Maturing Out of Addiction: An Age-Related Shift in Hyperbolic Temporal Discounting
http://www.addictioninfo.org/articles/3532/1/Maturing-Out-of-Addiction-An-Age-Related-Shift-in-Hyperbolic-Temporal-Discounting/Page1.html
RJ Branconnier
Roland J. Branconnier graduated from Suffolk University with a BS in Psychology. He attended graduate school at Boston University School of Medicine where he earned an MA in Pharmacology.
Roland is an Instructor in the Alcoholism/Chemical Dependency Treatment Services Program at UMass – Boston. His interests include the evolutionary basis and neuroscience of addiction. In the clinic, he advocates for client's rights to select a treatment regime from among evidence-based treatment options.
By RJ Branconnier
Published on 04/23/2009
The concept of addiction as a progressive, chronic disease remains an
idea with substantial support in the recovery community. This belief
persists despite substantial scientific evidence that significant
numbers of addicts eventually mature out of addiction as they age.
History of Addiction as a Disease:
According to Mosby’s Medical Dictionary (2009): "addiction [ədik′shən] is a compulsive, uncontrollable dependence on a chemical substance, habit, or practice to such a degree that either the means of obtaining or ceasing use may cause severe emotional, mental, or physiologic reactions."
British clergy in the early seventeenth century initiated the use of the term “addiction” to describe excessive consumption of alcohol (Warner, 1994). Consistent with the above definition, “addiction” was considered an obligation or devotion to something.
Therefore, the term “addiction” became a metaphor describing a pathological preference for a given activity that lead to behave “as if addicted.” i.e. devoted to the activity.
There is an inclination for metaphors of this type to be reified, internalized and given causal significance (Sarbin, 1968). This appears to happened with the term “addiction” that has progressed from being a metaphorical description of a devotion to a particular activity, to an internal state, the existence of which is revealed by the devotion and then to be cause of the devotion.
The result of this line of reasoning is a tautology where the “addiction” causes the “addiction” (Akers, 1991). Despite this fallacious circular reasoning, in time, the characterization of “addiction” as a pathological preference gave rise to the notion that excessive use of alcohol was, in fact, a disease.
In the eighteenth century, the concept of alcoholism as a disease was articulated by Benjamin Rush, the Surgeon General of George Washington's revolutionary armies, in a pamphlet published in 1784 entitled: An Enquiry into the Effects of Spriuitous Liquors upon the Human Body, and Their Influence upon the Happiness of Society.
Rush was also one of the first to prescribe total abstinence from spirits as the sole remedy: "taste not, handle not, touch not." He saw treatment of drunkenness as a political issue (White, 1998, Barton, 1999).
The idea that alcoholism is a disease has always been a political and moral notion with no valid scientific basis. It was promoted in the United States in the early nineteenth century as a speculation based on erroneous physiological theory (Levine, 1978), and later became a mantra of the temperance movement (Gusfield, 1963).
It was resurrected in the 1930s by the founders of Alcoholics Anonymous (AA), who derived their views from an mixture of religious ideas, personal experiences and observations, and the unsubstantiated theories of the physician, William Silkworth (Robinson, 1979).
The AA doctrine won support in the 1940s when the scientist, E.M. Jellinek, published an elaborate statistical study of the "phases of alcoholism" (Jellinek, 1946).
He portrayed an inevitable sequence of ever more uncontrollable drinking that led progressively to such symptoms as blackouts, tolerance, and withdrawal distress, until the drinker "hit bottom" as a derelict, became insane, or died.
Jellinek's work seemed to put a scientific imprimatur on the AA depiction of the alcoholic. That was not surprising, since he had taken his data from questionnaires that were prepared and distributed by AA and answered by fewer than 100 selected members.
Jellinek later acknowledged the source of his data and expressed reservations about its scientific validity (Jellinek, 1960). Nevertheless, his characterization of the intractable alcoholic has become widely accepted and is now entrenched as part of American folk science.
Historically, the excessive consumption of alcohol has been considered a disease of addiction for over 300 years (Warner, 1994). Likewise, the disease concept of addiction has been expanded for the opiates and other now illegal drugs for 100 years (Levine, 1978) and for tobacco product for several decades (Henningfeld and Keenan, 1993).
Today, in the twenty-first century, the concept of addiction as a progressive, chronic disease remains an idea with substantial support in the recovery community.
This belief persists despite substantial scientific evidence that significant numbers of addicts eventually Mature Out of addiction as they age (Granville and Cloud, 1999, DSM-IV-TR, 2000, Hester and Miller, 2003)
In the next section, we will review the evidence that supports this observation.
The concept of addiction as a progressive, chronic disease remains an
idea with substantial support in the recovery community. This belief
persists despite substantial scientific evidence that significant
numbers of addicts eventually mature out of addiction as they age.
By
Roland J. Branconnier, MA and Kelly A. Moncheski, BA
“In terms of prophecy…we are currently in an epoch of enormous change. The millennium has passed, and with it has ended the two-thousand-year-long astrological Age of Pisces-the fish, which is also the sign of Jesus. As any astrological symbolist will tell you, the Piscean ideal believes that man must be told what to do by higher powers because man is incapable of thinking for himself. Hence it has been a time of fervent religion. Now, however, we are entering the Age of Aquarius-the water bearer-whose ideals claim that man will learn the truth and be able to think for himself. The ideological shift is enormous, and it is occurring right now.”
- The Da Vinci Code
History of Addiction as a Disease:
According to Mosby’s Medical Dictionary (2009): "addiction [ədik′shən] is a compulsive, uncontrollable dependence on a chemical substance, habit, or practice to such a degree that either the means of obtaining or ceasing use may cause severe emotional, mental, or physiologic reactions."
British clergy in the early seventeenth century initiated the use of the term “addiction” to describe excessive consumption of alcohol (Warner, 1994). Consistent with the above definition, “addiction” was considered an obligation or devotion to something.
Therefore, the term “addiction” became a metaphor describing a pathological preference for a given activity that lead to behave “as if addicted.” i.e. devoted to the activity.
There is an inclination for metaphors of this type to be reified, internalized and given causal significance (Sarbin, 1968). This appears to happened with the term “addiction” that has progressed from being a metaphorical description of a devotion to a particular activity, to an internal state, the existence of which is revealed by the devotion and then to be cause of the devotion.
The result of this line of reasoning is a tautology where the “addiction” causes the “addiction” (Akers, 1991). Despite this fallacious circular reasoning, in time, the characterization of “addiction” as a pathological preference gave rise to the notion that excessive use of alcohol was, in fact, a disease.
In the eighteenth century, the concept of alcoholism as a disease was articulated by Benjamin Rush, the Surgeon General of George Washington's revolutionary armies, in a pamphlet published in 1784 entitled: An Enquiry into the Effects of Spriuitous Liquors upon the Human Body, and Their Influence upon the Happiness of Society.
Rush was also one of the first to prescribe total abstinence from spirits as the sole remedy: "taste not, handle not, touch not." He saw treatment of drunkenness as a political issue (White, 1998, Barton, 1999).
The idea that alcoholism is a disease has always been a political and moral notion with no valid scientific basis. It was promoted in the United States in the early nineteenth century as a speculation based on erroneous physiological theory (Levine, 1978), and later became a mantra of the temperance movement (Gusfield, 1963).
It was resurrected in the 1930s by the founders of Alcoholics Anonymous (AA), who derived their views from an mixture of religious ideas, personal experiences and observations, and the unsubstantiated theories of the physician, William Silkworth (Robinson, 1979).The AA doctrine won support in the 1940s when the scientist, E.M. Jellinek, published an elaborate statistical study of the "phases of alcoholism" (Jellinek, 1946).
He portrayed an inevitable sequence of ever more uncontrollable drinking that led progressively to such symptoms as blackouts, tolerance, and withdrawal distress, until the drinker "hit bottom" as a derelict, became insane, or died.
Jellinek's work seemed to put a scientific imprimatur on the AA depiction of the alcoholic. That was not surprising, since he had taken his data from questionnaires that were prepared and distributed by AA and answered by fewer than 100 selected members.
Jellinek later acknowledged the source of his data and expressed reservations about its scientific validity (Jellinek, 1960). Nevertheless, his characterization of the intractable alcoholic has become widely accepted and is now entrenched as part of American folk science.
Historically, the excessive consumption of alcohol has been considered a disease of addiction for over 300 years (Warner, 1994). Likewise, the disease concept of addiction has been expanded for the opiates and other now illegal drugs for 100 years (Levine, 1978) and for tobacco product for several decades (Henningfeld and Keenan, 1993).
Today, in the twenty-first century, the concept of addiction as a progressive, chronic disease remains an idea with substantial support in the recovery community.
This belief persists despite substantial scientific evidence that significant numbers of addicts eventually Mature Out of addiction as they age (Granville and Cloud, 1999, DSM-IV-TR, 2000, Hester and Miller, 2003)
In the next section, we will review the evidence that supports this observation.
Maturing-Out of Drug Addiction: A Major Factor in Sustained Remission
In his 1962 seminal paper entitled: “Maturing Out of Narcotic Addiction” Charles Winick demonstrated that a substantial portion of heroin addicts mature out of their addiction as the age.
The following is excerpted from that article:
“There have been no studies of the age at which addicts stop taking drugs. There has been considerable acceptance in both lay and professional circles of the thesis that many addicts never stop using drugs, but continue as addicts until they die, except for unsuccessful attempts at withdrawal or for periods of enforced abstinence in jails or hospitals. There is some feeling that there is a high state of relapse among addicts, and this had led to considerable scepticism [sic] about addict's ability to remain abstinent, and how many addicts do remain abstinent.”
“There is an established procedure for putting addicts who have been inactive for five years into an inactive file. Inactivity is defined as not being reported as a drug-user for a period of five years. The five-year period is well established in medicine as the period after which a person with a chronic disease may be assumed to have recovered from the disease, if he has not had any symptoms of the disease during this period.”
“There is clearly a substancial [sic] concentration of addicts becoming inactive in their thirties. The range from plus one standard deviation to minus one standard deviation, which includes 68% of the sample, is from 26.445 to 43.795. The mean age is 35.12, and the median age 29.7.”
