3.1: Addictive behaviours
There are many issues with studies that examine addictive behaviours:
Self reports:
Highly susceptible to social desirability bias, as addicts may lie about their worst behaviours.
Behaviour recall may be inaccurate with drug use.
Addicts may even lie about being ‘clean‘.
Validity issues:
Lab experiments do not mimic the conditions of actual addictive behaviour, making the study ungeneralisable.
For example, they avoid the social pressures and cognitive pressures of a real-life environment.
Many experiments are also done on animals and again not generalisable.
Ethical issues:
Researchers cannot ask participants to engage in addictive behaviours, especially chemically addictive ones, due to psychological and physical harm.
It may also be harmful to ask addicts about their behaviour, as it may cause them psychological harm and potentially relapse.
Sampling:
It is difficult to find active addicts, as many are in denial.
Often rehab centres are used to contact them, but these patients may share similar characteristics as they seek help, lowering generalisability.
Matched pairs are often used between the control and experimental condition, but this is again difficult as many of the control group may engage in addictive behaviours without an addiction (alcohol consumption).
Addictive behaviours can encompass both behaviours and drugs, but are most commonly associated with drugs. There are 10 categories in the DSM for drugs:
Alcohol, caffeine, cannabis, hallucinogens, inhalants, opioids, sedatives, stimulants, tobacco and others.
Gambling and internet gaming are the only behaviours viewed as addictive.
Other behaviours are noted as excessive behavioural patterns, but not included due to lack of peer reviewed evidence.
Examples are video games, exercise, shopping and sex.
Disorders are split into 2 categories:
Substance use disorders - addiction.
Substance induced disorders - intoxication, withdrawal and substance induced mental disorders.
Disorders are categorised as either mild, moderate or severe addiction based on how many symptoms out of a list of 11 they fulfil.
The DSM-5 has the issue of not labelling every potential addiction.
It has separate criteria for each of the ten categories, which allows for tailored treatment. Outside of this, there needs to be a separate criteria, especially for behavioural addictions.
Griffiths argued there are 6 criteria that need to be fulfilled for something to be labelled as an addiction.
These were intended for behavioural addictions, but can be applied to drug addictions as well.
He claims that addiction is a ‘biopsychosocial process‘, meaning it has many causes and influences and therefore cannot be diagnosed based on this.
He used his research on gambling to design these 6 criteria.
This refers to the activity becoming the most important thing in that person’s life and starts to dominate their thinking (preoccupation and cognitive distortion - similar to irrational thoughts from unit 1), feelings (cravings) and behaviour (decreased socialisation).
There is also reverse salience, where the addictive activity becomes the most important thing in a person’s life when they are prevented from engaging in the behaviour.
This occurs with less severe addictions, such as smoking.
An individual experiences a change in mood after they engage in the addictive behaviour. Examples include:
A ‘high‘ or ‘buzz‘.
A numbing.
This experience can even change based on the time. For example:
Smokers may smoke in the morning for the nicotine rush, but in the afternoon for it’s relaxant qualities.
This could be argued as expectation effects, meaning what a person wants is what they feel. Similar to placebo effect.
Therefore, the psychology overrules the physiology.
Addicts may use these consistent mood changes as a method of self-medicating.
Increasing amounts of the particular activity or drug are required to obtain the same effects.
Drug tolerances are common.
With behavioural addictions, this can vary from more of the activity needed to a stronger version of the activity.
For example, gamblers can either spend more money or spend more time gambling.
Griffith compared the heart rates of gamblers and non-gamblers after gambling, and found gamblers heart rates decreased faster due to their tolerance.
This occurs if the behaviour is stopped.
It includes:
Psychological effects, such as irritability and depression.
Physical effects, such as insomnia and sweating.
This occurs with behavioural addictions too:
Rosenthal and Lesieur found that 65% of pathological gamblers experienced 1 physical side effect during withdrawal.
This can be:
Interpersonal - conflict between the addict and others. This includes personal relationships, work or educational life, and other social or recreational activities (such as clubs).
Intrapsychic - conflict within the addict. Usually experienced as the addict tries to stop or cut down and finds they are unable to do so.
It occurs as the addict is choosing the activity, no matter long term consequences leading to inner and outer conflicts.
This refers to repeated returns to the addictive behaviour, even after years of non-engagement.
Even after years without a drug, extreme patterns manifest themselves quickly.
This happens with both behavioural and chemical addictions.
This is sometimes referred to as the pleasure chemical.
This originates from Olds and Milner (1954), who placed an electrode in a particular region of a rat’s brain and stimulating it every time a rat went into a certain corner of a box.
The rat then kept returning to this corner, as if the experience was pleasurable.
Further studies showed rats would press a lever to experience this stimulation, even forgoing other behaviours such as eating, which could be seen as similar to human addicts who only focus on their addictive behaviour.
This caused this area to become known as the pleasure centre.
It has been suggested that addictive behaviours, such as drug consumption, trigger the release of dopamine in the ventral tegmental area (VTA) of the brain, which leads to a sense a pleasure in the nucleus accumbens (NAc).
This is known as the reward pathway, and is a part of the mesolimbic pathway.
It has evolved to reward behaviours which are good to humans, such as eating, but responds to harmful behaviours such as drugs, and perhaps gambling and video gaming.
Research has shown that dopamine is released in both animals and humans in response to addictive substances and behaviours.
Joutsa et al. (2012) found dopamine levels were raised in participants performing in a gambling task regardless of whether the result was a win or not.
This disputes the idea slightly as dopamine as a ‘pleasure‘ neurotransmitter only, and here acts as indicator of how close you were to a reward, and encourages another attempt.
This could perhaps be linked to drugs, such as heroin, where addicts often attempt to trigger the first high again.
Boileau et al. (2003) found alcohol also increases dopamine levels in the brain.
The brain, and the entire human body, aims to maintain homeostasis - which is optimum functioning of the body.
To maintain this balance, the body employs negative feedback - the bodies response to return back to the optimum.
(A non-psychology example; glucagon is released when glucose is too low in the body to release more glucose, and insulin is released when glucose is too high in the body to store glucose)
In reference to the brain, negative feedback is known as neuroadaptation - the brain adapting to maintain this balance.
When drugs are consistently consumed, the brain’s natural balance is disturbed, and it will alter it’s structure to minimise the effect the drug has.
This is why higher amounts of a drug are required, known as tolerance. The brain adapts more and more to the drug, and more is required for the same effects.
This also explains withdrawal, as the brain adapts to life with the drug, and cannot continue normal functioning without it.
Another example is with D2 receptors, a specific receptor that dopamine attaches to.
With cocaine users, it was found they had less D2 receptors, and lower dopamine releases.
This would mean that cocaine users would require more cocaine to trigger the same pleasure response (tolerance) and would no longer produce enough dopamine once they stop consuming cocaine (withdrawal).
Volkow et al. (1997).
For example, nicotine can mimic a neurotransmitter (acetylcholine) which is associated with attention, memory, arousal and involuntary muscle movements.
This causes nicotine to increase response times.
Therefore, nAChR (neuronal nicotinic acetylcholine receptors) become less sensitive, which means more nicotine is needed for the same effects.
This is done as nAChR subtypes which desensitise the receptors over time increase.
When nicotine is no longer consumed, there is too little acetylcholine in the body. This causes the withdrawal symptoms.
Wittenberg et al. (2020) - https://pubmed.ncbi.nlm.nih.gov/32738308
A pleasure response is not enough to explain maintenance of addiction, or other characteristics such as withdrawal.
Volkow suggests that addictions cause changes in the frontal cortex which turns engaging in addictive behaviours into an addiction.
The frontal cortex is linked to high cognitive functions, such as decision-making and memory.
It is argued that addictive behaviours alter brain circuits involved in attention, and place too much attention to the behaviour and it’s cues (shown in attentional bias under cognitive biases explanation). This can explain salience.
However, many studies into brain damage and cognitive ability after addiction have cause and effect issues, as this impairment may have been present beforehand.
Robinson and Berridge (2003) argue that addicts want to engage in a behaviour, but they don’t necessarily enjoy or like it - similar to a compulsion.
Volkow et al. (1992) found cocaine addicts have frontal cortex abnormalities.
Bolla et al. (2003) found that cocaine addicts have impaired functioning in tasks that require the frontal cortex, such as decision making.
Wang et al. (1999) found addicts show an increase in frontal cortex activity when exposed again to the drugs or cues associated with their addiction.
Stokes et al. (2009) found no significant increase in dopamine levels in volunteers taking cannabis.
Yoder et al. (2007) found no consistent increase in dopamine levels in participants who consumed alcohol.
It does have some implications for internet and phone addictions addictions:
Levitin et al. (2015) attempting to focus on too many things at once causes a dopamine feedback loop.
This is caused as the dopamine pathway and frontal cortex prefer new, short bursts of information - therefore attempting to focus on multiple different things, such as a phone and TV, is rewarded.
Multitasking also uses up glucose stores faster, which has a negative effect on performance.
Dopamine is not just used as a reward:
Liberzon et al. (1999) found that the NAc had increased activation in PTSD-suffering war veterans who were exposed to battle sounds.
This suggests it also can initiate a fear response.
Joutsa et al. (2012) found dopamine levels were raised in participants performing in a gambling task regardless of whether the result was a win or not.
Here dopamine acts as an indicator of how close you were to a reward, and encourages another attempt. This could link it to behavioural addictions, such as gambling and gaming.
For this reason, Bell (2013) refers to dopamine as the ‘Kim Kardashian of neurotransmitters‘, stating the media uses dopamine as a blame for many issues, labelling it as causing sugar and firearm addictions.
Nutt et al. (2015) criticised the methodology of dopamine research.
Samples are often small, and the drug is given in different forms to how it would be in reality, such as a tablet.
They are also lab studies, which lowers their ecological validity.
Non-human animals are often used, which may avoid the ethical issues of studies but makes them hard to generalise.
It also cannot replicate behavioural addictions.
This also invokes the issue of how responsible addicts are for their own behaviour.
If the frontal lobe and mesolimbic pathways are altered, harming their decision making, do they have true free will? Addicts are often reported feeling powerless, supporting they idea they are not entirely responsible.
This can help by reducing stigma, as people will no longer see them as simply lacking willpower.
This theory does not explain the initiation of addiction.
It could be argued that addicts may have frontal lobe damage pre-addiction, and this may cause them to become addicted over others.
Longitudinal studies exploring this would be unethical.
Additionally, this theory does not explain why not all cocaine users become addicts:
Are some people more likely to release higher dopamine amounts (genetics)?
Are some people more likely to experience frontal lobe damage (genetics)?
Methadone mimics the dopamine effects of heroine, and is used as an agonist, while naltrexone is an antagonist and blocks dopamine.
NICE recommends both for usage.
Specifically the A1 variant of this gene has been linked to addiction:
This is due to it causing fewer dopamine receptors in the mesolimbic pathway (refer to dopamine explanation).
This may cause these individuals to compensate via engaging in addictive behaviours.
Comings et al. (1996a,b) found that 48.7% of smokers and ex-smokers carried the A1 gene variant, compared to 25.9% of non-addicts.
He also found that 50.9% of gamblers carried the A1 variant, compared to 25.9% of non-addicts.
This gene was originally identified using animal experiments.
ADH genes control the metabolism of alcohol into acetaldehyde via the alcohol dehydrogenase enzyme.
ALDH genes control the metabolism of alcohol into acetic acid and water via the acetaldehyde dehydrogenase enzyme.
Some variants of these genes can cause acetaldehyde concentrations in the body to increase, meaning alcohol consumption causes negative symptoms such as facial flushing and nausea.
This is found in higher concentrations of East Asian populations, which could explain the low alcoholism rates in these cultures.
Variations of ADH genes have been linked to an increased risk of alcoholism:
Some variations cause alcohol to be broken down slower, making people more likely to drink more and increase addiction likelihood.
Higuchi et al. (2006) found that lower activity variants were associated with an increased risk of alcohol dependence in oriental cultures.
Edenberg et al. (2006) found ADH4 affects alcoholism risk in European populations.
Goldman et al. (2005) concluded that addictions were moderately to highly heritable, and this heritability ranged from +39 for hallucinogens and +72 for cocaine.
Prescott and Kendler (1999) interviewed 3,516 male-male twin pairs born in Virginia between 1940-1974 on alcohol abuse and dependence.
They found that MZ twins agreed more than DZ twins, and concluded that 48-58% of alcohol addiction variance is genetic.
Additionally, they found environmental and social factors would influence drug initiation, whether addiction occurred was dependent on genetic factors.
Kendler et al. (2012) conducted a large scale adoption study in Sweden.
They found that children whose parents, siblings or half-siblings has a drug addiction had a significantly higher risk of drug addiction.
