
Hwang et al[93] | To directly compare patients with IA to patients with AD regarding impulsiveness, anger expression, and mood | n = 30 patients with IA (mean age = 22.7, SD = 6.7 yr) | N/A | Korean version of Youngs IAT[48,94] | IA and AD groups showed lower agreeableness and higher neuroticism, impulsivity, and anger expression compared to the HC group (all related to aggression) |
n = 30 patients with AD (mean age = 30.0, SD = 5.9 yr) | SCID[64] | Addiction groups had lower extraversion, openness to experience, and conscientiousness, were more depressive and anxious than HCs | |||
n = 30 HCs (HCs, mean age = 25.3, SD = 2.8 yr) | Alcohol Use Disorder Identification Test-Korean version[95] | Severity of IA and AD positively correlated with these symptoms | |||
Outpatient clinic in South Korea | Korean version of the NEO-PI-R[96,97] | ||||
Korean version of the BIS-11[98,99] | |||||
Korean version of the STAXI-K[100,101] | |||||
Kim[23] | To examine the effect of a reality therapy (R/T) group counselling programme for Internet addiction and self-esteem | n = 25 university students in South Korea (20 males, mean age = 24.2 yr) | Treatment group (n = 13, 10 males): Participated in R/T group counselling programme, 2 60-90 min sessions/wk for 5 consecutive weeks (with the purpose of taking control and changing thinking and behaviours) | K-IAS[102] | Treatment programme reduced addiction level and increased self-esteem |
CSEI[103] | |||||
Randomised controlled trial/quasi- experimental design | |||||
Control group (n = 12, 10 males): No treatment | |||||
Kim et al[25] | To evaluate the efficacy of CBT combined with bupropion for treating POGP in adolescents with MDD | n = 65 adolescents with MDD and POGP in South Korea (aged 13-18 yr) | n = 32 CBT group (medication and CBT): 8 wk intervention; 159 mg bupropion/d for 1 wk, then 300 mg/d for 7 wk; participated in 8 session weekly group CBT; weekly 10 min interviews | BDI[89] | Internet addiction decreased and life satisfaction increased in CBT and medication group relative to medication only group, but no changes in depression |
BAI[74] | |||||
YIAS[87,88] | |||||
Modified-School Problematic Behaviour Scale[104] | Anxiety increased in medicated group | ||||
Prospective trial | n = 33 clinical control group (medication only, as above) | Modified Students Life Satisfaction scale[105] | |||
Kim et al[106] | To investigate the value of Youngs IAT for subjects diagnosed with Internet addiction | n = 52 individuals presenting with Internet addiction at university hospital in South Korea (47 males; mean age = 21.7, SD = 7.1 yr, range: 11-38) | N/A | Clinical interview | Samples mean IAT score below cut-off (70) |
Youngs IAT[107,108] | |||||
Classification of IA severity via DSM-IV-TR[12] | IAT detected only 42% of sample as having Internet addiction | ||||
No significant differences in IAT scores between mild, moderate and severe Internet addition found | |||||
No association between IAT scores and Internet addiction duration of illness found | |||||
IAT has limited clinical utility for evaluating IA severity | |||||
Kim et al[109] | To compare patients with IGD with patients with AUD and HC regarding resting-state ReHo | n = 45 males seeking treatment in South Korea | N/A | Youngs IAT[87] | Significantly increased ReHo in PCC of the IGD and AUD groups |
n = 16 IGD patients (mean age = 21.6, SD = 5.9 yr) | SCID[64] | Decreased ReHo in right STG of IGD, compared with AUD and HC groups | |||
n = 14 AUD patients (mean age = 28.6, SD = 5.9 yr) | AUDIT-K[110] | Decreased ReHo in anterior cingulate cortex of AUD patients | |||
n = 15 HCs (mean age = 25.4, SD = 5.9 yr) | BDI[89] | Internet addiction severity positively correlated with ReHo in medial frontal cortex, precuneus/PCC, and left ITC in IGD | |||
BAI[74] | Impulsivity negatively correlated with ReHo in left ITC in IGD | ||||
BIS-11[111] | Increased ReHo in PCC: Neurobiological feature of IGD and AUD | ||||
