Examining Responsible Gambling Program Awareness and Engagement Trends and Relationships with Gambling Beliefs and Behaviors: A Three-Wave Study of Customers from a Major Gambling Operator

There are many documents that verify the evidence of a responsible gambling (RG) program in the land gambling field. This study is to investigate the recognition of the game sense RG program in MGM casino facilities in the United States using three samples of MGM Royal T e-Member members, the relationship between the awareness of the game sense RG program, the royalty trend, and the gambling. 。 One sample (n = 3748) collected just before the start of the game sense in 2017-2018, and two samples collected one year after the program (n = 4795) and two years (n = 3927). The repetition of the repetition of the revenue was used. As a result, the recognition of the game sense program rose before and after the implementation, but did not increase in two years after the implementation. As a result of the diverse analysis, the respondents with high recognition of the game sense understanded the concept of gambling and used more RG strategies. On the other hand, the respondents involved in the game sense used more RG strategies than unrelated respondents, but did not show that they could better understand the concept of gambling. The relationship between the recognition of the game sense and the use of the RG strategy by sel f-reported was also significant in multiple analysis using c o-numerals. Modelity analysis suggests only the respondents who went to local facilities, compared to respondents who went to Las Vegas and large cities facilities in Las Vegas and the respondents who went to local facilities in Las Vegas and large cities. It was suggested that all of the effects were weak, and the actual effects of this program are currently limited. This result is a suggestion of the research of the RG program rooted in the land, and provides a proposal to improve such a program.

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Avoid mistakes in the manuscript. < SPAN> There are many literature that verifies the evidence of a responsible (RG) program in land gambling fields. This study is to investigate the recognition of the game sense RG program in MGM casino facilities in the United States using three samples of MGM Royal T e-Member members, the relationship between the awareness of the game sense RG program, the royalty trend, and the gambling. 。 One sample (n = 3748) collected just before the start of the game sense in 2017-2018, and two samples collected one year after the program (n = 4795) and two years (n = 3927). The repetition of the repetition of the revenue was used. As a result, the recognition of the game sense program rose before and after the implementation, but did not increase in two years after the implementation. As a result of the diverse analysis, the respondents with high recognition of the game sense understanded the concept of gambling and used more RG strategies. On the other hand, the respondents involved in the game sense used more RG strategies than unrelated respondents, but did not show that they could better understand the concept of gambling. The relationship between the recognition of the game sense and the use of the RG strategy by sel f-reported was also significant in multiple analysis using c o-numerals. Modelity analysis suggests only the respondents who went to local facilities, compared to respondents who went to Las Vegas and large cities facilities in Las Vegas and the respondents who went to local facilities in Las Vegas and large cities. It was suggested that all of the effects were weak, and the actual effects of this program are currently limited. This result is a suggestion of the research of the RG program rooted in the land, and provides a proposal to improve such a program.

Introduction

Article January 30, 2018

Background

RG Programs and the GameSense RG Program

Paper Open Access February 05, 2024

Published on September 20, 2021~Avoid mistakes in manuscripts. There are many documents that verify the evidence of a responsible gambling (RG) program in a land gambling field. This study is to investigate the recognition of the game sense RG program in MGM casino facilities in the United States using three samples of MGM Royal T e-Member members, the relationship between the awareness of the game sense RG program, the royalty trend, and the gambling. 。 One sample (n = 3748) collected just before the start of the game sense in 2017-2018, and two samples collected one year after the program (n = 4795) and two years (n = 3927). The repetition of the repetition of the revenue was used. As a result, the recognition of the game sense program rose before and after the implementation, but did not increase in two years after the implementation. As a result of the diverse analysis, the respondents with high recognition of the game sense understanded the concept of gambling and used more RG strategies. On the other hand, the respondents involved in the game sense used more RG strategies than unrelated respondents, but did not show that they could better understand the concept of gambling. The relationship between the recognition of the game sense and the use of the RG strategy by sel f-reported was also significant in multiple analysis using c o-numerals. Modelity analysis suggests only the respondents who went to local facilities, compared to respondents who went to Las Vegas and large cities facilities in Las Vegas and the respondents who went to local facilities in Las Vegas and large cities. It was suggested that all of the effects were weak, and the actual effects of this program are currently limited. This result is a suggestion of the research of the RG program rooted in the land, and provides a proposal to improve such a program.~Article January 30, 2018

RG Programs: Examining Change Over Time

Paper Open Access February 05, 2024

The Present Study

Published on September 20, 2021

Research Questions and Hypotheses

Avoid mistakes that are common in manuscripts

1. Despite the large scope and presence of the GAMESENSE program in US casinos, the implementation was performed only on the main character of the start of this research project-one casino site (for example, Julber, et al. Louderback, Gray, et al. (2021) is the first study of the RG program effect over multiple casinos in addition to the implementation of the GameSense program in multiple casinos. The tendency or (2) a different owned type (that is, a regional casino vs. Casino vs. Casino vs. Las Vegas) is the effectiveness of the RG program. In order to fill these gaps in the literature, RG is used in the MG M-based facility 2 in this observation research. A survey of the awareness and involvement of the gambling program, the belief in gambling and the relationship between gambling behavior, one sample (n = 3, 748) collected just before the game development and one year after the program was implemented. Including (n = 4, 795) and two years later (n = 3, 927), the GAMESENSE program in the US casino is large. The implementation-the protagonist of the start of this research project-One of the casino sites (for example, Gray, Juliver, et al. LouderBack, Gray, et al. (2021), the GamesenSE program in multiple casinos This is the first study of the implementation, and (1) Tendency of the RG program effect over multiple casinos, or (2) a different owned type (that is, a regional casino vs. metropolitan casino. VS. Las Vegas (regional casino vs. Casino vs. Las Vegas, etc.) to fill these gaps in this gap. In this observation research foot note 2, the RG gambling program awareness and involvement of the RG gambling program, and the relevant to gambling behaviors and gambling behavior, using the three cros s-defined samples of MGM Royality Program members in MG M-based facilities. Investigated, one sample (n = 3, 748) collected just before the game development, one year after the program (n = 4, 795) and two years (n = 3, 927). Includes the collected two samples data. Despite the large scope and presence of the GAMESENSE program in US casinos, the implementation was performed only on the main character of the start of this research project-one casino site (for example, Julber, et al. Louderback, Gray, et al. (2021) is the first study of the RG program effect over multiple casinos in addition to the implementation of the GameSense program in multiple casinos. The tendency or (2) a different owned type (that is, a regional casino vs. Casino vs. Casino vs. Las Vegas) is the effectiveness of the RG program. In order to fill these gaps in the literature, RG is used in the MG M-based facility 2 in this observation research. A survey of the awareness and involvement of the gambling program, the belief in gambling and the relationship between gambling behavior, one sample (n = 3, 748) collected just before the game development and one year after the program was implemented. Includes (n = 4, 795) and two samples collected two years after (n = 3, 927).
   1. The RG program has been developed and implemented in accordance with the command of the RGZCZYNSKI et al. Although many RG programs are voluntary, in response to the command of the regulatory authorities (for example, Massachusetts Gaming Committee [MGC]). There is also a research review of the RG program 3 (BecketttRöm et al., 2020; Another review by Ladouceur et al. (2017) includes 29 methodology strict studies on various RG characteristics for gamblers (for example, casinos) in real world environments. They are the most studied RG characteristics of the RG characteristics, sel f-exclusion, behavioral characteristics (for example, potential gambling risks), set of gambling restrictions for spending time and amount, specific RG characteristics (eg, EGM] ) The < Span> RG program (for example, many RG programs (for example, Massachusetsu Gaming / Gaming Committee member (for example, Massachusetsu Gaming Committee member), is a gambling staff member. There is also a study of existing research on the RG program 3 (BeckettttRöm et al., 2020;, 2020; In the latest reviews by Ladouce Ut Al. 2017), for example, in other reviews in the real world (for example, regular customers in the world). They include 29 methodological research on RG characteristics, the most researched RG characteristics (for example, monitoring the potential gambling risks), the time spent. Or gambling restrictions on the amount, specific RG characteristics (eg, EGM], and gambling operators, many RG programs (Blaszczynski et al. Many RG programs are independent. RG programs are being developed and implemented in response to the regulatory authorities (for example, Massachusetts Gaming Committee [MGC]). RG Program: There is also a research review of existing research on footnote 3 (BeckettttttttttRöm et Al., 2020; LadouCeur et al., 2017). In the latest reviews, another review by Forsström et al. Ladouceur et al. (2017) is a 2 9-methodistics of various RG characteristics for gamblers (for example, casinos) in the real world environment. Includes strict research. They are the most studied RG characteristics of the RG characteristics, sel f-exclusion, behavioral characteristics (for example, potential gambling risks), set of gambling restrictions for spending time and amount, specific RG characteristics (eg, EGM] ), And observed the staff of the gambling operator.
   2. Despite the broad scope of GameSense programs and their widespread implementation in both U. S.-based gaming establishments and Canadian land-based gaming, there has been little research focus investigating customer perceptions and engagement (Gray et al., 2020; Louderback, Gray et al., 2019). In a laboratory-based experimental study, Zhou et al. (2019) found that branded animated GameSense videos increased students’ game knowledge and reduced gambling errors and intention to continue gambling. Gray et al. (2020) investigated the program’s reach among actual patrons of MA casinos and found that while program reach was low overall (approximately 1% of daily patrons spoke with a gaming advisor), patrons who spoke with a gaming advisor had positive views of gaming advisors and their presence in the casino. Finally, Louderback, Gray, et al. (2021) conducted a randomized, randomized, randomized, randomized study of 21 MGMs in the U. S. The study examined gaming programs in casinos and found that awareness of gaming was low overall (i. e., 10%), and involvement in the program (the role of receiving a gambling booklet) was even lower (2%). It also showed that patrons who received a gambling booklet were slightly more likely to report using RG strategies more while gambling.
   1. Research on RG features, such as a game sense project, is not a pr e-or pos t-analysis using more than one data, but mainly to the crossing data of a single sample. The two exceptions are experimental studies that examine these characteristics about the results of gambling knowledge and behavior. For example, Wohl et al. (2013) has seen a 3-minute educational video on gambling methods and actual winning rate, and is unlikely to have incorrect cognitive knowledge about gambling, and to restrict money while watching. I found that it is highly likely to comply. Similarly, Jonson et al. (2020) has been gambling in the tracking survey one year later, and more than one year later, gambler, who has been athletic intervention based on telephone or characte r-based. RG behavior (for example, up. These research does not directly evaluate the program of the game sense, but the former research contains a graphic element similar to a gambling pamphlet that educates the mechanism of gambling. Research contained motivation elements that are similar to what gambling counselors seek regular customers, such as gambling in a more healthy way in gambling.

