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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Psychol Addict Behav. Author manuscript; available in PMC 2010 June 1.
Published in final edited form as:
PMCID: PMC2777754

Family conflict and depression in HIV-negative heterosexuals: The role of methamphetamine use


Previous research has reported elevated levels of depressive symptoms among methamphetamine users, but little attention has been paid to possible links between family environment and psychological distress. This study examined relationships between family conflict, substance use, and depressive symptoms in a sample of 104 heterosexual methamphetamine users in San Diego, CA. Eighty-nine percent of the sample reported conflict with a family member in the past year. Conflict was reported most often with parents and siblings. Sources of conflict included drug use, lifestyle issues, interpersonal and communication issues, and concern for other family members. In regression analyses, being female, being a polydrug user, and facing social and legal stressors were associated with higher levels of family conflict. Multiple regression analyses also revealed a positive association between family conflict and depressive symptoms. Contrary to expectation, methamphetamine dose did not moderate the relationship between family conflict and depressive symptoms. Reducing family conflict may be an important first step toward ameliorating depressive symptoms and creating more supportive environments for methamphetamine users who are in urgent need of effective interventions.

Keywords: methamphetamine, family conflict, depressive symptoms, heterosexuals, gender differences


Family conflict has been associated with increased depressive symptomatology in a variety of populations, including drug and alcohol users (Nolen-Hoeksema, Wong, Fitzgerald, & Zucker, 2006; Papp, Goeke-Morey, & Cummings, 2007; Semple, 1992; Semple et al., 1997). From a clinical perspective, substance abuse often figures prominently in the relationship between family conflict and psychological distress (Mallett, Rosenthal, & Keys, 2005). Studies of adult substance-using populations have identified family conflict as a contributing factor to relapse (Sun, 2007), a trigger for heavy drinking among alcoholics with personality disorders (Smyth & Washousky, 1995), and a factor associated with injection frequency and with lower subjective quality of life among opiate addicts (Karow, Verthein, Krausz, & Schaefer, 2008; Knight & Simpson, 1996). To our knowledge, no studies have examined the relationship between family conflict, substance use, and psychological distress among methamphetamine users.

Methamphetamine is a powerful illicit stimulant that is available throughout the United States and increasingly worldwide (e.g., Morris & Parry, 2006; Reid, Devaney, & Baldwin, 2006). Recent studies indicate that methamphetamine use is associated with psychosocial problems, including elevated levels of depressive symptoms (Semple, Patterson & Grant, 2005; Shoptaw, Peck, Reback, & Rotheram-Fuller, 2003), interpersonal conflict (Sun, 2007) and personal stressors (Semple, Patterson, & Grant, 2005).

We propose that the relationship between methamphetamine use, depression, and family conflict can be considered within the conceptual framework of a stress process model (Pearlin, Menaghan, Lieberman, & Mullan, 1981). In this research, family conflict is viewed a primary stressor and depressive symptoms represent the health outcome of interest. The impact of stressors can be buffered by psychosocial resources (e.g., coping, social support) or stressors can combine with other aspects of the social environment to intensify negative health outcomes (i.e., moderating effects).

We investigated associations between family conflict, amount of methamphetamine used, and depressive symptoms in a sample of heterosexual methamphetamine users. Three research questions were addressed: 1) What are the correlates of family conflict?; 2) Is family conflict associated with depressive symptoms?; and 3) Does amount of methamphetamine used moderate the relationship between family conflict and depressive symptoms? In this study, we hypothesized that the impact of family conflict on depressive symptoms would be greater for those who reported using larger amounts of methamphetamine.

Identifying the correlates of family conflict and understanding the association between family conflict and depressive symptoms may help to inform the development of interventions for methamphetamine users. For example, interventions aimed at enhancing communication skills and interpersonal problem-solving skills might be effective in reducing occurrences of family conflict and improving psychological well-being.


