The role of impaired control in screening problematic pornography use: Evidence from cross-sectional and longitudinal studies in a large help-seeking male sample.

Abstract

In help-or treatment-seeking people, there may be a portion of individuals with self-perceived addiction; however, how to distinguish these individuals from help-seeking patients with dysregulated pornography use remains unclear. The present study sought to examine the specific role of impaired control in identifying individuals with self-perceived problems when screening problematic pornography use (PPU) in a large help-seeking male sample (N = 8,845; M age = 25.82 years, SD = 7.83). Based on the results of latent profile analysis, three groups were identified in the help-seeking sample: Self-perceived PPU group (n = 2,089; 23.6%), impaired control group (n = 4,180; 47.3%), and PPU group (n = 2,576; 29.1%). The self-perceived PPU group was characterized by the highest moral incongruence, but not objectively dysregulated in pornography use. The other two groups met the criteria of impaired control, suggesting that, impaired control may distinguish between self-perceived PPU and dysregulated use in help-seeking men. Six months later, self-reported data were collected again from 972 of these help-seeking men. The longitudinal cross-lagged analysis showed that impaired control at baseline positively predicted PPU at the 6-month follow-up; simultaneously, the reverse association was also significant and positive. In sum, impaired control functioned as a criterion to differentiate between self-perceived PPU and dysregulated pornography use. Impaired control might be used as a robust and reliable predictor of PPU, but it may not be a sufficient criterion of PPU in itself. Public Health Significance StatementImpaired control is a reliable feature when screening for problematic pornography use (PPU). Impaired control is a robust predictor of PPU over time. Impaired control may distinguish between individuals with self-perceived PPU and dysregulated PPU in help-seeking samples.

Hands-off: Feasibility and preliminary results of a two-armed randomized controlled trial of a web-based self-help tool to reduce problematic pornography use

“…It is important to note that similar attrition rates were observed in PPU treatment-seeking men in a recent study. Similarly to our results, only 11% of the participants completed the follow-up survey after participating in an app-based intervention for PPU (Chen, Jiang, Luo, Kraus, & B} othe, 2021). Based on follow-up interviews with participants dropping out from the study, several potential mechanisms were mentioned that might explain the high attrition, such as the unsuitability of reminders, feelings that pornography use-related problems did not change during the intervention, or using avoidance as a potential coping strategy (i.e., avoiding pornography-related content, including the follow-up surveys) (Chen et al, 2021).…”

“…As discussed above, several strategies (e.g., incentives) should be applied to retain higher adherence rates, providing the opportunity for more comprehensive analyses (e.g., including sexual wellbeing or general wellbeing, or other mental health-related variables). Lastly, no objective criteria were used to exclude participants from the study who had not demonstrated dysregulated, compulsive, or problematic pornography use, as the intervention was designed to be potentially effective in all groups of treatment-seeking individuals (e.g., individuals with dysregulated pornography use or individuals with self-perceived PPU due to moral incongruence towards pornography use) ( Chen et al, 2021 ; Grubbs, Perry, Wilt, & Reid, 2019 ; Kraus & Sweeney, 2019 ). Therefore, it is possible that some individuals might have realized that their pornography use is not problematic or might have simply been interested in the content of the intervention without any objective or self-perceived PPU, resulting in high dropout rates.…”

The Effect of Stress on Compulsive Sexual Behavior Disorder: Active Coping Strategy and Self-Control as Mediators

“…However, among the addicts with these problems, there are people with self-perceived addiction, and it is not yet clear how to distinguish these people from patients who seek help because their impulses are not controlled. 14 A person with high self-control learns appropriate skills or acts adaptively to meet social standards, while a person with low self-control is not able to set necessary longterm goals and is willing to act to gain immediate satisfaction. 15 It is thus more appropriate to describe compulsive sexual behavior disorder as a disorder or illness marked by an inability to control desire, rather than as a disorder in which the individual tries to indiscriminately dissipate sexual desire.…”

“…Self-control is involved in addiction because addiction is regarded as a problem of impulse control. However, among the addicts with these problems, there are people with self-perceived addiction, and it is not yet clear how to distinguish these people from patients who seek help because their impulses are not controlled [ 14 ]. A person with high self-control learns appropriate skills or acts adaptively to meet social standards, while a person with low self-control is not able to set necessary long-term goals and is willing to act to gain immediate satisfaction [ 15 ].…”

International Sex Survey: Study protocol of a large, cross-cultural collaborative study in 45 countries

“…For example, to identify compulsive and noncompulsive sexual behavior profiles, we will use the dimensions of the CSBD-19 as profile indicators, building on the ICD-11-based conceptualization of CSBD (World Health Organization, 2019) and previous LPA studies of CSBD (e.g., B} othe, T oth-Kir aly et al, 2020). In another LPA model, we will examine problematic and non-problematic pornography use profiles using the PPCS, BPS, frequency of pornography use, and moral incongruence towards pornography use as profile indicators, building on the engagement and moral incongruence models (Billieux, 2012;Billieux et al, 2019;, and previous empirical findings (B} othe, T oth- Kir aly, et al, 2020;Chen, Jiang, Luo, Kraus, & B} othe, 2021). The selection of the optimal number of classes will be guided by the theoretical meaningfulness and statistical adequacy of the extracted classes (Marsh, L€ udtke, Trautwein, & Morin, 2009), such as the Akaike Information Criterion, entropy, and Lo-Mendell-Rubin Adjusted Likelihood Ratio Test (Lubke & Muth en, 2007).…”