Issues in Interdisciplinarity 2019-20/Evidence in Addiction

Introduction edit

We define addiction as a persistent compulsive need for a substance or an activity that, in the long term, is detrimental to an individual's quality of life. Addiction is a complex topic which has created much controversy over its meaning, effects and treatment methods. This has yielded various research from different disciplines: Neuroscience, Psychology and Economics. Due to different methodologies, sources, intent and data, evidence has created tensions between the disciplines. However, when combined, they facilitate a more holistic understanding of the cause, nature and effect of addiction and therefore make useful contributions to governments' decision making to decrease the harm caused.

Evidence in Neuroscience edit

Brain imaging technologies provide most of the evidence used in neuroscience to study addiction. Imaging shows which parts of the brain are activated during craving, satisfaction, and withdrawal. Imaging studies show that during satisfaction or craving, the prefrontal regions of the brain are activated in a pattern that involves sections of the brain associated with reward, motivation, memory, and cognitive control.[1] Imaging also shows that dopamine levels in the brain increase during craving and satisfaction and that this increase deregulates the prefrontal regions of the brain which causes a loss of rational behavior and compulsive drug intake.[2]

The main imaging technologies are positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). PET measures brain activity by detecting the radioactivity emitted by injected positron-emitting isotopes —regions with high radioactive activity are associated with brain activity. fMRI measures the brain activity by detecting the changes in blood oxidation —when a region of the brain is more active, it consumes more oxygen. Other imaging technologies include Computed tomography (CT), Electroencephalography (EEG), Magnetoencephalography (MEG) and Near infrared spectroscopy (NIRS).[3] However, there are limitations in the quantitative methods used in brain imaging. They do not seem to measure subjective emotions and perception.

Another source of evidence for the study addiction in neuroscience are animal models of substance use disorder. For example, a study in nonhuman primates showed how environmental factors affect neuronal circuits, in turn influencing addictive behavior. The study showed that social status, dominant or subordinate, affects dopamine receptors' expression in the brain, which then influences an individual's drug intake.[4] However is it rigorous to extrapolate results from primate testing to apply to humans, with more complex society and interactions?

Evidence in Economics edit

Economics traditionally assumes humans displaying fully informed autonomous rational behaviour, thus understanding addiction is problematic when building supply-demand models of consumption. Evidence for addiction is usually in the context of drugs, both legal and illegal, taken from real-world case studies where independent variables are already in place for experimental analysis.

There is still a lack of control variables, but these ‘natural experiments’ are valuable because they cannot easily be synthetically recreated, for example, economists cannot simply change the drinking age for selected groups of teenagers simply to study the result on behaviour.[5] An example of identifying causality from a real-world case study is where researchers Norstrom and Skog took advantage of a phase-in of retail alcohol sales in Sewden, and studied the link of this policy with crime rates.

Data studying crime rates is also used in cost-of-illness methodologies, which provide quantitative evidence of the financial costs generated by consumption of addictive substances. These encompass both direct costs, such as those of health-care and social services, as well as indirect costs such as premature mortality, early retirement and costs relating to crime.[6] Limitations in the cost-of-illness methodology include difficulties in making precise estimations, especially for the indirect costs.[6] Additionally, indirect costs do not consider qualititative data such as burden on family members.

Price elasticity models show the ratio of change in quantity consumed to change in price, giving a more precise idea of the behavior of consumers of addictive substances.[7] For example, Caulkin discusses studies focusing on specific groups of consumers, demonstrating that marijuana consumption of high school students in the U.S. was less responsive to price changes than that of Australian adults [7]. Nevertheless, looking at elasticity evidence as an average concerning figures for drugs, addicts are grouped in with recreational drug users, so the individual personal elasticities are skewed by non-addicted users.

Evidence in Psychology edit

Psychological methods for obtaining evidence include creating hypothetical yet functional models, for example, positive and negative reinforcement models,[8] based on controlled qualitative data provided by social experiments to identify patterns in human behavior for addiction. These experiments can be specific, measuring differing effects on individuals obtained through patient-practitioner interactions. Broader case studies are also used as evidence to support models. One study looked at treatment programs, finding that patients who had supportive and constructed relationships were more likely to benefit from the treatment, it showed a 41% variance and helps to support functional models.[9]

However, various data needs to be collected to continuously modify models.[10] For example, the positive and negative reinforcement model which is highly based on quantitative data from studies on alcoholism shows that addicts stay addicted to maintain the positive effects of the addiction and to avoid the negative side effects of withdrawal. Though this model is supported by studies done on alcohol addiction, it cannot explain why psychoactive drugs which do not have withdrawal effects can be highly addictive.