They noted this risk was increased if the adoptive family had environmental risk factors, such as criminal activity, divorce, alcohol problems or death.
Agrawal and Lynskey (2008) performed a systematic review into the genetic basis of addiction, focusing on twin studies.
They found the genetic influence of addiction ranged from 30-70%.
They also highlighted the importance of the interplay between genes and the environment.
Winokur et al. (1970), Reich et al. (1980) and Guze et al. (1986) are family studies which researched the idea of an alcoholic family, and found:
With no alcoholic relatives, men were 20% likely and women were 4% likely to become alcoholics.
With a first degree alcoholic relative, men were 27-54% likely and women were 6-17% likely to become alcoholics.
This suggests that gender is a major factor in alcoholism, likely due to socialisation.
This suggests disorders, such as addictions, are developed when genetic predispositions combine with environmental stressors.
This explains why not everyone with certain genes becomes an addict.
Kaufman et al. (2007) found that the serotonin transporter gene (SHTT) only has implications in addiction when it interacts with environmental factors, such as childhood neglect.
Genes could code for both of these traits, such as the D2D2 A1 version coding for initiation and maintenance, but ADH genes linked to maintenance.
Kenneth and Prescott’s study links to this, as it states that initiation is caused by other factors, but maintenance via genes.
Inheritance studies:
Family studies:
Will be highly influenced by the environment, especially when considering children and parents.
Highly subject to social desirability, as people may not want to admit their family issues.
Twin studies:
Twins often grow up in extremely similar environments, therefore this can have an impact.
If studied from children, valid consent becomes an issue.
Even MZ are not completely identical genetically - de novo mutations occur after the egg has split in utero.
Adoption studies:
May have high attrition rates as are longitudinal.
Valid consent of the children is an issue.
Can ignore the influence of the adoptive family's influence.
Additionally, many drug users use multiple drugs, which makes family trends difficult to research.
Drug availability may also be an issue, for example painkiller prescriptions change with drug developments, meaning different generations may not have access to them, preventing this from being investigated (cohort effects).
There is also a lack of research into behavioural addictions.
Regier et al. (1990) found addiction is often comorbid with mental disorders.
This leads to a cause and effect issue, as to whether mental illness caused the addiction, or addiction caused the mental illness.
In some cases, addiction may be a symptom and not the main problem.
Many other genes have been identified as potentially causing addiction:
The serotonin transporter gene (SHTT).
Rsu 1 gene was found to lower alcohol sensitivity in fruit flies. When brain imaging techniques tested for this in humans, they found a relationship between this gene and alcohol dependency.
Ojelade et al. (2015).
The range of genes identified, and the variance in types of addiction, means one gene cannot be labelled.
Additionally, there are likely many that are not yet identified, making genetic links hard to determine.
Addiction is also likely polygenic, meaning it is a trait multiple genes influence it, especially behavioural addictions.
For example, ADH variations coupled with the A1 variant of D2D2 would drastically increase the likelihood of alcoholism compared to one of these genes alone.
This theory suggests that an addict has a lack of control in developing their addiction, as they have no control or knowledge of their genes.
It also reduces addiction down to biological factors, ignoring the influence of social factors.
This could cause an addict less guilt and led society to have a more lenient view towards addicts, but it may also cause addicts to feel they have no control and therefore not believe themselves able to change.
Lewis (2015), a neuroscientist and ex-addict views the idea that addiction is a disease as harmful, as it can damage addicts self-esteem.
Instead, he suggested viewing brain changes as learning, which may help them overcome the addiction.
However, this could also explain why not everyone becomes an addict.
This could potentially cause addiction to be blamed entirely on genes, and with developments in genetic testing, cause people to be labelled addicts prematurely.
While this could lead to them avoiding addictive substances, it could also cause them to be stressed and feel societal judgement.
It also has implications for addicts who do not have these genes, who may be judged more harshly.
Drugs could be developed to help people with these genes overcome addiction, for example stimulating dopamine receptors for those with the D2D2 A1 variant or speeding up ADH activity in those with lower activity genes.
Additionally, genetic profiling can help with dosages for certain treatments, such as methadone or antabuse.
Genetic explanations often ignore the role of other causes:
Kendler et al. (2000) studied Swedish twin pairs born between 1910 and 1958, and found women born earlier were influenced less by genetic factors than those born in the later years of the study, which was 60%.
This suggests the changing attitudes towards women was also a factor.
Boardman et al. (2008) studied sibling and twin pairs, finding there was a strong genetic component in the onset of smoking, but daily smoking varied across schools.
He found that schools where the most popular students were smokers had the highest heritability rate, suggesting peer influence is also a factor.
Additionally, most of the studies above recognise the importance of social factors.
Drugs may also vary across cultures, as alcohol is normalised in the UK but not in Middle Eastern countries.
Additionally, cannabis is legal in some countries, making it’s usage normalised compared to the UK where it is illegal.
This suggests there are three dimensions relating to personality:
Extraversion - Introversion.
Extraverts are sociable and lively, while introverts are reserved and quiet.
Neuroticism - Stability.
Neurotics are moody and irritable, while stable people are more controlled and even-tempered.
Psychoticism - Normality.
Psychotics are impulsive, aggressive and creative and those normal are more careful.
This is measured using the Eysenck Personality Questionnaire (EPQ).
Based off this, Eysenck suggested a resource model of addiction, where addiction develops to fulfill a need relating to a person’s personality profile.
He performed a study with Gossop on over 200 drug addicts and found, compared to a control group, the addicts had higher neuroticism and psychoticism scores, but lower extraversion scores.
There is little evidence to suggest a link between these personality traits and addiction.
Francis’ systematic review (1996) found 10 studies with negative relationships between extraversion and addiction, 2 with a positive relationship and 12 with no significant relationship.
Impulsivity is a main trait of psychoticism, and entails the tendency to act on a whim with no considerations of consequences. It is suggested this could lead people to engage in addictive behaviours.
de Wit’s systematic review (2009) found that impulsivity was both a cause and effect of drug abuse.
Dalley (2007) found impulsive rats had increased cocaine intake compared to low impulsivity rats.
Stevens et al. (2014) found impulsive individuals were less successful in treatment programmes as they had higher dropout rates, and that they were more likely to drop out and less likely to maintain abstinence.
Eysenck argued that neurotic individuals would self-medicate to deal with their anxiety and moodiness.
Sinha’s research review (2001) highlighted the role of stress in the initiation and relapse of addiction
Baumeister (1997) found those with low self-esteem act in a self-defeating way, such as addictive behaviours to escape their negative feelings about themselves.
Mehroof and Griffiths (2010) found that neuroticism alongside other traits such as sensation seeking, anxiety and aggression are associated with online gaming addiction.
This could be seen as online gaming being used as the same way as drugs, to self-medicate.
Francis (1996) found addicts (nicotine, alcohol, heroin and benzodiazepines) had higher levels of psychoticism and neuroticism when compared to non-addict controls.
Madhuri (2012) found addicts had higher levels of psychoticism and neuroticism compared to non-drug addicts. They also found lower extraversion in addicts.
Sahasi et al. (1990) found high levels of psychoticism and neuroticism in a sample of Indian heroin addicts when compared to controls.
Most studies on this topic are correlational, and therefore cause and effect cannot be proven.
This is especially an issue as drugs can alter mental states.
There are some studies that could address this:
Dong et al. (2013) did a study on Chinese university students before they entered university and 2 years after their addiction to the internet was assessed.
They found higher psychoticism and neuroticism scores were linked to addiction, which suggests this causes addiction.
Cuomo et al. (2009) conducted semi-structured interviews on a sample of prisoners with or without substance abuse.
Addicts had higher scores on psychoticism and more impulsivity. They were also more likely to have multiple incarcerations, more juvenile detentions, more violent behaviour and one or more suicide attempts.
They were also more likely to have childhood trauma, which could be said to have caused their personality, or the drugs as self-medication.
This clouds the cause and effect issue.
However, this only studied prisoners, which is not a group representative of the whole population.
Kubicka et al. (2001) conducted a 24 year long longitudinal study in the Czech Republic.
They found extraversion, neuroticism and low conscientiousness were quite stable over time, and were good predictors of drinking and smoking.
Smoking was also highly predicted by low IQ, and gender.
This shows there are many factors at play, not just personality.
McNamara et al. (2010) found that in rats, impulsivity was a predictor of taking more cocaine but not heroine.
Stoess (1993) found that, across a range of different addictive activities, there was not a common pattern. Therefore this may differ across personalities.
Kerr (1996) argues there is no such thing as an addictive personality, as many of the traits associated can be in non-addicts, and many addicts don’t have these traits.
Franques at al.(2000) stated that addictive personalities are not considered within addictive psychology, and said there are multiple factors, with none being the solo determinant.
Many of these traits can be associated with dopamine functioning.
Buckhoitz et al. (2010) measured levels of impulsivity in non-addicts before using amphetamines.
They found those with higher impulsivity had a higher dopamine release and lower receptivity.
This means people with ‘addictive personalities‘ may simply respond better to drugs.
Some conditions increase the likelihood of addiction, and could therefore be seen as a symptom rather than a disorder in its own right.
Neuroticism is generally linked to mental illness, therefore leading to self-medication.
A common comorbidity is ASPD.
Messina et al. (1999) found that 40-50% of addicts have ASPD, and 90% of those with ASPD are addicts.
Trull et al. (2004) found a relationship between personality disorder symptoms and substance abuse. They concluded these symptoms preceded substance abuse.
This theory is greatly determinist, which brings many issues:
Can addicts be held accountable for their behaviour if they can’t control their addiction?
Will people with addictive personalities always be addicts?
While this could help people see that those with addiction cannot be blamed, and therefore discourage stigma, it could mean people with these personalities are assumed to be addicts.
It also means people may feel powerless to change themselves, as personality within this theory is fixed.
Kahneman and Tversky (1973) proposed humans have particular methods of quick decision making known as heuristics.
These are described as mental shortcuts, and often involve focusing on one aspect and ignoring others.
This can cause people to deviate from normal logical decisions, causing cognitive biases.
Two examples of heuristics identified by Kahneman and Tversky, are:
Representativeness:
A heuristic that stems from comparisons to mental representations, such as stereotypes.
For example, assuming a man wearing a suit is a lawyer.
Availability:
Based on how easy it is to think of an example:
For example, believing airplane crashes are common as they are most shown in the media, even though there are thousands of successful flights annually.
Keren and Lewis (1994) identified two gamblers fallacies:
Type one fallacy:
Based on the representativeness heuristic, where an individual uses a mental representation of short term odds (such as a coin flip is 50-50) to a long term event (such as an actual coin flip).
Therefore, after 10 coin flips that landed on heads, this fallacy would presume a ‘tails‘ is due and must be next, even though each individual flip is 50-50.
This can be applied to other gambling games, with a gambler feeling they are ‘due‘ a win.
Type two fallacy:
This is when a person believes a truly random system (such as a roulette wheel) is biased, and therefore has a pattern.
They then underestimate the amount of observations needed to detect this bias, and believe they have discovered a fake pattern (such as the wheel is more likely to land on 16).
They will then bet on this number.
The availability heuristic can also be applied:
Events that are more likely to be remembered are assumed to be more common.
This includes winning the lottery as only winners are advertised.
People therefore overestimate their odds of winning.
Gambling machines are designed to induce this heuristic, by playing bright lights, playing music and giving out coins individually to make the reward seem bigger.
The machines are also placed closer together so you are able to hear other people winning.
The sunk-cost fallacy, Slough et al. (2008):
This is a fallacy which causes a tendency to invest more future resources something which a person has already invested into, over something a person has not invested into.
This means once a gambler has begun gambling, they will be compelled to keep gambling until they have won to justify the money they have already spent.
Illusion of control:
Many gamblers will believe if they can control some aspects of gambling, such as a particular seat, machine or method of dice rolling.
Hindsight bias:
A gambler claiming they expected the results of a gamble and could have predicted the results.
This helps them to maintain control, and believe that gambling is a skill they need to improve.
Self-serving bias:
Gamblers attribute wins to internal causes, such as their own skill, and any losses to external factors such as luck or bias.
This helps them to feel as if losses are not their fault.
Attentional bias, Weinstein and Cox (2006):
This refers to when addicts pay attention to certain stimuli and ignore others, which can increase motivation to engage in the behaviour.
This is because the addict pays more attention to stimuli which relates to the addiction, such as the smell of smoke or advertisements.
This can be tested using a stroop test, with a participant asked to identify the colour of words shown to them. Some of these are words relating to their addiction.
Johnsen et al. (1997) compared active smokers, abstinent smokers and non-smokers on their response times and found smokers had the longest reaction times.
