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Understanding Investigational Drugs

Have you ever thought about joining a clinical trial that is trying to find out if an investigational drug works in treating your disease or medical condition?  Or maybe your healthcare provider has talked to you about treating you with an investigational drug through expanded access. 

An investigational drug can also be called an experimental drug and is being studied to see if your disease or medical condition improves while taking it. Scientists are trying to prove in clinical trials:

If the drug is safe and effective.

How the drug might be used in that disease.

How much of the drug is needed.

Information about the potential benefits and risks of taking the drug.

When to consider using an investigational drug

Not every person’s disease or medical condition responds the same way to approved drugs. Your healthcare provider might have talked to you about using an investigational drug if you have:

Experienced side effects that are too severe to continue taking

Limited treatment options available.

Heard about promising early study results for a specific investigational drug.

No approved drugs available to treat your disease or medical condition.

Questions you may want to consider

If your healthcare provider thinks that using an investigational drug is an option for you, then consider asking questions like those listed below before deciding whether it is right for you.

What is this drug being studied for?

Is there a clinical trial site near you?

How much is already known about the investigational drug?

What basis is there for thinking that the drug will work better for your medical condition than using an approved treatment?

What scientific evidence is available to support the use of this investigational drug?

What are the potential risks of using this investigational drug?

Are there other drugs that are already approved to treat your disease or condition?

Have you already tried them?

Why or why not?

Many of these questions may be answered for you when you read the informed consent document. Before you can be given an investigational drug either through a clinical trial or through expanded access, your healthcare provider must give you additional information about the potential risks and potential benefits of the drug.

As promising as an investigational drug may sound. It is still being tested in clinical trials to determine if it can be used to treat a disease or medical condition. And not everyone who wants to enroll in a clinical trial will be able to participate.  Clinical trials have strict inclusion and exclusion criteria about who can participate. The criteria can be based on such factors as:

Having a certain type or stage of disease.

Having received (or not received) a certain kind of therapy in the past.

Being in a certain age group.

Your medical history.

Your current health status.

Criteria like those listed above can help researchers understand the medical differences among people in the trial and help them answer the questions they are studying about the drug. 

Finally, remember that approved drugs have completed extensive testing in clinical trials and there is scientific proof that they are safe and effective for treating the particular disease or medical condition that has been studied.  It is important to talk with your healthcare provider on a regular basis about the medicines you are taking and talking about the side effects you may be experiencing.  

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Design of experiments (DoE) in pharmaceutical development

Affiliations.

• 1 a Department of Pharmaceutical Technology, Faculty of Pharmacy , National and Kapodistrian University of Athens , Athens , Greece.
• 2 b Department of Pharmacy , University of Parma , Parma , Italy.
• 3 c PlumeStars s.r.l. , Parma , Italy.
• 4 d Department of Life Sciences and Biotechnology , University of Ferrara , Ferrara , Italy.
• PMID: 28166428
• DOI: 10.1080/03639045.2017.1291672

At the beginning of the twentieth century, Sir Ronald Fisher introduced the concept of applying statistical analysis during the planning stages of research rather than at the end of experimentation. When statistical thinking is applied from the design phase, it enables to build quality into the product, by adopting Deming's profound knowledge approach, comprising system thinking, variation understanding, theory of knowledge, and psychology. The pharmaceutical industry was late in adopting these paradigms, compared to other sectors. It heavily focused on blockbuster drugs, while formulation development was mainly performed by One Factor At a Time (OFAT) studies, rather than implementing Quality by Design (QbD) and modern engineering-based manufacturing methodologies. Among various mathematical modeling approaches, Design of Experiments (DoE) is extensively used for the implementation of QbD in both research and industrial settings. In QbD, product and process understanding is the key enabler of assuring quality in the final product. Knowledge is achieved by establishing models correlating the inputs with the outputs of the process. The mathematical relationships of the Critical Process Parameters (CPPs) and Material Attributes (CMAs) with the Critical Quality Attributes (CQAs) define the design space. Consequently, process understanding is well assured and rationally leads to a final product meeting the Quality Target Product Profile (QTPP). This review illustrates the principles of quality theory through the work of major contributors, the evolution of the QbD approach and the statistical toolset for its implementation. As such, DoE is presented in detail since it represents the first choice for rational pharmaceutical development.

Keywords: Experimental design; design space; factorial designs; mixture designs; pharmaceutical development; process knowledge; statistical thinking.

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Chapter 4. Experimental Study Designs

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• Experimental Study Designs: Introduction
• Experimental Design
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Experimental study designs are the primary method for testing the effectiveness of new therapies and other interventions, including innovative drugs. By the 1930s, the pharmaceutical industry had adopted experimental methods and other research designs to develop and screen new compounds, improve production outputs, and test drugs for therapeutic benefits. The full potential of experimental methods in drug research was realized in the 1940s and 1950s with the growth in scientific knowledge and industrial technology. 1

In the 1960s, the controlled clinical trial, in which a group of patients receiving an experimental drug is compared with another group receiving a control drug or no treatment, became the standard for doing pharmaceutical research and measuring the therapeutic benefits of new drugs. 1 By the same time, the double-blind strategy of drug testing, in which both the patients and the researcher are unaware of which treatment is being taken by whom, had been adopted to limit the effect of external influences on the true pharmacological action of the drug. The drug regulations of the 1960s also reinforced the importance of controlled clinical trials by requiring that proof of effectiveness for new drugs be made through use of these research methods. 2,3

In pharmacoepidemiology, the primary use of experimental design is in performing clinical trials, most notably randomized, controlled clinical trials. 4 These studies involve people as the units of analysis. A variation on this experimental design is the community intervention study, in which groups of people, such as whole communities, are the unit of analysis. Key aspects of the clinical and community intervention trial designs are randomization, blinding, intention-to-treat analysis, and sample size determination.

An experiment is a study designed to compare benefits of an intervention with standard treatments, or no treatment, such as a new drug therapy or prevention program, or to show cause and effect (see Figure 3-2 ). This type of study is performed prospectively. Subjects are selected from a study population, assigned to the various study groups, and monitored over time to determine the outcomes that occur and are produced by the new drug therapy, treatment, or intervention.

Experimental designs have numerous advantages compared with other epidemiological methods. Randomization, when used, tends to balance confounding variables across the various study groups, especially variables that might be associated with changes in the disease state or the outcome of the intervention under study. Detailed information and data are collected at the beginning of an experimental study to develop a baseline; this same type of information also is collected at specified follow-up periods throughout the study. The investigators have control over variables such as the dose or degree of intervention. The blinding process reduces distortion in assessment. And, of great value, and not possible with other methods, is the testing of hypotheses. Most important, this design is the only real test of cause–effect relationships.

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Experiment Definition in Science – What Is a Science Experiment?

In science, an experiment is simply a test of a hypothesis in the scientific method . It is a controlled examination of cause and effect. Here is a look at what a science experiment is (and is not), the key factors in an experiment, examples, and types of experiments.

Experiment Definition in Science

By definition, an experiment is a procedure that tests a hypothesis. A hypothesis, in turn, is a prediction of cause and effect or the predicted outcome of changing one factor of a situation. Both the hypothesis and experiment are components of the scientific method. The steps of the scientific method are:

• Make observations.
• Ask a question or identify a problem.
• State a hypothesis.
• Perform an experiment that tests the hypothesis.
• Based on the results of the experiment, either accept or reject the hypothesis.
• Draw conclusions and report the outcome of the experiment.

Key Parts of an Experiment

The two key parts of an experiment are the independent and dependent variables. The independent variable is the one factor that you control or change in an experiment. The dependent variable is the factor that you measure that responds to the independent variable. An experiment often includes other types of variables , but at its heart, it’s all about the relationship between the independent and dependent variable.

Examples of Experiments

Fertilizer and plant size.

For example, you think a certain fertilizer helps plants grow better. You’ve watched your plants grow and they seem to do better when they have the fertilizer compared to when they don’t. But, observations are only the beginning of science. So, you state a hypothesis: Adding fertilizer increases plant size. Note, you could have stated the hypothesis in different ways. Maybe you think the fertilizer increases plant mass or fruit production, for example. However you state the hypothesis, it includes both the independent and dependent variables. In this case, the independent variable is the presence or absence of fertilizer. The dependent variable is the response to the independent variable, which is the size of the plants.

Now that you have a hypothesis, the next step is designing an experiment that tests it. Experimental design is very important because the way you conduct an experiment influences its outcome. For example, if you use too small of an amount of fertilizer you may see no effect from the treatment. Or, if you dump an entire container of fertilizer on a plant you could kill it! So, recording the steps of the experiment help you judge the outcome of the experiment and aid others who come after you and examine your work. Other factors that might influence your results might include the species of plant and duration of the treatment. Record any conditions that might affect the outcome. Ideally, you want the only difference between your two groups of plants to be whether or not they receive fertilizer. Then, measure the height of the plants and see if there is a difference between the two groups.

Salt and Cookies

You don’t need a lab for an experiment. For example, consider a baking experiment. Let’s say you like the flavor of salt in your cookies, but you’re pretty sure the batch you made using extra salt fell a bit flat. If you double the amount of salt in a recipe, will it affect their size? Here, the independent variable is the amount of salt in the recipe and the dependent variable is cookie size.

Test this hypothesis with an experiment. Bake cookies using the normal recipe (your control group ) and bake some using twice the salt (the experimental group). Make sure it’s the exact same recipe. Bake the cookies at the same temperature and for the same time. Only change the amount of salt in the recipe. Then measure the height or diameter of the cookies and decide whether to accept or reject the hypothesis.

Examples of Things That Are Not Experiments

Based on the examples of experiments, you should see what is not an experiment:

• Making observations does not constitute an experiment. Initial observations often lead to an experiment, but are not a substitute for one.
• Making a model is not an experiment.
• Neither is making a poster.
• Just trying something to see what happens is not an experiment. You need a hypothesis or prediction about the outcome.
• Changing a lot of things at once isn’t an experiment. You only have one independent and one dependent variable. However, in an experiment, you might suspect the independent variable has an effect on a separate. So, you design a new experiment to test this.

Types of Experiments

There are three main types of experiments: controlled experiments, natural experiments, and field experiments,

• Controlled experiment : A controlled experiment compares two groups of samples that differ only in independent variable. For example, a drug trial compares the effect of a group taking a placebo (control group) against those getting the drug (the treatment group). Experiments in a lab or home generally are controlled experiments
• Natural experiment : Another name for a natural experiment is a quasi-experiment. In this type of experiment, the researcher does not directly control the independent variable, plus there may be other variables at play. Here, the goal is establishing a correlation between the independent and dependent variable. For example, in the formation of new elements a scientist hypothesizes that a certain collision between particles creates a new atom. But, other outcomes may be possible. Or, perhaps only decay products are observed that indicate the element, and not the new atom itself. Many fields of science rely on natural experiments, since controlled experiments aren’t always possible.
• Field experiment : While a controlled experiments takes place in a lab or other controlled setting, a field experiment occurs in a natural setting. Some phenomena cannot be readily studied in a lab or else the setting exerts an influence that affects the results. So, a field experiment may have higher validity. However, since the setting is not controlled, it is also subject to external factors and potential contamination. For example, if you study whether a certain plumage color affects bird mate selection, a field experiment in a natural environment eliminates the stressors of an artificial environment. Yet, other factors that could be controlled in a lab may influence results. For example, nutrition and health are controlled in a lab, but not in the field.
• Bailey, R.A. (2008). Design of Comparative Experiments . Cambridge: Cambridge University Press. ISBN 9780521683579.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 0-521-29925-X.
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments. Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
• Holland, Paul W. (December 1986). “Statistics and Causal Inference”.  Journal of the American Statistical Association . 81 (396): 945–960. doi: 10.2307/2289064
• Stohr-Hunt, Patricia (1996). “An Analysis of Frequency of Hands-on Experience and Science Achievement”. Journal of Research in Science Teaching . 33 (1): 101–109. doi: 10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Z

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Clinical trials and medical experiments

Published: 30 July 2019

Experimentation is an essential part of scientific medicine. 

Doctors have always conducted investigations and experiments in order to understand the body in sickness and health, and to test the effectiveness of treatments. Medical laboratories carry out experimental research into new techniques and treatments, but at some point developments intended for use on patients have to be tested on people. 

Experimenting with the living—animals and humans—is complex and sometimes dangerous. In their efforts to discover more about diseases and find effective treatments, doctors and researchers have put vulnerable and powerless patients at risk. 

The modern clinical trial—an experiment in which people are the test subjects—has developed over time not only to ensure the optimal conditions to produce valid, scientific results but also to safeguard the rights and well-being of participants.

Clinical trials

In the 1030s, the physician Ibn Sina put forward rules for testing the effect of drugs on patients. One key criterion was that:

The effect of the drug should be the same in all cases or, at least, in most. If that is not the case, the effect is then accidental, because things that occur naturally are always or mostly consistent. Ibn Sina

This remains the essential criterion for any treatment—that it has the same effect on most patients in similar conditions. But testing a drug on one person does not tell you very much. Their response may not be typical, side effects may be the result of an allergy, or their recovery may be due to some external factor. 

Today new medical devices and drugs have to undergo several stages of testing before they reach the final stage of being tested on people. Drug testing and regulation was tightened in the mid-1960s following the impact of thalidomide worldwide. Usually a therapy is tested on animals before clinical trials are permitted.

Participants in clinical trials are carefully selected in order to limit the number of variable factors that might affect the results. For example, only patients at the same stage of a particular condition may be selected in order to see if a new therapy is effective in treating the condition at that stage.

In order to run a clinical trial on people, researchers have to go through a rigorous procedure that includes registering the trial with the authorities and presenting their proposal to an ethics committee, who will decide it the trial is valid and that there are safeguards in place to ensure that participants understand what will happen to them.