Combining Evidence in Government Intervention edit

An interdisciplinary approach is essential in government policy-making. Governments should have a holistic view of addiction, considering evidence used by different disciplines to reduce cost to society.

Government intervention to reduce addiction has included tax increase for addictive substances, marketing bans, raising awareness through education, and legislation such as imposing a minimum age to buy a substance.

Decisions tend to be based on evidence of past world events, much of which is provided by economic data. To create innovative ideas of combatting abuse of addictive substances, using prediction models such as those used in psychology is beneficial. Rather than designing policies which fix the results of drug overuse, governments can consider ways to combat addiction at the source, by considering both qualitative and quantitative evidence, as well as ‘natural’ and ‘hypothetical’ experimental data used by the different disciplines.

To incorporate neuroscientific evidence, governments could consider theories developed from studying brain scans, explaining causes of addiction. It can also help understanding addicts' decision making. In addition, when looking at aspects of psychology such as cognition, the evidence can be more ambiguous than is presented by neuroscience. This could support by keeping ideas concrete and potentially creating effective treatments that would work physically, but also find the root cause of addiction.

Furthermore, psychology can build on neuroscience by understanding how individuals’ particular environments are more vulnerable to addiction, or to relapse after treatment. This can consequently allow economists to understand the psychology of addiction when it considers real-world case study evidence to build policies. For example, Bernheim and Rangel [11] discuss a policy of subsidising rehabilitation centers and treatment programs, with evidence from psychology illustrating that addicts are in fact rational enough to understand their condition, yet environmental factors play a large role in fostering that addiction.

This short study of evidence in addiction shows how an interdisciplinary approach is crucial when using academic research to solve real world complex issues.

References edit

  1. Volkow N, Fowler J, Wang G. The addicted human brain: insights from imaging studies. Journal of Clinical Investigation [Internet]. 2003;111(10):1444-1451. Available from:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC155054/#__ffn_sectitle
  2. Volkow ND, e. (2019). Dopamine in drug abuse and addiction: results of imaging studies and treatment implications. - PubMed - NCBI. [online] Ncbi.nlm.nih.gov. Available at: https://www.ncbi.nlm.nih.gov/pubmed/17998440 [Accessed 8 Dec. 2019].
  3. Demitri, M. M.D. Types of Brain Imaging Techniques [Internet]. Psych Central. 2019 [cited 3 December 2019]. Available from: https://psychcentral.com/lib/types-of-brain-imaging-techniques/
  4. Volkow N, Fowler J, Wang G. The addicted human brain: insights from imaging studies. Journal of Clinical Investigation [Internet]. 2003;111(10):1444-1451. Available from:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC155054/#__ffn_sectitle
  5. Caulkins, J. and Nicosia, N. (2010). Addiction and Its Sciences: What economics can contribute to the addiction sciences. Addiction, [online] 105(7), pp.1156-1163. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896982/.
  6. a b Andlin-Sobocki, P. (2004). Economic evidence in addiction: a review. The European Journal of Health Economics, [online] 5(S1), pp.s5-s12. Available at: https://link-springer-com.libproxy.ucl.ac.uk/content/pdf/10.1007%2Fs10198-005-0282-5.pdf.
  7. a b Caulkins, J. and Nicosia, N. (2010). Addiction and Its Sciences: What economics can contribute to the addiction sciences. Addiction, [online] 105(7), pp.1156-1163. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896982/.
  8. Farber, P. D., Khavari, K. A., & Douglass, F. M. (1980). A factor analytic study of reasons for drinking: Empirical validation of positive and negative reinforcement dimensions. Journal of Consulting and Clinical Psychology, 48(6), 780–781.Available from: https://doi.org/10.1037/0022-006X.48.6.780.
  9. Gifford, E, Humphreys, K. The psychological science of addiction. Addiction. SSA. 2007. Volume 102 (issue 3): pages 352-361.Available from: https://doi.org/10.1111/j.1360-0443.2006.01706.x.
  10. Robinson, E.T, Berridge, K.C. the psychology and neurobiology of addiction: an incentive-sensitization view. Addiction. SSA. 2000. Volume 95 (issue 8s2): pages 91-117. Available from: https://doi.org/10.1046/j.1360-0443.95.8s2.19.x
  11. 1. Bernheim B, Rangel A. A New Economic View of Addiction [Internet]. 2005. Available from: https://www.rnl.caltech.edu/publications/pdf/SEPR06FromNeurotoPubPol.pdf