Griffiths (1994) compared the verbalisations of 30 gamblers to 30 non-regular gamblers.
He found regular gamblers showed more irrational verbalisations (14%-2.5%=11.5% difference).
He also found these verbalisations supported the existence of the heuristics and cognitive biases.
Joukhador et al (2003) developed a 65 item questionnaire called the Gambling Belief Questionnaire which covered a range of cognitive biases such as the gambler’s fallacy.
They then compared 56 problem gamblers to 52 social gamblers, and found that problem gamblers always scored higher.
Definition of social vs problem gamblers may have been an issue here.
While this theory describes the thoughts of gamblers, it does not explain them, as explanations should be able to predict behaviour in specific situations.
However, it is impossible to predict which cognitive bias or heuristic will be used in any situation, as individuals do not use them in a pattern.
Griffiths (2013) uses the example of when a triple rollover occurred in the UK national lottery, the media reported that the number 13 had come up fewer times than any other.
Individuals using the representative heuristic (gambler’s fallacy one) would assume that it was due to come up (via using short term odds on long term issues).
Individuals using the availability heuristic would assume it won’t come up as it is rarer.
Research into biases requires self-report techniques or observations.
Self-reports, such as questionnaires, allow gamblers to lie about their thoughts to rationalise them (demand characteristics), or to lie about the amount of gambling they participate in (social desirability).
Observations allow researcher bias to occur, as they have to label the cognitive bias shown.
A major criticism is that all people have heuristics, but not all people become gamblers or other behavioural addicts.
Therefore, why do some people become addicts and some don’t?
Baboushkin et al. (2001) suggests heuristics are often appropriate in everyday situations, but not in chance events, such as gambling, which causes gamblers issues.
If gambling fallacies develop due to gambling, why does a person start gambling?
If cognitive biases cause the gambling, then how do they develop?
There also may be an intervening variable, such as the social explanations.
These cognitive biases may not be generalisable across all groups:
Strough et al. (2008) found that older adults were less likely to fall for the sunk-cost fallacy than younger adults, although she was not investigating gambling behaviour specifically.
Ibanez et al. (2003) investigated gender differences in gambling, and found more men than women were exposed to gambling in adolescence.
Women had a later age of first bet, but a faster evolution of the disorder.
Men were more likely to have comorbid alcohol abuse and ASPD, while women were more likely to have emotional disorders and a history of physical abuse.
This makes it highly likely their cognitive biases differ.
Visschers et al. (2009) found that people often hold odd beliefs about probability and gamblers find it hard to understand information about risk, especially if presented in a probabilistic form.
This may be the cause of people relying on heuristics, which does not apply to drug addictions where the probability is easier to understand, making it a poor explanation for these addictions.
The measurement of cognitive biases in gamblers may have useful implications in treatments:
Griffiths (1994) did a small scale study by playing back gambler’s irrational verbalisations back to them (from his study comparing gamblers and non-gamblers irrational verbalisations) and found most were shocked by what they said.
This suggests it may be useful in cognitive restructuring, by allowing addicts to understand the irrationality of their thoughts, and be able to identify them as such.
Fortune and Goodie (2012) report that studies have varied in using this idea as part of CBT, while other have focused on correcting specific beliefs and biases.
Both methods have shown some success in treating gambling addiction, suggesting cognitions play a role in addiction.
This is often thought of as direct peer pressure, but in reality is often more subtle.
Behaviourists would believe addictions are either maintained by classical conditioning (association of the high from a drug with its smell) or operant conditioning (association of a drug with the pleasant experience it gives), but this does not explain why the behaviour is started.
To solve this, Bandura developed SLT based on his Bobo doll experiments. It states that behaviours, such as addiction, are learned socially and indirectly from those around an individual.
He believed there were two elements to this, a role model and vicarious (indirect reinforcement from observing others) reinforcement.
There are four key processes of SLT:
Attention - The individual must pay attention to their role model engaging in this behaviour in order to understand how to do it.
Retention - The observed behaviour must be remembered, including each of the steps.
Reproduction - The individual must be able to repeat the observed behaviour, including the physical ability that comes with practice, and the necessary equipment.
Motivation - The individual must be motivated to continue the behaviour (vicarious reinforcement).
Behaviour is more likely to be imitated if the role model is the same gender, similar age of older, powerful, high status, friendly and likeable.
Motivation does not just come from the role model, but the consequences they receive. There are three types of this:
Vicarious reinforcement - Reinforcement from watching another person be rewarded for a behaviour, often socially, such as having more friends.
Vicarious punishment - Stopping a behaviour after watching another person be punished for it, such as a punishment from a teacher.
Vicarious extinction - Stopping a behaviour after watching a person get no reward for it, such as another person being ignored while attempting to gain attention for smoking.
Social norms are the rules of behaviour within certain social groups, and vary across cultures and subcultures.
For example, the UK has a strong drinking culture whereas in Middle Eastern countries alcohol is illegal.
There has been research into how these norms can affect young people, with Bosari and Carey defining two types of norms:
Descriptive norms - An individual’s perception of how much others engage in a behaviour, for example believing people drink every weekend.
Injunctive norms - An individual’s perception of the approval of the behaviour, for example believing that everyone else believes this is acceptable.
Perkins and Berkowitz (1986) found that a high proportion of students surveyed believed that being intoxicated was only acceptable in limited circumstances, but a high proportion also believed that their peers had a more liberal attitude towards drinking.
Therefore, people believe that the people around them are drinking more than them.
Fergusson and Horwood found that peer attitudes toward drug use are highly predictive of adolescent drug use.
Simon-Morton and Farhat’s peer review into 40 prospective longitudinal studies on the same participants found all but two had a positive correlation (NOT CAUSAL) between peers and smoking.
Parents are also an important factor, providing a protective effect from peer influence via direct and indirect methods, such as stopping an individual seeing smoking friends and simply not smoking.
Parental smoking was also found to be a big influence on adolescent smoking.
Neighbors et al. found that social norms were the best predictor of alcohol consumption among US college students.
However, they were not the best predictor of alcohol related issues, such as fights and drunk driving, showing there may be other factors involved in directly developing an addiction.
There is a debate whether peers influence an individual to engage in behaviours (peer influence) or an individual chooses friends as they engage in the same behaviours (peer selection)
Ennett and Bauman found that non-smoking participants with smoker friends were more likely to smoke at a follow-up.
They also found evidence that their friendship groups altered in line with their smoking or non-smoking behaviour.
This suggests that both of these processes are important in developing addictions.
This aligns with cause and effect issues:
Do people pick friends because they share an addiction (peer selection)?
Are people influenced by already existing friends to initiate an addiction (peer influence)?
Kobus suggests other factors, such as family and neighbourhood, need to be considered as larger social contexts.
Hawkins found parental drug use is associated with an adolescents initiation and frequency of usage in an adolescent.
They also found that if parents have permissive attitudes towards drugs, children are more likely to use drugs.
Additionally, not all addictions are social, such as online gaming addictions.
Not all individuals friends with addicts develop an addiction - are some people immune or are there additional factors?
This theory also doesn’t explain the maintenance of additions.
An Institute of Medicine study found no evidence for peer influence in the development or maintenance of drug addictions.
This theory would expect addictions to stop as soon as socialisation with a group stopped, but this is not true, addictions outlast social groups.
Studies into this are mainly focused on adolescents and teens, and substances such as tobacco, alcohol or drugs.
There is little research into older individuals or behavioural addictions.
Perhaps this theory is the main cause in younger people, but not older.
Additionally, most studies are around 10 years old and could be out of date, especially with the rising influence of social media.
It could be said that young people who develop an addiction due to peer influences are not responsible for their actions, as they were unknowingly coerced.
However, it is hard to blame the addicts they model, as they may not have intended to be copied.
Additionally, telling young addicts that those around them caused their behaviour may make them feel they do not have free will.
SLT can also be applied here, with celebrities acting as role models, and vicarious reinforcement taking the role of how the character is treated within the media, such as gaining approval, being rich or famous.
Portrayal of smoking and alcohol use is extremely common.
Lyons et al. (2011, 2013) found that alcohol use is seen in 86% of movies and 40% of TV programmes.
Glantz et al. (2002) compared smoking in films from 1950-2002. They found a decrease in smoking from 1950-1982, in 2002 this then increased back to 1950 levels.
Although smoking has decreased generally and awareness of negative effects has increased, smoking in media has remained fairly constant.
This behaviour is also presented in a positive light.
Gunasekera et al. (2005) used content analysis to analyse the 87 of the top 200 movies of the last 20 years. They found that alcohol and tobacco use are common, and incidents of cannabis and other drug use were noted.
The main finding was addictions tended to portray addictions positively without negative consequences, which shows vicarious reinforcement.
Wellman et al. (2006) reviewed a number of studies on how exposure to tobacco advertising and smoking in the media effects individuals, and found increased positive attitudes doubled the chances of starting to smoke.
However, adverts are different to simple media exposure as they directly encourage smoking.
Hanewinkel et al. studied 2,346 teenagers (12-14 years old) from a range of European cultures who reported they had never drunk alcohol and did not intend to. 12 months later, 40% of the sample had tried alcohol and 9% had engaged in binge drinking.
A range of variables were controlled for, including personality characteristics and school performance, exposure to alcohol occurrences in films was associated with increased risk of drinking.
Derevensky et al. (2010) found that teenagers who are already gambling were more likely to be influenced by gambling advertisements.
The majority of research into drugs and media is correlational, and therefore causal statements cannot be made.
There are many possible causes for these correlations:
Media causes addictive behaviours - more addictive media = more addictive behaviour.
Addictive behaviour affects media consumption - more addictive behaviour = higher engagement in media which has addictive behaviour.
An intervening factor may be involved, such as peers influencing addictive behaviour and media consumption.
However, Pechmann and Shih (1999) used an experimental method - showing two versions of a clip, one with smoking and one without.
They found that those that watched the smoking version had increased positive smoking attitudes and increased intention to smoke.
The research also lacks population validity, as it is mostly conducted on adolescents.
For adults, Jamieson and Romer (2015) compared tobacco use on television with smoking rates of the US population. They controlled for factors such as cigarette price and found a positive correlation.
It could be argued that teens are more susceptible to media influences as they are still developing, or that the theory was developed for teens.
Additionally, it most often focuses on alcohol and smoking.
Atkinson et al. (2011) interviewed adolescents and found they were aware celebrity drinking stories may be exaggerated, and did not feel the media was a major influence on their behaviour. They instead said they found peers and parents to have more of a role.
However, it may be they are unaware of the role of the media.
It could be said that young people who develop an addiction due to the media are not responsible for their actions, as they were ‘programmed‘.
Additionally, telling young addicts that the media caused their behaviour may make them feel they do not have free will.
However, the media may have positive effects. Pechmann and Shih’s study also found that effects of watching smoking in the film was negated by showing an anti-smoking advert beforehand.
The media also report on negative consequences, such as Amy Winehouse’s death, and films show negative effects, which can act as vicarious punishment. Some examples are:
Trainspotting.
Media campaigns such as “Faces of Meth“ in the USA, which shows people before and after meth addictive.
There was a similar UK campaign to publish a photo of Rachel Whitear, a girl who died of an overdose in her flat at age 21.
The Smokefree Movies Project aims to eradicate positive depictions of smoking from movies, with Disney pledging to ban smoking in all films targeting youth audiences, unless it was to maintain historical accuracy.
Aversion therapy uses classical conditioning to associate the addictive behaviour (normally a chemical addiction) with an unpleasant stimulus.
This means the addictive behaviour will then cause an unpleasant response, causing them to hopefully avoid the behaviour.
Due to ethical and safety reasons, it is often only used with alcohol and sometimes smoking.
In the past, aversion therapy has been associated with conversion therapy, which is highly unethical.
It occurs in 3 steps:
A naturally unpleasant stimulus (unconditioned stimulus, UCS) produces a negative response (Unconditioned response, UCR).
The UCS is then paired with the addictive behaviour (neutral stimulus, NS).
This leads to a conditioned response (CR), with the NS becoming a conditioned stimulus (CS).
This therefore should cause the addictive substance to be associated with a negative stimulus.
Antabuse is a drug used as the unconditioned stimulus.
When mixed in alcohol, the disulfiram reaction occurs, which stops aldehyde dehydrogenase from breaking down acetaldehyde and causes it to build up in the bloodstream.
This occurs within 10 minutes of consumption and can last for a few hours.
This drug has a long half-life, meaning it can occur up to a week after it is last taken.
NICE (National Institute for Health and Care Excellence) advise antabuse can be given after withdrawal.
It starts at 200mg daily, but can increase if the reaction is not bad enough.
