addiction - models

Georgie Hartshorne Psychology – Unit 4 Models of addiction

Smoking:

Biological Explanation:

Initiation:

People most susceptible in the initiation phase as the model argues that people have a predisposed biological vulnerability (also making relapse more likely).

Family/twin studies estimate heritability to be around 39% and 80%.

The link between cigarette smoking and genes involves dopamine regulation and nicotine dependency.

Nicotine activates Nicotine acetylecholine receptors which lead to the release of dopamine in the brains pleasure centre – the Mesolimbic pathway (meaning ‘do it again’)

Repeated exposure leads to increasing the sensitivity of the brain to their desirability which can persist even in the absence of the drug.

The disease model: Lerman et al - Some people have no reward gene and less dopamine receptors in the pleasure centres of brain and are therefore more likely to smoke more to get the same reward as others so are more likely to become addicted. Caine et al found that mice without the D1 receptor for dopamine do not self-administer cocaine when given the chance when normal mice will and therefore dopamine has a key role in addiction.

Vink et al - studied 1572 Dutch twin pairs. Found that both male and female individual differences in initiation were explained by genetic (44%) and environment (56%).

Boardman et al - studied 348 identical twins and 321 same-sex non-identical twins and estimated heritability to be around 42%.

Shield – looked at 42 twin pairs who had been reared apart. Only 9 were discordant (one smoked while the other didn’t).

Sabol – correctional study on 1107 smokers, former smokers and non-smokers. People with the gene variant SLC6A3-9 were less likely to smoke and more successful at quitting. Concluded this may be the result of them having an altered dopamine transmission which reduced their need for external rewards (e.g. – cigarettes).

Volkow et al – gave Ritalin (ADHD drug – gently lifts dopamine levels) to volunteers. Some like it while others didn’t – proposed that it was because those who liked it (from brain scans) had fewer dopamine receptors and therefore need that extra kick for happiness. Explains smokers as some have inherent vulnerability to smoking and will start to/continue to smoke whereas others will stop.

Maintenance:

Addiction – Models of addiction


Vink et al – nicotine dependency was influenced primarily by genetics (75%). Suggests that although initiation is influenced by environmental factors, maintenance is more linked to individual differences around nicotine metabolism.

Nicotine affects brain chemistry – triggers nicotinic acetylcholine receptors (nAchRs) which release dopamine (a pleasure hormone)

High nicotine concentration in blood equals short-lived pleasure, as it lowers its equal mood impairments and loss of concentration in a couple of hours which become the main driving force behind the cravings, so addicts smoke another cigarette to avoid withdrawal symptoms.

Chronic exposure to nicotine results in a reduction in the activity of positive reward circuits in the brain (down regulation) creating a stressful situation for the addict with withdrawal symptoms, which causes them to continue to smoke. They no longer take the drugs to gain please, but to avoid withdrawal symptoms.

Thorgeirsson et al - Icelandic study. Identified specific gene variant on chromosome 15 that influenced the number of cigarettes smoked per day, nicotine dependence and the risk of developing a smoking-related disease. Those smoking less than 10 a day were less likely to have the gene than those smoking more than ten. This suggests that genetics may not be the cause of initiation, but do make it more likely for smokers to subsequently become addicted once starting.

Buka et al - smoking in pregnancy doesn’t increase initiation rates in children, but mothers who smoked more than 20 a day had children who were more likely to become addicted than those with mothers smoking less once they began smoking (data on 1,248 17-39 year old women between 1959-66.)

Shachter – compared how many cigarettes different smokers need a week. Gave them either low or high nicotine cigarettes – those with low smoked more (predicted by the Nicotine Regulation Model) as the high allowed them to reach the needed level of nicotine with less cigarettes. Results clearest on heavy smokers – smoked on average 25% more low nicotine cigarettes than high. Argues that they continue to smoke to maintain nicotine in the body to avoid withdrawal.

Khaled et al – depression is highest in current smokers and lowest in non-smokers – showing need to smoke to gain rewarding feelings.

Relapse:

Eventually, the desire for the drug becomes the most important desire. Despite it now giving less pleasure, the brain still receives reward signals that force the smokers to continue smoking.

Permanent recovery is difficult as nicotine-induced changes create lasting memories of said drug. Capacity for self-control had been weakened and the pre-frontal cortex is now less effective at decision making/judging consequences.

Individuals are more vulnerable to relapse if their biological craving is linked to environmental stimuli (places they associate with the drug (pub)).


Sabol – correctional study on 1107 smokers, former smokers and non-smokers. People with the gene variant SLC6A3-9 were less likely to smoke and more successful at quitting. Concluded this may be the result of them having an altered dopamine transmission which reduced their need for external rewards (e.g. – cigarettes).

Twin studies show ability to quit smoking is genetic.

