Addiction - Explanations for Gambling Addiction Flashcards
What are the key features of the learning theory as an explanation for gambling addiction?
- vicarious reinforcement can be the start of an addiction
- direct reinforcement can be positive or negative
- partial reinforcement more effective than continuous
- variable reinforcement schedule is the most effective
- variable reinforcement is very resistant to extinction
- cue reactivity explains how associated stimuli can trigger gambling
How can vicarious reinforcement be the start of an addiction?
One way in which people begin gambling is through seeing others being rewarded for gambling (e.g. seeing someone else enjoying money and sometimes winning money).
Vicarious reinforcement can also be through newspaper articles reporting big wins (e.g. on the National Lottery).
How can direct reinforcement be positive or negative?
Positive reinforcement comes from a direct gain (e.g. winning money), and from the ‘buzz’ that accompanies a gamble (which is exciting).
Negative reinforcement occurs because gambling can offer a distraction from aversive stimuli (e.g. the anxieties of everyday life).
How is partial reinforcement more effective than continuous?
Skinner’s research with rats found that continuous reinforcement schedules do not lead to persistent behaviour change. Once the rewards stop, the behaviour quickly disappears (called extinction).
A partial reinforcement schedule leads to more persistent behaviour change. When only some bets are rewarded, there is an unpredictability about which gambles will pay off, which is enough to maintain the gambling.
How is variable reinforcement the most effective?
A variable (ratio) reinforcement schedule is a partial reinforcement schedule where the intervals between rewards vary. This kind of reinforcement schedule is highly unpredictable.
How is variable reinforcement very resistant to extinction?
Whilst it takes longer for learning to be established if the reinforcement schedule is variable, once it is established it is more resistant to extinction.
The gambler learns that they will not win with every gamble, but they will eventually win if they persist (and then the gambling is reinforced).
This explains why some people continue to gamble despite big losses.
How does cue reactivity explain how associated stimuli can trigger gambling?
In the course of their gambling, an individual will experience many secondary reinforcers - things they associate with the exciting arousal experienced through gambling.
These cues can both maintain gambling and cause its reinstatement after a period of abstinence.
What are the strengths of the learning theory as an explanation for gambling addiction?
- research support
- explains failure to stop gambling
What are the weaknesses of the learning theory as an explanation for gambling addiction?
- lack of explanatory power
- individual differences
- doesn’t explain all aspects of gambling
What research support is there for the learning theory as an explanation for gambling addiction?
Dickerson (1979) found high-frequency gamblers in natural settings were more likely than low-frequency gamblers to place bets in the last two minutes before a race.
These gamblers may delay betting to prolong the rewarding excitement (e.g. the tension they get from the radio commentary heard in the betting shop).
This is evidence for the role of positive reinforcement on gambling behaviour in frequent gamblers in a more ‘real-life’ setting than a psychology lab.
How does the learning theory explain failure to stop gambling?
Some people see continued gambling as a moral failure - the person wants to stop but lacks willpower. This can be explained by learning theory because learning occurs in the absence of active decisions.
Thus learning theory is an effective explanation of a common phenomenon - how gamblers fail to stop gambling whilst at the same time being determined to do so.
Their conscious desire to give up conflicts with the motivational forces acquired through conditioning that drive them to continue gambling.
How does the learning theory of gambling addiction lack explanatory power?
Learning theory explains some types of gambling better than others. Fruit machine gambling is dependent on chance and rewards are temporarily contiguous (no delay between the bet and the outcome).
In contrast, gambling games like poker require an element of skill and there is greater delay between the bet and knowing the outcome; this is more difficult to explain in terms of conditioning.
Therefore, learning theory lacks explanatory power because it does not provide a general explanation of all gambling addiction.
How are individual differences a weakness of the learning theory as an explanation for gambling addiction?
Griffiths and Delfabbro (2001) argue that people do not respond in the same ways to conditioning even when using identical stimuli.
Some people gamble to relax, some to be aroused. Some people stop gambling and never relapse but some are more vulnerable to cues.
These observations are difficult to explain for learning theory without invoking cognitive features of addiction such as distortions in thinking.
How does the learning theory not explain all aspects of gambling?
Gambling addiction is multifaceted. Psychologists have tried to use learning theory to understand the cycle of gambling addiction from initiation, through maintenance to cessation and relapse.
Conditioning processes may be less important at some points. Brown (1987), for example, suggests learning theory can explain the persistence of gambling behaviour but not its start.
This means that it is not a complete explanation for the cycle of gambling behaviour.
What are the key features of the cognitive theory as an explanation for gambling behaviour?
- expectancy theory (expected benefits outweigh costs)
- cognitive biases (selective processing of information)
- four different categories of cognitive bias
- relapse occurs due to a lack of self-efficacy
