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--> 7 Organization and Technology of Gambling Most research on the causes of pathological gambling examines gamblers themselves—their family back grounds, personality traits, experiences with gambling, attitudes about risk, motivations to gamble, and genetic attributes. Such research can lead to a better understanding of individual risk factors in pathological gambling and to better ways to predict and treat gambling problems. Another perspective examines changes in the social and technological environment surrounding gambling. From this perspective, we can ask whether changes in the organization of the gambling enterprise and technologies of gambling lead to more or fewer pathological or problem gamblers, or to new disorders associated with gambling. These are critical questions for developing sensible policies. Most of the research on these questions is only indirectly related to pathological gambling. At the level of games and betting, there is considerable experimental research on the effects of game structure and game presentation on people's propensity to take risks or to make "nonrational" gambles (e.g., Cole and Hastie, 1978; Mikesell and Zorn, 1987; Ladouceur and Gaboury, 1988). Papers have been authored about how, at the level of society, legalization has potentially affected the prevalence of gambling and pathological gambling (Rose, 1995, 1998). There also has been
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--> discussion, but not much empirical research, on how changes in the gambling industry have changed the social context of gambling (e.g., Clotfelter and Cook, 1989). More recently, researchers and policymakers are debating whether the spread of computer-based (video or machine) gambling is changing the prevalence or nature of pathological gambling (Fisher, 1994; Fisher and Griffiths, 1995). Research has not established whether distinctive types of gambling organization and technology cause systematic changes in pathological gambling, but some of the research suggests such links may exist (Griffiths, 1993, 1995, 1998). History Much of what we know about the effects of earlier changes in the gambling industry and gambling technologies—such as the introduction of slot machines and the legalization of casinos in Nevada—comes from historical, biographical, and ethnographic narratives (e.g., Chavetz and Simon, 1967; Skolnick, 1978; Thompson, 1986; Fabian, 1990). This work suggests a close relationship between the social context and technology of gambling, gambling behavior, and social outcomes. For example, according to Barrett (personal communication to the committee, 1998), the most significant early technological development in horse racing was the invention at the turn of the century of a wagering system and calculating machine called the Pari-Mutuel System. (The system survives today as "pari-mutuels.") The system allowed some bettors to improve their outcomes by predicting races more skillfully and/or by betting more wisely than most bettors, who underestimate the utility of betting on favorites compared with long shots (Griffiths, 1994; Metzger, 1985; Ladouceur et al., 1998). The system also gave rise to distinctive social roles (bookmaker, professional racetrack gambler, punter) and distinctive supporting technologies (e.g., the racing form). Different domains of gambling have evolved distinctive cultures, norms, technologies, and social groups who have dominated gambling markets in their respective domains. For example, bingo has its callers and parlors and mainly women patrons. In general, "female" gambling domains are those in which gambling is likely to be less skill-based or to involve less
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--> social assertiveness than "male" domains (Kiesler et al., 1985). Kallick and colleagues (1979) noted that, in the United States, Jewish men were overrepresented at the racetracks and were also likely to have gambling problems. This demographic pattern, which is not as discernible in current studies, perhaps was related to the proximity of racetracks to Jewish communities. In any event, there developed among these men a subculture of the track and racing lore. Close social networks were formed among those who bet at the track or in offtrack venues; they would trade tips and loans. Rosecrance (1986) and Zurcher (1970) have also provided accounts of the role of social groups in gambling. It is possible that the subculture of some gambling domains buffers the effects of pathological and problem gambling. For example, friends who gamble together may exert mutual social pressure to limit their gambling expenditures. Such social processes surrounding the technology of gambling have obvious implications for the advent of home gambling and machine games that may also encourage solo gambling. Nature and Structure of Games A large body of research suggests that today's gambling technologies and venues take advantage of people's normal responses to reward contingencies and to people's cognitive biases, perceptions of risk, and tendency to compartmentalize mental accounts of their expenditures (e.g., Fischhoff et al., 1981; Wagenaar, 1988; Varey et al., 1990; Kahneman and Tversky, 1979; Tversky and Kahneman, 1992). Some authors argue that gambling represents the purchase of an intangible leisure good, like purchasing a ticket to the movies (Vogel, 1994). However, because gamblers no doubt expect, or hope for, something tangible (money), gambling might be less similar to viewing a movie than to shopping for a luxury watch or car. The value of the activity draws in part from the social desirability of obtaining a rare tangible good and in part from the drama or pleasure of the activity itself. Risk may be part of the pleasure. Gambling is influenced both by the actual risks and rewards of games and by how people imagine these risks and rewards.