   In this study, a larg e-scale survey was conducted for MGM Resorts International (MGM) M-Life Program participants, and the awareness and behavior of the RG program of the game sense, the participation, and the gambling beliefs and actions. The correlation with the six valid measurement standards was measured. These data is a unique one that MGM provided access to M Life Program participants to our research team. After the introduction of the GameSense application in the US MGM Properties (that is, "Year 1" data, "n = 3748)," YEAR 2 "data, n = 4795 and" YEAR 3 "data, n = 3927 ) Analyzing the three duplicate datrosets collected in and evaluated the following pr e-registered research quests (https: // Osf. IO/mn7HQ):

   1. Regarding H1 and H2, the gaming program has been developed for a long time, and the number of chances to touch the program will increase the recognition and engagement over time.
   2. 1. What is the recognition of the game sense for 3 years?
   1. 1. H1. 1: The recognition of the game sense increases from the first year to the second year.
   2. 2. H1. 2: The recognition of the game sense increases from the second year to the third year.
   1. 1. H2: The royalty of the game sense increases from the second year to the third year.

   Methods

   Regarding H3 and H4, more employees receive game sense training, expand the range of RG tools, and their program mature, giving recognition / commitment of game sense and positive beliefs and actions for gambling. I made a hypothesis that a positive correlation would occur. Game sense and the knowledge of the program components are more healthy gambling beliefs and actions (for example, the probability and gambling mechanism, the scores of positive gambling scale increases) and participation in gambling. It should be related to restrictions. Also, gambling behavior with potentially risky recognition and commitment of game sense (that is, laplante et al.)

   Data Collection

   1. h3. 1: The recognition of the game sense is that three years after the program implementation, a more healthy gambling belief and behavior (that is, the active gambling: behavioral, gambling: gambling literacy scale, gambling concept It shows the understanding and positive relationship with the understanding of the responsible gambling strategy.

   2. H3. 2: The recognition of the game sense shows the frequency (= depth) three years after the program, and the number (= range) of various gambling games played.

   H4. 1: The involvement of the game sense is a belief and behavior of gambling three years after the program implementation (that is, the active gameplay scale: behavior, aggressive gameplay scale: understanding, responsibility, gambling concept, and responsibility. It shows a positive correlation with the measured value of a certain gambling strategy.~2. H4. 2: The royalty of the game sense indicates a negative correlation between the frequency (= depth) of the gambling and the number (= range) of various gambling games played three years after the program implementation.~1. Since this research topic is explorable, no hypothesis is set. < Span> 1. H1. 1: The recognition of the game sense increases from the first year to the second year.

   2. H1. 2: The recognition of the game sense increases from the second year to the third year.~1. H2: The royalty of the game sense increases from the second year to the third year.~Regarding H3 and H4, more employees receive game sense training, expand the range of RG tools, and their program mature, giving recognition / commitment of game sense and positive beliefs and actions for gambling. I made a hypothesis that a positive correlation would occur. Game sense and the knowledge of the program components are more healthy gambling beliefs and actions (for example, the probability and gambling mechanism, the scores of positive gambling scale increases) and participation in gambling. It should be related to restrictions. Also, gambling behavior with potentially risky recognition and commitment of game sense (that is, laplante et al.)

   Participants

   1. h3. 1: The recognition of the game sense is that three years after the program implementation, a more healthy gambling belief and behavior (that is, the active gambling: behavioral, gambling: gambling literacy scale, gambling concept It shows the understanding and positive relationship with the understanding of the responsible gambling strategy.~2. H3. 2: The recognition of the game sense shows the frequency (= depth) three years after the program, and the number (= range) of various gambling games played.

   Measures

   H4. 1: The involvement of the game sense is a belief and behavior of gambling three years after the program implementation (that is, the active gameplay scale: behavior, aggressive gameplay scale: understanding, responsibility, gambling concept, and responsibility. It shows a positive correlation with the measured value of a certain gambling strategy.

   GameSense Awareness/Engagement

   2. H4. 2: The royalty of the game sense indicates a negative correlation between the frequency (= depth) of the gambling and the number (= range) of various gambling games played three years after the program implementation.

   GameSense Component Awareness

   1. Since this research topic is explorable, no hypothesis is set. 1. H1. 1: The recognition of the game sense increases from the first year to the second year.

   Overall Summed GameSense Engagement

   2. H1. 2: The recognition of the game sense increases from the second year to the third year.

   Gambling Beliefs/Behaviors

   1. H2: The royalty of the game sense increases from the second year to the third year.

   Positive Play Scale: Behavior (7 items)

   Regarding H3 and H4, more employees receive game sense training, expand the range of RG tools, and their program mature, giving recognition / commitment of game sense and positive beliefs and actions for gambling. I made a hypothesis that a positive correlation would occur. Game sense and the knowledge of the program components are more healthy gambling beliefs and actions (for example, the probability and gambling mechanism, the scores of positive gambling scale increases) and participation in gambling. It should be related to restrictions. Also, gambling behavior with potentially risky recognition and commitment of game sense (that is, laplante et al.)

   Positive Play Scale: Gambling Literacy (3 items)

   1. h3. 1: The recognition of the game sense is that three years after the program implementation, a more healthy gambling belief and behavior (that is, the active gambling: behavioral, gambling: gambling literacy scale, gambling concept It shows the understanding and positive relationship with the understanding of the responsible gambling strategy.

   Use of RG Strategies (6 Items)

   2. H3. 2: The recognition of the game sense shows the frequency (= depth) three years after the program, and the number (= range) of various gambling games played.

   Understanding of Gambling Concepts (7 Items)

   H4. 1: The involvement of the game sense is a belief and behavior of gambling three years after the program implementation (that is, the active gameplay scale: behavior, aggressive gameplay scale: understanding, responsibility, gambling concept, and responsibility. It shows a positive correlation with the measured value of a certain gambling strategy.

   Frequency of Gambling in the Past Year (1 Item)

   2. H4. 2: The royalty of the game sense indicates a negative correlation between the frequency (= depth) of the gambling and the number (= range) of various gambling games played three years after the program implementation.

   Number of Different Gambling Games Played (1 Item)

   1. Since this research topic is explorable, no hypothesis is set.

   MGM Properties Attended

   After data collection and prior to data analysis, we pre-posted our study protocol and analysis plan to the Open Science Framework ([OSF], https://osf. io/mn7hq). We analyzed data collected in January, February, and March 2020 (i. e., Year 3), February and March 2019 (i. e., Year 2), and Fall 2017 (i. e., Year 1) from a survey of customers participating in MGM’s loyalty program in the United States.

   Property Type Attended

   This study is part of a longitudinal, multi-pronged analysis of the GameSense program and its implementation in the United States (see below). The OSF Year 2 project folder is here: https://osf. io/pu6hc/ and the OSF Year 3 project folder is here: https://osf. io/c5ef6/). The pre-recorded documents and project folders linked above provide more detailed information about the methodology and data collection across the three waves, much of which is also included in this section.

