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(p. 359) Substance Use Disorders 

(p. 359) Substance Use Disorders
Chapter:
(p. 359) Substance Use Disorders
Author(s):

Damaris J. Rohsenow

DOI:
10.1093/med-psych/9780190492243.003.0017
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date: 25 September 2018

Clinicians working with substance use disorders (SUDs) need good tools to help them evaluate patient needs, plan treatment strategies tailored to these individual needs, and monitor progress in treatment. This chapter provides an overview of the most widely used, psychometrically sound instruments that are potentially useful for clinicians working with clients with SUDs. Instruments that would probably only be used by researchers and commonly used, but psychometrically weak, instruments are not included. Accordingly, this chapter is not intended to provide an exhaustive list of available instruments, and someone’s preferred instrument may well be omitted. Nevertheless, most of the best instruments that are likely to be clinically useful are reviewed in the chapter. The focus is on alcohol and illicit drugs, not tobacco or other licit substances. However, because assessments for alcohol use disorders are covered in Chapter 18, measures specific to alcohol are not discussed here. Additional instruments used in research are described by Donovan and Marlatt (2005).

The Nature of Substance Abuse and Dependence

Whether called addiction, abuse, or dependence, patients with SUDs generally show a combination of physical indicators (generally an abstinence syndrome), a variety of serious or ongoing negative consequences of drug use that affect significant areas of their lives (including financial, employment, health, family, social relationships, and psychological function), and an apparent compulsion to seek and use drugs despite ongoing negative consequences. Many of the behaviors involved in getting the drugs also lead to victimization of others in terms of crime (usually committed to obtain funds to buy drugs) or physical victimization (e.g., gunshot wounds). As such, addiction has individual effects (physical, psychological, and family), community effects (social, employment, and financial burdens), and societal effects (crime, legal system, politics, and societal costs). However, for the practitioner, the primary focus is the individual with substance misuse (using the term in a broad sense), along with the consequences to that person and the effects of his or her drug use on his or her own network. The diagnostic criteria for SUDs are described later, but it should be noted that the terms “abuse,” “misuse,” or “addiction” are often used in the literature in a looser manner to refer to the person who continues to have ongoing use despite serious problems, regardless of whether formal diagnostic criteria for SUDs are met.

Comorbidity

Because this text is oriented toward the clinical assessment of SUDs, information on comorbidity derived from clinical samples will be emphasized as more relevant than community samples, to the extent that they differ. Abuse of one substance is often comorbid with abuse of a second substance of abuse. Approximately one-third of admissions to substance treatment programs are for both alcohol and illicit drug use (Substance Abuse and Mental Health Services Administration [SAMSHA], 2014). The most common additional substances of abuse for patients with opiate use disorders are marijuana, alcohol, and/or cocaine; for injecting drug abusers these are alcohol, benzodiazepines, cannabis, and/or amphetamines; and for patients with cocaine use disorders, they are marijuana or alcohol (SAMSHA, 2003). Patients with more than one drug of abuse are less likely to achieve remission and have more relapse after intensive treatment compared to patients abusing a single drug (Ritsher, Moos, & Finney, 2002; Walton, Blow, & Booth, 2000).

(p. 360) An estimated 37% of adults older than age 18 years with SUDs also have any mental illness, and 11% have a serious mental illness (SAMHSA, 2015). Comorbid disorders are most commonly affective disorders and anxiety disorders (Acosta, Haller, & Schnoll, 2005). Among people with cocaine use disorders, comorbidity rates for depressive disorders range from 11% to 55% (with depression usually preceding the SUD by approximately 7 years) and for bipolar disorder are approximately 42%; panic disorder is a common result of cocaine abuse; and the prevalence of post-traumatic stress disorder among those with SUDs is 10 times higher than among those who do not have a SUD (Acosta et al., 2005). Psychiatric comorbidities (other than personality disorders) for individuals with opioid use disorders are most commonly bipolar or anxiety disorders (Dilts & Dilts, 2005). The prevalence of current mood and/or anxiety disorder among heroin injectors with multiple substances of abuse is approximately 55%, with 25% having both a mood and an anxiety disorder (Darke & Ross, 1997). An excellent clinical guide to treatment issues involved with psychiatric comorbidity in those with SUDs is provided by Busch, Weiss, and Najavits (2005).

Personality disorders occur in approximately 27% of people with past-year alcohol dependence and 54% of people with past-year drug dependence (corrected re-analysis of National Epidemiological Survey on Alcohol and Related Conditions [NESARC] data of 2001–2005 presented in Trull et al., 2016). The most common comorbid personality disorders for drug dependence are antisocial (40.2%), borderline (27.88%), avoidant (14.2%), schizoid or schizotypal (14.2%), obsessive–compulsive (10.6%), histrionic (10.3%), and paranoid (7.8%) (Trull et al., 2016). The rates are lower for alcohol dependence, ranging from the most prevalent, antisocial personality (18.8%), to the least prevalent, histrionic personality (1.8%).

Prevalence, Gender, Race, Ethnicity, and Geography

The prevalence of current substance dependence or abuse in the United States in 2013 (SAMHSA, 2014) was approximately 8.2% of people aged 12 years or older. Of these, approximately 12% had both alcohol and illicit drug use disorders, 20% had an illicit drug use disorder but not alcohol use disorder, and 68% had alcohol use disorder without a disorder of illicit drugs. Although from age 12 to 17 years the same number of males and females have SUDs (5.3% vs. 5.2%, respectively), from age 18 years on almost twice as many men as women have SUDs in the past year (11.4% vs. 5.8%, respectively; SAMSHA, 2014). The geographic distribution of people in the United States with illicit drug use in the population is fairly even, but with somewhat higher rates in the West (11.8%) and Northeast (9.2%) than in the Midwest (8.7%) or South (8.3%) (SAMHSA, 2014). Only approximately 1.6% of people aged 12 years or older with lifetime SUD ever received any substance use treatment, and only 1.0% received it in substance abuse treatment facilities in 2014 (SAMSHA, 2015).