“Maturing out of addiction is the name we can give to the process by which the addict stops taking drugs, as the problems for which he originally began taking drugs become less salient and less urgent, if our hypothesis is correct. It is as if, metaphorically speaking, the addicts' inner fires have become banked by their thirties (emphasis added). They may feel that less is expected of them in the way of sex, aggressiveness, a vocation, helping their parents, or starting a family.
"As a result of some process of emotional homeostasis, the stresses and strains of life are becoming sufficiently stabilized for the typical addict in his thirties so that he can face them without the support provided by narcotics. This cycle may be analogous to that of the typical delinquent whose delinquency increases during his teens and remains constant till he reaches his late twenties, when it declines. His delinquencies may be his way of meeting the same needs which the addict meets by taking drugs. Since so many addicts are members of a delinquent sub-culture, the approximate consonance in age between addicts and delinquents may well be more than fortuitous.”
“The Federal Bureau of Narcotics made a tabulation of all the addicts originally reported to it during 1953 and 1954… There were 16,725 addicts originally reported during this period. Up to the end of 1959, 5,921 addicts had been reported again for the use of narcotics during the period between 1953-54 and 1959. There were 10,804 addicts, or 65%, who were originally reported, but who were not reported again during this period. These figures are roughly parallel to the findings of the federal hospitals at Lexington and Fort Worth that some 60% of their patients never return. It would thus seem possible to speculate that addiction may be a self-limiting process for perhaps two-thirds of addicts.” (emphasis added). (Winick, 1962).
The results of Winick’s study can be summarized as follows:
1. Addiction is not a chronic, progressive disease in a substantial portion (up to two-thirds) of addicts even when measured using a stringent criterion of five (5) years remission.
2. The Maturing Out of addiction process appears to begin in the mid-20s, peak in the mid-30, and for the majority of addicts is completed by the mid-40s.
3. Winick posits that the proximal cause of the Maturing Out process is due to: “the addicts' inner fires have become banked by their thirties.”
The results of the pioneering study have, for the most part, been replicated and extended since its publication 47 years ago.
There is now a substantial body of scientific evidence in the literature that suggests the Maturing Out of Addiction is a common property of all substances of abuse. (Robins, Helzer and Davis, 1975, Polich et al., 1980, Tuchfeld, 1981, Vaillant, 1983, Fillmore, 1988, Peele, 1991, Cunningham et al., 1995, Granfield and Cloud, 1999, Tucker et al., 2002, Hester and Miller, 2003, Miller, Wilbourne and Hettma, 2003, Grant et al., 2004).
The only aspect of Winick’s 1962 data that appears to be erroneous is an overly optimistic assessment of the portion of addicts who Mature Out. The more recent studies cited above suggest that the rate of sustained remission is closer to one-third.
In the next section, we will posit a neuroscientific basis for the Maturing Out process that Winick called: “the addicts' inner fires have become banked by their thirties.”
In his 1962 seminal paper entitled: “Maturing Out of Narcotic Addiction” Charles Winick demonstrated that a substantial portion of heroin addicts mature out of their addiction as the age.
The following is excerpted from that article:
“There have been no studies of the age at which addicts stop taking drugs. There has been considerable acceptance in both lay and professional circles of the thesis that many addicts never stop using drugs, but continue as addicts until they die, except for unsuccessful attempts at withdrawal or for periods of enforced abstinence in jails or hospitals. There is some feeling that there is a high state of relapse among addicts, and this had led to considerable scepticism [sic] about addict's ability to remain abstinent, and how many addicts do remain abstinent.”
“There is an established procedure for putting addicts who have been inactive for five years into an inactive file. Inactivity is defined as not being reported as a drug-user for a period of five years. The five-year period is well established in medicine as the period after which a person with a chronic disease may be assumed to have recovered from the disease, if he has not had any symptoms of the disease during this period.”
“There is clearly a substancial [sic] concentration of addicts becoming inactive in their thirties. The range from plus one standard deviation to minus one standard deviation, which includes 68% of the sample, is from 26.445 to 43.795. The mean age is 35.12, and the median age 29.7.”
“Maturing out of addiction is the name we can give to the process by which the addict stops taking drugs, as the problems for which he originally began taking drugs become less salient and less urgent, if our hypothesis is correct. It is as if, metaphorically speaking, the addicts' inner fires have become banked by their thirties (emphasis added). They may feel that less is expected of them in the way of sex, aggressiveness, a vocation, helping their parents, or starting a family.
"As a result of some process of emotional homeostasis, the stresses and strains of life are becoming sufficiently stabilized for the typical addict in his thirties so that he can face them without the support provided by narcotics. This cycle may be analogous to that of the typical delinquent whose delinquency increases during his teens and remains constant till he reaches his late twenties, when it declines. His delinquencies may be his way of meeting the same needs which the addict meets by taking drugs. Since so many addicts are members of a delinquent sub-culture, the approximate consonance in age between addicts and delinquents may well be more than fortuitous.”
“The Federal Bureau of Narcotics made a tabulation of all the addicts originally reported to it during 1953 and 1954… There were 16,725 addicts originally reported during this period. Up to the end of 1959, 5,921 addicts had been reported again for the use of narcotics during the period between 1953-54 and 1959. There were 10,804 addicts, or 65%, who were originally reported, but who were not reported again during this period. These figures are roughly parallel to the findings of the federal hospitals at Lexington and Fort Worth that some 60% of their patients never return. It would thus seem possible to speculate that addiction may be a self-limiting process for perhaps two-thirds of addicts.” (emphasis added). (Winick, 1962).
The results of Winick’s study can be summarized as follows:
1. Addiction is not a chronic, progressive disease in a substantial portion (up to two-thirds) of addicts even when measured using a stringent criterion of five (5) years remission.
2. The Maturing Out of addiction process appears to begin in the mid-20s, peak in the mid-30, and for the majority of addicts is completed by the mid-40s.
3. Winick posits that the proximal cause of the Maturing Out process is due to: “the addicts' inner fires have become banked by their thirties.”
The results of the pioneering study have, for the most part, been replicated and extended since its publication 47 years ago.
There is now a substantial body of scientific evidence in the literature that suggests the Maturing Out of Addiction is a common property of all substances of abuse. (Robins, Helzer and Davis, 1975, Polich et al., 1980, Tuchfeld, 1981, Vaillant, 1983, Fillmore, 1988, Peele, 1991, Cunningham et al., 1995, Granfield and Cloud, 1999, Tucker et al., 2002, Hester and Miller, 2003, Miller, Wilbourne and Hettma, 2003, Grant et al., 2004).
The only aspect of Winick’s 1962 data that appears to be erroneous is an overly optimistic assessment of the portion of addicts who Mature Out. The more recent studies cited above suggest that the rate of sustained remission is closer to one-third.
In the next section, we will posit a neuroscientific basis for the Maturing Out process that Winick called: “the addicts' inner fires have become banked by their thirties.”
Neurobiological Basis of Maturing Out of Addiction: An Age-Related Shift in Hyperbolic Temporal Discounting
The evolutionary basis for impulsive behavior may have evolved because in lower animals snatching up small rewards like food morsels rather than waiting for something bigger and better to come along can lead to getting more rewards in the long run.
This may help explain why a subset of modern day Homo sapiens find it so hard to turn down a smaller sooner rewards (SSR) for example, food, money, sex or euphoria rather than investing and waiting for a Larger Later Reward (LLR).
In nature, animals don't often encounter a situation where they must give up a better, but delayed, food morsel when they grab a quick meal. Impulsive behavior works well for animals because after grabbing the food, they can forget it and go back to their original foraging behavior.
That behavior can achieve high long-term gains even if it's impulsive (Barkow, Cosmides and Tooby, 1995, Stephens, Brown and Ydenburg, 2007).
The relationship between value and time falls under the general topic of Hyperbolic Temporal Discounting (HTD); the longer the delay to accessing a reward, the lower its value. There is a substantial literature on HTD in rats and pigeons and a smaller set of studies on non-laboratory animals such as jays, tamarins, marmosets and macaques (Ainslie, 2001, Rachlin, 2000).
In the HTD model, there is a trade-off between subjective value and time. Value is inversely proportional to time delay and preference reversal arises when the time delay to both rewards stretches out into the future (Logue, 1988, Montague, 2006).
The following example will help to clarify how the HTD model predicts decision making behavior:
I. If given the following choice, what would you do?
A) Get $50 immediately or
B) Get $100 two (2) months from now
Most people will choose “A”, the SSR.
II. Again, If given the following choice, what would you do?
C) Get $50 in ten (10) months
D) Get $100 in twelve (12) months
Most people will reverse their preference and choose “D” the LLR.
Since the difference in the delay is the same and the monetary payoffs are the same, the preference should be same. The HTD model predicts context effects such that that rewards dispensed in the future have a different subjective feel then rewards delivered in the immediate present. Human reverse their preferences depending on time and this fits the HTD model (Ainslie, 2001).
The reason for the preference reversal becomes apparent when we analyze the problem mathematically with the HTD formula. The formula for calculating a HTD curve is as follows:
v = V/ 1+(kD)
Where:
v = Current value
V = Initial Value
1 = Constant
k = Hyperbolic discount coefficient*
D = Delay in units of time
Applying the formula to Choice I we obtain:
A: v = $50/1+(1*0) = $50.00
B: v = $100/1+ (1*2) = $33.33
Since subjectively A > B, most people choose “A”
Applying the formula to Choice II we obtain:
C: v = $50/ 1+ (1*10) = $4.55
D: v = $100/ 1+ (1*12) = $7.69
Since subjectively D > C, most people choose “D”
The HTD model predicts context effects such that that rewards dispensed in the future have a different subjective feel than rewards delivered in the immediate present. Human reverse their preferences depending on time and this fits the HTD model.
*Hyperbolic discounting coefficients for practical purpose = 1(Chung and Herrenstein, 1967, Mazur, 1987, Ainslie, 2001) However, later we will provide data that coefficients > 1 may be a powerful predictor of vulnerability to addiction liability using a more complex formula developed by Lowenstein and Perlec (1992).
