Online Gambling A Systematic Review of Risk and Protective Factors in the Adult Population Journal

Online Gambling: A Systematic Review of Risk and Protective Factors in the Adult Population

In recent decades, Internet gambling has grown strongly and spreading with particularly attractive essential characteristics (ease of access, anonymity, games). The purpose of this paper is to introduce the current status of online gambling danger factors and protection factors. As a result of searching for Pubmed, Psychinfo, and Scopus databases, 42 papers were found, and they were reviewed. The methodological aspects, risk factors, and protection factors were analyzed across. The results related to risk factors and protection factors were distinguished by the analysis level of personal, relationship, and contextual. Two types of comparisons: online vs. offline gamblers and online no n-proble m-type gamblers vs. gambler. The results of the two comparisons were arranged, and the relationship between the consistency and the factor was analyzed. In general, reviews show that while the number of persona l-level danger factors and variables is being studied, the relevant and context protection factors require more detailed research in future research. Ta. More specifically, this review has revealed that online and offline gamblers share most risk factors and protection factors, but there are variables that both are common. These factors can be an important factor to be considered in ant i-gamblers and online gamblers.

The Prevalence and Clinical and Sociodemographic Factors of Problem Online Gambling: A Systematic Review

January 29, 2021

Emerging Gambling Problems and Suggested Interventions: A Systematic Review of Empirical Research

April 23, 2022

Preventive Interventions and Harm Reduction in Online and Electronic Gambling: A Systematic Review

August 24, 2022 article

Avoid mistakes that are common in manuscripts. In recent decades, Internet gambling has become a powerful growth and popularity due to its particularly attractive essential characteristics (ease of access, anonymity, game diversity). Has been achieved. The purpose of this paper is to introduce the current status of online gambling danger factors and protection factors. As a result of searching for Pubmed, PSYCHINFO, and SCOPUS databases, 42 papers were found, and they were reviewed. The methodological aspects, risk factors, and protection factors were analyzed across. The results related to risk factors and protection factors were distinguished by the analysis level of personal, relationship, and contextual. Two types of comparisons: online vs. offline gamblers and online no n-proble m-type gamblers vs. gambler. The results of the two comparisons were arranged, and the relationship between the consistency and the factor was analyzed. In general, reviews show that while the number of persona l-level danger factors and variables is being studied, the relevant and context protection factors require more detailed research in future research. Ta. More specifically, this review revealed that online and offline gamblers have shared most risk factors and protection factors. These factors can be an important factor to be considered in ant i-gamblers and online gamblers.

Introduction

January 29, 2021

April 23, 2022

August 24, 2022 article

Avoid mistakes in manuscripts over the past few decades, Internet gambling has become a powerful growth and spreading with particularly attractive essential characteristics (ease of access, anonymity, game diversity) for players. Ta. The purpose of this paper is to introduce the current status of online gambling danger factors and protection factors. As a result of searching for Pubmed, Psychinfo, and Scopus databases, 42 papers were found, and they were reviewed. The methodological aspects, risk factors, and protection factors were analyzed across. The results related to risk factors and protection factors were distinguished by the analysis level of personal, relationship, and contextual. Two types of comparisons: online vs. offline gamblers and online no n-proble m-type gamblers vs. gambler. The results of the two comparisons were arranged, and the relationship between the consistency and the factor was analyzed. In general, reviews show that while the number of persona l-level danger factors and variables is being studied, the relevant and context protection factors require more detailed research in future research. Ta. More specifically, this review revealed that online and offline gamblers have shared most risk factors and protection factors. These factors can be an important factor to be considered in preventive interventions for online gamblers and online gamblers.

January 29, 2021

Methods

Search Strategy

April 23, 2022

Inclusion Criteria

August 24, 2022 article

Study Selection, Data Extraction and Analysis

Avoid mistakes that are common in manuscripts

Results

Gambling is an entertainment that focuses on games and events, focusing on valuable things and property, and is mainly random (Boyd & Amp; Bolen, 1968). Gambling is one of the most widespread leisure activities since history in all cultures and society, which has not changed. For many people, gambling is a fun activity that does not affect life, but in contrast, gambling leads to addiction (Serpelloni, 2013). According to research so far, adult problem gamblers are 0. 12 to 5. 8 % (Calado & Amp; Griffiths, 2016). In addition, gambling has grown dramatically in the last few decades, and has increased significantly to access, participation, and expenditure (abbott, 2020). For this reason, gambling addiction is regarded as a social problem. Problem gambling has a negative effect on the network of individuals, their relationships, and welby swings in society as a whole, which impairs public health. Interventions and policies are required from the viewpoint of care and treatment and from the viewpoint of prevention.

Search Results and Flowchart

This phenomenon is affected by COVID-19. Lan d-based gamblers have experienced larg e-scale changes during lockdowns due to gambling and sporting events. Due to the pandemic, the number of gambling visitors has decreased overall, but Lan d-based players have shifted to Internet gambling (Hodgins & Amp; Stevens, 2021). On the other hand, according to the latest literature on the impact of Coronavirus on online gambling, it has been reported that the play of online gamblers has not changed, but this gambling mode has not seen a significant increase (Brodeur et al., 2021. Hodgins & amp; Stevens, 2021). Nevertheless, it has been reported that the level of gambling is high among those who have increased gambling addiction, and have a strong relevance to mental health problems and drug use. Considering these concerns that have deteriorated due to the COVID-19 epidemic, the spread of online gambling should be carefully monitored. gambling is an entertainment centered on games and events, focusing on valuable things and property, and is mainly random (Boyd & Amp; Bolen, 1968). Gambling is one of the most widespread leisure activities since history in all cultures and society, which has not changed. For many people, gambling is a fun activity that does not affect life, but in contrast, gambling leads to addiction (Serpelloni, 2013). According to research so far, adult problem gamblers are 0. 12 to 5. 8 % (Calado & Amp; Griffiths, 2016). In addition, gambling has grown dramatically in the last few decades, and has increased significantly to access, participation, and expenditure (abbott, 2020). For this reason, gambling addiction is regarded as a social problem. Problem gambling has a negative effect on networks of individuals, their relationships, and welby swings in society as a whole, causing public health. Interventions and policies are required from the viewpoint of care and treatment and from the viewpoint of prevention.

This phenomenon is affected by COVID-19. Lan d-based gamblers have experienced larg e-scale changes during lockdowns due to gambling and sporting events. Due to the pandemic, the number of gambling visitors has decreased overall, but Lan d-based players have shifted to Internet gambling (Hodgins & Amp; Stevens, 2021). On the other hand, according to the latest literature on the impact of Coronavirus on online gambling, it has been reported that the play of online gamblers has not changed, but this gambling mode has not seen a significant increase (Brodeur et al., 2021. Hodgins & amp; Stevens, 2021). Nevertheless, it has been reported that the level of gambling is high among those who have increased gambling addiction, and have a strong relevance to mental health problems and drug use. Considering these concerns that have deteriorated due to the COVID-19 epidemic, the spread of online gambling should be carefully monitored. Gambling is an entertainment that focuses on games and events, focusing on valuable things and property, and is mainly random (Boyd & amp; bolen, 1968). Gambling is one of the most widespread leisure activities since history in all cultures and society, which has not changed. For many people, gambling is a fun activity that does not affect life, but in contrast, gambling leads to addiction (Serpelloni, 2013). According to research so far, adult problem gamblers are 0. 12 to 5. 8 % (Calado & Amp; Griffiths, 2016). In addition, gambling has grown dramatically in the last few decades, and has increased significantly to access, participation, and expenditure (abbott, 2020). For this reason, gambling addiction is regarded as a social problem. Problem gambling has a negative effect on networks of individuals, their relationships, and welby swings in society as a whole, causing public health. Interventions and policies are required from the viewpoint of care and treatment and from the viewpoint of prevention.

To design effective interventions and policies, it is essential to know the risk and protective factors associated with a phenomenon (Coie et al., 1993). However, the literature on risk and protective factors for online problem gambling is not comprehensive. Most papers focus on identifying risk and protective factors for problem gambling, especially in offline gamblers, or do not even distinguish them from online gamblers. Furthermore, most of the studies on risk and protective factors have been conducted in adolescent populations (Dickson et al., 2008; Dowling et al., 2017), and few have been conducted in adult populations.

Features of Selected Studies

The most recent review on risk and protective factors for Internet gambling in adults was published by Gainsbury (2015), which focuses on the association between online gambling and problem gambling by comparing Internet gambling with land-based gambling. However, this is not a systematic review, and no information on the methodology used is presented. Given that most gamblers are not problematic, it is important to better understand whether there are differences among gamblers who choose to gamble online, without necessarily focusing on problem gamblers. Moreover, given the rapid increase in the phenomenon, it seems necessary to update our knowledge of the phenomenon to keep up with the changes.

The purpose of this paper is to review the knowledge and evidence on factors influencing the likelihood of being an online gambler and developing problem gambling behaviors in the adult population. To synthesize and organize the results on risk and protective factors, two types of comparisons were made: a comparison of factors that distinguish offline gamblers from online gamblers and a comparison of online non-problem gamblers from online problem gamblers. Furthermore, further comparisons were made to clarify whether similarities or differences emerged in terms of the factors investigated between the first and second comparisons.

To investigate online gambling dangerous factors and protection factors, a systematic search was performed in three different academic databases: PUBMED, PSYCHINFO, and Scopus. Similar syntax was launched only to pee r-back papers only. The main keywords are combined with "gambling", "online, Internet, interactive", "dangerous factors, protection factors, predictive factors, and correlations." The syntax entered in psychinfo is (AB (online) or AB (Internet) or AB (Internet)) and AB (Gambl*) and AB (AB (Risk Factor*) or AB (Protect Factor*). Or Ab (Promotive Factor*) or AB (Predictor*) or AB (Correlate*). Related publications have been added based on the references list of selected papers and discussions with the number of experts in the gambling field. The systematic review was implemented according to the PrefertRed Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2015 CHECKLIST (Moher et al., 2016).

Literature search was limited to pee r-back research published in English between 2010 and 2020. The only thing that has been investigated over the last ten years is to focus on the current status of knowledge about phenomena, especially in recent years. The target paper was composed of the following criteria from the viewpoint of Population Intervention Comparison Outcome (PICO): Reference group (P) consists of an adult online gambler (18 years old or older) and related to biological determination factors. Except for what to do, the risk factors and / or protective factors (I) of all levels (individual and environment) were investigated. Research results (O) include results on the degree of all addiction, severity (no n-problems, problems, pathology), and risks (low, medium, high) of online games. The type of analyzed comparison (C) was limited to paper comparing online gamblers, offline gamblers (C1) and / or online no n-problem gamblers and online problem gamblers (C2).