The National Survey on Drug Use and Health study (2013 survey; SAMHSA, 2014) showed the highest rates of SUDs for American Indians or Alaskan Natives (14.9%), then Native Hawaiians or Pacific Islanders (11.3%), multiracial people (10.9%), Hispanics (8.6%), non-Hispanic Whites (8.4%), and non-Hispanic Blacks (7.4%), with the lowest rates for Asians (4.6%). Gender differences in alcohol use disorders within each race/ethnicity were reported in the NESARC survey of 2001 and 2002 (National Institute on Alcohol Abuse and Alcoholism, 2006). In this survey, the highest rates were for American Indians (17.3% of males and 16.8% of females), then non-Hispanic Whites (17.3% of males and 8.1% of females), non-Hispanic Blacks (17.2% of males and 8.3% of females), and Hispanics (17.3% of males and 7.2% of females), with the lowest rates for Asians (11.0% of males and 6.8% of females). However, Whites have the highest rates of admission to publicly funded substance treatment facilities (2008 survey by SAMHSA; National Institute on Drug Abuse, 2011): Admissions were 59.8% White, 20.9% Black, 13.7% Hispanic, 2.3% American Indian or Alaskan Native, and 1.0% Asian or Pacific Islander.

The Addiction Career

There is little agreement on the etiology of SUDs—a topic difficult to study given that substances of abuse are not all similar in mechanism, effects, or likely determinants (Anthenelli & Schuckit, 1992). It is difficult to study the etiology of drug abuse or dependence for each drug of abuse completely separately, given the fact that people may use various substances at different times or the same time. Because different drugs of abuse involve different mechanisms, it has been difficult to investigate possible genetic factors specific to illicit drug abuse as opposed to alcohol abuse, so such research has focused on genetic factors in the neurotransmitters believed to confer greater susceptibility to drug dependence (e.g., mu or kappa opioid receptors or dopamine transmission) along with genes influencing externalizing (p. 361) psychopathology (Dick & Agrawal, 2008). Studies of sociocultural factors do little to explain who specifically will develop drug dependence given that such a small number of people affected by these influences develop drug dependence (Johnson & Muffler, 1992). There is no one psychological or sociopsychological theory that is generally accepted as explanatory (e.g., Schulenberg, Maggs, Steinman, & Zucker, 2001). However, there may be a general genetically influenced liability of negative emotionality that is expressed as personality characteristics and behavioral tendencies (inadequate emotional regulations and maladaptive responses to stress) common to abuse of various substances as well as to other comorbid disorders (Tully & Iacono, 2016). Adolescent substance abuse is highest for those who have high novelty seeking combined with low harm avoidance and low reward dependence personality traits (Wills, Vaccaro, & McNamara, 1994). These personality trait measures were correlated with other measures of behavioral undercontrol such as risk-taking, impulsivity, anger, independence, tolerance for deviance, and sensation seeking (Wills et al., 1994). A childhood pattern of behavioral undercontrol often leads to early onset of cigarette use, which in turn increases the probability of the onset of drug use (e.g., Brown, Gleghorn, Schuckit, Myers, & Mott, 1996; Farrell, Danish, & Howard, 1992; U.S. Department of Health and Human Services, 1989). The etiology of this pattern of behavioral undercontrol itself is unknown. However, this may not be the only pathway to substance dependence. For a review of the concept and evidence for and against behavioral undercontrol and negative emotionality as mechanisms, see Smith and Anderson (2001) and Tully and Iacono (2016).

A large study of the natural history of 581 people with narcotic addictions tracked the course of events during the 30-year period from 1956 to 1986 (Anglin et al., 1988). There were several notable findings. First, 5 years after starting narcotics use (approximately age 17 years), most were daily users, with few remaining as occasional users. Second, daily use peaked at approximately age 30 years, decreased slightly as people entered into methadone maintenance, and then remained stable. Third, incarceration rates were highest between ages 20 and 30 years (approximately 60% of group) and then dropped off to 11% for the last decade. Fourth, deaths started occurring within 10 years, with a mortality rate of 27% of the group at the end of 30 years (comparable to the 10% to 50% mortality rate within 8 years reported across studies by Finney, Moos, & Timko, 2013). Fifth, for the last 10 to 15 years of the study period, approximately 22% of the people were abstinent. Although these data are rather old, to the extent to which they reflect common developmental factors, the progression may hold up over time. Others have summarized the course of opiate addiction more simply: First use is usually in the teens or 20s, most active opiate users are 20 to 50 years old, the addiction abates slowly and spontaneously in middle age, with 9 years being the estimated average duration of active addiction (Dilts & Dilts, 2005; Jaffe, 1989). Anglin et al. concluded that substance abuse treatment is needed much earlier in the addiction careers because treatment interrupts the typical progression of addiction. The National Drug Abuse Treatment Outcome Study showed that, overall, treatment does work, with the greatest reductions in drug use occurring with treatments that last 3 or more months for 1-year results and 6 or more months for 5-year recovery (Hubbard, Craddock, & Anderson, 2003). Across 15 studies with 8 or more years of follow-up, the annualized “remission” rates averaged 4.0% (Finney et al., 2013).

Purposes of Assessment

Three specific assessment purposes of most relevance for clinical use are emphasized in this chapter: (a) diagnosis, (b) case conceptualization and treatment planning, and (c) treatment monitoring and outcome evaluation. The emphasis in the case conceptualization and treatment planning section is on problem severity. This section also includes assessment of expectancies, high-risk situations, self-efficacy in handling risk, and coping skills because these can be useful in planning motivational interventions, relapse prevention, and coping skills training specific to individual needs. Measures of overall functioning/impairment or functioning in interpersonal, family, psychiatric, medical, and employment domains can be useful in evaluating need for family or couples therapy, employment assistance, legal or medical services, social services, and so on. The focus in this chapter is on the assessment of SUDs regardless of substance, with less focus on measures that were developed for use with only one substance. The assessment of other behaviors that are sometimes seen as addictive, such as gambling or sexual offending, is not discussed here (the assessment of gambling is covered in Chapter 19). An excellent text that covers an array of substance-specific assessment measures, addictive behaviors not involving chemical substance, and measures designed for use in research studies is the one by Donovan and Marlatt (2005).

