9.8: Perspectives on Addiction
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- 221743
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- Describe and discuss the various psychological explanations for addiction
There are a number of genetic and environmental risk factors for explaining drug or alcohol abuse that vary across the population. Genetic and environmental risk factors each account for roughly half of an individual’s risk for developing an addiction; the contribution from epigenetic risk factors to the total risk is unknown. Even in individuals with a relatively low genetic risk, exposure to sufficiently high doses of an addictive drug for a long period of time (e.g., weeks to months) can result in an addiction.
This video explains how substance abuse disorders may develop.
You can view the transcript for “The development of substance use – Why do people use legal and illegal substances? | Khan Academy” here (opens in new window).
Genetic and Biological Approaches to Addiction
Epidemiological studies estimate that genetic factors account for 40–60% of the risk factors for alcoholism. Similar rates of heritability for other types of drug addiction have been indicated by other studies. Overall, the data implicating specific genes in the development of drug addiction is mixed for most genes. One reason for this may be that the case is due to a focus of current research on common variants. Many addiction studies focus on common variants with an allele frequency of greater than 5% in the general population; however, when associated with the disease, these only confer a small amount of additional risk with an odds ratio of 1.1%–1.3%.
Genome-wide association studies (GWAS) are used to examine genetic associations with dependence, addiction, and drug use. These studies employ an unbiased approach to finding genetic associations with specific phenotypes and give equal weight to all regions of DNA, including those with no ostensible relationship to drug metabolism or response. These studies rarely identify genes from proteins previously described via animal-knockout models and candidate-gene analysis. Instead, large percentages of genes involved in processes such as cell adhesion are commonly identified.
Cross addiction is when one already has a predisposed addiction and then starts to become addicted to something different. If one family member has a history of addiction, the chances of a relative or close family developing those same habits are much higher than one who has not been introduced to addiction at a young age. In a recent study done by the National Institute on Drug Abuse, from 2002 to 2017, overdose deaths have almost tripled amongst male and females. In 2017, 72,306 overdose deaths happened in the United States that were reported.
Environmental Factors
Environmental risk factors for addiction are the experiences of an individual during their lifetime that interact with the individual’s genetic composition to increase or decrease his or her vulnerability to addiction. A number of different environmental factors have been implicated as risk factors for addiction, including various psychosocial stressors. The National Institute on Drug Abuse (NIDA) cites lack of parental supervision, the prevalence of peer substance use, drug availability, and poverty as risk factors for substance use among children and adolescents. The brain disease model of addiction posits that an individual’s exposure to an addictive drug is the most significant environmental risk factor for addiction. However, many researchers, including neuroscientists, indicate that the brain disease model presents a misleading, incomplete, and potentially detrimental explanation of addiction.
Adverse childhood experiences (ACEs) are various forms of maltreatment and household dysfunction experienced in childhood. A study of 900 court cases involving children who experienced abuse found that a vast amount of them went on to suffer from some form of addiction in their adolescence or adult life. This pathway towards addiction, which is opened through stressful experiences during childhood, can be avoided by a change in environmental factors throughout an individual’s life and opportunities of professional help. If one has friends or peers who engage in drug use favorably, the chances of them developing an addiction increases. Family conflict and home management may also lead to alcohol or other drug use.
Age
Adolescence represents a period of unique vulnerability for developing an addiction. In adolescence, the incentive-rewards systems in the brain mature well before the cognitive control center. Therefore, adolescents are increasingly likely to act on their impulses and engage in risky, potentially addicting behavior before considering the consequences. Not only are adolescents more likely to initiate and maintain drug use, but once addicted they are more resistant to treatment and more liable to relapse.
Statistics have shown that those who start to drink alcohol at a younger age are more likely to become dependent later on. About 33% of the population tasted their first alcohol between the ages of 15 and 17, while 18% experienced it prior to this. As for alcohol abuse or dependence, the numbers start off high with those who first drank before they were 12 and then drop off after that. For example, 16% of alcoholics began drinking prior to turning 12 years old, while only 9% first touched alcohol between 15 and 17. This percentage is even lower, at 2.6%, for those who first started the habit after they were 21.
