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Nutt DJ, King LA, Phillips LD. Drug harms in the UK: a multicriteria decision analysis. Lancet 376: 1558-1565

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Proper assessment of the harms caused by the misuse of drugs can inform policy makers in health, policing, and social care. We aimed to apply multicriteria decision analysis (MCDA) modelling to a range of drug harms in the UK. Members of the Independent Scientific Committee on Drugs, including two invited specialists, met in a 1-day interactive workshop to score 20 drugs on 16 criteria: nine related to the harms that a drug produces in the individual and seven to the harms to others. Drugs were scored out of 100 points, and the criteria were weighted to indicate their relative importance. MCDA modelling showed that heroin, crack cocaine, and metamfetamine were the most harmful drugs to individuals (part scores 34, 37, and 32, respectively), whereas alcohol, heroin, and crack cocaine were the most harmful to others (46, 21, and 17, respectively). Overall, alcohol was the most harmful drug (overall harm score 72), with heroin (55) and crack cocaine (54) in second and third places. These findings lend support to previous work assessing drug harms, and show how the improved scoring and weighting approach of MCDA increases the differentiation between the most and least harmful drugs. However, the findings correlate poorly with present UK drug classification, which is not based simply on considerations of harm. Centre for Crime and Justice Studies (UK).
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Articles
www.thelancet.com Published online November 1, 2010 DOI:10.1016/S0140-6736(10)61462-6
1
Published Online
November 1, 2010
DOI:10.1016/S0140-
6736(10)61462-6
See Online/Comment
DOI:10.1016/S0140-
6736(10)62000-4
Neuropsychopharmacology
Unit, Imperial College, London,
UK (Prof D J Nutt FMedSci); UK
Expert Adviser to the European
Monitoring Centre for Drugs
and Drug Addiction (EMCDDA),
Lisbon, Portugal (L A King PhD);
and Department of
Management, London School
of Economics and Political
Science, London, UK
(L D Phillips PhD)
Correspondence to:
Prof David J Nutt,
Neuropsychopharmacology Unit,
Imperial College London,
Burlington-Danes Building,
Hammersmith Hospital, Du Cane
Road, London W12 0NN, UK
d.nutt@imperial.ac.uk
Drug harms in the UK: a multicriteria decision analysis
David J Nutt, Leslie A King, Lawrence D Phillips, on behalf of the Independent Scientifi c Committee on Drugs
Summary
Background Proper assessment of the harms caused by the misuse of drugs can inform policy makers in health,
policing, and social care. We aimed to apply multicriteria decision analysis (MCDA) modelling to a range of drug
harms in the UK.
Method Members of the Independent Scientifi c Committee on Drugs, including two invited specialists, met in a
1-day interactive workshop to score 20 drugs on 16 criteria: nine related to the harms that a drug produces in the
individual and seven to the harms to others. Drugs were scored out of 100 points, and the criteria were weighted to
indicate their relative importance.
Findings MCDA modelling showed that heroin, crack cocaine, and metamfetamine were the most harmful drugs to
individuals (part scores 34, 37, and 32, respectively), whereas alcohol, heroin, and crack cocaine were the most harmful
to others (46, 21, and 17, respectively). Overall, alcohol was the most harmful drug (overall harm score 72), with
heroin (55) and crack cocaine (54) in second and third places.
Interpretation These fi
ndings lend support to previous work assessing drug harms, and show how the improved scoring
and weighting approach of MCDA increases the diff erentiation between the most and least harmful drugs. However, the
ndings correlate poorly with present UK drug classifi cation, which is not based simply on considerations of harm.
Funding Centre for Crime and Justice Studies (UK).
Introduction
Drugs including alcohol and tobacco products are a major
cause of harms to individuals and society. For this reason,
some drugs are scheduled under the United Nations 1961
Single Convention on Narcotic Drugs and the 1971
Convention on Psychotropic Substances. These controls
are represented in UK domestic legislation by the 1971
Misuse of Drugs Act (as amended). Other drugs, notably
alcohol and tobacco, are regulated by taxation, sales, and
restrictions on the age of purchase. Newly available drugs
such as mephedrone (4-methylmethcathinone) have
recently been made illegal in the UK on the basis of
concerns about their harms, and the law on other drugs,
particularly cannabis, has been toughened because of
similar concerns.
