Simultaneously Observing Concurrently- Available

Simultaneously Observing ConcurrentlyAvailable Schedules as a Means to Study the Near Miss Event in Simulated Slot Machine Gambling Benjamin N. Witts, Patrick M. Ghezzi & Morgan Manson

The Psychological Record ISSN 0033-2933 Volume 65 Number 1 Psychol Rec (2015) 65:115-129 DOI 10.1007/s40732-014-0095-y

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Author's personal copy Psychol Rec (2015) 65:115–129 DOI 10.1007/s40732-014-0095-y

ORIGINAL ARTICLE

Simultaneously Observing Concurrently-Available Schedules as a Means to Study the Near Miss Event in Simulated Slot Machine Gambling Benjamin N. Witts & Patrick M. Ghezzi & Morgan Manson

Published online: 24 September 2014 # Association for Behavior Analysis International 2014

Abstract Traditionally, near-miss events in games of skill provide feedback to an individual regarding his or her performance. However, in games of chance, like slot machine gambling, the use fails to carry over. A near miss in slot machine gambling may still be endorsed when most of the symbols falling on a payline match, though technically this arrangement provides no real measure of skill or progress. To date, attempts to study the near miss in slot machine gambling have used resistance to extinction and preference assessment preparations, both of which unsuccessfully capture any putative reinforcement properties. The current investigation introduces a new methodology to assess putative conditioned reinforcement properties of stimuli correlated with the near miss in simulated slot machine gambling by incorporating the observing response with concurrently available schedules, termed simultaneous observing. Successful tests of the methodology regarding schedule-correlated stimuli in relation to win rates demonstrate its potential use, and failure to identify a nearmiss event as producing reinforcing effects for schedulecorrelated stimuli adds credibility to its ability to discriminate between functions.

Keywords Gambling . Conditioned reinforcement . Observing response . Humans Portions of this manuscript were presented at the Gambling Special Interest Group’s 2013 Conference in Reno, NV, in April, 2013. B. N. Witts : P. M. Ghezzi : M. Manson Department of Psychology, University of Nevada, Reno, Reno, NV, USA Present Address: B. N. Witts (*) Department of Community Psychology, Counseling, and Family Therapy, St. Cloud State University, 720 4th Ave, St. Cloud, MN 56301, USA e-mail: [email protected]

The interest in gambling research is growing among behavior analysts (Witts 2013). One area of study within gambling that has garnered a great deal of attention is the near-miss event (cf. Harrigan 2007, 2008), which has led to much speculation regarding its role in problem gambling. The near-miss event in games of chance has been documented across several game types, including blackjack (Dixon et al. 2009a), roulette (Dixon 2010; Sundali et al. 2012), and slot machines (e.g., Ghezzi et al. 2006). In slot machine gambling, a near-miss event occurs when most of the symbols on a series of slot machine reels match (e.g., Ghezzi et al. 2006; Skinner 1953). For example, in a three-reel slot machine, an individual may spin the reels and see matching jackpot symbols on the first and second reel, with the third reel displaying the same symbol either above or below the payline.1 To the player, this may look as though they have almost won (see Dixon et al. 2009b), which is also supported in neuro-behavioral translational research (see Habib and Dixon 2010). The reel alignment is randomly determined, although near-miss events may be artificially inflated by providing more physical (e.g., Mead 1983) or virtual (Harrigan 2007, 2008; Jensen 2010) reel stops for high-win symbols on the first and second reels on a three-reel machine (see Harrigan 2009, for an analysis of clustering). Skinner (1953, 1980) hypothesized that the near-miss event in slot machine gambling may be a relevant factor contributing to sustained play despite a preference to stop (see also Reid 1986). Research has supported this idea, showing that slot machine gamblers may endorse an element of skill to their play (e.g., Dixon and Schreiber 2004; Griffiths 1994). However, there has been a paucity of research conducted on the function that the near miss may play in slot machine gambling, and what does exist is generally not in agreement. 1 Modern slot machines may have over 100 paylines, though the traditional three matching symbols may still be present in the form of scatter symbol wins to initiate bonus games.

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The question of what role the near-miss event plays in slot machine gambling, then, is a subject that warrants further elaboration. Said simply, the effect in the “near-miss effect” has yet to be empirically identified. The Oxford English Dictionary defines the “near miss” as “(a) a shot that only just misses a target; also in extended use; (b) a situation in which a collision is narrowly avoided” (“Near Miss” 2012). With respect to definition (a), a near miss may serve as feedback in that the miss was spatially near the target. With respect to skill-based endeavors, then, the definition holds. Take, for example, a basketball player working on improving his or her free-throw shots. Hitting the backboard and subsequently the rim is closer to a successful shot than is hitting the backboard and having the ball pass straight to the floor. Although the shot was missed, it was near the target (thus, a near miss). This is contrasted to games of chance, in which events are independent of one another. In games of chance, the endorsement of a near miss is thus false, although the effect on subsequent responding may be similar to what occurs in games of skill (this is the realm of superstitious behavior; e.g., Skinner 1948). It is possible, then, that the near miss event may be functioning as a type of conditioned reinforcement. As mentioned, outcomes related to the putative conditioned reinforcement properties of the near miss event have been varied, along with their particular methodological approaches. These various methods, among others, are explored here prior to analyzing current research.

The Experimental Analysis of Conditioned Reinforcement Reinforcement can be divided into two categories: unconditioned and conditioned. The former requires no learning history to acquire its function whereas the latter does. Skinner (1953) proposed that the near-miss event in three-reeled slot machines may be a type of conditioned reinforcement in that “the device eventually makes two bars plus any other figure strongly reinforcing” (p. 397). The temporal nature of the reels stopping (e.g., Skinner 1980) may be similar to the conditioned reinforcement effects of the final link in a chain schedule (i.e., the delay-reduction hypothesis; Case and Fantino 1981; Fantino 1969, 2008; Fantino and Moore 1980; Fantino et al. 1993; cf. Reid 1986, for an alternative analysis of near misses). However, temporal proximity is not enough to warrant claims of conditioned reinforcement properties. As a potential type of conditioned reinforcement, behavior analysts are uniquely suited to explore the function of the near-miss event in slot machine gambling. However, there is a current lack of research on the topic, despite proposed methods for its inclusion as an area of focus for treatment (e.g., Nastally and Dixon 2012). Several tests have been made available that allow researchers to more rigorously study the stimulus

