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Treatment Statistics or, The Drug Czar is Lying to You
The Drug Czar and other drug warriors keep talking about the vast numbers of marijuana users in treatment, how the potency of pot is adding to the treatment numbers and how the high levels of treatment show that marijuana is not safe.
I've often debunked that notion here, but I thought I'd take a look at the drug warriors' own statistics and show them to you.
You can run your own charts off the raw government data here if you know how to do it. It's available through the Substance Abuse and Mental Health Data Archive in conjunction with SAMHSA.
I've done it below for you. Now the Drug Czar would run the numbers and eliminate alcohol from treatment statistics to increase the percentage of marijuana, or would focus on age ranges that would support his arguments better. I'm looking here at the overall data (let me know if there's a particular age range you'd like me to run if you don't know how).
In the first chart below, we're looking at a cross-reference of primary substance "problem" and referral source.
When you take a look at the various forms of referral for marijuana (percentages are the 2nd bold number in each cell in the marijuana row) you immediately see:
- 58.1% of all marijuana referrals to treatment were from the criminal justice system
- Only 16.6% of marijuana referrals to treatment were from individuals (that includes parents), which is where you would expect a large figure if, in fact, marijuana addiction (particularly in youths) was a real problem
That clearly shows that treatment numbers are a more a function of referral rather than any actual problems with marijuana use.
Now, take a look at the other numbers (how marijuana compares to other drugs by referral) and you see
- When it comes to individual referrals (individuals and parents, etc.), 38.9% are for alcohol and only 7.3% for marijuana. That gives you an idea of the actual concern people have regarding the use/abuse of substances despite the propaganda and legal status.
- More strangely, when it comes to schools, 57.9% of school referrals are for marijuana, while only 27.1% are for alcohol. Given the fact that alcohol is more dangerous and causes more actual problems, one of two things can be inferred:
- Alcohol regulation works so much better than marijuana prohibition, that more students are getting pot than alcohol
- Schools are ignoring alcohol problems and focusing on busting marijuana use.
[more below the chart]
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SDA 1.3: Tables
Treatment Episode Data Set, 2002
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|
Data run Aug 03, 2004 (Tue 07:09 PM EDT) |
| Variables |
| Role |
Name |
Label |
Range |
MD |
Dataset |
| Row |
SUB1 |
PRIMARY SUBSTANCE PROBLEM CODE |
1-20 |
-9 |
1 |
| Column |
PSOURCE |
PRINCIPAL SOURCE OF REFERRAL |
1-7 |
-9 |
1 |
|
| Frequency Distribution |
Cells contain:
-Column percent
-Row percent
-N of cases |
PSOURCE |
1
INDIVIDUAL (INCLUDES SELF-REFERRAL) |
2
ALCOHOL/ DRUG ABUSE CARE PROVIDER |
3
OTHER HEALTH CARE PROVIDER |
4
SCHOOL (EDUCATIONAL) |
5
EMPLOYER/ EAP |
6
OTHER COMMUNITY REFERRAL |
7
COURT/ CRIMINAL JUSTICE REFERRAL/ DUI/DWI |
ROW
TOTAL |
| SUB1 |
1: NONE |
1.1
39.8
6,906 |
.3
3.6
626 |
1.0
7.0
1,215 |
6.2
