Exploring the Relationship between Reward Sensitivity and Risky Decision Making
3.2 Study Two a: The Relationship between Reward Sensitivity and Risky Decision Making Decision Making
3.2.1 Method
3.2.1.1 Participants
A total of 120 participants (71 females) aged 18 – 25 years old (Mean age = 21.2 years SD = 1.86) completed the present study. As the study was not related to driving behaviour or experience at this point, no data regarding previous driving experience was obtained. Paid participants were recruited via the University of Plymouth paid participant pool and from advertisements around the University campus; and undergraduate psychology students also participated for course credit.
3.2.1.2 Materials
The Sensitivity to Punishment and Sensitivity to Rewards Questionnaire (SPSRQ) (Torrubia et al, 2001)
Participants completed the 48 yes-no response item questionnaire which incorporates two scales – sensitivity to punishment (24 items) and sensitivity to reward (24 items). This scale measures the behavioural expressions of Gray’s BIS/BAS by assessing a tendency to avoid punishment and frustrative non-reward and the tendency to approach or prefer rewarding situations.
Participants respond ‘yes’ or ‘no’ to each item, and their score is based on the total number of positive responses for each of the two subscales. A typical item for the Sensitivity to Reward scale (SR) is, “do you sometimes do things for quick gains?” An example of an item from the Sensitivity to Punishment scale (SP) is, “Generally, do you pay more attention to threats than to pleasant events?” See Appendix 3A for the full questionnaire.
The Iowa Gambling Task (Bechara et al, 1994)
Participants completed a computerized version of the Iowa Gambling Task (IGT, Bechara et al,1994) in which they had to select a card from four available decks varying in their amount of
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imaginary monetary reward and punishment. Rewards and punishments were the same as those described in Bechara et al. (1994). Participants were given an imaginary sum of $2000 and presented with four decks of cards. They were told to successively choose cards from the four decks to maximise their long-term outcome. Each time participants chose a card they received feedback on the reward and loss associated with that card, and their running tally. Participants were unaware that the reward and punishment outcomes were fixed, and each of the four decks contained a different payoff scheme. Decks A and B (known as ‘bad’ or ‘disadvantageous’
decks) offered high, immediate constant rewards but with even higher, unpredictable, occasional losses resulting in negative long-term outcomes. Decks C and D on the other hand were associated with lower, immediate constant rewards and were accompanied by even lower, unpredictable, occasional losses, thus resulting in positive long-term outcomes. Decks C and D were therefore known as ‘good’ or ‘advantageous’ decks (Bechara et al,1994). The decks also differed in the frequency of losses as whilst decks A and C yielded frequent losses, decks B and D yielded infrequent losses. Decks A and B caused participants to lose $250 on average during the course of ten trials, whereas decks C and D caused participants to win $250 on average over ten trials. Participants completed 100 trials and performance on the task was used as evidence of their sensitivity to punishment or rewards in terms of making decisions. See Appendix 3B for a screen shot from the IGT.
3.2.1.3 Procedure
Participants read the information sheet and instructions, after which they signed the consent form and returned it to the experimenter. Participants completed the set of measures on a laptop in their own time. The presentation order of the measures was the same for all participants and was as follows: demographic questions related to their date of birth, gender and education level, then the sensitivity to punishment and sensitivity to reward questionnaire. On completion of the questionnaire participants informed the experimenter who then set up the ‘Iowa Gambling Task’
on the laptop, whilst the participants read the standardised IGT instruction sheet. The experimenter made sure participants understood the aim of the game and how to play, and then
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participants completed 100 trials of the IGT in their own time. Once the trials were completed, participants received a debrief form, were given the opportunity to ask any questions about the study, and were thanked for their time. Participants taking part for course credit were allocated 1 point for their time; paid participants were awarded £4 for their time.
3.2.2 Results
3.2.2.1 Reliability of Measures
Reliability analyses were carried out on the sensitivity to reward and sensitivity to punishment measures to ensure they were reliable. The alpha scores were .75 and .83 respectively, which indicates good and very good reliability for both (Torrubia et al, 2001).
3.2.2.2 Analysis
In a study exploring the influence of reward sensitivity and punishment sensitivity on compulsive buying behaviour, Lawrence et al. (2014) rank ordered each of the responses and divided them in half, producing high and low groups of reward sensitivity and punishment sensitivity. A similar procedure was implemented in this study, whereby the mean scores for each of the measures was calculated, the data was rank ordered and then a median split divided the scores in half. The two halves were labelled as high and low [sensitivity to reward;
sensitivity to punishment]. The high sensitivity to reward group consisted of scores over 12.45, and the low sensitivity to reward group of scores less than 12.45. The high sensitivity to punishment group consisted of scores over 12.80 and the low sensitivity to punishment group of scores less than 12.80.
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Table 3.1 provides descriptive information on participants’ mean Deck B and Deck C choices on the IGT, separated by gender and organised by sensitivity to reward (HSR/ LSR) and sensitivity to punishment (HSP/ LSP). As can be seen males were more likely to score as highly sensitive to reward rather than low (29: 20); whereas females were more likely to score as being less sensitive to reward rather than high (41: 29). By contrast males were more likely to score as
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low in sensitivity to punishment rather than high (33: 16), but females were more likely to score as highly sensitive to punishment rather than low (43: 27).