They should remain under supervision every two weeks for the first two months, then monthly for the four months after this.
Takers must also be careful to not accidentally consume alcohol in mouthwash or food.
This is less common than alcohol aversion therapy.
A person has a puff of a cigarette every 6 seconds.
This will make them associate smoking with this feelings of nausea.
Therefore, the UCS is not an actual stimulus, it is the UCR of discomfort after intensive smoking.
Antabuse:
Niederhofer and Staffen (2003) compared antabuse to a placebo and assessed patients using self-report methods for 90 days.
They found antabuse patients had significantly greater abstinence duration than the control.
Jorgensen et al. (2011) found that those who took antabuse had more days until relapse and fewer drinking days.
Rapid smoking:
Most research into it’s effectiveness is out-of-date and limited.
Hajek and Stead (2004) reviewed previous literature and found it to be an unproven method.
They said that many effectiveness studies have methodological issues.
However, they said there are enough indications of potential to warrant further research.
McRobbie (2007) carried out a study on 100 smokers, with one group performing rapid smoking and one watching a video about quitting smoking.
He found there was a significant decrease in their urge to smoke after a day and a week, but after 4 weeks this difference was no longer significant.
This means it may not be an effective long term technique, but could be seen as a short term way of kick starting quitting.
However, these studies have many methodological issues:
No randomised controlled trials:
This is a sourcing issue, as sourcing alcoholics must come from those who admit to be addicts which could leave out the majority. (Ellis, 2013)
Sample size:
Often small as addicts who are willing to participate in these trials are hard to find. This makes the study less generalisable. (Ellis, 2013)
Attrition rate:
This lowers the sample size again, but also suggests the drug is either not working, or causing to harmful side effects.
However, many addiction studies on addicts have high attrition rates due to relapse rates.
Few comparison studies:
Means that antabuse is only effective when compared to a placebo, but perhaps not more effective than any other treatment.
This could be attributed to the lack of other similar drugs, however antabuse should be compared to therapeutic and in-patient treatments. (Ellis, 2013)
Placebo studies:
These are difficult as the moment a patient drinks, they will be aware of whether they are the placebo or not based on whether they experience adverse effects.
This may lead some people to drink out of curiosity.
Additionally, some people require higher doses of antabuse, and therefore may not receive it’s full effects without testing.
Not longitudinal enough:
Studies need to continue over many years in order to properly show the effects of antabuse.
If antabuse ends alongside the experiment, then there will be no proof that the CR remains and is still effective.
Antabuse could be seen as not treating the root causes of addiction.
This is an issue as addiction is usually comorbid with other disorders, such as ASPD and anxiety. If these are not addressed, an addict may turn to another addiction to cope.
Additionally, cognitive biases will still remain, raising a person’s likelihood of addiction.
The disulfiram reaction effects are extremely unpleasant, and is the process of rapid smoking.
However, this can be argued as how the treatment is actually supposed to work, and valid consent would have been provided.
A more ethical alternative, covert sensitisation, is suggested.
This works with individuals being encouraged to imagine imagery of nausea when they have the urge to drink.
Kraft (2005) presents case studies showing that it is a quick and effective technique for many individuals, and is more ethical.
Side effects also have many ethical implications, as a person must suffer in order to get good effects.
Antabuse can cause nausea, diarrhea, and fatigue.
Many addicts will stop taking antabuse if they are stressed in order to drink again:
O’Farrell and Bayog (1986) suggests the usage of an Antabuse Contract, designed for marriages.
The alcoholic spouse agrees to take antabuse and abstain from alcohol, while the spouse records this intake on a calendar. Both agree to stop discussions about past or future drinking.
O’Farrell et al. (1998) found that alcoholics taking Antabuse outcomes were much improved with the usage of this contract.
An Antabuse implant has also been suggested, which are inserted into the lower abdomen under local anaesthetic and slowly release antabuse, preventing incompliance.
This is not recommended for use in the UK, and are not available on the NHS due to concerns over long-term effects and ethics as someone cannot choose to simply not take it.
It is still available in Eastern Europe, however, and people may travel there to get it implanted.
Antabuse treatment is often used as a condition for early release, which could be seen as coercive.
An example is in El Cajon, California. Defendants are offered a year in jail or a year of antabuse treatment.
Marco argues this is a cruel and unusual punishment, coercive, and is not valid consent as participants are not fully informed as the risks and effects of Antabuse.
Devlin (2008) in a telegraph article highlighted the increase in antabuse and other drug treatments in treating alcoholism, from £1.08 million in 1998 to £2.25 million in 2008.
It can be argued that this is worthwhile, as it avoids other costs of addictions, specifically alcoholism.
The No Quick Fix report (Centre for Social Justice, 2013) stated that alcoholism costs the taxpayer £21 billion a year, including by unemployment benefits, healthcare (estimated at around £3.5 billion a year for the NHS, which includes long term health issues, accidents, etc.), property damage, etc.
Additionally, addiction can cause many social problems, such as debt, crime and homelessness. Therefore, it’s treatment is necessary, and outweighs the costs of ethical issues.
However, the government is predicted to earn £10.4 billion from 2023-24 on tobacco taxes, and £13.1 billion on taxes on alcohol in 2023, according to the Office for Budget Security.
Antabuse, however, is estimated to have cost taxpayers around 1.5 million pounds in 2023, showing there may be less expensive alternatives.
Agonists are chemicals that bind to a post-synaptic receptor and activate that receptor to produce a response.
Methadone is a synthetic replacement for heroin, and mimics its effects without producing a high.
This is needed as dopamine receptors become lessened and less sensitive after long-term addiction, and less dopamine overall is released. Methadone activates dopamine receptors.
This is utilised to reduce and hopefully eliminate withdrawal symptoms which could cause relapse.
Methadone is used as a maintenance treatment - preventing withdrawal symptoms to reduce cravings and withdrawal symptoms.
NICE recommends an initial dose of 10-40 mg, which is raised by up to 10mg daily until no withdrawal symptoms are experienced.
This dose is then known as the maintenance dose, which is usually around 60-120 mg a day.
Eventually, detoxification should occur by reducing the methadone dosage until abstinence is achieved.
Methadone is normally given orally as a green liquid, but can also be given as an injection or a tablet.
Needles are avoided as they could be seen as a reminder of the past addiction, perhaps triggering relapse, but also due to the damage some heroin users have at normal injection points.
A doctor, nurse or pharmacist sees patients each day for the first three months, ensuring the dosage is correct, people do not take multiple doses or sell it on.
This continues until patients are trusted.
NICE recommends maintenance treatment alongside psychosocial support.
Antagonists bind to a receptor and block the usual function of a particular substance.
Naltrexone is often used in the abstinence stage of recovery from addiction, as it blocks the pleasurable effects of opioids and makes them less rewarding, therefore discouraging relapse.
NICE guidelines recommend naltrexone for people who have stopped using opioids, and those who are highly motivated.
It is available orally.
It can also be available for usage as a depot injection (injection with a liquid that causes slow release) or as an implant, however this is only approved for use in the US and Russia.
Naltrexone can also be offered in cases of alcohol addiction, and similarly after interventions and withdrawal have occurred.
It can be used for up to a six month period, and users should be kept under supervision to check they don’t use again.
NHMRC (National Health and Medical Research Council) suggest it can also be used for problem gamblers, although they admit more research is needed into this.
This is due to naltrexone blocking dopamine receptors, therefore preventing dopamine responses.
Methadone:
NICE assessed 31 reviews of methadone effectiveness, including 27 randomised controlled trials.
There were higher levels of treatment retention and lower rates of illicit opioid use for those using methadone over a placebo or no treatment.
Van den Brink and Haasen (2006) conducted a meta-analysis of studies on a range of treatment effectiveness and found that, if the dosage is adequate, methadone is effective as a maintenance drug.
Gowings et al. (2001) found that methadone programmes are very effective at reducing the social and physical harms associated with drug abuse, with the longer someone remains in treatment, the better their outcomes and the lower their chances of relapse.
It could be argued this is due to methadones longer lasting action, which allows a person to separate themselves from the negative effects of drug culture, and allowing them to achieve social, legal and financial security.
Naltrexone:
NICE reviewed 17 studies into naltrexone effectiveness for heroin addiction, and found conflicting results.
Many randomised control trials showed no significant difference between naltrexone and a control treatment for treatment programme retention.
However, once pooled they found naltrexone is associated with lower relapse rates in those who were highly motivated, and with closely monitored patients who were offered extra support.
Lahti et al. (2010) tested naltrexone effectiveness on a small sample of gambler’s, who were instructed to take it before gambling or when they felt the urge to do so.
They found decreases in gambling levels. However, there was no placebo comparison, so more research is necessary.
Buprenorphine:
This is an alternative drug for both methadone and naltrexone, as it acts as both an agonist and antagonist, by activating opiate receptors and blocking euphoria.
This drug also has a ceiling effect, meaning after a certain amount has been taken, taking anymore will not increase it’s effects. This could reduce the risk of overdose.
Marteau et al. (2015) analysed data over 15 years and found that buprenorphine was 6x safer than methadone.
However, methadone is still used in the UK as it has higher treatment retention rates.
Whelan and Remski (2012) argue this is because addicts prefer the feeling they get from methadone.
NICE also identified specific issues with research in this area:
Treatment protocols across different countries may differ, such as methadone dosage, support and monitoring received. This may cause issues with comparisons.
Studies are not also longitudinal, and relapses can occur months or years after abstinence.
Attrition is common due to the social and psychological problems addicts often experience.
Both drugs can be seen as quick fix to addiction, as they do not treat the root cause which could be a variety of social, financial and mental issues such as PTSD.
This could be due to medications being cheaper.
This may lead a person to not receive adequate treatment, and replace their drug addiction with other behaviours, such as a behavioural addiction.
Methadone:
It can react with other drugs, such as alcohol and antidepressants to cause respiratory problems. This is a major issue as heroin use may have been to cope with depression, so treating both may become an issue.
Overdose can occur if combined with other drugs, with the UK Office for National Statistics reporting 640 deaths caused by methadone in 2022.
Additionally, it could be argued that methadone simply creates another addiction, and people may stay on it for prolonged periods of time, with detoxification and eventual abstinence being a struggle.
It also has many side effects, such as hallucinations and confusion, which could drive a person to return to heroin.
Naltrexone:
Has a greater risk of overdose, as individuals may take more of a drug to feel the effects over the naltrexone.
People addicted while taking naltrexone need to have their liver functioning monitored, and be monitored for withdrawal symptoms as naltrexone can displace opioids still in the system from their receptor.
It also has many serious side effects, such as seizures and anxiety, which could drive a person back to opioids.
Additionally, addicts who are jailed could be coerced into treatment programmes, such as these medications being a parole condition.
This could lead to free will issues, but also decreases the likelihood of treatment being effective.
However, Brecht et al. found that patients coerced performed equally well in methadone treatment as those who volunteered, suggesting this may be beneficial.
A report by the Centre for Policy studies (Gyngell, 2011) argued that methadone was an expensive failure, due to the cost of medication and drug addicts on benefits.
They suggested that rehabilitation units would be more effective.
This could be seen as akin to imprisonment.
The charity Drugscope (Doward, 2011) disputed this claim, saying the article overestimated the cost of methadone.
They highlighted how the National Audit Office described methadone as good value for money for taxpayers, and methadone users are able to function in society due to methadone making their addiction manageable.
The National Treatment Agency suggests that treating heroin users with methadone has an immediate positive effect by reducing criminality, suggesting reoffending rates are halved when addicts are in treatment.
However, the Centre for Policy studies (Gyngell, 2011) claimed drug related reoffending has continued to rise despite methadone availability.
Methadone availability, however, has nothing to do with whether people actually take it, and drug related reoffending is general to all drugs, not just heroin.
Another issue is the setting up of methadone programmes in certain areas, which is feared to increase crime and antisocial behaviour due to an increase in addicts.
Boyd et al. (2012) researched treatment centres in Baltimore and found that crime rates were similar to the surrounding areas.
However, drug abuse could be seen as a symptom of wider societal issues, as the The Advisory Council for the Misuse of Drugs report, ‘Drug Misuse and the Environment‘ (1998) argues.
Deprivation is associated with lower age of first use, progression to dependence, intravenous drug use, risky use, health and social complications due to use and criminal involvement.
These people are less likely to get treatment, have lower chances of overcoming drug use, and may earn money from drug dealing.
Therefore, programmes should focus on preventing initiation, and outreach for members of these communities.
Likely, this is not done as root causes are harder to treat by politicians, and quick fixes look better on campaign trails.
In 2022, the NHS spent £3.3 million on methadone, and drug abuse is estimated to cost around £20 billion according to the PM.
Methadone further benefits society by allowing for reintegration.