7.1
1,226 |
.7
.6
108 |
.9
8.8
1,520 |
.9
33.1
5,743 |
1.0
100.0
17,344 |
| 2: ALCOHOL |
38.9
31.2
243,702 |
49.1
12.1
94,905 |
52.0
8.0
62,474 |
27.1
.7
5,343 |
51.6
1.1
8,257 |
44.1
9.5
74,093 |
45.9
37.5
293,389 |
43.8
100.0
782,163 |
| 3: COCAINE/ CRACK |
14.5
38.8
90,845 |
16.2
13.4
31,431 |
14.4
7.4
17,280 |
2.2
.2
431 |
14.1
1.0
2,257 |
15.2
11.0
25,634 |
10.3
28.2
66,091 |
13.1
100.0
233,969 |
| 4: MARIJUANA/ HASHISH |
7.3
16.6
45,523 |
7.7
5.4
14,909 |
10.8
4.7
13,012 |
57.9
4.2
11,417 |
20.1
1.2
3,218 |
15.9
9.8
26,751 |
24.9
58.1
159,319 |
15.4
100.0
274,149 |
| 5: HEROIN |
28.3
63.4
177,498 |
18.6
12.8
35,915 |
10.6
4.5
12,714 |
1.2
.1
246 |
5.5
.3
881 |
9.5
5.7
16,054 |
5.7
13.1
36,628 |
15.7
100.0
279,936 |
| 6: NON- PRESCRIPTION METHADONE |
.2
53.2
1,296 |
.2
14.4
351 |
.1
6.8
166 |
.0
.0
1 |
.1
.7
17 |
.1
8.7
212 |
.1
16.1
392 |
.1
100.0
2,435 |
| 7: OTHER OPIATES AND SYNTHETICS |
3.4
51.4
21,522 |
3.1
14.4
6,050 |
3.7
10.6
4,425 |
.4
.2
74 |
3.2
1.2
520 |
1.8
7.4
3,102 |
1.0
14.8
6,206 |
2.3
100.0
41,899 |
| 8: PCP |
.2
29.0
1,089 |
.1
6.1
230 |
.1
4.2
157 |
.0
.2
8 |
.2
.7
27 |
.2
9.4
352 |
.3
50.4
1,896 |
.2
100.0
3,759 |
| 9: HALLUCINOGENS |
.2
36.0
1,397 |
.2
7.9
306 |
.2
4.8
186 |
.3
1.3
51 |
.1
.4
15 |
.4
19.1
740 |
.2
30.6
1,186 |
.2
100.0
3,881 |
| 10: METHAMPHETAMINE |
3.7
22.9
23,283 |
2.7
5.2
5,290 |
3.9
4.6
4,630 |
2.0
.4
394 |
2.6
.4
409 |
7.6
12.5
12,716 |
8.6
54.0
54,768 |
5.7
100.0
101,490 |
| 11: OTHER AMPHETAMINES |
.9
29.5
5,783 |
.4
4.0
775 |
.8
4.8
938 |
.5
.5
106 |
.9
.7
137 |
1.9
16.0
3,129 |
1.4
44.5
8,704 |
1.1
100.0
19,572 |
| 12: OTHER STIMULANTS |
.1
27.8
354 |
.0
6.9
88 |
.1
7.2
92 |
.3
3.9
50 |
.1
.8
10 |
.1
14.1
179 |
.1
39.2
499 |
.1
100.0
1,272 |
| 13: BENZODIAZEPINES |
.4
37.3
2,635 |
.6
16.4
1,162 |
.9
15.1
1,069 |
.1
.3
24 |
.4
.8
59 |
.6
13.6
963 |
.2
16.3
1,155 |
.4
100.0
7,067 |
| 14: OTHER TRANQUILIZERS |
.1
35.0
329 |
.0
9.1
86 |
.1
11.1
104 |
.2
3.7
35 |
.0
.7
7 |
.0
8.9
84 |
.0
31.5
296 |
.1
100.0
941 |
| 15: BARBITURATES |
.1
40.7
624 |
.1
11.4
175 |
.2
12.6
193 |
.0
.1
2 |
.1
1.0
16 |
.1
13.1
200 |
.1
21.0
322 |
.1
100.0
1,532 |
| 16: OTHER SEDATIVES OR HYPNOTICS |
.2
37.1
1,050 |
.2
14.6
414 |
.3
12.4
350 |
.1
1.0
27 |
.1
.8
23 |
.2
9.9
279 |
.1
24.3
687 |
.2
100.0
2,830 |
| 17: INHALANTS |
.1
30.0
344 |
.0
7.0
80 |
.1
12.0
138 |
.3
4.7
54 |
.0
.5
6 |
.1
12.4
142 |
.1
33.3
382 |
.1
100.0
1,146 |
| 18: OVER-THE- COUNTER MEDICATIONS |
.0
29.0
175 |
.0
9.6
58 |
.1
16.4
99 |
.2
6.1
37 |
.1
2.0
12 |
.0
11.8
71 |
.0
25.2
152 |
.0
100.0
604 |
| 20: OTHER |
.5
34.7
2,914 |
.3
7.4
620 |
.7
10.6
891 |
.9
2.1
176 |
.2
.4
37 |
1.1
22.9
1,923 |
.3
21.9
1,845 |
.5
100.0
8,406 |
| COL TOTAL |
100.0
35.2
627,269 |
100.0
10.8
193,471 |
100.0
6.7
120,133 |
100.0
1.1
19,702 |
100.0
.9
16,016 |
100.0
9.4
168,144 |
100.0
35.8
639,660 |
100.0
100.0
1,784,395 |
|
| Color coding: |
<-2.0 |
<-1.0 |
<0.0 |
>0.0 |
>1.0 |
>2.0 |
Z |
| N in each cell: |
Smaller than expected |
Larger than expected |
|
|
|
| Allocation of cases |
| Valid cases |
1,784,395 |
Cases with invalid codes on
row or column variable |
98,189 |
| Total cases |
1,882,584 |
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Note that the colors in the table are also generated by the government's data, and are also very interesting, particularly related to marijuana/hashish.