Give pigeons a choice between one and five food pellets; they consistently pick five and so will every other animal. Now make the pigeons work for its food. If they peck a red light, they are rewarded immediately with one pellet. If they peck a green light they get five food pellets.
I later is even a few seconds delay, the pigeon will consistently peck the red light for one pellet! It is irresistible. The value of the five pieces of food drops sharply after even a minimal delay. The observed impulsivity persists as long is there is a sizable difference between the SSR and LLR and there is some waiting period for the LLR and none for SSR.
With species as different as pigeons, rats, tamarins, macaques, the ability to wait for a LLR is on the order of seconds. Homo sapiens given a similar task will wait for hours, days and even years for an LLR. When it comes to patience we are the apex of the animal kingdom (Ainslie, 2001).
Applied to Homo sapiens, taking SSRs without hesitation may have paid off for our foraging Homo sapiens ancestors. Modern society forces us to make either or decisions about delayed benefits such as education, investment and marriage; the impulsive rules that work well for foragers do more harm than good when applied in these situations.
Impulsiveness is a major behavior problem for humans. Some humans do better at binary decisions making choices between an SSR and a LLR (Stephens, Brown and Ydenburg, 2007).
For over 40 years the social psychologist, Walter Mischel has conducted experiments with children and adults to characterize the capacity to Delay of Gratification (DoG).
His objective has been to determine how a child’s DoG changes over time, whether the capacity is inherited as an innate personality trait, and predicts intellectual competence in later life as well as impulsivity problem that lead to gambling, and addiction to substances.
In Mischel’s DoG studies, an experimenter brings a child into a room., sits the child down at a table and explains to the child that they may have a small treat immediately (SSR) or a larger treat later (LLR). The treats vary depending on the age of the child to sweets for the younger children and money for adolescents. The experimenter tells the child: “you can have this reward (SSR) now or, if you wait until I return, you can have several more of the same””.
If during the unspecified waiting period, the child wants the smaller reward, the child may ring a bell to bring the experimenter back into the room. Since the experimenter never specifies how long the child will have to wait, the children do not know how long they will have to wait for the LLR. The consistent finding is that children under the age of four have little to no DoG.
They almost invariably take the SSR instead of waiting for the LLR. Over time children gradually acquire the capacity to inhibit their impulses and wait for the LLR. The critical measure is not whether children do or do not take the SSR, but how long they wait to do so. Indeed, the number of seconds a two year old waits is highly predictive of later moral behavior.
Watch how long a child can inhibit DoG and you can predict how the child will be in the teen and into adulthood. Longitudinal studies of subjects tested as toddlers show that those children who have long DoG, cope better with negative situations in adulthood, have better job security, academic performance, and nonviolent stable interpersonal relationships.
Conversely, children who have little DoG have more anger and aggression toward the partners as adults. These studies suggest that impulsivity as measured by DoG is an excellent predictor of those who will transgress social norms (Mischel, Shoda and Rodriguez, 1989, Moore and Macgillivary, 2004).
The data presented above suggests that HTD curves change with aging. A cross-sectional experiment conducted by Green, Fry and Myerson (1994) the authors evaluated HTD curves in sixth grade children, college students and elderly adults (average age 68 years).
Each chose between hypothetical rewards stated on index cards. The delay of 1 week, 1 month, 6 months, 1 year, 3, years, 5 years, 10 years or 25 years. An immediate reward card (SSR) announced an amount of money to be received immediately. A single delay reward card (LLR) was keep in front of the subject while a series of immediate reward cards with amount varying up and down were show until the subject was indifferent between the SSR and the LLR.
Then a new delayed reward card (LLR) was place in front of the subject and the process repeated. A function was obtained for each subject showing the amount of money available immediately available equivalent to $1000 available with variable delays.
The results showed that three distinct HTD curves were generated with different degree of discounting coefficients (k). As expected children discount money most steeply, older adults less steeply. Thus, there is a progressive shift in HTD curves to be less steep from childhood through old age.
There must be some relationship between DoG in the Mischel experiments and the HTD experiment of Green, Fry and Myerson. It would be a violation of parsimony to regard the two highly correlated results as separate processes.
A real world example offered by Howard Rachlin (2000) illustrates how the two are related:
“Consider the following dilemma, which I frequently have to face. Several people are waiting for a crosstown bus at in New York at eleven o’clock on a cold night. Empty taxis (which cost three times as the bus) cruise around the shivering group like sharks around a shipwreck. How long do you wait before giving up and hailing a taxi? It depends on when you estimate that the next bus will come. The bus here represents the large-later reward (in the sense that the bus in that is lesser fare subtracts from less than the taxi from the reward of getting home). The taxi represent the smaller sooner reward and, as we have defined it, a temptation. If the larger-later reward (the coming of the bus) is not too far in the future, it would not be discounted too much and its current value, even when discounted, would be high than the small-sooner reward.
"In a normal situation were buses come on a fixed schedule, the time left until the coming of the bus would vary inversely with the time elapsed. The longer you waited, the less time you would have to wait. But a New York corner at eleven o’clock on a cold night is far from normal. A schedule is posted on the bus shelter, but as all the waiting people know, it is useless. There is in fact no way to know when the next bus will come. It may never come-or at least not until the next morning.
The people waiting for the bus are effectively equivalent to the children in Mischel’s experiment. The only possible basis for their estimation of how long they have to wait is how long they have already waited. Where waiting time is completely unpredictable, as at the bus stop, and in delay-of-gratification experiments , we would expect estimates of time left to vary directly with the time elapsed. The longer you have already waited for the bus, the longer you expect to wait. As time goes by, therefore, the larger reward recedes farther and farther into the distance. The steeper the discount function (The higher the k in Equation 2.2), the sooner the current value of the larger reward sinks below the constant smaller-sooner reward, the sooner the person waiting for the bus will hail a taxi, and the sooner the child in the delay-of-gratification will ring the bell. Thus, waiting time in the delay-of-gratification experiments depends on delay discount function, and people waiting for the bus hail taxis one by one in order of the flatness of their discount function.”
In recent years, excessively steep HTD curves have been implicated in vulnerability to the development of addiction (Ainslie, 2001, Bickel and Marsch, 2001, Bickel and Johnson, 2003, Glimcher, 2003). Vuchinich and Simpson (1998) demonstrated that heavy and problem drinking college students discounted delayed rewards more steeply than light drinkers.
Petry (2001) compared currently drinking alcoholics, abstaining alcoholics and non-alcoholic controls; He showed drinking alcoholic discounted more steeply than abstaining alcoholics, who in turn discounted more steeply than non-alcoholic controls.
Likewise with opiods Madden et al. (1997) and Madden, Bickel and Jacobs (1999) compared opiod-dependent subjects with matched control subjects from the same community. Opiod-dependent subjects the value of delayed hypothetical money more steeply than did control. Also, the opiod-dependent subjects discounted the value of a delayed hypothetical heroin reward still more steeply than the money.
Taken together these studies demonstrate that there are subject specific variations in the rate at which different types of rewards are discounted, and that HTD rates can be significantly higher for rewards that are frequently abuse.
Additional studies using real (not hypothetical) money also found that heroin using subjects discounted dramatically more steeply than non heroin controls (Kirby, Petry and Bickel, 1999, Kirby and Petry, 2004). It has also found that mild deprivation from opiod drugs leads to steeper discounting of delayed rewards in already dependent subjects (Giordano et al, 2002).
Recent studies on the neuroscience of addiction have found that the most if not all drugs of abuse from alcohol and marijuana to cocaine and opiods are mediated by stimulating the release of the neurotransmitter dopamine (DA) in the midbrain, nucleus accumbens (NAcc) (Berridge, 1996, Wise, 1996, Berridge and Robinson, 1998).
The NAcc is the same area that animals will stimulate electrically to the point of exhaustion. The NAcc is the same area that crack addicts will stimulate chemically to the point of exhaustion (Olds and Milner, 1954, Koob, Sanno, and Bloom, 1998, Johansen and Sagvolden, 2005).
Thus, addictive drugs by their direct action on the brain reward DA system provide the user with the ultimate SSR by delivering a powerful reinforcement with a minimum of delay. Redish and coworkers hypothesize that addiction lies partly in the brain and partly in the way we learn. By combining learning theory and the effects of drugs on DA, Redish posits that addictive drugs affect the same neurobiological mechanisms as natural learning systems.
These natural learning systems can be modeled through temporal-difference reinforcement learning (TDRL), which requires a reward-error signal that is carried by dopamine. Natural increases in DA occur after unexpected natural rewards. In TDRL, once the value function predicts the reward, learning stops. In contrast, addictive drugs produce a momentary increase in DA through neuropharmacological mechanisms, thereby continuing to drive learning and forcing the brain to over-select choices which lead to drug seeking behavior (Redish, Jensen and Johnson, 2008).
As important as the midbrain DA reward system is a regulating behavior, it is not predominate. While DA concentrations in the NAcc are necessary for addiction to occur, it is not sufficient. Stimulate drug such as methamphetamine and cocaine produce high concentrations of DA in the NAcc of non-addicts, a most people who are exposed to these addictive substances do not become addicts.
In animal with a frontal cortex, and especially in humans, cognitive judgment plays the dominate role in regulating behavior. Addiction, however, specifically limits the role of the top-down control by the frontal lobes. A substantial body of evidence that addictive drugs do more that commandeers the midbrain reward system. They also impair the inhibitory control of the DA midbrain reward system by the frontal lobes.
In effect, addiction first commandeers the DA reward system then impairs the top-down inhibitory control of the frontal lobes that would normally inhibit the midbrain DA reward system. Based on the above findings, Goldstein and Volkow (2002) have constructed an integrated model of addiction that they call “Impaired Response Inhibition and Salience Attribution” (I-RISA). The I-RISA model has received wide acceptance and is currently the dominate paradigm in the neuroscience of addiction.
In the final section of this paper, we will synthesize the information presented and posit the implication for the treatment and prognosis of addiction.