Randomised clinical trials

In randomised trials, the test subjects are divided into at least two different treatment groups. Participants are assigned to a group at random. 

One group is usually given the standard treatment for their condition. They are the control group.  People in the other group (or groups) will have the treatment or procedure that is being tested. A randomised trial that has a control group is called a randomised controlled trial (RCT).

If there is no standard treatment, then people in the control group may be given a dummy treatment, called a placebo. A placebo is a treatment with no medical effects. It allows researchers to take into account the psychological influence of experiencing treatment, regardless of what is in the treatment. 

A blind trial is a trial where the people taking part don't know which treatment they are getting. A double blind trial is a trial where neither the researchers nor the patients know what they are getting. The identity of patients in each group is kept secret until the end of the trial. 

What is informed consent?

Legally and ethically, participants in a clinical trial need to have adequate information to allow for an informed decision about participation in a trial. This includes what tests are involved what the risks and benefits may be, how much of your time it will take and what will happen to any of your samples after the trial. 

The modern definition of informed consent came out of the Nuremberg trials, a series of legal trials between 1945 and 1947 to prosecute surviving German war criminals after the Second World War. 

People were shocked by the horrific things done by doctors in the name of medical research and the Nuremberg Code was developed as a result. It is the basis for all rules regarding human experiments, including the requirement for informed consent.

Most countries now have regulatory boards for clinical trials that insist on informed consent before people can participate in clinical trials. 

Before the Nuremburg Code, people in charge of human experiments did not have to tell their patients what they were doing. Some groups of people had no choice in whether or not they participated. 

British troops heading to the South African War (1899–1902) were offered a new typhoid vaccine before it was fully tested and the side-effects understood and eliminated. These side effects were one reason why take-up of the vaccine was so low.  Alongside volunteers, some prisoners were used to test a new cholera vaccine in India in 1897. 

Throughout the 1900s, psychiatrists who wanted to find effective treatments for conditions such as schizophrenia tested experimental convulsive shock therapies on their patients. Researchers had little knowledge of the effects—and patients were not always asked for their consent.

Self-experimentation

Occasionally medical researchers decide to test a new idea or treatment on the most convenient test subject around—themselves. They might do this because the weight of medical opinion is resistant to their idea and they can’t get funding or support to test it any other way. 

Or they might simply have wanted to prove their theory before sharing it with others. Whatever their reasons, self-experimentation has contributed some valuable treatments and techniques to medicine—but it has also gone very wrong.

Do-it-yourself anaesthesia

One field of medicine seems to be full of self-experimenters. The American dentist William Morton was one of several people to try ether as an anaesthetic on himself after witnessing its numbing effects on revellers at the ‘ether frolics’ that were the craze in the 1800s.

The Scottish surgeon James Young Simpson and his friends  were searching for an  alternative general anaesthetic to ether and tested several compounds on themselves, including chloroform. Another celebrated surgeon, Joseph Lister , took a more scientific approach when he and his wife Agnes tested different doses of chloroform on themselves to find the most effective one for his patients.

But perhaps the most surprising case of self-experimentation in anaesthesia was that of the German surgeon August Bier, who decided to find out for himself the effects of cocaine as a local anaesthetic by having his assistant Augustus Hildebrandt inject it into the fluid surrounding the spinal cord. 

But, thanks to a mix-up with the equipment, Bier was left with a hole in his neck that began to leak cerebrospinal fluid. Rather than abandon the effort, however, the two men switched places. Once Hildebrandt had been anaesthetized, Bier stabbed, hammered and burned his assistant, pulled out his pubic hairs and squashed his testicles!

Needless to say both felt the after-effects in subsequent days. But cocaine did prove to be a very effective local anaesthetic and was a forerunner to the modern epidural.

How to cause an ulcer

Australian doctor Barry Marshall had a theory that challenged the medical consensus of the day. He and his colleague, pathologist Robin Warren, were convinced that ulcers were caused by the bacterium Helicobacter pylori, and not—as was the general medical opinion—that they were the result of lifestyle factors such as stress, spicy foods and alcohol.

They had tried to submit their findings to a peer-reviewed journal in 1983, but their paper was turned down. In 1984, Marshall drank a broth containing cultured H. pylori, because he wanted to see the effects on a healthy person. As he explained: "I was the only person informed enough to consent".

He expected to develop an ulcer after perhaps a year, so he was surprised when, only three days later, he developed nausea and halitosis  (bad breath). On day five, he began vomiting. On day eight, an endoscopy showed massive inflammation (gastritis, a precursor to an ulcer) in his stomach, and a biopsy showed that the H. pylori had colonised his stomach. 

On the fourteenth day Marshall began to take antibiotics to fight the H. pylori infection. 

The traditional treatment for severe ulcers was antacids and medications that block acid production in the stomach. Despite this treatment, there was a high recurrence of ulcers. Marshall and Warren’s discovery meant that ulcers could now be cured using antibiotics, preventing years of pain and discomfort and saving money on pharmaceuticals that didn’t work.

Marshall and Warren won the Nobel Prize for Physiology or Medicine in 2005 for their work. 

Animal experiments

Animals have long been used for dissections and medical experiments. For centuries, human dissection was severely restricted and physicians and surgeons relied on animal dissection to learn about human anatomy. 

The Roman physician Galen dissected pigs and monkeys to develop his knowledge anatomy. Although he was restricted by law to dissecting animals, the three years he spent from 158 CE as physician to the gladiators of his home city of Pergamon were a formative period in his life in medicine. The traumatic injuries he regularly encountered gave Galen the perfect opportunity to extend his practical medical knowledge of the human body.

Discussions about whether to experiment on animals has always been part of the debate. Some religious authorities said that animals had no souls and they were under the dominion of mankind, along with the rest of the natural world. The 1600s philosopher and researcher René Descartes (1596-1650) claimed that animals did not feel pain.

The number of experiments on animals increased in the 1800s with the rise of life sciences such as experimental physiology. The French physiologist Claude Bernard used animals in his research and drew criticism for it from opponents, including his own wife and daughters.

Louis Pasteur used rabbits to develop a vaccine for rabies and was the target of protests.

As scientific experimentation on living animals, known as vivisection, grew, so did the anti-vivisection movement. In 1875 the activist Frances Power Cobbe founded the Society for the Protection of Animals. The protests of the early animal rights movement led to the Cruelty to Animals Act of 1876, which regulated animal experimentation in England, Wales and Ireland.

Modern medical research still relies on animals. As well as medical research, testing on animals, primarily rats and mice, is used to assess the safety or effectiveness of products such as drugs, chemicals and cosmetics. Medical researchers are increasingly aware of animal welfare and continue to seek scientific alternatives to animal testing. 

Where the ability to replace animal experiments with alternatives such as tissue cultures, microorganisms or computer models is limited, researchers have tried to reduce the amount of animal testing needed. This is because, apart from the ethical concerns, animal experiments are expensive and (as with all experiments on living organisms) highly complicated.

Both scientific research organisations and animal rights groups promote the use and development of methods of scientific testing that don’t use animals, such as:

in Vitro techniques

An example of a toxicity test in animals that is being replaced is the LD50 test, in which the concentration of a chemical is increased in a population of test animals until 50 percent of the animals die. 

A similar in vitro test is the IC50 test, which tests the cytotoxicity (cell toxicity) of a chemical’s ability to inhibit the growth of half of a population of cells. The IC50 test uses human cells grown in the laboratory and thus produces data that are more relevant to humans than an LD50 value obtained from rats, mice, or other animals.

in silico techniques (computer modeling)

Researchers have developed a wide range of sophisticated computer models that simulate human biology and the progression of disease. Studies show that these models can be used to predict the ways that new drugs will react in the human body without the need for a lot of animal testing.  

Suggestions for further research

• A Harrington (ed.), The Placebo Effect: An Interdisciplinary Exploration , 1997
• J S Hawkins and E J.Emanuel (eds.), Exploitation and Developing Countries: The Ethics of Clinical Research , 2008
• Ruth Chadwick and Duncon Wilson, ' The Emergence and Development of Bioethics in the UK ', in Medical Law Review, Vol. 26 No. 2  

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Drugs, Brains, and Behavior: The Science of Addiction Preface

How science has revolutionized the understanding of drug addiction.

For much of the past century, scientists studying drugs and drug use labored in the shadows of powerful myths and misconceptions about the nature of addiction. When scientists began to study addictive behavior in the 1930s, people with an addiction were thought to be morally flawed and lacking in willpower. Those views shaped society’s responses to drug use, treating it as a moral failing rather than a health problem, which led to an emphasis on punishment rather than prevention and treatment.

Today, thanks to science, our views and our responses to addiction and the broader spectrum of substance use disorders have changed dramatically. Groundbreaking discoveries about the brain have revolutionized our understanding of compulsive drug use, enabling us to respond effectively to the problem.

As a result of scientific research, we know that addiction is a medical disorder that affects the brain and changes behavior. We have identified many of the biological and environmental risk factors and are beginning to search for the genetic variations that contribute to the development and progression of the disorder. Scientists use this knowledge to develop effective prevention and treatment approaches that reduce the toll drug use takes on individuals, families, and communities.

Despite these advances, we still do not fully understand why some people develop an addiction to drugs or how drugs change the brain to foster compulsive drug use. This booklet aims to fill that knowledge gap by providing scientific information about the disorder of drug addiction, including the many harmful consequences of drug use and the basic approaches that have been developed to prevent and treat substance use disorders.

At the National Institute on Drug Abuse (NIDA), we believe that increased understanding of the basics of addiction will empower people to make informed choices in their own lives, adopt science-based policies and programs that reduce drug use and addiction in their communities, and support scientific research that improves the Nation’s well-being.

Nora D. Volkow, M.D. Director National Institute on Drug Abuse

Addiction, Connection and the Rat Park Study

If only connection was enough..

Posted August 14, 2015 | Reviewed by Ekua Hagan

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Recently, I was bombarded with Facebook messages and posts about an addiction story everyone got really excited about.

This story followed Johann Hari’s book, Chasing the Scream , and his follow-up TED talk . In the talk, Johann mentioned the Rat Park experiment conducted by Bruce Alexander.

In this experiment, rats, who are participating in drug studies, are given a large cage with free food, access to sex , toys, and many playmates (the childhood kind, not Hugh Hefner’s). As Hari said in his talk, it was more a Rat Heaven then Rat Park... but still.

Under such conditions, Dr. Alexander found that rats actually refused drug cocktails, unlike their solo-caged study-mates.

The conclusion — it’s not the drugs that are an addiction but rather the environmental stressors that are placed on the rats we are studying. Eliminate the stress and you get rid of the addiction!

How amazing is that? If only things were really that simple…

Dealing with the real world

Let's ignore for a moment the methodological issues with Dr. Alexander's study (more on that here ). Assuming that what we are aiming for is not a world free of addicted rats, but rather a world free of addicted people, I have been wondering for quite a few years how we could translate these findings into real life.

The decriminalization efforts in Portugal , which Hari mentioned as well, are also something I’ve written about years ago and I agree that arresting drug users for their crimes leads to more , not less, addiction in the world.

The issue I am struggling with it this — marriages are imperfect, children are abused (physically and psychologically), wars affect citizens and soldiers and bad luck brings about traumatic loss. Our environment, unlike the environment created for the rats in Rat Heaven, is far from stress-free.

Worse still, as far as I can tell, we will, for the foreseeable future, be unable to create such a utopia for most people on Earth. If this is so, there is little doubt that some of the people affected by negative circumstances, traumatic experiences, or biological disturbances will be led down the path towards struggles with drugs and such.

To make matters more complicated, we know that biological influences related to genetic differences, neonatal (birth-related) circumstances, and early nutrition can alter brain mechanisms and make people more, or less, susceptible to the effects of trauma.

For instance, we now know that early life trauma alters the function of the hypothalamic-pituitary-adrenal axis, making individuals who have been exposed to trauma at an early age far more susceptible to stress, anxiety and substance use; or that hypoxia during delivery (certainly a form of trauma) can increase the chances of mental health defects later in life.

Like the Rat Heaven experiment, it should be somewhat obvious that without these early traumas, the individuals in question would experience less “need” for heavy-duty coping strategies like, let’s say, opiates. So biology is important here at least in this regard.

So trauma and stress are is not at all objective truths but rather individually determined patterns of influence. I am fully on board with making sure that the treatment system we use does not exacerbate the problems that stress and trauma bring about (so no shaming , breaking-down, or expulsion of clients for their struggles), but I think that the picture this TED talk and the related book presents is far too simplified to be as helpful as we want it to be.

I believe that more focus should be given to improved prevention efforts in order to reduce the likelihood of these early traumas and therefore of later drug-seeking experience in the first place. I also know that significant efforts are already being put into this sort of work through a multitude of social-services organizations and government agencies.

Needless to say, the demand for drug use has not abated despite these efforts. The work must be more difficult than setting children up with a big box, water, and some chew toys.

How oversimplification hurts us

And this brings up a question for me — what if humans are not like rats? I know it’s a shocking suggestion but just stay with me for a second.

What if human life is somewhat more complicated than rat life, science lab or not? What if Rat Heaven is not a recipe for success in eradicating human addiction because our own internal struggles , social networks and consciousness-seeking drive us farther in seeking mind-alteration than they do rats? Isn’t it possible that even if we were somehow able to make Earth a Utopia (and I would argue we are moving farther from such a reality and not closer) we would still be dealing with substance use? It’s been happening for at least 8000 years already and I’m thinking it’s here to stay.

So while I agree that social connection is very important for dealing with substance use problems (that is why we don’t shame our clients at I GNTD and don’t expel them for using when the program doesn’t call for it), it also matters who we’re connecting to and that, unfortunately, is something we control only to a limited extent.

