2. Methamphetamine: A 2005 Update Richard A. Rawson, Ph.D. UCLA Integrated Substance Abuse Programs Los Angeles, California rrawson@mednet.ucla.edu

3. Speed It is methamphetamine powder ranging in color from white, yellow, orange, pink, or brown. Color variations are due to differences in chemicals used to produce it and the expertise of the cooker. Other names: shabu, crystal, crystal meth, crank, tina, yaba

4. Ice High purity methamphetamine crystals or coarse powder ranging from translucent to white, sometimes with a green, blue, or pink tinge.

5. According to surveys and estimates by WHO and UNDCP, methamphetamine is the most widely used illicit drug in the world except for cannabis. World wide it is estimated there are over 42 million regular users of methamphetamine, as compared to approximately 15 million heroin users and 10 million cocaine users Scope of the Methamphetamine Problem Worldwide

6. IHS-Wide RPMS PCC Outpatient Encounters for Amphetamine Related Visit by Calendar Year

7. The Eastward Spread of Methamphetamine

10. Methamphetamine: A Growing Menace in Rural America In 1998, rural areas nationwide reported 949 methamphetamine labs. Last year, 9,385 were reported. This year, 4,589 rural labs had been reported as of July 26. Source: El Paso Intelligence Center (EPIC), U.S. DEA

11. Stove Top Labs The active ingredient in making methamphetamine is ephedrine or pseudoephedrine, commonly found in over the counter cold remedies.

12. Meth Lab Seizures A small percentage of labs seized are labeled “Super Labs” and are capable of producing over 10 lbs per batch. Super Labs are operated by Mexican National Drug Trafficking Organizations (MNDTO’s), and supply the majority of meth to the market.

13. Clandestine Meth Lab Equipment

15. A Major Reason People Take a Drug is they Like What It Does to Their Brains A Major Reason People Take a Drug is they Like What It Does to Their Brains

18. Methamphetamine abusers have abnormal brain activity

19. 0 0 50 100 150 200 0 0 60 120 180 Time (min) % of Basal DA Output NAc shell Empty Box Feeding Source: Di Chiara et al. FOOD Natural Rewards Elevate Dopamine Levels

20. 0 0 100 200 300 400 500 600 700 800 900 1000 1100 0 0 1 1 2 2 3 3 4 4 5 hr Time After Amphetamine % of Basal Release DA DOPAC HVA Accumbens AMPHETAMINE 0 0 100 200 300 400 0 0 1 1 2 2 3 3 4 4 5 hr Time After Cocaine % of Basal Release DA DOPAC HVA Accumbens COCAINE 0 0 100 150 200 250 0 0 1 1 2 2 3 3 4 4 5hr Time After Morphine % of Basal Release Accumbens 0.5 1.0 2.5 10 Dose (mg/kg) MORPHINE 0 0 100 150 200 250 0 0 1 1 2 2 3 hr Time After Nicotine % of Basal Release Accumbens Caudate NICOTINE Source: Di Chiara and Imperato Effects of Drugs on Dopamine Levels

21. Methamphetamine Addiction The brains of people addicted to Methamphetamine are different than those of non-addicts

26. Cocaine Methamphetamine Cocaine and Methamphetamine Effects Compared

27. Prolonged Drug Use Changes the Brain In Fundamental and Long-Lasting Ways

28. Sample Characteristics 305 Adolescents (13-18 years old) Average Age ~ 16yrs old (sd=1.138) Gender: 70.2% Males Ethnicity: 55.3% White & 33.1% Latino

29. Age Distribution

30. Ethnic Identification

31. Drug Use History (Ever Used?) Alcohol 220 (80.9%) Pot 257 (94.5%) LSD 61 (22.4%) Cocaine/Crack 72 (26.5%) Methamphetamine 131 (48.2%) MDMA (Ecstasy) 45 (16.5%) Opiates (Heroin, Codeine) 24 (8.8%) N=272

32. Drug Use History (Ever Used) *Missing responses

33. Drug Use by Gender

34. Drug Use by Age *P<.05

35. Drug Use by Ethnicity *P<.05

36. Parental & Peer Factors Family dysfunction was high for both groups. –64.3% reported parental drug use. –60.2% had divorced or separated parents. –40% lived in single-headed households (mothers only). Involvement with drug-using peers was high (65.9%).

