[AG-Drogen] Studie: Alkohol gefährlicher als Heroin / Drug harms in the UK: a multicriteria decision analysis

[Maximilian Plenert <kontakt AT max-plenert.de>]

Die Studie findet ihr im Anhang.

Studie: Alkohol gefährlicher als Heroin

Alkohol ist bei weitem die gefährlichste Droge in Großbritannien. Zu diesem
Schluss kommt eine Studie des Independent Scientific Committee on Drugs. Erst 
an
zweiter Stelle kommen demnach Heroin und Crack. Die im Medizinjournal „Lancet“
publizierte Studie könnte eine neue Debatte über die Klassifikation von Drogen
in Großbritannien auslösen.

Einer der Studienautoren, David Nutt, war vor rund einem Jahr als
Drogenbeauftragter der Regierung gefeuert worden, nachdem er dieser 
vorgeworfen
hatte, sie würden wissenschaftliche Erkenntnisse nicht ernst nehmen und
stattdessen populistisch handeln. Nutt hatte vorgeschlagen, Cannabis und 
Ecstasy
als weniger gefährlich zu klassifizieren.
Auch soziales Umfeld eingerechnet

In der neuen Studie unterscheiden die Forscher die Gefährlichkeit der Drogen 
für
den Konsumenten und für sein Umfeld. Gesundheitliche Auswirkungen sind dabei 
nur
ein Faktor, auch soziale und ökonomische Folgen werden miteinbezogen. Für das
Individuum sind demnach Heroin, Crack und Crystal Meth die gefährlichsten, für
das soziale Umfeld hingegen richtet Alkohol den größten Schaden an. Auf der
Skala von null bis 100 wurde für Alkohol damit der Wert 72 errechnet, Heroin 
und
Crack kommen auf 55 und 54. Nach diesen Berechnungen ist Tabak (27) auch weit
gefährlicher als Cannabis (20), Ecstasy (9) und LSD (7).