The two independent evaluators screened their research and extracted data. The selection of the dissertation was divided into two stages. First, the research was selected by reading the title and abstract, and unrelated ones were excluded. After two researchers compared their choices, only research that both researchers seemed to be qualified was left. In the second stage, the full text was read and the qualified standards were applied. If there were differences in opinion, we discussed the dissertation and obtained a consensus. After selecting the dissertation, the following data was extracted: research purpose, method and method type, specimen characteristics (size, representative, answer rate, recruitment method), used tools and analysis, contrasting groups or comparison Groups, countries, groups and su b-groups, surveyed variables, risk factors and protection factors. The mass of the population and the extraction of the partial group were related to social population statistical characteristics only. Data was extracted, two authors integrated the explanation, and another author discussed and fixed. When the data was extracted, an early stage of the analysis was performed. In accordance with the main purposes, each paper is a comparison type (online vs. offline, no n-problem online, both online, both online), the level of the research analysis (individual, relationship, context), and the type of factors (protection factors or protection factors (protection factors) It was classified by danger factors). The classification of the dissertation was screened by the two independent evaluators and extracted data. The selection of the dissertation was divided into two stages. First, the research was selected by reading the title and abstract, and unrelated ones were excluded. After two researchers compared their choices, only research that both researchers seemed to be qualified was left. In the second stage, the full text was read and the qualified standards were applied. If there were differences in opinion, we discussed the dissertation and obtained a consensus. After selecting the dissertation, the following data was extracted: research purpose, method and method type, specimen characteristics (size, representative, answer rate, recruitment method), used tools and analysis, contrasting groups or comparison Groups, countries, groups and su b-groups, surveyed variables, risk factors and protection factors. The mass of the population and the extraction of the partial group were related to social population statistical characteristics only. Data was extracted, two authors integrated the explanation, and another author discussed and fixed. When the data was extracted, an early stage of the analysis was performed. In accordance with the main purposes, each paper is a comparison type (online vs. offline, no n-problem online, both online, both online), the level of the research analysis (individual, relationship, context), and the type of factors (protection factors or protection factors (protection factors) It was classified by danger factors). The classification of the dissertation was screened by the two independent evaluators and extracted data. The selection of the dissertation was divided into two stages. First, the research was selected by reading the title and abstract, and unrelated ones were excluded. After two researchers compared their choices, only research that both researchers seemed to be qualified was left. In the second stage, the full text was read and the qualified standards were applied. If there were differences in opinion, we discussed the dissertation and obtained a consensus. After selecting the dissertation, the following data was extracted: research purpose, method and method type, specimen characteristics (size, representative, answer rate, recruitment method), used tools and analysis, contrasting groups or comparison Groups, countries, groups and su b-groups, surveyed variables, risk factors and protection factors. The mass of the population and the extraction of the partial group were related to social population statistical characteristics only. Data was extracted, two authors integrated the explanation, and another author discussed and fixed. When the data was extracted, an early stage of the analysis was performed. In accordance with the main purposes, each paper is a comparison type (online vs. offline, no n-problem online, both online, both online), the level of the research analysis (individual, relationship, context), and the type of factors (protection factors or protection factors (protection factors) It was classified by danger factors). The classification of the dissertation

The results are shown below. First, the search results and the screening process are shown. Second, from the viewpoint of methodology, the characteristics of the recording papers are brief. Third, the analysis of the risk factors and protection factors reported in the recording paper is shown. In this section, the factors related to online gambling are analyzed and subdivided according to the analysis level (individual, relationship, environment). Two types of comparisons were made to integrate and systematize the results related to risk factors and protective factors. Comparison of factors that distinguishes offline gamblers and online gamblers (C1) and online gamblers with no problem online gamblers (C2). Furthermore, between the first comparison and the second comparison, further comparisons were made to clarify whether similarities and differences have appeared on the factors (C3). The results are systematized and are shown in the table at the end of the paper (see Appendix A).

Risk and Protective Individual Factors

Sociodemographic Information

Figure 1 is a screening flowchart. A total of 785 papers were searched by the database search, and as a result of the deletion of duplication, 420 unique quotes were obtained. As the first stage, the screening by title and abstract was performed, and 52 papers were eligible. Furthermore, 12 studies were searched by references and gambling experts.

Figure 1

PRISMA flow diagram

In the second stage, research was selected through ful l-text screening related to the PICO standard. 42 out of 64 qualified papers were included in the review. Appendix B includes the title of the dissertation included in the review, the author, and the publishing year from a new one to the chronological order.

Gambling Patterns and Behaviours

Almost all of the selected studies were conducted in Europe, the United States, the United Kingdom, the United Kingdom, Australia, Canada, the United States, but only one was implemented in Asia (Macau) (WU ET). Al., 2015).

Eight Papers) (1) are a sample group in a young adult group (about 18 to 25 years old), mostly targeting university groups (Griffiths et al., 2010; Harris et al., 2013; HOPLEY & AMP; Nicki, 2010; Mackay & amp; Hodgins, 2012; Mihaylova et al., 2013; show et al., 2015).

Quantitative methodology is used in all papers, most of which are sel f-style online questionnaires. The two studies use a mixture approach that integrates quantitative data and hal f-stredged interviews (Granero et al., 2020; Schiavella et al., 2018). Almost all research is cros s-right. Since these studies are related to a single measurement, the direction of relationship between variables and results cannot be clearly recognized. There are only three papers that are vertical and examining different periods: 30 days (Goldstein et al., 2016), two years (BRAVERMAN & AMP; Shaffer, 2012; dufour et al., 2020).

Risky Behaviours

There is also a paper using a representative sample of random. These studies are usually part of a widespread national survey. However, most papers are sel f-selected.

Most papers were recruited on the Internet due to the characteristics of the sample. Participants were mostly recruited through specialized sites, forums, and online advertisements on social networks. In addition, remote methods for online gambling operators were often used to send invitation emails to randomly selected user samples. The latter includes newspapers, television, radio, telephone advertisements, and gambling posters.

Various types of analysis were performed for various purposes. The main ones are the specific gambler groups by cluster analysis (Braverman & amp; 2012; dufour et al., 2013, 2020; Granero et al., 2020; Khazaal et al., 2017; There are; perrot et al., 2018), comparison between groups by bilateral or multiple analysis, and exploration of group characteristics by description analysis. quantitative methodology is used in all papers, most of which are sel f-style online questionnaires. The two studies use a mixture approach that integrates quantitative data and hal f-stredged interviews (Granero et al., 2020; Schiavella et al., 2018). Almost all research is cros s-right. Since these studies are related to a single measurement, the direction of relationship between variables and results cannot be clearly recognized. There are only three papers that are vertical and examining different periods: 30 days (Goldstein et al., 2016), two years (BRAVERMAN & AMP; Shaffer, 2012; dufour et al., 2020).

There is also a paper using a representative sample of random. These studies are usually part of a widespread national survey. However, most papers are sel f-selected.

Health and Wellbeing

Physical Health

Various types of analysis were performed for various purposes. The main ones are the specific gambler groups by cluster analysis (Braverman & amp; 2012; dufour et al., 2013, 2020; Granero et al., 2020; Khazaal et al., 2017; There are; perrot et al., 2018), comparison between groups by bilateral or multiple analysis, and exploration of group characteristics by description analysis. Quantitative methodology is used in all papers, most of which are sel f-style online questionnaires. The two studies use a mixture approach that integrates quantitative data and hal f-stredged interviews (Granero et al., 2020; Schiavella et al., 2018). Almost all research is cros s-right. Since these studies are related to a single measurement, the direction of relationship between variables and results cannot be clearly recognized. There are only three papers that are vertical and examining different periods: 30 days (Goldstein et al., 2016), two years (BRAVERMAN & AMP; Shaffer, 2012; dufour et al., 2020).

Psychological distress and emotions

There is also a paper using a representative sample of random. These studies are usually part of a widespread national survey. However, most papers are sel f-selected.

Personality Characteristics and Cognitive Components

Personality Characteristics

Compared to offline gamblers, online gamblers were more common among men (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al., 2012; Goldstein et al. HARRIS et al., 2013; Lelonek-Kuleta et al., 2020; mackay & amp; Hodgins, 2012; mihaylova et al., 2015; shead et al. Wood & amp; WILLIAMS, 2011; Wu et al., 2015), young (Dowling et al., 2015; Edgren et al. 20; Redondo, 2015; Wardle et al., 2011; Wood & amp; Williams, 2011; Wu et al., 2015）、教育水準が高い（Dowling et al、 2015b; Griffiths et al., 2011; Redondo, 2015; Wardle et al., 2011; wu et al., 2015), with high income (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al., 2012; Wardle et al., 2011; 2011; wu et al., 2015). Among the papers included in the review, the results related to these four factors are very homogeneous. The only exception was Lelonek-Kuleta et al. (2020), and low-income was mostly related to Internet gamblers. Compared to the offline gambler, online gamblers were more common in men (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al., 2012; Goldstein et al., 2016; GRIFFITHS et al. , 2011; Harris et al., 2013; Kairouz et al., 2020; Mackay & amp; Hodgins, 2012; MIHAYLOVA et AL. l., 2012; Wood & Amp; WUILLIAMS, 2011; WU et al., 2015), young (Dowling et al. Leta et al. , 2020; Redondo, 2015; Wardle et al., 2011; Wood & amp; 2011; Wu et al. Wardle et al., 2011; wu et al., 2015), with high income (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al., 2012; Wardle et al., 2011; Williams, 2011; Wu et al., 2015). Among the papers included in the review, the results related to these four factors are very homogeneous. The only exception was Lelonek-Kuleta et al. (2020), and low-income was mostly related to Internet gamblers. Compared to offline gamblers, online gamblers were more common among men (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al., 2012; Goldstein et al. HARRIS et al., 2013; Lelonek-Kuleta et al., 2020; mackay & amp; Hodgins, 2012; mihaylova et al., 2015; shead et al. Wood & amp; WILLIAMS, 2011; Wu et al., 2015), young (Dowling et al., 2015; Edgren et al. 20; Redondo, 2015; Wardle et al., 2011; Wood & amp; Williams, 2011; Wu et al., 2015）、教育水準が高い（Dowling et al、 2015b; Griffiths et al., 2011; Redondo, 2015; Wardle et al., 2011; wu et al., 2015), with high income (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al., 2012; Wardle et al., 2011; 2011; wu et al., 2015). Among the papers included in the review, the results related to these four factors are very homogeneous. The only exception was Lelonek-Kuleta et al. (2020), and low-income was mostly related to Internet gamblers.

In addition to these widely researching factors, there are also some investigations of social population statistics. For example, for gambler occupations, paid jobs (Dowling et al., 2015; Wardle et al., 2011) and ful l-time work (Edgren et al., 2017; Gainsbury et al. Hubert and Griffiths (2018) (26) reports the inconsistent results, but it has been shown that Internet gamblers are more likely to be reported than lan d-based gamblers. There is. In contrast to the marriage status and relationship of the gambler, the consequences have been reported. According to the three papers, the online gambler lives with a stable partner (Dowling et al., 2015), is likely to be a married person (Hubert & Amp; Griffiths, 2018; WOOD & Amp; Williams, 2011) However, in other studies, the possibility of being married is low (Hubert & Amp; 2018; Wood & Amp; WILLIAMS, 2011) and is likely to be single (Griffiths et al., 2011; Kairouz et al. ) The two different authors are investigating the place of residence, making the opposite conclusion. According to Lelonek-Kuleta and others (2020), living in a rural area (not a city or town) is more likely to become an online gambler. In contrast, according to Gainsbury (2015A, 2015C), Internet gamblers are likely to live in a large city. Another variable is also investigated: The fact that there are dependent children is related to both online and offline gambling (Dowling et al.

Cognitive Components

In comparison between online problem gamblers and no n-problem gamblers, some different results are shown. The online problem gambler is a man (GAINSBURY et al., 2014b; hing et al., 2017; McCormack et al., 2013 WU et al. Granero et al., 2020; hing et al., 2017), lo w-educated, lo w-educated, lo w-income (Granero et al, 2020; hing et al., 2017), Online no n-problem gamblers are more unemployed or almost unemployed (barrault et al., 2017; Gainsbury et al., 2014c; 2015c; GRANERO et al., 2020) Al., 2015c; granero et al., 2020; khazaal et al., 2017), there are children (Lelonek-Kuleta et al.

There are several papers reporting the opposite results. Regarding the gambler gender, Gainsbury et al. (2014c) reports that women are more frequent than men, "chasing losing," related to pathological gambling. In comparative studies of Edgren et al. (2017), women's online gamblers have more gambling than men, and the risk of gamblers is highly risky. Furthermore, in Khazaal et al. (2017), the ratio of women was the most problematic cluster. The latter study reports that the most problematic cluster is characterized by the fact that the most problematic cluster has a higher age average compared to clusters with few problems.

Representations, Attitudes and Motivation to Gamble

Representations and Attitudes

Regarding gambling actions, there were differences between online gamblers and offline gamblers, especially those that were particularly noticeable: gambling strength and variable. Internet gamblers tended to gamble more frequently (barrault & amp; 2016; Dowling et al., 2015; duffour et al., 2013; et al., 2012, 2013; hubert & amp; gliffiths, 2018; kairouz et al., 2012; mackay & amp; Hodgins, 2012; mihaylova et al., 2012; showd et al. The consistent result from different research is that the highly relevant variability of gambling activities is more relevant to online gambling than offline gambling (Dowling et al., 2015; edgren et al., 2017; Gainsbury et al. 2012, 2013; kairouz et al., 2012; mackay & amp; Hodgins, 2012; mihaylova et al., 2013; Shead et al., 2012; Wardle et al., 2012; Wood & amp; 2011). In addition, online gamblers tend to gamble for a long time than offline gamblers and report high expenditures (Dowling et al., 2015; duffour et al., 2013; Goldstein et al., 2016; Kairouz et Al., 2012; Wood & amp; Williams, 2011) and have a high debt (mihaylova et al., 2013; Wood & amp; Williams, 2011). In contrast to these results, Barrault and Varescon (2016) states that offline gamblers are more likely to report long sessions, higher bets, and higher prizes than online gamblers.