Most individuals are exposed to and use addictive drugs for the first time during their teenage years. In the United States, there were just over 2.8 million new users of illicit drugs in 2013 (~7,800 new users per day); among them, 54.1% were under 18 years of age. In 2011, there were approximately 20.6 million people in the United States over the age of 12 with an addiction. Over 90% of those with an addiction began drinking, smoking, or using illicit drugs before the age of 18.
Comorbid Disorders
Individuals with comorbid (i.e., co-occurring) mental health disorders such as depression, anxiety, attention-deficit/hyperactivity disorder (ADHD) or post-traumatic stress disorder are more likely to develop substance use disorders. The NIDA cites early aggressive behavior as a risk factor for substance use. A study by the National Bureau of Economic Research found that there is a “definite connection between mental illness and the use of addictive substances” and a majority of mental health patients participate in the use of these substances: 38% alcohol, 44% cocaine, and 40% cigarettes.
Sociocultural Factors
Due to cultural variations, the proportion of individuals who develop a drug or behavioral addiction within a specified time period (i.e., the prevalence) varies over time, by country, and across national population demographics (e.g., by age group, socioeconomic status (SES), etc.)
Internationally, the United States and Eastern Europe contain the countries with the highest substance abuse disorder occurrence (5%-6%). Africa, Asia, and the Middle East contain countries with the lowest worldwide occurrence (1%-2%). Across the globe, those that tended to have a higher prevalence of substance dependence were in their twenties, unemployed, and male. The National Survey on Drug Use and Health (NSDUH) reports on substance dependence/abuse rates in various population demographics across the United States. When surveying populations based on race and ethnicity in those ages 12 and older, it was observed that American Indian/Alaskan Natives were among the highest rates and Asians were among the lowest rates in comparison to other racial/ethnic groups.
| Race/Ethnicity | Dependence/Abuse Rate |
|---|---|
| Asian | 4.6% |
| Black | 7.4% |
| White | 8.4% |
| Hispanic | 8.6% |
| Mixed race | 10.9% |
| Native Hawaiian/Pacific Islander | 11.3% |
| American Indian/Alaskan Native | 14.9% |
When surveying populations based on gender in those ages 12 and older, it was observed that males had a higher substance dependence rate than females. However, the difference in the rates are not apparent until after age 17. Drug and Alcohol Dependence reports that older adults abuse drugs including alcohol at a rate of 15–20%. It’s estimated that 52 million Americans beyond 12 years old have abused a substance.
| Age | Male | Female |
|---|---|---|
| 12 and older | 10.8% | 5.8% |
| 12–17 | 5.3% | 5.2% |
| 18 or older | 11.4% | 5.8% |
Alcohol dependence or abuse rates were shown to have no correspondence with any person’s education level when populations were surveyed in varying degrees of education from ages 26 and older. However, when it came to illicit drug use, there was a correlation in which those that graduated from college had the lowest rates. Furthermore, dependence rates were greater in unemployed populations ages 18 and older and in metropolitan-residing populations ages 12 and older.
| Education level | Rates | Employment status | Rates | Region | Rates |
|---|---|---|---|---|---|
| high school | 2.5% | unemployed | 15.2% | large metropolitan | 8.6% |
| no degree, college | 2.1% | part-time | 9.3% | small metropolitan | 8.4% |
| college graduate | 0.9% | full-time | 9.5% | non-metropolitan | 6.6% |
The National Opinion Research Center at the University of Chicago reported an analysis on disparities within admissions for substance abuse treatment in the Appalachian region, which comprises 13 states and 410 counties in the eastern part of the United States. While their findings for most demographic categories were similar to the national findings by NSDUH, they had different results for racial/ethnic groups that varied by sub-regions. Overall, Whites were the demographic with the largest admission rate (83%), while Alaskan Native, American Indian, Pacific Islander, and Asian populations had the lowest admissions (1.8%).
Alcohol and Drug Abuse Around the World
In Asia, the prevalence of alcohol dependence is not as high as is seen in other regions. Many Asians (30% to 50% of people of Chinese, Japanese, and Korean ancestry) have at least one ALDH2*2 allele, which may cause alcohol flush reaction, or a sensitivity to alcohol that causes flushes or blotches on the body after alcoholic consumption. In Europe in 2015, the estimated prevalence among the adult population was 18.4% for heavy episodic alcohol use (in the past 30 days); 15.2% for daily tobacco smoking; and 3.8, 0.77, 0.37 and 0.35% in 2017 for cannabis, amphetamine, opioid, and cocaine use, respectively. The mortality rates for alcohol and illicit drugs were highest in Eastern Europe.