The next chart deals with whether marijuana is mentioned at all in connection with treatment (at the admission interview).
Note that in only 24% of individual referrals to treatment is marijuana even mentioned. When you look at all treatment cases where marijuana is mentioned at admission (not necessarily the drug of treatment, but mentioned as having used it), almost half came through criminal justice referrals.
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SDA 1.3: Tables
Treatment Episode Data Set, 2002
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Data run Aug 03, 2004 (Tue 07:30 PM EDT) |
| Variables |
| Role |
Name |
Label |
Range |
MD |
Dataset |
| Row |
MARFLG |
MARIJUANA/HASHISH REPORTED AT ADM. |
0-1 |
|
1 |
| Column |
PSOURCE |
PRINCIPAL SOURCE OF REFERRAL |
1-7 |
-9 |
1 |
|
| Frequency Distribution |
Cells contain:
-Column percent
-Row percent
-N of cases |
PSOURCE |
1
INDIVIDUAL (INCLUDES SELF-REFERRAL) |
2
ALCOHOL/ DRUG ABUSE CARE PROVIDER |
3
OTHER HEALTH CARE PROVIDER |
4
SCHOOL (EDUCATIONAL) |
5
EMPLOYER/ EAP |
6
OTHER COMMUNITY REFERRAL |
7
COURT/ CRIMINAL JUSTICE REFERRAL/ DUI/DWI |
ROW
TOTAL |
| MARFLG |
0: SUBSTANCE NOT REPORTED |
75.9
41.2
485,147 |
70.5
11.6
136,812 |
69.6
7.3
86,025 |
30.1
.5
6,397 |
63.1
.9
10,296 |
63.1
9.3
109,044 |
52.7
29.3
345,099 |
64.7
100.0
1,178,820 |
| 1: SUBSTANCE REPORTED |
24.1
24.0
154,281 |
29.5
8.9
57,298 |
30.4
5.8
37,549 |
69.9
2.3
14,844 |
36.9
.9
6,016 |
36.9
9.9
63,787 |
47.3
48.2
310,105 |
35.3
100.0
643,880 |
| COL TOTAL |
100.0
35.1
639,428 |
100.0
10.6
194,110 |
100.0
6.8
123,574 |
100.0
1.2
21,241 |
100.0
.9
16,312 |
100.0
9.5
172,831 |
100.0
35.9
655,204 |
100.0
100.0
1,822,700 |
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| Color coding: |
<-2.0 |
<-1.0 |
<0.0 |
>0.0 |
>1.0 |
>2.0 |
Z |
| N in each cell: |
Smaller than expected |
Larger than expected |
|
|
|
| Allocation of cases |
| Valid cases |
1,822,700 |
Cases with invalid codes on
row or column variable |
59,884 |
| Total cases |
1,882,584 |
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| Datasets |
| 1 |
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/SDA/SAMHDA/04022-0001 |
| 2 |
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/SDA/SAMHDA/04022-0001 |
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CSM, UC Berkeley
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