The evolutionary basis for impulsive behavior may have evolved because in lower animals snatching up small rewards like food morsels rather than waiting for something bigger and better to come along can lead to getting more rewards in the long run.
This may help explain why a subset of modern day Homo sapiens find it so hard to turn down a smaller sooner rewards (SSR) for example, food, money, sex or euphoria rather than investing and waiting for a Larger Later Reward (LLR).
In nature, animals don't often encounter a situation where they must give up a better, but delayed, food morsel when they grab a quick meal. Impulsive behavior works well for animals because after grabbing the food, they can forget it and go back to their original foraging behavior.
That behavior can achieve high long-term gains even if it's impulsive (Barkow, Cosmides and Tooby, 1995, Stephens, Brown and Ydenburg, 2007).
The relationship between value and time falls under the general topic of Hyperbolic Temporal Discounting (HTD); the longer the delay to accessing a reward, the lower its value. There is a substantial literature on HTD in rats and pigeons and a smaller set of studies on non-laboratory animals such as jays, tamarins, marmosets and macaques (Ainslie, 2001, Rachlin, 2000).
In the HTD model, there is a trade-off between subjective value and time. Value is inversely proportional to time delay and preference reversal arises when the time delay to both rewards stretches out into the future (Logue, 1988, Montague, 2006).
The following example will help to clarify how the HTD model predicts decision making behavior:
I. If given the following choice, what would you do?
A) Get $50 immediately or
B) Get $100 two (2) months from now
Most people will choose “A”, the SSR.
II. Again, If given the following choice, what would you do?
C) Get $50 in ten (10) months
D) Get $100 in twelve (12) months
Most people will reverse their preference and choose “D” the LLR.
Since the difference in the delay is the same and the monetary payoffs are the same, the preference should be same. The HTD model predicts context effects such that that rewards dispensed in the future have a different subjective feel then rewards delivered in the immediate present. Human reverse their preferences depending on time and this fits the HTD model (Ainslie, 2001).
The reason for the preference reversal becomes apparent when we analyze the problem mathematically with the HTD formula. The formula for calculating a HTD curve is as follows:
v = V/ 1+(kD)
Where:
v = Current value
V = Initial Value
1 = Constant
k = Hyperbolic discount coefficient*
D = Delay in units of time
Applying the formula to Choice I we obtain:
A: v = $50/1+(1*0) = $50.00
B: v = $100/1+ (1*2) = $33.33
Since subjectively A > B, most people choose “A”
Applying the formula to Choice II we obtain:
C: v = $50/ 1+ (1*10) = $4.55
D: v = $100/ 1+ (1*12) = $7.69
Since subjectively D > C, most people choose “D”
The HTD model predicts context effects such that that rewards dispensed in the future have a different subjective feel than rewards delivered in the immediate present. Human reverse their preferences depending on time and this fits the HTD model.
*Hyperbolic discounting coefficients for practical purpose = 1(Chung and Herrenstein, 1967, Mazur, 1987, Ainslie, 2001) However, later we will provide data that coefficients > 1 may be a powerful predictor of vulnerability to addiction liability using a more complex formula developed by Lowenstein and Perlec (1992).
Give pigeons a choice between one and five food pellets; they consistently pick five and so will every other animal. Now make the pigeons work for its food. If they peck a red light, they are rewarded immediately with one pellet. If they peck a green light they get five food pellets.
I later is even a few seconds delay, the pigeon will consistently peck the red light for one pellet! It is irresistible. The value of the five pieces of food drops sharply after even a minimal delay. The observed impulsivity persists as long is there is a sizable difference between the SSR and LLR and there is some waiting period for the LLR and none for SSR.
With species as different as pigeons, rats, tamarins, macaques, the ability to wait for a LLR is on the order of seconds. Homo sapiens given a similar task will wait for hours, days and even years for an LLR. When it comes to patience we are the apex of the animal kingdom (Ainslie, 2001).
Applied to Homo sapiens, taking SSRs without hesitation may have paid off for our foraging Homo sapiens ancestors. Modern society forces us to make either or decisions about delayed benefits such as education, investment and marriage; the impulsive rules that work well for foragers do more harm than good when applied in these situations.
Impulsiveness is a major behavior problem for humans. Some humans do better at binary decisions making choices between an SSR and a LLR (Stephens, Brown and Ydenburg, 2007).
For over 40 years the social psychologist, Walter Mischel has conducted experiments with children and adults to characterize the capacity to Delay of Gratification (DoG).
His objective has been to determine how a child’s DoG changes over time, whether the capacity is inherited as an innate personality trait, and predicts intellectual competence in later life as well as impulsivity problem that lead to gambling, and addiction to substances.
In Mischel’s DoG studies, an experimenter brings a child into a room., sits the child down at a table and explains to the child that they may have a small treat immediately (SSR) or a larger treat later (LLR). The treats vary depending on the age of the child to sweets for the younger children and money for adolescents. The experimenter tells the child: “you can have this reward (SSR) now or, if you wait until I return, you can have several more of the same””.
If during the unspecified waiting period, the child wants the smaller reward, the child may ring a bell to bring the experimenter back into the room. Since the experimenter never specifies how long the child will have to wait, the children do not know how long they will have to wait for the LLR. The consistent finding is that children under the age of four have little to no DoG.
They almost invariably take the SSR instead of waiting for the LLR. Over time children gradually acquire the capacity to inhibit their impulses and wait for the LLR. The critical measure is not whether children do or do not take the SSR, but how long they wait to do so. Indeed, the number of seconds a two year old waits is highly predictive of later moral behavior.
Watch how long a child can inhibit DoG and you can predict how the child will be in the teen and into adulthood. Longitudinal studies of subjects tested as toddlers show that those children who have long DoG, cope better with negative situations in adulthood, have better job security, academic performance, and nonviolent stable interpersonal relationships.
Conversely, children who have little DoG have more anger and aggression toward the partners as adults. These studies suggest that impulsivity as measured by DoG is an excellent predictor of those who will transgress social norms (Mischel, Shoda and Rodriguez, 1989, Moore and Macgillivary, 2004).
The data presented above suggests that HTD curves change with aging. A cross-sectional experiment conducted by Green, Fry and Myerson (1994) the authors evaluated HTD curves in sixth grade children, college students and elderly adults (average age 68 years).
Each chose between hypothetical rewards stated on index cards. The delay of 1 week, 1 month, 6 months, 1 year, 3, years, 5 years, 10 years or 25 years. An immediate reward card (SSR) announced an amount of money to be received immediately. A single delay reward card (LLR) was keep in front of the subject while a series of immediate reward cards with amount varying up and down were show until the subject was indifferent between the SSR and the LLR.
Then a new delayed reward card (LLR) was place in front of the subject and the process repeated. A function was obtained for each subject showing the amount of money available immediately available equivalent to $1000 available with variable delays.
The results showed that three distinct HTD curves were generated with different degree of discounting coefficients (k). As expected children discount money most steeply, older adults less steeply. Thus, there is a progressive shift in HTD curves to be less steep from childhood through old age.
There must be some relationship between DoG in the Mischel experiments and the HTD experiment of Green, Fry and Myerson. It would be a violation of parsimony to regard the two highly correlated results as separate processes.
A real world example offered by Howard Rachlin (2000) illustrates how the two are related:
“Consider the following dilemma, which I frequently have to face. Several people are waiting for a crosstown bus at in New York at eleven o’clock on a cold night. Empty taxis (which cost three times as the bus) cruise around the shivering group like sharks around a shipwreck. How long do you wait before giving up and hailing a taxi? It depends on when you estimate that the next bus will come. The bus here represents the large-later reward (in the sense that the bus in that is lesser fare subtracts from less than the taxi from the reward of getting home). The taxi represent the smaller sooner reward and, as we have defined it, a temptation. If the larger-later reward (the coming of the bus) is not too far in the future, it would not be discounted too much and its current value, even when discounted, would be high than the small-sooner reward.
"In a normal situation were buses come on a fixed schedule, the time left until the coming of the bus would vary inversely with the time elapsed. The longer you waited, the less time you would have to wait. But a New York corner at eleven o’clock on a cold night is far from normal. A schedule is posted on the bus shelter, but as all the waiting people know, it is useless. There is in fact no way to know when the next bus will come. It may never come-or at least not until the next morning.
The people waiting for the bus are effectively equivalent to the children in Mischel’s experiment. The only possible basis for their estimation of how long they have to wait is how long they have already waited. Where waiting time is completely unpredictable, as at the bus stop, and in delay-of-gratification experiments , we would expect estimates of time left to vary directly with the time elapsed. The longer you have already waited for the bus, the longer you expect to wait. As time goes by, therefore, the larger reward recedes farther and farther into the distance. The steeper the discount function (The higher the k in Equation 2.2), the sooner the current value of the larger reward sinks below the constant smaller-sooner reward, the sooner the person waiting for the bus will hail a taxi, and the sooner the child in the delay-of-gratification will ring the bell. Thus, waiting time in the delay-of-gratification experiments depends on delay discount function, and people waiting for the bus hail taxis one by one in order of the flatness of their discount function.”
In recent years, excessively steep HTD curves have been implicated in vulnerability to the development of addiction (Ainslie, 2001, Bickel and Marsch, 2001, Bickel and Johnson, 2003, Glimcher, 2003). Vuchinich and Simpson (1998) demonstrated that heavy and problem drinking college students discounted delayed rewards more steeply than light drinkers.
Petry (2001) compared currently drinking alcoholics, abstaining alcoholics and non-alcoholic controls; He showed drinking alcoholic discounted more steeply than abstaining alcoholics, who in turn discounted more steeply than non-alcoholic controls.
Likewise with opiods Madden et al. (1997) and Madden, Bickel and Jacobs (1999) compared opiod-dependent subjects with matched control subjects from the same community. Opiod-dependent subjects the value of delayed hypothetical money more steeply than did control. Also, the opiod-dependent subjects discounted the value of a delayed hypothetical heroin reward still more steeply than the money.
Taken together these studies demonstrate that there are subject specific variations in the rate at which different types of rewards are discounted, and that HTD rates can be significantly higher for rewards that are frequently abuse.