FMRI resting data acquired via Philips Achieva 3-T MRI scanner using standard whole-head coil, obtaining 180 T2 weighted EPI volumes in each of 35 axial planes parallel to anterior and posterior commissures | Reduced ReHo in STG: Neurobiological marker for IGD specifically relative to AUD and HCs | ||||
King et al[112] | To present a case study of an individual with GPIU | n = 1, 16-yr old male in Australia | N/A | N/A | PIU identified due to: (1) use of several different Internet functions; (2) social isolation; (3) procrastination and time-wasting tendencies |
Case study | Problems unlikely to have occurred without the Internet | ||||
Ko et al[113] | To evaluate the diagnostic validity of IGD criteria, and to determine the cut-off point for IGD in DSM-5 | n = 225 adults in Taiwan (n = 75 individuals with IGD (63 males, mean age = 23.4, SD = 2.6 yr), no IGD (63 males, mean age = 22.9, SD = 2.5 yr), and IGD in remission (63 males, mean age = 23.8, SD = 2.9 yr), respectively) | N/A | Diagnostic interview based on DSM-5 IGD criteria[7] | Diagnostic accuracy of DSM-5 IGD items between 77.3% and 94.7% (except for deceiving and escape), and differentiated IGD from remitted individuals |
DC-IA-C[114] | Meeting ≥ 5 IGD criteria: Best cut-off point to differentiate IGD from non-IGD and remitted individuals | ||||
Chinese version of the MINI[115] | |||||
QGU-B[116] | |||||
CIAS[117] | |||||
Liberatore et al[118] | To describe the prevalence of IA in a clinical sample of Latino adolescents receiving ambulatory psychiatric treatment | n = 71 adolescent patients in Puerto Rico (39 males, aged 13-17 yr), 39.4% diagnosed with disruptive disorder, 31.0% with mood disorder, 19.7% with mood and disruptive disorder | N/A | Spanish version of the Internet Addiction Test (IAT)[87] | Sample did not involve any cases of severe IA |
71.8% of the sample had no IA problem | |||||
11.6% discussed Internet use with therapists | |||||
IA correlated with mood disorders | |||||
Liu et al[119] | To test the effectiveness and underlying MFGT | n = 92 (46 adolescents with 12-18 yr old, and 46 parents, aged 35-46 yr old) | MFGT is a new approach to treat Internet addiction (IA) behaviours that has not been tested before | Structured questionnaires at pre-test (T1), post-test (T2) and follow-up (T3): | Significantly decreased IA in EG at T2 and maintained in T3 (adolescents IA rate dropped from 100% at baseline to 4.8% after intervention, then remained at 11.1%) |
2 groups: 1 experimental (EG; MFGT adolescents and parents) and 1 control (CG; waiting-list similar adolescents and parents) | MFGT = group therapy for families, both adults and adolescents that have the same problem (IA) | Adolescents scales: | |||
Significantly better reports in the EG from adolescents and parents compared with those in the CG | |||||
Adolescent Pathological Internet Use Scale APIUS[120] | Underlying mechanism of less IA was partially explained by adolescent satisfaction of their psychological needs and improved parent-adolescent communication and closeness | ||||
EG: Adolescents: 17 males and 4 females (age: M = 15, SD = 1.73); | Advantage: Peer group (support and learn from peer confrontation) | Parents scales: | |||
Parents: 5 males and 16 females (age: M = 40.9, SD = 2.85) | Transference reactions occur within and between families | Closeness to Parents[121] | |||
CG: Adolescents: 21 males and 4 females (age: M = 15.7, SD = 1.2); Parents: Idem to EG (no sign. Diff). | Parent-Adolescent Communication Scale[122] | ||||
China | College Students Psychological Needs and Fulfillment Scale[123] | ||||
Quasi-experimental design | |||||
Müller et al[124] | To characterize German treatment seekers and to determine the diagnostic accuracy of a self-report scale for | n = 290 mostly male (93.8%) treatment seekers between 18 and 64 yr (M = 26.4, SD = 8.22) | Treatment of behavioural addictions | SCL-90R[125] | 71% met clinical IA diagnosis |
PHQ[126] | Displayed higher levels of psychopathology, especially depressive and dissociative symptoms | ||||
IA | Germany | Non-experimental design | GAD-7[127] | Half met criteria for one further psychiatric disorder, especially depression | |