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--> Reward Contingencies Most of the early experimental literature related to gambling focused on the tangible rewards in gambling and were derived from studies of learning through reinforcement and conditioning. Animal and human studies showed that behavior that is rewarded intermittently and randomly is likely to be repeated in the same situation and will be highly resistant to extinction (i.e., the behavior ceases only after many unrewarded trials). Thus, variable and multiple rewards in a gambling situation evoke more gambles and higher bets than single, consistent rewards do (Knapp, 1976). Because most commercial games comprise intermittent rewards of varying magnitude, early learning research suggested that what it called compulsive gambling is a learned or conditioned behavior; however, since few gamblers become compulsive, intermittent and variable reward alone cannot explain problem or pathological gambling. One possibility is that additional aspects of gambling reward experiences are likely to result in habitual or problem gambling. For instance, people are likely to continue gambling when they are ahead and can gamble "with the house's money" (Thaler and Johnson, 1990). As mentioned in Chapter 2, it has also been shown that near-wins (e.g., the slot machine shows two apples and one pear) are particularly motivating (Skinner, 1953) (see also Kahneman and Tversky, 1979, for cognitive explanations of this effect). With some exceptions (e.g., Ladouceur et al., 1995), this research has been conducted in hypothetical gambling situations or involved small amounts of money (e.g., Wagenaar, 1988). A few studies report that pathological gamblers say they experienced a jackpot or winning streak early on (e.g., Moran, 1970), which is consistent with the laboratory research, although these studies lack baseline data. Perhaps every gambler remembers his or her first big win. Cognitive Distortions Research on the cognitive processes involved in judgment and choice has been fruitful in helping to elucidate gambling choices and preferences and, by extension, the kinds of technologies that
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--> may encourage habitual or excessive gambling (Wagenaar, 1988). For example, several specific cognitive distortions have been noted as possible contributors to pathological and problem gambling, including: (1) the misunderstanding of the concepts of chance and randomness, (2) attitudinal and belief inertia, and (3) improper resetting of mental accounts. Each of these, discussed below, may contribute to biases in people's assessment of chance processes. Not surprisingly, many popular and profitable gambling products feature games that capitalize on biased judgments; many of these products are attractive to people even in the presence of very unlikely rewards. For example, many gamblers seem to think that multiple gambles give them ''more ways to win" even when the multiple gambles are actually disadvantageous to them (Cohen and Chesnick, 1970). And many gamblers also believe independent, random events are somehow connected (Ladoucer and Dube, 1997). People generally have a strong need to impose order or meaning on random processes, and researchers have investigated whether people can generate random sequences of binary events (such as flipping a coin). Results show that they are often poor at both recognizing and creating such sequences (Wagenaar, 1988), may impose too many alternations on a sequence, or may equate randomness with a balance of event frequencies (Wagenaar, 1972). These tendencies contribute to the gambler's fallacy, which dictates that past losing events are less likely to occur in the future (Cook and Clotfelter, 1993). For example, after several heads have appeared sequentially in the tossing of a coin, it is hard for many to resist the temptation to believe that the next toss will not be heads once again, even though the odds are still 50 percent heads versus 50 percent tails. In addition to trying to identify predictable patterns in random sequences, people also try to control random outcomes. Langer (1975) refers to this effect as the illusion of control. Gamblers have a variety of methods for exerting their control in gambling situations. For example, Henslin (1967) noted that some gamblers believe they can influence the outcomes of a die roll by tossing it softly for a low number and hard when a high number is desired. Keren and Wagenaar (1985) found that blackjack players would often switch to new tables after a streak of losses in