37. Social Problems by Drug Use

38. Psychological Distress by Drug Use *P<.05

39. Treatment Response by Drug Use Total (N=275*) Total (N=275*) *30 Missing CompletedDropped 139(50.5%)136(49.5%) METH(n=85) 37 (43.5%) (43.5%)46(54.1%) OTHER(n=190) 102(56.5%)88 (46.3%) (46.3%)

40. Overall Treatment Response % Completed Age Pre-Adol 13-14 (n=33) 15 (45.5%) Mid-Adol 15-16 (n=149) 66 (44.3%) Late Adol 17-18 (n=113) Late Adol 17-18 (n=113) 51 (45.1%) Gender Males (n=214) 100 (46.7%) Females (n=91) 39 (42.9%) Race* White (n=167) 81 (48.5%) Non-white (n=135) 56 (41.5%)

41. Drug Use at Discharge More than 50% of the sample reported using drugs or alcohol in the previous 30 days at discharge. –50% reported using their Drug of choice –20% reported using alcohol –15% reported using other drugs (not DOC)

42. Women and Meth

43. Meth and Women: Typical gender ratio of heroin users in treatment : 3 men to 1 woman Typical gender ratio of cocaine users in treatment : 2 men to 1 woman Typical gender ratio of methamphetamine users in treatment : 1 man to 1 woman * *among large clinical research populations

44. Drug Use by Gender

45. Self-Reported Reasons for Starting Methamphetamine Use

48. My sexual drive is increased by the use of … (Rawson et al., 2002)

49. My sexual pleasure is enhanced by the use of … (Rawson et al., 2002)

50. My sexual performance is improved by the use of … (Rawson et al., 2002)

51. CSAT Methamphetamine Treatment Project: Cross-Site Sample Description 1,016 clients Average age was 32.8 years 55% female 60% Caucasian 12.2 years of education on average 16% currently married 31% awaiting charges, trial, or sentencing

52. Methamphetamine Use History Avg. years of lifetime use:7.54 Avg. days used in past 30:11.53 Percent that usually smoked:65%

53. Violence Issues in Lifetime 78% experienced violence 39% experienced sexual abuse 81% experienced one or the other 36% experienced both

54. Psychological Issues in Lifetime 60% depressed 56% anxiety 45% memory problems 43% violence control problems 34% suicidal thoughts 32% received medication 9% memory problems

55. Gender Differences in Violence History (% Ever) Female (85%) Male (70%) Partner80%26% Friend16%38% Other14%43%

56. Gender Differences in Partner Violence FemaleMale Ever threatened 63%26% Ever Isolated 65%37% Ever Afraid 27%10%

57. Gender Differences in Sexual Abuse History (% Ever) Female (58%)Male (16%) Parent14%4% Sibling22%6% Partner32%7%

58. Analyses reveal that a history of physical or sexual violence (controlling for gender) is significantly related to a number of negative outcomes. These results suggest the importance of understanding client background factors before they enter treatment.

59. Those Who Have Experienced Violence Have Higher Scores on the BSI and the BDI Violence No Violence BSI GSI 1.01.68 BSI PSDI 1.791.55 BSI PST 27.1720.72 BDI16.2112.86

60. Those Who Have Experienced Violence Have Higher Average Composite Scores on the ASI Violence No Violence Drug.22.19 Medical.23.14 Employment.57.46 Family/Social.28.20 Psychiatric.25.17

61. Those Who Experienced Violence Were More Likely to Have Psychological Issues on the ASI Violence No Violence Depression64%44% Anxiety59%44% Violence Control Problems 48%27% Suicidal Thoughts 38%20% Psychiatric Medication 36%18% Suicide Attempts 24%12%

62. Implications Physical and sexual violence is related to psychological problems and drug use pattern differences Different types of traumas may have different outcomes and may affect people in different ways A history of trauma may be related to treatment engagement and outcome

63. Behavior Symptom Inventory (BSI) Scores at Baseline

64. Beck Depression Inventory (BDI) Scores at Baseline

65. Drug Endangered Children in California: Methamphetamine Use and Manufacture Nena Messina, Ph.D., Patricia Marinelli- Casey, Ph.D., Richard Rawson, Ph.D. UCLA Integrated Substance Abuse Programs

66. Children Inquisitive nature of young children makes them more prone to accidentally consuming toxic chemicals that are sometimes kept in unmarked containers in the refrigerator.

