This is a version of a blog I published a few years ago, but thought it still relevant today.
Doug Sellman is a professor of psychiatry and addiction medicine in New Zealand. In 2010 in the journal Addiction, he attempted the difficult task of distilling the ten things you need to know about addiction from the research of the last thirty years. No mean feat.
Well, what are they?
1. Addiction is fundamentally about compulsive behaviour. In normal behaviours, the control in our brains is top down. In addiction the cortex (the decision making bit of the brain) becomes ‘eroded’ to a ‘dehumanised’ compulsion. Sellman outlines the well-studied brain circuits involved, and points out how this view creates one of the defining marks of addiction: continuing to use despite negative consequences.
2. Compulsive drug seeking starts outside conscious thought. The debate about free will (and as the prof says ‘free won’t’) gets complicated here. Apparently the conscious part of our brain is about a half second behind imprinted learned behaviours. The lag and its effects are exaggerated in addiction and well learned patterns including cues call the shots over the ‘higher’ brain’s ability to avoid damaging choices. Result: illogical self-harming behaviours continue.
3. Addiction is about 50% inherited, but it’s much more complicated. Genetic and population studies show a strong genetic element for addiction with some folk being more vulnerable than others. It gets complicated because it’s not just about a single gene or even a few, but possibly hundreds, and even then they interact with infinite variations in environment. This is not about ‘nature versus nurture’, but represents a ‘new interactive model of nature via nurture’.
4. Most people with addictions who come for help have other psychiatric problems as well. For those wanting to move away from the medically dominated model of treatment, this is a big obstacle. 75-90% of those asking for help from services have diagnosable mental health problems including depression, social phobia and post traumatic stress disorder. Alarmingly though, many of our big treatment studies have excluded people suffering from mental health problems. For those of us involved in providing help for those wanting to recover, we will need to ensure that mental health needs are not overlooked. On a personal note though: I do hold a hopefully healthy observation that many of the psychiatric labels we pick up as active addicts melt away in recovery without the need for psychiatric treatment.
5. Addiction is a chronic relapsing disorder in the majority. This was the most challenging of the ten findings for me to simply accept. Prof Sellman says that fewer than 10% of those going through treatment will experience continuous long-term abstinent recovery. He does point out that life will be better for many after treatment and that we need to accept relapse as part of the deal for many. Not doing so will prevent folk coming back for help. There is a tension in this for me between instilling hope and optimism and being unrealistically positive. Other research gives more hope for longer term outcomes suggesting more than half will achieve remission.
Coming soon: Part 2
3 thoughts on “The ten most important things about addiction (part 1)”
Addiction is multi-factorial. As such a statistical factor analysis could be performed if the data were available. Hopefully one day someone get the PhD funding for it.
“Confirmatory factor analysis (CFA)
In psychology we make observations, but we’re often interested in hypothetical constructs, e.g. Anxiety, working memory. We can’t measure these directly, but we assume that our observations are related to these constructs in some way.
Regression and related techniques (e.g. Anova) require us to assume that our outcome variables are good indices of these underlying constructs, and that our predictor variables are measured without any error.
When outcomes are straightforward observed variables like plant yield or weight reduction, and where predictors are experimentally manipulated, then these assumptions are reasonable. However in many applied fields these are not reasonable assumptions to make: For example, to assume that depression or working memory are indexed in a straightforward way by responses to a depression questionnaire or performance on a laboratory task is naive. Likewise, we should not assume that a construct like working memory is measured without error when we use it to predict some other outcome (e.g. exam success).
Confirmatory factor analysis (CFA), structural equation models (SEM) and related techniques are designed to help researchers deal with these imperfections in our observations, and can help to explore the correspondence between our measures and the underlying constructs of interest.”
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