(p. 362) Assessment for Diagnosis

The diagnostic criteria of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013) have replaced those of DSM-IV-TR (APA, 2000) as the standard for clinical practice in the United States. Measures focused on World Health Organization (WHO) criteria are not addressed because they are less likely to be relevant to practice in the United States. DSM-5 revisions replaced the abuse and dependence categories with a single continuum, but people can be categorized based on number of criteria met into mild, moderate, and severe levels of SUD. Substance-related legal problems were eliminated due to low occurrence, cultural variability, and poor fit with the other diagnostic information (Goldstein et al., 2015; Schuckit, 2012), and craving or urge to use was added (to increase consistency with WHO criteria), but otherwise the list of criteria is the same. The SUD can be specified as “in a controlled environment,” “in early remission,” “in sustained remission,” and, for certain substances, “on maintenance therapy” (craving is the only criterion that can occur during remission).

SUDs are a maladaptive pattern of substance use leading to clinically significant impairment or distress as indicated by two or more of the following occurring within the same 12-month period: tolerance (increased amount needed for same effect or markedly less effect with same amount of use); withdrawal (either the characteristic withdrawal syndrome or using the substance or a closely related substance to prevent/relieve withdrawal); amount or duration of substance use that is greater than intended; repeated unsuccessful attempts to cut down or control substance use; much time spent in activities needed to obtain, use, or recover from the substance; important activities stopped or reduced due to substance use; substance use continues despite knowledge of a persistent or recurrent physical or psychological problem caused or exacerbated by the substance; recurrent substance use resulting in failure to fulfill major obligations at work, home, or school; recurrent substance use in situations in which it is physically hazardous; continued substance use despite the use causing or exacerbating social or interpersonal problems; and craving or strong desire or urge to use a specific substance. (For full, exact wordings of these criteria and any substance-specific differences, see DSM-5 or del Boca, Darkes, and McRee [2016].) Two or three symptoms indicate a mild SUD, four or five symptoms indicate a moderate SUD, and six or more symptoms indicate a severe SUD.

Screening Measures

Screening measures are typically used in settings such as general medical settings or employee assistance programs to identify or rule out probable SUD without providing a diagnosis. These are brief measures that can be quickly administered to identify people who may be in need of further evaluation or assistance. Cut-off points for screening measures can be set to err on the side of false positives or false negatives, depending on the purpose of the assessment. However, any positives should be followed up with further evaluation rather than being considered indicative of an SUD per se. The best known screening measures are rated in Table 17.1 and described in the (p. 363) following paragraphs. It was not necessary for test developers to update these measures to address DSM-5 criteria because they were never intended to assess those exact criteria. In addition, because reasonably similar prevalences of moderate to severe DSM-5 SUD and DSM-IV (APA, 1994) substance dependence occur (Goldstein et al., 2015), the screening measures are likely to work as well with the current DSM system. For a further discussion of alcohol-specific and adolescent-specific measures, see the review of assessments by del Boca et al. (2016).

Table 17.1 Ratings of Instruments Used for Screening or Diagnosis

Instrument

Norms

Internal Consistency

Inter-Rater Reliability

Test–Retest Reliability

Content Validity

Construct Validity

Validity Generalization

Clinical Utility

Highly Recommended

Screening for Substance Use Disorders

DAST

NA

E

NA

NR

A

A

E

A

DUSI-R

NA

G

NA

NR

A

A

E

A

Diagnostic Instruments

SCID-5

NA

NA

G

G

G

A

E

L

MINI

NA

NA

G

E

G

G

E

E

CIDI

NA

NA

G

G

G

A

E

L

SDSS

NA

G

NA

G

G

Ga

G

A

GAIN-I

A

G

NA

G

G

G

E

A

MWC

NA

NR

NA

G

G

G

G

E

a Good except for ICD-10 harmful use and cocaine dependence diagnoses, which were less than adequate.

Note: DAST = Drug Abuse Screening Test; DUSI-R = Drug Use Screening Inventory-Revised; SCID-5 = Structured Clinical Interview for DSM-5 Axis I Disorders-Patient Version; MINI = Mini-International Neuropsychiatric Interview 6.0; CIDI = Composite International Diagnostic Interview; SDSS = Substance Dependence Severity Scale, section on diagnoses; GAIN-I = Global Appraisal of Individual Needs-Initial Interview, substance use scales; MWC = Marijuana Withdrawal Checklist; L = Less Than Adequate; A = Adequate; G = Good; E = Excellent; NR = Not Reported; NA = Not Applicable.

Drug Abuse Screening Test

The Drug Abuse Screening Test (DAST; Skinner, 1982), a 28-item self-report test, and the 10-item short form (DAST-10) provide an indicator of who might have an SUD and need further evaluation, with evidence of excellent internal reliability and good validity (Gavin, Ross, & Skinner, 1989). Data on test–retest reliability are unavailable. Both ask about drug abuse in the past year, rather than over the lifetime, and an adolescent version is available. The DAST is composed of five factors (early psychosocial complications with problem recognition, late-onset serious social consequences, treatment/help-seeking, illegal activities, and inability to control drug use), but because psychometric properties of the separate factors were not investigated (Staley & El-Guebaly, 1990), only the total score should be used. Both the DAST and the DAST-10 focus on negative consequences of use rather than quantity or frequency of use.

Drug Use Screening Inventory

The Drug Use Screening Inventory (DUSI; Tarter, 1990), which is a longer self-report measure (140 yes/no items) with both adult and teen versions, assesses problem severity in the following 10 domains: substance use preferences and consequences, behavioral maladjustment, health, psychiatric disorder (depression, anxiety, antisocial, and psychotic), school adjustment, work adjustment, social competence, peer relationships (e.g., antisocial or substance involvement), family dysfunction/conflict, and recreation. It takes approximately 20 minutes to complete via paper or computer and is easy to manually score. Efforts were made to ensure items are free of cultural bias and at a fifth-grade reading level. The revised version (DUSI-R) has a validity check and Lie scale, has been found to have adequate or better psychometric qualities, and includes cut-off scores to indicate a probable diagnosis (Tarter & Kirisci, 1997). This measure is more highly recommended than the DAST and DAST-10, despite the extra administration time, because it provides more information.

Diagnostic Instruments

In clinical settings, diagnosis is often determined without a formal structured set of specific questions. When a formal system is needed to ensure accuracy of diagnosis (e.g., for research or clinical statistics), the instruments rated in Table 17.1 and described next are the best validated structured systems available. Because it can take up to 10 years to develop and test the reliability and validity of a structured interview, it may take a while before there is psychometric evidence for instruments that have been fully updated to DSM-5 criteria.