The number of cards selected from deck B was examined in relation to reward sensitivity scores and the number of cards selected from deck C was examined in relation to participants’
sensitivity to punishment scores. It was expected that participants scoring high on reward sensitivity may have selected more cards from deck B because of the relatively infrequent number of losses occurring when compared to potential gains. Whilst this was a disadvantageous deck (with participants losing more money overall than they win) participants with a greater tolerance for risk may have chosen from this deck because of the high potential gains. Conversely people scoring high on sensitivity to punishment may have avoided deck C because losses occurred more frequently on this deck compared to the other advantageous deck, D. Table 3.1 shows that highly sensitive to reward males chose many more cards from Deck B than low sensitive to reward males, whereas reward sensitivity did not appear to affect the number of cards females chose from Deck B. Punishment sensitivity had a slight effect on males’ Deck C choices, with highly sensitive to punishment males choosing slightly fewer cards from Deck C than low sensitive to punishment males; however punishment sensitivity did not appear to have an effect on females’ Deck C choices, with high and low punishment sensitive females choosing the same number from this deck.
Table 3.1. Descriptive statistics for participants’ Deck B and Deck C choices, organised by their sensitivity to reward and sensitivity to punishment scores.
Males Females
Mean Number of Deck C choices 25 28 23 23
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Reward sensitivity and gender were found to influence the number of Deck B cards chosen.
High reward sensitive males chose more cards from risky Deck B than low reward sensitive males or any females. A 2x2 ANOVA revealed a significant interaction between gender and reward sensitivity on the number of deck B cards chosen, F(1, 115) = 11.81, p< .05; and a simple main effect of reward sensitivity F(1, 115) = 10.04, p< .05 but not gender F(1, 115) = .23, p> .05. As Figure 3.1 shows, the interaction appears to have occurred because males scoring high on reward sensitivity chose more cards from deck B than males scoring low on reward sensitivity. All females appeared to choose a similar number of deck B cards, whether they scored low or high on reward sensitivity.
Figure 3.1. Total number of cards chosen from Deck B over 100 trials of the IGT, by high versus low sensitivity to reward male and female participants.
Previous research has highlighted the importance of looking at the learning curve of participants’ deck choices throughout the 100 trials of the IGT (e.g. Brogan, Hevey & Pignatti,
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2010). In this study, the authors examined the total number of cards chosen from each deck for every ‘block’ of 20 trials. This provided additional information about participants’ decision making patterns, and indicated where certain decks had been learnt to be avoided, and others chosen more frequently. For example a participant may have chosen lots of cards from deck B at the beginning of the task, but after a few blocks of trials learnt that this deck was associated with long-term negative outcomes and stopped choosing from it. If the total number of deck B cards chosen was the only measure used to identify risky decision making, important information relating to the learning curve experienced by the participant would have been lost.
In this way, exploring deck B choices across the 5 blocks of 20 trials can provide an index of learning and strategy used by participants throughout the task. Therefore a 2x2x5 mixed model ANOVA investigated deck B choices across the 5 trial blocks. There was a significant interaction between gender, reward sensitivity and block, F(4, 460) = 4.4, p< .05. Figures 3.2 and 3.3 show that high reward sensitive males chose more cards from deck B as the task went on whereas all other groups chose progressively less. A simple main effects analysis confirmed the significance of this difference, F(4, 224) = 10.52 p< .05, suggesting that only reward sensitive males made consistently risky decisions on the IGT; all others made less risky choices as the task went on.
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Figure 3.2. Total number of cards chosen from Deck B in each block of 20 trials on the IGT by low sensitive to reward male and female participants over the 100 trials of the IGT.
Figure 3.3. Total number of cards chosen from Deck B in each block of 20 trials of the IGT by highly sensitive to reward male and female participants.
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A 2x2 between subjects ANOVA found a non-significant interaction between punishment sensitivity and gender on Deck C choices F (1, 115) = .63, p> .05. There was no main effect of gender, F(1, 115) = 3, p> .05 nor punishment sensitivity, F (1, 115) = 1.1, p> .05 (Figure 3.4), but there was a slight trend indicating that low punishment sensitive males chose slightly more deck C cards than high punishment sensitive males. Punishment sensitivity did not have an effect on females’ Deck C choices.
Figure 3.4. Total number of cards chosen from Deck C over 100 trials of the IGT by high and low reward sensitivity male and female participants.
This study found that young males who scored highly on reward sensitivity made more card selections from risky Deck B, throughout the task, compared to low reward sensitive males and all females. These findings suggest that reward sensitivity may underpin specifically young males’ risky behaviour because females who were reward sensitive did not display a preference for risky Deck B. This relationship may underpin the differences in males’ and females’ risky
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driving behaviour, and their response to the L2L intervention, because reward sensitivity may only underpin the risky behaviour of young males.
We needed to make sure that the results from this study applied specifically to young males, rather than simply all reward sensitive males in general regardless of their age. It might be that all males who are sensitive to reward are more likely to make risky decisions. If this is the case then heightened reward sensitivity would not adequately explain young males’ higher propensity to drive in a risky way. Therefore study two b investigated this notion further by increasing the sample size to include a comparison group of older males, in order to investigate whether reward sensitivity underpins older males’ risk-taking in the same way it does for young males.
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