Additional studies using real (not hypothetical) money also found that heroin using subjects discounted dramatically more steeply than non heroin controls (Kirby, Petry and Bickel, 1999, Kirby and Petry, 2004). It has also found that mild deprivation from opiod drugs leads to steeper discounting of delayed rewards in already dependent subjects (Giordano et al, 2002).
Recent studies on the neuroscience of addiction have found that the most if not all drugs of abuse from alcohol and marijuana to cocaine and opiods are mediated by stimulating the release of the neurotransmitter dopamine (DA) in the midbrain, nucleus accumbens (NAcc) (Berridge, 1996, Wise, 1996, Berridge and Robinson, 1998).
The NAcc is the same area that animals will stimulate electrically to the point of exhaustion. The NAcc is the same area that crack addicts will stimulate chemically to the point of exhaustion (Olds and Milner, 1954, Koob, Sanno, and Bloom, 1998, Johansen and Sagvolden, 2005).
Thus, addictive drugs by their direct action on the brain reward DA system provide the user with the ultimate SSR by delivering a powerful reinforcement with a minimum of delay. Redish and coworkers hypothesize that addiction lies partly in the brain and partly in the way we learn. By combining learning theory and the effects of drugs on DA, Redish posits that addictive drugs affect the same neurobiological mechanisms as natural learning systems.
These natural learning systems can be modeled through temporal-difference reinforcement learning (TDRL), which requires a reward-error signal that is carried by dopamine. Natural increases in DA occur after unexpected natural rewards. In TDRL, once the value function predicts the reward, learning stops. In contrast, addictive drugs produce a momentary increase in DA through neuropharmacological mechanisms, thereby continuing to drive learning and forcing the brain to over-select choices which lead to drug seeking behavior (Redish, Jensen and Johnson, 2008).
As important as the midbrain DA reward system is a regulating behavior, it is not predominate. While DA concentrations in the NAcc are necessary for addiction to occur, it is not sufficient. Stimulate drug such as methamphetamine and cocaine produce high concentrations of DA in the NAcc of non-addicts, a most people who are exposed to these addictive substances do not become addicts.
In animal with a frontal cortex, and especially in humans, cognitive judgment plays the dominate role in regulating behavior. Addiction, however, specifically limits the role of the top-down control by the frontal lobes. A substantial body of evidence that addictive drugs do more that commandeers the midbrain reward system. They also impair the inhibitory control of the DA midbrain reward system by the frontal lobes.
In effect, addiction first commandeers the DA reward system then impairs the top-down inhibitory control of the frontal lobes that would normally inhibit the midbrain DA reward system. Based on the above findings, Goldstein and Volkow (2002) have constructed an integrated model of addiction that they call “Impaired Response Inhibition and Salience Attribution” (I-RISA). The I-RISA model has received wide acceptance and is currently the dominate paradigm in the neuroscience of addiction.
In the final section of this paper, we will synthesize the information presented and posit the implication for the treatment and prognosis of addiction.
Jails, Institutions and Death: Folk Science vs. Empirical Science of Addiction
Folk Science describes ways of understanding and predicting the natural and social world, without the use of rigorous methodologies of the scientific method.
Folk biology posited vitalism a life force flowing through all living things, which in their functional design, were believed to have been created ex nihilo by an intelligent designer. Folk psychology compelled us to search for the homunculus in the brain — a ghost in the machine — a mind somehow disconnected from the brain.
The reason folk science so often gets it wrong is that we evolved in an environment radically different from the one in which we now live. We live a scant three score and 10 years, far too short a time to witness evolution, continental drift or long-term environmental changes.
Folk science leads us to trust anecdotes as data, anecdotes involving transcendent beings, compelling us to make causal inferences linking these non-material entities to all manner of material events, illness being the most personal. Because people often recover from sickness naturally, whatever was done just before recovery receives the credit, prayer being the most common.
Of course, people will continue praying for their ailing loved ones, and by chance some of them will recover, and our folk science brains will find meaning in these random patterns. But for us to discriminate true causal inferences from false, real science need to trump folk science.
We began our discussion by tracing the history of the roots of the Disease Concept of Addiction (DCoA). The folk science of the DCoA suggests that addiction is a chronic, progressive, intractable process that inevitably leads to jail, institutions, and death.
This mantra was adopted by the Twelve Step Programs (TSPs) in the twentieth century and is still the dominate force in addiction recovery in the early twenty-first century. Their nostrum for addiction recovery involves turning your will over to a Higher Power (a code word for God) attending meeting and reforming your life according to the twelve steps originally promulgated by Alcoholics Anonymous (AA) in the 1930s. TSPs advocate that this formula is the only road to addiction recovery.
Indeed the “Big Book” of AA states categorically (Alcoholics Anonymous, 1986):
“Rarely have we seen a person fail who has thoroughly followed our path. Those who do not recover are people who cannot or will not completely give themselves to this simple program, usually men and women who are constitutionally incapable of being honest with themselves. There are such unfortunates. They are not at fault; they seem to have been born that way. They are naturally incapable of grasping and developing a manner of living which demands rigorous honesty.
We have learned from our group experience that those who keep coming to our meetings regularly stay clean.”
Likewise, the “White Book” of Narcotics Anonymous states (Narcotics Anonymous, 1986):
“Many of us ended up in jail, or sought help through medicine, religion, and psychiatry.
We feel that our approach to the disease of addiction is completely realistic, for the therapeutic value of one addict helping another is without parallel. None of these methods was sufficient for us. Our disease always resurfaced or continued to progress until, in desperation, we sought help from each other in Narcotics Anonymous.”
The problem with this TSP hyperbole is that it is based on folk science and completely unsupported by empirical science. A recent meta-analysis conducted by Ferri, Amato and Davoli (2006) of the efficacy of TSPs concluded the following:
“Alcoholics Anonymous (AA) is an international organization of recovering alcoholics that offers emotional support through self-help groups and a model of abstinence for people recovering from alcohol dependence, using a 12-step approach. Although it is the most common, AA is not the only 12-step intervention available there are other 12-step approaches labelled Twelve Step Facilitation (TSF)…
Eight trials involving 3417 people were included. AA may help patients to accept treatment and keep patients in treatment more than alternative treatments, though the evidence for this is from one small study that combined AA with other interventions and should not be regarded as conclusive. Other studies reported similar retention rates regardless of treatment group. Three studies compared AA combined with other interventions against other treatments and found few differences in the amount of drinks and percentage of drinking days. Severity of addiction and drinking consequence did not seem to be differentially influenced by TSF versus comparison treatment interventions, and no conclusive differences in treatment drop out rates were reported…
No experimental studies unequivocally demonstrated the effectiveness of AA or TSF approaches for reducing alcohol dependence or problems.”
Indeed, some evidence suggests that TSP may, in fact, impede rather facilitate recovery. Consider the following:
Two studies cited by Fingarette (1988) looked at eighteen-month follow-ups of people in AA found that, at most, 25% of people were still attending meetings, and that among regular AA members, only 22% consistently maintained sobriety. Taken together, these numbers indicate that fewer than 5.5% (0.22 x 0.25 x 100) of people both attended and stayed sober in AA.
We have presented data that the rate of Maturing Out of Addiction is approximately 30% If 30% of addicts achieve sustained remission as they Mature Out of Addiction and the rate of sustained remission in TSPs is 5.5% TSPs have a rate of sustained remission of -24.5%! We posit that such data strongly suggests that not only are TSPs ineffective but are like to impede the achievement of sobriety by their members.
Empirical science has shown that Maturing Out of Addiction (MOoA) is a real phenomenon that accounts for approximately 30% of sustained remissions. The neurobiological basis of MOoA is probably related to an age-related shift in the HTD. We posit that the flattening of HTD over the course of the life-span is among the multiple neural processes that exhibit slowing with aging (Powell and Whitla, 1994).
HTD may also offer an explanation of why some individual are vulnerable to addiction while others are not. HTD is an inherited trait that is an evolutionary product of our foraging behavior prior to the advent of agriculture during the Neolithic Revolution (Barkow, Cosmides and Tooby, 1995, Rudgley, 1999, Boyd and Richerson, 2005, Stephens, Brown and Ydenburg, 2007).
We posit that the HTD coefficients are probably expressed in a normal distribution. This would suggest that perhaps vulnerability to addiction has a defined cut-off point such as 2 standard deviations above the mean. While this is a working hypothesis, it is readily amenable to empirical scientific investigation.
Another question is why adolescent and even children are more vulnerable to developing addiction. In the prior section we examined the I-RISA model of addiction of Goldstein and Volkow (2002). Recall that the I-RISA model posits two important components to the development of addiction.
The first component is response inhibition or top-down control of the frontal lobe to inhibit the DA midbrain reward system. The second component is salience attribution i.e. addictive substance acquiring excessive importance (in HTD terms, addictive substances are the ultimate SSR).
Recent work on the maturation of the brain show that cerebral maturation proceeds from the posterior brain in the occipital lobes to the frontal lobes with the process reaching complete maturation around the age of twenty (Gogtay, Giedd and Lusk, 2004, Anderson, Jacobs and Anderson, 2008).
The implication of this finding is that adolescent and children do not possess the necessary top-down control to inhibit the DA midbrain reward system (Chambers, Taylor and Potenza, 2003). Combine this with excessive HTD and it is formula for development of addiction in youth.
Folk science suggests that addiction is a disease with a chronic, intractable, progressive course leading to jails, institutions and death. Empirical science challenges this conception and suggests that a significant number of addicts Mature Out as the age.
We posit that the empirical evidence does not support the conclusion that addiction, per se, is a disease. We suggest that addiction is primarily an autogenic dysaptation of the normal learing and memory system that evolution has developed to ensure survival.
We have coined the term autogenic dysaptation because we think that it is a more accurate description of the addiction phenomenon. Addiction is autogenic because it cannot occur until the agent ingests the first dose of an addictive substance. Addiction is a dysaptation because addictive substances subvert normal learning and memory systems to generate behavior, which in the long run, is counter-productive to survival.