Xian et al - twin study; studies genetic risk factors contributing to relapse. 54% of relapse is attributed to heritability.

Uhl et al – attempted to attribute specific gene clusters associated with quit success to match treatments with quitter.

Evaluation:

Negatives:

Limitations: Neglecting other possible determining factors, including social factors (reductionist) and also negates the problem to the individual so as they are the problem and it is irreversible. However, by regarding smoking as a biological problem, opens the possibility for a pharmacological cure and the emphasis is on treatment.

Reductionism: Biological explanations for addictions are generally reductionist; they reduce a complex phenomenon down to a relatively simple level of explanation. While this may have advantages (allowing researchers to study family genetics), it has its limitations. Influence of neurotransmitters such as dopamine is clearly important, but reducing addiction down to genes/chemicals ignores all other potential influences (irrational though process, social context).

Deterministic: biological model assumptions – addiction specified diagnosis (you can’t be ‘slightly addicted’)

Research: uses correlational evidence for genes and levels of smoking – twin studies but these do not show cause and effect. Caine study: animals.

Positives:

Research evidence: Thorgeirsson et al - This suggests that genetics may not be the cause of initiation, but do make it more likely for smokers to subsequently become addicted once starting.

Implications of treatments: Genomic medicine involves screening people to identify what genes they do/don’t carry. Individuals found to be at a high genetic risk could be advised a lifestyle change (e.g.: stop smoking) or seek medical treatment to reduce risk of related diseases. Smoking appears to be a good candidate for this approach; large public health burden. However, Gartner et al suggested that, at present, screening is unlikely to be successful because of the relatively small associations between specific genes and a smoking addiction. Also, allows treatment – those with specific gene clusters are given nicotine patches so they continue to get the high without the danger to keep withdrawal symptoms to a minimum.


Genetic role: Evidence suggests that effectiveness of medication for smoking cessation may be moderated by genetics. Smokers with the Asp40 variant of the mu-opioid gene are twice as likely to quit with high dose nicotine replacement therapy as a low dose. Smokers with more common Asn40 variant were equally likely to stop, regardless of the nicotine dose level. Consequently, genetic testing may also allow therapists to choose most appropriate cessation therapy (Lerman et al).

Scientific objective evidence: gene mapping cannot be influenced by demand characteristics therefore leading to valid results (can’t change genes).

Individual differences: Can be used to explain why some people develop an addiction while others do not under the same social pressures. Some people are more vulnerable to developing addictions than others because of their genetic predispositions (explained in the Diathesis-stress Model).

Learning Explanation:

Initiation:

Social learning theory: explains of experimental smoking propose that young people begin smoking as a consequence of those social models they have around them who smoke (Kandel and Wu). From this perspective, experimental smoking is primarily a function of parental and peer role modelling and the vicarious reinforcement that leads young people to expect positive physical and social consequences from smoking. Negative outcomes observed or experienced reduce the use of certain drugs and the selection of safer ones.

Popularity as a positive reinforce: popularity among peers may also serve as a positive reinforce in the initiation of smoking. Mayeux et al found a positive relationship between smoking at age 16 and boys’ popularity 2 years later.

Operant conditioning: positive reinforcement. All positive reinforcers release dopamine in the mesolimbic system. Natural reinforcers are drink, food and sex. Predictably, addictive drugs have the same effects (White).

Classical conditioning: secondary reinforcers are those things that precede or occur at the same time as the addiction itself. Glautier et al found that the sights and smells of a pub elicited the similar physiological responses as alcohol.

Maintenance:

The repetition of the act of smoking thousands of times a year eventually leads to a strong conditioned association between the sensory aspects of smoking (the sight of cigarettes, smell of the smoke) and the reinforcing effects of nicotine.

Although the effects of nicotine in the brain are important when first starting to smoke, smoking-related sensory cues rapidly become conditioned stimuli and so activate the same brain areas, making cessation more difficult (Franklin et al)

Operant conditioning: withdrawal from the drug causes unpleasant feelings (a negative situation).


Classical conditioning: maintenance is continued through the threat of withdrawal.

Social Learning Theory: West – suggested the observation of the positive and negative effects of drugs forms the continual conflict between the seduction of the addition and its avoidance.

Relapse:

Conditioned cues: cues associated previously with receiving nicotine, such as the availability of cigarettes or the smell of cigarettes smoke, increase the likelihood that the smoker will respond by smoking. Hogarth et al found that the amount of craving increased significantly when a conditioned stimulus related to smoking was presented to a smoker.

Refusal self-efficacy: a concept related to the social learning explanation of smoking is self-efficacy, a person’s belief in his/her ability to succeed in a particular situation. Among adults those who smoke more frequently have less confidence in their ability to abstain (Lawrance and Rubinson) and so are more likely to relapse. Lin showed that high self-efficacy increases quit success in internet addicts.

