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Gambling addiction

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Gambling addiction baron corbin

Postby Mikall В» 10.06.2019

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Concurrent drinking and gambling is prevalent among young adults and may increase negative consequences associated with each behavior. The effects of alcohol, initial gambling outcomes, gambling-related cognitions, and impulsivity on gambling behavior were evaluated. Initial gambling outcomes, gambling-related cognitions, and impulsivity were also assessed as potential moderators of the relation between alcohol and gambling behavior.

Alcohol consumption was associated with larger average bets and more rapid loss of all available funds, though no evidence was found for predicted main effects and interactions for gambling persistence. The effect of impulsivity was moderated by beverage condition, such that higher levels of impulsivity were associated with larger average bets for participants in the placebo but not the alcohol group.

Results have direct implications for individual-focused and public-health interventions. Late adolescence and young adulthood is marked by engagement in risky behaviors, including frequent and heavy use of alcohol Arnett, , Rates of heavy episodic consumption and drinking to intoxication are consistently higher among college students relative to their noncollege peers Johnston et al. Gambling also frequently co-occurs with alcohol use. The relatively poor enforcement of minimum drinking age and minimal cost of alcohol served to patrons who are actively gambling encourages an even higher percentage of underage college students to engage in casino gambling in order to obtain alcohol Despite their demonstrable association, relatively little research has been conducted on the co-occurrence of alcohol use and gambling, with even fewer studies evaluating the impact of alcohol on gambling behavior.

Maladaptive behavior occurring within a single gambling session i. This type of within-session chasing may lead to long-term gambling problems by precipitating between-session chasing i. Considering the ubiquitous availability of alcohol in many gambling venues, understanding how alcohol influences persistence and other betting behaviors that may serve as precursors to disordered gambling is a necessary step to inform prevention efforts for both behaviors.

Although limited in scope, there is some evidence to suggest that alcohol use may contribute to longer duration of gambling episodes and increased amount of money spent.

Compared to college students who never or rarely consume alcohol while gambling, those who frequently or always drink while gambling are more likely to report typical gambling episodes lasting 2 or more hours Giacopassi et al. Kyngdon and Dickerson also found greater persistence in gambling after alcohol consumption in a sample of moderate-to-heavy male drinkers placed on a progressive loss schedule.

This study used a computerized card game in which participants were asked to bet on whether the next card drawn would be high or low.

However, these results should be interpreted with caution given a marginally higher level of trait impulsivity at baseline among participants in the alcohol condition. Participants demonstrated shorter latency between betting decisions i.

In addition, these studies have relied minimally on theory to drive study hypotheses. Under conditions where both impelling and inhibiting cues are present, the model posits that behavior will be determined by the relative strength of the cues.

Thus, alcohol effects should be moderated by contextual and intrapersonal factors that influence cue salience. There are several possible contextual and intrapersonal factors that may influence the salience of internal and environmental cues for the individual. Perhaps the most obvious contextual factor is recent gambling outcomes. Thus, individuals who win during the initial portion of a gambling occasion should be more risk-averse i.

In terms of intrapersonal factors, maladaptive cognitions related to potential gambling outcomes may enhance the salience of cues for reward, thereby exerting direct effects on gambling behavior, as well as potentially moderating the effect of alcohol.

Irrational beliefs about gambling may lead individuals to continue gambling even when objective information suggests that they should stop. Finally, certain personality traits may affect cue salience. For example, individuals high in impulsivity tend to focus less on potential costs and more on cues for reward. Dispositional factors that incline an individual to demonstrate poor behavioral control may thus directly influence gambling behavior as well as serve to moderate the effects of alcohol.

Even when multiple measures have been used, they have typically assessed a single dimension of impulsivity e. The purpose of the current study was a to evaluate the impact of alcohol consumption on gambling behavior i. In pursuit of these aims, a two-group alcohol vs. Individuals with more erroneous beliefs about control over gambling outcomes and individuals scoring higher on measures of trait impulsivity were also expected to persist longer and wager more.

Specifically, alcohol effects were expected to be strongest among individuals experiencing initial losses, and among those with more distorted cognitions and higher levels of impulsivity. Participants between the ages of 21 and 30 were recruited from several New England college campuses and their surrounding communities. To qualify for participation an individual had to complete a telephone screen and report that he or she a consumed three or more drinks on at least one occasion per week over the last 3 months; b engaged in one or more forms of gambling at least once in the last 3 months; and c played a slot machine or gambled at a casino at least once during his or her lifetime.

Minimum inclusion criteria were selected to ensure that participants had sufficient familiarity with drinking and gambling of a nature consistent with the requirements of the study protocol , thereby minimizing any effects due to inexperience or novelty.

The first 15 participants provided pilot data leading to a change in the gambling task used to collect the criterion data see simulated slot machine description below. Values for age represent group means standard deviations.

No statistically significant differences were present when experimental groups were compared. Drinking and gambling data were collected via behavior-specific timeline followback interviews; see Interviewer-Administered Measures section for a full description.

Drinking data reflect estimates from the past 30 days whereas gambling data reflect estimates from the past 90 days. The protocol was implemented in groups of two to four individuals on weeknight evenings, with groups randomly assigned to alcohol and active placebo conditions.