Publiziert am 01.11.2010
http://orf.at/stories/2023132/


The Lancet, Early Online Publication, 1 November 2010
doi:10.1016/S0140-6736(10)61462-6Cite or Link Using DOI
Drug harms in the UK: a multicriteria decision analysis
Original Text
Prof David J Nutt FMedSci a Corresponding AuthorEmail Address, Leslie A King 
PhD
b, Lawrence D Phillips PhD c, on behalf of the Independent Scientific 
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.
Methods
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.
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 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.
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 differential 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, conflicting 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 first principles and with the MCDA approach, members identified 16 harm
criteria (figure 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 five 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
Click to toggle image size
Figure 1 Full-size image (16K) Download to PowerPoint
Evaluation criteria organised by harms to users and harms to others, and
clustered under physical, psychological, and social effects
In June, 2010, a meeting under the auspices of the Independent Scientific
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
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 conflicts 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
effectively 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 definitions 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 definitions 
were
adopted, and panel 1 shows the final version.
Panel 1
Evaluation criteria and their definitions
Drug-specific 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-specific mortality)—eg, road traffic accidents, lung cancers, HIV, 
suicide
Drug-specific damage
Drug-specific 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-specific impairment of mental functioning
Drug-specific 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), 
traffic
accident, fetal harm, drug waste, secondary transmission of blood-borne 
viruses
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 Classification of Diseases, tenth revision. DSM
IV=Diagnostic and Statistical Manual of Mental Disorders, fourth revision.
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 specific criterion. Zero indicated no harm. Weighting subsequently
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 different 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 different 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
affect assessments 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 straightforward assessment of a difference in harm. The next
step is to think about how much that difference in harm matters in a specific
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 difference in harm and how much do you care about that difference?”
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 difference of the four, so it was 
given a
weight of 100. The group judged the next largest swing in harm to be in
drug-specific mortality, which was 80% as great as for drug-related 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-specific 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 final 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 final responsibility for the
decision to submit for publication.
Results
Figure 1 shows the 16 identified 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 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 (figure 2).
Click to toggle image size
Figure 2 Full-size image (67K) Download to PowerPoint
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.
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 (figure 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 (figure 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.
Click to toggle image size
Figure 3 Full-size image (41K) Download to PowerPoint
Drugs shown for their harm to users and harm to others
LSD=lysergic acid diethylamide. GHB=γ hydroxybutyric acid.
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-specific 
mortality
was a substantial contributor to five of the drugs (alcohol, heroin, γ
hydroxybutyric acid [GHB], methadone, and butane), whereas economic cost
contributed heavily to alcohol, heroin, tobacco, and cannabis.
Click to toggle image size
Figure 4 Full-size image (124K) Download to PowerPoint
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 difference between the most harmful drug on the criterion and no harm.
CW=cumulative weight. GHB=γ hydroxybutyric acid. LSD=lysergic acid 
diethylamide.
Discussion
The results from this MCDA analysis show the harms of a range of drugs in the
UK. Our findings 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 correlation coefficient 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 defines risk as the probability that something unpleasant will
happen.9 Thus, assessors from Nutt and colleagues' 2007 work might have
interpreted their rating task differently 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 differential weights
were applied to the criteria in this ISCD study, as is shown in the key of
figure 4. Despite these many differences 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 five 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 effect 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 
classification
of drugs based on revisions to the UK Misuse of Drugs Act (1971) is 0·04,
showing that there is effectively 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 
effects
alone, Gable12 has shown that, on the basis of a safety ratio, alcohol is more
lethal than many 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 identified 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-specific
mortality, providing some evidence of validity of the ISCD input scores.
We also investigated drug-specific 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 five 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 certificates 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 five 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-specific 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 effects than other drugs.15 Social harms are harder to ascertain,
although estimates based on road traffic 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 records lend
support to the effect 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 affect 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 
