Problematic internet use (PIU): Associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry

Abstract

Problematic internet use is common, functionally impairing, and in need of further study. Its relationship with obsessive-compulsive and impulsive disorders is unclear. Our objective was to evaluate whether problematic internet use can be predicted from recognised forms of impulsive and compulsive traits and symptomatology. We recruited volunteers aged 18 and older using media advertisements at two sites (Chicago USA, and Stellenbosch, South Africa) to complete an extensive online survey. State-of-the-art out-of-sample evaluation of machine learning predictive models was used, which included Logistic Regression, Random Forests and Naïve Bayes. Problematic internet use was identified using the Internet Addiction Test (IAT). 2006 complete cases were analysed, of whom 181 (9.0%) had moderate/severe problematic internet use. Using Logistic Regression and Naïve Bayes we produced a classification prediction with a receiver operating characteristic area under the curve (ROC-AUC) of 0.83 (SD 0.03) whereas using a Random Forests algorithm the prediction ROC-AUC was 0.84 (SD 0.03) [all three models superior to baseline models p < 0.0001]. The models showed robust transfer between the study sites in all validation sets [p < 0.0001]. Prediction of problematic internet use was possible using specific measures of impulsivity and compulsivity in a population of volunteers. Moreover, this study offers proof-of-concept in support of using machine learning in psychiatry to demonstrate replicability of results across geographically and culturally distinct settings.

Perception of Sleep Disturbances due to Bedtime Use of Blue Light-Emitting Devices and Its Impact on Habits and Sleep Quality among Young Medical Students

“…Several studies showed the negative effects of bedtime blue light-emitting-device use on sleep due to its association to cognitive stimulation [1,4,6,7,[14][15][16][17][18] and/or to problematic excessive use [9,[18][19][20][21][22][23][24][25][26][27][28].…”

“…On the other hand, there is an emergent problematic and worrying excessive use of these new technologies in people of all ages reported by several studies [9,[18][19][20][21][22][23][24][25][26][27][28]. As we are all conscious of bedtime, wake time and the subjective quality of sleep, our appreciation of the importance of the sleep-wake cycle should be further enhanced when confronted with the consequences of its disruption [29].…”

Cognitive deficits in problematic internet use: meta-analysis of 40 studies

“…19 The current study extends beyond this prior meta-analysis by also considering the impact of study quality, and including a much larger range of available data. Problematic internet users are characterised by elevated behavioural impulsivity and compulsivity, 11,15 which are characteristics of a wide range of psychiatric disorders, including ADHD, OCD, impulse control and substance use disorders.…”

“…12 Based on empirical evidence, we define PIU as excessive online activities likely to be associated with marked functional impairment, including compulsive online buying, gambling, cybersex, as well as excessive use of online streaming and social media that have addictive, impulsive and/or compulsive elements. 11,13 Age may influence the presentation of PIU and its comorbidities. For example, one study found that attentiondeficit hyperactivity disorder (ADHD) and social anxiety were associated with PIU in young adults; whereas generalised anxiety disorder and obsessive-compulsive disorder (OCD) were associated with PIU in older adults.…”

Patologías asociadas al uso problemático de internet. Una revisión sistemática y metaanálisis en WOS y Scopus

“…Son varios los estudios que vinculan el UPI con el trastorno obsesivo-compulsivo (Derbyshire et al, 2013;Bozkurt et al, 2013;Burnay et al, 2015;Ioannidis et al, 2016;Bernal-Ruiz et al, El metaanálisis muestra un tamaño del efecto significativo a favor del grupo con UPI (p = .0004) (Figura 3), por lo que los dos estudios recogidos confirman que los sujetos con UPI presentan mayores puntajes en los instrumentos que miden el TOC.…”