The Structured Clinical Interview for the DSM (SCID-5; First, Williams, Karg, & Spitzer, 2015) is validated directly against both the DSM-5 and the 10th edition of the International Classification of Diseases (ICD-10; WHO, 1992; https://www.cdc.gov/nchs/icd/icd10cm.htm) diagnostic criteria. This interview is considered the most valid method for determining DSM-5 psychiatric diagnoses and is the most widely used structured diagnostic interview. The SCID-5 should be administered by clinicians, not other trained interviewers, with the version for clinicians called SCID-5-CV. This structured interview is very lengthy (1 hour or more for the full interview) and requires formal training in administration and scoring; as such, it may not be cost-effective for treatment agencies because the resulting data provide diagnostic information but no other information necessary for treatment planning.

A much briefer alternative is the Mini-International Neuropsychiatric Interview (M.I.N.I. 6.0;https://www.psychcongress.com/saundras-corner/scales-screeners/structured-diagnostic-interview-instruments/mini-international-neuropsychiatric-interview-60-mini-60; Sheehan et al., 1998), which evaluates all current diagnoses in approximately 15 to 17 minutes, so determining alcohol or SUDs takes only a fraction of that time. Although it was designed for researchers, a computerized version makes it easy for any clinician to use; it is used by health and mental health professionals in more than 100 countries. Because each section starts with one or more screening questions (questions about drinking a certain amount or using street drugs for the alcohol and substance use sections, respectively), the whole interview does not need to be administered for people who do not meet some minimal criteria for a section. Patients had positive opinions about the interview and the interview format (Pinninti, Madison, Musser, & Pissmiller, 2003). (p. 364) The M.I.N.I. was validated against the SCID for DSM-IV and the Composite International Diagnostic Interview (CIDI; Robins et al., 1988) for ICD-10 as well as against expert opinion (Sheehan et al., 1998), and it produces separate diagnoses for current (past 12 months) alcohol abuse, alcohol dependence, substance abuse, and substance dependence. So far, the mania/hypomania sections have been updated and validated for DSM-5 (Hergueta & Weiller, 2013) and a version for 17 DSM-5 diagnoses has been developed but was not available at the time this chapter was written http://harmresearch.org/index.php/product/mini-international-neuropsychiatric-interview-mini-7-0-2/.

The Diagnostic Interview Schedule (DIS; Robins, Helzer, Cottler, & Golding, 1989; Robins et al., 2000) was designed to provide reliable and valid SUD diagnoses based on DSM-III (APA, 1980) and DSM-IV criteria using a format involving fewer clinical judgments so it could be administered by a trained technician. It was replaced by the CIDI when WHO expanded and updated the DIS to meet international criteria (ICD-10). (A version for DSM-5 is due in 2018 https://www.hcp.med.harvard.edu/wmhcidi/trc_americas/.) However, it is designed for research, not clinical practice; takes 2 hours to administer; and requires extensive training, and is available only as a computerized version. Therefore, these instruments are usually not clinically useful.

For assessing withdrawal aspects specific to cannabis abuse, it is preferable to use a measure based on the empirical work that established the cannabis withdrawal syndrome. Budney, Moore, Vandrey, and Hughes (2003) demonstrated a unique pattern of withdrawal symptoms, including aggression, anger, anxiety, decreased appetite, decreased body weight, irritability, restlessness, shakiness, sleep problems, and stomach pain. A measure designed to assess this pattern, the Marijuana Withdrawal Checklist (MWC; Budney, Hughes, Moore, & Novy, 2001; Budney et al., 2003), is a self-report measure that includes the 15 items most frequently endorsed. Studies with the 15-item version found evidence of good test–retest reliability and validity and also the expected gradual change over days along the predicted time course of withdrawal (Budney et al., 2003).

Two instruments for assessing opiate withdrawal with some supporting reliability and validity evidence are the Subjective Opiate Withdrawal Scale (16 items, self-administered) and the Objective Opiate Withdrawal Scale (13 items, interviewer-administered), both developed by Handelsman et al. (1987). For cocaine dependence, withdrawal is an infrequently endorsed symptom. These measures are not rated in Table 17.1 because there is only limited evidence concerning their reliability and validity.

The Substance Dependence Severity Scale (SDSS; Miele et al., 2000a) is a semi-structured clinical interview that takes approximately 30 to 45 minutes and requires extensive training. Part of it results in current diagnoses for DSM-IV and ICD-10 (WHO, 1997) substance abuse/dependence/harmful use disorders by operationalizing every criterion used in diagnosis. Each diagnostic criterion is rated for both severity (usual and worst) and frequency (number of days and number of days at the worst). Scores on the SDSS scales have demonstrated good to excellent test–retest reliability (except for cannabis, for which it was fair to poor), internal consistency, and validity for the DSM-IV items (Miele et al., 2000a, 2000b). Percent agreement with DSM-IV diagnoses was 83% to 92% for alcohol, cocaine, heroin, sedatives, and cannabis (the only diagnoses investigated). The test–retest reliability and internal consistencies for the ICD-10 dependence scales of alcohol, heroin, and cocaine were excellent, but the ICD-10 harmful use scales mostly had unacceptably poor test–retest and/or internal consistency reliabilities. Percent agreement with ICD-10 dependence diagnoses was good to excellent for alcohol, heroin, and cannabis but only fair for cocaine, and for harmful use diagnoses were only fair (unacceptable) for heroin, cocaine, and cannabis. Therefore, as long as ICD-10 harmful use or cocaine dependence diagnostic information is not needed, this instrument will produce valid DSM-IV diagnoses for alcohol, cocaine, heroin, sedatives, and cannabis use disorders. It is not clear whether there are plans for an update to DSM-5. However, the SDSS severity scores, indicating degree of severity similar to the DSM-5 degree of severity, has been validated against clinical severity ratings for alcohol, cocaine, and heroin (Miele et al., 2000b).