Operant conditioning: the process of negative reinforcement.

Social Learning Theory: West – Claims that classical conditioning increases the likelihood of relapse as meeting other users or experiencing the shooting up ritual will trigger positive memories and therefore addicts will relapse.

Marlatt and George – suggested that the presence of multiple cues trigger positive memories and the likelihood of relapse.

Evaluation:

Positives:

Real-world Application: Botvin suggests that effective forms of drug prevention programme should target beginner adolescents. It is at this crucial developmental period that adolescents are most vulnerable to the influences of peers in particular and therefore most in need of drug resistance skills and social skill development. Resistance training not only teaches adolescents how to refuse drugs such as cigarettes, but also informs them of the influences of peers and adults on drug use. Botvin argues that it is imperative to equip adolescence with the anti-smoking and anti-drug messages and arguments needed to counter the pro-smoking and pro-drug messages received from their environment.

Social Learning Theory: Lawrence – Suggested the self-efficacy theory suggests smokers are likely to be those who feel the most pressure to conform.

Conditioned cues: Thewissen et al tested the importance of environmental contexts in the urge to smoke. In one room, they repeatedly presented 33 smokers with a cue predicting smoking, whilst in a 2nd they presented a cue predicting smoking unavailability. Consistent with expectations, results supported the view that a cue predicting smoking later led to a greater urge to smoke than did a cue associated with smoking unavailability.


Role Models: Many of the claims of social learning influences on the development of addictive behaviours have been supported by research evidence. For example, research found that peer group influences are the primary influence for adolescents who smoke/drugs (DiBlasio and Benda). Those adolescents who smoked were more likely to ‘hang out’ with other adolescents who also smoked. Karcher and Finn found that youth whose parents smoked were 1.88 times, sibling smoked were 2.64 times and if close friends smoked 8 times more likely than if their parents, siblings and friends did not smoke to start smoking.

Implications for treatment: Drummond et al propose a treatment approach based on the idea that the cues associated with smoking are an important factor in the maintenance of addiction. Cue Exposure (treatment) involves presenting cues without the opportunity to smoke after. This leads to stimulus discriminating; without the reinforcement of the cues with nicotine, the association between them extinguishes.

Classical conditioning: Robins – explains the desire to relapse when exposed to cues. Found Vietnam veterans addicted to heroin were less likely to relapse when returned to home environment.

Negatives:

Gender bias in smoking addiction research: Nerin de la Puerta and Jane argue that there is an inherent gender bias in much of the research relating to smoking addiction. The onset of smoking and development of smoking addiction follows a different pattern in men and woman according to Lopez et al. They found that women start smoking later than men, and that there are gender-related differences in relation to both the stages and context of smoking. Explanations of smoking addiction generally fail to address these gender differences.

Operant conditioning: Robinson and Berridge – it fails to explain how a great many experiment with addictive drugs but do not become addicted and so there therefore must be other factors.

Classical conditioning: Drummond – argued that repeated exposure to secondary reinforcers would lead to extinction if it were not accompanied with the high of actual drug taking – known as stimulus discrimination.

Cognitive Explanation:

Initiation:

Addicts differ from non-addicts in terms of their perceived expectancies about the positive vs. negative effects of a behaviour and the effect of psychoactive substances. Brandon et al proposed that a behaviour escalates into an addiction because of the expectancies that an individual has about the cost and benefits of that activity.

Adolescent smokers commonly smoke when having negative moods (Kassel et al) and expect smoking to reduce negativity/boredom and remove stress (Brandon and Baker). The expectancy of positive moods states (e.g. relaxation) is a reason adolescents begin to smoke (Mermelstein et al). This expectation is further reinforced by the actual effects of the drug/behaviour to escalate the addiction.


Eiser et al – suggested frequent smokers transmit positive expectations of smoking to novices who might otherwise be put off by negatives.

Self-medication model: Gelkopf et al proposes that individuals intentionally use different forms of pathological behaviour (e.g. alcohol, drugs, gambling) to treat the psychological symptoms from which they suffer. The particular activity an addict chooses is not selected at random, but tends to be one that is perceived as helping with a particular problem. For example, some activities may be chosen because they help the individual overcome anxiety, whereas others (gambling) appear to help with depression associated with poverty and so on. Gambling might not actually make things better, but needs only to be judged as doing so by the individual to become an addiction as the gambler expects good outcomes.

Expectancy theory: heavier drinkers have shown to have more positive expectancies about the effects of alcohol compared to lighter drinkers.

Self-efficacy theory: Bandura - refers to a belief in one’s self to organise and control any actions required to meet particular goals. Plays an important role in whether or not a person will start and addictive behaviour.