In addition to higher intensity, variability, and expenditure, online gamblers are likely to be at higher risk for problem gambling (Dufour et al., 2013, 2020; Goldstein et al., 2016; Griffiths et al., 2011; Harris et al., 2013; MacKay & Hodgins, 2012; Wardle et al., 2011; Wood & Williams, 2011; Wu et al., 2015). In fact, Internet gamblers have higher levels of the Problem Gambling Severity Index (PGSI) than land-based gamblers (Gainsbury et al., 2014b; Kairouz et al., 2012). In a study conducted in Macau by Wu et al. (2015), more pathological gambling symptoms were reported by online gamblers in both a sample representative of the adult population and a sample representative of university students. Moreover, two papers found that online players' first gambling experience was at a younger age than land-based players (Wu et al., 2015). Online players were around 19 years old and offline players around 24 years old (Dowling et al., 2015), highlighting that an earlier onset of gambling behavior is likely to be associated with the online mode (Granero et al., 2020). Online gamblers are more likely to be at higher risk for problem gambling, in addition to higher intensity, variability and expenditure (Dufour et al., 2013, 2020; Goldstein et al., 2016; Griffiths et al., 2011; Harris et al., 2013; MacKay & amp; Hodgins, 2012; Wardle et al., 2011; Wood & amp; Williams, 2011; Wu et al., 2015). In fact, Internet gamblers have higher levels of the Problem Gambling Severity Index (PGSI) than land-based gamblers (Gainsbury et al., 2014b; Kairouz et al., 2012). In a study by Wu et al. (2015) conducted in Macau, more pathological gambling symptoms were reported by online gamblers in both a sample representative of the adult population and a sample representative of university students. Furthermore, two papers showed that online players' first gambling experience was at a younger age than land-based players (Wu et al., 2015). Online players were around 19 years old and offline players around 24 years old (Dowling et al., 2015), highlighting that an earlier onset of gambling behavior is likely to be associated with the online mode (Granero et al., 2020). In addition to higher intensity, variability, and expenditure, online gamblers are likely to be at higher risk for problem gambling (Dufour et al., 2013, 2020; Goldstein et al., 2016; Griffiths et al., 2011; Harris et al., 2013; MacKay & Hodgins, 2012; Wardle et al., 2011; Wood & Williams, 2011; Wu et al., 2015). In fact, Internet gamblers have higher levels of the Problem Gambling Severity Index (PGSI) than land-based gamblers (Gainsbury et al., 2014b; Kairouz et al., 2012). In a study conducted in Macau by Wu et al. (2015), more pathological gambling symptoms were reported by online gamblers in both a sample representative of the adult population and a sample representative of university students. Moreover, two papers found that online players’ first gambling experience was at a younger age than land-based players ( Wu et al., 2015 ), around 19 years old for online players and 24 years old for offline players ( Dowling et al., 2015 ), highlighting that an earlier onset of gambling behavior is likely associated with the online mode ( Granero et al., 2020 ).

Motivations to Gamble

Most of the variables reported above are common to the risk factors of online gambling. In fact, the behavior of the problem gambler is high frequency (strength) (Braverman & amp; Shaffer, 2012; duffour et al., 2013; Gainsbury et al., 2014c; griffiths et al., 2010; hing et al., 2017; & amp; nicki, 2010; Laplainte et al., 2014; mackay & amp; Hodgins, 2012; McCormack et al, 2013b), participation in multiple different gambling forms (high variable) (BRAVERMAN & AMP; 2012 Gainsbury et al., 2014b, 2015a, 2015c; hing et al., 2017; Laplainte et al., 2014; Lloyd et al., 2010a, 2010b; McCormack et al, 2013b; Perrot et al., 2018) & amp; Varescon, 2013b; Varescon, 2016; Dufour et al., 2013; Gainsbury et al., 2014B, 2015C; al., 2012, 2016) It is. Regarding the impact on expenditures, as assumed by GAINSBURY (2015c), the problem gambler has been lost in gambling and the household debt amount is large compared to no n-problem gamblers and risky gamblers. It is reported that it is big. Gambling behavior that is easy to associate with online head risk gamblers is a long session (Barrault & Amp; Varescon, 2013a, 2013b, 2016; Griffiths et al., 2010; McCormack et al., 2013). Although there are few papers investigated, the risk factors of the problem gambling are common to the online problem gambling danger factors. In fact, the behavior of the problem gambler is high frequency (strength) (Braverman & amp; Shaffer, 2012; duffour et al., 2013; Gainsbury et al., 2014c; griffiths et al., 2010; hing et al., 2017; & amp; nicki, 2010; Laplainte et al., 2014; mackay & amp; Hodgins, 2012; McCormack et al, 2013b), participation in multiple different gambling forms (high variable) (BRAVERMAN & AMP; 2012 Gainsbury et al., 2014b, 2015a, 2015c; hing et al., 2017; Laplainte et al., 2014; Lloyd et al., 2010a, 2010b; McCormack et al, 2013b; Perrot et al., 2018) & amp; Varescon, 2013b; Varescon, 2016; Dufour et al., 2013; Gainsbury et al., 2014B, 2015C; al., 2012, 2016) It is. Regarding the impact on expenditures, as assumed by GAINSBURY (2015c), the problem gambler has been lost in gambling and the household debt amount is large compared to no n-problem gamblers and risky gamblers. It is reported that it is big. Gambling behavior that is easy to associate with online head risk gamblers is a long session (Barrault & Amp; Varescon, 2013a, 2013b, 2016; Griffiths et al., 2010; McCormack et al., 2013). Although there are few papers investigated, the risk factors of the problem gambling are common to most of the abov e-mentioned variables as the online problem gambling danger factors. In fact, the behavior of the problem gambler is high frequency (strength) (Braverman & amp; Shaffer, 2012; duffour et al., 2013; Gainsbury et al., 2014c; griffiths et al., 2010; hing et al., 2017; & amp; nicki, 2010; Laplainte et al., 2014; mackay & amp; Hodgins, 2012; McCormack et al, 2013b), participation in multiple different gambling forms (high variable) (BRAVERMAN & AMP; 2012 Gainsbury et al., 2014b, 2015a, 2015c; hing et al., 2017; Laplainte et al., 2014; Lloyd et al., 2010a, 2010b; McCormack et al, 2013b; Perrot et al., 2018) & amp; Varescon, 2013b; Varescon, 2016; Dufour et al., 2013; Gainsbury et al., 2014B, 2015C; al., 2012, 2016) It is. Regarding the impact on expenditures, as assumed by GAINSBURY (2015c), the problem gambler has been lost in gambling and the household debt amount is large compared to no n-problem gamblers and risky gamblers. It is reported that it is big. Gambling behavior that is easy to associate with online head risk gamblers is a long session (Barrault & Amp; Varescon, 2013a, 2013b, 2016; Griffiths et al., 2010; McCormack et al., 2013). Although there are few papers investigated, the risk factors of the problem gambling are early.

As reported in the previous paragraph, gambling is often related to other kinds of risk behavior, such as drug abuse. This correlation is effective for all kinds of gamblers, but the online gambler can use or misuse online gamblers rather than offline gamblers during gambling. It means that it is highly sexual (Dowling et al., 2015; Gainsbury et al., 2014b; griffiths et al., 2011; harris et al., 2013; et al., 2012; Wood & amp; Williams, 2011). According to GAINSBURY (2014B), Internet gamblers are significantly higher in reporting alcohol and smoking while engaging in Lan d-Base Gambling, compared to offline gamblers. In contrast, Goldstein et al. (2016) associated with the fact that taking a lot of substances during gambling is unlikely to be an online gambler. Many of the Internet gamblers report dangerous drinking (Dowling et al., 2015; Griffiths et al., 2011), alcohol intake and addicted (kairouz et al., 2012; mihaylova et al., 2013). 。 In relation to the use of other substances, online gamblers consume regular drugs (Dowling, 2015), illegal drugs (mihaylova, 2013) and Kannabinoids (2015; KAIROUZ, 2012). There is a high possibility. According to GAINSBURY (2014B), offline gamblers are more likely to be no n-smokers than online gamblers.

Even if there is a study (Harris and other 2013bes, 2013B) that the most risky gamblers are related to alcohol, tobacco, and drugs, the most risky online gambling pattern is dangerous. It represents the factor (GAINSBURY, 2014b; Granero et al. As reported above, ingestion of alcohol and other substances during gambling seems to be easier to associate with online problem gamblers than no n-problem gamblers (Gainsbury et al., 2015C; harris et al., 2013; hing. et al., 2017; mcCormack et al., 2013).

Risk and Protective Relational and Contextual Factors

Relational Factors

Risky behaviors related to gambling do not end with excessive substance use, there are other behaviors related to online gambling and problem gambling, such as excessive media use. Factors that are more likely to be associated with online gambling include early computer use (Hubert & amp; Griffiths, 2018) and computer gaming experience (Edgren et al.). In line with this, Lelonek-Kuleta et al. (2020) found that people with less daily Internet use were less involved in online gambling. Related involvement in gaming was also found to be a risk factor for the development of problematic gambling patterns (Khazaal et al.).

Contextual Factors

Deliberate self-harm is also a risk behavior that is more prevalent among the most problematic cluster of online gamblers (hyperactive players) compared to other clusters according to Lloyd et al. (2010a).

Discussion

Health and well-being were rarely investigated in the papers included in this review, and the results are mostly contradictory. For example, Wardle et al. (2011) found that online gamblers were more likely to report good general health than land-based gamblers. With regard to physical well-being, Shead et al. (2012) showed that land-based university gamblers were more likely to be of normal weight, while Internet gamblers were more likely to be underweight, overweight, or obese. Furthermore, physical disorders or serious mental health problems were more predictive of Internet gamblers than offline gamblers (Wood & Williams, 2011). According to Redondo (2015), online gamblers were less concerned about their future personal health and were more likely to engage in unhealthy activities.

In light of the above, a single risk factor for the development of a pathological gambling mode emerged from a study by McCormack et al. (2013b) on a sample of online gamblers. Problem gamblers were found to be more likely to report disorders than non-problem gamblers.

Regarding psychological happiness, there are only a few studies that report a significant difference between online and offline gamblers. Gainsbury et al. (2014b) argued that online gamblers are more likely to experience psychological pain than lan d-based gamblers. Furthermore, Goldstein et al. (2016) showed the relevant results, and they monitored the mood of young adult samples for 30 days. According to the collected data, gambling on the Internet experienced a higher and more negative emotions during the observation period compared to no n-online gamblers. Regarding psychological happiness, there are only a few studies that report a significant difference between online and offline gamblers. Gainsbury et al. (2014b) argued that online gamblers are more likely to experience psychological pain than lan d-based gamblers. Furthermore, Goldstein et al. (2016) showed the relevant results, and they monitored the mood of young adult samples for 30 days. According to the collected data, gambling on the Internet experienced a higher and more negative emotions during the observation period compared to no n-online gamblers. Regarding psychological happiness, there are only a few studies that report a significant difference between online and offline gamblers. Gainsbury et al. (2014b) argued that online gamblers are more likely to experience psychological pain than lan d-based gamblers. Furthermore, Goldstein et al. (2016) showed the relevant results, and they monitored the mood of young adult samples for 30 days. According to the collected data, gambling on the Internet experienced a higher and more negative emotions during the observation period compared to no n-online gamblers.