To provide better guidance to policy makers in health,
policing, and social care, the harms that drugs cause
need to be properly assessed. This task is not easy because
of the wide range of ways in which drugs can cause harm.
An attempt to do this assessment engaged experts to
score each drug according to nine criteria of harm,
ranging from the intrinsic harms of the drugs to social
and health-care costs.1 This analysis provoked major
interest and public debate, although it raised concerns
about the choice of the nine criteria and the absence of
any diff erential weighting of them.2
To rectify these drawbacks we undertook a review of
drug harms with the multicriteria decision analysis
(MCDA) approach.3 This technology has been used
successfully to lend support to decision makers facing
complex issues characterised by many, confl icting
objectives—eg, appraisal of policies for disposal of
nuclear waste.4 In June, 2010, we developed the
multicriteria model during a decision conference,5 which
is a facilitated workshop attended by key players, experts,
and specialists who work together to create the model
and provide the data and judgment inputs.
Methods
Study design
The analysis was undertaken in a two-stage process. The
choice of harm criteria was made during a special
meeting in 2009 of the UK Advisory Council on the
Misuse of Drugs (ACMD), which was convened for this
purpose. At this meeting, from fi rst principles and with
the MCDA approach, members identifi ed 16 harm
criteria (fi gure 1). Nine relate to the harms that a drug
produces in the individual and seven to the harms to
others both in the UK and overseas. These harms are
clustered into fi ve subgroups representing physical,
psychological, and social harms. The extent of individual
harm is shown by the criteria listed as to users, whereas
most criteria listed as to others take account indirectly of
the numbers of users. An ACMD report explains the
process of developing this model.6
In June, 2010, a meeting under the auspices of the
Independent Scientifi c Committee on Drugs (ISCD)—a
new organisation of drug experts independent of
government interference—was convened to develop the
MCDA model and assess scores for 20 representative
drugs that are relevant to the UK and which span the
range of potential harms and extent of use. The expert
group was formed from the ISCD expert committee plus
two external experts with specialist knowledge of legal
For more on the Independent
Scientifi c Committee on Drugs
see: http://www.drugscience.
org.uk
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www.thelancet.com Published online November 1, 2010 DOI:10.1016/S0140-6736(10)61462-6
highs (webappendix). Their experience was extensive,
spanning both personal and social aspects of drug harm,
and many had substantial research expertise in addiction.
All provided independent advice and no confl icts of
interest were declared. The meeting’s facilitator was an
independent specialist in decision analysis modelling.
He applied methods and techniques that enable groups
to work eff ectively as a team, enhancing their capability
to perform,7 thereby improving the accuracy of individual
judgments. The group scored each drug on each harm
criterion in an open discussion and then assessed the
relative importance of the criteria within each cluster and
across clusters. They also reviewed the criteria and the
defi nitions developed by the ACMD. This method
resulted in a common unit of harm across all the criteria,
from which a new analysis of relative drugs harms was
achieved. Very slight revisions of the defi nitions were
adopted, and panel 1 shows the fi nal version.
Scoring of the drugs on the criteria
Drugs were scored with points out of 100, with
100 assigned to the most harmful drug on a specifi c
criterion. Zero indicated no harm. Weighting sub-
sequently compares the drugs that scored 100 across all
the criteria, thereby expressing the judgment that some
drugs scoring 100 are more harmful than others.
In scaling of the drugs, care is needed to ensure that
each successive point on the scale represents equal
increments of harm. Thus, if a drug is scored at 50, then it
should be half as harmful as the drug that scored 100.
Because zero represents no harm, this scale can be
regarded as a ratio scale, which helps with interpretation of
weighted averages of several scales. The group scored the
drugs on all the criteria during the decision conference.