Rational choice theory: Becker and Murphy – people become addicts after weighing up the costs and benefits of the activity. Uses the concept of ‘utility’, weighing the costs against the benefits of an activity. From this perspective, addiction is experienced as an increase in consumption of ‘goods’ because the addicts have made a rational choice concerning their current and future ‘utility’ of their addiction.

Maintenance:

Brandon et al - suggests that as addictions develop, it is less influenced by the conscious expectations and more by the unconscious expectations involving automatic processing, which explains the loss of control that many addicts have and the difficulties of quitting. Expectancies can also be manipulated to prevent relapse; Tate et al told smokers they shouldn’t experience any withdrawal symptoms while abstaining from their addiction which lead to fewer somatic symptoms (shakes) and psychological effects (mood disturbance) than a control group. Those told they would experience somatic but not psychological experiences more numerous and sever somatic effects than a control group.

Self-perpetuating cycle: smokers engage in smoking, which leads to medical and financial problems, which them leads to a low, negative mood, which then leads to continuation of the smoking behaviour in order to cope with the depressing mood. Cohen and Lichtenstein found that smoking actually increases stress levels, suggesting that it is an irrational belief that smoking decreases stress level. Koski-Jannes – found that addictions form because of short-sighted means of dealings with stressful events. Initially giving positive effects and later negative consequences. Leading to a self-perpetuating cycle regulated by self-serving thoughts.

Beck et al – vicious cycle: low mood can be relieved by addictive behaviour. Addiction leads to financial/social/health problems, which lead to a low mood, resetting the circle.


Self-medication model: refer to initiation. Many smokers mention ‘stress release’ as a major reason for smoking – relieve stress of withdrawal symptoms.

Expectancy theory: Brandon et al – as addiction develops, the activity is influenced less by conscious expectations and more by unconscious expectations, explaining the loss of control many addicts feel and relapse difficulties

Self-efficacy theory: Bandura - refers to a belief in one’s self to organise and control any actions required to meet particular goals (they are no longer consciously thinking about the outcomes). Plays a role in whether an addict believes they can do anything to stop the addiction.

Rational choice theory: Becker and Murphy – refer to initiation. According to this theory, addicts are rational consumers who look ahead and behave in a way that is likely to maximise the preferences they hold.

Relapse: Expectations of the cost/benefits of smoking affect an individual’s readiness to quit and the likelihood of relapse. DeVries and Backbier demonstrated that smokers’ perception of pros and cons of smoking and of quitting affect their quitting behaviour. According to this perspective, those individuals who perceive smoking to have many benefits and quitting to have few are more likely to relapse.

Shiffman – interviewed 143 ex-smokers whose call to a relapse helpline was recorded finding that those who had relapse crisis’s had lower self-efficacy.

Eiser et al – studied 10,000 British adolescences found teenage smokers acquired expectations of smoking from veterans and had a greater external locus of control about their health compared to non-smokers.

Attitudes/Intentions/Beliefs: many cognitive theories or models aim to explain failure to abstain from addictive behaviour e.g. – Locus of Control; those with an external locus of control may fail to take responsibility for changing their own behaviour. Self-Efficacy; those with low self-efficacy may feeling capable of changing their addictive behaviour. We relapse if we have decreased self-efficacy (not believing they are able to quit). Relapses also reduce self-efficacy and make it more likely that you will relapse again (a vicious cycle). The Theory of Planned Action (Ajzen): one’s own or others unhelpful beliefs and attitudes about the benefits of changing addictive behaviour may negatively affect the intention to do so.


Expectancy theory: Brandon et al – as addiction develops, the activity is influenced less by conscious expectations and more by unconscious expectations, explaining the loss of control many addicts feel and relapse difficulties (they are no longer consciously thinking about the outcomes).




Evaluation:

Strengths:

Importance of expectancies: Juliano and Brandon found that smokers reported greater expectances that cigarettes alleviate negative mood states, and had a positive effect on weight control compared with the different forms on NRT. Therefore, smoker’s positive expectances for the effects of smoking do not appear to generalise to NRT, which may explain its modest cessation rate.

Intervention: having this knowledge can allow us to intervene because we can advise parents/media/schools how to show children the negative effects of the addiction so that they do not develop these expectations.

Practical Application: smokers who do not have negative expectations of quitting are more able to quit. Managing expectations could be used in release prevention therapy. Also, research shows that high self-efficacy is a key factor in relapse prevention, supported by Theory of Planned Behaviour.

Helps explain individual differences: as in, millions of people have smoked, but most are not addicted. This is explained because they do not have the faulty thought processes that addicts have.