Due to the many crossing research, it is not possible to clearly define the direction of the relationship between psychological and problem gambling. It is difficult to determine whether the former is a dangerous factor or the latter result. For example, it is unknown whether the high level of psychological distress is the result of a frequent gambling, or whether a person with psychological pain is particularly attracted to gambling. As expected, online gamblers, which have a high risk of problematic gambling, have shown that the level of psychological pain is higher than the gamblers with low risk (2014b; Granero et al. 2020; Hing etc., 2017; Nicki, 2010). 不安と抑うつは、研究された主な経験であり、病的ギャンブラーによって高い割合で報告された（Barrault & amp; Varescon, 2013a; Barrault et al., 2017; Hopley & amp; Nicki, 2010; Khazaal et al. ) Furthermore, mood disorders, such as hyponal experiences and uplifting mood, are reported to the most problematic cluster (Lloyd et al.) In addition, as an emotional state that is easy to associate with the dangerous constitution of gambling. There are dissatisfaction (WU et al., 2015) and loneliness (KHAZAAL, 2017). Furthermore, the gambler with a problem gambler and risks tended to feel euphoric, excitement, and happiness during gambling (McCormack et al.), And the gamblers have a strong tendency. 。

Regarding personality characteristics, there are few reports of online and offline gamblers. According to Redondo (2015), online gamblers have low sociability and many frugals. Due to many crossing research, it is not possible to clearly define the direction of psychological distress and gambling gambling. It is difficult to determine whether the former is a dangerous factor or the latter result. For example, it is unknown whether the high level of psychological distress is the result of a frequent gambling, or whether a person with psychological pain is particularly attracted to gambling. As expected, online gamblers, which have a high risk of problematic gambling, have shown that the level of psychological pain is higher than the gamblers with low risk (2014b; Granero et al. 2020; Hing etc., 2017; Nicki, 2010). 不安と抑うつは、研究された主な経験であり、病的ギャンブラーによって高い割合で報告された（Barrault & amp; Varescon, 2013a; Barrault et al., 2017; Hopley & amp; Nicki, 2010; Khazaal et al. ) Furthermore, mood disorders, such as hyponal experiences and uplifting mood, are reported to the most problematic cluster (Lloyd et al.) In addition, as an emotional state that is easy to associate with the dangerous constitution of gambling. There are dissatisfaction (WU et al., 2015) and loneliness (KHAZAAL, 2017). Furthermore, the gambler with a problem gambler and risks tended to feel euphoric, excitement, and happiness during gambling (McCormack et al.), And the gamblers have a strong tendency. 。

Regarding personality characteristics, there are few reports of online and offline gamblers. According to Redondo (2015), online gamblers have low sociability and many frugals. Due to the many crossing research, it is not possible to clearly define the direction of the relationship between psychological and problem gambling. It is difficult to determine whether the former is a dangerous factor or the latter result. For example, it is unknown whether the high level of psychological distress is the result of a frequent gambling, or whether a person with psychological pain is particularly attracted to gambling. As expected, online gamblers, which have a high risk of problematic gambling, have shown that the level of psychological pain is higher than the gamblers with low risk (2014b; Granero et al. 2020; Hing etc., 2017; Nicki, 2010). 不安と抑うつは、研究された主な経験であり、病的ギャンブラーによって高い割合で報告された（Barrault & amp; Varescon, 2013a; Barrault et al., 2017; Hopley & amp; Nicki, 2010; Khazaal et al. ) Furthermore, mood disorders, such as hyponal experiences and uplifting mood, are reported to the most problematic cluster (Lloyd et al.) In addition, as an emotional state that is easy to associate with the dangerous constitution of gambling. There are dissatisfaction (WU et al., 2015) and loneliness (KHAZAAL, 2017). Furthermore, the gambler with a problem gambler and risks tended to feel euphoric, excitement, and happiness during gambling (McCormack et al.), And the gamblers have a strong tendency. 。

Regarding personality characteristics, there are few reports of online and offline gamblers. According to Redondo (2015), online gamblers have low sociability and many frugals.

Personality-related variables were more relevant in comparisons between people at risk of developing problem gambling. Impulsivity, i. e. the tendency to carry out actions without considering possible consequences (Zuckerman & Kuhlman, 2000), is the most widely investigated personality trait and seems to be particularly associated with pathological gambling patterns (Barrault & Varescon, 2013b, 2016; Hopley & Nicki, 2010; Khazaal et al., 2017; Moreau et al., 2020). Other personality traits that increase the likelihood of developing a problem mode of gambling are a predisposition to boredom (Hopley & Nicki, 2010) and a lack of planning (Khazaal et al., 2017).

Granero et al. (2020) found that, in general, people with dysfunctional personality traits (e. g., characterized by high scores on the novelty-seeking dimension) were more likely to have gambling that leads to disorders. Conversely, individuals with functional personality traits are less likely to experience problem gambling. In addition, high scores on self-directedness, the ability to adjust behavior depending on the situation to achieve goals, and agreeableness traits are considered protective factors related to adaptive emotional and cognitive responses (Granero et al., 2020).

Several dysfunctional thinking mechanisms have been found to influence the likelihood of becoming an online gambler. Compared to offline gamblers, Internet gamblers are more likely to have two main types of cognitive distortions: illusion of control and perseverance (Dufour et al., 2020; MacKay & amp; Hodgins, 2012). In Wood and Williams (2011), the illusion of being able to manipulate the outcome of the game has been identified as a risk factor.

The presence of cognitive distortions regarding gambling increases the likelihood of developing problem gambling (Barrault & Varescon, 2013a; Gainsbury et al., 2014c, 2015c; MacKay & Hodgins, 2012; Moreau et al.). Comparing low-risk gamblers with pathological gamblers, the latter report significantly higher levels of all five types of cognitions analyzed in the Gambling-Related Cognitions Scale (GRCS): gambling-related expectancies, illusion of control, predictive control, perceived inability to stop gambling, and interpretation bias. Other risk factors associated with problem gambling found in analyses of poker players include dissociative episodes during play (Hopley & Nicki, 2010) and frequent tilt episodes (Moreau et al., 2020).

Gamblers' attitudes towards gambling have been found to influence their choice of gambling method. Literature suggests that having a positive attitude towards online gambling increases the likelihood of gambling on the Internet (Gainsbury et al., 2012; Harris et al., 2013; Wood & Williams, 2011; Wu et al., 2015). In Gainsbury et al. (2012), Internet gamblers experienced higher scores on items investigating the morality, legality, and costs-benefits of online gambling. In addition to attitudes, higher trust in the Internet was more likely to be associated with online gamblers than offline gamblers (Redondo, 2015). In Harris et al. (2013), significant differences emerged between groups of online gamblers and land-based gamblers. Internet gamblers reported higher scores on items related to trust in the safety of both online payments and websites than land-based gamblers. Furthermore, Redondo (2015) shows that online gamblers are less religious than offline gamblers, are less concerned about the future of the environment, and therefore less likely to participate in environmentally friendly activities.

Gambling attitudes seem to affect the possibility of developing problematic gambling. Hig h-risk Internet gamblers are known to have a more negative attitude toward gambling (haris et al., 2013; Hing et al., 2017). Gainsbury et al. (2015c) papers in the problem gamblers tended to think that gambling harm exceeded profits, gambling was an immoral act, and gambling in all forms should be illegal. The same results were shown by Hing et al. (2017), and it was found that the gambler was reporting a negative attitude. This result seems to be contrasting with the possibility of a problem gambler and the relationships on the trust of the Internet related to the relationship with the relationship between the relationships related to the Internet. It seems to affect the possibility. Hig h-risk Internet gamblers are known to have a more negative attitude toward gambling (haris et al., 2013; Hing et al., 2017). Gainsbury et al. (2015c) papers in the problem gamblers tended to think that gambling harm exceeded profits, gambling was an immoral act, and gambling in all forms should be illegal. The same results were shown by Hing et al. (2017), and it was found that the gambler was reporting a negative attitude. This result seems to be contrasting with the possibility of being a gambler related to the trust of the Internet, which is likely to be a gambler (Harris et al.) Gambling, and the possibility of developing a problematic gambling. It seems to affect. Hig h-risk Internet gamblers are known to have a more negative attitude toward gambling (haris et al., 2013; Hing et al., 2017). Gainsbury et al. (2015c) papers in the problem gamblers tended to think that gambling harm exceeded profits, gambling was an immoral act, and gambling in all forms should be illegal. The same results were shown by Hing et al. (2017), and it was found that the gambler was reporting a negative attitude. This result seems to be contrasting with the possibility of a problem gambler and the knowledge about the trust of the Internet related to the relationship (Harris et al.)

Limitations of the Review

Of the motivations for driving people into gambling, the four main reasons have been investigated: strengthening, dealing, social and financial. The motivation of reinforcement includes reasons related to the positive emotions and excitement caused by gambling, and the motivation is to gamble to celebrate for socializing, socializing. Motivation for dealing with is related to gambling to relax, forget the problem, or to feel better, and financial motivation is the potential to earn money, the possibility of gaining a lot of money, or Refers to make money (lloyd et al., 2010b; stewart & amp; zack, 2008). Compared to the lan d-based gambler, the gambling motivation that the online gambler reports is the most common is the reason for dealing with (Dowling et al.) (2015; Goldstein, 2016), and the financial reasons (Barrault & Amp; Varescon, 2016), to satisfy the challenge desire or to show the skills (Dowling and 2015; Goldstein etc., 2016). For social reasons (Barraurt & Amp; Varescon, 2016), I believe that it will provide a fun social encounter for gambling (Dowling et al., 2015) et al. Goldstein et al. (2016) analyzed online gamblers that online gambling starts to gain money, or online for the following purposes. The motivation to run a person to gamble, and the motivation for reinforcements was investigated by gambling. Including reasons related to positive emotions and excitements, the motivation to gamble for celebration, for socializing, to spend time with friends, is the motivation for dealing with. In relation to gambling to forget the problem or feel better, financial motivation refers to the need for money, the possibility of gaining a lot, or want to make money (LLOYD). Compared to the gambler of the land bass, the most common reasons for the gambler of the land (DOWLING) compared to the gambler of the land (DOWLING). 2016), financial reasons (Barrault & amp; Varescon, 2016), to satisfy the challenge of the challenge (for Dowling and 2015; Goldstein etc., 2016). Varescon, 2016), for the positive emotions brought by gambling (Dowling et al., 2015), or believing that this activity will provide a fun social encounter (Goldstein et al. Goldstein et al. (2016) (2016) The online gambler has tended to start online for gamblers to gain money, to enjoy money. Of the motivations for driving people into gambling, the four main reasons have been investigated: strengthening, dealing, social and financial. The motivation of reinforcement includes reasons related to the positive emotions and excitement caused by gambling, and the motivation is to gamble to celebrate for socializing, socializing. Motivation for dealing with is related to gambling to relax, forget the problem, or to feel better, and financial motivation is the potential to earn money, the possibility of gaining a lot of money, or Refers to make money (lloyd et al., 2010b; stewart & amp; zack, 2008). Compared to the lan d-based gambler, the gambling motivation that the online gambler reports is the most common is the reason for dealing with (Dowling et al.) (2015; Goldstein, 2016), and the financial reasons (Barrault & Amp; Varescon, 2016), to satisfy the challenge desire or to show the skills (Dowling and 2015; Goldstein etc., 2016). For social reasons (Barraurt & Amp; Varescon, 2016), I believe that it will provide a fun social encounter for gambling (Dowling et al., 2015) et al. Goldstein et al. (2016) analyzed online gamblers that online gambling starts to gain money, or online for the following purposes. Was strong.

Conclusion

The same main motives emerged when online gamblers were surveyed and compared according to severity. Problem gamblers were more likely to report reasons related to the emotions gambling provokes, such as excitement (Gainsbury et al., 2014c), financial aspects (Gainsbury et al., 2014c; Khazaal et al., 2017), or occupational aspects such as wanting to make money from gambling (Barrault et al., 2017), and coping aspects such as the aim to relax (Khazaal et al., 2017). In contrast to what was previously stated regarding the possibility that coping motives act as risk factors, gambling for relaxation seems to be more commonly reported by non-problem gamblers in the Gainsbury et al. (2014c) paper. Moreover, non-problem gambling is often done for pleasure, to experience positive emotions, as a distraction from daily life and therefore relaxation (Barrault & Varescon, 2013b, 2016), and as a social outlet (Khazaal et al.).

Data availability

Aspects related to the intrinsic characteristics of online gambling have been discussed in depth in the introduction, but have been less investigated in the literature of this review. Compared to offline gamblers, online gamblers report greater motivations due to accessibility, ease of use, variety of sites and activities, anonymity, and prevention/protection (Hubert & Griffiths, 2018). Moreover, accessibility and anonymity are two of the reasons why problem gamblers are more likely to report than non-problem gamblers (McCormack et al., 2013b).