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--> order to change their luck. Other blackjack players would try to interfere with the shuffled order of cards by drawing an extra card that they would normally never draw. In this way, they believed they could break an unlucky predetermined pattern and put themselves on a winning streak. The attempt to impose order on random sequences also relates to overestimating the importance of minimal skill involved in some types of gambling. This was described by Gilovich et al. (1985) who claim that the "hot hand," apparent in basketball when a player's performance is perceived to be significantly better than expected, may be no more than a long sequence of randomly generated events. That is, players occasionally may perform better than expected simply due to chance, and to believe otherwise may be a cognitive distortion. However, playing basketball involves skill. So, although a successful string of free throws may be the result of chance, it is also possible that a player's shooting on a particular day may have been much more skillful than normal and due to little if any chance at all. As previously indicated, some forms of gambling (e.g., cards and track betting) involve both chance and limited skill. Cognitive distortions can occur when gamblers over-or underestimate the chance and the skill involved. Other forms of gambling, such as slot machines, involve no skill at all but can nonetheless affect illusions of control. Griffiths (1994) asked those who gambled frequently and infrequently, "Is there any skill involved in playing the slot machine?" Those who gambled infrequently tended to say, "mostly chance," whereas frequent gamblers often said, "equal chance and skill.'' When asked, "How skillful do you think you are compared with the average person?" frequent gamblers thought they were often above average in skill, whereas infrequent gamblers said they were either below average or totally unskilled. Gamblers favor lotteries featuring complex games; they fail to multiply probabilities and believe they are more likely to win these games than they really are (Cole and Hastie, 1978). These perceptions may explain some of the attractions of slots, lotteries, and multiple-game video machines. Gamblers also favor long shots (Griffith, 1994; Metzger, 1985), a bias that causes them to win less than they might otherwise in sports betting. Experience
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--> does not necessarily increase accuracy. With experience, many gamblers lose their fear of taking risks, place larger bets, and bet more on long shots (Ladouceur and Mayrand, 1986). Gamblers' reduced fear with experience may be associated with their tendency to create stories about events and anthropomorphize gambling objects. Gamblers imbue artifacts such as dice, roulette wheels, and slot machines with character, calling out bets as though these random (or uncontrollable) generators have a memory or can be influenced (Langer, 1975). More generally, gamblers desire, and think they can have, more influence than they actually do on random events (Langer, 1975). They choose lucky numbers, get strong hunches about future random events, value numbers they choose more than numbers they don't, think they can influence a dealer's shuffle, and bet more on their own hands than on others' hands (Phillips and Amrhein, 1989; Chau and Phillips, 1995; Lacey and Pate, 1960). They develop retrospective stories about systematic turns of luck, resulting in the gambler's fallacy about past losses (Rule and Fischer, 1970) and a belief in winning streaks (Myers and Fort, 1963; Cohen et al., 1969). They also remember wins and explain away losses (Gilovich, 1983) and become more comfortable with risk and what they are "learning" as they make repeated gambles (Rachlin, 1989). The illusion of luck turning or of control increasing with experience encourages betting (Lupfer and Jones, 1971). Rachlin (1990) suggests that gamblers frame their games in strings, ending each string after a win. He claims people are especially attracted to large prizes because any win would more than eliminate losses. Pathological gambling often involves chasing losses (Lesieur and Custer, 1984). This behavior is addressed by Rachlin (1990), who argues that people who persist in gambling despite heavy losses do not adequately update their mental accounts. Normally, people keep track of their spending, winnings, and cash amounts mentally. Rachlin (1990) describes how gamblers may not reset their mental accounts often enough to recognize the full extent of their losses; that heavy gamblers temporarily discount losses more in long, negative strings than in short, positive strings. Negative strings can be evaluated positively in the mind of the gambler if losses are discounted. Furthermore, gamblers postpone
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--> their resetting as they continue to gamble, which can make negative strings falsely appear even more positive. This model of chasing losses can describe at least some of the cognitive distortion in pathological gambling. Moreover, peoples' attitudes, beliefs, and opinions are remarkably resistant to change, even when confronted with overwhelming evidence to the contrary (Klayman and Ha, 1987). This state of attitudinal and belief inertia is exacerbated by biased memories of past events. Some theorists have argued that people show evidence of a hindsight bias (Fischhoff, 1975). After an outcome has occurred, people may claim that they "knew it all along" (Wagenaar, 1988)—which may illustrate another form of omnipotence or an illusion of control. In addition, gamblers