Negatives:

Language: Attempts to understand the nature of addictions are clouded by the difficulties of obtaining objective data. Davies claims that addicts describe their addiction, when talking to heath worker or police, by using the language of addiction, i.e. their behaviour is out of control. However, when talking to peers, they use different language which suggests they are exercising preferences that are rational and understandable given their circumstances. This suggests that language off addicts serves an important function for the individual, i.e. may serve to absolve them of responsibility

Expectancy theories and publication bias: The focus of research into expectancy theory has largely been on positive research findings, with negative results receiving less attention. For example, studies have supported an association between expectancies and addictive behaviour but this constitutes a publication bias as the selective publication of positive results gives an unrepresentative view of a particular research area, particularly when the number of studies published is relatively small, replications are few and contradictory findings are frequent.

Addiction or excess: Much expectancy theory research is concerned more with excesses of a behaviour more than an addiction. Research may focus on ‘problematic behaviour’ (heavy smoking)


but not ‘loss of control’. Addiction involves the addict being unable to control their behaviour, in which case it is not clear what role expectancies play in the development of this loss of control.

Research support for link between expectancies and relapse: Study finding of effectiveness of nicotine patches, smoking cessation and relapse are inconsistent. Hurt et al found that using a patch did not improve cessation in adolescents whereas Moolchan et al found that patches did increase cessation success and reduce relapse rate, but only when accompanied by CBT.

Measuring Cognitive Factors: it is difficult to measure cognitive factors (expectancies/vicious cycle/self-efficacy) because you have to use self-report studies to find out about it so it will never be truly scientific evidence.

Gambling:

Biological Explanation:

Initiation:

Studies show that pathological gambling runs in families. Although many attribute this to learning theory, it is possible it is down to genetics as well.

Shah et al - twin study found evidence of genetic transmission of gambling in men.

Black et al – found that first-degree relatives of pathological gamblers were more likely to suffer from the addiction than more distant relatives (strong genetic link).

Alessi – found genetic predispositions for gambling may work indirectly through an ‘impulsivity’ trait (considered a significant predictor of sensation seeking behaviours).

However, inheritance of an ‘impulsivity’ gene only explains how people become addicted to risk-taking behaviours, but doesn’t explain why some become addicted to gambling while some to sky-diving. There is therefore an interaction between genes (‘impulsive’ traits) and environment (type of activities that are available).

Cavedini – compared 20 gambles to 40 controls on a decision making gambling task involving balancing immediate rewards with long term negative consequences. Significant difference between two groups – gamblers making a pattern of decisions associated with patients who have lower functioning pre-frontal cortex.

Wendy Slutske – looked at the concordance rates for about 5,000 MZ and DZ twins in relation to gambling addiction. Found that concordance for MZ twins was 2x DZ concordance and genetics were responsible for 64% overall gambling problems. However, she points out that it isn’t possible to isolate the genetic effects from environmental and social aspects, which are accountable for 36%. Instead, she describes a ‘perfect storm’ of inherited vulnerability and gambling role models (parents). Also focuses on men and women (previous research just men) and shows both are at risk.


Zuckerman – studied high and low sensation seekers. High sensation seekers have a low appreciation of risk and think of it more positively. He believes there are two reinforcers for gambling – the positive arousal during the time of risk of monetary loss and positive reinforcement of winning. Pathological gamblers need intense stimulation and excitement.

Blaszczynski - poor tolerance for boredom may contribute to repetitive gambling behaviour. Pathological gamblers had significantly higher boredom proneness scores than control group of non-gambler. No significant differences between different gambling styles.

This is intuitively a good explanation, as when people are bored they gamble, and some people need more stimulation than others and therefore gamble more. But Coventry and Brown found that horse-race gamblers were lower sensation seekers than a control, which opposes this explanation. However, they also found that casino gamblers were high sensation seekers, suggesting gambling is more complex and that there may be 2+ types of gamblers (Bonnaire et al).

Maintenance:

Pituitary-adrenal response: research suggests gambling is associated with underactive pituitary-adrenal response to gambling stimuli, as in if there is a physiological rush associated with the behaviour it is more likely to be maintained because of the activation of the dopamine reward system. The release of the dopamine may lead to them craving that rush again and therefore continuing gambling behaviour. Paris et al – measures gamblers’ cortisol (stress hormone) levels before/after watching a video of their addiction. And a video of neutral stimuli (rollercoaster ride). Recreational gamblers had significantly increased salivary cortisol levels after both, but addicts had no response to either.

Not the win that they play for, but the adrenaline from the near win.

Sensation-seeking: Zuckerman - claimed that there are individual differences in the need for optimal amounts of stimulation. Sensation seekers look for varied/novel experiences. High sensation-seekers have a lower appreciation of risk and anticipate arousal as more positive than do low sensation-seekers, and therefore more likely to gamble.

Meyer - carried out a repeated measures lab experiment with 10 male gamblers. The gamblers played 21 for money (experimental condition) or points (control). Also they were measuring heart rate and endocrine at a baseline, 30 minutes and 60 minutes into the game and also after playing. In the experimental condition, heart rate and cortisol levels were considerably raised by 30 minutes and continued to rise as a chemical indication stress/excitement).