   Control Variables

   For the second year, MGM’s direct marketing team emailed participants in the fall of 2017, prior to the rollout of GameSense at MGM properties, inviting them to complete the survey. At some MGM properties, the team called the entire participant database. At other properties, the team created a demographically representative participant pool and randomly selected potential respondents from that group for this study. The direct marketing team sent the emails through the Qualtrics survey platform on behalf of the University of Nevada, Las Vegas research team “working with MGM to evaluate their RG program, GameSense.” No compensation was charged for participating in the survey. The University of Nevada, Las Vegas Institutional Review Board approved the study protocol.

   Analytic Strategy

   Data collection for the second year (i. e., Year 2) was conducted in February-March 2019,

   16 months after the launch of GameSense’s RG program at MGM Properties in Springfield, MA, and

   6 months after the opening of the MGM Springfield, MA property in August 2018. MGM's direct marketing department emailed surveys to Life for Me subscribers.

   Data collection for the third year (i. e., year 3) was conducted in January, February, and March 2020,

   28 months after the game's development at MGM Properties, Springfield and

   18 months after the Springfield facility/games began operation there, MGM's direct marketing team emailed potential respondents to invite them to participate in the survey.

   Covariates and Significance Criteria

   MGM's direct marketing team emailed 73. 799 respondents in year 1, 105, 814 in year 2, and 130, 000 in year 3. Respondents were informed that the survey would take 10-15 minutes to complete and that they were eligible to participate because they were M. Life members. Respondents were sent a reminder email.< 0.05 as criteria for statistically significant results. All reported p -values were based on two-tailed tests of significance.

   Results

   Planned Descriptive Analyses

   One week after the initial survey invitation for each year. Sample sizes and response rates were 3748/5, 1% in year 1, 4795/4, 5% in year 2, and 4336/3, 4% in year 3. In year 3, we excluded respondents who visited MGM Northfield Park Casino and/or MGM Empire City Casino and/or MGM Corporate Properties (footnote 5), resulting in a year 3 analytic sample of 3927. By examining IP addresses (footnote 6), we compared overlap between survey respondents from each year, and found that most respondents did not appear in more than one sample. Therefore, we treated each year's sample as an independent sample. Because this is an observational study, randomization was not performed, and results should be understood in the context of the study design.

   All variables are summarized below. For more details, please see the documents "Year 1 Customer Survey," "Year 2 Customer Survey," and "Year 3 Customer Survey" in the linked OSF project folder.

   Confirmatory Analyses

   For all survey items, respondents who selected "prefer not to answer" or "prefer not to say" were recorded as missing for that question.

   Respondents were asked: "Are you familiar with GameSense?" (We asked whether they were aware of the specific components of the GameSense program: (1) the Gaming Helpline, (2) gaming promotional materials, (3) gaming advisors, and (4) brochures). Footnote 7 Respondents who reported being aware of GameSense advisors or brochures were asked whether they had ever engaged with them (i. e., "Have you spoken to a GameSense advisor?", "Have you spoken to a GameSense consultant at MGM Properties?", and "Have you picked up a brochure about responsible gaming?"). All "yes" were scored as "1" and all "no" were scored as "0". If a respondent indicated they were unfamiliar with GameSense in general, they were scored as "0" for all four items.

   To measure awareness of game elements, responses to the four game element awareness measures were summed. The resulting scale ranged from 0 to 4, with higher values ​​indicating awareness of more game elements.

   To measure awareness of game elements, responses to two scales of engagement in game elements were summed. The resulting scale ranged from 0 to 2, with higher values ​​indicating engagement in more game element awareness.

   To measure gambling beliefs and behaviors, six variables were measured, including (1) Active Gambling Scale: Behavior, (2) Active Gambling Scale: Gambling Literacy, (3) Use of RG Strategies, (4) Understanding of Gambling Concepts, (5) Frequency of Gambling in the Past Year, and (6) Number of Different Gambling Games.

   Positive Play Scale (PPS): Behavior was measured as a mean scale of seven Likert-type questions that utilized the concept of RG behavior based on Wood et al.'s (2017) validated scale. Responses ranged from 1 (never) to 7 (always). The questions included different RG behaviors such as “I thought about the amount of money I was willing to lose before gambling” and “I thought about the amount of time I was willing to spend before gambling.” Alpha was 0. 86 in Year 1, 0. 85 in Year 2, and 0. 81 in Year 3.

   We adapted this subscale from the original PPS created by Wood et al. (2017). Each respondent answered three questions about their beliefs about gambling education, with responses ranging from 1 (never) to 7 (always). The questions included different RG beliefs such as “If I gamble more often, I will win more than I lose” (reverse coded), and “Gambling is not a good way to make money.” We averaged these three items to create a scale. Alpha was 0. 51 in Year 1, 0. 49 in Year 2, and 0. 52 in Year 3.

   We asked the following questions: "Some people use strategies to keep gambling in a reasonable range. If you have used it in the past year, what is the strategy? "?" The respondents said "Yes, yes, I did not use more than planned", "I left a casino while I was advantageous", "I took a break to cool my head"). "I did so." Or "No, I didn't do that." In order to measure the usage of RG strategy, "yes" is "1" and "no" is "0", and each respondent has the total answer to the six questions (possible range = 0 to 6, scoring. The higher the use of the RG strategy, the higher the use of the RG strategy). The respondents who chose "none of the above" were "0" in this indicator.

   We measured the understanding of gambling concepts by combining the correct answer to the seven unknown questions that affect the gambling mechanism, such as the illusion of control and the independence of random events. The correct answer is "1" and the incorrect answer is "0", and the respondents answer the seven questions (the possible range is 0 to 7, and the higher the score, the higher the understanding of the concept of gambling. Is shown).

   The question of the gambling frequency in the past year has measured the depth of participation in gambling. As for the answer category, "I have never gambling" is "1" and "do every day" is "6".

   The range of participation in the gambling was measured by questioning the kind of gambling played by the respondents. The respondents were asked to select all the following questions: "Poker, table game (eg, blackjack, roulette, claps), bingo, slot games, sportsbetting, lacebetting, lottery, and other lotteries. Game: ______ "There is an answer option. In order to create indicators indicating the range of participation in gambling, the number of approved games was combined in the range of 0 to 7. In order to include gambling games with common forms between facilities, and to limit the maximum value of this variable to 7, this scale does not include the answer option "Other games: _____". 。 The respondents who chose no game were codeed to "0" to this indicator.

   Respondents were asked to indicate which MGM properties they had visited in the past 12 months using a multiple-choice drop-down menu. In the Year 2 and Year 3 surveys, respondents who selected “MGM Springfield” were asked to complete the survey with this property in mind.

   Based on the MGM properties attended variable and the Year 3 survey responses, we created three new variables to identify the type of property each participant had attended. We created a variable that equaled “1” if the respondent had attended one or more regional casinos (i. e., Beau Rivage, MGM Springfield, Footnote 8 Northfield Park, Gold Strike, or Grand Victoria) and “0” if they had attended only other MGM properties. We then created a variable that equaled “1” if the respondent had attended a metropolitan casino (i. e., MGM Springfield, Footnote 8 Northfield Park, Gold Strike, or Grand Victoria). MGM National Harbor, Borgata, Empire City Casino, MGM Grand Detroit), and a "0" if they attended only other MGM casinos. Finally, we scored a "1" if the respondent attended one or more MGM properties in Las Vegas (Bellagio, New York New York, Aria, Luxor, Vdara Hotel & Spa, Excalibur, MGM Grand Las Vegas, Circus Circus, MGM Grand Signature, Mirage, Monte Carlo, Park MGM [including T-Mobile Arena], Mandalay Bay, Delano Las Vegas), and a "0" if they attended only MGM properties outside Las Vegas.

   We measured five control variables: (1) age, (2) sex, (3) race/ethnicity, (4) education, and (5) total number of MGM properties visited in the past 12 months. We included controls for demographic variables because gambling behavior has been found to vary across demographic groups (Gainsbury et al., 2012; Potenza et al., 2006). We controlled for the total number of MGM venues visited in the past 12 months because research has shown that exposure to different gambling opportunities can influence gambling behavior (St-Pierre et al.

   All analysis was performed using version 3. 6. 2. First, the statistics of all continuous variables such as the average, median, standard deviation, range, etc. were calculated. Next, the two variables of variables included in the mult i-amount model were calculated. For multiple regression models, we analyzed outcom variables using the normal regression (OLS) approach, and checked the necessary statistical assumptions and conditions (that is, there is no excessive compatibility). The absence of excessive multiplexuality, the absence of an influential deviation, the regular nature of the connection and the error, a. Continuous result variable without extreme distortion). The multiplexuality of each model was tested using a distributed infraser (VIF), but there was no VIF that exceeded the standard & amp; gt; 4 described in HAR et al. (2010).

   In order to verify how the level of game awareness has changed over time, five 2x3 kai tw o-square tests were used. Next, a pair of comparison was examined to compare the ratio of each year (that is, Y1 vs. Y2, Y2 vs Y3), and a HOLM approach was used to correct multiple comparisons.

