Models of addictive behaviour

Brendan Williams
Mind Map by Brendan Williams, updated more than 1 year ago
Brendan Williams
Created by Brendan Williams about 6 years ago
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Undergraduate degree Psychology (The psychology of addictive behaviour) Mind Map on Models of addictive behaviour, created by Brendan Williams on 05/23/2014.

Resource summary

Models of addictive behaviour
1 The Biological approach
1.1 Gambling
1.1.1 Initiation - pathological gambling runs in families
1.1.1.1 Shah et al - evidence of genetic transmission in men
1.1.1.2 Biologically predisposed
1.1.1.3 Pleasurable behaviour - reward pathway releases dopamine
1.1.1.3.1 Prefrontal cortex - plans to create pleasure again
1.1.1.4 Black et al - first degree relatives of pathological gamblers more at risk than distant relatives
1.1.1.5 Noble et al - A1 variant on DRD2 gene of 2/3 deceased alcoholics, only on 1/5 non alcoholics - gene for addiction
1.1.1.6 Able to explain how people with the same experiences don't all develop addiction. More vulnerable to initiation/more resistant to treatment
1.1.1.7 Ignores factors such as peer pressure in initiation. Combined with diathesis stress more appropriate
1.1.1.8 Breen & Zimmerman - unable to explain why different types of gambling are more addictive. Horse racing more addictive, three years later video gambling more addictive
1.1.2 Maintenance - underactive pituitary adrenal response - stressful situations
1.1.2.1 Paris et al - pathological gamblers have no cortisol increase to gambling stimuli
1.1.2.1.1 Hormone associated with stress
1.1.2.2 Individual differences in optimal stimulation
1.1.2.2.1 Zuckerman - high sensation seekers have lower appreciation of risk. Anticipate arousal more positively than low sensation seekers - more likely to gamble
1.1.2.3 Bonnaire et al - gamblers at race tracks higher sensation seekers than card players in cafes
1.1.3 Relapse - vulnerability to boredom can lead to gambling
1.1.3.1 Blaszczynski et al - gamblers had higher boredom proneness scores than control
1.1.3.1.1 No significant difference between types of gambling
1.2 Smoking
1.2.1 Initiation - genetics play a role
1.2.1.1 Vink et el - individual differences in initiation 44% genetics, 56% environment
1.2.1.2 Boardman - DZ twins 42% heritability for smoking
1.2.1.3 Thorgeirsson et al - variant on chromosome 15 that influences number of cigarettes smoked, nicotine dependence & risk of related diseases
1.2.1.3.1 Not only determines initiation, also affects dependence
1.2.1.4 Individuals could be screened for genetic vulnerability to decrease chances of starting smoking behaviour
1.2.1.4.1 Gartner et al - only weak association between genes & smoking - screening unlikely to be successful
1.2.2 Maintenance - individual differences in nicotine metabolism
1.2.2.1 Vink et al - nicotine cases dopamine release, behaviour must be repeated to avoid withdrawal symptoms
1.2.2.2 Buka et al - mothers who smoked during pregnancy doubled child's risk of smoking addiction if they started smoking
1.2.3 Relapse
1.2.3.1 Xian et al - 54% risk for quit failure inherited
1.2.3.2 Lerman et al - ASP40 variant made smokers with high dosage of NRT x2 more likely to quit than lower NRT levels
1.2.3.2.1 Effect not found in those without variant - genetic testing allows choice of most appropriate treatment
1.2.4 Ignores social context of behviour
2 The learning approach
2.1 Gambling
2.1.1 Initation - operant conditioning - addiction comes from rewards received. psychological - near miss, social - peer praise
2.1.1.1 Generally don't win, greater weight on experience of winning
2.1.1.2 Individual differences in types of gambling not explained, scratch cards - short time period little skill, sport betting - long time period increased skill
2.1.1.3 Nower et al - behaviourally conditioned gamblers (peers & role models) least severe addiction & are more willing to receive treatment
2.1.1.3.1 Emotionally vulnerable gamblers underlying anxiety/depression, poor coping skills. More resistant to treatment
2.1.2 Maintenance - intermittent reinforcement means gamblers become used to long time without payout
2.1.2.1 Lambos et al - social reinforcement also provides reinforcement
2.1.2.2 Only a partial explanation - unable to explain why though most people will sometimes gamble, few become addicts
2.1.3 Relapse - addicts associate stimuli with their addiction, providing conditional cues
2.1.3.1 Exposure to conditional cues increase chance of relapse
2.1.3.2 Fulfilment of gambling needs dependent on ability to control arousal & need for reinforcement
2.1.3.3 Adaptive behaviours learnt to calculate advantage on average
2.2 Smoking
2.2.1 Initation - social learning - role models influence the likelihood of addictive behaviour