References

The choice of gambling method also seems to be influenced by aspects related to the gambler's interpersonal network. Studies have shown that the lower the quantity and quality of a gambler's relationships, the higher the chance of becoming an Internet gambler. An additional factor related to the online mode is reporting the subjective presence of problems in the home due to gambling (Mihaylova et al., 2013). At the relationship level, a single factor has been identified that increases the likelihood of developing problem gambling: having a gambler or problem gambler in the family. This result has been reported by two different authors, both in the general adult population (Lloyd et al., 2010a) and in university students (Harris et al., 2013).
In order to affect gambling, the environment and life background that the person belongs plays an important role, as well as personal and related factors. In the selected paper, few variables that act at the context level have been investigated. The environment of universities is the only environment that is investigated and evidence of risk factors. Academic problems in college students not only increase the chances of gambling using the Internet (mihaylova et al.
In this paper, the knowledge of online gambling dangerous factors and protection factors in adults is integrated. Several important factors have emerged from the implemented analysis. Regarding the methodology used in the research, two serious problems regarding the population and methods have emerged. Most papers use no n-representative samples. In future research, it is desirable to use samples that represent the population. Furthermore, most of the papers are crossing, but it is desirable to conduct vertical research in order to deepen the relationship between variables. In most papers, samples are mainly composed of men and emphasize that women are not included. Studies on women have reported that these gamblers are more risky to develop problematic gambling and are more attractive by Internet gambling. The topic was explored by a qualitative study by Corney and David (2010) focusing on the motivation of women's online gamblers. This paper suggests that the ease of access to gambling and the aspects related to anonymity are particularly related to women. In fact, online gambling that can be gambling at home and keeps anonymity is more attractive to women. For this reason, it would be appropriate to use typical samples in future research. In order to affect gambling, the environment and life background to which the person belongs plays an important role in the same way as personal and related factors. In the selected paper, few variables that act at the context level have been investigated. The environment of universities is the only environment that is investigated and evidence of risk factors. Academic problems in college students not only increase the chances of gambling using the Internet (mihaylova et al.
In this paper, the knowledge of online gambling dangerous factors and protection factors in adults is integrated. Several important factors have emerged from the implemented analysis. Regarding the methodology used in the research, two serious problems regarding the population and methods have emerged. Most papers use no n-representative samples. In future research, it is desirable to use samples that represent the population. Furthermore, most of the papers are crossing, but it is desirable to conduct vertical research in order to deepen the relationship between variables. In most papers, samples are mainly composed of men and emphasize that women are not included. Studies on women have reported that these gamblers are more risky to develop problematic gambling and are more attractive by Internet gambling. The topic was explored by a qualitative study by Corney and David (2010) focusing on the motivation of women's online gamblers. This paper suggests that the ease of access to gambling and the aspects related to anonymity are particularly related to women. In fact, online gambling that can be gambling at home and keeps anonymity is more attractive to women. For this reason, it would be appropriate to use typical samples in future research. In order to affect gambling, the environment and life background that the person belongs plays an important role, as well as personal and related factors. In the selected paper, few variables that act at the context level have been investigated. The environment of universities is the only environment that is investigated and evidence of risk factors. Academic problems in college students not only increase the chances of gambling using the Internet (mihaylova et al.
In this paper, the knowledge of online gambling dangerous factors and protection factors in adults is integrated. Several important factors have emerged from the implemented analysis. Regarding the methodology used in the research, two serious problems regarding the population and methods have emerged. Most papers use no n-representative samples. In future research, it is desirable to use samples that represent the population. Furthermore, most of the papers are crossing, but it is desirable to conduct vertical research in order to deepen the relationship between variables. In most papers, samples are mainly composed of men and emphasize that women are not included. Studies on women have reported that these gamblers are more risky to develop problematic gambling and are more attractive by Internet gambling. The topic was explored by a qualitative study by Corney and David (2010) focusing on the motivation of women's online gamblers. This paper suggests that the ease of access to gambling and the aspects related to anonymity are particularly related to women. In fact, online gambling that can be gambling at home and keeps anonymity is more attractive to women. For this reason, it would be appropriate to use typical samples in future research.
The review identified several factors. Social variables are the most studied in both comparisons. Gender, age, education level, occupation, income, and marital status have been primarily investigated. Being male and younger age seem to be more associated with online gamblers than offline gamblers, and with problem online gamblers than non-problem gamblers. Furthermore, higher education, higher income, and higher employment history are more likely to be associated with online gamblers than offline gamblers. At the same time, when looking at online gamblers, these factors seem to be more associated with non-problem gamblers than problem gamblers. Other contradictory results include marital status and emotional relationship. Having a stable partner seems to be more associated with online gambling than offline gambling, despite being more associated with non-problem gamblers than problem gamblers. Having dependent children is more likely to be associated with online gambling and problem gamblers, but has only been studied in a few papers.
Gambling patterns and behaviors are the second most studied category of factors. According to many papers, high gambling intensity, high variability and high expenditure are more likely to be associated with online gamblers and are risk factors for problem gambling. The same associations have been reported for longer session duration and earlier onset of gambling behavior. Some factors have only been studied in the second comparison. Among these, solitary gambling (not using virtual chats or forums), being a mixed-mode and long-term gambler, using mobile devices for gambling and having episodes of addiction represent risk factors for problem online gamblers, although only a few studies have shown these results.
Risky behaviors such as alcohol, drug and tobacco consumption have been studied in both comparisons. Substance misuse is more likely to be associated with online gamblers than with offline gamblers and with online problem gamblers than with less problem gamblers. Furthermore, similar associations have been reported for heavy media use and deliberate self-harm is more likely to be found in online problem gamblers.
Factors related to physical well-being have been less investigated and are mainly concerned with the comparison of online and offline gamblers. Offline gamblers appear to be more interested in healthy activities, feel healthier, and generally feel better fit than their online counterparts.
The psychological aspects are slightly investigated, and most of these papers are studying only the second comparison. Online problem gamblers tend to report psychological pain, anxiety, or depressive status than no n-problem gamblers. A small number of studies report that the negative mood, the extreme emotions during gambling, and the mood disorders are more likely to be related to the online problem gambler. However, one paper indicates that high emotional intelligence (emotional awareness, sel f-assertion, sel f-care, sel f-supporting, sel f-realization) may work as a protection factor, but further investigations are needed.
The personality characteristics are not widely investigated. High impulsive is the most wel l-studied factor, and as well as having the character of dysfunction, it is most associated with online problem gamblers. In contrast, online gamblers have a lower level of sociality and are at a high level of frugals than offline gamblers. Regarding cognitive elements, there is a high possibility that gambling is rich in cognitive distortion (as the illusion of control), which is more related to online and online gamblers than offline and no n-problem gamblers.
It has been shown that gambling attitudes affect the selection of gambling methods. It is said that a positive attitude toward online gambling is likely to be related to Internet gambling, and taking a negative attitude is likely to be related to the gambling of the problem. 。 This result should be further investigated.
Of the various reasons for gambling, social motives are often related to offline gamblers and no n-problem gamblers, and financial reasons are often related to online gambling and problem gambling. Further research is needed because there are contradictory results for dealing motivation and pleasure motivation, and it is not clear how these motives affect gambling behavior.
Relaxed factors and contextual factors are rarely noticed. There are several papers that suggest that having rare and negative relationships is easy to associate with online gambling. In addition, gambling in the family can affect the possibility of a problem gambler. Furthermore, problems in the context of life, such as studying, are reported mainly by online gambling people and problem gamblers.
The results of reviews on risk factors and protection factors indicate that the risk factors have been investigated more than protective factors. This significance emphasizes the need to identify variables associated with positive results and to intervene with the need to strengthen research from a happiness promoting approach. Furthermore, among the analytical levels studied in the literature, the deepest level is related to the individual aspects, and both relative and contextual levels are not much studied. In future research, it will be necessary to focus on the impact of the environment on individuals and incorporate a psychological social perspective to at least the level of all types. In addition, some of the factors are rarely investigated in the literature. For example, physical happiness, emotional and social functions, and variables related to interpersonal skills. One of the themes that is repeated in the category is the bond with others. In general, the existence of others in various situations in life works as a defensive factor in a problem gambling, and the absence of others seems to work as a dangerous factor. In the reviews, the level of relationships has not been investigated much, but at the individual level is studying the positive effects of relation. For example, the following is a marriage, dating a stable partner, and a gambling addiction preventive factor: Reviews on risk factors and protection factors indicate that the risk factors are more surveyed than protective factors. This significance emphasizes the need to identify variables associated with positive results and to intervene with the need to strengthen research from a happiness promoting approach. Furthermore, among the analytical levels studied in the literature, the deepest level is related to the individual aspects, and both relative and contextual levels are not much studied. In future research, it will be necessary to focus on the impact of the environment on individuals and incorporate a psychological social perspective to at least the level of all types. In addition, some of the factors are rarely investigated in the literature. For example, physical happiness, emotional and social functions, and variables related to interpersonal skills. One of the themes that is repeated in the category is the bond with others. In general, the existence of others in various situations in life works as a defensive factor in a problem gambling, and the absence of others seems to work as a dangerous factor. In the reviews, the level of relationships has not been investigated much, but at the individual level is studying the positive effects of relation. For example, the following is a marriage, dating a stable partner, and a gambling addiction preventive factor: The results of reviews on risk factors and protection factors indicate that the risk factors have been investigated more than protective factors. This significance emphasizes the need to identify variables associated with positive results and to intervene with the need to strengthen research from a happiness promoting approach. Furthermore, among the analytical levels studied in the literature, the deepest level is related to the individual aspects, and both relative and contextual levels are not much studied. In future research, it will be necessary to focus on the impact of the environment on individuals and incorporate a psychological social perspective to at least the level of all types. In addition, some of the factors are rarely investigated in the literature. For example, physical happiness, emotional and social functions, and variables related to interpersonal skills. One of the themes that is repeated in the category is the bond with others. In general, the existence of others in various situations in life works as a defensive factor in a problem gambling, and the absence of others seems to work as a dangerous factor. In the reviews, the level of relationships has not been investigated much, but at the individual level is studying the positive effects of relation. For example, the following is a marriage, dating a stable partner, and a gambling addiction preventive factor:
Most of the results of the factors are consistent with Gainsbury reviews (2015) and past documents on the risk factors of the problem gambling. For example, being a male, a young adult, having a gambling behavior that features high strength, variability, and high spending, lon g-term gambling, quickly developing gambling. The fact that the substance was misused, the psychological distress of gambling, the impulsivity, and the distortion of cognitive distortion were confirmed as the danger factor of the problem gambling. Furthermore, the fact that academic problems and gambling are familiar is also a dangerous factor for gambling. However, this review has emerged many other protection factors and dangerous factors, including social support, healthy lifestyles, emotions, motivation, use of technology, and interaction with others. This review is different from GainSbury's reviews in order to use additional and more systemized classifications in reading gambling danger factors and protective factors. Specifically, the difference between the degree of online gambling and the online gambling and the offline gambling. It is important to include these two comparisons in order to consider the differences between the complexity of online gambling and the target involved. These two comparisons have emerged similarities and differences, and the specific need for further investigations has been revealed. Most of the results of F factors are consistent with those that have emerged from Gainsbury reviews (2015) and past documents on the risk factors of the problem gambling. For example, being a male, a young adult, having a gambling behavior that features high strength, variability, and high spending, lon g-term gambling, quickly developing gambling. The fact that the substance was misused, the psychological distress of gambling, the impulsivity, and the distortion of cognitive distortion were confirmed as the danger factor of the problem gambling. Furthermore, the fact that academic problems and gambling are familiar is also a dangerous factor for gambling. However, this review has emerged many other protection factors and dangerous factors, including social support, healthy lifestyles, emotions, motivation, use of technology, and interaction with others. This review is different from GainSbury's reviews in order to use additional and more systemized classifications in reading gambling danger factors and protective factors. Specifically, the difference between the degree of online gambling and the online gambling and the offline gambling. It is important to include these two comparisons in order to consider the differences between the complexity of online gambling and the target involved. These two comparisons have emerged similarities and differences, and the specific need for further investigations has been revealed. Most of the results of the F factors are consistent with Gainsbury reviews (2015) and past documents on the danger factors of the gambling gambling. For example, being a male, a young adult, having a gambling behavior that features high strength, variability, and high spending, lon g-term gambling, quickly developing gambling. The fact that the substance was misused, the psychological distress of gambling, the impulsivity, and the distortion of cognitive distortion were confirmed as the danger factor of the problem gambling. Furthermore, the fact that academic problems and gambling are familiar is also a dangerous factor for gambling. However, this review has emerged many other protection factors and dangerous factors, including social support, healthy lifestyles, emotions, motivation, use of technology, and interaction with others. This review is different from GainSbury's reviews in order to use additional and more systemized classifications in reading gambling danger factors and protective factors. Specifically, the difference between the degree of online gambling and the online gambling and the offline gambling. It is important to include these two comparisons in order to consider the differences between the complexity of online gambling and the target involved. These two comparisons have emerged similarities and differences, and the specific need for further investigations has been revealed. F