The Global Appraisal of Individual Needs (GAIN-I; Dennis, 1999; Dennis, Scott, & Funk, 2003; Dennis, Titus, White, Unsicker, & Hodgkins, 2003) is a semi-structured interview designed to obtain comprehensive information about the functioning of adult or adolescent patients (see further description later). The latest version, GAIN 5.7, has been updated to DSM-5 criteria. It takes 1½ to 2½ hours to administer, and it requires considerable training. There is a Web-based Assessment Building System format (GAIN-ABS) that also provides DSM-5 diagnoses. The Initial Interview version includes a diagnostic section, and the diagnoses of SUDs as well as other disorders have evidence of good test–retest reliability (p. 365) estimates and concordance with independently obtained diagnoses (Dennis, 1999; Shane, Jasiukaitis, & Green, 2003). A 2- to 5-minute Short Screener (GAIN-SS) is available for rapidly identifying those who are likely to have an SUD.

Overall Evaluation

The previously discussed screening and diagnostic measures have all demonstrated scientific adequacy as screening or diagnostic measures. Screening measures such as the DAST are not relevant for SUD treatment programs, but they are useful in other settings to identify people probably in need of further assessment or treatment. The GAIN-SS (screening version) is useful for identifying people who need full diagnostic assessment for certain diagnoses (SUD or other), but psychometric information about this screener was not available. The DUSI, although intended to screen for SUDs, is also useful for screening for a number of areas of life function in a way comparable to the Addiction Severity Index (discussed later) but with easier administration and scoring; for this reason, it is highly recommended. The diagnostic measures are relevant only if accurate formal diagnoses are needed. Because many SUD treatment programs treat anyone who presents with substance-related problems or concerns, having access to accurate diagnoses is unlikely to affect treatment admission or planning, but diagnoses can affect reimbursement. The M.I.N.I., when updated to DSM-5, is recommended as a method that is fast, accurate, and shows patient acceptance. Otherwise, the diagnostic section of the GAIN 5.7 is most highly recommended as the next least time-intensive way to obtain the most diagnoses with good psychometric support. The others were not recommended due to the lengthy time and training needed (SCID-5, CIDI, and SDSS) or the cumbersome amount of information produced (SDSS).

Assessment for Case Conceptualization and Treatment Planning

Rationale for Instrument Selection

A number of assessment instruments are commonly used to provide clinicians with guidance for case conceptualization and treatment planning. Some measures include severity of drug use and problems specific to the drugs per se; others address the severity of problems in related aspects of life functioning (e.g., employment, legal, family), whether or not drugs are perceived as the cause of the problems, thus allowing for the determination of areas of life functioning in need of improvement and for additional specialized services such as social services, employment assistance, or marital or family therapy. Assessment of the patient’s anticipated positive and negative consequences of drug use is sometimes used in developing motivational interviewing treatment plans by investigating sources of and barriers to motivation. Relapse prevention training involves assessing high risk situations for relapse so as to prepare patients to cope with their own “Achilles heel” situations. Assessment of coping skills can provide information about skills and resources that can already be drawn on, maladaptive skills that need to be replaced, and skills and resources that are lacking. Skills training for substance abusers has focused either on making general lifestyle changes consistent with sobriety or on developing skills for coping with immediate urges to use in the presence of situations that pose a high risk for relapse (Monti, Kadden, Rohsenow, Cooney, & Abrams, 2002). In most cases, both types of skills need to be assessed.

Some potential assessment domains are not addressed in the chapter, based on either clinical or scientific reasons. First, measures of craving are not included because it is not clear that degree of craving per se can be useful in treatment planning, as opposed to identifying situations or events that trigger craving, which can be quite important. Second, although numerous studies have shown that having social networks that include substance users (particularly one’s partner) poses a serious risk for continued drug use (see review by Westphal, Wasserman, Masson, & Sorenson, 2005), this risk is easy to assess without any formal assessment tool. Although the Important People Drug and Alcohol interview predicted outcome for patients with cocaine use disorders, it was just the number of people in the daily network that predicted less drinking, drug use, and problem severity over 6 months, not the measures of the supportiveness or drinking status of the network (Zywiak et al., 2009), and that is easy to assess without using a measure. Therefore, this section focuses on tools that have adequate psychometric information and that could be useful in treatment planning. Detailed ratings of their psychometric properties can be found in Table 17.2.

Table 17.2 Ratings of Instruments Used for Case Conceptualization and Treatment Planning

Instrument

Norms

Internal Consistency

Inter-Rater Reliability

Test–Retest Reliabilitya

Content Validity

Construct Validity

Validity Generalization

Clinical Utility

Highly Recommended

Severity of Drug Use and Psychosocial Functioning

SDS

NA

E

NA

E

E

E

NR

A

SDSS

NA

E

NA

E

E

E

E

A

ASI-6

NA

G

G

G

A

A

G

A

GAIN-I

NA

G

NA

NA

G

G

A

A

Negative Consequences of Ongoing Use

IDUC

NA

E

NA

G

G

A

A

A

SIP-AD

NA

E

NA

G

G

A

A

A

MPS

NA

E

NA

NR

NR

A

NR

A

CNCC-87

NA

G

NA

NR

G

G

A

A

Expected Acute Effects of Use

SUBQ

NA

E

NA

NR

G

G

NR

A

CEQ

NA

G

NA

NR

G

G

A

A

Assessment for Relapse Prevention Treatment Planning

IDTS

A

G

NA

NR

G

G

G

A

DTCQ

NA

G

NA

NA

A

A

G

A

AASE

NA

E

NA

NR

A

G

NR

A

CRACS-SE

NA

E

NA

NR

A

G

G

A

POC-10 items

NA

A

NA

NA

A

A

NR

A

USS/GSC

NA

E

NA

NR

G

G

A

A

a Test–retest reliability is generally not applicable because clients in treatment are unstable in these areas and are expected to have variability over short periods of time.