There are many issues with studies that examine addictive behaviours:
Self reports:
Highly susceptible to social desirability bias, as addicts may lie about their worst behaviours.
Behaviour recall may be inaccurate with drug use.
Addicts may even lie about being ‘clean‘.
Validity issues:
Lab experiments do not mimic the conditions of actual addictive behaviour, making the study ungeneralisable.
For example, they avoid the social pressures and cognitive pressures of a real-life environment.
Many experiments are also done on animals and again not generalisable.
Ethical issues:
Researchers cannot ask participants to engage in addictive behaviours, especially chemically addictive ones, due to psychological and physical harm.
It may also be harmful to ask addicts about their behaviour, as it may cause them psychological harm and potentially relapse.
Sampling:
It is difficult to find active addicts, as many are in denial.
Often rehab centres are used to contact them, but these patients may share similar characteristics as they seek help, lowering generalisability.
Matched pairs are often used between the control and experimental condition, but this is again difficult as many of the control group may engage in addictive behaviours without an addiction (alcohol consumption).
Addictive behaviours can encompass both behaviours and drugs, but are most commonly associated with drugs. There are 10 categories in the DSM for drugs:
Alcohol, caffeine, cannabis, hallucinogens, inhalants, opioids, sedatives, stimulants, tobacco and others.
Gambling and internet gaming are the only behaviours viewed as addictive.
Other behaviours are noted as excessive behavioural patterns, but not included due to lack of peer reviewed evidence.
Examples are video games, exercise, shopping and sex.
Disorders are split into 2 categories:
Substance use disorders - addiction.
Substance induced disorders - intoxication, withdrawal and substance induced mental disorders.
Disorders are categorised as either mild, moderate or severe addiction based on how many symptoms out of a list of 11 they fulfil.
The DSM-5 has the issue of not labelling every potential addiction.
It has separate criteria for each of the ten categories, which allows for tailored treatment. Outside of this, there needs to be a separate criteria, especially for behavioural addictions.
Griffiths argued there are 6 criteria that need to be fulfilled for something to be labelled as an addiction.
These were intended for behavioural addictions, but can be applied to drug addictions as well.
He claims that addiction is a ‘biopsychosocial process‘, meaning it has many causes and influences and therefore cannot be diagnosed based on this.
He used his research on gambling to design these 6 criteria.
This refers to the activity becoming the most important thing in that person’s life and starts to dominate their thinking (preoccupation and cognitive distortion - similar to irrational thoughts from unit 1), feelings (cravings) and behaviour (decreased socialisation).
There is also reverse salience, where the addictive activity becomes the most important thing in a person’s life when they are prevented from engaging in the behaviour.
This occurs with less severe addictions, such as smoking.
An individual experiences a change in mood after they engage in the addictive behaviour. Examples include:
A ‘high‘ or ‘buzz‘.
A numbing.
This experience can even change based on the time. For example:
Smokers may smoke in the morning for the nicotine rush, but in the afternoon for it’s relaxant qualities.
This could be argued as expectation effects, meaning what a person wants is what they feel. Similar to placebo effect.
Therefore, the psychology overrules the physiology.
Addicts may use these consistent mood changes as a method of self-medicating.
Increasing amounts of the particular activity or drug are required to obtain the same effects.
Drug tolerances are common.
With behavioural addictions, this can vary from more of the activity needed to a stronger version of the activity.
For example, gamblers can either spend more money or spend more time gambling.
Griffith compared the heart rates of gamblers and non-gamblers after gambling, and found gamblers heart rates decreased faster due to their tolerance.
This occurs if the behaviour is stopped.
It includes:
Psychological effects, such as irritability and depression.
Physical effects, such as insomnia and sweating.
This occurs with behavioural addictions too:
Rosenthal and Lesieur found that 65% of pathological gamblers experienced 1 physical side effect during withdrawal.
This can be:
Interpersonal - conflict between the addict and others. This includes personal relationships, work or educational life, and other social or recreational activities (such as clubs).
Intrapsychic - conflict within the addict. Usually experienced as the addict tries to stop or cut down and finds they are unable to do so.
It occurs as the addict is choosing the activity, no matter long term consequences leading to inner and outer conflicts.
This refers to repeated returns to the addictive behaviour, even after years of non-engagement.
Even after years without a drug, extreme patterns manifest themselves quickly.
This happens with both behavioural and chemical addictions.
This is sometimes referred to as the pleasure chemical.
This originates from Olds and Milner (1954), who placed an electrode in a particular region of a rat’s brain and stimulating it every time a rat went into a certain corner of a box.
The rat then kept returning to this corner, as if the experience was pleasurable.
Further studies showed rats would press a lever to experience this stimulation, even forgoing other behaviours such as eating, which could be seen as similar to human addicts who only focus on their addictive behaviour.
This caused this area to become known as the pleasure centre.
It has been suggested that addictive behaviours, such as drug consumption, trigger the release of dopamine in the ventral tegmental area (VTA) of the brain, which leads to a sense a pleasure in the nucleus accumbens (NAc).
This is known as the reward pathway, and is a part of the mesolimbic pathway.
It has evolved to reward behaviours which are good to humans, such as eating, but responds to harmful behaviours such as drugs, and perhaps gambling and video gaming.
Research has shown that dopamine is released in both animals and humans in response to addictive substances and behaviours.
Joutsa et al. (2012) found dopamine levels were raised in participants performing in a gambling task regardless of whether the result was a win or not.
This disputes the idea slightly as dopamine as a ‘pleasure‘ neurotransmitter only, and here acts as indicator of how close you were to a reward, and encourages another attempt.
This could perhaps be linked to drugs, such as heroin, where addicts often attempt to trigger the first high again.
Boileau et al. (2003) found alcohol also increases dopamine levels in the brain.
The brain, and the entire human body, aims to maintain homeostasis - which is optimum functioning of the body.
To maintain this balance, the body employs negative feedback - the bodies response to return back to the optimum.
(A non-psychology example; glucagon is released when glucose is too low in the body to release more glucose, and insulin is released when glucose is too high in the body to store glucose)
In reference to the brain, negative feedback is known as neuroadaptation - the brain adapting to maintain this balance.
When drugs are consistently consumed, the brain’s natural balance is disturbed, and it will alter it’s structure to minimise the effect the drug has.
This is why higher amounts of a drug are required, known as tolerance. The brain adapts more and more to the drug, and more is required for the same effects.
This also explains withdrawal, as the brain adapts to life with the drug, and cannot continue normal functioning without it.
Another example is with D2 receptors, a specific receptor that dopamine attaches to.
With cocaine users, it was found they had less D2 receptors, and lower dopamine releases.
This would mean that cocaine users would require more cocaine to trigger the same pleasure response (tolerance) and would no longer produce enough dopamine once they stop consuming cocaine (withdrawal).
Volkow et al. (1997).
For example, nicotine can mimic a neurotransmitter (acetylcholine) which is associated with attention, memory, arousal and involuntary muscle movements.
This causes nicotine to increase response times.
Therefore, nAChR (neuronal nicotinic acetylcholine receptors) become less sensitive, which means more nicotine is needed for the same effects.
This is done as nAChR subtypes which desensitise the receptors over time increase.
When nicotine is no longer consumed, there is too little acetylcholine in the body. This causes the withdrawal symptoms.
Wittenberg et al. (2020) - https://pubmed.ncbi.nlm.nih.gov/32738308
A pleasure response is not enough to explain maintenance of addiction, or other characteristics such as withdrawal.
Volkow suggests that addictions cause changes in the frontal cortex which turns engaging in addictive behaviours into an addiction.
The frontal cortex is linked to high cognitive functions, such as decision-making and memory.
It is argued that addictive behaviours alter brain circuits involved in attention, and place too much attention to the behaviour and it’s cues (shown in attentional bias under cognitive biases explanation). This can explain salience.
However, many studies into brain damage and cognitive ability after addiction have cause and effect issues, as this impairment may have been present beforehand.
Robinson and Berridge (2003) argue that addicts want to engage in a behaviour, but they don’t necessarily enjoy or like it - similar to a compulsion.
Volkow et al. (1992) found cocaine addicts have frontal cortex abnormalities.
Bolla et al. (2003) found that cocaine addicts have impaired functioning in tasks that require the frontal cortex, such as decision making.
Wang et al. (1999) found addicts show an increase in frontal cortex activity when exposed again to the drugs or cues associated with their addiction.
Stokes et al. (2009) found no significant increase in dopamine levels in volunteers taking cannabis.
Yoder et al. (2007) found no consistent increase in dopamine levels in participants who consumed alcohol.
It does have some implications for internet and phone addictions addictions:
Levitin et al. (2015) attempting to focus on too many things at once causes a dopamine feedback loop.
This is caused as the dopamine pathway and frontal cortex prefer new, short bursts of information - therefore attempting to focus on multiple different things, such as a phone and TV, is rewarded.
Multitasking also uses up glucose stores faster, which has a negative effect on performance.
Dopamine is not just used as a reward:
Liberzon et al. (1999) found that the NAc had increased activation in PTSD-suffering war veterans who were exposed to battle sounds.
This suggests it also can initiate a fear response.
Joutsa et al. (2012) found dopamine levels were raised in participants performing in a gambling task regardless of whether the result was a win or not.
Here dopamine acts as an indicator of how close you were to a reward, and encourages another attempt. This could link it to behavioural addictions, such as gambling and gaming.
For this reason, Bell (2013) refers to dopamine as the ‘Kim Kardashian of neurotransmitters‘, stating the media uses dopamine as a blame for many issues, labelling it as causing sugar and firearm addictions.
Nutt et al. (2015) criticised the methodology of dopamine research.
Samples are often small, and the drug is given in different forms to how it would be in reality, such as a tablet.
They are also lab studies, which lowers their ecological validity.
Non-human animals are often used, which may avoid the ethical issues of studies but makes them hard to generalise.
It also cannot replicate behavioural addictions.
This also invokes the issue of how responsible addicts are for their own behaviour.
If the frontal lobe and mesolimbic pathways are altered, harming their decision making, do they have true free will? Addicts are often reported feeling powerless, supporting they idea they are not entirely responsible.
This can help by reducing stigma, as people will no longer see them as simply lacking willpower.
This theory does not explain the initiation of addiction.
It could be argued that addicts may have frontal lobe damage pre-addiction, and this may cause them to become addicted over others.
Longitudinal studies exploring this would be unethical.
Additionally, this theory does not explain why not all cocaine users become addicts:
Are some people more likely to release higher dopamine amounts (genetics)?
Are some people more likely to experience frontal lobe damage (genetics)?
Methadone mimics the dopamine effects of heroine, and is used as an agonist, while naltrexone is an antagonist and blocks dopamine.
NICE recommends both for usage.
Specifically the A1 variant of this gene has been linked to addiction:
This is due to it causing fewer dopamine receptors in the mesolimbic pathway (refer to dopamine explanation).
This may cause these individuals to compensate via engaging in addictive behaviours.
Comings et al. (1996a,b) found that 48.7% of smokers and ex-smokers carried the A1 gene variant, compared to 25.9% of non-addicts.
He also found that 50.9% of gamblers carried the A1 variant, compared to 25.9% of non-addicts.
This gene was originally identified using animal experiments.
ADH genes control the metabolism of alcohol into acetaldehyde via the alcohol dehydrogenase enzyme.
ALDH genes control the metabolism of alcohol into acetic acid and water via the acetaldehyde dehydrogenase enzyme.
Some variants of these genes can cause acetaldehyde concentrations in the body to increase, meaning alcohol consumption causes negative symptoms such as facial flushing and nausea.
This is found in higher concentrations of East Asian populations, which could explain the low alcoholism rates in these cultures.
Variations of ADH genes have been linked to an increased risk of alcoholism:
Some variations cause alcohol to be broken down slower, making people more likely to drink more and increase addiction likelihood.
Higuchi et al. (2006) found that lower activity variants were associated with an increased risk of alcohol dependence in oriental cultures.
Edenberg et al. (2006) found ADH4 affects alcoholism risk in European populations.
Goldman et al. (2005) concluded that addictions were moderately to highly heritable, and this heritability ranged from +39 for hallucinogens and +72 for cocaine.
Prescott and Kendler (1999) interviewed 3,516 male-male twin pairs born in Virginia between 1940-1974 on alcohol abuse and dependence.
They found that MZ twins agreed more than DZ twins, and concluded that 48-58% of alcohol addiction variance is genetic.
Additionally, they found environmental and social factors would influence drug initiation, whether addiction occurred was dependent on genetic factors.
Kendler et al. (2012) conducted a large scale adoption study in Sweden.
They found that children whose parents, siblings or half-siblings has a drug addiction had a significantly higher risk of drug addiction.