67. Children Hundreds of children are neglected by parents who are meth cooks. Nationally, over 20% of the seized meth labs in 2002 had children present. In Washington State, the counties of Grays Harbor, Spokane, Thurston, and Klickitat all reported that children were found at half the labs seized in 2002. In Lewis County, children were found at 60-70 %, and in Clark-Skamania, 35%.

68. Children Children who live in and around the area of the meth lab become exposed to the drug and its toxic precursors and byproducts. 80-90% of children found in homes where there are meth labs test positive for exposure to meth. Some are as young as 19 months old.

69. Children Children can test positive for methamphetamine by: –Having inhaled fumes during the manufacturing process –Coming into direct contact with the drug –Through second-hand smoke.

70. Children Hundreds of children are neglected by parents who are meth cooks. Nationally, over 20% of the seized meth labs in 2002 had children present. In Washington State, the counties of Grays Harbor, Spokane, Thurston, and Klickitat all reported that children were found at half the labs seized in 2002. In Lewis County, children were found at 60-70 %, and in Clark-Skamania, 35%.

71. Children In 2002, a total of 142 children were present at lab seizures in Riverside and San Bernardino Counties. Most children reported as being present during a seizure were school age.

72. Children Children are uniquely susceptible to neurological contamination in the environment because their brains are still developing. Children are uniquely susceptible to neurological contamination in the environment because their brains are still developing. Lead poisoning is an example of what the child is exposed to in these meth labs. A small amount of lead that may not affect an adult can cause neurological damage in a child.

73. Children are not small adults! Different diet Growing & developing rapidly Higher metabolic & respiratory rate Developing nervous system Unusual habits (hand-to-mouth behaviors; close to floor, contact with many surfaces, at risk for all poisonings) Biologic & developmental vulnerability

74. Drug Endangered Children Response Teams Multi-Need Families; Multi-Need Individuals Multi-Disciplinary Approach Spirit of Cooperation Sharing of Information Case Coordination for Best Family and Individual Outcome Why the Team Concept Is Needed and Works...

75. CORE TEAM MEMBERS: –LAW ENFORCEMENT (24/7) –CHILD PROTECTIVE SERVICES (24/7) –DISTRICT ATTORNEY’S OFFICE (24/7) –MEDICAL PERSONNEL (24/7) “AUXILIARY” TEAM MEMBERS: –MENTAL HEALTH & THERAPEUTIC PERSONNEL FOR CHILDREN –ENVIRONMENTAL SERVICES, FIRE, & PUBLIC HEALTH –DRUG TREATMENT PROVIDERS FOR PARENTS AND FAMILY MEMBERS DEC RESPONSE TEAM

76. States with DEC Response Teams DEC Team ` ` No DEC DEC Resource Center, 2001

77. States Having Received DEC Training from California DEC Training No Training DEC Resource Center, 2001

78. Methamphetamine Treatment Contingency Management Matrix Model

79. Investigating the use of contingency management to treat methamphetamine abuse Contingency management is arguably the most effective behavioral strategy for treating other types of drug abuse. Human laboratory investigations (Roll, Newton, Chudzynski & Fong, under review) suggest that methamphetamine use is amenable to modification via the presentation of alternative sources of reinforcement.

80. Combined data from several pilot studies (Roll, Huber, et al., in press; Roll & Shoptaw, in press All studies provided vouchers with specified monetary values for the provision of urine samples which indicated no recent methamphetamine use. Urines were collected under direct observation. Vouchers could be exchanged for goods or services that were congruent with developing a drug free lifestyle.

81. All trials were 12 weeks in duration and collected urine sample three times/week. All trials had a cognitive behavioral psychosocial platform that was administered by trained clinicians and delivered three times/week.

82. Participants 112 treatment-seeking methamphetamine users (29 CBT and 83 CBT + Contingency Management) mean age was 31.4 (sem 0.8) years. 62.7% were Caucasian, 30.1% were Hispanic, 2.4% were African American, 2.4% were African American, 2.4% were American Indian, and 2.4% were Pacific Islander 44.8% were employed full time 22.9% were married

85. CTN 006 methamphetamine data (Roll, et al.,in prep.) Used the variable magnitude of reinforcement procedure developed by Petry. 113 methamphetamine abusing individuals were part of the larger trial. Received the chance to win prizes for the provision of stimulant negative urine samples.