We have to deal with the circumstances we are born into — dysfunctional marriages, depression , dietary limitations, and gang violence — and sometimes substances are the solution, not the problem.

So let’s keep moving towards a shame-free way of looking at addiction but let’s not pretend that wishing the struggles away will make it so.

An earnest hug is great, but it is not a panacea.

We have a lot of hard work to do.

© 2015 Adi Jaffe, All Rights Reserved

Read Dr. Jaffe's book, The Abstinence Myth , and be sure to check out his TEDx talk, Rebranding Our Shame , as well as his podcast .

Adi Jaffe , Ph.D. , is a lecturer at UCLA and the CEO of IGNTD, an online company that produces podcasts and educational programs on mental health and addiction.

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Phases of Drug Use: From Experimentation to a Substance Use Disorder

In 2016, roughly 7.4 million  people over the age of 11 were affected by substance misuse or addiction. Everyone with a substance use disorder has a unique story about how they began to get involved with drugs. While many people with addiction can relate to each other, it’s important to remember that everyone’s experience is personal. Still, most people’s addiction spurred from several phases ranging from their first introduction to their spiral into dependency. Examining the different periods of drug use that eventually lead to addiction can help people understand where recreational drug use ends and where a dangerous substance use disorder begins.

• Introduction

A lot of people experiment with drugs or alcohol before reaching adulthood. The natural curiosity and rebellion of teenagers and young people usually cause the initiation into trying substances for the first time. With the help of some added peer pressure and desire to fit in, young people are most often at the most significant risk of exposure in early life. Because adolescents still don’t have fully developed prefrontal lobes in their brains, their judgment and impulse control is often shaky, making them vulnerable for potential misuse or addiction. A survey conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA) showed that 2.8 million people above the age of 12 used an illicit drug for the first time in 2013. Every day, about 4,220 people under the age of 18 will use drugs and alcohol for the first time.

However, even people who abstained from an early introduction to substance use can still experience this stage later on in life. As adults, we deal with many stressful situations on the job, at home, and even personal struggles with mental health. This can prompt some people to self-medicate with drugs or alcohol, especially when they are emotionally compromised. Even those who are not dealing with personal issues may want to fit in with co-workers, friends, or even family members who may be misusing drugs recreationally. After this first introduction to a substance, people generally will decide to experiment further or decide against it.

• Experimentation

Upon the initial first try, drug use can quickly become experimental, occurring more frequently. Some people start this by only using drugs in a specific situation, like a party or during events like concerts. This exploratory phase is usually a more social matter that involves drugs as a way to relax or have some fun. At this point, people generally don’t seem to think about these substances too much other than right before the time they plan to use them. Cravings generally do not exist at this phase, but the anticipation of the social event of using the drug may become a factor. At this time people will decide to consciously consume drugs, understanding the potential consequences, or they will take the drugs impulsively, without much pre-planning. Still, their thoughts and concerns aren’t centered on their drug use, and will only take part when it is convenient.

• Recreational Use

Recreational drug use is more common than most people realize. Some use drugs to “party,” while others use them to unwind. When someone is regularly buying and ingesting drugs, it qualifies as recreational use that can be as frequent as every weekend or several times a week. At this stage, people are more aware of their intake and usually have a ritual surrounding their methods of obtaining and preparing the drugs. Sometimes they may miss work or school due to the after-effects of using the drugs. This drug use often goes hand-in-hand with people who are looking for drugs to escape their situations or cope with other issues. Others may use drugs regularly because they feel that it makes their social interactions much more exciting and enjoyable. At this point, they prefer to use drugs socially rather than stay sober.

When someone enters this phase, their drug use is considered to be risky and has become a problem. People that are misusing substances will sometimes have run-ins with dangerous situations like DWIs or other negative legal consequences. Their performance at work or school will be dwindling, and their relationships with loved ones are negatively impacted by their frequently unpredictable behavior. When someone is misusing drugs, they are beyond the point of regular recreational use and are walking the fine line between risky use and a substance use disorder. This is often the stage where people will first be approached by someone concerned about their frequent intoxication.

Drug dependency can be split into three parts: tolerance, physical dependence, and psychological dependence. When someone builds tolerance, they will require more and more of the drug they are misusing to achieve the desired effect. When a physical dependence occurs, it means that the person will go through withdrawal responses when they aren’t able to ingest their drug of choice. These withdrawals can range from light cravings to severe symptoms that can leave the user in significant pain. Psychological dependence happens when cravings are not only controlled by painful or bothersome withdrawals, but by the mental drive to use drugs. Some people who prefer to be ‘high’ constantly or under the influence are not able to face simple day-to-day tasks without their drug and require it to function. These three steps are cumulative and usually progress within several weeks or months of each other depending on the frequency of use.

• Substance Use Disorder (SUD)

When someone’s drug use has spiraled out of control, they will experience the following symptoms to fit the SUD criteria:

• They cannot control their use
• They continue to use despite drastically negative consequences
• They cannot function daily without their drug
• They have abandoned personal relationships and hobbies
• They have issues with the law
• Their health and life is in danger

Addiction is a disease that has developed from these long phases of drug use, carefully rewiring the brain’s reward pathway to constantly prioritize drug use over all else. Even when this person has attempted to cease their drug use, they have been unsuccessful and experienced dangerous relapses, returning to their previous behaviors. Usually, at this phase, people rarely can feel the high they once desired and continue to use the drug to keep withdrawal at bay.

The last stage of the substance use disorder progression is treatment , remembering however that treatment can begin at any phase of drug use. There are several treatment options for people who are faced with addiction that involve medication, behavioral therapy, and other counseling to help get them on the road to recovery.

Sources: https://www.stanfordchildrens.org/en/topic/default?id=stages-of-substance-abuse-1-3060

https://www.drugs.ie/drugs_info/about_drugs/the_nature_and_states_of_drug_use/

Related Posts About The Phases Of Drug Use

• How Drug Addiction Affects Relationships
• Can Boredom Lead to a Drug Addiction?
• Medical Consequences of Substance Use Disorders
• Signs of Pill Addiction

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Materials and methods, study end date, exposure classification scheme.

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Observation and Experiment with the Efficacy of Drugs: A Warning Example from a Cohort of Nonsteroidal Anti-inflammatory and Ulcer-healing Drug Users

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Alex D. McMahon, Observation and Experiment with the Efficacy of Drugs: A Warning Example from a Cohort of Nonsteroidal Anti-inflammatory and Ulcer-healing Drug Users, American Journal of Epidemiology , Volume 154, Issue 6, 15 September 2001, Pages 557–562, https://doi.org/10.1093/aje/154.6.557

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Observational data are well suited for many types of medical research, especially when randomized controlled trials are inappropriate. However, some researchers have attempted to justify routine use of observational data in situations in which randomized controlled trials are normally conducted. Literature searches cannot be used to directly compare the results of the two types of research, because invalid observational studies normally are not publishable in the journal literature. The author created a study (1989–1994) to determine the efficacy of one exposure (ulcer-healing drugs) in preventing the serious upper gastrointestinal toxicity associated with another exposure (nonsteroidal anti-inflammatory drugs (NSAIDs)). A cohort of subjects from Tayside, Scotland, receiving both NSAIDs and ulcer-healing drugs appeared to experience a large rise in their risk of gastric bleeding and perforation (e.g., the rate ratio was 10.00 (95% confidence interval: 6.68, 14.97) when this cohort was compared with one receiving NSAIDs alone). This increased risk was due to confounding. Thus, use of a “restricted cohort design” was not able to eliminate uncontrollable bias. It is possible that if many different studies were carried out, then observational research would be found to be only occasionally useful for studying drug efficacy.

It has been traditional to place observational research lower down the quality ranks of clinical evidence than research based on experiment. Cohort studies and case-control studies are usually considered inferior to randomized controlled trials ( 1 ). At worst, observational studies are reckoned to be useful only in generating hypotheses that subsequently can be tested in randomized studies. However, it is well known that randomized controlled trials cannot answer every question and that observational data are useful in many different situations ( 2 , 3 ). The regulatory requirement to carry out randomized controlled trials applies to only the small percentage of clinical studies conducted to licence newly discovered drugs for their targeted indication. Observational data are particularly suited to studying the unintended effects of interventions, such as unexpected drug toxicity, which may be rare and/or have a long delay of onset ( 4 ). One researcher made a reasonable defense of observational studies in 1996 and requested more studies of direct comparisons between observational and randomized studies ( 2 ).

When the two types of studies are compared directly, observational studies are often criticized ( 5 ). However, recently there has been somewhat of a backlash against this view. An effort is under way to move observational studies further up the rankings of “strength of evidence” ( 6 ). The debate has being going on for some time, and every now and then a paper is published attempting to justify observational research on the efficacy of therapies ( 7 ). A paper by Britton et al. in Health Technology Assessment was devoted to this issue ( 8 ), and the research was later summarized in BMJ ( 9 ). The conclusion of this substantial piece of research was that neither method of study tended to produce larger estimates of the effect of treatment. Two recent articles in The New England Journal of Medicine have added more fuel to the controversy ( 6 , 10 ). One set of authors explicitly stated that their results challenge the consensus on the hierarchy of strength of evidence ( 6 ). The implied suggestion is that observational studies may be just as acceptable in informing clinical decisions as their experimental counterparts.

These developments published in the journal literature are a matter of some concern for researchers of pharmaceutical interventions. These papers tend not to reference what could be considered the key papers studying the effectiveness of drugs by using epidemiologic methods ( 11 – 14 ), although one paper ( 8 ) fleetingly refers to the study by Miettinen ( 11 ). There are indeed some situations in which good observational studies may be performed that investigate drug efficacy. Examples are well known, such as in the study of vaccines or insulin use in diabetics ( 2 , 15 ). The only known adverse reaction to the recent papers is limited to several editorials ( 16 , 17 ). Davies and Crombie also published a recent and relevant paper ( 18 ).

The main thrust of these papers is that the literature on a variety of topics has been searched for direct comparisons of the two study methodologies. No systematic differences between the two methodologies have been noted. It has been pointed out that authors who have found differences ( 5 ) have unfairly included observational studies that made use of historical controls ( 7 , 17 , 19 ). One suggested reason for the similar results with the two methods is that observational studies have been improving and now are conducted by adhering to a higher standard ( 10 , 17 ). This line of thought exposes a flaw in the logic of those who would replace randomized controlled trials with more inexpensive observational research ( 6 , 19 ). The fact that the results of controlled trials and observational studies are similar may simply be a result of experienced epidemiologists knowing when a study is invalid because of uncontrollable bias. Invalid studies tend not to be carried out anymore, so this source of conflict with the randomized controlled trial will not manifest itself as published research. Some authors have gone even further and have criticized randomized controlled trials for producing contradictory results and being prone to selection bias ( 6 ). It also has been said that the paucity of good comparative papers is due to observational studies not being “trustworthy,” which turns the argument on its head.

The purpose of the current study was to conduct an examination of drug efficacy that is difficult to carry out by using observational research. It is hoped that this study will serve as both a reminder and a warning that dangerous sources of bias such as confounding by indication are very real ( 12 , 20 , 21 ) and have not been eliminated by using modern epidemiologic techniques. The effects of confounding by indication are still a research topic ( 22 , 23 ). The lesson about the confounded association between warfarin and thrombosis seems to have been forgotten ( 11 ). Some of the serious sources of bias associated with the study of drugs are described by Salas et al. ( 24 ). Confounding by indication occurs when the indication for a treatment is a confounder, and confounding by severity (a related issue) arises when the severity of the disease acts as a confounding variable. Protopathic bias occurs when a treatment is given for early symptoms of the outcome being studied. One recent author has conceded that observational studies of efficacy cannot be used when a treatment is routinely given to the sickest patients ( 10 ). This phenomenon is very common, even when drugs are prescribed for the same illness ( 23 ). At one time it was hoped that statistical adjustment of confounding variables would enable observational study of drug efficacy so that databases could replace randomized studies ( 7 ), but this was a forlorn hope ( 25 ). A research team has even implied that observational data are particularly useful for the study of drug efficacy ( 6 ).

It is not disputed that some observational studies of drug efficacy are indeed possible. With close attention to methodology, observational studies occasionally may provide estimates of a treatment effect that are very similar to the results of an equivalent randomized controlled trial ( 19 ). In the absence of randomization, the single most powerful weapon in the armory of observational studies is selection ( 26 – 28 ). Careful use of subject inclusion criteria in the manner of a clinical trial has been advocated, and this type of study has been dubbed the “restricted cohort design” ( 6 , 19 , 29 ). The idea is to exclude subjects with risk factors that are strong indications for or contraindications to a given treatment, similar to the screening rules in clinical trials. Thus, it may be possible to create groups that are “similar for prognostically important clinical severity” ( 19 ).

As an aside, it has been argued that the clinical trial ultimately fails as a paradigm for observational research ( 27 , 30 ). Attempts to introduce a “time zero” into the restricted cohort design ( 19 ) (to “approximate the point of randomization”) may be thwarted because an observational study may not have a true baseline time point. If no intervention has been applied to the study subjects, then the start of exposure may be an artificial concept, especially when routine medical records are used. There may be no strongly identifiable anchor of time upon which to base the study other than when the outcome occurs at the end of the study.

The current study attempted to remove all possible bias by using very strict subject selection criteria. The data were taken from a previous study of gastric bleeding and perforation associated with use of nonsteroidal anti-inflammatory drugs (NSAIDs) ( 31 ). Unlike the previous study, the current one was designed to specifically examine the protective effects of ulcer-healing drugs when used in combination with NSAIDs. This study looked at the efficacy of one exposure (ulcer-healing therapy) in preventing the toxicity of another (NSAIDs). The aim was to use observational data to determine whether confounding could be combated and to demonstrate that ulcer-healing drugs can protect NSAID users from serious upper gastrointestinal toxicity.