   Planned Exploratory Analyses

   After the program was implemented, a 2x2 kai tw o-square test was used to examine how the participation level in the game changed over time. Next, a pair of comparison was performed using HOLM correction, and the ratio of Y2 vs. Y3 was compared. < SPAN> All analysis was performed using version 3. 6. 2. First, the statistics of all continuous variables such as the average, median, standard deviation, range, etc. were calculated. Next, the two variables of variables included in the mult i-amount model were calculated. For multiple regression models, we analyzed outcom variables using the normal regression (OLS) approach, and checked the necessary statistical assumptions and conditions (that is, there is no excessive compatibility). The absence of excessive multiplexuality, the absence of an influential deviation, the regular nature of the connection and the error, a. Continuous result variable without extreme distortion). The multiplexuality of each model was tested using a distributed infraser (VIF), but there was no VIF that exceeded the standard & amp; gt; 4 described in HAR et al. (2010).

   In order to verify how the level of game awareness has changed over time, five 2x3 kai tw o-square tests were used. Next, a pair of comparison was examined to compare the ratio of each year (that is, Y1 vs. Y2, Y2 vs Y3), and a HOLM approach was used to correct multiple comparisons.

   After the program was implemented, a 2x2 kai tw o-square test was used to examine how the participation level in the game changed over time. Next, a pair of comparison was performed using HOLM correction, and the ratio of Y2 vs. Y3 was compared. All analysis was performed using version 3. 6. 2. First, the statistics of all continuous variables such as the average, median, standard deviation, range, etc. were calculated. Next, the two variables of variables included in the mult i-amount model were calculated. For multiple regression models, we analyzed outcom variables using the normal regression (OLS) approach, and checked the necessary statistical assumptions and conditions (that is, there is no excessive compatibility). The absence of excessive multiplexuality, the absence of an influential deviation, the regular nature of the connection and the error, a. Continuous result variable without extreme distortion). The multiplexuality of each model was tested using a distributed infraser (VIF), but there was no VIF that exceeded the standard & amp; gt; 4 described in HAR et al. (2010).

   Unplanned Exploratory Analyses

   In order to verify how the level of game awareness has changed over time, five 2x3 kai tw o-square tests were used. Next, a pair of comparison was examined to compare the ratio of each year (that is, Y1 vs. Y2, Y2 vs Y3), and a HOLM approach was used to correct multiple comparisons.

   Discussion

   After the program was implemented, a 2x2 kai tw o-square test was used to examine how the participation level in the game changed over time. Next, a pair of comparison was performed using HOLM correction, and the ratio of Y2 vs. Y3 was compared.

   Using customer survey data for the year, verify how gambling consciousness is related to gambling creed and action measured values ​​for three years after gambling (H3. 1 and H3 2). Elements and (1) PPS: action, (2) PPS: Gambling literacy, (3) Use of RG strategy, (5) Gambling frequency in the past year, (6) various things played Number of gambling games. Next, in order to determine whether each relationship is stubborn to add metaphors, 12 separate linear regression models were applied. The first six models included general gambling awareness as predictors. The controlled variables are the total number of ages, gender, races, ethnic groups, educational background, and the total number of MGM facilities that have been visited in the last 12 months. The six scale of beliefs and actions for gambling were used as results variables. Model 7 to 12 contains the same control variables and result variables, but includes gambling items as predictive variables.

   First of all, to verify how the engagement of the game sense is related to the indicators of gambling three years after the game development, using customer survey data for the third year is used. (1) Examination of the doubl e-change correlation between (1) Action: (2) PPS: Gambling literacy, (3) Use of RG strategy, (5) Gambling frequency in the past year (6) Number of gambling games. Next, six separate regression models were applied to determine whether each relationship was stubborn to add metaphors. These six models include the total commitment to gambling as a predictive variable, as a control variable, age, gender, ethnic group, total number of MGM facilities visited in the last 12 months, and gambling as a result variable. It contained six scale of beliefs and actions. Use < SPAN> Use the customer survey data of the year to verify how gambling consciousness is related to gambling beliefs and behavior measured (H3. 1 and H3. 2). Components of consciousness and (1) PPS: behavior, (2) PPS: Gambling literacy, (3) Use of RG strategy, (5) Gambling frequency in the past year, (6) play The number of gambling games that did. Next, in order to determine whether each relationship is stubborn to add metaphors, 12 separate linear regression models were applied. The first six models included general gambling awareness as predictors. The controlled variables are the total number of ages, gender, races, ethnic groups, educational background, and the total number of MGM facilities that have been visited in the last 12 months. The six scale of beliefs and actions for gambling were used as results variables. Model 7 to 12 contains the same control variables and result variables, but includes gambling items as predictive variables.

   First of all, to verify how the engagement of the game sense is related to the indicators of gambling three years after the game development, using customer survey data for the third year is used. (1) Examination of the doubl e-change correlation between (1) Action: (2) PPS: Gambling literacy, (3) Use of RG strategy, (5) Gambling frequency in the past year (6) Number of gambling games. Next, six separate regression models were applied to determine whether each relationship was stubborn to add metaphors. These six models include the total commitment to gambling as a predictive variable, as a control variable, age, gender, ethnic group, total number of MGM facilities visited in the last 12 months, and gambling as a result variable. It contained six scale of beliefs and actions. Using customer survey data for the year, verify how gambling consciousness is related to gambling creed and action measured values ​​for three years after gambling (H3. 1 and H3 2). Elements and (1) PPS: action, (2) PPS: Gambling literacy, (3) Use of RG strategy, (5) Gambling frequency in the past year, (6) various things played Number of gambling games. Next, in order to determine whether each relationship is stubborn to add metaphors, 12 separate linear regression models were applied. The first six models included general gambling awareness as predictors. The controlled variables are the total number of ages, gender, races, ethnic groups, educational background, and the total number of MGM facilities that have been visited in the last 12 months. The six scale of beliefs and actions for gambling were used as results variables. Model 7 to 12 contains the same control variables and result variables, but includes gambling items as predictive variables.

   Practical Implications

   First of all, to verify how the engagement of the game sense is related to the indicators of gambling three years after the game development, using customer survey data for the third year is used. (1) Examination of the doubl e-change correlation between (1) Action: (2) PPS: Gambling literacy, (3) Use of RG strategy, (5) Gambling frequency in the past year (6) Number of gambling games. Next, six separate regression models were applied to determine whether each relationship was stubborn to add metaphors. These six models include the total commitment to gambling as a predictive variable, as a control variable, age, gender, ethnic group, total number of MGM facilities visited in the last 12 months, and gambling as a result variable. It contained six scale of beliefs and actions.

   Finally, in order to verify whether the relationship between the game sense, royalties, and gambling religion / behavior varies depending on the own form, a mult i-year search analysis was performed using customer survey data for the third year. First, the same six multiple regression models as the previous RQ4 were added to the dummy variables of the local property, the overall game sense royalties and the local property dummy variable. Second, the same six mult i-modified regression models described above are the same as the dummy variables of the metropolitan casino, the comprehensive gamesense royalty and the metropolitan casino dummy variable. I let it do. Third, the same six mult i-amount regression models as the RQ4 above were calculated by adding the alternation of the dummy variables of Las Vegas Casino, the comprehensive royalty of Gamesense and the dummy variable of the Las Vegas casino. The total number of regression models was 18. We have not evaluated the confirmation hypothesis, and we do not make a multiple comparison correction in this kind of exploring research on multiple comparison (for example, Bonferroni). (Vender & Amp; amp; Lange, 2001).

   Theoretical Implications

   As a c o-changing amount in the mult i-amount model, (1) the normal scale of the age, (2) and (3) the category of racial / ethnic group, (4) the normal scale of the educational background, (5) in the past 12 months. The five scale of the MGM casinos that I visited were used, the integer scale of the integer. Details of coding of these variables are described in the pr e-print of this research. Finally, we explore a large amount of quantity using customer survey data in the third year to verify whether the relationship between the game sense, royalties, and gambling religion / behavior varies depending on the own form. Analysis was performed. First, the same six multiple regression models as the previous RQ4 were added to the dummy variables of the local property, the overall game sense royalties and the local property dummy variable. Second, the same six mult i-modified regression models described above are the same as the dummy variables of the metropolitan casino, the comprehensive gamesense royalty and the metropolitan casino dummy variable. I let it do. Third, the same six mult i-amount regression models as the RQ4 above were calculated by adding the alternation of the dummy variables of Las Vegas Casino, the comprehensive royalty of Gamesense and the dummy variable of the Las Vegas casino. The total number of regression models was 18. We have not evaluated the confirmation hypothesis, and we do not make a multiple comparison correction in this kind of exploring research on multiple comparison (for example, Bonferroni). (Vender & Amp; amp; Lange, 2001).~As a c o-changing amount in the mult i-amount model, (1) the normal scale of the age, (2) and (3) the category of racial / ethnic group, (4) the normal scale of the educational background, (5) in the past 12 months. The five scale of the MGM casinos that I visited were used, the integer scale of the integer. Details of coding of these variables are described in the pr e-print of this research. Finally, we perform a mult i-amount search analysis using the third year of customer survey data to verify whether the relationship between the game sense, royalties, and gambling religion / behavior varies depending on the own form. Ta. First, the same six multiple regression models as the previous RQ4 were added to the dummy variables of the local property, the overall game sense royalties and the local property dummy variable. Second, the same six mult i-modified regression models mentioned above are compatible with the interaction between the dummy variables of the metropolitan casino and the dummy variables of the metropolitan casino in GamesEnse. I let it do. Third, the same six mult i-amount regression models as the RQ4 above were calculated by adding the alternation of the dummy variables of Las Vegas Casino, the comprehensive royalty of Gamesense and the dummy variable of the Las Vegas casino. The total number of regression models was 18. We have not evaluated the confirmation hypothesis, and we do not make a multiple comparison correction in this kind of exploring research on multiple comparison (for example, Bonferroni). (Vender & Amp; amp; Lange, 2001).