Consistency checking is an essential part of proper
scoring, since it helps to minimise bias in the scores and
encourages realism in scoring. Even more important is
the discussion of the group, since scores are often changed
from those originally suggested as participants share their
diff erent experiences and revise their views. Both during
scoring and after all drugs have been scored on a criterion,
it is important to look at the relativities of the scores to see
whether there are any obvious discrepancies.
Weighting of the criteria
Some criteria are more important expressions of harm
than are others. More precision is needed, within the
context of MCDA, to enable the assessment of weights on
the criteria. To ensure that assessed weights are meaningful,
the concept of swing weighting is applied. The purpose of
weighting in MCDA is to ensure that the units of harm on
the diff erent preference scales are equivalent, thus enabling
weighted scores to be compared and combined across the
criteria. Weights are, essentially, scale factors.
MCDA distinguishes between facts and value
judgments about the facts. On the one hand, harm
expresses a level of damage. Value, on the other hand,
indicates how much that level of damage matters in a
particular context. Because context can aff ect assess-
ments of value, one set of criterion weights for a
particular context might not be satisfactory for decision
making in another context. It follows then, that two
stages have to be considered. First, the added harm
going from no harm to the level of harm represented by
a score of 100 should be considered—ie, a straight-
forward assessment of a diff erence in harm. The next
step is to think about how much that diff erence in harm
matters in a specifi c context. The question posed to the
group in comparing the swing in harm from 0 to 100 on
one scale with the swing from 0 to 100 on another scale
was: “How big is the diff erence in harm and how much
do you care about that diff erence?”
During the decision conference participants assessed
weights within each cluster of criteria. The criterion
within a cluster judged to be associated with the largest
swing weight was assigned an arbitrary score of 100.
Then, each swing on the remaining criteria in the
cluster was judged by the group compared with the
100 score, in terms of a ratio. For example, in the
cluster of four criteria under the category physical
harm to users, the swing weight for drug-related
mortality was judged to be the largest diff erence of the
four, so it was given a weight of 100. The group judged
the next largest swing in harm to be in drug-specifi c
mortality, which was 80% as great as for drug-related
Drug-specific mortality
Drug-related mortality
Drug-specific damage
Drug-related damage
Dependence
Drug-specific impairment of mental functioning
Drug-related impairment of mental functioning
Loss of tangibles
Loss of relationships
Injury
Crime
Environmental damage
Economic cost
Physical
Psychological
To users
To others
Social
Overall harm
Physical and psychological
Social
Community
Family adversities
International damage
Figure 1: Evaluation criteria organised by harms to users and harms to others, and clustered under physical,
psychological, and social eff ects
See Online for webappendix
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www.thelancet.com Published online November 1, 2010 DOI:10.1016/S0140-6736(10)61462-6
3
mortality, so it was given a weight of 80. Thus, the
computer multiplied the scores for all the drugs on the
drug-related mortality scale by 0·8, with the result that
the weighted harm of heroin on this scale became 80
as compared with heroin’s score of 100 on drug-specifi c
mortality. Next, the 100-weighted swings in each cluster
were compared with each other, with the most harmful
drug on the most harmful criterion to users compared
with the most harmful drug on the most harmful
criterion to others. The result of assessing these weights
was that the units of harm on all scales were equated. A
nal normalisation preserved the ratios of all weights, but
ensured that the weights on the criteria summed to 1·0.
The weighting process enabled harm scores to be combined
within any grouping simply by adding their weighted
scores. Dodgson and colleagues3 provide further guidance
on swing weighting. Scores and weights were input to the
Hiview computer program, which calculated the weighted
scores, provided displays of the results, and enabled
sensitivity analyses to be done.
Role of the funding source
The sponsor of the study had no role in study design,
data collection, data analysis, data interpretation, or
writing of the report. All authors had full access to all the
data in the study, and had fi nal responsibility for the
decision to submit for publication.