Participants were asked to refrain from consuming alcohol or other drugs during the preceding 24 hours, and to refrain from eating for 4 hours prior to the protocol. Upon arriving at the lab, participant age was verified, informed consent was obtained, and breathalyzer tests were administered to ensure a zero breath alcohol concentration BrAC. Female participants were required to perform a urine test to rule out pregnancy. Participants were subsequently asked to complete a set of computer-based self-report measures assessing a demographic characteristics; b gambling-related cognitions; c personality traits; d experience with and preference for specific types of gambling; and other constructs unrelated to the current study.

Participants also completed interviewer-administered retrospective-recall measures of gambling and alcohol behavior. Following completion of the interviews and self-report measures participants were administered three drinks over 30 minutes in a simulated bar setting.

In order to keep research assistants who served the drinks blind to the beverage condition, alcohol and active placebo presentations alcohol bottles filled with pure 80 proof vodka or a ratio of flat tonic water to 80 proof vodka, respectively and the delivery vehicle a nonalcoholic mixer comprising a ratio of lemon-lime soda, cranberry juice, and lime juice , were prepared in advance by a protocol supervisor.

A target BrAC of 0. Moreover, this target is consistent with the higher range of BACs that are evident among individuals who engage in heavy episodic drinking i. In addition to including a small amount of alcohol in the placebo mixture and floating a small amount of alcohol on the top of each drink, beverage glasses were rimmed with alcohol to enhance the credibility of the placebo.

The total volume of alcohol served to participants in the active placebo condition was calculated to achieve a target BrAC of 0. Both alcohol and placebo presentations were poured in full view of participants before being added to the nonalcoholic mixer at a ratio. Concurrent with BrAC assessments, participants were asked to provide estimates of subjective intoxication as a manipulation check.

Participants were subsequently given the opportunity to play a simulated slot machine the criterion task in an adjoining room. The task was set up in blocks of 15 trials to allow manipulation of contingencies, and participants were assigned to one of three initial gambling outcome conditions win, breakeven, loss.

As all participants completed the task simultaneously in the same room similar to playing slot machines in a casino , assignment to initial gambling outcome condition was stratified to avoid arousing suspicion.

On evenings when two or three participants were present, each participant was assigned to a different initial gambling outcome condition; when four participants were present, one condition was repeated. Participants were told that they could play for as long as they chose. However, the program was terminated when all credits were exhausted. Following play on the slot machine, participants completed two additional tasks unrelated to the current study.

BrAC measurements were taken by the protocol supervisor and estimates of subjective intoxication were provided by participants following each task. At the end of the protocol all participants were debriefed, and individuals in the placebo condition were allowed to leave.

In accordance with recommendations from the National Advisory Council on Alcohol Abuse and Alcoholism , participants in the alcohol condition were required to remain in the laboratory until their BrAC dropped to 0. Demographic information assessed included age, sex, ethnic and racial identity, educational background, academic standing, and socioeconomic status. Internal consistency reliability alpha coefficients for the three subscales were. This larger subscale comprises two separate subscales assessing sensation seeking needs sensation seeking; 11 items , and lack of planning and tendency to act without thinking impulsivity; 8 items.

Internal consistency reliability alpha coefficients were. Participants were also asked to rank the different types of gambling from 1 most like to engage in to 10 least like to engage in. Two separate items were used to assess perceived amount of alcohol consumed i.

Whole numbers 0 to 6 , with nine evenly spaced intervening tick marks representing one-tenth increments; e. Two-digit decimals. For each question, participants were asked to place an X on a line corresponding to their estimate. Participants rated the extent to which they experienced each effect on point Likert-type scales with anchors at 0 not at all and 10 extremely.

Coefficient alpha was calculated at each of the four separate assessment points. Values were in excess of. Total number of drinking days in the past month, hours spent drinking per drinking day, and number of drinks consumed per drinking day served as the primary indices from this measure.

With the assistance of the interviewer and a day calendar, participants were asked to identify on which days they had gambled. For each gambling episode, participants were asked to indicate the a game played or activity engaged in; b time spent gambling; c amount of money they intended to bet; d amount of money actually risked i.

Three indices capturing different aspects of quantity and frequency of gambling activity during the past 3 months were computed: number of gambling days; hours spent gambling per gambling day; and dollars gambled per gambling day. A computerized slot machine program originally developed by MacLin, Dixon, and Hayes was used to administer the initial gambling outcome manipulation and assess gambling persistence and betting behavior the criterion variables.

The program visually simulates a three-reel, single pay-line slot machine with five symbols, including the motion of the reels spinning and stopping; no additional sensory features e. Persistence was measured as the total number of trials played and betting behavior was measured by the average amount bet per trial played.

Prior to conducting the primary analyses, data were screened for the presence of univariate outliers. If necessary, data were transformed to normalize their distribution. If extreme values were still evident, another transformation was performed. Data screening and all analyses were conducted using SPSS Thus, a single composite was created to eliminate potential problems with multicollinearity and to address concerns about use of individual scales with reliability coefficients below.

BrAC observations were analyzed using a 2 beverage condition by 4 assessment time analysis of variance ANOVA , with beverage condition serving as a between-subjects factor and assessment time serving as a within-subject factor. Individuals in the alcohol and placebo condition attained mean peak BrACs of 0.

Actual BrACs before and after completion of the criterion task were. Observed BrACs and estimated BACs by beverage condition at postabsorption Time 1 , following play on the simulated slot machine Time 2 , and after two successive min intervals Time 3 and 4.

Although the two groups differed significantly, the estimates provided by the placebo group were relatively high. At postabsorption, participants in the placebo group estimated they had received an average of 2. At postabsorption, participants in the placebo group reported a mean stimulation rating of 2.

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