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characteristics purported to serve as conditioned reinforcement. These methods include the new response method, preference assessments, resistance to extinction, the changeover delay procedure, choice procedures, and the observing response procedure. Each method will be explored for its potential applicability to the near-miss event in slot machine gambling. To date, behavior analysts have focused primarily on two methods to test for conditioned reinforcement in the near miss: preference and resistance to extinction. Additional preparations have been used that suggest a potential reinforcing function for the near miss, such as measuring interresponse times compared to wins (Dillen and Dixon 2008), nomination to continue playing in the presence of near misses despite tacting them as aversive (Clark et al. 2009, 2012), and elevated biological reactions under near-miss presentations (e.g., Clark et al. 2012). The New Response Method The new response method requires that some new response be acquired and maintained by the putative conditioned reinforcement alone (Williams 1994). With slot machines, the apparatus itself sets limits on the opportunity to employ this technique. Specifically, the typical slot machine comes equipped with a standard array of operandi. Any additional button, lever, plunger, or treadle would likely be conspicuous to the research participant. Furthermore, the new response method is not able to parse out if the response was the result of maintenance (i.e., reinforcement) or of the stimulus evoking more responses (see, e.g., Fantino 2008; Fantino and Romanowich 2007). Preference Assessments Within gambling research, preference (see Hendry 1969) has been used as a means to study payback rates and percentages (e.g., Dixon et al. 2006; Haw 2008; Weatherly et al. 2009). Less attention has been paid to the preferences of near-miss densities in slot machine gambling research, although two known studies exist. MacLin et al. (2007) created three concurrently available simulated slot machines that produced a winning outcome on 20 % of trials. Machines differed in that the remaining trials consisted of either 15 %, 30 %, or 45 % near-miss outcomes, with the others being full losses. Eighteen participants played 100 forced trials and additional extinction trials in which the wins were removed but near misses were retained. Overall results showed a nonsignificant trend toward the 45 % near-miss density alternative. Győző and Körmendi (2012) had 159 participants play 50 trials on each of four sequentially presented simulated slot machines (200 trials total) that produced equivalent wins while varying near-miss densities (15 %, 30 %, 0 %, and 45 %, respectively). Starting with the second round, a 1minute break was introduced where the participant was asked

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if he or she preferred to replay the current slot machine or the previous one (i.e., 30 % or 15 % machine). After the third round, the current machine (0 %) was compared to the selected machine from the first assessment, and then, finally, the selected machine on this second assessment against the 45 % machine. Results indicated that although participants were unable to identify which of the four machines produced the most near misses, they did tend to select the 30 % machine as the one most wanted to repeat, with the 45 % being selected least. Further exploration is necessary, as preference is no guarantee of any reinforcing value. This claim is echoed in the applied literature (e.g., DeLeon et al. 2013) with a distinction being drawn between preference and reinforcement assessments (cf. Cooper et al. 2007; Piazza et al. 1996). Putative reinforcement in a reinforcement assessment must generate or maintain more responding (Cooper et al. 2007) and/or show greater resistance to extinction (DeLeon et al. 2013). Resistance to Extinction Resistance to extinction (e.g., Hendry 1969; Williams 1994), sometimes referred to as persistence in the gambling literature, is an experimental arrangement in which some response is met with a schedule of (putative) conditioned and unconditioned reinforcement. In gambling studies, the unconditioned reinforcement is replaced with generalized conditioned reinforcement, such as money or its equivalent (e.g., points, tokens). Upon completion of some response or time requirement, the experimental conditions switch to one of two alternatives: an extinction condition, or a condition in which only the unconditioned or generalized conditioned reinforcement is removed. Differences between groups in each condition are used to determine whether the stimulus under study is considered to be conditioned reinforcement or not. Specifically, if responding persists less so under full extinction conditions, then an argument of conditioned reinforcement may be had. Methodological variations are seen through this resistance to extinction literature in slot machine gambling, with few keeping to the methods outlined above (e.g., Côté et al. 2003; see also Table 1). Research using resistance to extinction, however, may be problematic. Consider that during extinction

any reinforcing characteristics of the conditioned reinforcement may be weakened through repeated exposure (Hendry 1969) and that the differences between extinction conditions and prior conditions may be great (Williams 1994). Additional concerns plague human experimental work on resistance to extinction in that study termination may be due to factors other than the experimental parameters (e.g., restroom needs, boredom, access to activities with greater reinforcement; see also Shull and Lawrence 1998). For these reasons, resistance to extinction may not produce valid results. Changeover Delay A changeover delay (COD) tests for reinforcement through punishment of alternations between two or more schedules, which serves to prevent matching to reinforcement schedules and the accidental reinforcement of switching (see Shahan and Lattal 1998). The COD consists of one response on two or more signaled schedules of reinforcement, with an additional response to some other operandum that serves to change the current schedule in effect (i.e., a changeover response). The changeover response will enact a delay after the first response on the changeover operandum, the last response on the current schedule, or the first response on the new schedule. Within gambling research, the inclusion of the COD is feasible, although it may require adequate computer programming skills or finances to hire a programmer. For example, one could arrange for two or more simulated slot machines to be made available individually. After training on each machine, a changeover button could be presented that serves to switch between machines. Similar to Madden and Perone (1999), a simulated slot machine may present a “loading” screen, in which a progress bar is displayed that fills based on a time schedule, topographically similar to what occurs during a streaming video on the Internet. As with resistance to extinction research, the COD procedure may be subject to competition from other reinforcement when used with human participants. Consider that any COD enacted may be aversive simply because it prolongs participation. If, for example, a participant is required to spin a simulated slot machine for 100 rounds, any procedure that

Table 1 Summary of persistence studies on the near miss and their corresponding near-miss density that produced the best outcomes Authors

Forced Trials

Sample Reels Win Rate

EXT* Near-Miss Densities

Strickland and Grote 1967 Kassinove and Schare 2001 Côté et al. 2003 Ghezzi et al. 2006 Ghezzi et al. 2006 Ghezzi et al. 2006 Daugherty and MacLin 2007

100 50 48 25, 50, 75, 100 100 50 50

44 180 59 320 120 240 132

A D C, D A A A D

3 4 3 3 3 3 3

10 % 10 % 18.75 % (0 % control) 40 % 40 % 10 % 30 %

*A = no extinction; B = win extinction; C = near-miss extinction; D = full extinction.