Results
Figure 1 shows the 16 identifi ed harm criteria. Figure 2
shows the total harm score for all the drugs and the part-
score contributions to the total from the subgroups of
harms to users and harms to others. The most harmful
drugs to users were heroin (part score 34), crack cocaine
(37), and metamfetamine (32), whereas the most harmful
Panel 1: Evaluation criteria and their defi nitions
Drug-specifi c mortality
Intrinsic lethality of the drug expressed as ratio of lethal dose
and standard dose (for adults)
Drug-related mortality
The extent to which life is shortened by the use of the drug
(excludes drug-specifi c mortality)—eg, road traffi c accidents,
lung cancers, HIV, suicide
Drug-specifi c damage
Drug-specifi c damage to physical health—eg, cirrhosis,
seizures, strokes, cardiomyopathy, stomach ulcers
Drug-related damage
Drug-related damage to physical health, including
consequences of, for example, sexual unwanted activities and
self-harm, blood-borne viruses, emphysema, and damage
from cutting agents
Dependence
The extent to which a drug creates a propensity or urge to
continue to use despite adverse consequences (ICD 10 or
DSM IV)
Drug-specifi c impairment of mental functioning
Drug-specifi c impairment of mental functioning—eg,
amfetamine-induced psychosis, ketamine intoxication
Drug-related impairment of mental functioning
Drug-related impairment of mental functioning—eg, mood
disorders secondary to drug-user’s lifestyle or drug use
Loss of tangibles
Extent of loss of tangible things (eg, income, housing, job,
educational achievements, criminal record, imprisonment)
Loss of relationships
Extent of loss of relationship with family and friends
Injury
Extent to which the use of a drug increases the chance of
injuries to others both directly and indirectly—eg, violence
(including domestic violence), traffi c accident, fetal harm,
drug waste, secondary transmission of blood-borne viruses
(Continues in next column)
(Continued from previous column)
Crime
Extent to which the use of a drug involves or leads to an
increase in volume of acquisitive crime (beyond the use-of-
drug act) directly or indirectly (at the population level, not
the individual level)
Environmental damage
Extent to which the use and production of a drug causes
environmental damage locally—eg, toxic waste from
amfetamine factories, discarded needles
Family adversities
Extent to which the use of a drug causes family adversities—
eg, family breakdown, economic wellbeing, emotional
wellbeing, future prospects of children, child neglect
International damage
Extent to which the use of a drug in the UK contributes to
damage internationally—eg, deforestation, destabilisation of
countries, international crime, new markets
Economic cost
Extent to which the use of a drug causes direct costs to the
country (eg, health care, police, prisons, social services,
customs, insurance, crime) and indirect costs (eg, loss of
productivity, absenteeism)
Community
Extent to which the use of a drug creates decline in social
cohesion and decline in the reputation of the community
ICD 10=International Classifi cation of Diseases, tenth revision. DSM IV=Diagnostic and
Statistical Manual of Mental Disorders, fourth revision.
For more on Hiview see http://
www.catalyze.co.uk
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www.thelancet.com Published online November 1, 2010 DOI:10.1016/S0140-6736(10)61462-6
to others were alcohol (46), crack cocaine (17), and heroin
(21). When the two part-scores were combined, alcohol
was the most harmful drug followed by heroin and crack
cocaine (fi gure 2).
Another instructive display is to look at the results
separately for harm to users and to others, but in a two-
dimensional graph so that the relative contribution to
these two types of harm can be seen clearly (fi gure 3).
The most harmful drug to others was alcohol by a wide
margin, whereas the most harmful drug to users was
crack cocaine followed closely by heroin. Metamfetamine
was next most harmful to users, but it was of little
comparative harm to others. All the remaining drugs
were less harmful either to users or to others, or both,
than were alcohol, heroin, and crack cocaine (fi gure 3).
Because this display shows the two axes before
weighting, a score on one cannot be compared with a
score on the other, without knowing their relative scale
constants.
Figure 4 shows the contributions that the part scores
make on each criterion to the total score of each drug.
Alcohol, with an overall score of 72, was judged to be
most harmful, followed by heroin at 55, then crack
cocaine with a score of 54. Only eight drugs scored,
overall, 20 points or more. Drug-specifi c mortality was a
substantial contributor to fi ve of the drugs (alcohol,
heroin, γ hydroxybutyric acid [GHB], methadone, and
butane), whereas economic cost contributed heavily to
alcohol, heroin, tobacco, and cannabis.