CDS-2[128] | Level of functioning decreased in all domains | ||||
AICA-S showed | |||||
AICA-S[129] | good psychometric properties and satisfying diagnostic accuracy (sensitivity: 80.5%; specificity: 82.4%) | ||||
Müller et al[130] | To compare personality profiles of a sample of patients in different rehabilitation centres | IA group: 70 male patients with an addiction disorder that additionally met the criteria for IA; M =29.3 yr (SD = 10.66; range 16-64) | N/A | Computer game | Patients with comorbid IA can be discriminated from other patients by higher neuroticism and lower extraversion and lower conscientiousness |
Non-experimental design | Addiction (AICA-S)[129] | ||||
AD group: 48 male patients suffering from AD; M = 31.7 yr; SD = 9.18; range 17-65) | NEO-FFI[131] | After controlling for depressive symptoms, lower conscientiousness turned out to be a disorder-specific risk factor | |||
Germany | BDI-II[132] | ||||
Müller et al[133] | To evaluate the relationships between personality traits and IGD | n = 404 males aged 16 yr and above | N/A | AICA-S[44] | IGD associated with higher neuroticism, decreased conscientiousness and low extraversion |
4 groups: | Experimental design: Characteristics of people selected for assigning them to two groups, non-random allocation | The comparisons to pathological gamblers indicate that low conscientiousness and low extraversion in particular are characteristics of IGD | |||
IGD group: 115 patients with IGD | AICA-C[134] | Etiopathological model proposed for addictive online gaming | |||
Clinical CG: 74 controls seeking treatment for IGD, but not diagnosable | Berlin Inventory for Gambling[135] | ||||
Gambling group: 115 gambling patients | NEO Five-Factor Inventory[131] | ||||
Healthy CG: 93 individuals with regular or intense use of online games | |||||
Germany | |||||
Park et al[136] | To examine the effectiveness of treating an Internet-addicted young adult suffering from interpersonal problems based on the MRI interactional model and Murray Bowen's family systems theory | 1 family case study consisting of husband (age 50), wife (age 50), 2 sons (ages 22, 23), older son with Internet addiction and interpersonal problems | Comparative analysis method | Characteristics of the parents family of origin and dysfunctional communication pattern associated with interpersonal problems revealed by participants | |
South Korea | Miles and Huberman's matrix and network[137] | Both the MRI model and Bowen's family systems theory produced effective treatments | |||
Poddar et al[138] | To describe a pilot intervention using MET and CBT principles to treat IGD in an adolescent | n = 1 | Initial therapy session: Rapport building with patient, detailed interview, primary case formulation | IQ ESDST, | IGD due to child neglect and boredom, consolidated by subsequent negative reinforcements |
14-yr-old boy | Subsequent sessions: Psychoeducation, cost/benefit analysis of behaviour (motivation level improved) | BVMGT, and TAT | |||
India | Progressive muscle relaxation because gaming urge accompanied by physiological/emotional arousal | IAT | Individual interventions encouraged as there are varied antecedents and consequences for IGD development | ||
Case study | MET-CBT principles for IGD resulted in improvement | ||||
Subsequently: Game addiction assessment, contract for behaviour modification (reduce gaming time, increase other activities) | Therapy terminated when gains had consolidated | ||||
Tokens introduced as positive reinforcement | Good exam scores achieved | ||||
Less time spent gaming on weekdays, but excess on weekends | Weekend gaming times reduced | ||||
Patient recorded Thoughts, | IAT score reduced to 48 (from 83) | ||||
Emotions and Behaviors (TE and B) contributing to gaming (result: Gaming due to boredom) | |||||
Non-gaming behaviour reinforced via scooty rides | |||||
Santos et al[139] | To describe a treatment of a patient with PD, OCD (both anxiety disorders) and IA involving pharmacotherapy and CBT and test its efficacy | Case report | Pharmacotherapy and CBT | Hamilton Anxiety Scale (HAMA-A)[40] | Treatment effective for anxiety and IA |