5% 15 % 0% 0% 0% 0% 0%

25 30 25 33 33 33 15

% % % % % % %

Best NM Density

25 % 30 % 25 % 66 % 100 % 66 % 66 % 100 % None 66 % 100 % Mixed 30 % 45 % 45 % 45 %

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delays completion of the requirement may alter its use (i.e., avoidance of the changeover response). Choice Procedures Choice procedures involve concurrently available alternative schedules of reinforcement, often with exclusive entry into a terminal link being achieved only after some schedule requirement is completed on one of the initial links. In terms of the near-miss event, it is possible to arrange for choice procedures. For instance, two concurrently available slot machines could have schedules of wins superimposed on the chain schedules, or solely in the terminal links. As a study of the near miss as conditioned reinforcement, these too would need to be included as a sort of conjoint schedule alongside the schedule of wins, ensuring that the two do not overlap (i.e., one cannot win on a near-miss trial). That one must include and vary the rate of near misses raises concerns about the effects that conditioned reinforcement may have on choice. Although some researchers conclude that the rate of conditioned reinforcement affects choice (e.g., Shahan et al. 2006), others find contrary evidence (e.g., Fantino 2008). As this debate is yet resolved, researchers are at least cautioned to tread lightly in drawing conclusions about the near miss from such preparations. Observing Response Wyckoff (1952) introduced the observing response experimental arrangement and defined it as a response that produces discriminative stimuli involved with the reinforcement schedule(s), and which is distinct from the response that produces reinforcement. The hypothesis was that these discriminative stimuli could take on conditioned reinforcement properties, which could then be used to sustain observing. Typically, observing responses are made to some operandum that produces discriminative stimuli correlated with a single operandum that is on a mixed schedule of reinforcement. The observing response, then, alters the mixed schedule (i.e., no discriminative stimuli present) to a multiple schedule of reinforcement (i.e., discriminative stimuli present), at least momentarily. Arrangements such as this maintain observing so long as some of the stimuli produced are correlated with the presentation of reinforcement, even minimally (see Fantino and Silberberg 2010; Silberberg and Fantino 2010). In other words, observing is more likely to occur when some or all of the stimuli are correlated with S+, but not when they are correlated with S- (cf. Silberberg and Fantino 2010, for a potential exception). Relatively little is known about observing with respect to schedules of conditioned reinforcement, as much of the observing response literature incorporates unconditioned reinforcement. In one example, Shahan (2002) arranged for the self-administration of a 10 % ethanol solution to be produced on an RR25 schedule or not at all on an extinction condition with four rats. When the RR condition was in effect, a blinking

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house light and pulsating tone (both S+) were presented, and when extinction was in effect, a constant light and tone (both S-). After training, Shahan removed the S+ and S- stimuli and introduced a separate observing response lever. Observing was produced predictably under S+ conditions. Next, Shahan replaced the 10 % ethanol solution with a 2 % sucrose solution, while keeping all other variables equivalent. Thus, both RR25 and extinction conditions were, in essence, extinction conditions from 10 % ethanol solutions. Although observing during this phase was low, it was still higher than responses to the lever previously correlated with the ethanol solution delivery. In other words, stimuli correlated with drug administration was sufficient to maintain observing in the absence of the drug itself, lending credibility to the use of observing response procedures in the analysis of conditioned reinforcement. Given Shahan’s (2002) results, it seems logical that an observing response analysis of the putative conditioned reinforcement properties of the near miss in simulated slot machine gambling may be had. We propose the following arrangement, combining Shahan’s results to MacLin et al.’s (2007) concurrently available slot machine preparation, to begin a systematic investigation into the potential role that the near-miss event may play in sustaining gambling or producing, as others have theorized, patterns of problem gambling. The current analysis was conducted over two experiments. In Experiment 1, three concurrently available slot machines were made available that differed on background color and win rate. As winnings are arguably more likely to function as reinforcement when compared to other slot outcomes (e.g., near misses), win rate was selected to test the general methodology. Experiment 2 was contingent upon Experiment 1’s success and used the same general strategy, but replaced win rate with near-miss rate. The Simultaneous Observing Procedure The term simultaneous observing is proposed here to describe the general procedure, which is seen during the final phase of a three-phase procedure. During the first phase, participants were asked to play each of three machines individually, each of which was correlated with a particular color (i.e., red, blue, green). The second phase made all machines concurrently available, and the participants became familiar with the arrangement in which machines rotated positions after each trial while keeping their respective colors and schedules. This second phase set the occasion for the third phase, in which the program removed background colors and presented an observing response (i.e., “Show” button), which served to bring back the background colors. The second phase is akin to a preference assessment, with the third being more like a reinforcement assessment. Thus, consistency in machine selection between Phases 2 and 3, contingent upon observing

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response selection, would be indicative of reinforcement properties for the background colors. That is, the background color, as a discriminative stimulus, may have conditioned reinforcement properties in that it permits discriminated betting (i.e., response allocations). Table 2 outlines potential outcomes for this particular arrangement, based on the results of Phases 2 and 3. Explicitly, putative (conditioned) reinforcement conclusions for background color are derived from a combination of observing response executions, response allocations in Phase 2, and response allocations in Phase 3. Whereas response allocations in Phases 2 and 3 are not necessarily tests of conditioned reinforcement, inconsistent responding between phases may be indicative of some aspect of the arrangement other than machine-based schedules as maintaining the reinforcing properties of background colors. An additional arrangement was made in that half of participants were free to observe while the other half incurred a three-credit loss for observing, thus helping to analyze the degree to which any particular machine may be reinforcing.

General Method Participants and Setting Undergraduate students at a large university in the Western United States were recruited through the use of universitybased online recruitment software. Participant characteristics are shown in Table 3 and are divided by experiment and condition. No significant differences were found between ages or estimated average annual income (all ps>.05). Participants completed the study in either the University’s library’s study rooms, consisting of several chairs, a large conference table, and various electronic equipment (e.g., television), or in one of two small research rooms located in the basement of an off-

campus University building. The latter location consisted of two chairs, one or two desks, and a computer on each desk. Sessions lasted 20 to 40 minutes, depending upon experiment and phase. All participants signed an informed consent document, approved by the university’s IRB.

Apparatus A simulated slot machine was developed for this study, and its participant interface for Phase 3 (observing response phase) can be seen in Fig. 1. Upon completion of the study, data were coded for each feature thus described and exported as a .csv file for review in Microsoft Excel. Specifications for certain features are explored to allow for greater replication. Reel Strips Eight images of either a liberty bell (winning symbol) or a plum (losing symbol) were arranged on a 109× 179-pixel virtual-reel strip. Each reel consisted of (1) liberty bell, (2) plum, (3) plum, (4) plum, (5) plum, (6) liberty bell, (7) plum, and (8) plum. This arrangement was designed to permit multiple positions for a liberty bell above, on, or below the payline, and to allow for reels to stop such that no winning symbols are visible on a given reel. Reel start positions could be programmed to match the stop position of the previous spin or to have its reels at any position other than the stop positions. This latter feature was necessary to prevent participants from tracking a machine during Phase 3 (observing response phase), while machines rotated position without the aid of background colors to differentiate machines. Reel stop positions were programmable based on the eight stopping positions described above. By coding stop positions for each trial by each machine, individual variability due to differential outcomes could be better controlled for. In addition, each spin’s duration could be programmed in 1.25 second increments (e.g., a stopping time of “2” would result in