A study population of all identifiable residents of Tayside, Scotland, was created. The MEMO record-linkage database was used to provide details on prescriptions for NSAIDs and ulcer-healing drugs from 1989 to 1994 ( 32 ). The year 1989 was used as a screening period so that bias could be removed by applying the “sacrifice of early data” principle ( 33 ). Therefore, subjects who had received prescriptions for NSAIDs or ulcer-healing drugs during 1989 were excluded from the study base. Subjects for whom the database start date occurred after January 1, 1989, were also excluded. A summary of all inclusion and exclusion criteria is given in table 1 .

Summary of the inclusion and exclusion criteria used to study the efficacy of drugs, Tayside, Scotland, 1989–1994

Subjects were required to meet all screening rules.

NSAID, nonsteroidal anti-inflammatory drug.

In addition to providing a set of new users of the study drugs, the screening period was also required so that the order in which the two types of drugs were prescribed could be determined. This order could be known only after a prescription-free period. The primary outcome was a subject's first emergency hospitalization at a Tayside hospital for a serious upper gastrointestinal diagnosis (i.e., bleeding peptic ulcer or perforated peptic ulcer). The study start date was the date on which the subject received the first prescription (either NSAID, ulcer-healing drug, or both on the same day) after the screening period, that is, from January 1, 1990, onward.

After these exclusions were made, a further set of study exclusions was applied. To ensure that all subjects had at least 6 months of follow-up, all subjects whose study start date was on or after June 1, 1994, were excluded. Subjects who had any hospitalizations for a gastrointestinal diagnosis (not just one of the study outcomes) prior to the study start date also were excluded (data were available from 1980 onward). In addition, all subjects with an endoscopy prior to the study start date were excluded (data were available from 1980 onward). If the first prescription (after the study start date) was for an ulcer-healing drug, then these subjects also were excluded.

There were two reasons for these last three exclusions. Firstly, to minimize confounding problems, subjects who had had gastrointestinal events and endoscopies were excluded. Thus, subjects thought to be at high risk of gastrointestinal problems would be prescribed different patterns of drugs from those prescribed to subjects thought to be at low risk. In a previous study, the risk was indeed found to be higher for subjects with prior events; however, the authors did not find any excess NSAIDs-associated toxicity in these subjects ( 31 ). If subjects who received ulcer-healing drugs in addition to NSAIDs were compared with those who did not, confounding would be particularly problematic.

Secondly, if subjects had received an ulcer-healing drug before an NSAID, then clearly they already were under suspicion (at least) of having peptic disease and probably had some gastrointestinal symptoms. Therefore, this occurrence would again result in confounding, and these subjects were excluded. This study was designed to determine whether ulcer-healing drugs might protect against NSAID toxicity, which might suggest that prior use of ulcer-healing drugs would be of interest. However, because subjects were not randomly allocated to this prior exposure, which would have been prescribed for existing gastrointestinal disease, they were excluded. Note that if the first ulcer-healing drug was prescribed on the same day as the first NSAID, then the subject was allowed into the study.

The first period of NSAID exposure was defined as the chain of all overlapping or consecutive NSAID use beginning on the study start date. A consecutive prescription was defined as one that started the day after the previous one ended. Similarly, the second, third, and following periods of NSAID exposure were estimated. A similar definition was used for periods of exposure to ulcer-healing drugs.

It was anticipated that it would be difficult to realistically define “continuous” periods of exposure exactly given the dates that the pharmacies dispensed the drugs. Short gaps between prescriptions were possible, especially if a patient was not required to take the treatment every day (e.g., the regimen was “as required”). Therefore, before exposure periods were calculated, a period of 7 days was added to the duration of each prescription. Two study groups were created.

The combination therapy group . This group consisted of those subjects whose first period of ulcer-healing drug exposure overlapped a period of NSAID use. Thus, the combined effects of NSAIDs and ulcer-healing drugs could be examined. The “end of exposure” was defined as the day before the second period of ulcer-healing drug exposure began (when there was more than one period of exposure). A subject's exposure was truncated at this point, because the outcome rates for further periods of ulcer-healing drug exposure would have been confounded by the earlier ones.

The NSAID group . Subjects in this group were experiencing their first period of NSAID use and were not part of the combination therapy group. The group included those subjects who had either never received ulcer-healing drugs or received their ulcer-healing drugs when they were not using NSAIDs. Only the first exposure period was considered, because only one type of person-years from this group could be used as the referent. The “end of exposure” was defined as the last day of the first period of NSAID exposure.

The study end date was defined as December 31, 1994, the date of death, the date of the end of exposure, or the date of a study outcome, whichever was the earliest.

For each subject in the combination therapy group, person-years were partitioned into the following types of exposure or nonexposure ( figure 1 ): 1) prior exposure to NSAIDs (possibly several periods), 2) prior nonexposure (possibly several periods), 3) simultaneous exposure to both NSAIDs and ulcer-healing drugs, 4) exposure to ulcer-healing drugs only (if the prescription lasted longer than the one for NSAIDs), 5) “after” exposure to NSAIDs (if the NSAID prescription lasted longer than the one for ulcer-healing drugs, and possibly several more exposure periods had occurred), and 6) “after” nonexposure (possibly several periods). Subjects in the NSAID group simply had “NSAID exposure,” which was collected from their first period of NSAID use.

Sample exposure patterns for subjects in the combination therapy group of drug users, Tayside, Scotland, 1989–1994. N, nonsteroidal anti-inflammatory drug; U, ulcer-healing drug. Refer to the text for an explanation of these patterns.

Each type of exposure for subjects in the combination therapy group was compared with the NSAID group experience (i.e., the referent category of risk). The number of days of exposure was totaled separately for each type of exposure. Incidence rates were calculated by using the number of events per 1,000 person-years of exposure. Rate ratios and 95 percent confidence intervals were calculated.

The main contrast of interest was “combination therapy” versus the NSAID group. Also of interest was the contrast between “prior exposure to NSAIDs” and the NSAID group. This contrast was intended to give some indication of how successful the attempts were to control for confounding. If there was no differential prescribing based on any perceived risk of peptic disease, then the incidence rates in these two groups would be similar.

In the NSAID group, the incidence rate for bleeding and perforation was 6.30 events per 1,000 person-years of exposure ( table 2 ). In the combination therapy group, the incidence rate was 4.70 during the periods of nonexposure before the combination of NSAIDs and ulcer-healing drugs started. This rate is slightly but not significantly lower than the rate for the NSAID group. For prior NSAID use, the rate rose to 56.40, which was significantly higher than the rate for the NSAID group; the rate ratio was 8.95 (95 percent confidence interval: 6.63, 12.08). During combination therapy with ulcer-healing drugs, the incidence rate rose even higher to 63.00, and the rate ratio was 10.00 (95 percent confidence interval: 6.68, 14.97). The rate was lower for types of exposure that occurred after the combination period, namely, 8.51 for ulcer-healing drugs only and 7.12 for NSAIDs only, and it fell to 4.55 for subsequent periods of nonexposure.

Incidence of gastric bleeding and perforation in each study group and for each type of drug exposure, Tayside, Scotland, 1989–1994

NSAID, nonsteroidal anti-inflammatory drug; UHD, ulcer-healing drug.

Therefore, the rate was higher in the combination therapy group during either initial NSAID use or the actual combination therapy with ulcer-healing drugs. The rate of gastrointestinal toxicity in this group became similar to the rate in the NSAID group only after the ulcer-healing drug exposure had ended (postcombination NSAID use was associated with a rate of 7.12 compared with a rate of 6.30 in the NSAID group).

The combination therapy group had a high incidence of toxicity. This finding was probably due to confounding, despite the study design. Ulcer-healing drugs did not reduce the rate either, because the drugs were consequently prescribed to subjects at an increased risk. The fact that the risk was very high in the combination therapy group, even before treatment with ulcer-healing drugs, demonstrates that the two groups of patients were not comparable with regard to gastrointestinal risk. It has been shown that some types of NSAIDs are channeled toward patients at a higher gastrointestinal risk than others are ( 23 ). It is reasonable to assume that this effect would be even more pronounced when comparing those who have and have not been exposed to ulcer-healing drugs when they are also using prescribed NSAIDs. Some evidence suggests that ulcer-healing drugs can prevent gastric toxicity associated with exposure to NSAIDs, although this evidence is by no means conclusive (especially for H 2 -antagonists) ( 34 – 36 ). Even if these drugs are not effective in preventing this type of NSAID toxicity, they certainly are not responsible for a 10-fold increase in toxicity.

In this instance, observational data were found to be unsuitable for detecting the intended effects of a pharmaceutical intervention. This study failed to be internally valid , which is obviously a prerequisite to being externally valid ( 37 ). In the United States, the government body called the Agency for Healthcare Research and Quality (AHRQ) accepts applications for funding of observational studies of effectiveness, provided they are methodologically rigorous and both internally and externally valid. The current study provides an example of a treatment and disease pair that was not suitable for study without introduction of random allocation of treatments. When the study was designed, every effort was made to exclude every source of measurable bias. Every subject in the population who had ever received an endoscopy, or even an ulcer-healing drug, was excluded. Therefore, the principles of the “restricted cohort design” were followed.

Unfortunately, diagnostic notes from general practitioners were not accessible, because that type of information was not available in the particular record-linkage database used in the study ( 31 , 32 ). It may be possible to access further information regarding symptoms and severity of disease in a more detailed observational study, for example, in a prospective study that uses patient interviews. That type of study would have some advantages over a “database study.” However, using that type of information probably would not have changed the conclusions drawn from the present study, even if the rate ratios had decreased slightly. One advantage of the database used in the study is that every prescription dispensed for the entire population was available. Everything that could be done was done. Note that analytical techniques such as propensity scores ( 38 ) are only useful for reducing confounding that has been measured.

What can be deduced from the results of the current study? If proper refutationist logic ( 39 , 40 ) is followed, observational and experimental studies do not always produce equal estimates of a treatment effect. However, other authors similarly have been unable to prove that observational studies are always as good as randomized controlled trials (a claim that very few people would make anyway). The implicit message is that observational studies of drug efficacy may often or even usually produce valid estimates. I suspect that observational studies of drug efficacy will usually not produce accurate results. This idea is testable in principle but not in practice. The hypothesis that both techniques are similar could be refuted by carrying out a large number of head-to-head tests for various classes of pharmaceuticals. However, this research would be very unsatisfying for researchers to conduct and would never be funded, and publication would no doubt be problematic. Nevertheless, the current study should serve as a timely caution for researchers thinking of applying data from observational databases to research into the efficacy (or effectiveness) of pharmaceutical treatments.

(Reprint requests to Dr. Alex D. McMahon at this address).

The author thanks the research team of the MEMO unit in Dundee, Scotland, especially Professor Tom MacDonald, Dr. Josie Evans, Dr. Mark McGilchrist, Gary White, and Douglas Boyle.

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Drug Experimentation: Symptoms, Causes, and Effects

Drug experimentation is a stage within the complex journey of drug addiction, characterized by individuals exploring and engaging in substance use for various reasons. People who experiment with drugs or alcohol do it as a one-time thing for the purpose of experiencing the effects of the drug or to get over a certain emotional or mental state.. Some individuals may also do it out of curiosity, peer influence, or as a coping mechanism. However this is done, it is unhealthy and can become a precursor to active drug addiction.

The effects of drug experimentation can range from instant impaired decision-making to social and emotional strain, addiction vulnerability, and health challenges. While it may look like a quick getaway from reality, the consequences and risks of experimenting with drugs can be devastating.

What is Drug Experimentation?

Drug experimentation is the act of trying or using drugs recreationally, often driven by curiosity, peer influence, or personal circumstances. It represents an initial step in the continuum of substance use, where individuals are motivated by a desire to experience altered states of consciousness or to cope with certain emotions or situations.

Drug experimentation is the first stage in the cycle and journey to full-blown drug addiction, preceding drug abuse, drug tolerance and dependence, and eventual recovery. Drug experimentation is also the most common in adolescents among all the phases of drug addiction, as reported by the Monitoring The Future (MTF) study conducted by the University of Michigan. The report states that in 2020, approximately 35% of high school seniors in the United States had experimented with illicit drugs at least once.

Engaging in drug experimentation, regardless of the substance involved—be it alcohol, marijuana, or prescription medication—poses a significant risk of developing addiction. It is important to understand that one’s perceived ability to handle the drug does not necessarily safeguard against the dangers that drug experimentation entails. The potential consequences of such experimentation can swiftly manifest and pose serious risks to individuals involved.

What are the Causes of Drug Experimentation?

The cause of drug experimentation can vary from person to person and can be influenced by environmental, social, and personal decisions. An article by the National Institute on Drug Abuse (NIDA) highlights that curiosity, social influences, and a desire for novel experiences are common reasons for drug experimentation among adolescents and young adults.

1. Curiosity

Curiosity can be a significant cause of drug experimentation because it drives individuals to seek new experiences and explore the unknown. Curiosity about drugs often arises from various sources, such as hearing about drug experiences from others, media portrayals, or societal discussions. Individuals may become intrigued by the altered states of consciousness or sensory experiences that drugs can induce. They might be curious about how different substances affect their perceptions, emotions, or cognitive functions.

2. Peer Influence

Peer influence is a significant cause of drug experimentation, particularly during adolescence and young adulthood, when individuals are highly influenced by their social circles. Young people might experiment with drugs and other harmful substances for the sake of social acceptance and belonging perceived benefits, or even peer pressure. Some people may also engage in their first drug use by modeling the behavior of their peers.