Beck et al – vicious cycle: low mood can be relieved by addictive behaviour. Addiction leads to financial/social/health problems, which lead to a low mood, resetting the circle.

Relapse:

Boredom avoidance: the pathological gambler is seen as a person who needs this intense stimulation and excitement. Blaszczynski et al – poor tolerance for boredom may contribute to repetitive


gambling behaviour. Pathological gamblers had significantly higher boredom proneness scores than control group of non-gambler. No significant differences between different gambling styles.

Rational Decision Making: Relapse my occur if their rational decision making processes are compromised which will happen if there is lower functioning in the pre-frontal cortex (this is the same reason they start in the first place).

Cavedini – compared 20 gambles to 40 controls on a decision making gambling task involving balancing immediate rewards with long term negative consequences. Significant difference between two groups – gamblers making a pattern of decisions associated with patients who have lower functioning pre-frontal cortex.

Evaluation:

Positives:

Individual Differences: Genetics can explain why some people become addicted while others, with the same environmental pressures, do not. Some people are more vulnerable because of a genetic predisposition. This idea may also explain why some people are more resistant to treatment than others.

Sensation seeking: Bonnaire et al – tested the sensation-seeking explanation in 2 groups of French gambling addicts; one who played café games, another betting on horses. Those betting on horses had a significantly higher sensation-seeking score than the others. This led researchers to conclude that there are 2 clinically distinct subgroups of gamblers – one playing ‘active’ games, gambling for the arousal and another playing ‘passively’, to avoid boredom.

Implications of treatments: Having this knowledge may lead to us being able to warn people that they are at risk; e.g. if they have lowered functioning in the prefrontal cortex.

Used alongside the cognitive approach: Used this way it can give a more complex examination (e.g. – a low functioning pre-frontal cortex along with the cognitive symptom).

Biological explanation: pathological gamblers do suffer from physiological withdrawal symptoms which supports a biological model.

Negatives:

Reductionism: Biological explanations for addictions are generally reductionist; they reduce a complex phenomenon down to a relatively simple level of explanation. While this may have advantages (allowing researchers to study family genetics), it has its limitations. Influence of neurotransmitters such as dopamine is clearly important, but reducing addiction down to genes/chemicals ignores all other potential influences (irrational though process, social context).

Ignores other factors: Explaining an addiction in biological terms alone ignores the importance of external factors such as accessibility to gambling opportunities, incentives to gambling (peer


pressure/free bets) and alcohol provision while playing. Therefore, it is more likely that addiction is caused by biological dispositions and external factors.

Explanatory limitations: Biological explanations cannot explain why some types of gambling (online/video) are more addictive than others. Breen and Zimmerman - found that men and women who got hooked on video gambling became compulsive gamblers in around a year, while those addicted to betting on horses/sports took over 3.5 years before at risk to become addicted.

Deterministic: Ignores people’s decision making abilities – free will.

Small sample: Cavedini’s study (60 participants total) and therefore unrepresentative.

Learning Explanation:

Initiation:

Operant conditioning: proses that any behaviour that produces a consequences that the individual finds rewarding, then becomes more frequent. Griffiths argues that gamblers playing slot machines may become addicted because of the physiological rewards (getting a buzz from winning), psychological rewards (near miss), social rewards (peer praise) and financial rewards (if win). This may seem strange given that the gambler generally loses but, as Delfabbro and Winefield point out, gamblers are not always rational in their thinking, and greater weight may be given to the experience of winning.

Classical conditioning: secondary reinforcers are those things that precede or occur at the same time as the addiction itself. Glautier et al found that the sights and smells of a pub elicited the similar physiological responses as alcohol.

Maintenance:

Intermittent reinforcement: the operant conditioning model proposes that people continue to gamble because of the intermittent (occasional) reinforcement that is characteristic of most types of gambling. As a result, they become used to long periods without reward and their gambling behaviour is reinforced by the occasional pay-out.

Social approval: This type of behaviour may also be maintained because reinforcement is provided in the form of social approval from others. Lambos et al found that peers and family members of problem gamblers were more likely to approve of gambling. Respondents who received this form of reinforcement for their gambling not only gambled more than other respondents, but also more intended to continue doing so in the future.

Relapse:

Conditional cues: addicts learn (through classical conditioning) to associate other stimuli with their gambling behaviour (e.g. the sights and sound of a casino or the presence of other gamblers). These stimuli act as triggers for gambling because they have the ability to increase arousal. If, after a period


of absence, an individual comes into contact with one of these conditional cues, they are at a higher risk of relapse.

Approach-avoidance conflict: because gambling has both positive and negative consequences for the individual, they are motivated to approach and to avoid situations where gambling is involved. This creates an approach-avoidance conflict, where motivation fluctuates between wanting to gamble and wanting to stop. Whether or not the gambler will gamble when faced with an urge to do so is related to their ability to control the increased arousal and delay their need for reinforcement.