   As a c o-changing amount in the mult i-amount model, (1) the normal scale of the age, (2) and (3) the category of racial / ethnic group, (4) the normal scale of the educational background, (5) in the past 12 months. The five scale of the MGM casinos that I visited were used, the integer scale of the integer. Details of coding of these variables are described in the pr e-print of this research. We are P

   Conclusion

   Table 1 presents descriptive statistics. Five features of this table are significant. First, about one in ten (11, 3%) third-year respondents were aware of the GameSense program. Second, the mean awareness of GameSense elements (M = 0, 24, SD = 0, 81) and overall involvement in GameSense were both low (M = 0, 02, SD = 0, 16), ranging from 0 to 4 and 0 to 2, respectively. Third, respondents' understanding of gambling concepts was generally high (M = 5, 48, SD = 1, 43), with high scores on a 1 to 7 scale on both the PPS for behavior (M = 6, 20, SD = 1, 02) and the PPS for gambling literacy (M = 6, 12, SD = 1, 08). Fourth, most respondents tended to play monthly or less than monthly (73, 55%), and respondents played only a limited variety of games, with the average being a mix of two types of games (M = 1, 97, SD = 1, 11). Fifth, the Year 3 sample was predominantly White/Caucasian (55, 60%), with significant percentages of Black/African American (5, 96%), Hispanic (4, 24%), and Asian (3, 06%) respondents.

   Study Limitations

   Table 1 Year 3 Descriptive Statistics (n = 3. 927)

   Directions for Future Research

   Table 2 shows the percentage of respondents who reported knowing about games in general, knowing about specific components of games, and participating in GameSense for each of the three waves. Comparing Years 1 and 2, there was a significant increase from pre- to post-implementation for the game awareness variable.

   Table 2 Frequency across all three years of data collection (Y1: 2017, Y2: 2019, Y3: 2020)

   H3. 1: Gambling awareness is positively associated with healthier gambling beliefs and behaviors (i. e., measures of gambling beliefs and behaviors) three years after program implementation (Positive Gambling Scale: Behavior, Positive Gambling Scale: Gambling Literacy, Understanding Gambling Concepts, Use of Responsible Gambling Strategies).

   Concluding Thoughts

   Table 3 shows the Spearman rank correlation analysis of all variables in the third year. General gambling awareness was significantly but weakly positively correlated with the use of RG strategies (p = 0, 07) (p = - 0, 04) and was not related to the PPS subscale: behavior (p = 0, 00) and understanding of gambling concepts (p = 0, 03). A similar pattern emerged when considering the sum of gambling components known by the respondents, but this scale was also significantly but weakly correlated with understanding of gambling concepts (p = 0, 04) and was not significantly correlated with the PPS: gambling literacy subscale (p = - 0, 02).

   Availability of Data and Materials

   Table 3 Double correlations

   Notes

   We examined the relationships between variables other than gambling awareness. The PPS: behavior subscale was negatively correlated with gambling frequency (p = - 0, 17) and positively correlated with understanding of gambling concepts (p = 0, 15). Educational background was positively correlated with understanding of gambling concepts (p = 0, 06) and use of RG strategies (p = 0, 04), but the relationship was weak.

   H3. 2: Gambling awareness will be negatively correlated with gambling frequency (= depth) and number of different gambling games played (= breadth) three years after program implementation.

   In contrast to H3. 2, overall gaming awareness was positively correlated with gambling frequency (p=0, 06) and weakly correlated with the sum of gaming components perceived by the respondent (p=0, 05), but both measures were unrelated to the number of games played.

   Regarding the multivariate analysis with covariates, Table 4 shows the results of OLS regression models in the third year with predictor variables including general gaming awareness and control variables, and outcome variables including PPS behaviors: behavior (Model 1), PPS:2), understanding of gambling concepts (Model 3), use of RG strategies (Model 4), gambling frequency (Model 5), and amplitude participation (Model 6). The first four models further verify H3. 1, and the last two models further verify H3. 2. Table 4 also displays models of awareness of gambling items and control variables with the same six outcome variables (Models 7-12).

   Table 4 OLS regression models of general game awareness, game component awareness, and game beliefs/behaviors

   Model 4 shows that the positive relationship between general game awareness and RG strategy use was significant even after controlling for metaphorical components (B = 0, 204, SE = 0, 077). Furthermore, model 10 shows that awareness of game components was positively related to RG strategy use even after adding control variables (B = 0, 097, SE = 0, 029). However, the effect sizes were small in both models. Respondents who generally perceived game sense or who perceived additional game components used fewer RG strategies on average. Thus, H3. 1 regarding general awareness, game awareness, and RG strategy use was empirically supported in the multivariate model. H3. 2 was not supported.

   H4. 1: Gambling involvement will be positively associated with measures of gambling beliefs and behaviors (i. e., measures of gambling beliefs and behaviors (Positive Gambling Scale: Behavior, Positive Gambling Scale: Gambling Literacy, Understanding of Gambling Concepts, Use of Responsible Gambling Strategies)

   H4. 2: GameSense engagement will be negatively associated with gambling frequency (i. e., depth) and number of different gambling games played (i. e., amplitude) 3 years after program implementation.