They noted this risk was increased if the adoptive family had environmental risk factors, such as criminal activity, divorce, alcohol problems or death.
Agrawal and Lynskey (2008) performed a systematic review into the genetic basis of addiction, focusing on twin studies.
They found the genetic influence of addiction ranged from 30-70%.
They also highlighted the importance of the interplay between genes and the environment.
Winokur et al. (1970), Reich et al. (1980) and Guze et al. (1986) are family studies which researched the idea of an alcoholic family, and found:
With no alcoholic relatives, men were 20% likely and women were 4% likely to become alcoholics.
With a first degree alcoholic relative, men were 27-54% likely and women were 6-17% likely to become alcoholics.
This suggests that gender is a major factor in alcoholism, likely due to socialisation.
This suggests disorders, such as addictions, are developed when genetic predispositions combine with environmental stressors.
This explains why not everyone with certain genes becomes an addict.
Kaufman et al. (2007) found that the serotonin transporter gene (SHTT) only has implications in addiction when it interacts with environmental factors, such as childhood neglect.
Genes could code for both of these traits, such as the D2D2 A1 version coding for initiation and maintenance, but ADH genes linked to maintenance.
Kenneth and Prescott’s study links to this, as it states that initiation is caused by other factors, but maintenance via genes.
Inheritance studies:
Family studies:
Will be highly influenced by the environment, especially when considering children and parents.
Highly subject to social desirability, as people may not want to admit their family issues.
Twin studies:
Twins often grow up in extremely similar environments, therefore this can have an impact.
If studied from children, valid consent becomes an issue.
Even MZ are not completely identical genetically - de novo mutations occur after the egg has split in utero.
Adoption studies:
May have high attrition rates as are longitudinal.
Valid consent of the children is an issue.
Can ignore the influence of the adoptive family's influence.
Additionally, many drug users use multiple drugs, which makes family trends difficult to research.
Drug availability may also be an issue, for example painkiller prescriptions change with drug developments, meaning different generations may not have access to them, preventing this from being investigated (cohort effects).
There is also a lack of research into behavioural addictions.
Regier et al. (1990) found addiction is often comorbid with mental disorders.
This leads to a cause and effect issue, as to whether mental illness caused the addiction, or addiction caused the mental illness.
In some cases, addiction may be a symptom and not the main problem.
Many other genes have been identified as potentially causing addiction:
The serotonin transporter gene (SHTT).
Rsu 1 gene was found to lower alcohol sensitivity in fruit flies. When brain imaging techniques tested for this in humans, they found a relationship between this gene and alcohol dependency.
Ojelade et al. (2015).
The range of genes identified, and the variance in types of addiction, means one gene cannot be labelled.
Additionally, there are likely many that are not yet identified, making genetic links hard to determine.
Addiction is also likely polygenic, meaning it is a trait multiple genes influence it, especially behavioural addictions.
For example, ADH variations coupled with the A1 variant of D2D2 would drastically increase the likelihood of alcoholism compared to one of these genes alone.
This theory suggests that an addict has a lack of control in developing their addiction, as they have no control or knowledge of their genes.
It also reduces addiction down to biological factors, ignoring the influence of social factors.
This could cause an addict less guilt and led society to have a more lenient view towards addicts, but it may also cause addicts to feel they have no control and therefore not believe themselves able to change.
Lewis (2015), a neuroscientist and ex-addict views the idea that addiction is a disease as harmful, as it can damage addicts self-esteem.
Instead, he suggested viewing brain changes as learning, which may help them overcome the addiction.
However, this could also explain why not everyone becomes an addict.
This could potentially cause addiction to be blamed entirely on genes, and with developments in genetic testing, cause people to be labelled addicts prematurely.
While this could lead to them avoiding addictive substances, it could also cause them to be stressed and feel societal judgement.
It also has implications for addicts who do not have these genes, who may be judged more harshly.
Drugs could be developed to help people with these genes overcome addiction, for example stimulating dopamine receptors for those with the D2D2 A1 variant or speeding up ADH activity in those with lower activity genes.
Additionally, genetic profiling can help with dosages for certain treatments, such as methadone or antabuse.
Genetic explanations often ignore the role of other causes:
Kendler et al. (2000) studied Swedish twin pairs born between 1910 and 1958, and found women born earlier were influenced less by genetic factors than those born in the later years of the study, which was 60%.
This suggests the changing attitudes towards women was also a factor.
Boardman et al. (2008) studied sibling and twin pairs, finding there was a strong genetic component in the onset of smoking, but daily smoking varied across schools.
He found that schools where the most popular students were smokers had the highest heritability rate, suggesting peer influence is also a factor.
Additionally, most of the studies above recognise the importance of social factors.
Drugs may also vary across cultures, as alcohol is normalised in the UK but not in Middle Eastern countries.
Additionally, cannabis is legal in some countries, making it’s usage normalised compared to the UK where it is illegal.
This suggests there are three dimensions relating to personality:
Extraversion - Introversion.
Extraverts are sociable and lively, while introverts are reserved and quiet.
Neuroticism - Stability.
Neurotics are moody and irritable, while stable people are more controlled and even-tempered.
Psychoticism - Normality.
Psychotics are impulsive, aggressive and creative and those normal are more careful.
This is measured using the Eysenck Personality Questionnaire (EPQ).
Based off this, Eysenck suggested a resource model of addiction, where addiction develops to fulfill a need relating to a person’s personality profile.
He performed a study with Gossop on over 200 drug addicts and found, compared to a control group, the addicts had higher neuroticism and psychoticism scores, but lower extraversion scores.
There is little evidence to suggest a link between these personality traits and addiction.
Francis’ systematic review (1996) found 10 studies with negative relationships between extraversion and addiction, 2 with a positive relationship and 12 with no significant relationship.
Impulsivity is a main trait of psychoticism, and entails the tendency to act on a whim with no considerations of consequences. It is suggested this could lead people to engage in addictive behaviours.
de Wit’s systematic review (2009) found that impulsivity was both a cause and effect of drug abuse.
Dalley (2007) found impulsive rats had increased cocaine intake compared to low impulsivity rats.
Stevens et al. (2014) found impulsive individuals were less successful in treatment programmes as they had higher dropout rates, and that they were more likely to drop out and less likely to maintain abstinence.
Eysenck argued that neurotic individuals would self-medicate to deal with their anxiety and moodiness.
Sinha’s research review (2001) highlighted the role of stress in the initiation and relapse of addiction
Baumeister (1997) found those with low self-esteem act in a self-defeating way, such as addictive behaviours to escape their negative feelings about themselves.
Mehroof and Griffiths (2010) found that neuroticism alongside other traits such as sensation seeking, anxiety and aggression are associated with online gaming addiction.
This could be seen as online gaming being used as the same way as drugs, to self-medicate.
Francis (1996) found addicts (nicotine, alcohol, heroin and benzodiazepines) had higher levels of psychoticism and neuroticism when compared to non-addict controls.
Madhuri (2012) found addicts had higher levels of psychoticism and neuroticism compared to non-drug addicts. They also found lower extraversion in addicts.
Sahasi et al. (1990) found high levels of psychoticism and neuroticism in a sample of Indian heroin addicts when compared to controls.
Most studies on this topic are correlational, and therefore cause and effect cannot be proven.
This is especially an issue as drugs can alter mental states.
There are some studies that could address this:
Dong et al. (2013) did a study on Chinese university students before they entered university and 2 years after their addiction to the internet was assessed.
They found higher psychoticism and neuroticism scores were linked to addiction, which suggests this causes addiction.
Cuomo et al. (2009) conducted semi-structured interviews on a sample of prisoners with or without substance abuse.
Addicts had higher scores on psychoticism and more impulsivity. They were also more likely to have multiple incarcerations, more juvenile detentions, more violent behaviour and one or more suicide attempts.
They were also more likely to have childhood trauma, which could be said to have caused their personality, or the drugs as self-medication.
This clouds the cause and effect issue.
However, this only studied prisoners, which is not a group representative of the whole population.
Kubicka et al. (2001) conducted a 24 year long longitudinal study in the Czech Republic.
They found extraversion, neuroticism and low conscientiousness were quite stable over time, and were good predictors of drinking and smoking.
Smoking was also highly predicted by low IQ, and gender.
This shows there are many factors at play, not just personality.
McNamara et al. (2010) found that in rats, impulsivity was a predictor of taking more cocaine but not heroine.
Stoess (1993) found that, across a range of different addictive activities, there was not a common pattern. Therefore this may differ across personalities.
Kerr (1996) argues there is no such thing as an addictive personality, as many of the traits associated can be in non-addicts, and many addicts don’t have these traits.
Franques at al.(2000) stated that addictive personalities are not considered within addictive psychology, and said there are multiple factors, with none being the solo determinant.
Many of these traits can be associated with dopamine functioning.
Buckhoitz et al. (2010) measured levels of impulsivity in non-addicts before using amphetamines.
They found those with higher impulsivity had a higher dopamine release and lower receptivity.
This means people with ‘addictive personalities‘ may simply respond better to drugs.
Some conditions increase the likelihood of addiction, and could therefore be seen as a symptom rather than a disorder in its own right.
Neuroticism is generally linked to mental illness, therefore leading to self-medication.
A common comorbidity is ASPD.
Messina et al. (1999) found that 40-50% of addicts have ASPD, and 90% of those with ASPD are addicts.
Trull et al. (2004) found a relationship between personality disorder symptoms and substance abuse. They concluded these symptoms preceded substance abuse.
This theory is greatly determinist, which brings many issues:
Can addicts be held accountable for their behaviour if they can’t control their addiction?
Will people with addictive personalities always be addicts?
While this could help people see that those with addiction cannot be blamed, and therefore discourage stigma, it could mean people with these personalities are assumed to be addicts.
It also means people may feel powerless to change themselves, as personality within this theory is fixed.
Kahneman and Tversky (1973) proposed humans have particular methods of quick decision making known as heuristics.
These are described as mental shortcuts, and often involve focusing on one aspect and ignoring others.
This can cause people to deviate from normal logical decisions, causing cognitive biases.
Two examples of heuristics identified by Kahneman and Tversky, are:
Representativeness:
A heuristic that stems from comparisons to mental representations, such as stereotypes.
For example, assuming a man wearing a suit is a lawyer.
Availability:
Based on how easy it is to think of an example:
For example, believing airplane crashes are common as they are most shown in the media, even though there are thousands of successful flights annually.
Keren and Lewis (1994) identified two gamblers fallacies:
Type one fallacy:
Based on the representativeness heuristic, where an individual uses a mental representation of short term odds (such as a coin flip is 50-50) to a long term event (such as an actual coin flip).
Therefore, after 10 coin flips that landed on heads, this fallacy would presume a ‘tails‘ is due and must be next, even though each individual flip is 50-50.
This can be applied to other gambling games, with a gambler feeling they are ‘due‘ a win.
Type two fallacy:
This is when a person believes a truly random system (such as a roulette wheel) is biased, and therefore has a pattern.
They then underestimate the amount of observations needed to detect this bias, and believe they have discovered a fake pattern (such as the wheel is more likely to land on 16).
They will then bet on this number.
The availability heuristic can also be applied:
Events that are more likely to be remembered are assumed to be more common.
This includes winning the lottery as only winners are advertised.
People therefore overestimate their odds of winning.
Gambling machines are designed to induce this heuristic, by playing bright lights, playing music and giving out coins individually to make the reward seem bigger.
The machines are also placed closer together so you are able to hear other people winning.
The sunk-cost fallacy, Slough et al. (2008):
This is a fallacy which causes a tendency to invest more future resources something which a person has already invested into, over something a person has not invested into.
This means once a gambler has begun gambling, they will be compelled to keep gambling until they have won to justify the money they have already spent.
Illusion of control:
Many gamblers will believe if they can control some aspects of gambling, such as a particular seat, machine or method of dice rolling.
Hindsight bias:
A gambler claiming they expected the results of a gamble and could have predicted the results.
This helps them to maintain control, and believe that gambling is a skill they need to improve.
Self-serving bias:
Gamblers attribute wins to internal causes, such as their own skill, and any losses to external factors such as luck or bias.
This helps them to feel as if losses are not their fault.
Attentional bias, Weinstein and Cox (2006):
This refers to when addicts pay attention to certain stimuli and ignore others, which can increase motivation to engage in the behaviour.
This is because the addict pays more attention to stimuli which relates to the addiction, such as the smell of smoke or advertisements.
This can be tested using a stroop test, with a participant asked to identify the colour of words shown to them. Some of these are words relating to their addiction.
Johnsen et al. (1997) compared active smokers, abstinent smokers and non-smokers on their response times and found smokers had the longest reaction times.