3. Coping Mechanisms

Some individuals turn to drug experimentation to cope with post-trauma, stress, emotional challenges, or underlying mental health issues, such as depression or anxiety. Substances like opioids, benzodiazepines, alcohol, and cannabis can be used by people going through mental, emotional, and even physical pain to relieve symptoms of depression and anxiety. However, the relief that can be gotten from using these substances is temporary and can lead people deeper into the hole of addiction.

4. Cultural and Societal Influences

Cultural norms, media portrayals, and societal attitudes toward drug use can shape individuals’ perceptions and influence their willingness to experiment with drugs. Cultural acceptance or normalization of drug use can play a role in facilitating experimentation. 

6. Genetic and Biological Factors

Genetic and biological factors can contribute to an individual’s susceptibility to drug experimentation. While they may not directly cause drug experimentation, they can influence certain predispositions and vulnerabilities that increase the likelihood of engaging in such behaviors.

Biological factors, including enzyme activity and metabolism, can affect an individual’s drug sensitivity. Some individuals may metabolize substances more slowly or rapidly, leading to variations in drug effects and potentially heightened or prolonged experiences. This heightened sensitivity or altered drug response may contribute to the appeal or curiosity surrounding drug experimentation.

7. Personal Factors

Personal factors, such as low self-esteem, a lack of coping skills, a history of trauma, or a predisposition to seek novel experiences, can contribute to drug experimentation. These factors may make individuals more susceptible to trying drugs as a means of self-exploration or self-medication.

It is essential to recognize that these causes are multifaceted and often interact with one another. Each individual’s journey with drug experimentation is unique and influenced by a combination of these factors. By understanding the causes, we can develop effective prevention strategies and interventions to address the underlying motivations and reduce the risks associated with drug experimentation.

What Are the Signs That Someone Is Experimenting With Drugs?

The signs that someone might be experimenting with drugs and other substances can be challenging to notice because this is only a one-time thing, and the individual may go to great lengths to conceal their activities. These signs are far from what one might experience in the full-blown drug addiction phase. However, several behavioral, physical, and psychological signs may indicate drug experimentation. It is important to note that these signs are not definitive proof of drug use, but they can serve as possible indicators. 

• Sudden and unexplained changes in social circles, friends, or peer groups.
• A decline in academic or work performance, loss of interest, or increased absenteeism.
• Uncharacteristic or unpredictable behavior, such as mood swings, irritability, or aggression.
• Increased secrecy, withdrawal from family and friends, or a loss of interest in previously enjoyed activities.
• Bloodshot or glazed eyes, dilated or constricted pupils.
• Sudden weight loss or gain, changes in appetite.
• Frequent nosebleeds, sniffing, or a runny nose (for individuals using drugs that are snorted).
• Slurred speech, impaired coordination, or unsteady gait.
• Poor hygiene, lack of grooming, or a disheveled appearance.
• Neglecting personal responsibilities, such as household chores or self-care.
• Insomnia or excessive sleepiness.
• Irregular sleep patterns, such as staying up all night or sleeping during the day.
• Discovering drug paraphernalia, such as pipes, needles, small plastic bags, or rolled-up dollar bills.
• Finding drug-related items like burnt spoons, lighters, or foil with burn marks.
• Sudden and unexplained changes in mood or personality.
• Increased anxiety, paranoia, or depression.
• Decreased motivation or loss of interest in future goals.
• Memory problems, confusion, or difficulty concentrating.

If you notice these signs in your loved one, it is important to approach the situation with empathy and support. Consider having an open and non-judgmental conversation with them. Encouraging them to seek professional help or connecting them with appropriate resources can be crucial in addressing the issue effectively.

Is Drug Experimentation Common Among Adults?

While drug experimentation is often associated with adolescence, it is not uncommon among adults. Factors such as life changes, exposure to new social circles, or the desire for new experiences can lead adults to experiment with drugs.

Can Drug Experimentation Lead to Other Risky Behaviors?

Yes, drug experimentation can be associated with other risky behaviors, such as unprotected sex, driving under the influence, or experimenting with multiple substances simultaneously. The impaired judgment resulting from drug use can contribute to these behaviors.

What are the Effects of Drug Experimentation?

Drug experimentation can have a range of effects on individuals, encompassing physical, psychological, social, and legal consequences. While the specific effects can vary depending on the drug used, the frequency and duration of experimentation, and individual factors, here are some common effects:

Short-Term Effects

• Immediate physical changes, such as altered heart rate, blood pressure, and body temperature.
• Symptoms like nausea, dizziness, impaired coordination, and increased risk of accidents or injuries.
• Mood alterations, ranging from euphoria and increased confidence to anxiety, agitation, or depression.
• Impaired judgment, problem-solving, and decision-making abilities.
• Risk of acute overdose or adverse reactions, depending on the drug and dosage.

Long-Term Effects

• Physical health consequences, such as organ damage (e.g., liver damage from alcohol, kidney damage from certain drugs), cardiovascular issues, respiratory problems, compromised immune system, and increased risk of chronic diseases.
• Increased risk of developing mental health disorders, such as anxiety disorders, depression, psychosis, and substance-induced mood disorders.
• Strained relationships with family, friends, and romantic partners due to changes in behavior and increased secrecy.
• Isolation and withdrawal from social activities and responsibilities.
• Financial difficulties, job loss, legal issues, and involvement in criminal activities.
• Increased risk of developing addiction and experiencing the associated physical, psychological, and social consequences.
• Academic or professional setbacks decreased performance and missed opportunities for personal growth and advancement.
• Legal ramifications, such as arrests, fines, or imprisonment, depending on the drug’s legal status and jurisdiction.

The effects of drug experimentation can be far-reaching, impacting multiple areas of an individual’s life. Seeking early intervention, support, and treatment can help mitigate the potential negative effects and promote healthier choices and outcomes.

What is the Difference Between Drug Experimentation and Drug Abuse?

While both drug experimentation and abuse are stages in the cycle of drug addiction, they happen at different levels and with different levels of intensity. Drug experimentation refers to the act of trying drugs out of curiosity or a desire for a new experience. It involves using substances on an occasional or limited basis, often in social settings. People experimenting with drugs are typically driven by curiosity and may want to explore the effects and sensations associated with substance use. They do not have a strong reliance on drugs, and their use is not a central part of their daily lives. Furthermore, they do not experience cravings or a compulsive need to use substances to function normally.

Drug abuse is the excessive and consistent use of drugs, often resulting in negative consequences for the individual’s physical health, mental well-being, relationships, and overall functioning. Drug abusers use substances excessively and suffer consequences from their use, but they are not physically tolerant and do not experience severe withdrawal symptoms when they stop using. An example of a drug abuser is someone who goes out to a bar and blacks out, and uses cocaine once a month. Additionally, drug abuse can occur more frequently, including at school or work, and often takes place in isolation.

People in both of these phases of drug addiction need help and support from their loved ones or a therapist. If you or a loved one has been experimenting with drugs or abusing them, speak with a professional to help you retrace your steps and be on the path to a drug-free, healthy, and wholesome life.

Break Free From Addiction Today At Valley Spring Recovery Center

What Prevention and Treatment Methods Can Help People in The Drug Experimentation Phase?

Prevention methods aimed at individuals in the drug experimentation phase focus on providing education, support, and alternative coping strategies to help them make informed and healthier choices. Because individuals in this phase of drug addiction have not yet begun experiencing many of the harmful effects of abusing drugs, treatment options are usually limited to helping them move past drug use and focus on living a healthy life. Outpatient treatment and PHP addiction treatment are usually good ways for drug experimenters to receive counseling and support without having to go to an inpatient residential program. 

In this phase, education and awareness is vital. Providing accurate and evidence-based information about the risks, consequences, and potential harms associated with drug use is crucial. Also, since peer pressure can be a causative factor, they can also be taught effective peer resistance skills to empower them to resist peer pressure and make choices that align with their values and well-being. 

People in this phase also need to develop healthy coping mechanisms, build healthy and supportive relationships, and seek early intervention to address specific risk factors. It’s important to note that prevention methods should be comprehensive, addressing multiple levels of influence, including individual, family, community, and societal factors.

Is It Possible To Recover From Drug Experimentation?

It is possible to overcome the drug experimentation phase. Many individuals who have engaged in drug experimentation are able to move past that phase and make positive changes in their lives. Overcoming drug experimentation involves a combination of self-reflection, support, and adopting healthier coping mechanisms. 

Individuals experimenting with illegal substances can seek self-reflection, support, and motivation, build resilience, learn from their mistakes, and set and achieve drug avoidance goals. 

It’s important to note that overcoming drug experimentation may vary for each individual and that professional help and support can greatly enhance the process. No matter how small, every step towards change is a positive step towards a drug-free and healthier life.

Is Drug Experimentation a Gateway to Addiction?

While drug experimentation does not guarantee that an individual will develop an addiction, it can increase the risk. Experimenting with drugs exposes a person to substances that have the potential for abuse and dependency, making it a possible gateway to more frequent use or addiction.

What Factors Influence Drug Experimentation?

Several factors can influence drug experimentation, including peer pressure, curiosity, and environmental factors like availability. Psychological factors such as stress or emotional pain can also contribute to the decision to experiment with drugs.

Can Drug Experimentation Affect Mental Health?

Yes, even casual or experimental drug use can have an impact on mental health. Some drugs can exacerbate symptoms of anxiety, depression, or other mental health conditions. Additionally, the act of experimenting with drugs can introduce stressors, such as legal risks and social consequences, that affect mental well-being.

How Can One Seek Help for Drug Experimentation?

If you or someone you know is concerned about drug experimentation, various resources are available for help. PHP addiction treatment programs are usually a perfect fit for individuals experimenting with drugs that need help before they progress into abuse, tolerance, and addiction.  

• https://deepblue.lib.umich.edu/bitstream/handle/2027.42/171751/mtf-overview2021.pdf?sequence=1&isAllowed=y
• https://nida.nih.gov/publications/drugs-brains-behavior-science-addiction/drug-misuse-addiction

With a decade of experience in producing content for drug rehabilitation centers, Ben has developed a deep understanding of the challenges and triumphs in this sphere. In 2019, he founded the video blog "A String Of Hope," a platform that has become a beacon of inspiration and positive change for individuals seeking recovery, reaching millions worldwide. As someone who is personally journeying through recovery, Ben's work is not only rooted in professional knowledge but also enriched by his own experiences. His commitment to sharing stories of hope and resilience has established him as a credible and respected figure in the addiction treatment community.

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A smarter way to streamline drug discovery

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The use of AI to streamline drug discovery is exploding. Researchers are deploying machine-learning models to help them identify molecules, among billions of options, that might have the properties they are seeking to develop new medicines.

But there are so many variables to consider — from the price of materials to the risk of something going wrong — that even when scientists use AI, weighing the costs of synthesizing the best candidates is no easy task.

The myriad challenges involved in identifying the best and most cost-efficient molecules to test is one reason new medicines take so long to develop, as well as a key driver of high prescription drug prices.

To help scientists make cost-aware choices, MIT researchers developed an algorithmic framework to automatically identify optimal molecular candidates, which minimizes synthetic cost while maximizing the likelihood candidates have desired properties. The algorithm also identifies the materials and experimental steps needed to synthesize these molecules.

Their quantitative framework, known as Synthesis Planning and Rewards-based Route Optimization Workflow (SPARROW), considers the costs of synthesizing a batch of molecules at once, since multiple candidates can often be derived from some of the same chemical compounds.

Moreover, this unified approach captures key information on molecular design, property prediction, and synthesis planning from online repositories and widely used AI tools.

Beyond helping pharmaceutical companies discover new drugs more efficiently, SPARROW could be used in applications like the invention of new agrichemicals or the discovery of specialized materials for organic electronics.

“The selection of compounds is very much an art at the moment — and at times it is a very successful art. But because we have all these other models and predictive tools that give us information on how molecules might perform and how they might be synthesized, we can and should be using that information to guide the decisions we make,” says Connor Coley, the Class of 1957 Career Development Assistant Professor in the MIT departments of Chemical Engineering and Electrical Engineering and Computer Science, and senior author of a paper on SPARROW.

Coley is joined on the paper by lead author Jenna Fromer SM ’24. The research appears today in Nature Computational Science .

Complex cost considerations

In a sense, whether a scientist should synthesize and test a certain molecule boils down to a question of the synthetic cost versus the value of the experiment. However, determining cost or value are tough problems on their own.

For instance, an experiment might require expensive materials or it could have a high risk of failure. On the value side, one might consider how useful it would be to know the properties of this molecule or whether those predictions carry a high level of uncertainty.

At the same time, pharmaceutical companies increasingly use batch synthesis to improve efficiency. Instead of testing molecules one at a time, they use combinations of chemical building blocks to test multiple candidates at once. However, this means the chemical reactions must all require the same experimental conditions. This makes estimating cost and value even more challenging.

SPARROW tackles this challenge by considering the shared intermediary compounds involved in synthesizing molecules and incorporating that information into its cost-versus-value function.

“When you think about this optimization game of designing a batch of molecules, the cost of adding on a new structure depends on the molecules you have already chosen,” Coley says.

The framework also considers things like the costs of starting materials, the number of reactions that are involved in each synthetic route, and the likelihood those reactions will be successful on the first try.

To utilize SPARROW, a scientist provides a set of molecular compounds they are thinking of testing and a definition of the properties they are hoping to find.

From there, SPARROW collects information on the molecules and their synthetic pathways and then weighs the value of each one against the cost of synthesizing a batch of candidates. It automatically selects the best subset of candidates that meet the user’s criteria and finds the most cost-effective synthetic routes for those compounds.

“It does all this optimization in one step, so it can really capture all of these competing objectives simultaneously,” Fromer says.

A versatile framework

SPARROW is unique because it can incorporate molecular structures that have been hand-designed by humans, those that exist in virtual catalogs, or never-before-seen molecules that have been invented by generative AI models.