n = 1 | CBT 1x/week for 10 wk | Hamilton Depression Scale (HAM-D)[39] | |||
24-yr-old Caucasian woman | Pharmacotherapy [clonazepam (0.5 mg) and sertraline (50 mg) once daily] | Chambless BSQ[140] | |||
A patient with PD, OCD and IA | Both (pharmaco and CBT) started together | Bandelow PA[141] | |||
Brazil | CBT focus: Teach patient how to deal with anxiety and internet use (i.e., breathing retraining with diaphragmatic breathing exercise, education about PD and OCD symptoms and internet use, time management, identifying PIU triggers, changing habits, cognitive restructuring, exposure and response prevention, social support promotion, building alternative activities, functional internet use promotion) | IAT | |||
CGI[142] | |||||
Senormanci et al[143] | To investigate the attachment styles and family functioning of patients with IA | n = 60 | N/A | IAT[48] | Patients with IA had higher BDI and higher attachment anxiety sub-scores on the ECR-r compared with those in the CG |
2 groups: | BDI[89] | ||||
EG: 30 male patients with IA [age: M = 21.6 (18-20) yr] | Experiences in Close Relationships Questionnaire-r [144] | IA patients evaluated their family functioning as more negative and reported problems in every aspect addressed by the FAD | |||
CG: 30 healthy males without IA | |||||
Non-experimental | Family Assessment Device[145] | Scores on the FAD behaviour control, affective responsiveness, and problem-solving subscales (and on the FAD communication, roles, and general functioning subscales) significantly higher in patients compared with CG | |||
Senormanci et al[146] | To determine the predictor effect of depression, loneliness, anger and interpersonal relationship styles for IA in patients diagnosed with IA | n = 40 male IA patients with at least 18-yr-old | N/A | IAT[48] | Duration of Internet use (hours/day) and STAXI anger in subscale predicted IA. Although the duration is not adequate for IA diagnosis, it predicts IA |
Turkey | BDI[89] | It is helpful for clinicians to regulate the hours of Internet use for patients with excessive or uncontrolled internet use | |||
STAXI[100] | |||||
UCLA Loneliness Scale[147] | |||||
IRSQ, subscale “Contributing and inhibiting styles”[148] | Psychiatric treatments for expressing anger and therapies focussing on emotion validation may be useful | ||||
Shek et al[149] | To described an indigenous multi-level counselling programme designed for young people with IA problems based on the responses of clients | n = 59 | Indigenous multilevel counselling program designed to provide services for young people with Internet addictive behaviour in Hong Kong: | 3 versions of IA Young's assessment tools[150]: 10-item, 8-item and 7-item measures[151-153] | The outcome evaluation, pretest and posttest data showed IA problems decreased after joining programme |
58 male and 1 female | (1) Emphasis on controlled and healthy use of the Internet; (2) Understanding the change process in adolescents with Internet addiction behaviour; (3) Utilization of motivational interviewing model; (4) Adoption of a family perspective; (5) Multi-level counselling model; (6) Utilization of case work and group work | Goldberg's framework[154] | |||
Most in early adolescence (aged 11-15 yr; n = 29) and late adolescence (aged 16-18 yr; n = 27), while 3 were over 18 | Chinese Internet Addiction Scale (CIA-Goldberg) | Slight positive changes in parenting attributes | |||
China | Items for assessing beliefs and behaviours for using Internet: 7 items from Computer Use Survey[155] | Participants subjectively perceived the programme was helpful | |||
6 items from OCS[80] | |||||
6 items from Internet Addiction-Related Perceptions and Attitudes Seale[156] | |||||
2 items from IAD-Related Experience Scale[157] | |||||
33-item C-FAI developed[158] | |||||
Chinese Purpose in Life Questionnaire[159] | |||||
Chinese Beck Depression Inventory[160] | |||||
Chinese Hopelessness Seale[161] | |||||
Chinese Rosenberg Self-Esteem Seale[162] | |||||