Lin - showed that high self-efficacy increases quit success in internet addicts.

Evaluation:

Positives:

Research applications: Blaszczynski and Nower - claim different pathways of gambling that predict the likelihood of treatment being successful. Gamblers in the ‘behaviourally conditioned’ pathway may have begun gambling because of exposure to gambling through role models or peer groups. They tend to show the least severe gamblers and gambling-associated difficulties of ant pathological gamblers, are motivated to enter treatment and are more likely to be successful in curbing their gambling as a result. However, a second subgroup tends to have accompanying anxiety and/or depression, a history of poor coping skills, as well as negative background experiences and life events. These factors produce an ‘emotionally vulnerable gambler’, who uses gambling primarily to relieve their aversive emotional states. Unlike the behaviourally conditioned group, the accompanying psychological dysfunctional in the emotionally vulnerable group makes them more resilient to change and necessitates treatment that addresses the underlying vulnerabilities as well as the gambling behaviour.

The significance of occasional reinforcement: Learning explanations propose that people become ‘hooked’ on specific activities (such as smoking/gambling) because when they engage in them it leads to some desired consequences (e.g. feeling less depressed). In real life this positive consequence is likely to be occasional rather than consistent, as smoking a cigarette (or engaging in gambling behaviour) will not always produce a desired positive mood state or relieve a negative one. As the world is an unpredictable place, organisms tend to learn adaptive behaviours that work to their advantage on average. Provided engaging in a particular behaviour produces the desired consequences now and then (e.g. making the person feel better), then a pattern of addictive behaviour will become established and maintained.

Negatives:

Can’t explain all forms: A problem for explanations of gambling based on operant conditioning is that it is difficult to apply the same principles to all different forms of gambling. For example, some forms of gambling have a short time-period between the behaviour and the consequences (e.g. scratch cards) whereas others (such as sports betting) have a much longer period between bet and outcome, which is also less to do with chance and more to do with the skill of the individual.

Fails to explain why only some people become addicted: This explanation of pathological gambling explains addiction in terms of the consequences of the gambling behaviour. Although this may


explain why some people initially take potentially addictive drugs or engage in potentially addictive behaviour, there are aspects of addiction that are not dealt with by this explanation. Although many people gamble at some time during their lives and experience the reinforcements associated with this behaviour, relatively few become addicts. This suggests, therefore, that there are other psychological factors involved in the transition from gambling behaviour to gambling addiction.

Cognitive Explanation:

Initiation:

Self-medication model: Gelkopf et al - proposes that individuals intentionally use different forms of pathological behaviour (e.g. alcohol, drugs, gambling) to treat the psychological symptoms from which they suffer. The particular activity an addict chooses is not selected at random, but tends to be one that is perceived as helping with a particular problem. For example, some activities may be chosen because they help the individual overcome anxiety, whereas others (gambling) appear to help with depression associated with poverty and so on. Gambling might not actually make things better, but needs only to be judged as doing so by the individual to become an addiction as the gambler expects good outcomes.

Casinos exploit the sight of others winning to encourage positive expectations about the success of gambling.

Rational choice theory: Becker and Murphy – people become addicts after weighing up the costs and benefits of the activity. Uses the concept of ‘utility’, weighing the costs against the benefits of an activity. From this perspective, addiction is experienced as an increase in consumption of ‘goods’ because the addicts have made a rational choice concerning their current and future ‘utility’ of their addiction. DOESN’T WORK FOR GAMBLING! Unless you include Griffiths study: gamblers have irrational thought processes.

Griffiths – examined scratch card gambling in adolescent males. 204 Birmingham boys aged 11 to 16 were given a questionnaire about their gambling. 10 children (12% of the gamblers who had brought the tickets themselves) met DSM-IV criteria for pathological gambling. Also, a significant relationship was found between parents buying scratch cards and children’s purchases (supporting expectancies – see their parent’s expectations and therefore think they will too).

Expectancy theory: heavier drinkers have shown to have more positive expectancies about the effects of alcohol compared to lighter drinkers

Self-efficacy theory: Bandura - refers to a belief in one’s self to organise and control any actions required to meet particular goals. Plays an important role in whether or not a person will start and addictive behaviour.

Maintenance:


Role of irrational beliefs: cognitive distortions or irrational beliefs play a role in the maintenance of pathological gambling specifically (Oei and Gordon). Despite the objective probability of failure related to any games based on chance, problem gamblers frequently have irrational perceptions about their ability to influence the outcomes of their gambling.

Cognitive distortions associated with gambling include the ‘gambler’s fallacy’, i.e. the belief that completely random events are influenced by recent events. For example, runs of losses will be equalled out by runs of wins. Illusions of control are demonstrated through the performance of superstitious behaviours, which gamblers believe helps them manipulate the outcome.