   References

   • In bivariate analyses, overall gambling involvement was significantly and positively associated with RG strategy use (p = 0, 05), but not significantly associated with other aspects of gambling beliefs/behaviors or with gambling frequency or number of games played in bivariate analyses. Both of these results provide partial empirical support for H4. 1 and no support for H4. 2.
   • Multivariate Tests Regarding H4. 1, Table 5 shows the results of the OLS regression models with predictor variables including total gambling involvement and control variables, and outcome variables including PPS: behavior (Model 1), PPS: gambling literacy (Model 2), understanding of gambling concepts (Model 3), use of RG strategies (Model 4), gambling frequency (Model 5), and participation amplitude (Model 6). These results revealed that the significant relationship between overall gambling involvement and use of RG strategies obtained in the bivariate analysis was not observed after controlling for covariates. Therefore, H4. 1 and H4. 2 were not supported in the multivariate analysis.
   • Table 5 OLS Regression Models of Total Problem Gambling and Gambling Beliefs/Behaviors
   • Are there differences between gambling commitment and gambling beliefs and behaviors by type of establishment (regional casino vs. big city casino vs. Las Vegas)? Regional casino vs. big city casino vs. Las Vegas). Full results of these models are reported in the online supplement of this paper (see Supplementary Tables 1-3 in the online supplement). Across all 18 regression models with total gambling commitment, control variables, and interaction terms between total gambling commitment and each of the three property grouping variables (i. e., six models for each of the three groupings), the only model with a significant interaction term was for respondents who attended a regional property and the PPS outcome variable gambling literacy. Specifically, these neutralized results (see Figure 1) indicate that respondents who attended a regional property showed a significant and positive association between their overall gambling involvement and the PPS: Reinforcing the Benefits of the Same PPS subscale.
   • Figure 1
   • Interactions of total game sense commitment and variables of neighboring intellectual properties visited on the game sense scale:
   • We also conducted a series of additional unplanned exploratory analyses in response to reviewer requests (see Supplementary Tables 4-6 in the online supplement). These analyses used the same approach as the planned exploratory analyses with interaction terms described immediately above, but included game item awareness as the primary predictor and included the three interaction terms in three sets of six models. In all 18 models, none of the interaction terms between constructs and ownership type were statistically significant, suggesting that there are differences in the associations between game awareness and gambling beliefs or gambling behaviors by ownership type.
   • The RG game sense program awareness of the RG Game Sense Program is recognized by using three repetitive crossing data for subscribers of the MGM MGM royalty program collected between 2017 and 2020. ) It increased between) and the introduction (that is, the second year), but did not rise in two years (that is, the third year) after the introduction, and after the introduction (= 2nd year). However, it did not increase in two years (= third year) after the introduction. The engagement level to the program was generally low in both the follo w-up period after the introduction and the follo w-up period after the introduction and the introduction, and did not increase during this period.
   • (Ii) In the modified analysis, evidence has been found that respondents who know the program or participate in the program report that they are using more RG strategies, but these relationships are weak and mult i-quantic coordinates. In the model, only the relationship between the recognition of the game and the use of the RG strategy remained significant. In a multiple analysis, it is shown that the recognition and involvement of the program also have a positive correlation with gambling frequency, and maybe the risk of gambling problems may be high (Binde et al., 2017; Laplainte et al. . As with the previous relationship, these relationships were weak. < SPAN> The recognition of the RG game sense program is used (that is, the recognition of the RG Game Sense Program using three repetitive crossing data for subscribers of the MGM MGM royalty program collected between 2017 and 2020. It rose between the first year and the introduction (that is, the second year), but did not rise in two years (that is, the third year) after the introduction, and after the introduction (= 2nd year). Although it increased, it did not increase in two years (= third year) after the introduction. The engagement level to the program was generally low in both the follo w-up period after the introduction and the follo w-up period after the introduction and the introduction, and did not increase during this period.
   • (Ii) In the modified analysis, evidence has been found that respondents who know the program or participate in the program report that they are using more RG strategies, but these relationships are weak and mult i-quantic coordinates. In the model, only the relationship between the recognition of the game and the use of the RG strategy remained significant. In a multiple analysis, it is shown that the recognition and involvement of the program also have a positive correlation with gambling frequency, and maybe the risk of gambling problems may be high (Binde et al., 2017; Laplainte et al. . As with the previous relationship, these relationships were weak. The RG game sense program awareness of the RG Game Sense Program is recognized by using three repetitive crossing data for subscribers of the MGM MGM royalty program collected between 2017 and 2020. ) It increased between) and the introduction (that is, the second year), but did not rise in two years (that is, the third year) after the introduction, and after the introduction (= 2nd year). However, it did not increase in two years (= third year) after the introduction. The engagement level to the program was generally low in both the follo w-up period after the introduction and the follo w-up period after the introduction and the introduction, and did not increase during this period.
   • (Ii) In the modified analysis, evidence has been found that respondents who know the program or participate in the program report that they are using more RG strategies, but these relationships are weak and mult i-quantic coordinates. In the model, only the relationship between the recognition of the game and the use of the RG strategy remained significant. In multiple variable analysis, it is also shown that the recognition and involvement of the program have a positive correlation with gambling frequency, and perhaps the risk of gambling problems (Binde et al., 2017; Laplainte et al. , 2014), the higher the involvement, the more likely it is to recognize the elements of the game sense program and be involved. As with the previous relationship, these relationships were weak.
   • Such establishments tend to be smaller replicant market establishments with fewer entertainment options and a more local customer base who may gamble more frequently (Lucas & Kilby, 2008). Therefore, such establishments may be less distracted by other activities, which may increase the opportunities for patrons to become aware of and participate in the Gamesense program, which in turn may help promote healthy gambling beliefs. There may also be certain local casino characteristics that increase awareness and participation in the program, such as Louderback, Gray, et al. (2021) finding that awareness and participation in the Gamesense program at MGM Springfield was significantly higher than at other MGM properties. Such differences were partially explained by the fact that MGM Springfield uses a model of a state-regulated Gamesense program, with highly visible branding at designated Gamesense RG Information Centers and gaming consultants walking the casino floor and casino floor in conspicuous green shirts. Therefore, it is likely that the program has significantly higher awareness and participation than other MGM properties. An important caveat to these findings is the fact that less than 1% of all establishments reported having met a GameSense advisor and less than 3% reported receiving a GameSense brochure. This means that participation in the program was low even in the third year. Similarly, the observed effect sizes were generally very small. Thus, although many statistically significant differences were observed in our planned analyses, the practical significance of the results was limited. This suggests that the GameSense program implemented in MGM casinos in the United States likely requires significant modification in order to have a positive impact on player behavior.
   • Programs designed to encourage RG's beliefs and actions should be regularly evaluated to confirm that they are effective in achieving their goals. Otherwise, there is a risk that resources will head in the wrong direction or that the accountability is being fulfilled. In this study, individual players are passively contacted with RG messages (for example, EGM's help line number), dialogue with RG materials or request support resources (for example, pamphlets. It suggests that land RG programs that depend on (picking up, etc.) may have a limit, but this survey shows the games program (border settings and money management skills). It should not be interpreted as suggesting that the impact on individuals who may need an educational pamphlet or the person who is directly painful for gambling is limited. Although data on specific exchange cases is not collected, a qualitative study on the game sense program (Abarbanel et al., 2018) has established a relationship with people who gamble frequently gambling. It is shown that a certain gambling can intervene. Therefore, it is important to recognize both quality (= content and results) and quantity (= reach and engagement) of program engagement. < SPAN> Programs designed to encourage RG's beliefs and actions should be regularly evaluated to confirm that they are effective in achieving their goals. Otherwise, there is a risk that resources will head in the wrong direction or that the accountability is being fulfilled. In this study, individual players are passively contacted with RG messages (for example, EGM's help line number), dialogue with RG materials or request support resources (for example, pamphlets. It suggests that land RG programs that depend on (picking up, etc.) may have a limit, but this survey shows the games program (border settings and money management skills). It should not be interpreted as suggesting that the impact on individuals who may need an educational pamphlet or the person who is directly painful for gambling is limited. Although data on specific exchange cases is not collected, a qualitative study on the game sense program (Abarbanel et al., 2018) has established a relationship with people who gamble frequently gambling. It is shown that a certain gambling can intervene. Therefore, it is important to recognize both quality (= content and results) and quantity (= reach and engagement) of program engagement. Programs designed to encourage RG's beliefs and actions should be regularly evaluated to confirm that they are effective in achieving their goals. Otherwise, there is a risk that resources will head in the wrong direction or that the accountability is being fulfilled. In this study, individual players are passively contacted with RG messages (for example, EGM's help line number), dialogue with RG materials or request support resources (for example, pamphlets. It suggests that land RG programs that depend on (picking up, etc.) may have a limit, but this survey shows the games program (border settings and money management skills). It should not be interpreted as suggesting that the impact on individuals who may need an educational pamphlet or the person who is directly painful for gambling is limited. Although data on specific exchange cases is not collected, a qualitative study on the game sense program (Abarbanel et al., 2018) has established a relationship with people who gamble frequently gambling. It is shown that a certain gambling can intervene. Therefore, it is important to recognize both quality (= content and results) and quantity (= reach and engagement) of program engagement.
   • Therefore, it is important to discuss two potential policy implications based on these observations and our survey results. First, after losing in gambling, you should consider being more aggressive with customers, such as being drunken, calling out to customers who are visibly frustrated. In fact, according to GIROUX et al. (2008) research, a more aggressive approach is to help the supervisor and start introducing it as part of the "help chain", so that we have helped and treating customers who have troubled. It is suggested that leading to resource screening is more effective. Second, as described above, the RG program should be considered using an untreated or sem i-experimental approach (White & Amp; Amp; SABARWAL, 2014), and in such an approach. Compare the prior beliefs and actions that were not exposed to (for example, matching population statistical characteristics and gambling participation indicators). Such an approach will approach the rating of causal relationships in the validity of the RG program. Such a methodological approach is more effective in both time and financial investment, but as a result, the actual impact of gambling and risky gambling, which is responsible and risky. We will provide reliable data.
   • The results of this study gave two suggestions on the theoretical framework of RG, including the Linomodel. First, even if the RG program exists and the client recognizes it, it is suggested that the involvement and actual impact to encourage more healthy gambling behavior may be limited. But this does not mean that casin o-based RG programs do not have a positive effect on clients with gambling or gambling disorders. In fact, other research on casin o-based gaming programs in a US lan d-based casino (for example, the preyet park casino in Massachusetts, Gray et Al. This value is a problem gambling in the United States Since it is almost the same as the estimated disease rate (WILLIAMS, volberg & amp; AMP; Stevens, 2012), 1%(or 0. < SPAN> to participate with a counselor, and our observation results and our observation results. Based on the results of the survey, it is important to discuss two possible policy implications, and after gambling, it seems to be drunken. According to GIROUX et al. It is suggested that it may be more effective to start a concerned customer to the help and treatment resource screening by starting the introduction as part of. The RG program should be considered using an untreated experimental or sem i-experimental approach (White & Amp; Amp; Sabarwal, 2014), and with such an approach, the prior beliefs that were not exposed to the program and Such an approach to the effectiveness of the RG program is comparable, for example, a gambling participation indicator. It costs both time and financial investment, which provides more effective and reliable data on the actual impact of gambling and risky gambling in which programs like game sense are responsible. See.
   • The results of this study gave two suggestions on the theoretical framework of RG, including the Linomodel. First, even if the RG program exists and the client recognizes it, it is suggested that the involvement and actual impact to encourage more healthy gambling behavior may be limited. But this does not mean that casin o-based RG programs do not have a positive effect on clients with gambling or gambling disorders. In fact, other research on casin o-based gaming programs in a US lan d-based casino (for example, the preyet park casino in Massachusetts, Gray et Al. This value is a problem gambling in the United States Since it is almost the same as the estimated value of the disease rate (Williams, Volberg & Amp; AMP; Stevens, 2012), 1%(or to participate with a counselor 0. Thus, these observation results and our survey results. Based on the two possible policy implications, it is important to first lose in gambling and are visibly frustrated. According to GIROUX et al. Starting the introduction as a department, it is more effective to lead a concerned customer to help and treatment resources, as described above. , Should be considered using an untreated experimental or sem i-experimental approach (White & Amp; Amp; SABARWAL, 2014), and in such an approach, prior beliefs and behaviors that were not exposed to the program (for example) Comparing the demographic characteristics and gambling participation indicators, such an approach to the effectiveness of the RG program. Although it is costly in both investment, the result will provide more effective and reliable data on the actual impact of a gambling and risky gambling.
   • The results of this study gave two suggestions on the theoretical framework of RG, including the Linomodel. First, even if the RG program exists and the client recognizes it, it is suggested that the involvement and actual impact to encourage more healthy gambling behavior may be limited. But this does not mean that casin o-based RG programs do not have a positive effect on clients with gambling or gambling disorders. In fact, other research on casin o-based gaming programs in a US lan d-based casino (for example, the preyet park casino in Massachusetts, Gray et Al. This value is a problem gambling in the United States Since it is almost the same as the estimated disease rate (Williams, Volverg & Amp; amp; Stevens, 2012), 1%(or participate with a counselor 0.
   • In this survey, 2 % of people have received leaflet, but when they are participating in the program, new gambling and current gambling issues are needed.