Tao et al[163] | To develop diagnostic criteria for IAD and to evaluate the validity of proposed diagnostic criteria for discriminating non-dependent from dependent Internet use in the general population | 3 stages: Criteria development and item testing; criterion-related validity testing; global clinical impression and criteria evaluation; | N/A | N/A: Authors developed the proposed Internet addiction diagnostic criteria, which have been one of the main sources for the APAs IGD criteria | Proposed Internet addiction diagnostic criteria: Symptom criterion (7 clinical IAD symptoms ), clinically significant impairment criterion (functional and psychosocial impairments), course criterion (duration of addiction lasting at least 3 mo, with at least 6 h of non-essential Internet use per day) and exclusion criterion (dependency attributed to psychotic disorders) |
Stage 1: n = 110 patients with IA in SG, M = 17.9 SD = 2.9 yr (range: 12-30 yr), 91.8% (n = 101) males; 408 patients in IA in TG, M = 17.6, SD = 2.7 yr (range: 12-27 yr), 92.6% (n = 378) male; Stage 2: n = 405; Stage 3: n = 150 (M = 17.7, SD = 2.8, (92.7% males) | Diagnostic score of 2 + 1, where first 2 symptoms (preoccupation and withdrawal symptoms) and min. 1/5 other symptoms (tolerance, lack of control, continued excessive use despite knowledge of negative effects/affects, loss of interests excluding Internet, and Internet use to escape or relieve a dysphoric mood) was established | ||||
China | Inter-rater reliability: 98% | ||||
Te Wildt et al[164] | To examine the question whether the dependent use of the Internet can be understood as an impulse control disorder, an addiction or as a symptom of other psychiatric conditions | EG: n = 25 patients (76% male, M = 29.36 yr, SD = 10.76) | 2 groups matched: The EG and CG | Preliminary telephone interview to test inclusion criteria with Young's and Beard's IA criteria[48,66] | Compared to controls, patient group presented significantly higher levels of depression (BDI), impulsivity (BIS) and dissociation (DES) |
CG: Matched for age (M = 29.48; SD = 9.56), sex (76% males) and school education, and similar level of intelligence | Non-experimental design | Statistical Clinical Interview for DSM-IV[64] | PIU shares common psychopathological features and comorbidities with substance-related disorders | ||
German Internet Addiction Scale ISS[165] | |||||
German version of the Barratt Impulsiveness Scale BIS[49] | Should be viewed as diagnostic entity in itself within a spectrum of behavioural and substance dependencies | ||||
Derogatis Symptom Checklist (SCL-90-R)[166,167] | |||||
BDI[89,168] | |||||
DES[169,170] | |||||
SOC[171,172] | |||||
IIP-D[173,174] | |||||
Tonioni et al[26] | To test whether patients with IA present different psychological symptoms, temperamental traits, coping strategies and relational patterns relative to patients with PG | Two clinical groups: | N/A | IAT[48] | IA and PG had higher scores than control group on depression, anxiety and global functioning |
31 IA patients (30 males) and 11 PG patients (10 males) and a control group (38 healthy subjects; 36 males) matched with the clinical groups for gender and age were enrolled | Hamilton Anxiety Rating Scale[40] | IA patients had higher mental and behavioural disengagement associated with an important interpersonal impairment relative to PG patients | |||
Hamilton Depression Scale[39] | IA and PG groups used impulsive coping, and had socio-emotional impairment | ||||
Global Assessment of Functioning[112] | |||||
Snaith-Hamilton Pleasure Scale[175] | |||||
Temperament and Character Inventory-Revised[176] | |||||
Coping Orientation to Problems Experienced[177] | |||||
Inventory of Parent and Peer Attachment[178] | |||||
Tonioni et al[27] | To investigate psychopathological symptoms, behaviours and hours spent online in patients with IAD | n = 86: 21 clinical patients in hospital-based psychiatric IAD service (mean age=24, SD = 11 yr); 65 control subjects | N/A | Internet addiction interview[47] | IAD patients had significantly higher scores on IAT relative to controls |
