Every month the Reddit community of /r/dataisbeautiful holds a “DataVis Battle” where they provide a dataset for users to visualize. This month the dataset was titled “Drug harm and dependence”.

The dataset included a list of 20 drugs with a measure of risk for the physical harm, dependence, and social harm associated with each drug. The risk assessment used nine parameters outlined by the British Advisory Council on the Misuse of Drugs.

I plan to explore the dataset in terms of the British drug classification system.

---

About the classification system:

• Class A drugs deemed the most harmful and class C the least

• NC: Not Controlled

• The drug classifications used here are current as of February 2019.

The nine parameters used by the Advisory Council to rank the drugs are broken down into three factors:

• Physical Harm:
  • Acute pain, chronic pain, and intravenous harm
• Depedence:
  • Physical, psychological, and the intensity of pleasure
• Social Harm:
  • Intoxication, associated health care costs, and other social harms

Each drug was given a score between 0-3 (no risk - extreme risk) on each of the nine parameters.

---

Visualization Choice:

The risk of each drug is displayed as a combination of a dynamite and dot plot. The dynamite plot provides a simple way to display the mean risk and classification of each drug. The dot plot gives us more information on the spread of the parameters within each drug.

Trends/Observations:

• The classification system appears to have little order in terms of the mean risk.

• Ecstasy, LSD and 4-MTA occupy a Class A designation though they are ranked lower on the risk scale.

• Uncontrolled substances penetrate higher on the scale

• Several substances (Tobacco, 4-MTA) show a high variability in risk between the parameters suggesting that perhaps using the overall mean score is not the ideal method to assess the risk of a given drug. Perhaps a weighted parameter scale would be better at assessing “riskier” drugs.

With that in mind, lets see how the classifications hold up within each harm parameter.

---

Visualization Choice:

A boxplot was chosen for this visualization as I wanted to get a feel of the range of risk within each classification.

Trends/Observations:

• The existing classifications hold up best in the parameter of acute pain and psychological dependence.

• With the exception of intravenous use, the not controlled substances tend to have higher risk scores than class C and in some instances class B drugs.

• There is alot of variability within the class A distinction.

---

Final Thoughts

• Overall it seems the current classification system is not synonymous with the risk assessment in terms of the mean risk scores or individual parameters.