With the dawning of the Age of Aquarius in the twenty first century folk science and its advocates will be supplanted by empirical science in addiction recovery.
Neuroscience is unlocking the mechanisms of addiction, and from that knowledge will be developed effective somatic treatments for addiction. Knowledge is growing in this area so rapidly, that we suggest, that it is not overly optimistic, to predict a cure for addiction in the next ten years.
If you doubt the power of empirical science over folk science consider the following scenario:
You are a recovering heroin addict. You have 60 days clean time. You decide that you will attend your Narcotic Anonymous home group tonight. As you arrive at the meeting you are greeted by one of your old running buddies. He has heroin and asked you if you want some. You immediately say YES. You go to the rest room, shoot-up and decide it’s a good idea to go to the meeting. You sit down, nod-off, fall on the floor and turn blue.
You are overdosed and are about to die.
What do you want your group members to do?
A. Pray for you or
B. Call 911 and get you a shot of Narcan ASAP
Case closed.
Until neuroscience solves the puzzle of addiction, the addict need not despair. The aging process is your best ally. For you, getting older means getting better.
[See page 5 for references]
Folk Science describes ways of understanding and predicting the natural and social world, without the use of rigorous methodologies of the scientific method.
Folk biology posited vitalism a life force flowing through all living things, which in their functional design, were believed to have been created ex nihilo by an intelligent designer. Folk psychology compelled us to search for the homunculus in the brain — a ghost in the machine — a mind somehow disconnected from the brain.
The reason folk science so often gets it wrong is that we evolved in an environment radically different from the one in which we now live. We live a scant three score and 10 years, far too short a time to witness evolution, continental drift or long-term environmental changes.
Folk science leads us to trust anecdotes as data, anecdotes involving transcendent beings, compelling us to make causal inferences linking these non-material entities to all manner of material events, illness being the most personal. Because people often recover from sickness naturally, whatever was done just before recovery receives the credit, prayer being the most common.
Of course, people will continue praying for their ailing loved ones, and by chance some of them will recover, and our folk science brains will find meaning in these random patterns. But for us to discriminate true causal inferences from false, real science need to trump folk science.
We began our discussion by tracing the history of the roots of the Disease Concept of Addiction (DCoA). The folk science of the DCoA suggests that addiction is a chronic, progressive, intractable process that inevitably leads to jail, institutions, and death.
This mantra was adopted by the Twelve Step Programs (TSPs) in the twentieth century and is still the dominate force in addiction recovery in the early twenty-first century. Their nostrum for addiction recovery involves turning your will over to a Higher Power (a code word for God) attending meeting and reforming your life according to the twelve steps originally promulgated by Alcoholics Anonymous (AA) in the 1930s. TSPs advocate that this formula is the only road to addiction recovery.
Indeed the “Big Book” of AA states categorically (Alcoholics Anonymous, 1986):
“Rarely have we seen a person fail who has thoroughly followed our path. Those who do not recover are people who cannot or will not completely give themselves to this simple program, usually men and women who are constitutionally incapable of being honest with themselves. There are such unfortunates. They are not at fault; they seem to have been born that way. They are naturally incapable of grasping and developing a manner of living which demands rigorous honesty.
We have learned from our group experience that those who keep coming to our meetings regularly stay clean.”
Likewise, the “White Book” of Narcotics Anonymous states (Narcotics Anonymous, 1986):
“Many of us ended up in jail, or sought help through medicine, religion, and psychiatry.
We feel that our approach to the disease of addiction is completely realistic, for the therapeutic value of one addict helping another is without parallel. None of these methods was sufficient for us. Our disease always resurfaced or continued to progress until, in desperation, we sought help from each other in Narcotics Anonymous.”
The problem with this TSP hyperbole is that it is based on folk science and completely unsupported by empirical science. A recent meta-analysis conducted by Ferri, Amato and Davoli (2006) of the efficacy of TSPs concluded the following:
“Alcoholics Anonymous (AA) is an international organization of recovering alcoholics that offers emotional support through self-help groups and a model of abstinence for people recovering from alcohol dependence, using a 12-step approach. Although it is the most common, AA is not the only 12-step intervention available there are other 12-step approaches labelled Twelve Step Facilitation (TSF)…
Eight trials involving 3417 people were included. AA may help patients to accept treatment and keep patients in treatment more than alternative treatments, though the evidence for this is from one small study that combined AA with other interventions and should not be regarded as conclusive. Other studies reported similar retention rates regardless of treatment group. Three studies compared AA combined with other interventions against other treatments and found few differences in the amount of drinks and percentage of drinking days. Severity of addiction and drinking consequence did not seem to be differentially influenced by TSF versus comparison treatment interventions, and no conclusive differences in treatment drop out rates were reported…
No experimental studies unequivocally demonstrated the effectiveness of AA or TSF approaches for reducing alcohol dependence or problems.”
Indeed, some evidence suggests that TSP may, in fact, impede rather facilitate recovery. Consider the following:
Two studies cited by Fingarette (1988) looked at eighteen-month follow-ups of people in AA found that, at most, 25% of people were still attending meetings, and that among regular AA members, only 22% consistently maintained sobriety. Taken together, these numbers indicate that fewer than 5.5% (0.22 x 0.25 x 100) of people both attended and stayed sober in AA.
We have presented data that the rate of Maturing Out of Addiction is approximately 30% If 30% of addicts achieve sustained remission as they Mature Out of Addiction and the rate of sustained remission in TSPs is 5.5% TSPs have a rate of sustained remission of -24.5%! We posit that such data strongly suggests that not only are TSPs ineffective but are like to impede the achievement of sobriety by their members.
Empirical science has shown that Maturing Out of Addiction (MOoA) is a real phenomenon that accounts for approximately 30% of sustained remissions. The neurobiological basis of MOoA is probably related to an age-related shift in the HTD. We posit that the flattening of HTD over the course of the life-span is among the multiple neural processes that exhibit slowing with aging (Powell and Whitla, 1994).
HTD may also offer an explanation of why some individual are vulnerable to addiction while others are not. HTD is an inherited trait that is an evolutionary product of our foraging behavior prior to the advent of agriculture during the Neolithic Revolution (Barkow, Cosmides and Tooby, 1995, Rudgley, 1999, Boyd and Richerson, 2005, Stephens, Brown and Ydenburg, 2007).
We posit that the HTD coefficients are probably expressed in a normal distribution. This would suggest that perhaps vulnerability to addiction has a defined cut-off point such as 2 standard deviations above the mean. While this is a working hypothesis, it is readily amenable to empirical scientific investigation.
Another question is why adolescent and even children are more vulnerable to developing addiction. In the prior section we examined the I-RISA model of addiction of Goldstein and Volkow (2002). Recall that the I-RISA model posits two important components to the development of addiction.
The first component is response inhibition or top-down control of the frontal lobe to inhibit the DA midbrain reward system. The second component is salience attribution i.e. addictive substance acquiring excessive importance (in HTD terms, addictive substances are the ultimate SSR).
Recent work on the maturation of the brain show that cerebral maturation proceeds from the posterior brain in the occipital lobes to the frontal lobes with the process reaching complete maturation around the age of twenty (Gogtay, Giedd and Lusk, 2004, Anderson, Jacobs and Anderson, 2008).
The implication of this finding is that adolescent and children do not possess the necessary top-down control to inhibit the DA midbrain reward system (Chambers, Taylor and Potenza, 2003). Combine this with excessive HTD and it is formula for development of addiction in youth.
Folk science suggests that addiction is a disease with a chronic, intractable, progressive course leading to jails, institutions and death. Empirical science challenges this conception and suggests that a significant number of addicts Mature Out as the age.
We posit that the empirical evidence does not support the conclusion that addiction, per se, is a disease. We suggest that addiction is primarily an autogenic dysaptation of the normal learing and memory system that evolution has developed to ensure survival.
We have coined the term autogenic dysaptation because we think that it is a more accurate description of the addiction phenomenon. Addiction is autogenic because it cannot occur until the agent ingests the first dose of an addictive substance. Addiction is a dysaptation because addictive substances subvert normal learning and memory systems to generate behavior, which in the long run, is counter-productive to survival.
With the dawning of the Age of Aquarius in the twenty first century folk science and its advocates will be supplanted by empirical science in addiction recovery.
Neuroscience is unlocking the mechanisms of addiction, and from that knowledge will be developed effective somatic treatments for addiction. Knowledge is growing in this area so rapidly, that we suggest, that it is not overly optimistic, to predict a cure for addiction in the next ten years.
If you doubt the power of empirical science over folk science consider the following scenario:
You are a recovering heroin addict. You have 60 days clean time. You decide that you will attend your Narcotic Anonymous home group tonight. As you arrive at the meeting you are greeted by one of your old running buddies. He has heroin and asked you if you want some. You immediately say YES. You go to the rest room, shoot-up and decide it’s a good idea to go to the meeting. You sit down, nod-off, fall on the floor and turn blue.
You are overdosed and are about to die.
What do you want your group members to do?
A. Pray for you or
B. Call 911 and get you a shot of Narcan ASAP
Case closed.
Until neuroscience solves the puzzle of addiction, the addict need not despair. The aging process is your best ally. For you, getting older means getting better.
[See page 5 for references]
References
Ainslie, G. (2001). Breakdown of Will. Cambridge: Cambridge University Press.
Akers, R. (1991). Addiction: The troublesome concept. Journal of Drug Issues 21: 777-793.
Alcoholics Anonymous (1986). The Story of How Many Thousands of Men and Women Have Recovered from Alcoholism. New York: Alcoholics Anonymous World Services, Inc.
American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th edn. Text Revision. Washington, D.C.: American Psychiatric Association.
Anderson, V., R. Jacobs and P. Anderson (2008). Executive Functions and the Frontal Lobes: A Lifespan Perspective. New York: Psychology Press.
Barkow, J.H., L. Cosmides and J. Tooby (1995). The Adapted Mind: Evolutionary Psychology and the Generation of Culture. New York: Oxford University Press.
Barton, D. (1999). Benjamin Rush. Aledo, TX: Wallbuilder Press.