Table 2 Possible outcomes for any one parametric variation of an array of concurrently available schedules of putative (conditioned) reinforcers Category

Observing Response

Phase 2 Response Allocation

Phase 3 Response Allocation

Conclusion

A B C D

Yes Yes Yes Yes

Differentiated Differentiated Differentiated Undifferentiated

Differentiated (same as Phase 2) Differentiated (different from Phase 2) Undifferentiated Differentiated

E

Yes

Undifferentiated

Undifferentiated

F

No

Differentiated

G H

No No

Differentiated / Undifferentiated Differentiated Undifferentiated

Reinforcement Unknown / Possible satiation or schedule effect Unknown / Possible satiation or schedule effect Possible reinforcement – recheck methods and Phase 1 training length Not reinforcement OR Phase 1 was ineffective at differentiating responses Information regarding schedule location likely available to participant Not reinforcement at this cost/effort level Not reinforcement / Ineffective Phase 1

Undifferentiated Undifferentiated

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Table 3 Participant characteristics for Experiments 1 and 2 Experiment 1 Cond. 1

Experiment 2 Cond. 2

Pre-Experimental

Experimental Cond. 1

Cond. 2

Women Men Average Age Age Range Average Year in School Caucasian Hispanic/Latino Asian African-American Other Average SOGS

3 2 20.20 18-27 2.20 1 1 2 0 1 0.40

5 0 23.20 19-32 3.00 4 1 0 0 0 0.40

19 6 21.69 18-48 2.25 18 6 1 1 0 0.25

5 4 21.67 20-25 2.67 7 1 1 0 0 0.33

8 2 22.80 19-32 3.5 8 1 1 0 0 0.40

Average Annual Income (estimated) Income Range

$22,000 $10,000–$50,000

$38,000 $10,000–$75,000

$12,000 $10,000–$25,000

$17,500 $10,000–$50,000

$23,000 $10,000–$75,000

Note. One participant endorsed two ethnicities, and thus the totals are greater than 100 % of the participant possible.

2.50 seconds of reel spinning prior to stopping). Thus, reels on the left could be programmed to stop first. On losing non-nearmiss trials, reels were set to stop times of 2, 4, and 6. On nearmiss and winning trials, the stop times were set to 2, 4, and 8. Sound Effects Several studio-quality sound effects were purchased, with some recombined, for these experiments. Unaltered sounds were used for pressing the observing response button and reel spins during losing trials. During a winning or near-miss trial, the pitch of the reel spin sound was altered after the second reel stopped to give the effect of faster spinning reels and would spin for an additional 5 seconds before stopping on a matching symbol (win) or with a

Fig. 1 Sample simulated slot machine interface with three background colors from left to right; blue, green, and red

matching symbol landing above or below the payline (near miss). If the trial was a winning trial, winning sounds similar to those heard in a casino were combined and played. Visible and Hidden Features During the third phase of Experiments 1 and 2, the user would see the background colors disappear after each spin prior to the repositioning of the machines. Pressing the “Show” button (unavailable during Phase 1 and 2) would allow the background colors to appear for one spin. During the preexperimental phase of Experiment 2, an “Exit” button was made available after the forced trials that permitted participants to terminate the study after any spin.

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Procedure

Method

Participants first completed the South Oaks Gambling Screen (SOGS; Lesieur and Blume 1987), a 20-item self-report measure of past gambling behavior. The SOGS is a standard measurement tool for identifying nongamblers, probable gamblers, and pathological gamblers. A participant earning a score of 2 or above, indicative of probable-pathological gambling, was excluded. Next, participants completed a demographics questionnaire assessing age, gender, ethnicity, year in school, and parental annual income (see Table 3). Prior to interacting with the simulation, participants were read a script corresponding to their respective experiment and condition.2 After the slot machine simulation terminated, participants answered questions in an exit survey that assessed what they thought the study was about, if they had a strategy while playing, how they thought they performed compared to other players, and if and how often they play slot machines in casinos. As similarities existed between experiments, several simulation parameters will be discussed here for brevity. Each spin cost one credit and each win paid five credits. Participants were informed that the player who ended his or her session with the most credits earned would receive a $50 cash prize. This $50 cash prize was arranged to serve as a potential incentive to encourage optimized response allocation (Experiments 1 and 2) or to sustain play (Experiment 2, preexperimental; see Peterson and Weatherly 2011). In other words, the prize served as a means to establish credits earned through gambling as being reinforcing. In accordance with state laws3 and IRB regulations, one participant was selected from each condition, randomly, to receive the $50 prize. Near misses were defined as a liberty bell on the payline of Reels 1 and 2, with a liberty bell above or below the payline on Reel 3. A losing trial saw no liberty bells on Reels 1 or 2. The distribution of wins, losses, and near misses was produced with a random number generator in Microsoft Excel. Specifically, the number of events was predetermined, but their sequencing was randomized, thus reducing the possibility of potential experimenter biases while sequencing events (e.g., placing near misses prior to wins, creating an artificial reduction in delay to reinforcement post-near-miss event).

Ten participants (see Table 3) were divided between Condition 1 and Condition 2 and Configuration 1 and Configuration 2 (see Table 4). One additional individual was not permitted to participate due to a SOGS score that exceeded the cutoff score, and was awarded extra course credit for his or her effort. Participants were provided 50 credits with which to bet on simulated reel spins across three phases. During Phase 1, participants operated one of three nonconcurrently available slot machines from left to right for 30 trials (10 trials each; e.g., see Fig. 1). Each machine was identified by a dedicated background color and its particular winning outcome rate (i.e., 0 %, 33 %, or 67 %). Win rate, then, is not to be confused with payback percentage, which in this case would be 0 %, 167 %, and 333 %, respectively. While the participant was interacting with a single machine, the other two were made inoperable by disabling the spin button and rendering their background colors gray. After 10 consecutive trials, the next rightmost machine was made available while the other two became inoperable. Phase 1 was terminated when the rightmost machine completed its 10-spin requirement. Phase 2 started with all three machines concurrently available with which the participant could interact. However, with each completed trial (i.e., spin) the machines rotated positions in a random pattern. The patterning of machine positions was determined prior to the study, ensuring every participant had the same experience. Machine colors, not position, determined the win percentage. Said differently, if the Blue Machine was programmed to win on 67 % of trials, it would do so from any position. Phase 2 continued until the participant completed 30 spins, regardless of response allocation. Finally, in Phase 3, conditions from Phase 2 were replicated with two exceptions. First, prior to any spin and before any rearrangement of slot positions, the background colors for each machine were disabled (i.e., transparent backgrounds). Second, a “Show” button was made available that served to enable the background colors for one spin when pressed. Participants in Condition 1 had no cost associated with their

Experiment 1

Background Phase 1 Position Payback Percent Near Miss Density

Experiment 1 served as a test of the current method for examining the near-miss event by using an arguably more salient type of reinforcement—a win. 2

Full scripts can be obtained by contacting the primary author. 3 In the state in which the study was conducted, it is illegal to gamble with one’s own or someone else’s money, or for a cash prize, in an establishment without a gaming license. The procedure used disconnects the gambling outcome from the prize awarded.