“We have all these different sources of ideas. Part of the appeal of SPARROW is that you can take all these ideas and put them on a level playing field,” Coley adds.

The researchers evaluated SPARROW by applying it in three case studies. The case studies, based on real-world problems faced by chemists, were designed to test SPARROW’s ability to find cost-efficient synthesis plans while working with a wide range of input molecules.

They found that SPARROW effectively captured the marginal costs of batch synthesis and identified common experimental steps and intermediate chemicals. In addition, it could scale up to handle hundreds of potential molecular candidates.

“In the machine-learning-for-chemistry community, there are so many models that work well for retrosynthesis or molecular property prediction, for example, but how do we actually use them? Our framework aims to bring out the value of this prior work. By creating SPARROW, hopefully we can guide other researchers to think about compound downselection using their own cost and utility functions,” Fromer says.

In the future, the researchers want to incorporate additional complexity into SPARROW. For instance, they’d like to enable the algorithm to consider that the value of testing one compound may not always be constant. They also want to include more elements of parallel chemistry in its cost-versus-value function.

“The work by Fromer and Coley better aligns algorithmic decision making to the practical realities of chemical synthesis. When existing computational design algorithms are used, the work of determining how to best synthesize the set of designs is left to the medicinal chemist, resulting in less optimal choices and extra work for the medicinal chemist,” says Patrick Riley, senior vice president of artificial intelligence at Relay Therapeutics, who was not involved with this research. “This paper shows a principled path to include consideration of joint synthesis, which I expect to result in higher quality and more accepted algorithmic designs.”

“Identifying which compounds to synthesize in a way that carefully balances time, cost, and the potential for making progress toward goals while providing useful new information is one of the most challenging tasks for drug discovery teams. The SPARROW approach from Fromer and Coley does this in an effective and automated way, providing a useful tool for human medicinal chemistry teams and taking important steps toward fully autonomous approaches to drug discovery,” adds John Chodera, a computational chemist at Memorial Sloan Kettering Cancer Center, who was not involved with this work.

This research was supported, in part, by the DARPA Accelerated Molecular Discovery Program, the Office of Naval Research, and the National Science Foundation.

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Teen Drug Experimentation

Learn about teen drug experimentation and the dangers that it can lead to..

Teen drug use is a serious problem. According to the National Institute on Drug Abuse, by their senior year of  high school , more than 20% of teenagers have used a prescription drug for a non-medical purpose, 40% have smoked a cigarette, 50% have taken an illegal drug and 70% have tried alcohol. Many parents fail to understand that statistically, their teenager is likely to have used drugs or alcohol by the time they graduate.

Many parents who learn about these alarming statistics wonder, “What is experimental drug use?” Experimental drug use  takes place  when an individual takes a drug less than three times to experience its effects.

How Experimental Teen Drug Use Begins

Teens often begin using drugs at school or with friends who already use drugs.  Peer pressure  is the primary cause of experimental drug use and often influences teens who have been taught not to use drugs. Teens are likely to receive most of their information about drug use from peers. Experimental drug use often initially involves a more socially acceptable drug, such as  marijuana ,  nicotine  or  alcohol . When a teen uses one of these drugs and finds out that this single-use does not cause significant harm or immediately turns into an addiction, they may develop a false sense of security and try more dangerous drugs.

Why Do Teens Use Drugs?

Many parents who have teenagers wonder, “Why do teens start using drugs?” There are several reasons that teens may begin experimenting with drugs, including:

• Giving in to peer pressure
• Desiring to feel good
• Self-medicating stress, anxiety or untreated mental illness
• Improving academic performance
• Experimenting and curiosity

Even teenagers who have been educated about drug use and its dangers may rationalize using drugs “just once” for any of the above reasons.

Experimenting with Drugs is NOT Harmless

As teenage drug abuse statistics show, teenage drug use is a significant problem. Over  5,000 young people between the ages of 15 and 25 die each year from drug overdoses. Many of those who overdose started with experimentation that they never expected to develop into anything more.

Experimentation with drugs may create a higher  risk of overdose , as a teenager may not be aware of what a particular dose of drugs may do to them and may be more likely to overdose. This can be an especially significant problem when a peer who has used a drug and becomes tolerant to its effects gives that same dose to another teenager who has never used the substance. This high dose can cause the teen who is experimenting to overdose and lead to permanent injury or death. Even if experimentation does not cause harm, it can start teens on the path to drug addiction — a path that can have profound consequences on their future.

Experimenting vs. Addiction

Teen addiction  almost always starts with experimentation. Experimentation can lead to recreational drug use, which begins to rewire the brain and can quickly lead to an addiction. Experimentation does not always lead to addiction, but addiction is always a result of having experimented with drugs or alcohol at some point. When teens never experiment with a drug, they are ensuring that they will not develop an addiction to that drug.

Talking to Your Teenager About Teen Drug Use

Talking to teens about drugs is vital to help prevent them from experimenting with drugs later in life. When you talk to your teen about drugs, be sure that you explain the potential dangers of drugs, including the physical and social dangers that drugs can create. Be sure that they understand that their peers who use drugs likely do not understand the long-term dangers that are associated with drug use and will only share one perspective about drug use.

When talking to your teen, be sure to address the reasons that teens use drugs, and help them plan ways to avoid situations that could lead to drug use. Developing a plan before these situations are encountered will help your teen better deal with them when they arise. Be sure to let your teen know that you are there to help them, not judge them.

If you suspect or know that your  teen is using drugs , you should seek immediate professional help for them to reduce the risk of the long-term consequences of drug use. The Recovery Village has a strong record of helping teens who have used drugs to achieve and maintain sobriety.   Reach out  to a representative today to learn more about our evidence-based treatment programs.

Alcohol and Drug Foundation. “ Alcohol & Drug Use “> Alcohol […]amp; Drug Use .” 2019. Accessed August 25, 2019.

National Institute on Drug Abuse. “ Principles of Adolescent Substance Use Disorder Treatment: A Research-Based Guide .” Jan. 2014. Accessed Aug. 25, 2019.

National Institute on Drug Abuse. “ Why Do Adolescents Take Drugs? ” January 2014. Accessed August 25, 2019.

National Institutes of Health. “ Drug Overdoses in Youth “> Drug Ove[…]oses in Youth .” February 2019. Accessed Aug. 25, 2019.

U.S. Department of Health & Human Services. “ United States Adolescent Substance Abuse Facts “> United S[…]e Abuse Facts .” May 1, 2019. Accessed August 25, 2019.

The Recovery Village aims to improve the quality of life for people struggling with substance use or mental health disorder with fact-based content about the nature of behavioral health conditions, treatment options and their related outcomes. We publish material that is researched, cited, edited and reviewed by licensed medical professionals. The information we provide is not intended to be a substitute for professional medical advice, diagnosis or treatment. It should not be used in place of the advice of your physician or other qualified healthcare providers.

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Where is the line between experimenting with drugs and drug misuse? There is no healthy way to experiment with drugs. These substances can impact your health and lead to a serious substance use disorder. While many view experimental drug use in a casual way, the effects on a person’s life and health should not be underestimated.

Why Do People Experiment With Drugs?

It’s estimated that nearly 20% of people in the United States have tried illicit drugs of some kind, including opioids, cocaine , meth and marijuana . That’s over 50 million people who have, at the very least, experimented with drug use. There are a number of reasons people try drugs recreationally:

• Curiosity or boredom: Drugs pique the curiosity of those who view using these substances as a new or daring experience.
• Normalization: Much of our culture has normalized drug use to the point where it’s seen as a common rite of passage, not a potentially life-threatening activity.
• Peer pressure: Teenagers are especially susceptible to experimenting with drugs if they believe everyone in their peer group is doing it. They’re afraid of not being accepted by others.
• Pushing boundaries:  Drugs are often viewed as a means to rebel against parents or authority.
• To feel good: Many people struggle with underlying mental health problems, such as anxiety or depression. These individuals sometimes experiment with drug use to try to feel better.

Why is Drug Experimentation Dangerous?

Teenagers and young adults are programmed to experiment. Yet drug use is an activity that comes with negative consequences and potential risks:

• Accident or injury: There’s no way to tell how your body will react to certain drugs. Overdose, seizure and respiratory distress are just a few of the severe injuries that can have fatal consequences.
• Repeat use: Drugs release a flood of neurochemicals throughout your body. These effects may seem to relieve emotional and physical issues. Because of this, you may feel compelled to repeat the drug use over and over, quickly leading you down the road to addiction.
• Developmental impact: Experimentation is more common among adolescents. Yet drug use can have a severe impact on the developing brains and bodies of teenagers, such as cognitive damage.
• Contributes to risky behavior:  Drug use frequently occurs with other risky behavior, like driving under the influence or having unprotected sex.
• Health problems: Experimentation often gives way to long-term drug misuse, which can contribute to a variety of health problems, including sleep disorders, high blood pressure and heart disease.
• Mystery Ingredients: The creation of illegal drugs is an unregulated industry, so you don’t know what you are actually getting. Drug ingredients can vary and be cut or laced with deadly substances such as Fentanyl, Carfentanil, rat poison, etc.

Get Help for Uncontrollable Drug Use at Gateway Foundation

Experimentation can easily transform into addiction. Some people manage to experiment with drugs recreationally without becoming addicted. However, you never know how these drugs will influence your body or behavior.

If your occasional drug use has gotten out of control, Gateway Foundation can help. We provide a judgment-free, safe environment where you can break addiction’s hold over your life. Our evidence-based treatments are personalized to your exact needs to offer hope and healing as you learn to live sober and free. Learn more when you contact Gateway Foundation today .

Gateway Foundation

Gateway Foundation is a recognized leader in evidence-based addiction treatment proven to get results. Our experts in Addiction Medicine—including highly educated clinical and medical professionals and expert psychiatrists and nurses—deliver care that never stops. For over 50 years, Gateway Foundation has been helping individuals and their families recover from addictions and behavioral health issues and is the only provider that covers the entire state of Illinois with 16 facilities from the Wisconsin Border to the Kentucky Border. Gateway has specific programs focusing on substance use disorders, trauma, depression, anxiety, and other co-occurring issues. We’re licensed by the state of Illinois and accredited by the Joint Commission. We are in-network with all the major commercial insurance plans. Gateway Foundation: Addiction medicine, saving lives.

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Under the Influence? Drugs and the American Work Force.

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4 Impact of Alcohol and Other Drug Use: Laboratory Studies

Despite substantial national efforts, drug abuse remains a serious public health problem for a sizable proportion of the population. Since data presented in Chapter 3 suggest that a sizable portion of the work force uses drugs, reducing use by the active work force would have an impact on drug use overall, reducing the pool of illicit drug users in the United States and moving us closer to the societal goal of eliminating drug abuse. The workplace is thus an obvious site for user-focused interventions.

• Strengths And Limitations Of Laboratory Studies

This societal perspective is seldom used to justify programs to reduce or eliminate drug use by the work force, and there may be constitutional problems with workplace drug-testing programs aimed predominantly at this goal. Interventions aimed at securing a drug-free workplace are justified instead largely on safety and productivity grounds. The data obtained in worker population studies, however, do not provide clear evidence of the deleterious effects of drugs other than alcohol on safety and other job performance indicators. This does not mean there are no deleterious effects; it may reflect the paucity of relevant data and the quality of the research done to date.

The extent to which impaired worker performance due to drug use can affect safety and productivity in the workplace is not well understood, although a substantial amount of laboratory research has been carried out evaluating the effects of single doses of various abusable drugs on cognitive and psychomotor performance. The results of such research cannot be extrapolated directly to the workplace because the effects of drugs on workplace performance are a complex function of the interaction between the dynamic workplace environment and the multiplicity of other variables impinging on the worker. For example, the job performance of a worker who has slept little the night before, is anxious about a family member's problem, has not eaten breakfast, must work with a dangerous piece of equipment, and has continually changing job demands is likely to be affected differently by a prior night's use of marijuana or cocaine than a well-rested worker performing a routine task. The challenge of modeling such complex interactions and simplifying the issues so that they can be studied in the laboratory is obvious and may never fully be met. Yet laboratory research can provide a base from which to start understanding such problems. Even if it cannot capture the full richness of the occupational world, it can help us understand how the drugs people take interact with different kinds of ongoing behavior; this is knowledge we must have in order to design and implement effective intervention programs.

A second goal of laboratory research on drug effects is to develop reliable measures of the acute impairment associated with drug use. To date, the most commonly used method for identifying drug use by the work force relies on urinalysis to detect the presence of drugs or their metabolites. Such testing does not address the issue of drug-induced impairment. Although there are data relating dose of alcohol to level of impairment, there are no data relating the level of other drugs (or their metabolites) obtained from urinalysis to levels of impairment. Laboratory-developed measures of impairment that lead to the development of a reliable and easily administered performance battery for the detection of workplace performance impairment could be an enormous improvement over the current technologies (discussed in Chapter 6 ).

A myriad of laboratory performance studies have been carried out to test the effects, under controlled conditions, of such drugs as stimulants, marijuana, sedatives, benzodiazepines, and alcohol (see Table 4.1 ). 1 However, even apart from the complex interaction effects mentioned above, these studies have numerous shortcomings as guides to understanding the effects of alcohol and other drug use by the work force. Although the doses studied are sometimes (but not always) the same as those being used by drug users in the work force, patterning of drug use comparable to that of many drug users (i.e., multiple doses, periodically repeated doses, etc.) has not been adequately addressed. Moreover, with few exceptions, no attempt has been made to model the specific task used to measure impairment after specific workplace performances, and multiple variations on similar tasks make generalization across studies difficult.

Examples of Task and Performance Effects of Selected Drugs of Abuse.