Note: SDS = Severity of Dependence Scale; SDSS = Substance Dependence Severity Scale; ASI-6 = Addiction Severity Index-Version 6; GAIN-I = Global Appraisal of Individual Needs-Initial Interview, substance use scales; IDUC = Inventory of Drug Use Consequences, four scales (excluding intrapersonal); SIP-AD = Short Inventory of Problems–Alcohol and Drugs; MPS = Marijuana Problems Scale; CNCC-87 = Cocaine Negative Consequences Checklist; SUBQ = Substance Use Beliefs Questionnaire; CEQ = Cocaine Effects Questionnaire; IDTS = Inventory of Drug Taking Situations; DTCQ = Drug-Taking Confidence Questionnaire; AASE = Alcohol Abstinence Self-Efficacy; CRACS-SE = Self-Efficacy ratings from the Cocaine Related Assessment of Coping Skills: POC-10 = 10 items extracted from the Processes of Change Questionnaire for a study with opiate-using patients; USS/GSC = Urge-Specific Strategies Questionnaire and General Change Strategies Questionnaire; L = Less Than Adequate; A = Adequate; G = Good; E = Excellent; NR = Not Reported; NA = Not Applicable.

Increasing Honest Reporting

Structured interviews with individuals with SUDs about their drinking or substance use have been found to (p. 366) provide sensitive and reliable information when there is (a) an interviewer and clinical set that encourages honest reporting (i.e., no unpleasant consequences, including interviewer disapproval), (b) assurances of confidentiality, (c) breath alcohol testing at the interview to ensure the person is alcohol-free during the interview, and (d) interviewee awareness that his or her reports will be corroborated by urine screens and/or reports of family members or close friends (Ehrman & Robbins, 1994; Sobell et al., 1996; Sobell & Sobell, 1986). Patients are likely to become dishonest in their reporting when expecting scolding, lectures, disappointing the therapist, changes in treatment, or reporting to others who may impose consequences as a result of disclosing use. Thus, the interviewer set is particularly important both with interviews and with self-report measures: Knowing that there will be no negative consequences or disapproval for reporting substance use removes the primary disincentive to honesty.

Severity of Substance Use and Psychosocial Functioning

Number of DSM-5 Symptoms

With DSM-5 indicating severity on a continuum, the number of criteria met is designed to be used as a measure of SUD severity.

The Severity of Dependence Scale

If the clinician is not assessing in order to obtain a formal diagnosis, the simplest assessment alternative is the Severity of Dependence Scale (SDS; Ferri, Marsden, de Araujo, Laranjeira, & Gossop, 2000; Gossop, Best, Marsden, & Strang, 1997; Gossop et al., 1995), which uses just five face-valid items (about worry/anxiety, feeling out of control, and desire to stop or difficulty with stopping) to assess a pattern of dependence severity across the (p. 367) patient’s preferred substance. It has demonstrated excellent psychometric properties, and although there is no information about any racial diversity in any of the validation samples, it has been validated in three countries (England, Australia, and Brazil).

Substance Dependence Severity Scale

The SDSS (Miele et al., 2000a), a semi-structured clinical interview, assesses the severity of every symptom of both DSM-IV and ICD-10 (WHO, 1997) substance abuse/dependence/harmful use disorders among people aged 16 years or older. Substance-specific questions assess frequency, recency, and amount of use in the past 30 days only, as well as asking usual and worst severity of each diagnostic criterion and also number of days of any use and number of days at the worst severity for each. These questions cover a wide range of abused substances, including alcohol, cocaine, heroin, stimulants, licit opiates, sedatives, methadone, cannabis, hallucinogens, and two “other” categories covering drugs such as inhalants. However, the cannabis items omit withdrawal, which was only found to be a valid symptom after this measure was developed. The SDSS takes specialized training and can require as much as 45 minutes to administer.

The SDSS scale scores have been found to demonstrate good to excellent test–retest reliability, internal consistency, and validity for the use (quantity/frequency) items, DSM-IV severity items (except for cannabis), and ICD-10 dependence but not harmful use scales (Miele et al., 2000a, 2000b). The best validity was shown for the alcohol, heroin, and cocaine severity scales. Patients reporting more days that symptoms were present returned to drug use more quickly, suggesting that this frequency scale predicts need for more intensive care (Miele et al., 2001). On the other hand, greater usual severity of dependence symptoms predicted slower return to drug use (Miele et al., 2001), consistent with more serious problems or concern about consequences of drug use making people more motivated for change. Therefore, this instrument has generally excellent psychometric properties (except for cannabis scales for either DSM-IV or ICD-10 harmful use) and can be a useful way to assess recent use and severity of specific DSM-IV SUD symptoms.

Addiction Severity Index

The Addiction Severity Index (ASI; Cacciola, Alterman, Habing, & McLellan, 2011; McLellan, Luborsky, Woody, & O’Brien, 1980; McLellan et al., 1992). This structured interview has become the most widely used instrument for assessing both SUD severity and severity of other life problems in SUD treatment settings. It was recently updated to the sixth edition so as to correct some psychometric problems with the widely used fifth edition, including adding a 6-month time frame to the lifetime and 30-day questions, thus improving the structure and clarity of the questions, and reducing the time burden of the many additional questions by adding screening questions with skip-outs. The ASI provides severity scores that have been found to be reliable and valid for recent (past 30 days) drug use (not specific to any one drug), alcohol use, and problems in five life areas: medical, employment/finances, legal, psychiatric, and social/family functioning (three scales for this aspect: adult relationships (problems and support), use of free time, and problems and needs regarding minor children). The drug and alcohol use sections ask about past 30 days, past 6 months, and lifetime frequency of use of each of a number of drugs and also of a number of consequences of drug or alcohol use. Each section of the interview previously included an overall clinical rating of severity, but because these ratings and the previous composite scores were not acceptably reliable, they were replaced by newly developed summary indices that were developed empirically (Cacciola et al., 2011; Denis, Cacciola, & Alterman, 2013). However, whether or not a summary score is desired, the specific information derived from the interview provides the clinician with a wealth of useful information. The ASI requires specialized training offered by the authors in Philadelphia, requires computerized scoring of the summary indices, and requires approximately 45 to 90 minutes to administer. A computer-administered version eases some of the burden. The new version shows acceptable support for each of the indices in terms of separation and stability, with strong evidence of reliability and validity for the 30-day indices (Cacciola et al., 2011). (Psychometrics for the 6-month and lifetime indices were not reported.) Like the original version, this edition was developed using patients in a variety of community settings in an urban area, with the primary substance of abuse being cocaine, heroin, or alcohol, but it was limited to mostly unemployed patients. Generalizability was assessed between genders and between Whites and African Americans and was found to be acceptable. It has been validated in Spanish (Díaz Mesa et al., 2010) and in Portuguese in Brazil (Kessler et al., 2012).