Griffiths (1994) compared the verbalisations of 30 gamblers to 30 non-regular gamblers.
He found regular gamblers showed more irrational verbalisations (14%-2.5%=11.5% difference).
He also found these verbalisations supported the existence of the heuristics and cognitive biases.
Joukhador et al (2003) developed a 65 item questionnaire called the Gambling Belief Questionnaire which covered a range of cognitive biases such as the gambler’s fallacy.
They then compared 56 problem gamblers to 52 social gamblers, and found that problem gamblers always scored higher.
Definition of social vs problem gamblers may have been an issue here.
While this theory describes the thoughts of gamblers, it does not explain them, as explanations should be able to predict behaviour in specific situations.
However, it is impossible to predict which cognitive bias or heuristic will be used in any situation, as individuals do not use them in a pattern.
Griffiths (2013) uses the example of when a triple rollover occurred in the UK national lottery, the media reported that the number 13 had come up fewer times than any other.
Individuals using the representative heuristic (gambler’s fallacy one) would assume that it was due to come up (via using short term odds on long term issues).
Individuals using the availability heuristic would assume it won’t come up as it is rarer.
Research into biases requires self-report techniques or observations.
Self-reports, such as questionnaires, allow gamblers to lie about their thoughts to rationalise them (demand characteristics), or to lie about the amount of gambling they participate in (social desirability).
Observations allow researcher bias to occur, as they have to label the cognitive bias shown.
A major criticism is that all people have heuristics, but not all people become gamblers or other behavioural addicts.
Therefore, why do some people become addicts and some don’t?
Baboushkin et al. (2001) suggests heuristics are often appropriate in everyday situations, but not in chance events, such as gambling, which causes gamblers issues.
If gambling fallacies develop due to gambling, why does a person start gambling?
If cognitive biases cause the gambling, then how do they develop?
There also may be an intervening variable, such as the social explanations.
These cognitive biases may not be generalisable across all groups:
Strough et al. (2008) found that older adults were less likely to fall for the sunk-cost fallacy than younger adults, although she was not investigating gambling behaviour specifically.
Ibanez et al. (2003) investigated gender differences in gambling, and found more men than women were exposed to gambling in adolescence.
Women had a later age of first bet, but a faster evolution of the disorder.
Men were more likely to have comorbid alcohol abuse and ASPD, while women were more likely to have emotional disorders and a history of physical abuse.
This makes it highly likely their cognitive biases differ.
Visschers et al. (2009) found that people often hold odd beliefs about probability and gamblers find it hard to understand information about risk, especially if presented in a probabilistic form.
This may be the cause of people relying on heuristics, which does not apply to drug addictions where the probability is easier to understand, making it a poor explanation for these addictions.
The measurement of cognitive biases in gamblers may have useful implications in treatments:
Griffiths (1994) did a small scale study by playing back gambler’s irrational verbalisations back to them (from his study comparing gamblers and non-gamblers irrational verbalisations) and found most were shocked by what they said.
This suggests it may be useful in cognitive restructuring, by allowing addicts to understand the irrationality of their thoughts, and be able to identify them as such.
Fortune and Goodie (2012) report that studies have varied in using this idea as part of CBT, while other have focused on correcting specific beliefs and biases.
Both methods have shown some success in treating gambling addiction, suggesting cognitions play a role in addiction.
This is often thought of as direct peer pressure, but in reality is often more subtle.
Behaviourists would believe addictions are either maintained by classical conditioning (association of the high from a drug with its smell) or operant conditioning (association of a drug with the pleasant experience it gives), but this does not explain why the behaviour is started.
To solve this, Bandura developed SLT based on his Bobo doll experiments. It states that behaviours, such as addiction, are learned socially and indirectly from those around an individual.
He believed there were two elements to this, a role model and vicarious (indirect reinforcement from observing others) reinforcement.
There are four key processes of SLT:
Attention - The individual must pay attention to their role model engaging in this behaviour in order to understand how to do it.
Retention - The observed behaviour must be remembered, including each of the steps.
Reproduction - The individual must be able to repeat the observed behaviour, including the physical ability that comes with practice, and the necessary equipment.
Motivation - The individual must be motivated to continue the behaviour (vicarious reinforcement).
Behaviour is more likely to be imitated if the role model is the same gender, similar age of older, powerful, high status, friendly and likeable.
Motivation does not just come from the role model, but the consequences they receive. There are three types of this:
Vicarious reinforcement - Reinforcement from watching another person be rewarded for a behaviour, often socially, such as having more friends.
Vicarious punishment - Stopping a behaviour after watching another person be punished for it, such as a punishment from a teacher.
Vicarious extinction - Stopping a behaviour after watching a person get no reward for it, such as another person being ignored while attempting to gain attention for smoking.
Social norms are the rules of behaviour within certain social groups, and vary across cultures and subcultures.
For example, the UK has a strong drinking culture whereas in Middle Eastern countries alcohol is illegal.
There has been research into how these norms can affect young people, with Bosari and Carey defining two types of norms:
Descriptive norms - An individual’s perception of how much others engage in a behaviour, for example believing people drink every weekend.
Injunctive norms - An individual’s perception of the approval of the behaviour, for example believing that everyone else believes this is acceptable.
Perkins and Berkowitz (1986) found that a high proportion of students surveyed believed that being intoxicated was only acceptable in limited circumstances, but a high proportion also believed that their peers had a more liberal attitude towards drinking.
Therefore, people believe that the people around them are drinking more than them.
Fergusson and Horwood found that peer attitudes toward drug use are highly predictive of adolescent drug use.
Simon-Morton and Farhat’s peer review into 40 prospective longitudinal studies on the same participants found all but two had a positive correlation (NOT CAUSAL) between peers and smoking.
Parents are also an important factor, providing a protective effect from peer influence via direct and indirect methods, such as stopping an individual seeing smoking friends and simply not smoking.
Parental smoking was also found to be a big influence on adolescent smoking.
Neighbors et al. found that social norms were the best predictor of alcohol consumption among US college students.
However, they were not the best predictor of alcohol related issues, such as fights and drunk driving, showing there may be other factors involved in directly developing an addiction.
There is a debate whether peers influence an individual to engage in behaviours (peer influence) or an individual chooses friends as they engage in the same behaviours (peer selection)
Ennett and Bauman found that non-smoking participants with smoker friends were more likely to smoke at a follow-up.
They also found evidence that their friendship groups altered in line with their smoking or non-smoking behaviour.
This suggests that both of these processes are important in developing addictions.
This aligns with cause and effect issues:
Do people pick friends because they share an addiction (peer selection)?
Are people influenced by already existing friends to initiate an addiction (peer influence)?
Kobus suggests other factors, such as family and neighbourhood, need to be considered as larger social contexts.
Hawkins found parental drug use is associated with an adolescents initiation and frequency of usage in an adolescent.
They also found that if parents have permissive attitudes towards drugs, children are more likely to use drugs.
Additionally, not all addictions are social, such as online gaming addictions.
Not all individuals friends with addicts develop an addiction - are some people immune or are there additional factors?
This theory also doesn’t explain the maintenance of additions.
An Institute of Medicine study found no evidence for peer influence in the development or maintenance of drug addictions.
This theory would expect addictions to stop as soon as socialisation with a group stopped, but this is not true, addictions outlast social groups.
Studies into this are mainly focused on adolescents and teens, and substances such as tobacco, alcohol or drugs.
There is little research into older individuals or behavioural addictions.
Perhaps this theory is the main cause in younger people, but not older.
Additionally, most studies are around 10 years old and could be out of date, especially with the rising influence of social media.
It could be said that young people who develop an addiction due to peer influences are not responsible for their actions, as they were unknowingly coerced.
However, it is hard to blame the addicts they model, as they may not have intended to be copied.
Additionally, telling young addicts that those around them caused their behaviour may make them feel they do not have free will.
SLT can also be applied here, with celebrities acting as role models, and vicarious reinforcement taking the role of how the character is treated within the media, such as gaining approval, being rich or famous.
Portrayal of smoking and alcohol use is extremely common.
Lyons et al. (2011, 2013) found that alcohol use is seen in 86% of movies and 40% of TV programmes.
Glantz et al. (2002) compared smoking in films from 1950-2002. They found a decrease in smoking from 1950-1982, in 2002 this then increased back to 1950 levels.
Although smoking has decreased generally and awareness of negative effects has increased, smoking in media has remained fairly constant.
This behaviour is also presented in a positive light.
Gunasekera et al. (2005) used content analysis to analyse the 87 of the top 200 movies of the last 20 years. They found that alcohol and tobacco use are common, and incidents of cannabis and other drug use were noted.
The main finding was addictions tended to portray addictions positively without negative consequences, which shows vicarious reinforcement.
Wellman et al. (2006) reviewed a number of studies on how exposure to tobacco advertising and smoking in the media effects individuals, and found increased positive attitudes doubled the chances of starting to smoke.
However, adverts are different to simple media exposure as they directly encourage smoking.
Hanewinkel et al. studied 2,346 teenagers (12-14 years old) from a range of European cultures who reported they had never drunk alcohol and did not intend to. 12 months later, 40% of the sample had tried alcohol and 9% had engaged in binge drinking.
A range of variables were controlled for, including personality characteristics and school performance, exposure to alcohol occurrences in films was associated with increased risk of drinking.
Derevensky et al. (2010) found that teenagers who are already gambling were more likely to be influenced by gambling advertisements.
The majority of research into drugs and media is correlational, and therefore causal statements cannot be made.
There are many possible causes for these correlations:
Media causes addictive behaviours - more addictive media = more addictive behaviour.
Addictive behaviour affects media consumption - more addictive behaviour = higher engagement in media which has addictive behaviour.
An intervening factor may be involved, such as peers influencing addictive behaviour and media consumption.
However, Pechmann and Shih (1999) used an experimental method - showing two versions of a clip, one with smoking and one without.
They found that those that watched the smoking version had increased positive smoking attitudes and increased intention to smoke.
The research also lacks population validity, as it is mostly conducted on adolescents.
For adults, Jamieson and Romer (2015) compared tobacco use on television with smoking rates of the US population. They controlled for factors such as cigarette price and found a positive correlation.
It could be argued that teens are more susceptible to media influences as they are still developing, or that the theory was developed for teens.
Additionally, it most often focuses on alcohol and smoking.
Atkinson et al. (2011) interviewed adolescents and found they were aware celebrity drinking stories may be exaggerated, and did not feel the media was a major influence on their behaviour. They instead said they found peers and parents to have more of a role.
However, it may be they are unaware of the role of the media.
It could be said that young people who develop an addiction due to the media are not responsible for their actions, as they were ‘programmed‘.
Additionally, telling young addicts that the media caused their behaviour may make them feel they do not have free will.
However, the media may have positive effects. Pechmann and Shih’s study also found that effects of watching smoking in the film was negated by showing an anti-smoking advert beforehand.
The media also report on negative consequences, such as Amy Winehouse’s death, and films show negative effects, which can act as vicarious punishment. Some examples are:
Trainspotting.
Media campaigns such as “Faces of Meth“ in the USA, which shows people before and after meth addictive.
There was a similar UK campaign to publish a photo of Rachel Whitear, a girl who died of an overdose in her flat at age 21.
The Smokefree Movies Project aims to eradicate positive depictions of smoking from movies, with Disney pledging to ban smoking in all films targeting youth audiences, unless it was to maintain historical accuracy.
Aversion therapy uses classical conditioning to associate the addictive behaviour (normally a chemical addiction) with an unpleasant stimulus.
This means the addictive behaviour will then cause an unpleasant response, causing them to hopefully avoid the behaviour.
Due to ethical and safety reasons, it is often only used with alcohol and sometimes smoking.
In the past, aversion therapy has been associated with conversion therapy, which is highly unethical.
It occurs in 3 steps:
A naturally unpleasant stimulus (unconditioned stimulus, UCS) produces a negative response (Unconditioned response, UCR).
The UCS is then paired with the addictive behaviour (neutral stimulus, NS).
This leads to a conditioned response (CR), with the NS becoming a conditioned stimulus (CS).
This therefore should cause the addictive substance to be associated with a negative stimulus.
Antabuse is a drug used as the unconditioned stimulus.
When mixed in alcohol, the disulfiram reaction occurs, which stops aldehyde dehydrogenase from breaking down acetaldehyde and causes it to build up in the bloodstream.
This occurs within 10 minutes of consumption and can last for a few hours.
This drug has a long half-life, meaning it can occur up to a week after it is last taken.
NICE (National Institute for Health and Care Excellence) advise antabuse can be given after withdrawal.
It starts at 200mg daily, but can increase if the reaction is not bad enough.
They should remain under supervision every two weeks for the first two months, then monthly for the four months after this.