Table 4 Summary of counterbalancing in Experiments 1 and 2

Background Phase 1 Position Payback Percent Near Miss Density

Configuration 1 (Exp 1: n=6; Exp 2: n=9) Blue Red Green Left Middle Right 0% 67 % 33 % 25 % 0% 50 % Configuration 2 (Exp 1: n=4; Exp 2: n=10) Blue Red Green Right Left Middle 67 % 33 % 0% 50 % 0% 25 %

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Show button, while those in Condition 2 were required to pay three credits for each Show button press. Under the best possible outcomes, a participant in Condition 2 who presses the Show button 30 times in Phase 3 in an effort to identify the 67 % machine would lose a total of 20 credits by the end of the phase. In addition, the starting positions of the reels were randomized with a random number generator coded in the software to prevent participants from tracking a machine based on final reel positions (e.g., a machine ends with three liberty bells can easily be tracked to its next position without the use of the observing response). Similar to Phase 2, Phase 3 terminated after 30 spins, regardless of response allocation and regardless of whether the participant selected the Show button.

Results Figure 2 displays the number of observing responses during Phase 3 as well as the distribution of responses to each machine during trials in which the participant engaged in the observing response. A planned one-tailed independent 100%

Percentage of responses allocated to each machine

Condition 1 Participant 1 Participant 2 Participant 3 Participant 4 Participant 5

50%

0% 100%

Condition 2

Participant 7 50%

0% Show

67%

33%

0%

Slot Machine Win Percent

Fig. 2 Percentage of Show button presses and response allocation to slot machines during trials in which the Show button was pressed for Conditions 1 and 2 during Experiment 1

samples t test (Gravetter and Wallnau 2008) was conducted between Conditions 1 and 2 with respect to the number of observing responses. There were significantly more observing responses made when there was no cost, t(8)=2.26, p.05) or 2 (p>.05). Data on machine preference in Phases 2 and 3 were ordinal in nature and thus subject to nonparametric analysis. Therefore, a Friedman test (Gravetter and Wallnau 2008) was conducted to evaluate preference between the machines as a nonparametric alternative to the more traditional analysis of variance test. The Friedman test compared the 67 % (Median=2.7), the 33 % (Median=1.9), and the 0 % win machine (Median=1.5) for Phase 2 participants. The test was significant; χr2 =6.95 (2, n=10), p.05, which is consistent with the results of 25 % of other resistant to extinction research on the near miss in simulated slot machine gambling (i.e., Ghezzi et al. 2006, Experiment 2; Whitton and Weatherly 2009). However, general trends in responding allowed the use of the Preexperimental Phase to set up parameters for the Experimental Phase in Experiment 2. Specifically, we selected the near miss densities that produced the most (25 %; M= 12.40, SD=7.93), least (0 %; M=1.20, SD=1.79), and median (falling between the 25 % and 0 % results; 50 %, M= 7.80, SD=7.43) number of trials played under the extinction condition. Experimental Phase The Experimental Phase consisted of a partial replication of Experiment 1, with win rates being replaced with near-miss rates. This allowed for the testing of the conditioned reinforcement properties of the background color as they relate to nearmiss productions. Method Nineteen participants completed the Experimental Phase of Experiment 2 (see Table 3). Two additional participants were excused due to high SOGS scores, and an additional third withdrew voluntarily prior to the completion of the experiment. These three participants were awarded extra course credit. The remaining participants completed three phases that were identical in presentation to those in Experiment 1 (e.g., three 10-trial interactions in Phase 1, 30 trials with rotating machine positions in Phase 2, and 30 trials with the opportunity to observe background stimuli in Phase 3). However, in Experiment 2’s Experimental Phase, all machines were programmed to win on 20 % of all trials. This means that machines only differed on two factors: background color and associated near-miss density (see Table 4 for counterbalancing). Participants were given 100 credits to gamble with. If, during Phase 3, the participant were to observe on every trial, an anticipated loss of 90 credits would ensue. Average Number of Trials in Extinction

Discussion

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15 10 5 0 0%

10% 25% 33% 50% Slot Machine Near Miss Density

Fig. 3 Average number of trials in extinction for each near-miss density in the Preexperimental Phase of Experiment 2

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Results Figure 4 provides a display of the number of observing responses made for those participants who engaged in observing, as well as the distribution of responses for trials in which the participant observed. A planned one-tailed independent samples t test found significant differences between Condition 1 and Condition 2 in terms of observations made, t(17)=2.308, p.05) or 2 (p>.05). A Friedman test was conducted to assess differences in preference between the 50 % (Median=2.0), 25 % (Median= 2.1), and 0 % (Median=1.9) machines in Phase 2. The results were not significant (p>.05), indicating no preference for any near miss density. A Friedman test was conducted to assess difference in preference between the 50 % (Median=1.9), 25 % (Median=2.1), and 0 % (Median=2.0) machines for all participants in Phase 3 who observed. The results were not significant (p>.05). Participant 12 Participant 14 Participant 19

Percentage of responses allocated to each machine

100%

Participant 13 Participant 16

Condition 1

50%

0%

Condition 2 100% Participant 20 Participant 26

50%

0% SHOW

50.00%

25.00%

0.00%

Slot Machine Near Miss Density Fig. 4 Percentage of Show button presses and response allocation in Experiment 2, Phase 2 to slot machines during trials in which the Show button was pressed for Conditions 1 and 2