may have better recall for absolute wins than for relative net winnings—because they gamble frequently, they may win frequently, and some of their wins may be quite large. Nonetheless, those who gamble also lose frequently, and given the fact that the odds are against them, losses usually surpass wins by a considerable margin. Yet it is the wins, especially the big wins, that tend to be remembered, and loses tend to be discounted or forgotten. An important question is whether electronic slots, video poker, and video lottery machines, all of which are spreading rapidly and involve chance-based betting, are more or less harmful than more traditional games, such as racetrack betting and playing poker and blackjack. There are arguments on both sides of this question, and empirical research has not settled the matter. In part the question depends on who gambles. Games that are part skill-based might attract particular groups, such as men (Chantal et al., 1995; Oster and Knapp, 1998), educated people, or people who desire control (Langer, 1975; Chantal et al., 1995); such groups may be more or less prone to pathological gambling. On one hand, problem gambling could result from skill-based betting per se, if people's belief in their gambling skills encouraged them to hold misplaced illusions of control or respond overly to short-term streaks (Phillips and Amrhein, 1989). On the other hand, skill-based gambling might be less likely to lead to pathological gambling than wagering in purely chance games. If wagering involves skill, then negative feedback (losses) could cause further study or rational adjustments in strategy. Game
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--> speed may be important. Skill-based betting may be experienced as slow or unexciting compared with most chance betting situations (Barrett and Russell, 1998). Although the absence of time pressure tends to encourage betting in the laboratory (Phillips and Amrhein, 1989), gambling without time pressures in real-world settings could be experienced as relaxing and might encourage gamblers to bet limited amounts to extend their play time. Game Structure The characteristics of game technologies, such as the number of gambles offered per time period, the physical and informational environment of games, game rules, speed of play, probabilistic structure, cost per play, and jackpot size, appear to affect gambling preferences and habits. For instance, repetitive and multiple interactive games can be created in which the gambler's illusions of increasing skill and premonitions of impending luck are encouraged through reward contingencies. These technology attributes, of course, are more easily manipulated by those who develop and offer games than are attributes of gamblers themselves. New computer-based video machines, in particular, can be programmed to emit the most empirically profitable stimuli and reward contingencies. Often today's machines and games are tested with customers in real gambling settings; those that pay off best are retained and those that customers tire of are discarded (McKay, personal communication to the committee, 1998). Hence these products adapt to the marketplace, evolving to present more enticing gambling situations. State lottery commissions have increasingly changed the structure of lotteries to take advantage of cognitive biases and responses to reward. A powerful phenomenon is people's attraction to bets featuring large rewards with small probabilities of winning as opposed to bets with smaller rewards and bigger probabilities of winning (Herrnstein, 1990). In the 1990s, numerous front-page stories documented public zeal over multimillion-dollar jackpots with infinitesimal chances of winning. Cook and Clotfelter (1993) provided a thorough account, both theoretical and empirical, of the effect of odds and jackpots on lotto play. They note that the size of the market may influence lotto ticket
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--> sales and determine whether a long-odds game is feasible to implement in states like Delaware with relatively small populations. Lyons and Ghezzi's (1995) time series analysis of Oregon's and Arizona's lotteries is one of the few quasi-experimental studies showing how these preferences interact with changes in technology. The authors showed that Oregon's lottery was modified five times and Arizona's four times from 1985 to 1991. Each modification resulted in lower odds of winning and/or a bigger jackpot. On one hand, reducing the odds was unrelated in either state to changes in betting, suggesting that people like low stakes and do not discriminate different odds or changes in the odds when the odds are small anyway (see also Waerneryd, 1996; Huber et al., 1997). On the other hand, increasing the jackpot was strongly related to increased betting. Betting also increased when lotteries were drawn twice weekly instead of weekly, which could be explained either by increased opportunity to play or by reduced risk aversion with more familiarity (Rachlin, 1989). Sales trends suggested that ever-larger jackpots were required to sustain previous levels