Sample selection

These analyses used baseline data from a sample of 104 HIV-negative, heterosexually-identified men and women who were enrolled in the FASTLANE-II research project at the University of California, San Diego (UCSD). The protocol is a nine-session, individual counseling program that uses motivational interviewing concepts (Miller & Rollnick, 1991), cognitive behavioral therapy (A. T. Beck, Rush, Shaw, & Emery, 1979), and social cognitive strategies (Bandura, 1986) to reduce high-risk sexual practices, depressive symptoms, and methamphetamine use. Eligible participants were at least 18 years of age, male or female, HIV-negative, self-identified as heterosexual, reported having unprotected vaginal or anal sex with at least one opposite-sex partner during the previous two months, and reported no sex with a same-sex partner during this timeframe. Eligible participants also had to report using methamphetamine at least twice during the past two months and at least once during the past 30 days. Exclusion criteria were: not sexually active or always used condoms in the past two months; sex with a spouse or steady partner only; active psychotic symptoms or suicidal ideation; and currently enrolled in a formal outpatient or residential drug treatment program. Individuals with a score of 3 or less on the 7-item Beck Depression Inventory-Fast Screen for medical patients (BDI-FS) (A. T. Beck, Steer, & Brown, 2000) were also excluded. BDI-FS scores less than 3 are associated with mild depressive symptoms such that individuals in this scoring range are not appropriate candidates for mood regulation counseling. The FASTLANE-II research protocol was approved by UCSD’s Human Research Protections Program. Data were gathered using audio-CASI technology (Turner et al., 1998). As shown in Table 1, the sample was predominantly male, African American or Latino, never married, living with another adult in a non-sexual relationship or living alone, unemployed, with a high school diploma or less, an income of less than or equal to $19,999 per year, and an average age of 37 years. Using the SSAGA, about 94% of the sample met criteria for methamphetamine dependence (Bucholz et al., 1994; 1995). Three gender differences were identified. Females were significantly more likely to be married and were less educated than males. Males used methamphetamine on a significantly greater number of days in the previous 30 days compared to females.

Table 1
Sample characteristics of HIV-negative, heterosexual methamphetamine users by gender


Family conflict

Family conflict was defined as overt disagreement between the participant and any family member to whom s/he was related through birth, marriage, or adoption (Semple, 1992). Participants were asked to indicate how much disagreement they had with anyone in their family in the past year because: “They don’t accept you for who you are”; “They are critical of your lifestyle”; “They think that you can change the way you are”; “They seem to avoid you”; and “They don’t approve of your partner.” Items were measured on a 4-point scale ranging from 1 (no disagreement) to 4 (quite a bit of disagreement). Cronbach’s alpha for the scale was 0.86. Participants were also asked: “What is the primary source of disagreement or conflict with your (mother/father)?” Responses were recorded and analyzed using qualitative strategies (Miles & Huberman, 1984).

Socio-demographic characteristics

Age was represented by a continuous variable. Education, marital status, income, and living arrangement were treated as categorical variables. Gender, race, and employment status were coded as binary variables.

Substance use variables

Methamphetamine use was measured as the number of grams of methamphetamine consumed in the past 30 days. Alcohol use was measured by two items from the Alcohol Use Disorders Identification Test (AUDIT): “How often do you have a drink containing alcohol?” (0 = never to 4 = four or more times a week); “How many drinks containing alcohol do you have on a typical day when you are drinking? (0 =1 or 2 drinks to 4 = 10 or more drinks) (Fiellin, Reid, & O’Connor, 2000; National Institute on Alcohol Abuse and Alcoholism, 1995; Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). Participants were also presented with a list of 15 drugs (e.g., marijuana, cocaine, heroin) and asked how often they had used each drug in the past month (Vlahov et al., 1991). Response categories ranged from 0 (never) to 6 (every day). A summary variable was created to represent number of illicit drugs used in the past month. Injection drug use in the past two months was represented by a dichotomous variable (1 = yes, 0 = no).

Personal stressors

Participants were asked about their exposure to three types of personal stressors, including physical health problems (e.g., diarrhea), mental or emotional health problems (e.g., paranoia), and social and legal problems (e.g., problems at work, trouble with the law). Response categories for each stressor were coded 1 (yes) or 0 (no).

Depressive symptoms

Depressive symptoms were assessed using the Beck Depression Inventory (BDI-II) (A.T. Beck, Steer, & Brown, 1996). The BDI-II is composed of 21 items, each of which has four graded statements ordered (0–3) to show increasing depressive symptoms. Summary scores thus ranged from 0 to 63. Cronbach’s alpha for the BDI-II in this sample was 0.91.