The realities of opioid use and abuse in Latin America may be deceptive if observations are limited to epidemiological findings. In the United Nations Office on Drugs and Crime report, although South America produced 3% of the world’s morphine and heroin and 0.01% of its opium, the prevalence of use is uneven. According to the Inter-American Commission on Drug Abuse Control, consumption of heroin is low in most Latin American countries, although Colombia is the area’s largest opium producer. Mexico, because of its border with the United States, has the highest incidence of use.
United States
Based upon representative samples of the U.S. youth population in 2011, the lifetime prevalence of addictions to alcohol and illicit drugs has been estimated to be approximately 8% and 2%-3%, respectively. Based upon representative samples of the U.S. adult population in 2011, the 12-month prevalence of alcohol and illicit drug addictions were estimated at roughly 12% and 2%-3% respectively. The lifetime prevalence of prescription drug addictions is currently around 4.7%.
As of 2016, about 22 million people in the United States need treatment for an addiction to alcohol, nicotine, or other drugs. Only about 10%, or a little over two million, receive any form of treatment, and those that do generally do not receive evidence-based care. One-third of inpatient hospital costs and 20% of all deaths in the United States every year are the result of untreated addictions and risky substance use. In spite of the massive overall economic cost to society, which is greater than the cost of diabetes and all forms of cancer combined, most doctors in the United States lack the training to effectively address drug addiction.
In 2019, opioid addiction was acknowledged as a national crisis in the United States. An article in The Washington Post stated that “America’s largest drug companies flooded the country with pain pills from 2006 through 2012, even when it became apparent that they were fueling addiction and overdoses.
In this video, Dr. Femke Buisman-Pijlman explains how biological, psychological, and social factors interact to either increase or reduce the risk that a person may develop a drug use disorder.
You can view the transcript for “Biopsychosocial Model” here (opens in new window).
Other Addictions
There are other types of addictions, unrelated to drugs, that elicit similar behaviors and patterns of abuse in individuals. Recall that a mental disorder is characterized by deviance, dysfunction, distress, and danger. Some behaviors may become so addictive that a person’s thinking is dysfunctional, their behaviors are deviant, and that causes obvious distress. One disorder fitting this category in the DSM-5 is gambling disorder. This is classified when an individual has at least four of the following symptoms in a 12-month period:
- Needs to gamble with increasing amounts of money in order to achieve the desired excitement
- Is restless or irritable when attempting to cut down or stop gambling
- Has made repeated unsuccessful efforts to control, cut back, or stop gambling
- Is often preoccupied with gambling (e.g., having persistent thoughts of reliving past gambling experiences, handicapping or planning the next venture, thinking of ways to get money with which to gamble)
- Often gambles when feeling distressed (e.g., helpless, guilty, anxious, depressed)
- After losing money gambling, often returns another day to get even (“chasing” one’s losses)
- Lies to conceal the extent of involvement with gambling
- Has jeopardized or lost a significant relationship, job, education, or career opportunity because of gambling
- Relies on others to provide money to relieve desperate financial situations caused by gambling
Would you consider yourself addicted to any social media platforms or games? Excessive Internet use has not been recognized as a disorder by the World Health Organization, the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), or the International Classification of Diseases (ICD-11), though the diagnosis of gaming disorder has been included in the International Classification of Diseases (ICD-11). Gaming disorder is defined as the problematic, compulsive use of video games that results in significant impairment to an individual’s ability to function in various life domains over a prolonged period of time.
Mental health professionals have debated including compulsive shopping, stealing, excessive sexual behavior, and internet use as possible disorders, though there is controversy about whether or not a repetitive behavior in and of itself should constitute an addiction. There is also disagreement about whether these types of addictions should constitute a separate clinical entity, or whether they are a manifestation of underlying psychiatric disorders. Research has approached the question from a variety of viewpoints, with no universally standardized or agreed definitions, leading to difficulties in developing evidence-based recommendations.
gambling disorder: mental disorder defined by an addiction to gambling
gaming disorder: controversial disorder described in the ICD-11 related to video game addiction
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