of play. Lyons and Ghezzi's (1995) time series study strongly suggests that gambling can be manipulated by lottery organizations through adjustments of lottery structure and rewards. However their study did not examine all aspects of the game environment. For instance, Orgeon has added instant scratch-off numbers games, keno, video poker, sports betting, and the multistate Lotto American game. Both states border Nevada and California, which offer competing products. The behavior of the Oregon and Arizona lottery commissions suggests strongly that lottery organizations model one another in devising competitive market strategies; hence changes in the environment of gambling arise from interstate as well as intrastate competition. Advances in telecommunications and the spread of Internet-supported gambling suggest that gambling is becoming a global business, responsive to competitive pressures across the world. "Stimulus" Context of Games A dimension of games that has not received much research attention is the physical and informational environment in which
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--> games are presented. This environment includes such factors as informational variations in advertising and instructions, visual differences in the architecture of casinos, and what interface designers call the "form factor" of games (e.g., whether the slot machine has an arm or buttons, takes coins or reads plastic cards, and so forth). Advertising and other information affect what people know about gambling and how they think about it. For instance, lottery organizations publicize winners of big jackpots and use slogans that emphasize the pleasures of playing and winning (see Michael, 1993). Casinos design their architecture to make customers feel as though they are visiting a fantastic, but legitimate world (along the lines of Disneyland); rooms, lighting, sound, and the array of game areas are meant to create feelings of welcome, excitement, comfort, and luxury (Skea, 1995; Kranes, 1995). Research on working memory and the consequences of cognitive load suggest that gambling situations with many distractions cause changes in how people make decisions and judgments. Generally, this research shows that multiple conflicting stimuli, multiple calls on attention, and noisy environments cause increases in cognitive load (effort of processing information and using working memory), which in turn cause people to process information using guesses and stereotypes and to respond more automatically to stimuli (Gopher and Donchin, 1986). Casinos, racetracks, and increasingly lines at multistate lottery venues feature crowds and crowd suspense and a celebratory atmosphere. Casinos have large rooms, lines of noisy machines, the sound of coins spilling into trays, flashing neon lights, multimedia presentations, loud announcements over the sound system, and the smells of food, perfume, and alcohol (Skea, 1995; Hirsch, 1995). This barrage of distracting stimuli is likely to induce high levels of cognitive load, which in turn could reduce introspection, increase the use of guessing in gambles, and more generally encourage thoughtless gambling. Legalization and Social Influence Legalization is assumed to dramatically change the organization and technology of gambling as new businesses enter the mar-
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--> cially of home gambling and the Internet, are highly uncertain. Putnam (1995) and Condry (1993) have pointed to the television as a technology that has caused Americans to withdraw from personal and civic relationships, to the detriment of the television watchers themselves and the community as a whole. However, even for the case of television, which has been around for years, we have only a weak causal chain, suggesting that television viewing reduces social involvement or activity which in turn reduces physical and psychological health. The chain for the case of gambling machines and home gambling is even weaker. Studies of the prevalence of pathological or problem gambling for different types of gambling do not generally control for extraneous factors, including survey questions, locale, and year in which the survey was done. Computer-based video machine gambling is new enough that it is not well represented even in the modest number of surveys that address the issue. Hence the impact of technology remains an important but open question. We do not know whether problem gamblers are more attracted to video or machine gambling than gamblers without problems, and we do not understand the mechanisms that account for the associations reported in the literature. Research is needed that allows us to better understand the link between use of gambling technologies and subsequent changes in gambling disorders. By conducting natural experiments and prospective studies, preferably with national samples, it would be possible to estimate the extent to which conclusions from correlational cross-sectional studies are valid or widespread and to determine some of their limiting conditions. By differentiating social and asocial types of gambling, and by employing careful measures such as time diaries and assessments of the size and type of social circles that gamblers maintain, researchers would be able to test several of the plausible mechanisms by which use of technology may change vulnerability to pathological gambling. Research on the organization and technology of gambling should be evaluated in the context of the sparse research on social and technological change more generally. Little empirical research exists even about the social effects of such important technologies as the television and the telephone. Laboratory studies on technology in gambling have tended to focus on the structure