Global Appraisal of Individual Needs

The GAIN’s (Dennis, 1999; Dennis, Scott, et al., 2003; Dennis, Titus, et al., 2003; http://www.chestnut.org/li/ (p. 368) gain) semi-structured interview has sections on family/living arrangement, substance use, physical health, risk behaviors, mental health, environment, legal, and vocation. As such, it can provide comprehensive background information on patients similar to that obtained by the ASI. It can be used for American Society of Addiction Medicine-based level of care placement, Joint Committee on Accreditation of Hospital Organization-based treatment planning, and Drug Outcome Monitoring Study-based outcome monitoring. The GAIN can be administered by paper or computer and takes 60 to 120 minutes for the initial evaluation. The substance use section, in addition to providing diagnostic information (as previously described), asks for self-reported frequency of use in the past month for categories of drugs or any substance, recency of use of each of these categories, peak quantity of use of each category, frequency (days) of use of each, number of days with problems from substance use, number of past-month SUD diagnostic symptoms, and a current withdrawal scale, all with excellent reliability and validity (Dennis, Titus, et al., 2003). In a comparison of biometric data (hair and urine) and three self-report measures (recency, quantity, and frequency) of use of marijuana, cocaine, opioids, and other substance, the GAIN’s Substance Frequency Scale performed as well or better than other measures or methods of combining measures (Lennox, Dennis, Scott, & Funk, 2006). Other scales in the GAIN, all with evidence of at least adequate reliability and validity, include number of days of past treatment, environmental risks for relapse, illegal activities, emotional problems, and employment activities.

Negative Consequences of Use

Although the assessment of negative consequences of substance abuse overlaps with material addressed in the preceding section, the measures described previously either focused on severity of diagnostic symptoms alone or on life functioning (whether or not problems in life functioning could be directly attributed to substance use). Assessment of a range of consequences perceived by patients to be specifically due to substance use can be useful for treatment planning in two ways. First, it provides an overview of areas of functioning that should improve as a result of abstinence and treatment. Second, the information can be used to increase the patient’s awareness of areas of life that could be improved via abstinence.

The Inventory of Drug Use Consequences (IDUC; Tonigan & Miller, 2002) is a 50-item self-report measure of the consequences of drug or alcohol use (not differentiated from each other). There are separate versions for lifetime and the past 3 months of use, and each of these has a version worded in the third person that can be completed by a family member or friend. The IDTC was developed to provide clinicians with a relatively brief (approximately 10–15 minutes) and easy tool that is in the public domain. Scores on four of the five scales have demonstrated excellent internal consistency reliability (physical problems, social relationships, interpersonal problems, and impulse control), and a confirmatory factor analysis showed that these same four scales adequately represent a larger domain of negative consequences and correlate with other measures of negative consequences (Tonigan & Miller, 2002). Further work produced the 15-item Short Inventory of Problems–Alcohol and Drugs (SIP-AD; Blanchard, Morgenstern, Morgan, Labouvie, & Bux, 2003). The items all load on one scale (indicating the degree of adverse consequences) that has been found to yield excellent reliability estimates and that significantly correlates with other measures of alcohol and drug severity, dependence symptoms, substance use frequency, and psychiatric severity. Although both versions have demonstrated good to excellent reliability and at least adequate validity (see Table 17.2), the long version (excluding the intrapersonal section) would be more useful in treatment planning because it provides reliable indices of problems in four different life areas that can be targeted for coping skills training or motivational approaches.

The Marijuana Problems Scale (MPS; Stephens, Roffman, & Curtin, 2000) assesses 19 recent and lifetime problems that patients with SUDs attribute to marijuana use, each rated as no problem, minor problem, and serious problem, and that are summed to provide an index of problem severity. This self-report measure was derived in part by rewording many DAST items for marijuana, deleting the treatment items, and adding some other consequences (Stephens, Wertz, & Roffman, 1993). (In one publication, it was called the Marijuana Consequences Questionnaire [Budney, Higgins, Radonovich, & Novy, 2000], which can result in confusion with the other measure by that name.) Domains include psychological, social, legal, and occupational consequences (examples include memory problems, family problems, and procrastination). A 26-item version is a checklist, but the 19-item version asks patients to rate each item as a mild or major problem versus no problem. There is limited psychometric information available on either version of (p. 369) this measure. For the 19-item version, one study reported very high internal consistency reliability (Stephens et al., 2000) and showed change in problems during a 4-month period among marijuana-dependent patients in active treatment versus delayed-treatment condition that paralleled changes reported for frequency of marijuana use and number of dependence symptoms (Stephens et al., 2000). However, no other forms of validity analyses have been conducted. Although the 26-item checklist has been used in more studies, there is virtually no supporting psychometric information for this version, with one report of high internal consistency reliability at follow-up (Stephens et al., 1993) but no reported reliability pretreatment, no concurrent correlations reported to support its validity, and no differences between pretreatment abstainers and users of marijuana in scores (Moore & Budney, 2002). Therefore, the 19-item MPS is a brief and valid measure of degree of initial problems, but further psychometric information is needed and psychometric properties of the 26-item checklist version are unknown. A separate 50-item measure called the Marijuana Consequences Questionnaire (Simons, Dvorak, Merrill, & Read, 2012) was developed and validated only on college students and so is not recommended for clinical use.

The Cocaine Negative Consequences Checklist (CNCC; Michalec et al., 1996) assesses long-term negative life events that cocaine abusers perceive to result from their own cocaine use. The items all fall on a single scale that has demonstrated evidence of high reliability, but they can also be scored for four reliable content area scales: physical health, emotional/psychological, social/relationship, and legal problems. The scales correlated significantly with other measures of use and severity in two samples, and they were found to predict which cocaine users would seek help (Varney et al., 1995). An expanded second edition, with 75 items (CNCC-75) that added financial and vocational items (Rohsenow, Monti, et al., 2004), has been reported to yield equally high reliability estimates and predicts cocaine use outcomes after treatment.

Expected Effects of Use

In addition to assessing past consequences, often due to longer term use, the assessment of positive and negative effects expected fairly immediately from an episode of substance use can be used as feedback in motivational interviewing (Miller & Rollnick, 1991, 2002) or in functional analysis-based coping skills training (Rohsenow, Monti, et al., 2004). These measures are inherently specific to specific substances. Measures developed on and for college students are not covered because they are not known to be relevant to clinical populations and often involve a high reading level and large number of items.