A Friedman test was conducted to assess the difference in preference between the 50 % (Median=1.8), 25 % (Median= 2.1), and 0 % (Median=2.1) machines for all participants in Phase 3 who observed in the no-cost condition. The results were not significant (p>.05). Only two participants paid to observed in the three-credit cost condition, and as such no statistical analyses were conducted. Visual inspection of the data failed to reveal a preference (see Fig. 4). Finally, a Friedman test was conducted to assess the difference in preference between the 50 % (Median=1.9), 25 % (Median=2.1), and 0 % (Median=2.0) machines in Phase 3 when no observing response was made. The results were not significant (p>.05). Additional categorical analyses were conducted (see Table 2) for Experiment 2 (results outlined in Table 5). Three participants in Condition 1 met criteria for Category A, which is indicative of a potential conditioned reinforcement effect for background color. However, no two participants interacted with the same machine, suggesting that the reinforcing effect of background color was maintained by different properties of the apparatus (e.g., different near-miss densities) for each participant in this analysis. Specifically, Participant 13 interacted with the 25 % near-miss machine, Participant 16 with the 50 % machine, and Participant 12 selected the 0 % near-miss machine. The remaining six category-based outcomes suggested weak evidence for a conditioned reinforcement effect (Category E, n=2; Category G, n=3; Category H, n=1). Condition 2 category-based analyses yielded no evidence for a conditioned reinforcement effect. Specifically, one met criteria for Category E, four for Category G, and five for Category H. Discussion With respect to the current preparation, little evidence was found to support a consistent conditioned reinforcement effect for background color as it relates to the near-miss event in simulated slot machine gambling. It is possible that the lack of conditioned reinforcement effect was the result of the magnitude of reinforcement during a winning outcome. In other words, investing one credit to win five might not be enough to support preference for the near-miss densities, as evidenced by greater observing of background colors. However, Ghezzi et al. (2006) provided tentative data suggesting that magnitude may not play a vital role in this analysis. Unlike the statistical analyses, the category-based analyses yielded a potential elusive conditioned reinforcement effect when no cost was required. The potential elusiveness of the effect is based on two observations. First, 67 % of participants in Experiment 1, Condition 1 met criteria for Category A, whereas 33 % of participants in Experiment 2, Condition 1 did. Second, of the three participants in Experiment 2,

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Condition 1 who met Category A criteria, no two opted for the same machine when he or she observed. It could further be argued that Participant 12 exhibited patterns conducive to an avoidance response, working to play the machine that produced no near-miss events. In summary, even if there is a putative conditioned reinforcement effect for schedulecorrelated stimuli, the evidence presented here suggests that it may be idiosyncratic, which is masked by statistical analysis. More probable, then, is that background colors function as discriminative stimuli, and any conditioned reinforcement properties, as they relate to near miss densities, are minimal.

General Discussion Given the difficulties in studying putative conditioned reinforcement in slot machines, a simultaneous observing procedure was developed in an effort to better shed light on the near-miss event. Experiment 1 tested the general methodology by correlating schedule-related stimuli (i.e., background color) with an arguably more salient conditioned reinforcement—a win. Both statistical and categorical results supported the claim that background color may function as conditioned reinforcement in the presence of varying win percentages, particularly when there was no cost to observe machine characteristics. However, we must be clear that the low n may have influenced statistical results, and thus larger replications are needed. Experiment 2 extended the analysis by replacing win percentages with near-miss densities, derived from a preexperimental analysis. Results of this second experiment did not yield so robust of results as did Experiment 1, suggesting either no conditioned reinforcement effect (statistical analyses) or an elusive, idiosyncratic one if any at all (category-based analyses), especially when no cost for observing was enforced. These results, notably from Experiment 1, suggest that with some refinement the simultaneous observing procedure may be useful in studying (conditioned) reinforcement effects for events that are not so easily subjected to existing methods (cf. Williams 1994). Perhaps the most perplexing outcome from these studies was that the rate of observing under the zero cost condition was less than 100 %. Several reasons may exist for this outcome. First, participant guessing resultant from “trying to figure out the study” may have led some participants to omit the observing response. Second, the observing response may have been seen as an additional step that would result in a delay to study termination in a study they found uninteresting. Finally, the observing response may or may not have been correlated with differential outcomes. Said differently, if pressing the Show button was positively correlated with winning trials, then participants may be more motivated to continue using this feature, with the opposite outcome potentially

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related to extinction contingencies. One remedy to this is to use one machine at a time with a modification to the reels in which the last reel is hidden on trials, as was outlined in Ghezzi et al. (2006). Future studies should pay close attention to the relation between observing and winning in simulated slot machine research, as this may prove to be a valuable variable. Such an analysis is beyond the scope of this article, and will likely require specially designed parameters to capture any effect. As the near-miss event in slot machine gambling is not extensively studied in terms of conditioned reinforcement (e.g., Table 1), several post hoc analyses were conducted. An exit survey revealed that 72.24 % of participants had played slot machines, and that of these 85.71 % considered themselves inexperienced. However, further inspection of these data yielded no hypotheses worthy of investigation. Additionally, Peterson and Weatherly (2011) found that in video-poker simulations, participants engaged in more riskseeking behavior when they also reported larger incomes. No such relation was found in the current study with respect to number of observing responses (Phase 3), response allocations (Phase 2), or trials played under extinction conditions (Preexperimental Phase). However, larger sample sizes or alternative samples may provide different outcomes, as most reported incomes below $10,000 (51.58 %). As the near-miss effect, if it indeed exists, is likely elusive and the current methodologies are novel, future investigations in both are warranted before any claims can be drawn. As such, a brief exploration of both the near-miss event and the simultaneous observing method are presented. The Near-Miss Event The outcomes of the current experiments argue against a conditioned reinforcement effect for the near-miss event in simulated slot machine gambling as the near miss event failed to consistently sustain observing of schedule-correlated stimuli (i.e., background colors). Prior to any definitive claims, however, several factors will need to be addressed. First, participants in Experiment 1 tended to complete Phase 2 with nearly twice the number of starting credits (M=106.00, SD= 17.13). Witts et al. (2011) found evidence that potential riskaversive patterns may emerge as the result of winning more than chance. With respect to Phase 3, observing, which for some cost three credits, may have been avoided as any loss of credits may have been viewed as adding to the gamble, thus making the act riskier. The simultaneous observing procedure would thus benefit from extensions that incorporate winning, losing, and break-even outcomes prior to the opportunity to observe. Furthermore, the near-miss densities selected may have influenced the results. Consider that in the Preexperimental Phase of Experiment 2 greater resistance to extinction was

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achieved for the 25 % near-miss density machine, yet in the Experimental Phase allocations were given more predominantly to the 50 % density machine. It may be the case that the 25 % machine was responded to differently because it was in the presence of a 0 % and 50 % machine, which may have been different had there been a 0 % and a 100 % machine instead (or any other combination for that matter) as contrast may have been a factor (see DeLeon et al. 2013). Refinement may be had through parametric analyses, which are easily executed with the current methods. A potential confound may have existed in the temporal proximity between near-miss presentations and wins. While all outcomes were decided with a random number generator and held constant between experiments and conditions, some patterning may be more active in the development of conditioned reinforcement properties (cf. delay-reduction hypothesis). Similarly, near-misses followed by several losses may have the opposite effect. The effect that various configurations of near-miss presentations and wins may have is indeed a topic of sizeable interest. Consider that the near-miss itself might function as conditioned reinforcement, a discriminative stimulus for alternative wagering (e.g., bet max credits when having bet minimum credits), or as a setting factor (e.g., motivating operation) that serves to alter the influence of a subsequent win. It is possible that with particular arrangements any one of these roles may emerge, and change, in relation to the various configurations. What is, perhaps, more intriguing is the possibility that the near-miss event may already have such a role—be it any of the above-mentioned, or others—without explicit training during the research session. In fact, such an assumption was made when exploring the near miss event in the current investigations. As Ghezzi et al. (2006) noted, near-miss densities may be secondary to their topography in terms of conditioned reinforcement. The current methods, again, may be important in helping to discern the validity of this assertion. Once identified, if at all, variations in densities for different topographies under simultaneous observation arrangement would prove enlightening. Simultaneous Observing This study provided preliminary support for the use of the simultaneous observing procedure for studying conditioned reinforcement effects. It is likely that similar outcomes would be seen for unconditioned reinforcement as well. One of the more promising outcomes from these experiments was the fact that subsequent Wilcoxon tests used an adjusted alpha, which was determined a priori and is not considered a necessary adjustment for these data. However, we required a more stringent alpha, as the methodology is novel and is thus potentially prone to Type I errors. As the results in Experiment 1 were significant, future research may be able