IAT[179] | Only item 7 (how often do you check your e-mail before something else that you need to do?) showed a significant inverse trend | ||||
Symptom Checklist-90-Revised[125] | SCL-90-R anxiety and depression scores and IAT item 19 (How often do you choose to spend more time online over going out with others?) positively correlated with weekly online hours in IAD patients | ||||
van Rooij et al[180] | To evaluate the pilot treatment for IA created for the Dutch care organization (to explore the possibility of using an existing CBT and MI based treatment programme (lifestyle training) from therapists experiences with 12 Internet addicts | n = 12 Internet addicts and n = 5 therapists treating them | Treatment: A manual-based CBT | Data sources: (1) Session Reports; (2) Case Review Meeting Minutes; (3) Questionnaires: | Therapists report programme (originally used for substance dependence and pathological gambling) fits problem of Internet addiction well |
The Netherlands | Standard Lifestyle Training programme, a manual-based treatment programme[181,182] | Compulsive Internet Use Scale (CIUS)[55] | Interventions focused on controlling and reducing Internet use, and involved expanding (real life) social contacts, regaining proper daily structure, constructive use of free time, and reframing beliefs | ||
Therapy combines CBT and MI[183,184] | Brief Situational Confidence questionnaire[187] | Therapist report: Treatment achieved progress for all 12 treated patients | |||
Focuses on eliciting and strengthening motivation to change, choosing a treatment goal, gaining self-control, relapse prevention, and coping skills training[185,186] | Patient report: Satisfaction with treatment and behavioural improvements | ||||
10 outpatient sessions of 45 min each, with 7 of these taking place within a period of 10 wk, the remaining 3 within a period of 3 mo | |||||
Each session: Introduction, evaluation of current status, discussing homework, explaining theme of the day, practicing a skill, receiving homework, and finally closing the session | |||||
Wölfling et al[188] | To investigate whether IA is an issue in patients in addiction treatment | n = 1826 clients in impatient centres | N/A | Internet and Computer Game Addiction (AICA-S)[189,190] | Comorbid IA associated with higher levels of psychosocial symptoms, especially depression, obsessive-compulsive symptoms, and interpersonal sensitivity |
Male patients meeting criteria for comorbid IA (EG; n = 71) compared with a matched control group of male patients treated for alcohol addiction without addictive Internet use (CG; n = 58) | Symptom Checklist 90R (SCL-90-R)[191] | ||||
PHQ[126] | IA patients meet criteria for additional mental disorders more frequently and display higher rates of psychiatric symptoms, especially depression, and might be in need of additional therapeutic treatment | ||||
GAD-7[127] | |||||
Germany | |||||
Wölfling et al[192] | To test the effects of a standardized CBT programme for IA | n = 42 patients with IA, all male from 16-yr-old (M = 26.1, SD = 6.60, range: 18-47) | Short-Term outpatient Treatment for Internet and Computer Game | Inclusion criteria: | 70.3% of patients completed therapy |
Addiction STICA (127) based on CBT techniques known from treatment programmes of other forms of addictive behaviour, consisting of 15 group sessions and additional 8 individual therapy sessions | AICA-S[193,194] | After treatment, symptoms of IA decreased significantly | |||
Standardized clinical interview of IA (AICA-C; Checklist for the Assessment of Internet and Computer Game Addiction)[132] | Psychopathological symptoms and associated psychosocial problems decreased | ||||
Individual sessions dealt with individual contents; group sessions followed clear thematic structure: First third of programme: Main themes about development of individual therapy aims, identification of Internet application associated with symptoms of IA, conducting holistic diagnostic investigation of psychopathological symptoms, deficits, resources, and comorbid disorders | GSE[195] | ||||