effect
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-specific mortality or on drug-related mortality by
more than 15 of 100 points before heroin displaced alcohol in first position 
of
overall harm. A similarly large change in the weight on drug-specific damage
would be needed, from about 4% to slightly more than 70%, for tobacco to
displace alcohol at first 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 benefits to the user, at least initially, otherwise they would
not be used, but this effect might attenuate over time with tolerance and
withdrawal. Some drugs such as alcohol and tobacco have commercial benefits to
society in terms of providing work and tax, which to some extent offset 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 affected by their
availability and legal status, which varies across countries, so our results 
are
not necessarily applicable to countries with very different 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 effect of different 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 specific circumstances.
In conclusion, we have used MCDA to analyse the harms of a range of drugs in
relation to the UK (panel 2). Our findings lend support to previous work in 
the
UK and the Netherlands, confirming that the present drug classification 
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.
Panel 2
Research in context
Systematic review
We analysed the data obtained from a multicriteria decision analysis (MCDA)
conference on drug harms. The harms were assessed according to a new set of 16
criteria developed by the Advisory Council on the Misuse of Drugs (the UK
Government committee on drug misuse). A panel of drug-harm experts was 
convened
to establish scores for 20 representative drugs that are relevant to the UK 
and
which span the range of potential harms and extent of use. Participants scored
the relative harms of each drug on each of 16 criteria, and then assessed
criterion weights to ensure that units of harm were equivalent across all
criteria. Calculation of weighted scores provided a composite score on two
dimensions, harm to the individual and harm to society, and an overall 
weighted
harm score.
Interpretation
These findings lend support to earlier work from both UK and Dutch expert
committees on assessment of drug harms, and show how the improved scoring and
weighting approach of MCDA increases the differentiation between the most and
least harmful drugs. On the basis of these data it is clear that the present 
UK
drug classification system is not simply based on considerations of harm.
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.
Conflicts 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.
WebExtra Content
Supplementary webappendix
Open file
PDF (40K)
References
1 Nutt D, King LA, Saulsbury W, Blakemore C. Development of a rational scale 
to
assess the harm of drugs of potential misuse. Lancet 2007; 369: 1047-1053.
Summary | Full Text | PDF(124KB) | CrossRef | PubMed
2 Murphy PN, Britton J, Arnott D, et al. Assessing drug-related harm. Lancet
2007; 369: 1856-1857. Full Text | PDF(41KB) | CrossRef | PubMed
3 Dodgson J, Spackman M, Pearman A, Phillips L. Multi-criteria analysis: a
manual. London: Department of the Environment, Transport and the Regions, 
2000.
4 Morton A, Airoldi M, Phillips L. Nuclear risk management on stage: the UK's
Committee on Radioactive Waste Management. Risk Anal 2009; 29: 764-779. 
CrossRef
| PubMed
5 Phillips LD. Decision conferencing. In: Edwards W, Miles RF, von Winterfeldt
D, eds. Advances in decision analysis: from foundations to applications.
Cambridge: Cambridge University Press, 2007: 375-399.
6 Advisory Council on the Misuse of Drugs. Consideration of the use of
Multi-Criteria Decision Analysis in drug harm decision making. London: Home
Office, 2010. http://www.homeoffice.gov.uk/publications/drugs/acmd1. (accessed
Aug 24, 2010).
7 Regan-Cirincione P. Improving the accuracy of group judgment: a process
intervention combining group facilitation, social judgment analysis, and
information technology. Organ Behav Hum Decis Process 1994; 58: 246-270.
CrossRef | PubMed
8 van Amsterdam JGC, Opperhuizen A, Koeter M, van den Brink W. Ranking the 
harm
of alcohol, tobacco and illicit drugs for the individual and the population. 
Eur
Addict Res 2010; 16: 202-227. CrossRef | PubMed
9 British Medical Association. Living with risk. Chichester: John Wiley & 
Sons,
1987.
10 Academy of Medical Science. Calling time: the nation's drinking as a major
health issue. London: Academy of Medical Sciences, 2004.
11 NICE. Alcohol-use disorders: preventing the development of hazardous and
harmful drinking. London: National Institute for Health and Clinical 
Excellence,
2010.
12 Gable RS. Comparison of acute lethal toxicity of commonly abused 
psychoactive
substances. Addiction 2004; 99: 686-696. CrossRef | PubMed
13 King LA, Corkery JM. An index of fatal toxicity for drugs of misuse. Hum
Psychopharmacol 2010; 25: 162-166. CrossRef | PubMed
14 Anthony JC, Warner LA, Kessler RC. Comparative epidemiology of dependence 
on
tobacco, alcohol, controlled substances and inhalants: basic finding from the
National Comorbidity Survey. Exp Clin Psychopharmacol 1994; 2: 244-268. 
CrossRef
| PubMed
15 Horn G. Brain science, addiction and drugs. London: The Academy of Medical
Sciences, 2008.
16 Werb D, Rowell G, Guyatt G, Kerr T, Montaner J, Wood E. Effect of drug law
enforcement on drug-related violence: evidence from a scientific review.
Vancouver: International Centre for Science in Drug Policy, 2010.
17 United Nations Office on Drugs and Crime. World Drug Report 2010. Vienna:
United Nations, 2010.
18 House of Commons Health Committee. Alcohol. Report number: HC 151-I. 
London:
House of Commons, 2010.
19 Lloyd C, McKeganey N. Drugs research: an overview of evidence and questions
for policy. York: Joseph Rowntree Foundation, 2010.
20 Coomber R. Assessing the real dangers of illicit drugs—risk analysis as the
way forward?. Addict Res Theory 1999; 7: 85-90. PubMed
a Neuropsychopharmacology Unit, Imperial College, London, UK
b UK Expert Adviser to the European Monitoring Centre for Drugs and Drug
Addiction (EMCDDA), Lisbon, Portugal
c Department of Management, London School of Economics and Political Science,
London, UK
Corresponding Author Information Correspondence to: Prof David J Nutt,
Neuropsychopharmacology Unit, Imperial College London, Burlington-Danes
Building, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK

Attachment: PIIS0140673610614626.pdf
Description: Adobe PDF document