In conclusion, with the aim of filling the gap in literature on online gambling preventive factors, the results of this literature review are to develop efficient prevention strategies beyond the responsible gambling option provided by the gambling platform. The foundation can be provided (Gainsbury et al., 2014a; Velasco et al., 2021). These findings are most fascinated by online gambling and contribute to identifying the most vulnerable groups in the onset of problem gambling. These people should focus on future research and do individual interventions with a focus on targets. From a more general prevention point of view, there is a need for more cooperation between research evidence, institutions, and institutions to support gambling disadvantaged policies and social culture to protect the health of online gamblers. Specifically, given the common nature of online gambling and offline gambling and protection factors, it seems that there is no need to create a new preventive intervening measure that specializes in online gambling directly. On the other hand, given that there are aspects related only to online gamblers and there are differences in social variables, it is reasonable to r e-evaluate some intervention measures to adapt to these specificity. It seems to be in the way. For example, given that gamblers of groups (highly educated), which are considered to be low risk, are strongly attracted to gambling, target them with a specific intervention. It would be important to include it in a universal intervention. On the other hand, gamblers, which have few resources, are likely to be a problematic gambler, so it seems needed to be involved in the instructions to promote or strengthen protection factors. You should be more careful about accepting and dealing with a female gambler taboo. Despite being a very valuable theme, it was rarely featured in the reviews included in the reviews. Finally, when planning an online gambling preventive intervention, the relationship between social relationships and sociality during gambling should be considered. Gambling online access can promote lonely play and isolated habits and reduce social protection factors. As a conclusion, for the purpose of filling the gap in literature on online gambling preventive factors, the result of this literature review is developed an efficient prevention strategy beyond the responsible gambling option provided by the gambling platform. You can provide the basics to do (Gainsbury et al., 2014a; Velasco et al., 2021). These findings are most fascinated by online gambling and contribute to identifying the most vulnerable groups in the onset of problem gambling. These people should focus on future research and do individual interventions with a focus on targets. From a more general prevention point of view, there is a need for more cooperation between research evidence, institutions, and institutions to support gambling disadvantaged policies and social culture to protect the health of online gamblers. Specifically, given the common nature of online gambling and offline gambling and protection factors, it seems that there is no need to create a new preventive intervening measure that specializes in online gambling directly. On the other hand, given that there are aspects related only to online gamblers and there are differences in social variables, it is reasonable to r e-evaluate some intervention measures to adapt to these specificity. It seems to be in the way. For example, given that gamblers of groups (highly educated), which are considered to be low risk, are strongly attracted to gambling, target them with a specific intervention. It would be important to include it in a universal intervention. On the other hand, gamblers, which have few resources, are likely to be a problematic gambler, so it seems needed to be involved in the instructions to promote or strengthen protection factors. You should be more careful about accepting and dealing with a female gambler taboo. Despite being a very valuable theme, it was rarely featured in the reviews included in the reviews. Finally, when planning an online gambling preventive intervention, the relationship between social relationships and sociality during gambling should be considered. Gambling online access can promote lonely play and isolated habits and reduce social protection factors. In conclusion, with the aim of filling the gap in literature on online gambling preventive factors, the results of this literature review are to develop efficient prevention strategies beyond the responsible gambling option provided by the gambling platform. The foundation can be provided (Gainsbury et al., 2014a; Velasco et al., 2021). These findings are most fascinated by online gambling and contribute to identifying the most vulnerable groups in the onset of problem gambling. These people should focus on future research and do individual interventions with a focus on targets. From a more general prevention point of view, there is a need for more cooperation between research evidence, institutions, and institutions to support gambling disadvantaged policies and social culture to protect the health of online gamblers. Specifically, given the common nature of online gambling and offline gambling and protection factors, it seems that there is no need to create a new preventive intervening measure that specializes in online gambling directly. On the other hand, given that there are aspects related only to online gamblers and there are differences in social variables, it is reasonable to r e-evaluate some intervention measures to adapt to these specificity. It seems to be in the way. For example, given that gamblers of groups (highly educated), which are considered to be low risk, are strongly attracted to gambling, target them with a specific intervention. It would be important to include it in a universal intervention. On the other hand, gamblers, which have few resources, are likely to be a problematic gambler, so it seems needed to be involved in the instructions to promote or strengthen protection factors. You should be more careful about accepting and dealing with a female gambler taboo. Despite being a very valuable theme, it was rarely featured in the reviews included in the reviews. Finally, when planning an online gambling preventive intervention, the relationship between social relationships and sociality during gambling should be considered. Gambling online access can promote lonely play and isolated habits and reduce social protection factors.
This review has several limits. It does not include met a-analysi s-specific statistics to evaluate the results. However, the ability of this review, which integrates evidence over many documents, provides valid outline and some recommendations. Regarding the recorded studies, not all papers show the same level of methodological quality, and the standards used in research groups were quite different. In addition, the literature has no clear definition to distinguish between online and offline gamblers. In fact, some authors consider only those who use this mode as an online gambler, while others define those who use online mode and define those who gamble offline as online gamblers. In consideration of the heterogeneity of the literature and the need to integrate and systematize the results, information about "exclusively Internet gambler" or "mixed mode gambler" is the same online gambler, regardless of the definition used by the author. Included in the category of. Behind this choice, there were only a few papers that specified such an exclusive distinction, so we considered online gamblers that are at least partially online. Furthermore, there is no unified or agreed definition to classify online gamblers depending on the strength of gambling, so we considered an online gambler without distinguishing the author's different definitions. For example, this review of online gambling has several limits. It does not include met a-analysi s-specific statistics to evaluate the results. However, the ability of this review, which integrates evidence over many documents, provides valid outline and some recommendations. Regarding the recorded studies, not all papers show the same level of methodological quality, and the standards used in research groups were quite different. In addition, the literature has no clear definition to distinguish between online and offline gamblers. In fact, some authors consider only those who use this mode as an online gambler, while others define those who use online mode and define those who gamble offline as online gamblers. In consideration of the heterogeneity of the literature and the need to integrate and systematize the results, information about "exclusively Internet gambler" or "mixed mode gambler" is the same online gambler, regardless of the definition used by the author. Included in the category of. Behind this choice, there were only a few papers that specified such an exclusive distinction, so we considered online gamblers that are at least partially online. Furthermore, there is no unified or agreed definition to classify online gamblers depending on the strength of gambling, so we considered an online gambler without distinguishing the author's different definitions. For example, this review of online gambling has several limits. It does not include met a-analysi s-specific statistics to evaluate the results. However, the ability of this review, which integrates evidence over many documents, provides valid outline and some recommendations. Regarding the recorded studies, not all papers show the same level of methodological quality, and the standards used in research groups were quite different. In addition, the literature has no clear definition to distinguish between online and offline gamblers. In fact, some authors consider only those who use this mode as an online gambler, while others define those who use online mode and define those who gamble offline as online gamblers. In consideration of the heterogeneity of the literature and the need to integrate and systematize the results, information about "exclusively Internet gambler" or "mixed mode gambler" is the same online gambler, regardless of the definition used by the author. Included in the category of. Behind this choice, there were only a few papers that specified such an exclusive distinction, so we considered online gamblers that are at least partially online. Furthermore, there is no unified or agreed definition to classify online gamblers depending on the strength of gambling, so we considered an online gambler without distinguishing the author's different definitions. For example, online gambling
The aim of this paper is to review knowledge and evidence on factors influencing the likelihood of developing online gambling addiction and problem gambling behaviors in adults. The review synthesized and organized risk and protective factors associated with online gambling. Specifically, it compared factors that distinguish offline gamblers from online gamblers, and compared online non-problem gamblers with online problem gamblers. Furthermore, further comparisons were made to clarify whether similarities or differences in the results emerged in terms of the factors investigated between the first and second comparisons. The results of this study are useful in suggesting directions for the development of prevention programs targeted at offline and online gamblers, which can aim to strengthen or increase protective factors and limit and reduce risk factors. Furthermore, this review provides some suggestions for distinguishing online problem gambling from non-problem gambling. Finally, this review found that even though most risk and protective factors are common to online and offline gamblers, some variables are not. These factors may be important to consider when projecting prevention interventions targeting target online gamblers and problem online gamblers.
Data sharing does not apply to this paper as no new data were generated or analyzed in this study.
Abbott, M. W. (2020). The changing epidemiology of gambling disorders and gambling-related harm: Public health implications. https://doi. org/10. 1016/j. puhe. 2020. 04. 003ArticleCASPubMedGoogle Scholar
Barrault, S., & amp; Varescon, I. (2013a). Cognitive distortions, anxiety, and depression in habitual and pathological online poker players. Cyberpsychology, Behavior, and Social Networking, 16 (3), 183-188. https://doi. org/10. 1089/cyber. 2012. 0150ArticlePubMedGoogle Scholar.
Barrault, S., & amp; Varescon, I. (2013b). Compulsive sensation seeking and gambling behavior in a sample of online poker players: A comparison between nonpathological, problem, and pathological gamblers. https://doi. org/10. 1016/j. paid. 2013. 04. 022ArticleGoogle Scholar.
Barrault, S., & amp; Varescon, I. (2016). Online and live poker players: Do they differ in their compulsive sensation seeking and gambling practices? Journal of Behavioral Addictions, 5 (1), 41-50. https://doi. org/10. 1556/2006. 5. 2016. 015ArticlePubMedPubMed CentralGoogle Scholar
Barrault, S., Bonnaire, C., & amp; Herrmann, F. (2017). Anxiety, depression, and emotion regulation in frequent online poker players. Journal of Gambling Studies, 33 (4), 1039-1050. https://doi. org/10. 1007/s10899-017-9669-3ArticlePubMedGoogle Scholar.
Bolen, D. W., & amp; Boyd, W. H. (1968). Gambling and gamblers: A review and preliminary findings. Archives of General Psychiatry, 18 (5), 617-630. https://doi. org/10. 1001/archpsyc. 1968. 01740050105018ArticleCASPubMedGoogle Scholar
Braverman, J., & amp; Shaffer, H. J. (2012). How problem gamblers start gambling: Identifying behavioral markers of high-risk Internet gambling. The European Journal of Public Health, 22 (2), 273-278. https://doi. org/10. 1093/eurpub/ckp232ArticlePubMedGoogle Scholar
Brodeur, M., Audette-Chapdelaine, S., Savard, A. C., & amp; Kairouz, S. (2021). Gambling and the COVID-19 pandemic: a scoping review. Progress in Neuro-Psychopharmacology and Biological Psychiatry . https://doi. org/10. 1016/j. pnpbp. 2021. 110389ArticlePubMedGoogle Scholar
Calado, F., & amp; Griffiths, M. D. (2016). Problem gambling worldwide: an update of empirical research and systematic review (2000-2015). Journal of Behavioral Addictions, 5 (4), 592-613. https://doi. org/10. 1556/2006. 5. 2016. 073ArticlePubMedPubMed CentralGoogle Scholar
Coie, J. D., Watt, N. F., West, S. G., Hawkins, J. D., Asarnow, J. R., Markman, H. J., Ramey, S. L., Shure, M. B., & amp; Long, B. (1993). The science of prevention: A conceptual framework and directions for a national research program. American Psychologist, 48 (10), 1013-1022. https://doi. org/10. 1037/0003-066X. 48. 10. 1013ArticleCASPubMedGoogle Scholar
Corney, R., & amp; Davis, J. (2010). The attractions and risks of Internet gambling for women: A qualitative study. https://doi. org/10. 4309/jgi. 2010. 24. 8ArticleGoogle Scholar.
Dickson, L., Derevensky, J. L., & amp; Gupta, R. (2008). Gambling problems among adolescents: An examination of risk and protective factors. International Gambling Studies, 8 (1), 25-47. https://doi. org/10. 1080/14459790701870118ArticleGoogle Scholar
Dowling, N. A., Lorains, F. K., & Amp; Jackson, A. C. (2015). Can the Internet Gambler profile in the past year be a normal Internet gambler? Computers in Human BEHAVIOR, 43, 118-128. Https://doi. org/10. 1016/j. chb. 2014. 10. 019Articlegoogle Scholar
Dowling, N. A., S. S. S., C. J., OLDENHOF, TOUMBOUROU, J. W., & Amp; YouSSEF, G. J. (2017). Systematic reviews and meta analysis 。 Clinical Psychology Review., 51, 109-124. Https://doi. org/10. 1016/j. cpr. 2016. 10. 008ArticleCaspubmedGoogle Scholar
DUFOUR, M., Brunelle, N., & Amp; Roy, é. (2013). Potential class analysis. https://doi. org/10. 1007/s10899-013-9429-yarticleGoogle schoolar.
Dufour, M., Morvannou, A., Laverdière, é., Brunelle, N., Kairouz, S., Nolin, M. A, Nadeau, Nadeau, L., dussault, F., & amp; Berbiche, D. (2020). If you do an online poker, is it always online poker? Two years of trajectory of poker modality. Addictive BehavioRs Reports, 11. https://doi. org/10. 1016/j. Abrib. 2020. 100251
Edgren, R., Castrén, S., ALHO, H., & amp; Salonen, A. H. Computers in Human BEHAVIOR, 72, 46-56. Https://doi. org/10. 1016/j. chb. 2017. 02. 033articleGOOGLE SCHOLAR
Gainsbury, S. (2012). Internet gambling: Internet gambling: Current research results and meaning. Https://doi. org/10. 1007/978-1007/978-1-4614-3390-3BookGoogle Schoolar
GainSbury, S., Wood, R., Russell, A., Hing, N., & amp; Blaszczynski, A. (2012). Digital Revolution: Digital Revolution: Digital Revolution: Digital Revolution: Internet Gambler and No n-Internet Gambler Population Statistical Professional Producer Comparison of attitude and gambling behavior. Computers in Human BEHAVIOR, 28 (4), 1388-1398. Https://doi. org/10. 1016/j. chb. 2012. 02. 024ArticleGOOGLE SCHOLAR
Gainsbury, S. M. (2015). Online gambling addiction: Internet gambling and disturbed gambling. Current Addiction Reports, 2 (2), 185-193. Https://doi. org/10. 1007/s40429-015-0057-8articlePubmedPubmed CentralGoogle Schoolar
GainSbury, S. M., BLANKERS, M., C., Schelleman-OFFERMANS, K., & Amp; Cousijn, J. (2014a). International Gambling minimization guidelines: Effective public health policy Comparison. https://doi. org/10. 1007/s10899-013-9389-2articlePubmedGoogle Schoolar.
Gainsbury, S. M., LIU, Y., Russell, A. M. T., & Amp; Teichert, T. (2016). Are all internet gambling a problem? Consider the relationship between access form and gambling problem. Computers in Human BEHAVIOR, 55, 717-728. Https://doi. org/10. 1016/j. chb. 2015. 10. 006Articlegoogle Scholar.
Gainsbury, S. M., Russell, A., Blaszczynski, A., & amp; hing, n. (2015a). European Journal of Public Health, 25 (4), 723-728. Https://doi. org/10. 1093/eurpub/ckv006articlePubmedPubmed CentralGOLGLE SCHOLAR
Gainsbury, S. M., Russell, A., Blaszczynski, A., & Amp; Hing, N. (2015B). Gambling and access form interactions: Internet only, land basis, and comparison of gamblers in mixed mode. Addictive Behaviors, 41, 34-40. Https://doi. org/10. 1016/j. addbeh. 2014. 09. 023articlePubmedGoogle Scholar
Gainsbury, S. M., Russell, A., Hing, N., Wood, R., & Amp; Blaszczynski, A. Comparison of. Psychology of Addictive Behaviors, 27 (4), 1092. https://doi. org/10. 1037/a0031475articlePubmedGoogle Scholar
Gainsbury, S. M., Russell, A., Hing, N., Wood, R., Lubman, D. I., & Amp; Blaszczynski, A. (2014b). Evaluation of technology effects. PSYCHOLOGY OF ADDICTIVE BEHAVIORS: JOURNAL OF TO PSYCHOLOLOGISTS IN Addictive BEHAVIORS, 28 (3), 769-779. A0036207articlePubmedGoogle Schoolar.
Gainsbury, S. M., Russell, A., Wood, R., Hing, N., & amp; Blaszczynski, A. (2015c). What is the risk of Internet gambling? Comparison of Internet gambler su b-groups based on gambling addiction. New Media & Amp; Society, 17 (6), 861-879. Https://doi. org/10. 1177/146144444813518185Articlegoogle Scholar.
Gainsbury, S. M., SUHONEN, N., & amp; Saastamoinen, J. (2014c). Tracking losses in online pokers and casino games: Gamblin g-addicted Internet gamblers and game play. Psychiatry research, 217 (3), 220-225. Https://doi. org/10. 1016/j. psychres. 2014. 03. 033articlePubmedGoogle Scholar
Goldstein, A. L., Vilhena-Churchill, N., Stewart, S. H., Hoaken, P. N. S., & amp; Flett, G. L. (2016). 気分、動機、お金：オンラインと非オンラインの若年成人ギャンブラーを区別する要因の検討。 Journal of BEHAVIORAL ADDICTIONS, 5 (1), 68-76. Https://doi. org/10. 1556/2006. 5. 2016. 003ArticleepubmedPubmed CentralGOGLE SCHOLAR
Granero, R., Jiménez-Murcia, S., Del Pino-Gutiéérrez, a., Mora, b. , Codina, E., lópez-genzález, H, H, H, H, Mena-Moreno, T., Mestre-Bach, G., Valero-Solís, S., Rivas, S., S. LOZANO-MADRID, M., Menchón, J. M., & amp; Fernández-Aranda, F. (2020). Frontiers in psychiatry . https: //doi. org/10. 3389/fpsyt. 2020. 00482articlePubmed centralGOOGLE SCHOLAR
Griffiths, M., Parke, J., Wood, R., & amp; rigbye, J. (2010). Online poker gambling for university students: Further discovered from online surveys. International Journal of Mental Health and Addition, 82-89. Https://doi. org/10. 1007/s11469-009-920-7ArticleGoogle Scholar.
Griffiths, M., Wardle, H., ORFORD, J., Sproston, K., & Amp; Erens, B. (2011). Internet gambling, health, smoking, alcohol use: 2007 British gambling addiction rate Survey The result of. International Journal of Mental Health and Addition, 9 (1), 1-11. Https://doi. org/10. 1007/s11469-009-9246-9articleGOOGLE SCHOLAR.
HARRIS, N. M., Mazmanian, D., & amp; Jamieson, J. Gambling problem journal https://doi. org/10. 4309/jgi. 2013. 28. 5articleglegle school
Hing, n., gainsbury, s., blazzczynski, a., lubman, lubman, d., & amp; russell, a. (2014). Interactive gambling. QUOR, GAMING AND RACING , Department of Justice, Victoria.
Hing, N., Russell, A. M., & amp; Browne, M. (2017). Risk of gambling problems in online electronic game consoles, lacebetting, and sports betting. Frontiers in psychology . https: //doi. org/10. 3389/fpsyg. 20779sticlepubmed centralGOGLE SCHOLAR
Hodgins, D. C., & amp; Stevens, R. M. G. (2021). COVID-19 effects on gambling and gambling disorders: New data. Current option in psychiatry, 34 (4), 332-343. Https://doi. org/10. 1097/yco. 0000000000009articlePubmedPubmed centralGOGLE SCHOLAR
HOPLEY, A. A. B., & amp; nicki, R. M. (2010). Cyberpsychology, behavior, and social networking, 13 (4), 379-385. Https://doi. org/10. 1089/cyber. 2009. 0223articlePubmedGle Skolar
Hubert, P., & Amp; griffiths, M. D. (2018). Comparison of online and offline gambling in Portugal's pathological gamblers: Evilic research. International Journal of Mental Health and Addition, 1219-1237. Https://doi. org/10. 1007/s11469-017-9846-846-846-846-8articlePubmedGoGle R.
Kairouz, S., Paradis, C., & amp; nadeau, L. (2012). Is the online gambler higher than offline gamblers? CyberPsychology, Behavior, and Social Networking, 15 (3), 175-180. Https://doi. org/10. 1089/cyber. 2011. 0260articlePubmedGoogle Scholar.
Khaza, Y., Chatton, A., ACHAB, S., Monney, Thorens, G., Dufour, M., Zullino, Zullino, D., & Amp; Rothen, S. (2017). Internet gamblers are social Different in variables: potential class analysis. https://doi. org/10. 1007/s10899-016-016-9664-0articlePubmedGoogle schoolar.
Kim, H. S., & Amp; King, D. L. (2020). I. ORG/10. 1080/14459795. 2020. 18229055Articlegoogle Schoolar.
Laplainte, D. A., Nelson, S. E., & amp; Gray, H. M. (2014). Deeply involved and deep involvement: Understand the relationship between involvement in Internet gambling and gambling addiction. Psychology of Addictive Behaviors, 28 (2), 396-403. Https://doi. org/10. 1037/a0033810ARTICLEPUBMEDGOGLE SCHOLAR