NEO Five-Factor Inventory[131] | |||||
Symptom Checklist 90R[196] | |||||
Motivational techniques applied to enhance patients intention to cut down dysfunctional behaviour | |||||
Second third: Psychoeducation elements; deepened Internet use behaviour analysis (focusing on triggers and patient reactions on cognitive, emotional, psychophysiological, and behavioural levels in that situation (SORKC scheme)[193] for development of a personalized model of IA for each patient based on interaction between online application, predisposing and maintaining factors of the patient (e.g., personality traits) and the patients social environment | |||||
Last stage: Situations with heightened craving for getting online further specified and strategies to prevent relapse developed | |||||
Wölfling et al[197] | To investigate the occurrence of BSD in patients with excessive Internet use and IA | n = 368 treatment seekers with excessive to addictive Internet use screened for bipolar spectrum disorders | N/A | AICA-S[194] | Comorbid BSD more frequent in patients meeting criteria for IA (30.9%) than among excessive users (5.6%) |
Germany | BSD assessed using MDQ[198] | This subgroup showed heightened psychopathological symptoms, including substance use disorders, affective disorders and personality disorders | |||
SCL-90R[199,200] | |||||
Further differences were found regarding frequency of Internet use regarding social networking sites and online-pornography in patients with BSD who engage more frequently | |||||
Patients with IA have heightened probability for meeting BSD criteria | |||||
Recommendation: Implement BSD screening in patients presenting with IA | |||||
Young[201] | To investigate the efficacy of using CBT with Internet addicts | n = 114 Internet addicts in treatment (42% women (mean age = 38; men mean age = 46) | Sessions conducted between client and principle investigator | IAT[48] | Preliminary analyses indicated most clients managed their presenting complaints by the eighth session |
Initial sessions gathered familial background, nature of presenting problem, its onset and severity | Self-devised Client Outcome Questionnaire administered after 3rd, 8th, and 12th online session, and at 6 mo follow-up: | Symptom management sustained at 6-mo follow-up | |||
CBT utilized to address presenting symptoms related to computer use, specifically abstinence from problematic online applications and strategies to control online use | 12 items regarding clients behaviour patterns and treatment successes during counselling process; questions rated how effective counselling was at helping clients achieve targeted treatment goals associated with Internet addiction recovery; questions assessed motivation to quit Internet abuse, ability to control online use, engagement in offline activities, improved relationship functioning, and improved offline sexual functioning (if applicable) | ||||
Counselling also focused on behavioural issues or other underlying factors contributing to online abuse, such as marital discord, job burnout, problems with co-workers, and academic troubles, depending on respective client | |||||
Young[202] | To test a specialized form of CBT, CBT-IA | n = 128 clients to measure treatment outcomes using CBT-IA (65% male; age range: 22-56 yr) | CBT-IA: 3-phase approach including behaviour modification to control compulsive Internet use, cognitive restructuring to identify, challenge, and modify cognitive distortions that lead to addictive use, and harm reduction techniques to address and treat co-morbid issues associated with the disorder | IAT[48] | Over 95% of clients managed symptoms at the end of the 12 wk period |
78% sustained recovery six months following treatment | |||||
Administered in 12 weekly sessions | CBT-IA ameliorated IA symptoms after 12 weekly sessions and consistently over 1, 3 and 6 mo after therapy | ||||
Sessions conducted between client and principle investigator | |||||
Initial sessions gathered familial background, | |||||
