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


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 Shah et al - evidence of genetic transmission in men Biologically predisposed Pleasurable behaviour - reward pathway releases dopamine Prefrontal cortex - plans to create pleasure again Black et al - first degree relatives of pathological gamblers more at risk than distant relatives Noble et al - A1 variant on DRD2 gene of 2/3 deceased alcoholics, only on 1/5 non alcoholics - gene for addiction Able to explain how people with the same experiences don't all develop addiction. More vulnerable to initiation/more resistant to treatment Ignores factors such as peer pressure in initiation. Combined with diathesis stress more appropriate 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 Paris et al - pathological gamblers have no cortisol increase to gambling stimuli Hormone associated with stress Individual differences in optimal stimulation Zuckerman - high sensation seekers have lower appreciation of risk. Anticipate arousal more positively than low sensation seekers - more likely to gamble 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 Blaszczynski et al - gamblers had higher boredom proneness scores than control No significant difference between types of gambling
1.2 Smoking
1.2.1 Initiation - genetics play a role Vink et el - individual differences in initiation 44% genetics, 56% environment Boardman - DZ twins 42% heritability for smoking Thorgeirsson et al - variant on chromosome 15 that influences number of cigarettes smoked, nicotine dependence & risk of related diseases Not only determines initiation, also affects dependence Individuals could be screened for genetic vulnerability to decrease chances of starting smoking behaviour Gartner et al - only weak association between genes & smoking - screening unlikely to be successful
1.2.2 Maintenance - individual differences in nicotine metabolism Vink et al - nicotine cases dopamine release, behaviour must be repeated to avoid withdrawal symptoms Buka et al - mothers who smoked during pregnancy doubled child's risk of smoking addiction if they started smoking
1.2.3 Relapse Xian et al - 54% risk for quit failure inherited Lerman et al - ASP40 variant made smokers with high dosage of NRT x2 more likely to quit than lower NRT levels 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 Generally don't win, greater weight on experience of winning Individual differences in types of gambling not explained, scratch cards - short time period little skill, sport betting - long time period increased skill Nower et al - behaviourally conditioned gamblers (peers & role models) least severe addiction & are more willing to receive treatment 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 Lambos et al - social reinforcement also provides reinforcement 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 Exposure to conditional cues increase chance of relapse Fulfilment of gambling needs dependent on ability to control arousal & need for reinforcement 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 People begin smoking because their peers do, positive social expectations Mayeux - 16 year old males, relationship between smoking & popularity 2 years later Diblasio & Benda - smokers more likely to hang out with other smokers Karcher & Finn - parents smoking doubled likelihood of smoking, peers smoking x8 likelihood NIDA - 90% American smokers started in teens, mainly from observing peers Winett et al - role models with higher social status more likely to influence those of lower social status 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 Lawrance & Rubinson - frequent smokers have less self confidence in abstinence & more likely to relapse 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 Conditioned stimuli activate same part of the brain as nicotine, making quitting hard Thewissen et al - placed smokers in rooms either with/without smoking cues. Cues produced greater urge to smoke 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 Able to explain loss of control Kassel et al - teens think smoking when they're in a bad mood Brandon & Baker - they expect smoking will improve mood Not seen as a loss of control, only an excessive behaviour Addiction often involves loss of control, cannot be explained how expectancies affect this Rational choice theory - addictive behaviour occurs after weighing up pros & cons Gambling the exception as monies lost should cause offset Pleasure received may offset this
3.1.2 Maintenance - automatic processing - as addiction develops, conscious thoughts less important Explains the loss of control & difficulty abstaining Tate et al - expectancies can be manipulated to prevent relapse NRT treatment effectiveness not always consistent 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 Individuals who see many benefits in smoking more likely to relapse after quitting 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 Gelkopf et al - individuals use pathological behaviour to treat psychological symptoms Behaviour perceived to help with issue Mood regulation Performance management Distraction Brandon - addictive behavior influenced more by unconscious expectations Li et al - pathological gamblers who gambled to escape more likely to have other addictions Self medication states one behaviour must precede the other Becona et al - comorbidity of depression & gambling 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 Gamblers fallacy - cognitive distortion probability changes based on recent events Illusions of control Langer - gamblers overestimate skill in chance situations Exaggerated self confidence in beating the system & success due to skill not chance 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' Described losses as near misses Benhasin & Ladoucer - no difference in cognitive distortions of students in/not in statistics Delfabbro et al - irrational cognitions in gamblers but just as accurate in calculating odds as non gamblers
3.2.3 Relapse Blanco et al - gamblers remember & overestimate wins, rationalise losses String of losses not a negative, gamblers feel they will eventually be rewarded - just world hypothesis, they deserve to win 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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