Funding

Lelonek-kuleta, B., BARTCZUK, R. P., WIECHETEK, M., Chwaszcz, J., & Amp; NIEWIADOMSKA, I. (2020). International Journal of ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH. E Scholar

Author information

Authors and Affiliations

LLOYD, J., H., Hawton, K., Dutton, W. H., Geddes, J. R., GOODWIN, G. M., & amp; Rogers, R. D. (2010A). Internet gambler: Her actions and health experiences. https://doi. org/10. 1007/s10899-010-9188-yarticlePubmedGOOGLE SCHOLAR.
LLOYD, J., H., Hawton, K., Dutton, W. H, Geddes, J. R., GOODWIN, G. M., & Amp; Rogers, R. D. (2010B). Is it: Internet gambler online research. Biological psychiatry, 68 (8), 733-740. Https://doi. org/10. 1016/j. biopsych. 2010. 03. 038articlePubmedGoogle Scholar

MacKay, T. L., & amp; Hodgins, D. C. (2012). Cognitive distortions as a risk factor for problem gambling on the Internet. International Gambling Studies, 12 (2), 163-175. https://doi. org/10. 1080/14459795. 2011. 648652ArticleGoogle Scholar

The Rise of Mobile Gambling Is Leaving People Ruined and Unable to Quit

McCormack, A., Shorter, G. W., & amp; Griffiths, M. D. (2013a). Examining the relationship between online gambling participation and problem gambling. https://doi. org/10. 1556/JBA. 2. 2013. 1. 5ArticlePubMedGoogle Scholar.

McCormack, A., Shorter, G. W., & amp; Griffiths, M. D. (2013b). Characteristics and predictors of problem gambling on the Internet. International Journal of Mental Health and Addiction, 11 (6), 634-657. https://doi. org/10. 1007/s11469-013-9439-0ArticleGoogle Scholar.

Videos by VICE

Mihaylova, T., Kairouz, S., & amp; Nadeau, L. (2013). Online poker gambling among college students: Risky endeavor or harmless pastime? Problem Gambling Journal https://doi. org/10. 4309/jgi. 2012. 27. 15Article Google Scholar Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., Stewart, L. A., Estarli, M., Barrera, E. S. A., Martínez-Rodríguez , R, Baladia, E., Agüero, S. D., Camacho, S., Buhring, K., Herrero-López, A., Gil-González, D. M., Altman, D. G., Booth, A., & amp; Whitlock, E. (2016). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Revista Espanola De Nutricion Humana y Dietetica, 20 (2), 148-160. https://doi. org/10. 1186/2046-4053-4-1ArticleGoogle Scholar

Moreau, A., Chauchard, É., Sévigny, S., & amp; Giroux, I. (2020). Tilt in online poker: loss of control and gambling disorders. International Journal of Environmental Research and Public Health, 17 (14), 1-14. https://doi. org/10. 3390/ijerph17145013ArticleGoogle Scholar

Perrot, B., Hardouin, J. B., Grall-Bronnec, M., & amp; Challet-Bouju, G. (2018). Typifying online lottery and scratch game gambler behavior: A multilevel latent class cluster analysis applied to player account-based gambling data. International Journal of Methods in Psychiatric Research . https://doi. org/10. 1002/mpr. 1746ArticlePubMedPubMed CentralGoogle Scholar

Redondo, I. (2015). Assessing the risks associated with online lottery and casino gambling: A comparative analysis of players' personal characteristics and gambling types. International Journal of Mental Health and Addiction, 13 (5), 584-596. https://doi. org/10. 1007/s11469-014-9531-0ArticleGoogle Scholar.