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--> of gambles rather than gambling habits and social outcomes. These studies have led to important theories about the nature of betting, but their implications for technology and gambling problems have not been tested. Few if any gambling organizations would be willing to run public experiments on these issues, and even if they did, the link to pathological gambling would be difficult to trace. Field research on the organization and technology of gambling is rare, although there is a body of literature on the effects of legalization, most of which relies on cross-sectional surveys and self-reports of gambling behaviors. Since legalization is likely to change reporting along with the technology, markets, attitudes, and constraints of gambling, it is hard to draw conclusions about how a particular aspect of legalization is affecting people. One way to study the effects of new technology or organization in natural settings is through natural experiments; natural experiments elicit data to which time series analyses can be applied (see Lyons and Ghezzi, 1995). Another approach would be to conduct prospective, longitudinal studies of individuals. This approach has long been used in studies of health and disease (e.g., the Framingham heart study). However, it is possible that little is to be gained from a dedicated longitudinal prospective study of pathological gambling, since only a tiny percentage of the sample is likely to develop a gambling problem. Still, it would seem feasible and worthwhile to add measures of gambling and related leisure activities and outcomes (e.g., debts) to other prospective longitudinal studies in health or mental health. Doing so would not only add valuable information about gambling over time, but would also provide important information about baseline date and comorbidity. Even prospective studies can pose threats to valid causal claims. First, statistical controls may not adequately equate groups (e.g., gamblers and nongamblers) on other factors. Preexisting factors (ranging from cohort characteristics to biological stress) could cause people to be predisposed to gambling and as well to be attracted to a particular type of game or gambling setting. Second, unmeasured variables that change over time may induce both gambling of certain types and changes in outcomes such as problem gambling. Measuring gambling in relationship
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--> to how people spend their time and money more generally might be useful in understanding other factors that may be related to both normal, social gambling and problem gambling. Detailed studies using time and expenditure measures; measures of social network size, social activities, and stress; psychological measures of social support and physical and mental health could contribute to understanding of the relationships between problem gambling, how people use technology, time, and money, social interaction, and the size of social networks. References Anderson A., and H. Van Der Heijden 1998 Media, culture, and the environment. Environmental Politics 7(4):188-189. Barrett, L.F., and J.A. Russell 1998 Independence and bipolarity in the structure of current affect. Journal of Personality and Social Psychology 74(4):967-984. Bureau of the Census 1997 Estimates for recorded music and video games include persons 12 and older. Pp. 565-566 in Statistical Abstract of the United States. Washington, DC: U.S. Department of Commerce. Chantal, Y., R.J. Vallerand, and E.F. Vallieres 1995 Motivation and gambling involvement. Journal of Social Psychology 135(6):755-763. Chau, A.W., and J.G. Phillips 1995 Effects of perceived control upon wagering and attributions in computer blackjack. Journal of General Psychology 122. Chavetz, H., and C. Simon 1967 Play the Devil: A History of Gambling in the United States. New York: C.N. Potter. Cialdini, R.B. 1993 Influence: Science and Practice, 3rd ed. New York: Harper Collins College Publishers. Clotfelter, C.T., and P.J. Cook 1989 Selling Hope: State Lotteries in America. Cambridge, MA: Harvard University Press. Coate, D., and G. Ross 1974 The effect of off-track betting in New York City on revenues to the city and state governments. National Tax Journal 27:63-69. Cohen, J., L.E. Boyle, and A.P.W. Shubsachs 1969 Rouge et noir: Influence of previous play on choice of binary event outcome and size of stake in a gambling situation. Acta Psychologica 31:340-352.