Emotional support

Emotional support was measured using a seven-item scale that assesses the availability of family members and friends who are perceived as caring, trustworthy, uplifting, and as confidants (Pearlin, Mullan, Semple, & Skaff, 1990). Items were rated on a four-point scale ranging from 1 (strongly disagree) to 4 (strongly agree). The alpha coefficient for this scale in the present sample was 0.92.

Data Analysis

The distribution of all variables was examined. Alcohol use and the number of grams of methamphetamine used in the past 30 days revealed skewness; both variables were corrected using a log 10 transformation. T-tests and contingency table analysis were used to examine gender differences in continuous and categorical variables, respectively. To address research question one, four separate regressions were performed. In regression 1, family conflict was regressed on socio-demographic variables. In regressions 2 and 3, family conflict was regressed on substance use variables and personal stressors, respectively. In regression 4, variables that were significant in regressions 1, 2, and 3 were entered into a final model. To address research questions two and three, we performed a hierarchical regression with depression as the dependent variable. In step 1, gender, emotional support, and number of grams of methamphetamine were entered together as control variables. In step 2, family conflict was entered into the regression. In step 3, the interaction term (family conflict × grams of methamphetamine) was entered into the regression equation. Gender, number of grams of methamphetamine, and emotional support were treated as control variables because previous research has demonstrated an association between each variable and depressive symptoms (Semple, Patterson & Grant, 2005; Stockard & Johnson, 1992).


Prevalence of family conflict

Eighty-nine percent of the sample reported some conflict with a family member in the past year. Females reported significantly higher levels of family conflict compared to males (2.6 versus 2.1, respectively, t = 2.6, p < 0.01, range = 1 to 4). Methamphetamine users reported conflict with the following family members (in rank order): parents (57.0%), siblings (48.4%), children (23.7%), aunts or uncles (19.4%), cousins (17.2%), spouse (16.1%), and grandparents (5.4%). No gender differences were found regarding the type of family member with whom conflict was reported.

Conflict with parents

Parents were the most frequently named category of family members with whom conflict was experienced. Four sources of conflict were identified: 1) conflict relating to the participant’s use of methamphetamine; 2) conflict stemming from the participant’s lifestyle; 3) conflict stemming from interpersonal and communication issues; and 4) conflict related to concerns about other family members. Males and females did not differ in the percentage reporting conflict with mothers (80.5% vs. 83.3%, χ2 = 0.10, p > 0.05) or fathers (60.0% vs. 72.7%, χ2 = 0.66, p > 0.05), respectively. Mean levels of conflict with parents did not differ for males and females (2.4 vs. 2.7, t = 1.1, p > 0.05), respectively. Table 2 presents examples of conflict issues with parents.

Table 2
Dimensions of Parental Conflict

Correlates of family conflict

In separate equations, family conflict was regressed on socio-demographic characteristics, substance use factors, and personal stressors. In the first regression, gender was the only significant variable; being female was positively associated with family conflict. In the second regression, number of drugs used in the past month was positively associated with family conflict. In the third regression, social and legal stressors had a significant positive association with family conflict. The three variables that were significant in the above regressions were examined together in a fourth regression; all three variables were associated with higher levels of family conflict (see Table 3).

Table 3
Family conflict regressed on socio-demographic characteristics (Regression 1), substance use factors (Regression 2), personal stressors (Regression 3), and final equation with significant variables identified in regressions 1–3 (Regression 4) ...

Family conflict and depressive symptoms

A hierarchical regression was used to examine the effects of family conflict on depressive symptoms. In step one, the control variables (gender, number of grams of methamphetamine used, emotional support) together accounted for 11 percent of the variance in depressive symptoms. Emotional support was the only significant variable at this step. In step 2, family conflict accounted for an additional 10 percent of variance in the depressive symptoms. Family conflict was positively associated with depressive symptoms (see Table 4).

Table 4
Beck depression scores regressed on family conflict and family conflict × grams of methamphetamine controlling for gender, amount of methamphetamine useda, and emotional support (N = 104)

Does the amount of methamphetamine used moderate the relationship between family conflict and depressive symptoms?