Discussion
The results from this MCDA analysis show the harms of
a range of drugs in the UK. Our fi ndings lend support to
the conclusions of the earlier nine-criteria analysis
undertaken by UK experts1 and the output of the Dutch
addiction medicine expert group.8 The Pearson cor-
relation coeffi cient between Nutt and colleagues’ 2007
study1 and the new analysis presented here for the
15 drugs common to both studies is 0·70. One reason
for a less-than-perfect correlation is that the scores from
Nutt and colleagues’ previous study were based on four-
point ratings (0=no risk, 1=some risk, 2=moderate risk,
and 3=extreme risk). The ISCD scoring process was
based on 0–100 ratio scales, so they contain more
information than the ratings do.
Throughout Nutt and colleagues’ 2007 paper, harm
and risk are used interchangeably, but in the ISCD
work, risk was not considered because it is susceptible
to varying interpretations. For example, the British
Medical Association defi nes risk as the probability that
something unpleasant will happen.9 Thus, assessors
from Nutt and colleagues’ 2007 work might have
interpreted their rating task diff erently from the scoring
task of the ISCD experts. Furthermore, in Nutt and co-
workers’ 2007 study, ratings were simply averaged
across the nine criteria (called parameters in the report),
three each for physical harm, dependence, and social
harms, whereas diff erential weights were applied to the
criteria in this ISCD study, as is shown in the key of
Alcohol
Heroin
Crack cocaine
Metamfetamine
Cocaine
Tobacco
Amfetamine
Cannabis
GHB
Benzodiazepines
Ketamine
Methadone
Mephedrone
Butane
Khat
Anabolic steroids
Ecstasy
LSD
Buprenorphine
Mushrooms
0
10
20
30
40
50
60
70
80
Overall harm score
72
55 54
33
27 26
23
20 19
15 15 14 13 11 910 9776
Harm to users (CW 46)
Harm to others (CW 54)
Figure 2: Drugs ordered by their overall harm scores, showing the separate contributions to the overall scores of harms to users and harm to others
The weights after normalisation (0–100) are shown in the key (cumulative in the sense of the sum of all the normalised weights for all the criteria to users, 46; and for
all the criteria to others, 54). CW=cumulative weight. GHB=γ hydroxybutyric acid. LSD=lysergic acid diethylamide.
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www.thelancet.com Published online November 1, 2010 DOI:10.1016/S0140-6736(10)61462-6
5
gure 4. Despite these many diff erences between the
two studies, there is some degree of linear association
between both sets of data.
The correlations between the Dutch addiction medicine
expert group2 and ISCD results are higher: 0·80 for
individual total scores and 0·84 for population total scores.
As with Nutt and colleagues’ 2007 study, the Dutch experts
applied four-point rating scales to 19 drugs. However, they
used fi ve criteria: acute toxicity, chronic toxicity, addictive
potency, social harm at individual level, and social harm at
population level. Simple averages produced two overall
mean harm ratings, one each for individuals and for
populations. The probable explanation for the greater
correlation between the ISCD and Dutch data lies in the
greater relative ranges of the overall results than in Nutt
and co-workers’ 2007 study. The highest and lowest overall
harm scores in the ISCD study are 72 for alcohol and 5 for
mushrooms, which is a ratio of about 14:1; whereas in
Nutt and colleagues’ study it was a ratio of just over 3:1,
from 2·5 for heroin to 0·8 for khat. The highest and lowest
scores for the Dutch individual ratings were 2·63 for crack
cocaine and 0·40 for mushrooms, which is a ratio of 6·6:1;
and for the population ratings 2·41 for crack cocaine and
0·31 for mushrooms, which is a ratio of 7·8:1. The ratio
scaling in the ISCD study spanned a wider range, making
the three most harmful drugs—alcohol, heroin, and crack
cocaine—much more harmful relative to the other drugs
than can be expressed with rating scales, so that additional
information stretched the scatterplot in one dimension,
making it seem more linear. Additionally, because the
Dutch scale attributes only a quarter of the scores to social
factors, whereas in the ISCD scoring these factors
comprise nearly half of the scores (seven of 16 criteria),
drugs such as alcohol which have a major eff ect will rank
more highly in the ISCD analysis, with tobacco ranked
lower because its harms are mainly personal.