   • Second, this knowledge is information about the accurate knowledge of gambling mechanisms and information on support resources, which are important, for the purpose of promoting healthy gambling. The most vulnerable and most risky gambler group may be overlooked by the psychological and social characteristics of these groups, and DSM-5 of gambling disorders. Those who meet clinical standards (APA, 2013) show the distortion of awareness of the possibility that they can actually earn money and the illusion of control on the personal role that controls games acquired in gambling games. Often (Brooks et al., 2020? In fact, not only such cognitive distortions, but also strong interest in hig h-risk gamblers (Mcbride et al., 2010) are "careless blindness" (Kreitz et al. , 2015), as a result, ignoring the existence of the program (that is, the recognition is limited), and the use of gambling assistance resources may be limited (that is, low involvement).
   • Based on this result, which indicates that the perception and involvement of the land RG program is limited, and that the relevance of these indicators, beliefs and gambling behavior is weak, we will strengthen outreach activities for program elements and customers. We recommend that you conduct further research. However, it is necessary to interpret these results carefully for the methodology of observation and cros s-designed designs (Vanderweele, 2021). Therefore, this section ends in terms of the limits and directions of the future research on the game sense and the RG program in general. < SPAN> This survey requires a new gambling problem and a service for the current gambling problem when 2 % of people receive leaflet).
   • Second, this knowledge is information about the accurate knowledge of gambling mechanisms and information on support resources, which are important, for the purpose of promoting healthy gambling. The most vulnerable and most risky gambler group may be overlooked by the psychological and social characteristics of these groups, and DSM-5 of gambling disorders. Those who meet clinical standards (APA, 2013) show the distortion of awareness of the possibility that they can actually earn money and the illusion of control on the personal role that controls games acquired in gambling games. Often (Brooks et al., 2020? In fact, not only such cognitive distortions, but also strong interest in hig h-risk gamblers (Mcbride et al., 2010) are "careless blindness" (Kreitz et al. , 2015), as a result, ignoring the existence of the program (that is, the recognition is limited), and the use of gambling assistance resources may be limited (that is, low involvement).
   • Based on this result, which indicates that the perception and involvement of the land RG program is limited, and that the relevance of these indicators, beliefs and gambling behavior is weak, we will strengthen outreach activities for program elements and customers. We recommend that you conduct further research. However, it is necessary to interpret these results carefully for the methodology of observation and cros s-designed designs (Vanderweele, 2021). Therefore, this section ends in terms of the limits and directions of the future research on the game sense and the RG program in general. In this survey, 2 % of people have received leaflet, but when they are participating in the program, new gambling and current gambling issues are needed.
   • Second, this knowledge is information about the accurate knowledge of gambling mechanisms and information on support resources, which are important, for the purpose of promoting healthy gambling. The most vulnerable and most risky gambler group may be overlooked by the psychological and social characteristics of these groups, and DSM-5 of gambling disorders. Those who meet clinical standards (APA, 2013) show the distortion of awareness of the possibility that they can actually earn money and the illusion of control on the personal role that controls games acquired in gambling games. Often (Brooks et al., 2020? In fact, not only such cognitive distortions, but also strong interest in hig h-risk gamblers (Mcbride et al., 2010) are "careless blindness" (Kreitz et al. , 2015), as a result, ignoring the existence of the program (that is, the recognition is limited), and the use of gambling assistance resources may be limited (that is, low involvement).
   • Based on this result, which indicates that the perception and involvement of the land RG program is limited, and that the relevance of these indicators, beliefs and gambling behavior is weak, we will strengthen outreach activities for program elements and customers. We recommend that you conduct further research. However, it is necessary to interpret these results carefully for the methodology of observation and cros s-designed designs (Vanderweele, 2021). Therefore, this section ends in terms of the limits and directions of the future research on the game sense and the RG program in general.
   • We recognize four major constraints. First of all, this study is a study that reports on recognition and involvement in game programs, and sel f-report of beliefs and behaviors on games (for example, Braverman, Tom & Amp; Amp; Shaffer, 2014; Heirene, Wang & amp; GainSbury et al .) Social needs and recall bias (Van der Mass, Nower, Matheson, et al., 2021) may not be completely accurate. Similarly, the final wave data may have affected the responder's response patterns, as the COVID-19 was collected in early 2020, which spread throughout Asia and Europe. An approach to measuring gambling behavior using an electronically collected player (for example, a point card or online gambling record) may be improved to a sel f-reported method (Louderback, Laplainte, et See a similar approach of Al., 2021). Second, our samples have repeated cros s-sections, and the respondents are not tracked over time with propective or retro spective, so we have a strong claim about the causal of our hypothesis. I can't. Third, our analysis is only a MGM loyalty program member, a US land gaming company, so our results cannot be generalized to gaming operators in the United States. < SPAN> We recognize four major constraints. First of all, this study is a study that reports on recognition and involvement in game programs, and sel f-report of beliefs and behaviors on games (for example, Braverman, Tom & Amp; Amp; Shaffer, 2014; Heirene, Wang & amp; GainSbury et al .) Social needs and recall bias (Van der Mass, Nower, Matheson, et al., 2021) may not be completely accurate. Similarly, the final wave data may have affected the responder's response patterns, as the COVID-19 was collected in early 2020, which spread throughout Asia and Europe. An approach to measuring gambling behavior using an electronically collected player (for example, a point card or online gambling record) may be improved to a sel f-reported method (Louderback, Laplainte, et See a similar approach of Al., 2021). Second, our samples have repeated cros s-sections, and the respondents are not tracked over time with propective or retro spective, so we have a strong claim about the causal of our hypothesis. I can't. Third, our analysis is only a MGM loyalty program member, a US land gaming company, so our results cannot be generalized to gaming operators in the United States. We recognize four major constraints. First of all, this study is a study that reports on recognition and involvement in game programs, and sel f-report of beliefs and behaviors on games (for example, Braverman, Tom & Amp; Amp; Shaffer, 2014; Heirene, Wang & amp; GainSbury et al .) Social needs and recall bias (Van der Mass, Nower, Matheson, et al., 2021) may not be completely accurate. Similarly, the final wave data may have affected the responder's response patterns, as the COVID-19 was collected in early 2020, which spread throughout Asia and Europe. An approach to measuring gambling behavior using an electronically collected player (for example, a point card or online gambling record) may be improved to a sel f-reported method (Louderback, Laplainte, et See a similar approach of Al., 2021). Second, our samples have repeated cros s-sections, and the respondents are not tracked over time with propective or retro spective, so we have a strong claim about the causal of our hypothesis. I can't. Third, our analysis is only a MGM loyalty program member, a US land gaming company, so our results cannot be generalized to gaming operators in the United States.
   • Based on the knowledge obtained in this study, and the meanings and limits described above, there are three possibilities for future research. First, considering that the recognition and involvement of the programs in other studies (eg, Louderback, Gray, et al., 2021) that examined the aspects of this research and the GameSense RG program, RG resources are considered. It is important to consider how much to provide in a different communication style or in different places in a casino. For example, placing a game sense RG resources in a place that is easy to see the lan d-based casino may help to increase the awareness of available education and support resources. Such an approach can also reduce the blindness of these gamesense resources while giving customers a tool that helps manage gambling behavior by enhancing sel f-efficacy (Quinn et al.).
   • Second, conducting a comparative analysis with RG programs based on other casinos in the United States and overseas, how to compare the results of the game sense program with other types of RG initiatives with different program elements and customer base. It is necessary to clarify whether it will be done. It is not clear whether the observed survey results are typical of the general RG program or this is unique to the implementation of this game sense. Specifically, randomization comparative testing methodology (DeveloperAux & Amp; amp; Yusuf, 2003) or sem i-experimental approach (bärnign heavySen et al.
   • Third, the nature and content of the interaction between the game sense advisor and the customer will be related to the belief and behavior results of different types of gambling. A typical survey would be a fruitful way for future research. Game sense advisors are likely to occur between those who have a specific belief in gambling in advance. If this is a fact and those who need more knowledge acquisitions could not engage, program designers would need to narrow down the target and design intervention measures. < SPAN> Based on the knowledge obtained in this study, and the meaning and limitations described above, three possibilities are considered as a path of future research. First, considering that the recognition and involvement of the programs in other studies (eg, Louderback, Gray, et al., 2021) that examined the aspects of this research and the GameSense RG program, RG resources are considered. It is important to consider how much to provide in a different communication style or in different places in a casino. For example, placing a game sense RG resources in a place that is easy to see the lan d-based casino may help to increase the awareness of available education and support resources. Such an approach can also reduce the blindness of these gamesense resources while giving customers a tool that helps manage gambling behavior by enhancing sel f-efficacy (Quinn et al.).
   • Second, conducting a comparative analysis with RG programs based on other casinos in the United States and overseas, how to compare the results of the game sense program with other types of RG initiatives with different program elements and customer base. It is necessary to clarify whether it will be done. It is not clear whether the observed survey results are typical of the general RG program or this is unique to the implementation of this game sense. Specifically, randomization comparative testing methodology (DeveloperAux & Amp; amp; Yusuf, 2003) or sem i-experimental approach (bärnign heavySen et al.
   • Third, the nature and content of the interaction between the game sense advisor and the customer will be related to the belief and behavior results of different types of gambling. A typical survey would be a fruitful way for future research. Game sense advisors are likely to occur between those who have a specific belief in gambling in advance. If this is a fact and those who need more knowledge acquisitions could not engage, program designers would need to narrow down the target and design intervention measures. Based on the knowledge obtained in this study, and the meanings and limits described above, there are three possibilities for future research. First, considering that the recognition and involvement of the programs in other studies (eg, Louderback, Gray, et al., 2021) that examined the aspects of this research and the GameSense RG program, RG resources are considered. It is important to consider how much to provide in a different communication style or in different places in a casino. For example, placing a game sense RG resources in a place that is easy to see the lan d-based casino may help to increase the awareness of available education and support resources. Such an approach can also reduce the blindness of these gamesense resources while giving customers a tool that helps manage gambling behavior by enhancing sel f-efficacy (Quinn et al.).
   • Second, conducting a comparative analysis with RG programs based on other casinos in the United States and overseas, how to compare the results of the game sense program with other types of RG initiatives with different program elements and customer base. It is necessary to clarify whether it will be done. It is not clear whether the observed survey results are typical of the general RG program or this is unique to the implementation of this game sense. Specifically, randomization comparative testing methodology (DeveloperAux & Amp; amp; Yusuf, 2003) or sem i-experimental approach (bärnign heavySen et al.
   • Third, the nature and content of the interaction between the game sense advisor and the customer will be related to the belief and behavior results of different types of gambling. A typical survey would be a fruitful way for future research. Game sense advisors are likely to occur between those who have a specific belief in gambling in advance. If this is a fact and those who need more knowledge acquisitions could not engage, program designers would need to narrow down the target and design intervention measures.
   • GameSense shows the potential of Pledge as a RG tool to increase gambling literacy and use of RG strategies. However, improvements are needed to increase both awareness and engagement and ensure that the program elements have a significant (and quantifiable) impact on RG habits among patrons visiting land-based casinos. Providing new and innovative player safety tools to those who wish to gamble is important to maintain a healthier gambling environment. Central to such innovations is proper and routine empirical evaluation. Without independent evaluation, well-intentioned but ineffective RG programs may become widespread and have limited impact on reducing problem gambling harm among casino patrons.
   • Data for this article was taken from the Transparency Project website (www. thetransparencyproject. com).
   • Casino operators can decide whether to include various elements of the RG program within their GameSense brand. These elements range from limited, with RG video kiosks displaying instructional videos, to more comprehensive, including educational brochures on gaming project methods, trained gaming counselors to assist patrons, and referral resources for at-risk players (e. g., voluntary self-exclusion programs), as applied to MGM-based properties.
   • Importantly, we collected observational data from a cross-sectional sample rather than a longitudinal panel sample. This point is discussed in more detail in the discussion section.
   • Another review by Beckett et al. (2020) included 22 studies and investigated research on RG training for employees at land-based gaming properties, but this study was focused only on customer experience and not on employees in the gaming industry.
   • The “3-year” period in survey items 3 and 4 is used as an estimate of the time period from the introduction of GameSense at each property to the end of customer survey data collection 3. The actual time period may not be exactly 3 years for all properties, as there are slight differences in the GameSense introduction process for all properties.
   • The first two properties were added to the Year 3 survey because they were purchased by MGM between the Year 2 and Year 3 data collection periods but did not have a gaming program at the time of the survey. Also, MGM Corporate is not a gaming property. For these reasons, we notified the respondents in advance of our intention to exclude only those who visited one of these three properties.
   • Three of the 16 IP addresses were included in the Year 1 data set and 55 in the Year 2 data set. This indicates very little overlap in the survey samples from year to year.
   • The survey also included a question asking whether the respondent was aware of or had used the VSE program. However, because very few respondents reported participating in the VSE program (e. g., four in Year 2), we decided to exclude both VSE variables from the analysis. Additionally, all respondents who were on the VSE list were opted out of email contact from Marketing, so these respondents were VSE program participants prior to each year of data collection.
   • As described in Louderback, Gray, et al. (2021), the way GameSense is applied at the Springfield, Massachusetts casino differs substantially from the way it is applied at MGM casinos outside of Massachusetts, including these four other area properties. These analyses should be understood in this context, and the results are discussed with this program element in the discussion section.
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   • Abarbanel, B., Gray, H. M., Laplante, D. A., & amp; amp; Bernhard, B. J. (2019). Association between Employee Division and Perceptions of Responsible Gaming Programs. International Gaming Studies, 19 (3), 471-488. Article in print
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   Acknowledgements

