drugriskfactors: Personality risk factors for drug consumption
In mark-andrews/isdsr-pkg: Tools and Datasets to Accompany ISDSR Textbook
drugriskfactors R Documentation
Personality risk factors for drug consumption
Description
Personality variables and drug consumption habits of 1885
individuals in mostly English speaking countries. Twelve personality
or demographic variables were measured, as was the respondent's consumption
of 18 mostly illegal drugs.
Format
A data frame with 1885 rows and 32 variables:
id(factor) A unique identifier of the survey respondent.
age(ordinal) Respondent's age group, e.g. 18-24, 35-44,
etc.
gender(factor) Gender of respondent (Female/Male).
education(ordinal) Respondent's education level.
country(factor) The country where respondent lives.
ethnicity(factor) Ethnicity of respondent.
nscore(numeric) Respondent's NEO-FFI-R Neuroticism score.
escore(numeric) Respondent's NEO-FFI-R Extraversion score.
oscore(numeric) Respondent's NEO-FFI-R Openness score.
ascore(numeric) Respondent's NEO-FFI-R Agreeableness score.
cscore(numeric) Respondent's NEO-FFI-R Conscientiousness score.
impuls(numeric) Respondent's BIS-11 impulsiveness score.
senseek(numeric) Respondent's ImpSS sensation seeking score.
alcohol(ordinal) Respondent's alcohol consumption. For this
and every other drug consumption variable, consumption was measured on
a seven point ordinal scale: 1) "Never Used", 2) "Used over a Decade Ago",
3) "Used in Last Decade", 4) "Used in Last Year", 5) "Used in Last Month",
6) "Used in Last Week", 7) "Used in Last Day". In the analysis described in
Fehrman et al (2017), a respondent was labelled a "non-user" of a given
drug if they chose "Never Used" or "Used over a Decade Ago" as their
response describing their consumption of that drug, and were labelled a
"user" for all other five values, i.e. "Used in Last Decade" to "Used in
Last Day".
amphet(ordinal) Respondent's amphetamines consumption.
amyl(ordinal) Respondent's amyl nitrite consumption.
benzos(ordinal) Respondent's benzodiazepine consumption.
caff(ordinal) Respondent's caffeine consumption.
cannabis(ordinal) Respondent's cannabis consumption.
choc(ordinal) Respondent's chocolate consumption.
coke(ordinal) Respondent's cocaine consumption.
crack(ordinal) Respondent's crack cocaine consumption.
ecstasy(ordinal) Respondent's ecstasy (Methylenedioxymethamphetamine, MDMA) consumption.
heroin(ordinal) Respondent's heroin consumption.
ketamine(ordinal) Respondent's ketamine consumption.
legalh(ordinal) Respondent's legal high (designer psychoactive drugs) consumption.
lsd(ordinal) Respondent's LSD (lysergic acid diethylamide) consumption.
meth(ordinal) Respondent's methadone consumption. Note that is methadone, and not methamphetamine.
mushrooms(ordinal) Respondent's psilocybin mushrooms consumption.
nicotine(ordinal) Respondent's nicontine consumption.
semer(ordinal) Respondent's "semeron" consumption. Semeron is a fictitious drug that was used to identify over-claimers.
vsa(ordinal) Respondent's volatile substance abuse (solvents etc) consumption.
Details
This dataset is based on the dataset entitled
"Drug
consumption (quantified)" in the UCI Machine Learning Repository. That
dataset is the dataset that accompanies the Fehrman et al (2017) paper.
However, most of the variables in that dataset were recoded from their
original values by converting them into standardized real numbers. Details
of the original values of all variables
UCI
Machine Learning Repository webpage, and also in the codebook named
"36536-0001-Codebook.pdf" available from
https://www.icpsr.umich.edu/web/ICPSR/studies/36536/.
Here, we have de-coded all variables back to their original values.
Source
The original source of this data is described in the paper Fehrman,
E., Muhammad, A. K., Mirkes, E. M., Egan, V., & Gorban, A. N. (2017). The
five factor model of personality and evaluation of drug consumption risk.
In Data science (pp. 231-242). Springer, Cham, which is available
here.