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to relax the alpha levels. While statistical analyses are possible with the procedure, categorical outcomes may better capture individual patterns of responding. Table 2 outlines a suggested scheme for the two-phase analysis (plus training phase) used in these experiments. Elaborated designs with more phases would permit even greater control, though more complicated categorizations would also be necessary. Thus far, four variables are identified as being readily manipulated in the simultaneous observing procedure. First, one can manipulate the number of concurrently available schedules. The current experiments used three, though more could be added. Consider, though, that with each new schedule diminishing returns on discriminability of responding are anticipated, which may result in heightened false negative rates. Stimuli discriminative for punishment or extinction, or having each schedule delivering its own type of reinforcement, (e.g., praise, tangibles, edibles) may serve to enhance contrast between stimuli. The second identified variable relates to the reinforcement schedule correlated with each stimulus. By altering schedules of reinforcement, punishment, and extinction, one can create a multitude of contextual conditions under which to explore the potentially varying degrees of reinforcement for a given schedule. Consider that the contextual change from the Preexperimental to Experimental phases for Experiment 2 may account for a shift in participant responding (25 % vs. 50 %, respectively). This is similar to saying, “I enjoy Stimulus A, but not when I have alternative access to Stimulus B.” The third variable is the cost or effort required to complete an observing response. In the current study, observing declined as a result of the associated cost. Parametric analyses of within-subject responding may be used to identify an indifference point at which observing ceases to occur. Thus, the individual value, so to speak, of putative reinforcement could be identified. Additional preparations could look to replace cost with effort, which may be more amenable to operandi other than slot machines. Finally, reinforcement and punishment magnitude can be manipulated. For instance, the current study used a five-credit win for a one-credit investment. Results may have been different given a higher credit win. The incorporation of punishment is interesting in its own right, as an individual may observe in an effort to avoid an outcome rather than pursue one, as was hinted at with the participant in Experiment 2 who observed and operated the 0 % machine in Phase 3. Although the current results argue for a weak, some might argue nonexistent, conditioned reinforcement effect for stimuli correlated with the different near-miss densities in simulated slot machine gambling, manipulation of these four variables may help to reveal any effect should one exist. Currently, this study is the first to argue adamantly against a putative conditioned reinforcement effect for the near miss,

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though parametric variations will be necessary before any definitive conclusion can be reached. For the time being, however, researchers and policy makers may be wise to proceed cautiously when discussing the impact of the near-miss event.

Acknowledgements The authors would like to thank Cleborne Maddux for his invaluable assistance with the statistical tests. We are indebted to the comments offered by the reviewers, and particularly to Reviewer 2’s interesting interpretation. This manuscript was completed as a doctoral dissertation by the first author

References Case, D. A., & Fantino, E. (1981). The delay-reduction hypotheses of conditioned reinforcement and punishment: observing behavior. Journal of the Experimental Analysis of Behavior, 35, 93–108. Clark, L., Lawrence, A. J., Astley-Jones, F., & Gray, N. (2009). Gambling near-misses enhance motivation to gamble and recruit win-related brain circuitry. Neuron, 61, 481–490. Clark, L., Crooks, B., Clarke, R., Aitken, M. R. F., & Dunn, B. D. (2012). Physiological responses to near-miss outcomes and personal control during simulated gambling. Journal of Gambling Studies, 28, 123– 137. Cooper, J. O., Heron, T. E., & Heward, W. L. (2007). Applied behavior analysis (2nd ed.). Upper Saddle River: Pearson. Côté, D., Caron, A., Aubert, J., Desrochers, V., & Ladouceur, R. (2003). Near wins prolong gambling on a video lottery terminal. Journal of Gambling Studies, 19, 433–438. Daugherty, D., & MacLin, O. H. (2007). Perceptions of luck: near win and near loss experiences. Analysis of Gambling Behavior, 1, 123– 132. DeLeon, I. G., Bullock, C. E., & Catania, A. C. (2013). Arranging reinforcement contingencies in applied stings: Fundamentals and implications of recent basic and applied research. In G. J. Madden et al. (Eds.), APA handbook of behavior Analysis: Vol. 2. Translating principles into practice. Washington, DC: American Psychological Association. Dillen, J., & Dixon, M. R. (2008). The impact of jackpot and near-miss magnitude on rate and subjective probability of slot machine gamblers. Analysis of Gambling Behavior, 2, 121–134. Dixon, M. R. (2010). The roulette near-miss effect. Analysis of Gambling Behavior, 4, 54–60. Dixon, M. R., & Schreiber, J. E. (2004). Near-miss effects on response latencies and win estimations of slot machine players. The Psychological Record, 54, 335–348. Dixon, M. R., MacLin, O. H., & Daugherty, D. (2006). An evaluation of response allocations to concurrently available slot machine simulations. Behavior Research Methods, 38, 232–236. Dixon, M. R., Nastally, B. L., Hahs, A. D., Homer-King, M., & Jackson, J. W. (2009a). Blackjack players demonstrate the near miss effect. Analysis of Gambling Behavior, 3, 56–61. Dixon, M. R., Nastally, B. L., Jackson, J. E., & Habib, R. (2009b). Altering the near-miss effect in slot machine gamblers. Journal of Applied Behavior Analysis, 42, 913–918. Fantino, E. (1969). Choice and rate of reinforcement. Journal of the Experimental Analysis of Behavior, 12, 723–730. Fantino, E. (2008). Choice, conditioned reinforcement, and the Prius Effect. The Behavior Analyst, 31, 95–111.