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--> Cohen, J., and E.I. Chesnick 1970 The doctrine of psychological chances. British Journal of Psychology 61(3):323-334. Cohen, S., and T.A. Wills 1985 Stress, social support, and the buffering hypothesis. Psychological Bulletin 98(2):310-357. Cole, W.R., and R. Hastie 1978 The effects of lottery game structure and format on subjective probability and attractiveness of gambles. Personality and Social Psychology Bulletin 4(4):608-611. Condry, J. 1993 Thief of time, unfaithful servant: Television and the American child. Daedalus 122(1):249-278. Cook, C.T., and P.J. Clotfelter 1993 The peculiar scale economies of lotto. American Economic Review 83(3):633-634. Cox, S., H.R. Lesieur, R.J. Rosenthal, and R.A. Volberg 1997 Problem and Pathological Gambling in America: The National Picture. Columbia, MD: National Council on Problem Gambling. Dandurand, L. 1990 Market niche analysis in the casino gaming industry. Journal of Gambling Studies 6:73-85. Dixey, R. 1987 It's a great feeling when you win: Women and bingo. Leisure Studies 6(2):199-214. Downes, D.M., B. Davies, and M.E. David 1976 Gambling, Work and Leisure: A Study Across Three Areas. London: Routledge and Kegan . Eadington, W.R. 1982 Studies in the Business of Gambling. Reno: Bureau of Business and Economic Research, University of Nevada. Emerson, M.O., and J.C. Laundergan 1996 Gambling and problem gambling among adult Minnesotans: Changes 1990 to 1994. Journal of Gambling Studies 12(3):291-304. Fabian, A. 1990 Card Sharps, Dream Books, and Bucket Shops: Gambling in 19th-Century America. Ithaca, NY: Cornell University Press. Fabian, T. 1995 Pathological gambling: A comparison of gambling at German-style slot machines and "classical" gambling. Journal of Gambling Studies 11(3):249-263. Fischhoff, B. 1975 Hindsight = foresight: The effect of outcome knowledge on judgment under uncertainty. Journal of Experimental Psychology, Human Perception & Performance 1:288-299.
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--> Fischhoff, B., S. Lichtenstein, P. Slovic, S.L. Derby, and R. Keeney 1981 Acceptable Risk. New York: Cambridge University Press. Fisher, S.E. 1994 Identifying video game addiction in children and adolescents. Addictive Behaviors 19(5):545-553. Fisher, S.E., and M. Griffiths 1995 Current trends in slot machine gambling: Research and policy issues. Special Issue: Slot Machine Gambling. Journal of Gambling Studies 11(3):239-247. Gilovich, T. 1983 Biased evaluation and persistence in gambling. Journal of Personality and Social Psychology 44:1110-1126. Gilovich, T., R. Vallone, and A. Tversky 1985 The hot hand in basketball: On the misperception of random sequences. Cognitive Psychology 17:295-314. Gopher, D., and E. Donchin 1986 Workload--An examination of the concept. Pp. 41-48 in Handbook of Perception and Human Performance, K.R. Boff, L. Kaufman, and J.P. Thomas, eds. New York: John Wiley. Griffith, R.M. 1949 Odds adjustment by American horse-race bettors. American Journal of Psychology 62:290-294. Griffiths, M.D. 1990 The acquisition, development, and maintenance of fruit machine gambling in adolescents. Journal of Gambling Studies 6(3):193-204. 1993 Fruit machine gambling: The importance of structural characteristics. Journal of Gambling Studies 9:133-152. 1994 The role of cognitive bias and skill in fruit machine gambling. British Journal of Psychology 85:351-369. 1995 Technological addictions. Clinical Psychology Forum 76:14-19. 1998 Gambling Technologies: Lessons from Scholarly Literature and Prospects for Pathological Gambling. Presentation to the National Research Council Committee on the Social and Economic Impact of Pathological Gambling, September 2. Nottingham Trent University, Nottingham, Australia. Gupta, R., and J.L. Derevensky 1996 The relationship between gambling and video-game playing behavior in children and adolescents. Journal of Gambling Studies 12(4):375-394. Harris, J.R., and R.M. Liebert 1991 The Child: A Contemporary View of Development, 3rd ed. Englewood Cliffs, NJ: Prentice-Hall, Inc. Henslin, J.M. 1967 Craps and magic. American Journal of Sociology 73:316-330. Herrnstein, R. 1990 Behavior, reinforcement and utility. American Psychologist (45):356.
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