Berridge, K.C. (1996). Food reward: Brain substrates of wanting and liking. Neuroscience and Behavior Reviews 20: 1-25.
Berridge, K. and T. Robinson. (1998). what is the role of dopamine in reward: Hedonic impact, reward learning or interactive salience? Brain Research Reviews 28: 309-369.
Bickel, W., and L. Marsch. (2001). toward a behavioral economic understanding of drug dependence: Delay discounting processes. Addiction 96: 73-86.
Bickel, W., and M. Johnson. (2003). Delay discounting: A fundamental behavioral process of drug dependence. In Time and Decision: Economic and Psychological Perspectives on Intertemporal Choice, Ed G. Lowenstein, D. Read, and R. Baumeister. New York: Russel Sage Foundation.
Boyd, R. and P.J. Richerson (2005). The Origin and Evolution of Cultures. New York: Oxford University Press.
Brown, D. (2003). The Da Vinci Code: A Novel. New York: Doubleday, pp. 267-68.
Chambers, R.A., J. Taylor, and M. Potenza (2003). Developmental neurocircuitry of motivation in adolescence: A critical period of addiction vulnerability. American Journal of Psychiatry 160: 1041-1052.
Chung, S., and R. Herrenstein. (1967). Choice and delay of reinforcement. Journal of the Experimental Analysis of Behavior 10: 67-74.
Cunningham, J., L. Sobell and G. Kapur (1995). Resolution from alcohol problems with and without treatment: reasons for change. Journal of Substance Abuse 7(3): 365-372.
Ferri, M., L. Amato and M. Davoli (2006). Alcoholic’s anonymous and other 12-step programmes for alcohol dependence. Addiction 8: 1402-1403.
Fillmore, K.M. (1988). Spontaneous Remission of Alcohol Problems: Evaluating Recovery Outcomes. San Diego: University of California.
Fingarette, H. (1988). Heavy Drinking. Berkley, CA: University of California Press.
Giordano, L., W. Bickel, G. Lowenstein, E. Jacobs, L. Marsch, and G. Badger (2002). Mild opiod deprivation increases the degree that opiod-dependent outpatients discount delayed heroin and money. Psychopharmacology 163: 174-182..
Glimcher, P. (2003). Decisions, Uncertainty, and the Brain. Cambridge, MA: MIT Press.
Gogtay, N., J. N. Giedd, L. Lusk, et al. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences 101(21): 8174-8179.
Goldstein, R., and N. Volkow (2002). Drug addiction and its underlying neurobiological basis: Neuroimaging evidence for the involvement of the prefrontal cortex. American Journal of Psychiatry 159: 1642-1652..
Granfield, R. and W. Cloud (1999). Coming Clean: Overcoming Addiction without Treatment. New York: New York University Press.
Grant, B.; D. A. Dawson, F.S., Stinson, et al. (2004). The 12-month prevalence and trends in DSM-IV alcohol abuse and dependence; United States, 1991-1992 and 2001-2002. Drug and Alcohol Dependence 74: 223-234.
Green, L., A. Fry, and J. Myerson (1994). Discounting of delayed rewards: A life-span comparison. Psychological Science 5: 33-36.
Gusfield, J.R. (1963). Symbolic Crusade: Status Politics and the American Temperance Movement. University of Illinois Press: Urbana.
Henningfeld, J.E. and R.M. Keenan (1993) Nicotine delivery kinetics and abuse liability. Journal of Consulting Clinical Psychology 61: 743-750.
Hester, R.K., and W.R. Miller. (2003) Handbook of Alcoholism Treatment Approaches: Effective Alternatives. Boston: Allyn & Bacon, Inc.
Jellinek, E.M. (1946). Phases in the drinking history of alcoholics. Quarterly Journal of Studies on Alcohol 7: 1-88.
Jellinek, E.M. (1960). The Disease Concept of Alcoholism. New Haven, CT: Hillhouse Press.
Johansen E.B., and T. Sagvolden. (2005). Behavioral effects of intra-cranial self-stimulation in an animal model of attention-deficit/hyperactivity disorder (ADHD). Behavioral Brain Research 162(1):32-46.
Kirby, K., N. Petry, and W. Bickel (1999). Heroin addicts discount delayed rewards at higher rates than non-drug using controls. Journal of Experimental Psychology: General Processes 128: 78-87.
Kirby, K., and N. Petry (2004). Heroin and cocaine abusers have higher discount rates for delayed rewards than alcoholics and non-drug-using controls. Addiction 99: 461-471.
Koob, G., Paolo Sanno, and F. Bloom (1998). Neuroscience of addiction. Neuron 21: 467-676.
Levine, H. (1978). The discovery of addiction: Changing conceptions of habitual drunkenness in America. Journal of Studies of Alcohol 39: 143-174.
Logue, A.W. (1988). Research on self-control: An integrated framework. Behavioral and Brain Sciences 11: 665-679.
Lowenstein, G., and D. Prelec (1992). Anomalies in intertemporal choice: Evidence and interpretation. Quarterly Journal of Economics 107: 573-597.
Madden G., N. Petry, G. Badger, and W. Bickel (1997). Impulsive and self-control choices in opiod-dependent subjects and non-drug using controls. Drugs and monetary rewards. Experimental and Clinical Psychopharmacology 5: 256-262.
Madden G., W. Bickel, and E. Jacobs (1999). Discounting of delayed rewards in opiod-dependent outpatients: Exponential or hyperbolic discounting functions. Experimental and Clinical Psychopharmacology 7: 284-293.
Mazur, J.E (1987). An adjusting procedure for studying delayed reinforcement. In M.L. Commons, J.E. Mazur, J.A. Nevins and H. Rachlin, Eds. Quantitative Analysis of Behavior Vol. 5: The effects of delay and intervening event on reinforcement value. Mawah, NJ: Erlbaum, pp 55-73.
Miller, W.R., P.L. Wilbourne, and J.E. Hettma (2003). What works? A summary of alcohol treatment outcomes research. In R.K. Hester and W.R. Miller, eds. Handbook of Alcohol Treatment Approaches: Effective Alternatives. Boston: Allyn & Bacon.
Mischel, W., Y. Shoda, and M. Rodriguez (1989) Delay of gratification in children. Science 244: 933-938.
Montague, Read. (2006). Why choose this book? : How we make decisions.
New York: Penguin Group.
Moore, C. and S. Macgillivray. (2004). Altruism, prudence, and theory of mind in preschoolers. New Directions for Child and Adolescent Development 103: 51-62.
Mosby's Medical Dictionary (2009), 8th edn. Amsterdam: Elsevier.
Narcotics Anonymous (1986). Van Nuys, CA: Narcotics Anonymous World Services, Inc.
Olds, J. and P. Milner (1954). Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. Journal of Comparative and Physiological Psychology 47: 419-427.
Peele, S. (1991). The Truth about Addiction and Recovery: The Life Process Program for Outgrowing Destructive Habits. New York: Simon & Schuster.
Petry, N. (2001). Delay discounting of money in alcohol in actively using alcoholics, currently abstinent alcoholics, and controls. Psychopharmacology 154: 243-250.
Polich, J.M., D.J. Armor, and H.B. Braiker (1980). Patterns of alcoholism over four years. Journal Studies of Alcohol. 41(5): 397-416.
Powell, D.H., and D.K. Whitla. (1994). Profiles in Cognitive Aging. Cambridge, MA: Harvard University Press.
Rachlin, H. (2000). The Science of Self-Control. Cambridge, MA: Harvard University Press.
Redish, A.D., S. Jensen and A. Johnson (2008). A unified framework for addiction: vulnerabilities in the decision process. Behavioral Brain Science 4: 415-437.
Robins, L.N., J.E. Helzer, and D.H. Davis (1975). Narcotic use in Southeast Asia and afterward: An interview study of 898 Vietnam returnees. Archives of General of Psychiatry 32(8): 955-961.
Robinson, D. (1979). Talking Out of Alcoholism: The Self-Help Process of Alcoholics Anonymous. Croom Helm: London.
Rudgley, R. (1999) The Lost Civilizations of the Stone. Age New York, NY: Free Press.
Rush, B. (1784). An Enquiry into the Effects of Spriuitous Liquors upon the Human Body, and Their Influence upon the Happiness of Society. Philadelphia, Pa: Thomas Bradford.
Sarbin, T. (1968). Ontology recapitulates philology: The mythic nature of anxiety. American Psychologist 23: 411-418.
Stephens, D.W., J.S. Brown and R.C. Ydenburg. (2007) Foraging: Behavior and Ecology. Chicago: The University of Chicago Press.
Tucker, J., R. Vuchinich, and P. Rippens (2002). Predicting natural resolutions of alcohol-related problems: A prospective behavioral economic analysis. Experimental and Clinical Psychopharmacology 10: 248-257.
Tuchfeld, B. (1981). Spontaneous remission in alcoholics. Journal of Studies on Alcohol. (42): 626-41.
Vaillant, George E. (1983). The Natural History of Alcoholism. Cambridge, MA: Harvard University Press.
Vuchinich, R., and C. Simpson (1998). Hyperbolic temporal discounting in social drinkers and problem drinkers. Experimental and Clinical Psychopharmacology 6: 292-305.
Warner, J. (1994). Resolv'd to drink no more: Addiction as a preindustrial construct. Journal of Studies of Alcohol 55: 685-691.
White, W. (1998). Slaying the Dragon: The History of Addiction Treatment and Recovery in America. Bloomington, IL: Chestnut Health Systems.
Winick, C. (1962). Maturing out of narcotic addiction. Bulletin on Narcotics 14: 1-7.
Wise RA. (1996). Addictive drugs and brain stimulation reward. Annual Review of Neuroscience 19: 319-4
Akers, R. (1991). Addiction: The troublesome concept. Journal of Drug Issues 21: 777-793.
Alcoholics Anonymous (1986). The Story of How Many Thousands of Men and Women Have Recovered from Alcoholism. New York: Alcoholics Anonymous World Services, Inc.
American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th edn. Text Revision. Washington, D.C.: American Psychiatric Association.