symptoms of the presenting problem, its onset, and severity | |||||
CBT-IA addressed presenting symptoms related to computer use, specifically abstinence from problematic online applications and strategies to control use | |||||
CBT-IA also focused on cognitive issues and harm reduction for underlying factors contributing to Internet abuse such as marital discord, job burnout, problems with co-workers, or academic troubles, depending on respective client | |||||
Internet use routinely evaluated and treatment outcomes evaluated after 12 sessions and at 1, 3 and 6 mo follow-up | |||||
Yung et al[203] | To improve IAD involving Google Glass through residential treatment for alcohol use disorder | n = 1 (31-yr-old man who exhibited problematic use of Google Glass) | Navys SARP | N/A regarding SARP and measures, only about his reactions (e.g., withdrawal, craving, etc.) | Following treatment, reduction in irritability, movements to temple to turn on device, and improvements in short-term memory and clarity of thought processes |
Case report | All electronic devices and mobile computing devices customarily removed from patient during substance rehabilitation treatment | ||||
United States | 35-d residential treatment | Patient continued to intermittently experience dreams as if looking through the device | |||
Zhou et al[204] | To examine whether Internet addicted individuals share impulsivity and executive dysfunction with alcohol-dependent individuals | n = 66 | N/A | BIS-11 | Impulsiveness scores, false alarm rate, total response errors, perseverative errors, failure to maintain set of IAD and AD group significantly higher than that of NC group |
22 IAD, 22 patients with AD, and 22 NC (NC consisting of citizens living in the city) | Go/no-go task | ||||
Wisconsin Card Sorting Test (Beijing Ka Yip Wise Development Co., Ltd, computerized version VI) | Hit rate, percentage of conceptual level responses, number of categories completed, forward scores, backwards scores of IAD and AD group significantly lower than that of NC group | ||||
China | Digit span task | ||||
Experimental design | Modified Diagnostic Questionnaire for Internet Addiction (YDQ)[66] | No differences in above variables between IAD group and AD group | |||
Structured clinical interview (Chinese version) | Internet addicted individuals share impulsivity and executive dysfunction with alcohol-dependent patients | ||||
SADQ[205] | |||||
Hamilton Depression Scale[206] | |||||
Barratts Impulsivity Scale (BIS-11)[49] | |||||
Zhu et al[207] | To observe the effects of CT with EA in combination with PI on cognitive function and ERP, P300 and MMN in patients with IA | n = 120 patients in China with IA randomly divided into 3 groups: | Overall treatment period = 40 d | Internet Addiction Test[208] | Following treatment, IA decreased in all groups |
n = 39 EA group (n = 40, 27 male, mean age = 22.5, SD = 2.1 yr) | EA applied at acupoints Baihui (GV20), Sishencong (EX-HN1), Hegu (LI4), Neiguan (PC6), Taichong (LR3), Sanyinjiao (SP6) and retained for 30 min once every other day | Wechsler Memory Scale (WMS)[209] | Decrease stronger in CT group relative to both other groups | ||
n = 36 PI group (n = 25 male, mean age = 21.0, SD = 2.0 yr) | PI with cognitive-behaviour mode every 4 d | ERP observation[210] using MEB 9200-evoked detector | P300 latency depressed and amplitude raised n EA group | ||
n = 37 CT group (n = 40, 27 males, mean age = 22.5, SD = 2.3 yr) | EA and PI used in CT group | Latency and amplitude of MMN and P300 recorded via EEG | MMN amplitude increased in CT group | ||
Short-term memory capacity and short-term memory span improved | |||||
EA and PI improves cognitive function in IA via acceleration of stimuli discrimination and information processing on brain level |
- Citation: Kuss DJ, Lopez-Fernandez O. Internet addiction and problematic Internet use: A systematic review of clinical research. World J Psychiatr 2016; 6(1): 143-176
- URL: https://www.wjgnet.com/2220-3206/full/v6/i1/143.htm
- DOI: https://dx.doi.org/10.5498/wjp.v6.i1.143