The correlations between the ISCD overall scores and
the present classifi cation of drugs based on revisions to
the UK Misuse of Drugs Act (1971) is 0·04, showing that
there is eff ectively no relation. The ISCD scores lend
support to the widely accepted view10,11 that alcohol is an
extremely harmful drug, both to users and society; it
scored fourth on harms to users and top for harms to
society, making it the most harmful drug overall. Even in
terms of toxic eff ects alone, Gable12 has shown that, on the
basis of a safety ratio, alcohol is more lethal than many
010 20 30 40 50 60 70 80 90
0
10
20
30
40
50
60
70
80
90
Score for harm to others
Score for harm to users
Alcohol
Heroin
Crack cocaine
Metamfetamine
Cocaine
Tobacco
Amfetamine
Cannabis
GHB
Benzodiazepines
Ketamine
Methadone
Mephedrone
Butane
Khat
Anabolic steroids
Ecstasy
LSD
Buprenorphine
Mushrooms
Figure 3: Drugs shown for their harm to users and harm to others
LSD=lysergic acid diethylamide. GHB=γ hydroxybutyric acid.
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illicit drugs, such as cannabis, lysergic acid diethylamide
(LSD), and mushrooms.
The MCDA process provides a powerful means to deal
with complex issues that drug misuse presents. The
expert panel’s scores within one criterion can be to some
extent validated by reference to published work. For
example, we compared the 12 substances in common
between this study and those in Gable’s study,12 who for
20 substances identifi ed a safety ratio—the ratio of an
acute lethal dose to the dose commonly used for non-
medical purposes. The log10 of that ratio shows a
correlation of 0·66 with the ISCD scores on the criterion
drug-specifi c mortality, providing some evidence of
validity of the ISCD input scores.
We also investigated drug-specifi c mortality estimates
in studies of human beings.13 These estimates show a
strong correlation with the group input scores: the mean
fatality statistics from 2003 to 2007 for fi ve substances
(heroin, cocaine, amfetamines, MDMA/ecstasy, and
cannabis) show correlations with the ISCD lethality
scores of 0·98 and 0·99, for which the substances
recorded on the death certifi cates were among other
mentions or sole mentions, respectively.
A comparison of the ICSD experts’ ratings on the
dependence criterion with lifetime dependence reported
in the US survey by Anthony and co-workers14 showed a
correlation of 0·95 for the fi ve drugs—tobacco, alcohol,
cannabis, cocaine, and heroin—that were investigated in
both studies, showing the validity of the MCDA input
scores for those substances.
Drug-specifi c and drug-related harms for some drugs
can be estimated from health data and other data that
show alcohol, heroin, and crack cocaine as having much
larger eff ects than other drugs.15 Social harms are harder
to ascertain, although estimates based on road traffi c
and other accidents at home, drug-related violence,16 and
costs to economies in provider countries (eg, Colombia,
Afghanistan, and Mexico)17 have been estimated. Police
Drug-specific mortality (CW 5·1)
Drug-related mortality (CW 6·4)
Drug-specific damage (CW 4·1)
Drug-related damage (CW 4·1)
Dependence (CW 5·7)
Drug-specific impairment of mental functioning (CW 5·7)
Drug-related impairment of mental functioning (CW 5·7)
Loss of tangibles (CW 4·5)
Loss of relationships (CW 4·5)
Injury (CW 11·5)
Crime (CW 10·2)
Environmental damage (CW 3·8)
Family adversities (CW 8·9)
International damage (CW 3·8)
Economic cost (CW 12·8)
Community (CW 3·2)
Alcohol
Heroin
Crack cocaine
Metamfetamine
Cocaine
Tobacco
Amfetamine
Cannabis
GHB
Benzodiazepines
Ketamine
Methadone
Mephedrone
Butane
Khat
Anabolic steroids
Ecstasy
LSD
Buprenorphine
Mushrooms
0
10
20
30
40
50
60
70
80
Overall harm score
72
55 54
33
27 26
23
20 19
15 15 14 13
11 910 9
776
Figure 4: Overall weighted scores for each of the drugs
The coloured bars indicate the part scores for each of the criteria. The key shows the normalised weight for each criterion. A higher weight indicates a larger diff erence
between the most harmful drug on the criterion and no harm. CW=cumulative weight. GHB=γ hydroxybutyric acid. LSD=lysergic acid diethylamide.