The arXiv-ed preprint is available at
https://arxiv.org/abs/1506.06297.
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| drugriskfactors | R Documentation |
Personality risk factors for drug consumption
Description
Personality variables and drug consumption habits of 1885 individuals in mostly English speaking countries. Twelve personality or demographic variables were measured, as was the respondent's consumption of 18 mostly illegal drugs.
Format
A data frame with 1885 rows and 32 variables:
id(factor) A unique identifier of the survey respondent.
age(ordinal) Respondent's age group, e.g. 18-24, 35-44, etc.
gender(factor) Gender of respondent (Female/Male).
education(ordinal) Respondent's education level.
country(factor) The country where respondent lives.
ethnicity(factor) Ethnicity of respondent.
nscore(numeric) Respondent's NEO-FFI-R Neuroticism score.
escore(numeric) Respondent's NEO-FFI-R Extraversion score.
oscore(numeric) Respondent's NEO-FFI-R Openness score.
ascore(numeric) Respondent's NEO-FFI-R Agreeableness score.
cscore(numeric) Respondent's NEO-FFI-R Conscientiousness score.
impuls(numeric) Respondent's BIS-11 impulsiveness score.
senseek(numeric) Respondent's ImpSS sensation seeking score.
alcohol(ordinal) Respondent's alcohol consumption. For this and every other drug consumption variable, consumption was measured on a seven point ordinal scale: 1) "Never Used", 2) "Used over a Decade Ago", 3) "Used in Last Decade", 4) "Used in Last Year", 5) "Used in Last Month", 6) "Used in Last Week", 7) "Used in Last Day". In the analysis described in Fehrman et al (2017), a respondent was labelled a "non-user" of a given drug if they chose "Never Used" or "Used over a Decade Ago" as their response describing their consumption of that drug, and were labelled a "user" for all other five values, i.e. "Used in Last Decade" to "Used in Last Day".
amphet(ordinal) Respondent's amphetamines consumption.
amyl(ordinal) Respondent's amyl nitrite consumption.
benzos(ordinal) Respondent's benzodiazepine consumption.
caff(ordinal) Respondent's caffeine consumption.
cannabis(ordinal) Respondent's cannabis consumption.
choc(ordinal) Respondent's chocolate consumption.
coke(ordinal) Respondent's cocaine consumption.
crack(ordinal) Respondent's crack cocaine consumption.
ecstasy(ordinal) Respondent's ecstasy (Methylenedioxymethamphetamine, MDMA) consumption.
heroin(ordinal) Respondent's heroin consumption.
ketamine(ordinal) Respondent's ketamine consumption.
legalh(ordinal) Respondent's legal high (designer psychoactive drugs) consumption.
lsd(ordinal) Respondent's LSD (lysergic acid diethylamide) consumption.
meth(ordinal) Respondent's methadone consumption. Note that is methadone, and not methamphetamine.
mushrooms(ordinal) Respondent's psilocybin mushrooms consumption.
nicotine(ordinal) Respondent's nicontine consumption.
semer(ordinal) Respondent's "semeron" consumption. Semeron is a fictitious drug that was used to identify over-claimers.
vsa(ordinal) Respondent's volatile substance abuse (solvents etc) consumption.
Details
This dataset is based on the dataset entitled "Drug consumption (quantified)" in the UCI Machine Learning Repository. That dataset is the dataset that accompanies the Fehrman et al (2017) paper. However, most of the variables in that dataset were recoded from their original values by converting them into standardized real numbers. Details of the original values of all variables UCI Machine Learning Repository webpage, and also in the codebook named "36536-0001-Codebook.pdf" available from https://www.icpsr.umich.edu/web/ICPSR/studies/36536/. Here, we have de-coded all variables back to their original values.
Source
The original source of this data is described in the paper Fehrman, E., Muhammad, A. K., Mirkes, E. M., Egan, V., & Gorban, A. N. (2017). The five factor model of personality and evaluation of drug consumption risk. In Data science (pp. 231-242). Springer, Cham, which is available here. The arXiv-ed preprint is available at https://arxiv.org/abs/1506.06297.
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