Also show exaggerated self-confidence in their ability to ‘beat the system’ and influence chances. This is part due to the different attributes that many gamblers make about their gambling, with success being attributed to their personal ability or skill, and failure attributed to chance factors, such as bad luck.

Cognitive bias in fruit machine gambling: Griffiths - set out to discover whether regular gamblers thought and behaved differently to non-regular gamblers. He compared 30 regular and 30 non-regular gamblers in terms of their verbalisations as they played a fruit machine (‘fruitskill’). Regular gamblers believed they were more skilful than they actually were, and were more likely to make irrational verbalisations during play (e.g. – ‘putting only a quid in bluffs the machine’). They tended to treat the machine as if it were a person (e.g. – ‘this ‘fruity’ isn't in a good mood’). Regular gamblers also explained away their losses by seeing ‘near misses’ as ‘near wins’, i.e. they weren’t constantly losing, but constantly ‘nearly winning’, something that justified their continuation.

Self-medication model: refer to initiation. Many smokers mention ‘stress release’ as a major reason for smoking.




Relapse:

Recall bias and the ‘just world’ hypothesis: pathological gamblers often suffer from a ‘recall bias’, i.e. the tendency to remember and overestimate wins while forgetting about, understanding or rationalising losses (Blanco et al). Consequently, a string of losses does not always act as a disincentive for future gambling. Such individual believe they will eventually be rewarded for their efforts and could be motivated to return on subsequent occasions because of a belief that they ‘deserve’ to win, having lost so often on previous occasions (the ‘just world hypothesis).






Evaluation:

Positives:

Research support: Li et al - provided research support for the self-medication model. They found that, compared to pathological gamblers who gambled for pure pleasure, pathological gamblers who gambled to escape the painful reality of life were significantly more likely to have other substance dependencies. They also found that these ‘self-medicating’ gamblers were less likely to commit crimes to finance their gambling behaviours compared with other types of pathological gamblers. Pathological gamblers motivated by self-medication usually have substitute means to satisfy their goal, whereas those who gamble for pure pleasure do not.

Implications for treatments: The evidence that there is more than one motivation for becoming a pathological gambler implies that there is more than one motivation for becoming a pathological gambler implies that there should be differing approaches to helping in their treatment, depending on their motivation for gambling. For example, for self-medicating gamblers, it might be more beneficial attempting to get them to quit gambling. As irrational beliefs such as the gambler’s fallacy play a key role in the initiation and maintenance of gambling, cognitive theory attempts to correct these cognitive errors, which in turn reduces the motivation to gamble.

Intervention: having this knowledge can allow us to intervene because we can advise parents to show children the negative effects of the gambling (losing) so that they do not develop these expectations.

Helps explain individual differences: as in, millions of people have gambled, but most are not addicted. This is explained because they do not have the faulty thought processes that addicts have.

Negatives:

Expectancy theories and publication bias: The focus of research into expectancy theory has largely been on positive research findings, with negative results receiving less attention. For example, studies have supported an association between expectancies and addictive behaviour but this constitutes a publication bias as the selective publication of positive results gives an


unrepresentative view of a particular research area, particularly when the number of studies published is relatively small, replications are few and contradictory findings are frequent.

Language: Attempts to understand the nature of addictions are clouded by the difficulties of obtaining objective data. Davies claims that addicts describe their addiction, when talking to heath worker or police, by using the language of addiction, i.e. their behaviour is out of control. However, when talking to peers, they use different language which suggests they are exercising preferences that are rational and understandable given their circumstances. This suggests that language off addicts serves an important function for the individual, i.e. may serve to absolve them of responsibility.

Opposing research: Despite the logic underlying cognitive explanations of pathological gambling, research suggests that possessing relevant knowledge does not make people less susceptible to cognitive distortions. For example, Benhsain and Ladouceur administrated a gambling-related cognitive scale to two groups of university students, one group trained in statistics and the other in a non-statistical field. They found no difference between the two groups in their susceptibility to irrational gambling-related cognition, but were just as accurate as non-gamblers in estimating the odds of winning.

Problems of cause and effect: The self-medication model argues that some form of psychological distress must precede drug use, as the one necessitates the use of the other. There is some evidence to support this, for example research has shown that a major depressive disorder is evident in the majority of pathological gamblers (Becona et al). However, this correlation between depression and gambling does not necessarily mean that depression is the cause of gambling. Indeed, it is equally possible that depression is a consequence of the personal and financial costs of pathological gambling.

Griffiths – found that regular players were capable of gambling on auto pilot and were therefore not thinking about what they were doing, suggesting the cognitive approach is not a major role in the maintenance of addiction.

addiction - models

Education