Schiavella, M., Pelagatti, M., Westin, J., Lepore, Lepore, G., & amp; Cherubini, P. (2018). Online Poker Player Profiling: Execution function is correlated with poker abilities and problems gambling ? Gambling Research Journal, 34 (3), 823-851. Https://doi. org/10. 1007/s10899-017-9741- ZarticlePubmedGoogle Scholar

Serpelloni, G. (2013). Gambling gambling is a problem and pathological: General Overview, Physical Mechanism, Vulnerability, Scientific Evidence for Prevention / Treatment / Recovery. Scientific evidence for disease prevention, treatment, and recovery.

Shead, N. W., Derevensky, J. L., Fong, T. W., & amp; GUPTA, R. (2012). Journal of College Student Development, 53 (1), 133-148. Https://www. proquest MONG-SAMPLE/DOCVIEW/922390516/SE-2

Stewart, S. H., & amp; Zack, M. (2008). Development and psychological evaluation of 3D gambling motivation form. Addiction, 103 (7), 1110-1117. Https://doi. org/10. 1111/j. 1360-0443. 2008. 02235. xarticlePubmedGoogle Scholar

Velasco, V., Scattola, P., Gavazzeni, L., MARCHESI, L., Nita, I. E., & amp; Comprehensive review of evidence. International Journal of ENVIRONMENTAL RESEARCH and PUBLIC HEALTH, 18 (18), 9484. CentralGOOGLE SCHOLAR

Wardle, H., Moody, A., GRIFFORD, M., ORFORD, J., & Amp; Volberg, R. (2011). Evidence from the Definition and behavior of online gamblers: Evidence from the UK Gamble League Survey 2010 。 International Gambling Studies, 11 (3), 339-356. Https://doi. org/10. 1080/14459795. 201. 628684Articleglegoom

Wood, R. T., & amp; Williams, R. J. (2011). Internet gambler comparison profile: Appigible Features, Game Play patterns, gambling addiction. New Media and Society, 13 (7), 1123-1141. Https://doi. org/10. 1177/1461444810397650ARTICOGLE SCHOLAR

Wu, A. S. S. S. S., Lai, M. H. C., & amp; Tong, K. K. (2015). Internet gambling for local working adults and university students in Macau. https://doi. org/10. 1007/s10899-014-9451-8articlePubmedGoogle Schoolar.

Zuckerman, M., & amp; kuhlman, m. (2000). Personality and risk take: Common biological social factors. https://doi. org/10. 1111/1467-6494. 00124articleCaspubmedGoogle Schoolar.

Providing open access funds by the CRU I-CARE agreement at the University of Milan University Bikokka (Università DEGLI STUDI DI Milan o-bicocca). This study is a subsidy 2609/2019, a assistance for science cooperation with Società Cooperativa SoccoLo Principe (ID IRIS: 2021-ECO-0031). It was.

Milan Bikokka University Psychology Department (Piazza Dell Ateneo Nuovo 1, 20126, Milan, Italy) Michela Ghelfi & amp; veronica Velasco

Piccolo Princippe Social Cooperative, 24061, Bergamo, Italian Paola Scatula & Zilbert Juditi

Michela Gelfi

The bad situation for Jason was recently that it became gambling on mobile phones and became socially acceptable.

Most of my life bet on poker with friends and sometimes go to casinos when I was a teenager. I sometimes bet on sports through a company based overseas.

Until the pandemic occurs. Last year, sports gambling was legalized in his local Illinois, and casino gambling was also expanded. It didn't take much time for Jason to hear about gambling every day. In 2020, when a personal problem began to occur at home, he began to take a break at a casino.

However, I quickly began to prefer online gambling. The casino was inefficient, and he thought that he had too much time without gambling, and came to wonder where he was. In comparison, if you use a mobile phone, you can "100 % connection" from anywhere without asking questions. "I could do everything I could do with a casino," he says. But he added: There was no need to answer anyone.

"It was almost impossible to stop because I was able to sitting on a bed and gambling on my mobile phone."

Unlike sports betting, online casino gambling is still illegal in Illinois, and Jason was not sure if the online game he was playing was legal. "But there was no government work to pass to play these games," he said.

The growing penetration of gambling into society, legal or not, helped Jason justify his habit. He would gamble until 3am while his kids were asleep, then wake up and gamble again. Not a day went by this year that Jason didn't gamble.

"It felt like I had to gamble all the time," he says.

He ended up losing "hundreds of thousands of dollars" before admitting to his gambling addiction in May. Still, Jason considers himself a "slightly better case than average." Since joining Gamblers Anonymous, he's heard stories of people who have lost their homes and are living in their cars.

In the United States this century, gambling has been fully legalized, freed from the confines of Atlantic City and Las Vegas and into the broader culture. Gambling advertisements are scattered across the country, and casinos are now legal in more than 20 states, up from just nine in 2001. A similar number of states have legalized online sports betting, and more and more people are pushing for the legalization of online casinos.

Politicians say legalizing gambling will bring much-needed extra revenue to states, allow governments to better oversee gambling and help those who develop problems responsibly. These arguments, like those against general prohibition schemes, are difficult to refute in theory.

Do you have any insight into the online gambling industry? How has it affected your life? Let us know what you think. Contact our reporter at maxwell. strachan@vice. com or via Signal at 310-614-3752 from any device other than work.

The ubiquity of gambling and gambling-like activities has made financial catastrophe a few clicks away for anyone with a cell phone. Experts are increasingly equating the simultaneous rise of online sports betting, online casinos (legal or not), cryptocurrency trading, and day trading to the same underlying problem: gambling.

In many cases, the same person is involved. A survey data published last year by the National Gambling Additional Council (National Council On Problem Gambling) has been significantly correlated between those who trade and gamble on a weekly basis. "There is a big duplication," says Keith Whitie, the organization. Lucas Troutman, a medical department of the Oxford Treatment Center in Mississippi, who has been treating patients with gambling, Lucas Troutman, has just begun to reveal the truth of this problem, and further research has been further revealed. I say it is necessary.

"This was blown away in our nose," says Troutman.

Cindy M has certainly realized that many people like Jason have come to the rally. She is a member of Gamblaz Annimus, and is now a public relations chairman of the Group's Council. He said that the number of young men appearing at the meeting is increasing dramatically.

The impact on young people, especially young men, is remarkable for Cindy, and his sons have said, "Recently, all my friends will gamble." (After Motherboard posted this article, Cindy asked to delete her last name.)

This is also the same as the additional survey data of the National Council On Problem Gambling Council. The council was online gambling last year from 18 to 44 years old (only 21 % between the ages of 45 to 54), and more than on e-quarter of the pandemic. He has revealed that he was increasing the amount of play.

"They can access the gambling on the palms 24 hours a day. Temptation is always there.

"They can access 24 hours a day in the palms." Temptation is always there. You can leave the casino or racetrack, but you can't stop using your mobile phone.

Whitey says that Jaso n-like people are more likely to become gambling addiction and have difficulty to control the urge to bet.

"The fact that ease of access is a dangerous factor in gambling addiction has a considerable decisive basis in gambling literature," says WHYTE. "The ease of access alone does not cause gambling addiction, but it is certainly a factor that increases the proportion of gambling addiction and severity."

The accessibility is clear, and it's growing. In January, the first month mobile sports gambling was legal in New York, people bet $1. 6 billion online, a record, more than any other state. But Ashley Owen, team leader at the New York City Gambling Problem Center, which receives funding from the New York State Office of Addiction Services and Support, is struggling to convince people to take gambling problems seriously. One problem, she says, is that gambling problems are becoming harder to detect. People with gambling problems are less likely to show physical symptoms than people with drug addictions. And the rise of mobile gambling has allowed people to gamble at home without their loved ones knowing.

We call it a "hidden addiction." "With a smartphone, you have access to all kinds of gambling at your fingertips."

One middle-aged man near Chicago, who asked Motherboard not to use his name because his job gives him access to customers' personal information, was able to hide the reality of his online gambling addiction from his wife until he got a new patio.

"It was just terrifying to have everything at your fingertips."

The problem started when a Chicago man lost his job early in the pandemic and needed extra income to support his wife and three children. "I have three kids, so when I lost one job, it put a big hole in my finances. It was pretty tough. I was like, where am I going to get this money?" Then a friend introduced him to an online poker app that lets you host games. At first, he didn't do much, so he was open with his wife about his play. Occasionally, he would see a few hundred dollars in his bank account.

But the accessibility of gambling games made it hard to stop. "It was just so terrifying to have everything at your fingertips," he says. Soon, he was playing at work, and he could barely sleep, thinking about gambling. "In the morning, I was waiting for the poker guys to open the next table. Sometimes I was shaking. I kept thinking, 'I can't stop, I want to do it again,'" he said.

He was also "really really secret." I opened my current account account and made multiple credit cards. Entered a salary account and pulled out extra $ 200 every two weeks. He also made a loan to develop online addiction.

"I also made a loan to play online.

He applied for a loan to set up a new courtyard in the backyard. The man knew he would be investigated his trust. What he noticed was to give his wife a copy of his credit information. He saw it and said, "I was going crazy. I thought it was over. I thought my life and marriage were over and I thought I would lose the children."

We call this "hidden poisoning". If you have a smartphone, you can access any gambling with your fingertips. "

X
The wife accompanied him, and the man tried to install the gambling prevention app on his smartphone and stop online gambling. He joined Gamblaz Annimus and was shocked by the number of young people he met there. "I can't believe that young people in their 20s will gather." I'm very disappointed. "
A 2 1-yea r-old Nick living in California is one of such young people. When I visited a family on the east coast, my cousin introduced a legal online sports gambling. At that time, Nick was not the age of gambling, but it was easy to avoid the system set by companies. "It was not so difficult to create an account with my father's name," he says. By the third year of high school, Nick was gambling on a laptop during class. When I went to college, I moved from online sports gambling to a flea shop that could be emailed all the time, and the situation worsened.

One email. One story. Every week. Sign up for the VICE newsletter.

"Now that you can sit on a bed and gamble on your mobile phone, it is almost impossible to stop gambling." I can't let go of my phone.

More Like This

"I can't believe that young people in their 20s will gather," said one of the members of Gamblers Annimas.

Elim Poon - Journalist, Creative Writer

Last modified: 27.08.2024

This article reviews the current research about the risk and protective factors of online gambling among adults. What was done? The authors conducted a. Among adults, 8·7% (6·6–11·3) were classified as engaging in any risk gambling, and 1·41% (1·06–1·84) were engaging in problematic gambling. This paper aims to present the current state of knowledge of the risk and protective factors of online gambling. A literature search conducted in the PubMed.

Play

accepted

Online Gambling A Systematic Review of Risk and Protective Factors in the Adult Population Journal

Online Gambling: A Systematic Review of Risk and Protective Factors in the Adult Population

Similar content being viewed by others

The Prevalence and Clinical and Sociodemographic Factors of Problem Online Gambling: A Systematic Review

Emerging Gambling Problems and Suggested Interventions: A Systematic Review of Empirical Research

Preventive Interventions and Harm Reduction in Online and Electronic Gambling: A Systematic Review

Introduction

Methods

Search Strategy

Inclusion Criteria

Study Selection, Data Extraction and Analysis

Results

Search Results and Flowchart

Features of Selected Studies

Risk and Protective Individual Factors

Sociodemographic Information

Gambling Patterns and Behaviours

Risky Behaviours

Health and Wellbeing

Physical Health

Psychological distress and emotions

Personality Characteristics and Cognitive Components

Personality Characteristics

Cognitive Components

Representations, Attitudes and Motivation to Gamble

Representations and Attitudes

Motivations to Gamble

Risk and Protective Relational and Contextual Factors

Relational Factors

Contextual Factors

Discussion

Limitations of the Review

Conclusion

Data availability

References

Funding

Author information

Authors and Affiliations

The Rise of Mobile Gambling Is Leaving People Ruined and Unable to Quit

Videos by VICE

One email. One story. Every week. Sign up for the VICE newsletter.

More Like This