In step 3 of the hierarchical regression, the family conflict × grams of methamphetamine interaction term was added to the regression equation. Family conflict and emotional support yielded direct and independent effects on depressive symptoms. The non-significant interaction term revealed that amount of methamphetamine used did not moderate the relationship between family conflict and depressive symptoms. Results are presented in Table 4.


In this study of heterosexual methamphetamine users, family conflict was significantly associated with increased levels of depressive symptoms. This suggests that reducing family conflict may be an important intervention goal in the treatment of depressive symptoms among methamphetamine users. A variety of family therapies with varying degrees and types of family involvement are currently available. For example, Attachment-Based Family Therapy (ABFT) and Family-focused Cognitive Behavioral Therapy have yielded positive treatment outcomes among adolescents with clinical levels of depression and anxiety (Siqueland, Rynn, & Diamond, 2005; Wood, Piacentini, Southam-Gerow, Chu, & Sigman, 2006).

The development of successful interventions to reduce family conflict requires knowledge of the social contexts and conditions under which the conflict occurs. We found that significant correlates of family conflict included being a female, engaging in polydrug use, and experiencing social and legal stressors. These factors represent possible avenues of intervention in the treatment of psychologically-distressed methamphetamine users.

Contrary to expectation, the amount of methamphetamine used did not moderate the relationship between family conflict and depressive symptoms. Our data revealed that methamphetamine use and related lifestyle issues were primary sources of conflict; thus, it is not surprising that family conflict exerted its negative psychological effect at all levels of use. This explanation is consistent with previous research that has identified high levels of social stigma associated with methamphetamine use (Semple, Grant, & Patterson, 2005). Future studies should examine the role of social stigma in the development and resolution of family conflict.

Mean levels of family conflict were modest for all participants in this study; however, the psychological impact was significant. It is plausible that negative family interactions have a greater effect on psychological well-being because they are rarer and thus more salient than positive ones (Rook, 1984). The low levels of conflict reported by our sample might be a function of our definition of family conflict or it could reflect avoidant coping behavior on part of the participant, family members, or both. It might also be informative in future studies to examine differences between individuals who report family conflict and those who do not.

This investigation suggests additional research directions. Among adolescents, interpersonal conflict has been identified as an antecedent of substance use and depression (Aseltine et al., 1998; Brody & Forehand, 1993; Siebenbruner et al., 2006). Future studies should use prospective data to identify pathways that connect family conflict, methamphetamine use, and depressive symptoms in samples of adult drug users. Although much research has focused on the neurobiology of addiction (Goodman, 2008), our data suggest that situational factors such as family conflict should also be considered in the onset of substance use.

Despite the potential clinical importance of our research findings, several study limitations need to be acknowledged. First, the findings should not be generalized to the more global population of methamphetamine users since it is possible that participants had higher levels of depressive symptoms and sexual risk-taking, and used more methamphetamine than non-participants. Another study limitation stems from the use of self-report to measure family conflict. As reported in previous studies of the effects of emotional distress upon patient perceptions (e.g., Gross et al., 2007), it is plausible that depressed mood influenced participants’ perceptions of family interactions, resulting in more reports of family conflict. It is also possible that the disparate timeframes associated with our measures of depressive symptoms and family conflict resulted in an underestimation of the association between these two variables. Concurrent measures of both constructs should be used in future studies. Moreover, the cross-sectional design of this study makes it impossible to determine causality in the relationship between family conflict and depressive symptoms. Future research should use prospective data and longitudinal analyses to examine causality and bi-directional causation. Future studies should also include comprehensive assessments of lifetime history and current psychiatric status.


Further research on the relationship between family conflict and family support could help to inform the development of successful treatment programs. In the present study, emotional support from family and friends was associated with fewer depressive symptoms. This finding is consistent with previous research, which has identified supportive family relationships and reductions in conflict among family members as factors associated with help-seeking and better quality of life among substance abusers (Karow et al., 2008; Neale, Sheard, & Tompkins, 2007).