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7
records lend support to the eff ect of drug dealing on
communities and of alcohol-related crime.18 However,
data are not available for many of the criteria, so the
expert group approach is the best we can provide. The
many high correlations (of our overall results with those
of the Dutch addiction medicine expert group, and of
some of our input scores with objective data) provide
some evidence of the validity of our results.
The issue of the weightings is crucial since they aff ect
the overall scores. The weighting process is necessarily
based on judgment, so it is best done by a group of experts
working to consensus. Although the assessed weights
can be made public, they cannot be cross-validated with
objective data. However, the eff ect of varying the
weightings can be explored in the computer program
through sensitivity analysis. For example, we noted that it
would be necessary to increase the weight on drug-
specifi c mortality or on drug-related mortality by more
than 15 of 100 points before heroin displaced alcohol in
rst position of overall harm. A similarly large change in
the weight on drug-specifi c damage would be needed,
from about 4% to slightly more than 70%, for tobacco to
displace alcohol at fi rst position. And an increase in the
weight on harm to users from 46% to nearly 70% would
be necessary for crack cocaine to achieve the overall most
harmful position. Extensive sensitivity analyses on the
weights showed that this model is very stable; large
changes, or combinations of modest changes, are needed
to drive substantial shifts in the overall rankings of the
drugs. Future work will explore these weightings with
use of other groups—both expert panels and those from
the general public.
Limitations of this approach include the fact that we
scored only harms. All drugs have some benefi ts to the
user, at least initially, otherwise they would not be used,
but this eff ect might attenuate over time with tolerance
and withdrawal. Some drugs such as alcohol and tobacco
have commercial benefi ts to society in terms of providing
work and tax, which to some extent off set the harms and,
although less easy to measure, is also true of production
and dealing in illegal drugs.19 Many of the harms of drugs
are aff ected by their availability and legal status, which
varies across countries, so our results are not necessarily
applicable to countries with very diff erent legal and
cultural attitudes to drugs. Ideally, a model needs to
distinguish between the harms resulting directly from
drug use and those resulting from the control system for
that drug. Furthermore, they do not relate to drugs when
used for prescription purposes. Other issues to explore
further include building into the model an assessment of
polydrug use, and the eff ect of diff erent routes of
ingestion, patterns of use, and context.20 Finally, we
should note that a low score in our assessment does not
mean the drug is not harmful, since all drugs can be
harmful under specifi c circumstances.
In conclusion, we have used MCDA to analyse the
harms of a range of drugs in relation to the UK (panel 2).
Our fi ndings lend support to previous work in the
UK and the Netherlands, confi rming that the present
drug classifi cation systems have little relation to the
evidence of harm. They also accord with the conclusions
of previous expert reports11,18 that aggressively targeting
alcohol harms is a valid and necessary public
health strategy.
Contributors
DJN designed and participated in the study. LAK participated in the
study. LDP participated in the running of the study and analysed data.
All authors wrote the report and responded to referees’ comments.
Confl icts of interest
DJN and LAK received travel expenses to attend the decision
conference meeting. LAK is a consultant to the Department of Health
and the EMCDDA. LDP is a director of Facilitations Limited, which
paid him a consulting fee because it was the company engaged by the
Centre for Crime and Justice Studies to run the study and analyse
the data.
Acknowledgments
This study is funded by the Centre for Crime and Justice Studies (UK).
Yuji Wu assisted with some of the data analyses.
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