Anderson, V., R. Jacobs and P. Anderson (2008). Executive Functions and the Frontal Lobes: A Lifespan Perspective. New York: Psychology Press.
Barkow, J.H., L. Cosmides and J. Tooby (1995). The Adapted Mind: Evolutionary Psychology and the Generation of Culture. New York: Oxford University Press.
Barton, D. (1999). Benjamin Rush. Aledo, TX: Wallbuilder Press.
Berridge, K.C. (1996). Food reward: Brain substrates of wanting and liking. Neuroscience and Behavior Reviews 20: 1-25.
Berridge, K. and T. Robinson. (1998). what is the role of dopamine in reward: Hedonic impact, reward learning or interactive salience? Brain Research Reviews 28: 309-369.
Bickel, W., and L. Marsch. (2001). toward a behavioral economic understanding of drug dependence: Delay discounting processes. Addiction 96: 73-86.
Bickel, W., and M. Johnson. (2003). Delay discounting: A fundamental behavioral process of drug dependence. In Time and Decision: Economic and Psychological Perspectives on Intertemporal Choice, Ed G. Lowenstein, D. Read, and R. Baumeister. New York: Russel Sage Foundation.
Boyd, R. and P.J. Richerson (2005). The Origin and Evolution of Cultures. New York: Oxford University Press.
Brown, D. (2003). The Da Vinci Code: A Novel. New York: Doubleday, pp. 267-68.
Chambers, R.A., J. Taylor, and M. Potenza (2003). Developmental neurocircuitry of motivation in adolescence: A critical period of addiction vulnerability. American Journal of Psychiatry 160: 1041-1052.
Chung, S., and R. Herrenstein. (1967). Choice and delay of reinforcement. Journal of the Experimental Analysis of Behavior 10: 67-74.
Cunningham, J., L. Sobell and G. Kapur (1995). Resolution from alcohol problems with and without treatment: reasons for change. Journal of Substance Abuse 7(3): 365-372.
Ferri, M., L. Amato and M. Davoli (2006). Alcoholic’s anonymous and other 12-step programmes for alcohol dependence. Addiction 8: 1402-1403.
Fillmore, K.M. (1988). Spontaneous Remission of Alcohol Problems: Evaluating Recovery Outcomes. San Diego: University of California.
Fingarette, H. (1988). Heavy Drinking. Berkley, CA: University of California Press.
Giordano, L., W. Bickel, G. Lowenstein, E. Jacobs, L. Marsch, and G. Badger (2002). Mild opiod deprivation increases the degree that opiod-dependent outpatients discount delayed heroin and money. Psychopharmacology 163: 174-182..
Glimcher, P. (2003). Decisions, Uncertainty, and the Brain. Cambridge, MA: MIT Press.
Gogtay, N., J. N. Giedd, L. Lusk, et al. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences 101(21): 8174-8179.
Goldstein, R., and N. Volkow (2002). Drug addiction and its underlying neurobiological basis: Neuroimaging evidence for the involvement of the prefrontal cortex. American Journal of Psychiatry 159: 1642-1652..
Granfield, R. and W. Cloud (1999). Coming Clean: Overcoming Addiction without Treatment. New York: New York University Press.
Grant, B.; D. A. Dawson, F.S., Stinson, et al. (2004). The 12-month prevalence and trends in DSM-IV alcohol abuse and dependence; United States, 1991-1992 and 2001-2002. Drug and Alcohol Dependence 74: 223-234.
Green, L., A. Fry, and J. Myerson (1994). Discounting of delayed rewards: A life-span comparison. Psychological Science 5: 33-36.
Gusfield, J.R. (1963). Symbolic Crusade: Status Politics and the American Temperance Movement. University of Illinois Press: Urbana.
Henningfeld, J.E. and R.M. Keenan (1993) Nicotine delivery kinetics and abuse liability. Journal of Consulting Clinical Psychology 61: 743-750.
Hester, R.K., and W.R. Miller. (2003) Handbook of Alcoholism Treatment Approaches: Effective Alternatives. Boston: Allyn & Bacon, Inc.
Jellinek, E.M. (1946). Phases in the drinking history of alcoholics. Quarterly Journal of Studies on Alcohol 7: 1-88.
Jellinek, E.M. (1960). The Disease Concept of Alcoholism. New Haven, CT: Hillhouse Press.
Johansen E.B., and T. Sagvolden. (2005). Behavioral effects of intra-cranial self-stimulation in an animal model of attention-deficit/hyperactivity disorder (ADHD). Behavioral Brain Research 162(1):32-46.
Kirby, K., N. Petry, and W. Bickel (1999). Heroin addicts discount delayed rewards at higher rates than non-drug using controls. Journal of Experimental Psychology: General Processes 128: 78-87.
Kirby, K., and N. Petry (2004). Heroin and cocaine abusers have higher discount rates for delayed rewards than alcoholics and non-drug-using controls. Addiction 99: 461-471.
Koob, G., Paolo Sanno, and F. Bloom (1998). Neuroscience of addiction. Neuron 21: 467-676.
Levine, H. (1978). The discovery of addiction: Changing conceptions of habitual drunkenness in America. Journal of Studies of Alcohol 39: 143-174.
Logue, A.W. (1988). Research on self-control: An integrated framework. Behavioral and Brain Sciences 11: 665-679.
Lowenstein, G., and D. Prelec (1992). Anomalies in intertemporal choice: Evidence and interpretation. Quarterly Journal of Economics 107: 573-597.
Madden G., N. Petry, G. Badger, and W. Bickel (1997). Impulsive and self-control choices in opiod-dependent subjects and non-drug using controls. Drugs and monetary rewards. Experimental and Clinical Psychopharmacology 5: 256-262.
Madden G., W. Bickel, and E. Jacobs (1999). Discounting of delayed rewards in opiod-dependent outpatients: Exponential or hyperbolic discounting functions. Experimental and Clinical Psychopharmacology 7: 284-293.
Mazur, J.E (1987). An adjusting procedure for studying delayed reinforcement. In M.L. Commons, J.E. Mazur, J.A. Nevins and H. Rachlin, Eds. Quantitative Analysis of Behavior Vol. 5: The effects of delay and intervening event on reinforcement value. Mawah, NJ: Erlbaum, pp 55-73.
Miller, W.R., P.L. Wilbourne, and J.E. Hettma (2003). What works? A summary of alcohol treatment outcomes research. In R.K. Hester and W.R. Miller, eds. Handbook of Alcohol Treatment Approaches: Effective Alternatives. Boston: Allyn & Bacon.
Mischel, W., Y. Shoda, and M. Rodriguez (1989) Delay of gratification in children. Science 244: 933-938.
Montague, Read. (2006). Why choose this book? : How we make decisions.
New York: Penguin Group.
Moore, C. and S. Macgillivray. (2004). Altruism, prudence, and theory of mind in preschoolers. New Directions for Child and Adolescent Development 103: 51-62.
Mosby's Medical Dictionary (2009), 8th edn. Amsterdam: Elsevier.
Narcotics Anonymous (1986). Van Nuys, CA: Narcotics Anonymous World Services, Inc.
Olds, J. and P. Milner (1954). Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. Journal of Comparative and Physiological Psychology 47: 419-427.
Peele, S. (1991). The Truth about Addiction and Recovery: The Life Process Program for Outgrowing Destructive Habits. New York: Simon & Schuster.
Petry, N. (2001). Delay discounting of money in alcohol in actively using alcoholics, currently abstinent alcoholics, and controls. Psychopharmacology 154: 243-250.
Polich, J.M., D.J. Armor, and H.B. Braiker (1980). Patterns of alcoholism over four years. Journal Studies of Alcohol. 41(5): 397-416.
Powell, D.H., and D.K. Whitla. (1994). Profiles in Cognitive Aging. Cambridge, MA: Harvard University Press.
Rachlin, H. (2000). The Science of Self-Control. Cambridge, MA: Harvard University Press.
Redish, A.D., S. Jensen and A. Johnson (2008). A unified framework for addiction: vulnerabilities in the decision process. Behavioral Brain Science 4: 415-437.
Robins, L.N., J.E. Helzer, and D.H. Davis (1975). Narcotic use in Southeast Asia and afterward: An interview study of 898 Vietnam returnees. Archives of General of Psychiatry 32(8): 955-961.
Robinson, D. (1979). Talking Out of Alcoholism: The Self-Help Process of Alcoholics Anonymous. Croom Helm: London.
Rudgley, R. (1999) The Lost Civilizations of the Stone. Age New York, NY: Free Press.
Rush, B. (1784). An Enquiry into the Effects of Spriuitous Liquors upon the Human Body, and Their Influence upon the Happiness of Society. Philadelphia, Pa: Thomas Bradford.
Sarbin, T. (1968). Ontology recapitulates philology: The mythic nature of anxiety. American Psychologist 23: 411-418.
Stephens, D.W., J.S. Brown and R.C. Ydenburg. (2007) Foraging: Behavior and Ecology. Chicago: The University of Chicago Press.
Tucker, J., R. Vuchinich, and P. Rippens (2002). Predicting natural resolutions of alcohol-related problems: A prospective behavioral economic analysis. Experimental and Clinical Psychopharmacology 10: 248-257.
Tuchfeld, B. (1981). Spontaneous remission in alcoholics. Journal of Studies on Alcohol. (42): 626-41.
Vaillant, George E. (1983). The Natural History of Alcoholism. Cambridge, MA: Harvard University Press.
Vuchinich, R., and C. Simpson (1998). Hyperbolic temporal discounting in social drinkers and problem drinkers. Experimental and Clinical Psychopharmacology 6: 292-305.
Warner, J. (1994). Resolv'd to drink no more: Addiction as a preindustrial construct. Journal of Studies of Alcohol 55: 685-691.
White, W. (1998). Slaying the Dragon: The History of Addiction Treatment and Recovery in America. Bloomington, IL: Chestnut Health Systems.
Winick, C. (1962). Maturing out of narcotic addiction. Bulletin on Narcotics 14: 1-7.
Wise RA. (1996). Addictive drugs and brain stimulation reward. Annual Review of Neuroscience 19: 319-4