The authors would like to thank the participants in this study for their time and support, and Mr. Brian R. Kelly for assistance with editing the manuscript. Support for this work was provided, in part, by National Institute of Mental Health (NIMH) grant R01 MH061146 (Reducing HIV/STD Risk, Methamphetamine Use, and Depression Among Heterosexuals), National Institute of Drug Abuse (NIDA) grant R01 DA021115 (Behavior Change and Maintenance Intervention for HIV+ MSM Methamphetamine Users), and the Department of Veterans Affairs.


Publisher's Disclaimer: The following manuscript is the final accepted manuscript. It has not been subjected to the final copyediting, fact-checking, and proofreading required for formal publication. It is not the definitive, publisher-authenticated version. The American Psychological Association and its Council of Editors disclaim any responsibility or liabilities for errors or omissions of this manuscript version, any version derived from this manuscript by NIH, or other third parties. The published version is available at


  • Aseltine RH, Gore S, Colten ME. The co-occurrence of depression and substance abuse in late adolescence. Developmental Psychopathology. 1998;10(3):549–570. [PubMed]
  • Bandura A. Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall; 1986.
  • Beck AT, Rush AJ, Shaw BF, Emery G. Cognitive therapy of depression. New York: Guilford Press; 1979.
  • Beck AT, Steer RA, Brown GK. Manual for the Beck Depression Inventory,II. San Antonio, TX: Psychological Corporation; 1996.
  • Beck AT, Steer RA, Brown GK. Manual for the BDI Fastscreen for medical patients. The Psychological Corporation; 2000. [no city]
  • Brody GH, Forehand R. Prospective associations among family form, family processes, and adolescents' alcohol and drug use. Behavior Research and Therapy. 1993;31(6):587–593. [PubMed]
  • Bucholz KK, Cadoret R, Cloninger RD, Dinwiddie SH, Hesselbrock VM, Nurnberger JI, Reich TR, Schmidt I, Schuckit MA. A new semi-structured psychiatric interview for use in genetic linkage studies. A report on the reliability of the SSAGA. Journal of Studies in Alcohol. 1994;55:149–158. [PubMed]
  • Bucholz KK, Hesselbrock VM, Shayka JJ, Nurnberger JI, Schuckit MA, Schmidt I, Reich T. Reliability of individual diagnostic criterion items for psychoactive substance dependence and the impact on diagnosis. Journal of Studies in Alcohol. 1995;56:500–505. [PubMed]
  • Fiellin DA, Reid MC, O’Connor PG. Screening for alcohol problems in primary care: A systematic review. Archives of Internal Medicine. 2000;160(13):1977–1989. [PubMed]
  • Goodman A. Neurobiology of addiction. An integrative review. Biochemical Pharmacology. 2008;75(1):266–322. [PubMed]
  • Gross R, Brammli-Greenberg S, Tabenkin H, Benbassat J. Primary care physicians’ discussions of emotional distress and patient satisfaction. International Journal of Psychiatric Medicine. 2007;37(3):331–345. [PubMed]
  • Karow A, Verthein U, Krausz M, Schafer I. Association of personality disorders, family conflicts and treatment with quality of life in opiate addiction. European Addiction Research. 2008;14(1):38–46. [PubMed]
  • Knight DK, Simpson DD. Influences of family and friends on client progress during drug abuse treatment. Journal of Substance Abuse. 1996;8(4):417–429. [PubMed]
  • Mallett S, Rosenthal D, Keys D. Young people, drug use and family conflict: Pathways into homelessness. Journal of Adolescence. 2005;28(2):185–199. [PubMed]
  • Miles M, Huberman A. Qualitative data analysis: A source book for new methods. Beverly Hills: Sage Publications; 1984.
  • Miller WR, Rollnick S. Motivational interviewing: Preparing people to change addictive behavior. New York, NY: Guilford Press; 1991.
  • Morris K, Parry C. South African methamphetamine boom could fuel further HIV. Lancet Infectious Diseases. 2006;6(8):471. [PubMed]
  • National Institute on Alcohol Abuse and Alcoholism. The physician’s guide to helping patients with alcohol problems. NIH Pub. No. 95-3769. Rockville, MD: National Institutes of Health; 1995.