To further complicate the picture, there has been little effort to model the subject population in laboratory studies after the work force population. The most frequently used research subject is a college student, paid to participate in a research project, or expected to participate in order to fulfill a course requirement. In addition, unlike the worker who is experienced in the task being performed, the subjects in most drug use studies are frequently performing the tasks on which impairment is measured for the first time or after only a brief period of training. Behavioral histories are seldom taken into account in laboratory research. Other common weaknesses of experimental design include inattention to doses used, time points for measurements, and contingencies in maintaining behavior. Despite these problems, however, a few generalizations can be drawn about the likely effects of different classes of drugs on performance.

• Drugs And Their Effects

Stimulant Drugs

Stimulant drugs (e.g., caffeine, amphetamine, cocaine) increase general activity, lead to reports of positive subjective effects, and are often used clinically to reduce food intake (Fischman, 1987). Despite users' reports of substantial performance enhancement after stimulant use, this effect has not been systematically replicated in the laboratory (Johanson and Fischman, 1989). When improvement in performance has occurred, the margin of improvement has either been less than 10 percent, or stimulants prevented or reversed a decrement in performance due to fatigue or boredom. Of course in some situations like athletic competitions, a minor improvement in performance could have large positive effects for the performer (Laties and Weiss, 1981), and, when otherwise unavoidable fatigue or boredom are fought off, decrements in performance may be forestalled. In general, however, it is important to point out that significant performance enhancement is not apparent; much of what users report are the subjective effects of stimulants (e.g., increased levels of energy, friendliness), which lead to a belief that behavior is improved without any actual improvement (Fischman, 1987).

The use of marijuana and products containing δ 9 -tetrahydrocannabinol (THC) has a long history, and the literature on the effects of these substances on performance is voluminous. Concentrated efforts to delineate marijuana-related effects on behavior have yielded variable results, with the most consistent effects being decrements in time estimation and divided attention tasks (e.g., Jones and Stone, 1970; Marks and MacAvoy, 1989). Marijuana interfered with performance on a variety of other tasks on approximately 50 percent of the occasions it was studied (e.g., arithmetic, Chesher et al., 1977; tracking, Barnett et al., 1985), suggesting that experimental conditions play a substantial role in determining the effects of this substance. Although there is some evidence that marijuana can affect performance for several hours after it is used (e.g., Miller and Cornett, 1978), there are almost no data on what behaviors are impaired, for how long, and to what extent.

There has been a general belief that smoking marijuana can lead to a cluster of signs and symptoms often referred to as an amotivational syndrome . If it does, repeated rather than occasional use of marijuana could have severe implications for behavior and productivity in the workplace. The motivational effects of marijuana have provided a focus for research over the past several decades, with variable results. In general, well-controlled epidemiological studies of marijuana use have failed to confirm the existence of such a syndrome (e.g., Comitas, 1976; Stefanis et al., 1977; Page, 1983), and laboratory research suggests that environmental conditions can influence the amotivational effects of marijuana, determining its presence or absence (Foltin et al., 1989, 1990).

Alcohol and Sedatives

The majority of studies evaluating acute effects of alcohol administration have found that single doses cause decrements in a variety of performance tasks, particularly tracking, visual vigilance, divided attention, postural stability, and cancellation tasks, with less robust effects on memory tasks. Since the problems that alcohol use poses for transportation safety are well recognized, it has received substantial attention from the transportation research community. As with other laboratory studies, the magnitude of impairment in transportation-related tasks has been shown to be dependent on the nature of the task, research subject characteristics (e.g., skill level, tolerance) and environmental factors (e.g., fatigue). Overlearned tasks (e.g., coordination, balance) are relatively resistant to alcohol consumption (Burns, 1992), while divided attention, information processing, and attention processes are highly susceptible to alcohol-induced impairment (Streufert et al., 1992). Performance on these latter tasks are impaired at low blood alcohol levels, implying that relatively small amounts of alcohol can have detrimental consequences for both traffic safety as well as other workplace safety-sensitive positions. Although there is a relationship between blood alcohol level and decrements in performance, there is considerable variability in the alcohol level at which decrements occur. In addition, there is variability in the amount of alcohol required to reach a given blood alcohol level, even when body weight is controlled (O'Neil et al., 1983). This source of variability is largely related to variations in metabolic rate. Furthermore, although the data are not as clear for all the benzodiazepines, data with prototypic benzodiazepines (diazepam, lorazepam, and triazolam) suggest that, as with alcohol, these drugs produce decrements on a full range of performance tasks, from gross motor tasks such as postural stability (Evans et al., 1990) to complex tasks such as divided attention (Erwin et al., 1986).

Residual Drug Effects

Although residual effects can refer to any effects that occur a number of hours after major drug effects have dissipated, this has come to mean next-day effects or hangover effects . The issue here is whether substances used at home on one day affect job performance the next day. These effects can either be manifested as prolonged drug effects, similar to the initial drug effect, or can differ from the initial drug effect. This latter change in behavior is best characterized by what is commonly called hangover. Thus, alcohol consumed during the evening can produce intoxication, slurred speech, etc. Six or eight hours later, after some sleep and no further alcohol intake, a different set of symptoms (e.g., headache, irritability, inability to concentrate, etc.) might be apparent. Such hangover effects can be disruptive in the workplace, reducing productivity and perhaps interfering with safe and accurate performance and/or social interactions. In addition, it is possible that hangover or drug withdrawal effects are contributing factors in the maintenance of drug-seeking behavior.

In addressing the issue of residual drug effects, we have to differentiate between chronic, regular, daily drug use and acute, or occasional, drug use. Repeated drug use can result in tolerance to some of the effects of the drug. When tolerance develops, it takes a larger dose of the drug to achieve the same effect. The development of tolerance does not by itself affect workplace performance, although it can moderate what would otherwise be the effects of drug-taking behavior or allow greater consumption of a drug than would otherwise occur. The aspect of chronic drug use that can affect workplace performance adversely is the development of dependence. Physical dependence is manifested as a syndrome of effects that appear upon abrupt cessation of a drug after chronic use and can be alleviated by intake of that drug. The most widely described drug dependence is probably for the opiates, as seen with chronic heroin use. Comparable dependence is seen with many if not all classes of psychotropic drugs.

The data on the development of dependence to alcohol, sedatives, and opiates are clear. Repeated and regular intake of these substances has been shown to result in physical dependence, manifested by a replicable withdrawal syndrome that can be alleviated by the administration of the substance that the individual has been taking. The data for marijuana are less clear. A number of laboratory studies have been carried out in which research subjects were given marijuana cigarettes to smoke, or δ 9 -THC to consume, repeatedly for 10-30 days. In general, both tolerance to many of marijuana's effects and dependence are seen (Jones and Benowitz, 1976; Mendelson et al., 1976). Withdrawal is manifested as irritability, restlessness, decreased appetite, tremor, etc., and has been described (Jones, 1978) as a clinical picture similar to that seen after withdrawal of the sedative-hypnotics. It is possible that the maintenance of stable THC blood levels is important for the development of dependence, and that cessation of use could result in a withdrawal syndrome with workplace consequences.

Residual effects of occasional marijuana use appear slight if they exist at all. Some researchers searching for hangover effects recount subjective reports of feeling "spacey" or "stoned" or "hung over'' the next day (Cousens and DiMascio, 1973). The few objective measures that purport to show decrements attributable to the consumption of marijuana a day earlier are suggestive at best (Yesavage et al., 1985; Leirer et al., 1991). Thus, we cannot at this time conclude that the occasional use of marijuana will have measurable next-day residual effects, nor can we conclude that some subtle effects are not present.

Accuracy in identifying small amounts of cannabis metabolites in urine is excellent. This means that even occasional use of marijuana is often picked up in urine screens taken in relation to an accident or other workplace problems. We cannot, however, on the basis of the available data, assign particular behavioral consequences to the presence of these metabolites in the urine. Thus, when post-accident drug screening reveals that a responsible person tested positive for marijuana, it does not mean that marijuana use played a causal role in the incident.

Alcohol hangover effects can apparently degrade performance. They have been reported to impair drivers' and pilots' performance (Laurell and Tornros, 1983; Yesavage and Leirer, 1986), although the extent of the impairment was in part related to both age and experience with the task. For example, performance of older pilots was more impaired than that of younger pilots, but the older pilots were more aware of their impairment for up to 4 hours after reaching peak blood alcohol levels.

There are no data on the residual effects of occasional stimulant use except for fatigue related to secondary sleep deprivation. When stimulants are used repeatedly in binges, a "crash," marked by irritability, hypersomnolence, and some depression can occur (Fischman, 1987). This constellation of next-day effects, however, has not been linked to specific performance changes, and it may be that the effects do not differ from decrements measured after sleep deprivation in the absence of drug use.

Methodological Issues

Where laboratory conditions are different from the conditions that characterize actual drug use, drug users, and job performance, there is a question of how far one can generalize from laboratory results to predict the actual implications of drug use that are of interest (Berkowitz and Donnerstein, 1982; Dipboye and Flanahan, 1979; Locke, 1986; Sears, 1986; Sackett and Larson, 1991). This is the external validity problem. Not all differences between the laboratory and the outside world pose serious threats to external validity. This depends on whether there is reason to believe the differences are consequential for the generalizations one would like to make. Unfortunately, in assessing the research done to date on the performance implications of drug use, many of the differences between the currently available laboratory studies and drug use outside the laboratory appear large and potentially important. Often, however, these differences, or at least the size of these differences, are not inherent in the laboratory methodology. Thus identifying important differences not only highlights the limitations of extant research, but it also suggests ways in which future studies can be improved.

The failure to examine combinations of drugs constitutes a major gap in the research on drugs' effects on performance. It is becoming increasingly rare to find a single-drug-class abuser (or even drug user). Polydrug use is generally the norm, and this is particularly the case for alcohol. Many substances, such as marijuana, nicotine, and sedatives, are frequently taken in combination with alcohol, and the effects of these combinations are generally unknown. It has recently been reported that the combined intake of cocaine and alcohol results in formation of a metabolite, cocaethylene, which has a half-life of more than 2 hours, and is considerably more toxic than either drug alone (Hearn et al., 1992; Perez-Reyes and Jeffcoat, 1992). Although not yet studied, it is possible that this active metabolite could result in behavioral changes long after measurable cocaine or alcohol levels are present in the body. Other combinations of drugs may have effects that are different from or longer lasting than the effects of the drugs taken singly.

Research on the performance implications of drug use must also consider carefully the experimental population. There are several research objectives to be met in determining an appropriate research subject population. Initial research studies evaluating a specific substance or a specific task should be carried out in a single well-studied population in which multiple variables can be controlled, motivational variables can be either manipulated or controlled, and basic mechanisms can be addressed. This approach exemplifies much of the research summarized above. Subjects in these studies were generally male college or graduate students. Unfortunately, few studies move on to the next phase of research in which issues of generalizability and predictability are addressed. It is difficult to know how generalizable data from the population of male college or graduate students, tested individually and in isolation, are to the general work force. On one hand, students, who are younger than much of the work force, have commonly learned to perform under less than optimal conditions, often taking tests under conditions of sleep deprivation and substantial stress. On the other hand, student subjects may seldom or never have used the drugs administered, and unlike the occasional or regular user, they may not have learned how to function productively under the influence of the drug. In addition, laboratory performance tests are often novel, with minimal opportunity for practice prior to testing. Members of the work force are generally performing well-learned tasks in familiar, more social environments, with familiar cues designed to enhance performance as the working environment undergoes minor modifications (e.g., illumination changes, personnel changes).

Much of the research being carried out on the effects of psychoactive substances on performance has not been designed with the "at risk" population in mind. For example, at least 20 percent of truck drivers are said to drive under the influence of marijuana, methamphetamine, or cocaine (Beilock, 1988). Yet little research on the effects of these drugs has the specific situations of truck drivers in mind. Prescribed medications (e.g., benzodiazepines) may well impair performance, yet few studies evaluating them in the populations most likely to need them have been carried out. Epidemiologic studies are necessary to help define the populations at risk, the substances most generally used, and the environments in which they are most likely to be used. Data from such statistics can then feed into laboratory research.

As we have already noted, few performance studies model drug use outside the laboratory. With many drugs, it is rare for a user to take a single dose each day. Stimulants such as cocaine, for example, are taken repeatedly, in binges, for several hours or days at a time (Johanson and Fischman, 1989). Under these conditions, it is likely that tolerance will develop to some of the effects of the drug, although dosing can escalate to substantial levels. Thus, the single doses often administered in research settings do not accurately reflect, in either pattern or number, those taken by habitual or even occasional users.

Many of the studies evaluating the effects of single doses of drugs on laboratory performance employ contingencies for correct or efficient performance. Points exchangeable for money, for example, are awarded when tasks are completed according to instructions. In the workplace there may be eventual contingencies (e.g., firing for those whose performance is habitually substandard), but there is rarely a performance monitor providing performance feedback on a minute-by-minute basis. This difference also undercuts the generalizability of the data from laboratory to workplace.