86. Methamphetamine Outcomes from CTN 006

88. Project Structure: Study Sites Billings, MTHonolulu, HI San Mateo, CA (2)San Diego, CA Concord, CACosta Mesa, CA Hayward, CA Coordinating Center UCLA Integrated Substance Abuse Programs Steering Committee Scientific Advisory Board Community Advisory Board

89. Baseline Demographics Participants Served (n)1016 Age (mean)32.8 years Education (mean)12.2 years Methamphetamine Use (mean)7.5 years Marijuana Use (mean)7.2 years Alcohol Use (mean)7.6 years

90. Gender Distribution of Participants

91. Sample Description

92. Ethnic Identification of Participants

93. Route of Methamphetamine Administration

94. Changes from Baseline to Treatment-end

95. Days of Methamphetamine Use in Past 30 (ASI) Possible is 0-30; t paired =20.90; p-value<0.000 (highly sig.)

96. Beck Depression Inventory (BDI) Total Scores Possible is 0-63; t paired =16.87; p-value<0.000 (highly sig.)

97. BSI Scores (mean) BL 1 Tx-end Paired t * Somatization0.70.57.67 Obsessive-Compulsive1.20.911.40 Interpersonal Sensitivity1.00.711.40 Depression1.20.811.98 Anxiety0.90.611.24 Hostility0.80.69.39 Phobic Anxiety0.60.48.47 Paranoid Ideation1.10.711.49 Psychoticism0.90.610.70 1 Possible, all scores, is 0-4; * all p-values<0.000 (highly sig.)

98. Positive Symptom Total (PST) from Brief Symptom Inventory (BSI) Possible is 0-53; t paired =14.33; p-value<0.000 (highly sig.)

99. Mean Number of Weeks in Treatment

100. Mean Number of UA’s that were MA-free during treatment

101. Figure 4. Percent completing treatment, by group

102. Figure 6. Participant self-report of MA use (number of days during the past 30) at enrollment, discharge, and 6-month follow-up, by treatment condition

103. Methamphetamine Route of Administration

104. Route of Methamphetamine Administration

105. Route of Administration by Site P<.05

106. Craving by Route P<.05

107. Drop Rates by Route P<.05

108. Treatment Length by Route P<.05

109. Treatment Completion by Route P<.05

110. MA-Free Samples by Route P<.05

111. BSI Psychiatric Symptoms by Route P<.05 Positive Symptom Total (PST)

112. Depression Symptoms by Route P<.05

113. Psychopathology and Route IDUs > likely to have a psychiatric disability. IDUs > likely to have prior hospitalizations for psychiatric problems.

114. Methamphetamine Methamphetamine User Tx Response vs Cocaine User Tx Response Methamphetamine User Tx Response vs Cocaine User Tx Response

115. Medical and Psychiatric Symptoms More MA users experienced headaches (p<.05) and over 25% of each group experienced chest pains. 7.7% of MA users and 5.8% of cocaine users reported loss of consciousness during the 30 days prior to treatment admission. MA users appeared more disturbed and more cognitively impaired than cocaine users.

116. Medical and Psychiatric Symptoms Hallucinations were reported by one-third of MA users and one quarter of cocaine users (p<.05). More MA users entered treatment in a state of severe depression (p<.05). A small portion of both groups reported suicidal ideation (6.9% and 2.8% respectively, p<.05). Anecdotal reports of the clinic staff suggest that the admission to treatment with intense paranoid ideation was much more frequent in MA users.

117. Medical and Psychiatric Symptoms MA Users %Cocaine Users % Current medical problems -Chest pain29.825.5 -Headaches*42.432.8 -Seizures2.04.2 -Loss of consciousness7.76.5 -Need medical treatment10.75.8 Current psychiatric problems -Depressed a lot*19.312.1 -Suicidal thoughts*6.92.8 -Want to injure others17.114.5 -Hallucinations*34.825.1 -Paranoid thoughts28.825.5 Previous psychiatric treatment14.416.5 *p<.05

118. Treatment Length by Stimulant Users

119. Response to Treatment There is no difference in the amount or type of treatment received. –The two groups were retained in treatment for the same duration, and the survival curves are nearly identical. Methamphetamine and cocaine users participated similarly in the program. Treatment outcomes, as measured by urine toxicology results, does NOT vary significantly between methamphetamine and cocaine users.

120. Hepatitis C by Route P<.05