   Funding

   Braverman, J., Tom, M. A., & amp; amp; Shaffer, H. J. PsyChological Evaluation, 26 (3), 865-877. ArticlePubmedGoogle School

   Author information

   Authors and Affiliations

   1. British Colombia Lottery Corporation (BCLC). Gamesense Home Page. Https: // www. Gamesense. Com.
   2. Cognitive factors of gambling disorders, which are behavioral addiction. A. Verdejo-Garcia (Ed.), Cognition and Addiction (pp. 209-219). Academic press. Google scholarship
   3. Devrow, P. YUSUF, S. (2003). Randomization comparison test evolution and evidence's role in decisio n-making. Journal of Internal Medicine, 254 (2), 105-113. ArticleCaspubmedGoogle School
   4. Feedler, I., Kairouz, S., & amp; amp; amp; Reynolds, J. Journal of Public Health, 29 (4), 993-1000. Papers
   5. Finkenwirth, S., Macdonald, K., Deng, H., Lesch, L. (2021). USING MACHINE Learning to Predict Self-Exclusion Studus in Gambline. ON The Playnow. com Platform in British Columbia. International Gaming Studies, 21 (2), 220-237. Papers
   6. Forstrom, D., spoofy, J., Peterson, Blund, a., & amp; Amp; Amp; Amp; Amp; Amp; Amp; Amp; Amp; Addiction Theory, 29 (5), 398-412. Papers
   1. Gainsbury, S., Wood, R., Russell, A., Hing, N., & amp; amp; amp; amp; Blaszczynski, A. Comparison of attitude and gambling behavior. Computers in Human BEHAVIOR, 28 (4), 1388-1398.
   

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   Last modified: 27.08.2024

   lcusoccer.org › pmc › articles › PMC 4 Citations · Examining Responsible Gambling Program Awareness and Engagement Trends and Relationships with Gambling Beliefs and Behaviors: A Three-Wave Study of. Tiange Xu (Hospitality), Brett Abarbanel (International Gaming Institute), and Shane Kraus (Psychology) presented a poster, "Problem Gambling and Mental Health.