Perhaps the most important effect missed in most laboratory performance studies is the interaction of the drug taken with the behavior of the user and others in the environment (i.e., laboratory studies do not involve a social environment). Although drugs have pharmacological effects that at high doses can be substantial, the effects of using a drug often depend on what else is going on in the environment and the feedback given to the individual performing under the effect of the drug. For this reason, studies that emulate workplace conditions can more accurately assess drug effects than those that do not. In an interesting series of experiments, Kelly and colleagues have examined the behavioral profiles associated with using marijuana (Kelly et al., 1990), amphetamines (Kelly et al., 1991), and diazepam (Kelly et al., 1993). Healthy volunteers resided continuously in a laboratory designed for the long-term unobtrusive measurement of human behavior (Brady et al., 1974). The laboratory day was designed to emulate a normal day, with subjects working in their private rooms from about 9:00 a.m. to 5:00 p.m., followed by a social activities period when subjects had access to other subjects and a common social/exercise space. Data were collected simultaneously on a wide range of behaviors under naturalistic living conditions: performance, social behavior, food intake, cigarette smoking, and subjective effects. By comparing drug effects across multiple dimensions of human behavior, it was possible to ascertain a behavioral profile of each drug's action. In addition, this design addresses the risk factors discussed in the introduction of this section and narrows the gap between laboratory studies and the workplace. By using a social setting, distracting events, extensive training with weeks of practice, and a sample of nonstudents, this study comes closer to simulating the workplace and living conditions associated with ordinary drug use than the studies we have discussed thus far.

Kelly and his colleagues found that smoking marijuana cigarettes decreased accuracy on a digit symbol substitution task (DSST), increased food intake, and decreased verbal interaction and tobacco cigarette smoking (Kelly et al., 1990). When comparing the relative potency of marijuana across these measures, it was clear that DSST performance, food intake, and social behavior were all altered at doses that had no effects on task performance other than the DSST. This suggests that THC doses that affect performance are equal to, if not greater, than doses that affect social and eating behavior.

Oral amphetamine administration decreased food intake, improved accuracy on some work tasks, and increased verbal interaction, cigarette smoking, and verbal ratings of drug effect (Kelly et al., 1991). The relative potency comparisons, in this case, suggested that the doses that were affecting performance also had significant effects on other dimensions of human behavior. Oral diazepam administration, in contrast, increased verbal interaction at low doses and decreased verbal interaction at high doses, disrupted only one measure of task performance, increased food intake at one or both doses, and increased verbal ratings of drug effect (Kelly et al., 1993). The relative potency comparisons in this experiment suggested that diazepam at clinical doses disrupted dimensions of human performance, other than task performance.

The Kelly et al. experiments clearly indicate the utility of multiple measures in studying the performance effects of drugs. The unique aspect of these experiments is that measures of normal social and eating behavior were obtained, providing a source of potency comparisons involving normal nonlaboratory-dependent behavior. The findings suggest that, at least for diazepam and marijuana, experiments that measure only task performance may miss the effects that particular drug doses have on other behaviors. Where significant performance effects are found, other significant changes in behavior are also likely. The use of multiple dependent measures in performance experiments will make it easier to put into the context the changes in performance observed in laboratory experiments.

Measures of the subjective effects of test drugs can also provide essential information about the effectiveness of the dose range being studied. For example, in an experiment on the effects of buspirone on performance, Critchfield and Griffiths (1991) did not observe any performance effects of a high buspirone dose (four to five times the therapeutic dose) in sedative users, but did observe significant ratings of "bad drug effect." Without the self-report data, there would have been no verification that an effective dose range was being tested. Visual analog scales, often used in the assessment of momentary changes in affect (Folstein and Luria, 1973), require little effort, represent minimal intrusion on existing protocols, and can be incorporated readily into most laboratory procedures.

• Limits And Realities Of Laboratory Studies

There are no studies that provide direct estimates of the effects of drug use on job performance or on behavior in organizations. As is often the case with research in the social and behavioral sciences and in medicine, ethical constraints make it impossible to conduct definitive controlled studies of the long-term effects of drug use at work. Rather, it is necessary to infer the impact of drug use at work from a variety of studies conducted in the laboratory and the field. Laboratory studies provide evidence regarding the effects of controlled, short-term exposure to specific drugs on the performance of specific tasks. Field studies provide evidence regarding the links between drug use (either self-reported or detected through other means) and a number of work behaviors, but they lack the controls needed to allow researchers to isolate specific drug effects.

Difficulties in generalizing from behavioral research are by no means unique to research on the impact of drugs in the workplace; these same issues emerge in virtually any area of research that involves human behavior. It is therefore important to keep an appropriate perspective in discussing the methodological limitations of research on drugs and work. Nevertheless, it is important to note at the outset that these difficulties are an important reason why the existing research base does not demonstrate conclusively that the effects of drug use on the work force are either large or small. The challenge is to overcome them.

One way to appraise the generalizability of any specific set of laboratory findings is through a risk factors model, in which each of the potentially important differences between the laboratory and the work setting is treated as a factor that is likely to limit the generalizability of laboratory research. The more risk factors that are present, the greater the likelihood that the effects of the drug examined will be different in the lab than in the field. Table 4.2 lists several risk factors, some of which have already been mentioned, that commonly threaten the external validity of laboratory studies relating drug usage to task performance.

Features of Typical Laboratory Studies that Differ from the Workplace.

It is common in the workplace to distinguish between tests of maximal performance and tests of typical performance. In laboratory settings, in which subjects are under scrutiny, people are often motivated to perform well and are able to perform with few distractions. Thus, they are likely to demonstrate maximal performance. In work settings, in which people are not under the same level of scrutiny, their typical performance is not likely to be as high or as consistent. The typical-maximal performance distinction is particularly important for studying the effects of drugs that affect attention, fatigue, and vigilance. Subjects may make special efforts to overcome the effects of these drugs in laboratory settings, which they would not make in work settings. The incorporation of distractions (e.g., multiple attention tasks) in laboratory studies is one way to address this issue.

Laboratory studies often present unfamiliar or novel tasks that require constant attention and monitoring. In contrast, many work tasks are overlearned, and individuals may perform those tasks in an automatic processing mode after extensive training and practice. Also, as already pointed out, laboratory studies often employ novice subjects (e.g., college students), whereas in the workplace most workers are relatively experienced with the tasks that need to be performed. Laboratory studies should include overlearned (i.e., highly practiced) tasks as well as novel tasks.

Laboratory studies often require subjects to perform in isolation, whereas job performance is usually carried out in a social setting. The effects of the presence of other workers on performance are themselves complex (e.g., social facilitation effects can enhance performance, whereas distraction can detract from performance); when jobs involve social interactions and interdependencies, the generalizability of studies in which subjects work alone can be especially hazardous. The addition of studies carried out in social settings could address this issue.

Laboratory studies often involve a single, relatively simple task (e.g., a reaction time task), whereas job performance often involves multiple, complex tasks. Furthermore, the evaluation of performance in the laboratory is often considerably simpler than in the field. That is, the standards that define good performance are often clear and well understood in the laboratory, but the same is not always the case in work settings. What is defined as poor performance in a work setting may not be the result of impairment, but rather the effect of disagreement over the definition of adequate performance.

Laboratory studies often employ convenience samples (e.g., college students, military pilots), which tend to be homogeneous. This may cause those studies to underestimate the importance of individual differences, as well as differences in training and experience when generalizing to the workplace. Similarly, the exposure of subjects to drugs in laboratory experiments is usually carefully controlled (e.g., fixed doses of specific drugs taken in specific settings), whereas in the workplace there may be extensive variation in patterns and levels of drug use, including different configurations of polydrug use. Studies using experienced drug users with variations in drug use history as subjects may be useful in this regard; polydrug configurations must be tested.

Finally, laboratory studies are usually limited in scope, and subjects often know the approximate time span of the study. It may be easier to maintain maximal performance levels, or to adopt strategies to mitigate the effects of drugs on performance, in tasks whose duration is known (and is short) than it is over the course of a typical workday. Experimental sessions extending over the course of a workday, or at least for several hours, are more likely to capture drug effects than those of shorter duration.

As in all applications of risk factor approaches, a simple count of the factors that are present or absent in a given study does not necessarily determine its external validity. What is crucial is the plausibility of the threats posed by specific factors in the context of the given research. Indeed, it is possible that a study might exhibit all the potential barriers to generalizability shown in Table 4.2 and still produce generalizable results (e.g., effect of cyanide on performance using animals as subjects). The risk factor approach does provide a rough and probabilistic statement about generalizability; the more factors that are present, the less likely that laboratory results will replicate exactly in the field. It is particularly useful for evaluating the existing body of research on drug effects as a whole; the prevalence of studies that share almost all listed risk factors is disheartening. We reiterate, however, that this is not inherent in the laboratory methodology, as some researchers have shown.

• General Findings

Perhaps the most obvious finding of this survey of the literature on performance effects is the lack of consistent and significant effects. While sufficient amounts of almost any substance will have a deleterious effect on work force behavior, this is not the issue. The question is whether alcohol and other drugs of abuse, taken in the doses and patterns that people are using, either occasionally or regularly have detrimental effects on behavior, particularly workplace performance The literature suggests that, in single doses and under laboratory conditions, stimulant drugs (caffeine, cocaine, methylphenidate, amphetamine and nicotine) either have no effect or they moderately improve performance. Smoking marijuana seems to have variable effects, with inconsistent decrements on performance. Sedative drugs (alcohol, benzodiazepines, barbiturates) generally disrupt performance. There are large differences across experiments and drugs in terms of experimental design, and the proportion of experiments reporting significant drug effects varies widely across tasks and drugs. The extent to which this variation is due to task methodology rather than dose needs investigation. Information gained from such research will also help identify factors that can moderate, as well as accentuate, drug-induced effects on performance.

Given the variability in tasks and procedures, the fact that, at certain doses, drugs affected performance in 40 to 80 percent of the experiments reviewed by the committee indicates that this field, though experimentally mature, requires additional research rooted in more careful attention to methodology. Although an impressive array of tasks has been used in the research to date, experimental protocols have rarely been similar across studies. Suggestions for future protocols include use of control groups, training subjects prior to participation, testing of more than one dose, testing for drug combinations, and testing of performance before and several times after drug administration. A greater range of subject populations beyond the student population should also be sampled. Task standardization, including instructions to subjects, duration of performance, feedback to subjects, motivational conditions, and details of presentation should be maximized across studies at least in some conditions, to provide a common metric for comparison.

The relevance of tasks performed in the laboratory to tasks performed in the workplace is often not clear, and even when there is a plausible link, it has seldom been demonstrated. Clearly it is not possible to model every type of performance by the work force. And yet it should be possible to differentiate several functional categories of tasks to be studied. For example, acquisition of new behavior (i.e., learning) and stable performance of practiced tasks might be differentiated and both aspects modeled in testing. It would be useful for future research designs in which new tasks are being developed to include one or two standardized benchmark tasks for comparison of drug effects across studies. This would provide the systematic replication necessary to generalize across studies. Reliability across tasks could then be evaluated, and importantly, predictive validity could be assessed.

The relationship between drug doses that affect performance and doses that are used clinically, or self-administered for nonmedical purposes, determines the effects of drugs on work force performance. The greater the extent of the overlap between these dose ranges, the greater the potential hazards to both the drug user and society. Therefore, it is important that research in this area incorporate usage information collected in epidemiologic or other laboratory studies so that we can optimize the utility of the data being collected in performance testing for predicting decrements in workplace performance. Future research, using more standardized protocols and tasks with broad subject populations, should address the varied issues relating to public safety and the creation of work and home environments that minimize potential adverse drug effects.

In sum, laboratory research has the potential for providing valuable information about the relationship between alcohol and other drug use, social behavior, and job performance. To date, despite some research designs that are abstractly elegant, that potential has hardly been tapped. Recognizing the important contribution laboratory research can make to improving our understanding of the impact of individual alcohol and other drug use on work performance, and after having carefully reviewed the current scientific knowledge base, the committee offers the following conclusions and recommendations.

• Conclusions And Recommendations

• Laboratory studies of the effects of alcohol and other drugs on behavior have shown inconsistent results. These differences may be due, in part, to differences in the populations tested, the measurements used, and the range of drug doses administered.

Recommendation: Benchmark measures should be included in laboratory studies to permit generalization across studies. Funding agencies should consider holding conferences to establish such benchmarks.

Laboratory studies show small performance-enhancing effects of commonly used doses of cocaine and other stimulants. Commonly used doses of marijuana produce variable decrements in performance. Alcohol and prescribed sedatives produce decreases in performance depending on the dose, time of consumption, and the time-course of circulating concentrations of the drug's active metabolites, relative to the work schedule. All drug effects are influenced by dose and prior experience. The age of individuals and the presence of other drugs may also mediate the influence of particular drugs.

• The use of alcohol and other drugs away from the work site, including prescription drugs and over-the-counter medication, may have detrimental effects during work, especially for those in safety-sensitive positions. Thus, a long-acting drug taken the night before work or alcohol taken at lunch away from the job may have on-the-job effects like those of drugs taken at the work site. In addition, cessation of drug use may produce either withdrawal or hangover effects that affect work site performance. To date there has been little research directed toward any of these issues.

Recommendation: Researchers and funding agencies should devote more attention to the ways in which prescription and over-the-counter medications affect job performance, especially for safety-sensitive positions.

Recommendation: Studies of work site alcohol and other drug use should encompass off-site use that may have on-the-job effects. Hangover and withdrawal effects should also be considered in assessing the workplace implications of alcohol and other drug use.

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This discussion is based on a review, for the National Research Council, of approximately 250 papers by Foltin and Evans (1992). The studies included were published between 1970 and 1991 and involved healthy volunteers tested using laboratory tasks and given single doses of stimulant, sedative-hypnotic, alcohol, or marijuana. A shorter version of that review has recently been published by the Journal of Human Psychopharmacology (see Foltin and Evans, 1993). Review of the 250 papers yielded data on 305 tasks, only 118 of which were used in more than one experiment. For simplicity of discussion, tasks were grouped into general categories and only general behavioral effects are discussed.

• Cite this Page National Research Council (US) and Institute of Medicine (US) Committee on Drug Use in the Workplace; Normand J, Lempert RO, O'Brien CP, editors. Under the Influence? Drugs and the American Work Force. Washington (DC): National Academies Press (US); 1994. 4, Impact of Alcohol and Other Drug Use: Laboratory Studies.
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