  • Neale J, Sheard L, Tompkins CN. Factors that help injecting drug users to access and benefit from services: A qualitative study. Substance Abuse Treatment and Prevention Policy. 2007;2:31. [PMC free article] [PubMed]
  • Nolen-Hoeksema S, Wong MM, Fitzgerald H, Zucker RA. Depressive symptoms over time in women partners of men with and without alcohol problems. Journal of Abnormal Psychology. 2006;115(3):601–609. [PMC free article] [PubMed]
  • Papp LM, Goeke-Morey MC, Cummings EM. Linkages between spouses’ psychological distress and marital conflict in the home. Journal of Family Psychology. 2007;21(3):533–537. [PubMed]
  • Pearlin LI, Menaghan EG, Lieberman MA, Mullan JT. The stress process. Journal of Health and Social Behavior. 1981;22(4):337–356. [PubMed]
  • Pearlin LI, Mullan JT, Semple SJ, Skaff MM. Caregiving and the stress process: An overview of concepts and their measures. Gerontologist. 1990;30(5):583–594. [PubMed]
  • Reid G, Devaney ML, Baldwin S. Drug production, trafficking and trade in Asia and Pacific Island countries. Drug and Alcohol Review. 2006;25(6):647–650. [PubMed]
  • Rook KS. The negative side of social interaction: Impact on psychological well-being. Journal of Personality and Social Psychology. 1984;46(5):1097–1108. [PubMed]
  • Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption,II. Addiction. 1993;88(6):791–804. [PubMed]
  • Semple SJ. Conflict in Alzheimer’s caregiving families: Its dimensions and consequences. Gerontologist. 1992;32(5):648–655. [PubMed]
  • Semple SJ, Grant I, Patterson TL. Utilization of drug treatment programs by methamphetamine users: The role of social stigma. American Journal on Addictions. 2005;14(4):367–380. [PubMed]
  • Semple SJ, Patterson TL, Grant I. Methamphetamine use and depressive symptoms among heterosexual men and women. Journal of Substance Use. 2005;10(1):31–47.
  • Semple SJ, Patterson TL, Temoshok LR, Straits-Troster K, Atkinson JH, Koch W, et al. Family conflict and depressive symptoms: A study of HIV-seropositive men. AIDS and Behavior. 1997;1:53–60.
  • Shoptaw S, Peck J, Reback CJ, Rotheram-Fuller E. Psychiatric and substance dependence comorbidities, sexually transmitted diseases, and risk behaviors among methamphetamine-dependent gay and bisexual men seeking outpatient drug abuse treatment. Journal of Psychoactive Drugs. 2003:161–168. [PubMed]
  • Siebenbruner J, Englund MM, Egeland B, Hudson K. Developmental antecedents of late adolescence substance use patterns. Developmental Psychopathology. 2006;18(2):551–571. [PubMed]
  • Siqueland L, Rynn M, Diamond GS. Cognitive behavioral and attachment based family therapy for anxious adolescents: Phase I and II studies. Journal of Anxiety Disorders. 2005;19(4):361–381. [PubMed]
  • Smyth NJ, Washousky RC. The coping styles of alcoholics with Axis II disorders. Journal of Substance Abuse. 1995;7(4):425–435. [PubMed]
  • Stockard J, Johnson MM. Sex and gender in society. 2nd ed. Englewood Cliffs, NJ: Prentice-Hall; 1992.
  • Sun AP. Relapse among substance-abusing women: Components and processes. Substance Use & Misuse. 2007;42(1):1–21. [PubMed]
  • Turner CF, Forsyth BH, O’Reilly J, Cooley PC, Smith TK, Rogers SM, et al. Automated self-interviewing and the survey measurement of sensitive behaviors. In: Couper MP, Baker RP, Bethlehem J, Clark CZF, Martin J, Nicholls WLN, et al., editors. Computer assisted survey information collection. New York: Wiley; 1998.
  • Vlahov D, Anthony JC, Munoz A, Margolick J, Nelson KE, Celentano DD, et al. The ALIVE study, a longitudinal study of HIV-1 infection in intravenous drug users: Description of methods. Journal of Drug Issues. 1991;21(4):759–776. [PubMed]
  • Wood JJ, Piacentini JC, Southam-Gerow M, Chu BC, Sigman M. Family cognitive behavioral therapy for child anxiety disorders. Journal of the American Academy of Child Adolescent Psychiatry. 2006;45(3):314–321. [PubMed]