Datasets containing information about the use of pain relievers for non medical purpose.
Format
A tibble with either 100 or 55271 rows, and 8 variables:
- caseid
The identifier code of the respondent
- hydrocd
Ever use hydrocodone nonmedically?
- oxycodp
Ever use ever percocet, percodan, tylox, oxycontin... nonmedically?
- codeine
Ever used codeine nonmedically?
- tramadl
Ever used tramadol nonmedically?
- morphin
Ever used morphine nonmedically?
- methdon
Ever used methadone nonmedically?
- vicolor
Ever used vicodin, lortab or lorcert nonmedically?
Details
These datasets are a small subset from the "National Survey on Drug Use and Health, 2014".
All variables related to drug use have been recoded into vectors of integers talking value 0 for
"No/Unknown" and value 1 for "Yes". The original variable names were the same as those defined
here but in upper case and ending with the number 2. The dataset called drugs contain the first
100 rows of the one called drugs_full.
References
United States Department of Health and Human Services. Substance Abuse and Mental Health Services Administration. Center for Behavioral Health Statistics and Quality. National Survey on Drug Use and Health, 2014. Ann Arbor, MI: Inter-university Consortium for Political and Social Research (distributor), 2016-03-22. doi:10.3886/ICPSR36361.v1
Examples
drugs
#> # A tibble: 100 × 8
#> caseid hydrocd oxycodp codeine tramadl morphin methdon vicolor
#> <chr> <int> <int> <int> <int> <int> <int> <int>
#> 1 1 0 0 0 0 0 0 0
#> 2 2 0 0 0 0 0 0 0
#> 3 3 0 0 0 0 0 0 0
#> 4 4 0 0 0 0 0 0 0
#> 5 5 0 0 0 0 0 0 0
#> 6 6 0 0 0 0 0 0 0
#> 7 7 0 0 0 0 0 0 0
#> 8 8 0 0 0 0 0 0 0
#> 9 9 0 0 0 0 0 0 1
#> 10 10 0 0 0 0 0 0 0
#> # ℹ 90 more rows
drugs_full
#> # A tibble: 55,271 × 8
#> caseid hydrocd oxycodp codeine tramadl morphin methdon vicolor
#> <chr> <int> <int> <int> <int> <int> <int> <int>
#> 1 1 0 0 0 0 0 0 0
#> 2 2 0 0 0 0 0 0 0
#> 3 3 0 0 0 0 0 0 0
#> 4 4 0 0 0 0 0 0 0
#> 5 5 0 0 0 0 0 0 0
#> 6 6 0 0 0 0 0 0 0
#> 7 7 0 0 0 0 0 0 0
#> 8 8 0 0 0 0 0 0 0
#> 9 9 0 0 0 0 0 0 1
#> 10 10 0 0 0 0 0 0 0
#> # ℹ 55,261 more rows