Psychol Rec (2015) 65:115–129 Fantino, E., & Moore, J. (1980). Uncertainty reduction, conditioned reinforcement, and observing. Journal of the Experimental Analysis of Behavior, 33, 3–13. Fantino, E., & Romanowich, P. (2007). The effect of conditioned reinforcement rate on choice: a review. Journal of the Experimental Analysis of Behavior, 87, 409–421. Fantino, E., & Silberberg, A. (2010). Revisiting the role of bad news in maintaining human observing behavior. Journal of the Experimental Analysis of Behavior, 93, 157–170. Fantino, E., Preston, R. A., & Dunn, R. (1993). Delay reduction: current status. Journal of the Experimental Analysis of Behavior, 60, 159–169. Ghezzi, P. M., Wilson, G. R., & Porter, J. C. K. (2006). The near-miss effect in simulated slot machine play. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.), Gambling: Behavior theory, research, and application (pp. 155–170). Reno: Context Press. Gravetter, F. J., & Wallnau, L. B. (2008). Statistics for the behavioral sciences. Belmont: Wadsworth. Griffiths, M. (1994). The role of cognitive bias and skill in fruit machine gambling. British Journal of Psychology, 85, 351–369. Győző, K., & Körmendi, A. (2012). Can we perceive near miss? An empirical study. Journal of Gambling Studies, 28, 105–111. Habib, R., & Dixon, M. R. (2010). Neurobehavioral evidence for the “near-miss” effect in pathological gamblers. Journal of the Experimental Analysis of Behavior, 93, 313–328. Harrigan, K. A. (2007). Slot machine structural characteristics: distorted player views of payback percentages. Journal of Gambling Issues, 20, 215–234. Harrigan, K. A. (2008). Slot machine structural characteristics: creating near misses using high award symbol ratios. International Journal of Mental Health, 6, 353–368. Harrigan, K. A. (2009). Slot machines: pursuing responsible gaming practices for virtual reels and near misses. International Journal of Mental Health Addiction, 7, 68–83. Haw, J. (2008). The relationship between reinforcement and gaming machine choice. Journal of Gambling Studies, 24, 55–61. Hendry, D. P. (1969). Introduction. In D. P. Hendry (Ed.), Conditioned reinforcement. Homewood: The Dorsey Press. Jensen, M. (2010). The big book of slots and video poker (2nd ed.). Las Vegas: Cardoza Publishing. Kassinove, J. I., & Schare, M. L. (2001). Effects of the “near miss” and the “big win” on persistence at slot machine gambling. Psychology of Addictive Behaviors, 15, 155–158. Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): a new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144, 1184–1188. MacLin, O. H., Dixon, M. R., Daugherty, D., & Small, S. L. (2007). Using a computer simulation of three slot machines to investigate a gambler’s preference among varying densities of near-miss alternatives. Behavior Research Methods, 39, 237–241. Madden, G. J., & Perone, M. (1999). Human sensitivity to concurrent schedules of reinforcement: effects of observing schedule-correlated stimuli. Journal of the Experimental Analysis of Behavior, 71, 303–318. Mead, D. R. (1983). Handbook of slot machine reel strips. Las Vegas: Mead Publishing Company. Nastally, B. L., & Dixon, M. R. (2012). The effect of a brief acceptance and commitment therapy (ACT) intervention on the near miss effect in problem gamblers. The Psychological Record, 62, 677–690. Nastally, B. L., Dixon, M. R., & Jackson, J. W. (2009). The effect of stopping devices and win rate on preference in slot machine players. Analysis of Gambling Behavior, 3, 27–30. Near miss. (2012). In Oxford English Dictionary. Retrieved from http:// www.oed.com/view/Entry/125544?redirectedFrom=near+ miss#eid34963145 Peterson, J. M., & Weatherly, J. N. (2011). Comparing three strategies of motivating gambling behavior in the laboratory environment. Analysis of Gambling Behavior, 5, 28–34.

Author's personal copy Psychol Rec (2015) 65:115–129 Piazza, C. C., Fisher, W. W., Hagopian, L. P., Bowman, L. G., & Toole, L. (1996). Using a choice assessment to predict reinforcer effectiveness. Journal of Applied Behavior Analysis, 29, 1–9. Reid, R. L. (1986). The psychology of the near miss. Journal of Gambling Behavior, 2, 32–39. Shahan, T. A. (2002). The observing-response procedure: a novel method to study drug-associated conditioned reinforcement. Experimental and Clinical Psychopharmacology, 10, 3–9. Shahan, T. A., & Lattal, K. A. (1998). On the functions of the changeover delay. Journal of the Experimental Analysis of Behavior, 69, 141–160. Shahan, T. A., Podlesnik, C. A., & Jimenez-Gomez, C. (2006). Matching and conditioned reinforcement rate. Journal of the Experimental Analysis of Behavior, 85, 167–180. Shull, R. L., & Lawrence, P. S. (1998). Reinforcement: Schedule performance. In K. A. Lattal & M. Perone (Eds.), Handbook of research methods in human operant behavior (pp. 95–129). New York: Plenum Press. Silberberg, A., & Fantino, E. (2010). Observing responses: maintained by good news only? Behavioural Processes, 85, 80–82. Skinner, B. F. (1948). ‘Superstition’ in the pigeon. Journal of Experimental Psychology, 38, 168–172. Skinner, B. F. (1953). Science and human behavior. New York: Macmillan. Skinner, B. F. (1980). Notebooks. Englewood Cliffs: Prentice Hall.

129 Strickland, L. H., & Grote, F. W. (1967). Temporal presentation of winning symbols and slot-machine playing. Journal of Experimental Psychology, 74, 10–13. Sundali, J. A., Safford, A. H., & Croson, R. (2012). The impact of nearmiss events on betting behavior: an examination of casino rapid roulette play. Judgment and Decision Making, 7, 768–778. Weatherly, J. N., Thompson, B. J., Hodny, M., & Meier, E. (2009). Choice behavior of nonpathological women playing concurrently available slot machines: effect of changes in payback percentages. Journal of Applied Behavior Analysis, 42, 895–900. Whitton, M., & Weatherly, J. N. (2009). The effect of near-miss rate and card control when American Indians and non-Indians gamble in a laboratory situation: the influence of alcohol. American Indian and Alaska Native Mental Health Research, 16(2), 28–42. Williams, B. A. (1994). Conditioned reinforcement: experimental and theoretical issues. The Behavior Analyst, 17, 261–285. Witts, B. N. (2013). Cumulative frequencies of behavior analytic journal publications related to human research on gambling. Analysis of Gambling Behavior, 7, 59–65. Witts, B. N., Ghezzi, P. M., & Weatherly, J. N. (2011). Altering probability discounting in a gambling simulation. Analysis of Gambling Behavior, 5, 83–92. Wyckoff, L. B., Jr. (1952). The role of observing responses in discrimination learning: part I. Psychological Review, 59, 431–442.