2.2.1.1 People begin smoking because their peers do, positive social expectations
2.2.1.2 Mayeux - 16 year old males, relationship between smoking & popularity 2 years later
2.2.1.3 Diblasio & Benda - smokers more likely to hang out with other smokers
2.2.1.4 Karcher & Finn - parents smoking doubled likelihood of smoking, peers smoking x8 likelihood
2.2.1.5 NIDA - 90% American smokers started in teens, mainly from observing peers
2.2.1.5.1 Winett et al - role models with higher social status more likely to influence those of lower social status
2.2.1.5.1.1 Brynner - media images of smoking made it appear more attractive & tough
2.2.2 Relapse - conditioned cues, such as smell of cigarette smoke increase likelihood of relapse
2.2.2.1 Lawrance & Rubinson - frequent smokers have less self confidence in abstinence & more likely to relapse
2.2.2.2 Lopez et al - there is gender bias in research as addiction development is different in men & women
2.2.3 Maintenance - classical conditioning - repetition leads to conditioned association with sensory aspects of smoking & reinforcing properties of nicotine
2.2.3.1 Conditioned stimuli activate same part of the brain as nicotine, making quitting hard
2.2.3.2 Thewissen et al - placed smokers in rooms either with/without smoking cues. Cues produced greater urge to smoke
2.2.3.3 Drummond et al - producing cues without nicotine reinforcement can create stimulus discrimination, association extinguished
3 The cognitive approach
3.1 Smoking
3.1.1 Initiation - expectancy theory - expectations of outcomes of behaviour contribute to excessive use
3.1.1.1 Able to explain loss of control
3.1.1.2 Kassel et al - teens think smoking when they're in a bad mood
3.1.1.2.1 Brandon & Baker - they expect smoking will improve mood
3.1.1.3 Not seen as a loss of control, only an excessive behaviour
3.1.1.3.1 Addiction often involves loss of control, cannot be explained how expectancies affect this
3.1.1.3.2 Rational choice theory - addictive behaviour occurs after weighing up pros & cons
3.1.1.3.2.1 Gambling the exception as monies lost should cause offset
3.1.1.3.2.1.1 Pleasure received may offset this
3.1.2 Maintenance - automatic processing - as addiction develops, conscious thoughts less important
3.1.2.1 Explains the loss of control & difficulty abstaining
3.1.2.2 Tate et al - expectancies can be manipulated to prevent relapse
3.1.2.3 NRT treatment effectiveness not always consistent
3.1.2.3.1 Moolchan et al - NRT only effective when combined with CBT to change expectancies of smoking
3.1.3 Relapse - expectations of cost benefit will affect likelihood of quitting
3.1.3.1 Individuals who see many benefits in smoking more likely to relapse after quitting
3.1.3.2 Juliano & Brandon - smokers have greater expectancies of smoking improving mood & cutting craving. More positive effect on weight control - expantancies not generalised to NRT explain poor success rate
3.2 Gambling
3.2.1 Initation - gambling behaviour used for self medicaiton
3.2.1.1 Gelkopf et al - individuals use pathological behaviour to treat psychological symptoms
3.2.1.1.1 Behaviour perceived to help with issue
3.2.1.1.1.1 Mood regulation
3.2.1.1.1.2 Performance management
3.2.1.1.1.3 Distraction
3.2.1.2 Brandon - addictive behavior influenced more by unconscious expectations
3.2.1.3 Li et al - pathological gamblers who gambled to escape more likely to have other addictions
3.2.1.3.1 Self medication states one behaviour must precede the other
3.2.1.3.1.1 Becona et al - comorbidity of depression & gambling
3.2.1.3.1.1.1 Correlation does not show causality, depression may be due to financial difficulties
3.2.2 Maintenance - irrational beliefs - overestimate how much they think they can alter outcome
3.2.2.1 Gamblers fallacy - cognitive distortion probability changes based on recent events
3.2.2.2 Illusions of control
3.2.2.2.1 Langer - gamblers overestimate skill in chance situations
3.2.2.3 Exaggerated self confidence in beating the system & success due to skill not chance
3.2.2.4 Griffiths - regular gamblers made more irrational verbalisations such as 'only putting in a pound fools the machine' & 'this fruity is not in a good mood'
3.2.2.4.1 Described losses as near misses
3.2.2.5 Benhasin & Ladoucer - no difference in cognitive distortions of students in/not in statistics
3.2.2.5.1 Delfabbro et al - irrational cognitions in gamblers but just as accurate in calculating odds as non gamblers
3.2.3 Relapse
3.2.3.1 Blanco et al - gamblers remember & overestimate wins, rationalise losses
3.2.3.2 String of losses not a negative, gamblers feel they will eventually be rewarded - just world hypothesis, they deserve to win
3.2.3.3 Treatment should involve targeting underlying issue & motivation
3.3 Beck's vicious circle - Low mood - substance abuse - financial/medical/social problems
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