Takers must also be careful to not accidentally consume alcohol in mouthwash or food.
This is less common than alcohol aversion therapy.
A person has a puff of a cigarette every 6 seconds.
This will make them associate smoking with this feelings of nausea.
Therefore, the UCS is not an actual stimulus, it is the UCR of discomfort after intensive smoking.
Antabuse:
Niederhofer and Staffen (2003) compared antabuse to a placebo and assessed patients using self-report methods for 90 days.
They found antabuse patients had significantly greater abstinence duration than the control.
Jorgensen et al. (2011) found that those who took antabuse had more days until relapse and fewer drinking days.
Rapid smoking:
Most research into it’s effectiveness is out-of-date and limited.
Hajek and Stead (2004) reviewed previous literature and found it to be an unproven method.
They said that many effectiveness studies have methodological issues.
However, they said there are enough indications of potential to warrant further research.
McRobbie (2007) carried out a study on 100 smokers, with one group performing rapid smoking and one watching a video about quitting smoking.
He found there was a significant decrease in their urge to smoke after a day and a week, but after 4 weeks this difference was no longer significant.
This means it may not be an effective long term technique, but could be seen as a short term way of kick starting quitting.
However, these studies have many methodological issues:
No randomised controlled trials:
This is a sourcing issue, as sourcing alcoholics must come from those who admit to be addicts which could leave out the majority. (Ellis, 2013)
Sample size:
Often small as addicts who are willing to participate in these trials are hard to find. This makes the study less generalisable. (Ellis, 2013)
Attrition rate:
This lowers the sample size again, but also suggests the drug is either not working, or causing to harmful side effects.
However, many addiction studies on addicts have high attrition rates due to relapse rates.
Few comparison studies:
Means that antabuse is only effective when compared to a placebo, but perhaps not more effective than any other treatment.
This could be attributed to the lack of other similar drugs, however antabuse should be compared to therapeutic and in-patient treatments. (Ellis, 2013)
Placebo studies:
These are difficult as the moment a patient drinks, they will be aware of whether they are the placebo or not based on whether they experience adverse effects.
This may lead some people to drink out of curiosity.
Additionally, some people require higher doses of antabuse, and therefore may not receive it’s full effects without testing.
Not longitudinal enough:
Studies need to continue over many years in order to properly show the effects of antabuse.
If antabuse ends alongside the experiment, then there will be no proof that the CR remains and is still effective.
Antabuse could be seen as not treating the root causes of addiction.
This is an issue as addiction is usually comorbid with other disorders, such as ASPD and anxiety. If these are not addressed, an addict may turn to another addiction to cope.
Additionally, cognitive biases will still remain, raising a person’s likelihood of addiction.
The disulfiram reaction effects are extremely unpleasant, and is the process of rapid smoking.
However, this can be argued as how the treatment is actually supposed to work, and valid consent would have been provided.
A more ethical alternative, covert sensitisation, is suggested.
This works with individuals being encouraged to imagine imagery of nausea when they have the urge to drink.
Kraft (2005) presents case studies showing that it is a quick and effective technique for many individuals, and is more ethical.
Side effects also have many ethical implications, as a person must suffer in order to get good effects.
Antabuse can cause nausea, diarrhea, and fatigue.
Many addicts will stop taking antabuse if they are stressed in order to drink again:
O’Farrell and Bayog (1986) suggests the usage of an Antabuse Contract, designed for marriages.
The alcoholic spouse agrees to take antabuse and abstain from alcohol, while the spouse records this intake on a calendar. Both agree to stop discussions about past or future drinking.
O’Farrell et al. (1998) found that alcoholics taking Antabuse outcomes were much improved with the usage of this contract.
An Antabuse implant has also been suggested, which are inserted into the lower abdomen under local anaesthetic and slowly release antabuse, preventing incompliance.
This is not recommended for use in the UK, and are not available on the NHS due to concerns over long-term effects and ethics as someone cannot choose to simply not take it.
It is still available in Eastern Europe, however, and people may travel there to get it implanted.
Antabuse treatment is often used as a condition for early release, which could be seen as coercive.
An example is in El Cajon, California. Defendants are offered a year in jail or a year of antabuse treatment.
Marco argues this is a cruel and unusual punishment, coercive, and is not valid consent as participants are not fully informed as the risks and effects of Antabuse.
Devlin (2008) in a telegraph article highlighted the increase in antabuse and other drug treatments in treating alcoholism, from £1.08 million in 1998 to £2.25 million in 2008.
It can be argued that this is worthwhile, as it avoids other costs of addictions, specifically alcoholism.
The No Quick Fix report (Centre for Social Justice, 2013) stated that alcoholism costs the taxpayer £21 billion a year, including by unemployment benefits, healthcare (estimated at around £3.5 billion a year for the NHS, which includes long term health issues, accidents, etc.), property damage, etc.
Additionally, addiction can cause many social problems, such as debt, crime and homelessness. Therefore, it’s treatment is necessary, and outweighs the costs of ethical issues.
However, the government is predicted to earn £10.4 billion from 2023-24 on tobacco taxes, and £13.1 billion on taxes on alcohol in 2023, according to the Office for Budget Security.
Antabuse, however, is estimated to have cost taxpayers around 1.5 million pounds in 2023, showing there may be less expensive alternatives.
Agonists are chemicals that bind to a post-synaptic receptor and activate that receptor to produce a response.
Methadone is a synthetic replacement for heroin, and mimics its effects without producing a high.
This is needed as dopamine receptors become lessened and less sensitive after long-term addiction, and less dopamine overall is released. Methadone activates dopamine receptors.
This is utilised to reduce and hopefully eliminate withdrawal symptoms which could cause relapse.
Methadone is used as a maintenance treatment - preventing withdrawal symptoms to reduce cravings and withdrawal symptoms.
NICE recommends an initial dose of 10-40 mg, which is raised by up to 10mg daily until no withdrawal symptoms are experienced.
This dose is then known as the maintenance dose, which is usually around 60-120 mg a day.
Eventually, detoxification should occur by reducing the methadone dosage until abstinence is achieved.
Methadone is normally given orally as a green liquid, but can also be given as an injection or a tablet.
Needles are avoided as they could be seen as a reminder of the past addiction, perhaps triggering relapse, but also due to the damage some heroin users have at normal injection points.
A doctor, nurse or pharmacist sees patients each day for the first three months, ensuring the dosage is correct, people do not take multiple doses or sell it on.
This continues until patients are trusted.
NICE recommends maintenance treatment alongside psychosocial support.
Antagonists bind to a receptor and block the usual function of a particular substance.
Naltrexone is often used in the abstinence stage of recovery from addiction, as it blocks the pleasurable effects of opioids and makes them less rewarding, therefore discouraging relapse.
NICE guidelines recommend naltrexone for people who have stopped using opioids, and those who are highly motivated.
It is available orally.
It can also be available for usage as a depot injection (injection with a liquid that causes slow release) or as an implant, however this is only approved for use in the US and Russia.
Naltrexone can also be offered in cases of alcohol addiction, and similarly after interventions and withdrawal have occurred.
It can be used for up to a six month period, and users should be kept under supervision to check they don’t use again.
NHMRC (National Health and Medical Research Council) suggest it can also be used for problem gamblers, although they admit more research is needed into this.
This is due to naltrexone blocking dopamine receptors, therefore preventing dopamine responses.
Methadone:
NICE assessed 31 reviews of methadone effectiveness, including 27 randomised controlled trials.
There were higher levels of treatment retention and lower rates of illicit opioid use for those using methadone over a placebo or no treatment.
Van den Brink and Haasen (2006) conducted a meta-analysis of studies on a range of treatment effectiveness and found that, if the dosage is adequate, methadone is effective as a maintenance drug.
Gowings et al. (2001) found that methadone programmes are very effective at reducing the social and physical harms associated with drug abuse, with the longer someone remains in treatment, the better their outcomes and the lower their chances of relapse.
It could be argued this is due to methadones longer lasting action, which allows a person to separate themselves from the negative effects of drug culture, and allowing them to achieve social, legal and financial security.
Naltrexone:
NICE reviewed 17 studies into naltrexone effectiveness for heroin addiction, and found conflicting results.
Many randomised control trials showed no significant difference between naltrexone and a control treatment for treatment programme retention.
However, once pooled they found naltrexone is associated with lower relapse rates in those who were highly motivated, and with closely monitored patients who were offered extra support.
Lahti et al. (2010) tested naltrexone effectiveness on a small sample of gambler’s, who were instructed to take it before gambling or when they felt the urge to do so.
They found decreases in gambling levels. However, there was no placebo comparison, so more research is necessary.
Buprenorphine:
This is an alternative drug for both methadone and naltrexone, as it acts as both an agonist and antagonist, by activating opiate receptors and blocking euphoria.
This drug also has a ceiling effect, meaning after a certain amount has been taken, taking anymore will not increase it’s effects. This could reduce the risk of overdose.
Marteau et al. (2015) analysed data over 15 years and found that buprenorphine was 6x safer than methadone.
However, methadone is still used in the UK as it has higher treatment retention rates.
Whelan and Remski (2012) argue this is because addicts prefer the feeling they get from methadone.
NICE also identified specific issues with research in this area:
Treatment protocols across different countries may differ, such as methadone dosage, support and monitoring received. This may cause issues with comparisons.
Studies are not also longitudinal, and relapses can occur months or years after abstinence.
Attrition is common due to the social and psychological problems addicts often experience.
Both drugs can be seen as quick fix to addiction, as they do not treat the root cause which could be a variety of social, financial and mental issues such as PTSD.
This could be due to medications being cheaper.
This may lead a person to not receive adequate treatment, and replace their drug addiction with other behaviours, such as a behavioural addiction.
Methadone:
It can react with other drugs, such as alcohol and antidepressants to cause respiratory problems. This is a major issue as heroin use may have been to cope with depression, so treating both may become an issue.
Overdose can occur if combined with other drugs, with the UK Office for National Statistics reporting 640 deaths caused by methadone in 2022.
Additionally, it could be argued that methadone simply creates another addiction, and people may stay on it for prolonged periods of time, with detoxification and eventual abstinence being a struggle.
It also has many side effects, such as hallucinations and confusion, which could drive a person to return to heroin.
Naltrexone:
Has a greater risk of overdose, as individuals may take more of a drug to feel the effects over the naltrexone.
People addicted while taking naltrexone need to have their liver functioning monitored, and be monitored for withdrawal symptoms as naltrexone can displace opioids still in the system from their receptor.
It also has many serious side effects, such as seizures and anxiety, which could drive a person back to opioids.
Additionally, addicts who are jailed could be coerced into treatment programmes, such as these medications being a parole condition.
This could lead to free will issues, but also decreases the likelihood of treatment being effective.
However, Brecht et al. found that patients coerced performed equally well in methadone treatment as those who volunteered, suggesting this may be beneficial.
A report by the Centre for Policy studies (Gyngell, 2011) argued that methadone was an expensive failure, due to the cost of medication and drug addicts on benefits.
They suggested that rehabilitation units would be more effective.
This could be seen as akin to imprisonment.
The charity Drugscope (Doward, 2011) disputed this claim, saying the article overestimated the cost of methadone.
They highlighted how the National Audit Office described methadone as good value for money for taxpayers, and methadone users are able to function in society due to methadone making their addiction manageable.
The National Treatment Agency suggests that treating heroin users with methadone has an immediate positive effect by reducing criminality, suggesting reoffending rates are halved when addicts are in treatment.
However, the Centre for Policy studies (Gyngell, 2011) claimed drug related reoffending has continued to rise despite methadone availability.
Methadone availability, however, has nothing to do with whether people actually take it, and drug related reoffending is general to all drugs, not just heroin.
Another issue is the setting up of methadone programmes in certain areas, which is feared to increase crime and antisocial behaviour due to an increase in addicts.
Boyd et al. (2012) researched treatment centres in Baltimore and found that crime rates were similar to the surrounding areas.
However, drug abuse could be seen as a symptom of wider societal issues, as the The Advisory Council for the Misuse of Drugs report, ‘Drug Misuse and the Environment‘ (1998) argues.
Deprivation is associated with lower age of first use, progression to dependence, intravenous drug use, risky use, health and social complications due to use and criminal involvement.
These people are less likely to get treatment, have lower chances of overcoming drug use, and may earn money from drug dealing.
Therefore, programmes should focus on preventing initiation, and outreach for members of these communities.
Likely, this is not done as root causes are harder to treat by politicians, and quick fixes look better on campaign trails.
In 2022, the NHS spent £3.3 million on methadone, and drug abuse is estimated to cost around £20 billion according to the PM.
Methadone further benefits society by allowing for reintegration.