Compulsive use of Internet-based sexually explicit media: Adaptation and validation of the Compulsive Internet Use Scale (CIUS)

Downing, Martin J.; Antebi, Nadav; Schrimshaw, Eric W.

doi:10.1016/j.addbeh.2014.03.007

Cited by 36 publications

(29 citation statements)

References 29 publications

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“…Special attention to nomenclature was required here, as the disorder is studied under different headings. For example, in addition to the primary term of Internet Addiction, additional terms include “Compulsive Internet Use” [ 28 , 29 , 30 , 31 , 32 , 33 ], Internet Addiction Disorder [ 34 ], Internet Use Disorder [ 35 ], “Pathological Internet Use” [ 14 , 36 ], and “Problematic Internet Use” [ 37 , 38 , 39 , 40 , 41 , 42 ]. As such, the following search terms and their derivatives were used in multiple combinations: Addict*, compulsive, “compulsive internet”, cyber, Internet, “Internet use”, online, “pathological internet” and “problem* Internet” (to allow for problem and problematic).…”

Section: Methodsmentioning

confidence: 99%

Neuroscience of Internet Pornography Addiction: A Review and Update

Love¹,

Laier

Brand

et al. 2015

Behavioral Sciences

194

131

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Many recognize that several behaviors potentially affecting the reward circuitry in human brains lead to a loss of control and other symptoms of addiction in at least some individuals. Regarding Internet addiction, neuroscientific research supports the assumption that underlying neural processes are similar to substance addiction. The American Psychiatric Association (APA) has recognized one such Internet related behavior, Internet gaming, as a potential addictive disorder warranting further study, in the 2013 revision of their Diagnostic and Statistical Manual. Other Internet related behaviors, e.g., Internet pornography use, were not covered. Within this review, we give a summary of the concepts proposed underlying addiction and give an overview about neuroscientific studies on Internet addiction and Internet gaming disorder. Moreover, we reviewed available neuroscientific literature on Internet pornography addiction and connect the results to the addiction model. The review leads to the conclusion that Internet pornography addiction fits into the addiction framework and shares similar basic mechanisms with substance addiction. Together with studies on Internet addiction and Internet Gaming Disorder we see strong evidence for considering addictive Internet behaviors as behavioral addiction. Future research needs to address whether or not there are specific differences between substance and behavioral addiction.

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Section: Methodsmentioning

confidence: 99%

Neuroscience of Internet Pornography Addiction: A Review and Update

Love¹,

Laier

Brand

et al. 2015

Behavioral Sciences

194

131

View full text Add to dashboard Cite

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“…Advertisements instructed interested persons to click on an embedded link to an online survey. These procedures are similar to those used in past studies [68] , [73] . As in these other studies, the respondent sample may have been biased because the participants self selected.…”

Section: Methodsmentioning

confidence: 91%

Prescription Drug Diversion: Predictors of Illicit Acquisition and Redistribution in Three U.S. Metropolitan Areas

et al. 2015

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Objective Prescription drug diversion, the transfer of prescription drugs from lawful to unlawful channels for distribution or use, is a problem in the United States. Despite the pervasiveness of diversion, there are gaps in the literature regarding characteristics of individuals who participate in the illicit trade of prescription drugs. This study examines a range of predictors (e.g., demographics, prescription insurance coverage, perceived risk associated with prescription drug diversion) of membership in three distinct diverter groups: individuals who illicitly acquire prescription drugs, those who redistribute them, and those who engage in both behaviors. Methods Data were drawn from a cross-sectional Internet study ( N = 846) of prescription drug use and diversion patterns in New York City, South Florida, and Washington, D.C.. Participants were classified into diversion categories based on their self-reported involvement in the trade of prescription drugs. Group differences in background characteristics of diverter groups were assessed by Chi-Square tests and followed up with multivariate logistic regressions. Results While individuals in all diversion groups were more likely to be younger and have a licit prescription for any of the assessed drugs in the past year than those who did not divert, individuals who both acquire and redistribute are more likely to live in New York City, not have prescription insurance coverage, and perceive fewer legal risks of prescription drug diversion. Conclusion Findings suggest that predictive characteristics vary according to diverter group.

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“…Interested men are directed to the study website for more information and to be screened for eligibility. The research team has successfully used these methods in past research with MSM and MSMW [49,76,[79][80][81].…”

Section: Recruitment Strategymentioning

confidence: 99%