Expectancies Across Four Substances

A brief Substance Use Beliefs Questionnaire (SUBQ) was designed to assess expected effects of alcohol, nicotine, opiates, and stimulants among users seeking treatment or willing to seek treatment (Kouimtsidis, Stahl, West, & Drummond, 2014). The two resulting factors are positive versus negative expectancies, with good criterion and predictive validity. The 98-item original version was reduced to 28 items, with evidence of excellent internal reliability estimates and substantial correlations with the long version. The negative expectancies scales predicted change in dependence level 3 months after treatment. No other measures of opiate or stimulant expectancies were found that had evidence of at least adequate reliability and validity. Most other measures of alcohol expectancies were developed on and for university students, most of whom did not have alcohol diagnoses.

Expectancies for Cocaine

The Cocaine Effects Questionnaire for Patient Populations (CEQ; Rohsenow, Sirota, Martin, & Monti, 2004) is a 33-item self-report instrument with seventh-grade reading level that assesses seven factors of fairly immediate positive and negative effects that patients said they expected from cocaine use. Reliability and validity estimates have been found to be good, with several subscales correlated with amount of cocaine use and with urge to use cocaine. This information was used in coping skills treatment planning by helping patients identify alternative nondrug ways to obtain desired positive effects and to remind patients of negative experiences they wish to avoid (Rohsenow, Monti, Martin, Michalec, & Abrams, 2000), and it was used in motivational interviewing as a way to augment discussion of advantages and disadvantages of cocaine use (Rohsenow, Monti, et al., 2004). Other cocaine expectancy measures and a parallel measure for marijuana expectancies have been developed on college populations, most of whom did not use cocaine/marijuana, much less meet criteria for SUDs, so these measures are not considered useful for patient populations.

(p. 370) Assessment for Relapse Prevention

According to social learning models of relapse prevention (e.g., Monti et al., 2002), some of the most important areas to assess for treatment intervention include (a) situations (interpersonal, emotional/cognitive, and environmental) that increase risk of relapse, (b) self-efficacy about staying abstinent (both in general and in specific high-risk situations), and (c) types of coping skills available to use and/or actually used when in high-risk situations or in general to prevent relapse. If initiation of abstinence in treatment seekers who are not abstinent is the goal, these same domains are important to target. The use of other substances is another source of relapse risk, but methods of monitoring these are covered in other sections of this chapter.

Assessing High-Risk Situations

The Inventory of Drug Taking Situations (IDTS; Annis & Martin, 1985; Turner, Annis, & Sklar, 1997) assesses high-risk situations for relapse based on common domains of relapse risk situations. The categories were derived from analyses of alcohol-dependent patients’ relapse risk situations and therefore omit some triggers relevant to people with drug dependence (e.g., the presence of money or ATM cards [Rohsenow et al., 2000; Rohsenow, Monti, et al., 2004]), but the measure was normed on 364 drug-dependent patients with primary cocaine (n = 159), cannabis (n = 98), or alcohol use disorders (n = 76). Factor structure and reliability estimates have been shown to be good, but there is no simple way to validate items on actual risk situations. The 50 self-report items fall into factors of unpleasant emotions, pleasant emotions, physical discomfort, testing personal control, urges/temptations to use, conflict with others, social pressure to use, and pleasant times with others. These factors can be grouped into three second-order factors (with good psychometric model fit): negative situations, positive situations, and urges and testing personal control. Although the reliability (internal consistency) estimate was poor for the physical discomfort scale, all other scales have demonstrated acceptable to good reliability. For each situation described, patients report how often they have used drugs in that situation in the past. The information can be used to design personalized relapse prevention training by emphasizing skills needed for handling the situations a person has actually most often associated with drug use.

For identifying highly idiosyncratic relapse risk situations, the Drinking Triggers Inventory (DTI; Monti et al., 2002; Rohsenow et al., 2001), a structured interview developed to identify highly personal relapse risk situations for use in cue exposure therapy, is easily adapted for use with any drug of abuse, as was done in identifying personal high-risk situations of cocaine-dependent patients as the basis of functional analysis-based cocaine-specific coping skills training (Monti, Rohsenow, Michalec, Martin, & Abrams, 1997; Rohsenow et al., 2000). However, there is insufficient psychometric information to allow this instrument to be rated in the table.

Assessing Self-Efficacy

Self-efficacy for ability to resist using in high-risk situations can be useful at any stage of treatment for identifying situations in which a patient expects to have the most trouble. These can be assessed with several measures. First, the Drug-Taking Confidence Questionnaire (DTCQ; Sklar, Annis, & Turner, 1997) is a 50-item measure that uses the same list of situations as in the IDTS to assess self-efficacy. It requires respondents to rate how confident they are that they would be able to resist the urge to use drugs in that situation. Thus, the IDTS is behavioral but past-oriented, whereas the DTCQ is more subjective but future-oriented. This measure also was developed on people with a range of types of SUDs. The confirmatory factor analysis supported essentially the same three high-order factors as the IDTS: positive situations, negative situations, and temptation situations. An 8-item short form also has been found to have generally good psychometric properties (Sklar & Turner, 1999).

Second, the Alcohol Abstinence Self-Efficacy Scale (AASE; DiClemente, Carbonari, Rosario, Montgomery, & Hughes, 1994) has patients rate 20 situations on 5-point scales for how confident they are that they would not drink in each situation and again for how tempted they are to drink. The categories of high-risk situations included are (a) negative affect, (b) social interactions and positive states, (c) physical and other concerns, and (d) withdrawal and urges. The total score had high internal reliability and good validity. A brief 12-item version (McKiernan et al., 2011) has two factors (temptation and confidence) with high internal consistency and concurrent validity. This would be less useful for treatment planning because only 6 situations are involved. It also has been adapted for use with drug abusers as the Drug Abstinence Self-Efficacy Scale (DASE; Hiller, Broome, Knight, & Simpson, 2000), resulting in the same four subscales. However, because information on reliability and validity was not found, this measure was not rated in the table.

(p. 371) Third, in the Cocaine Related Assessment of Coping Skills (Rohsenow, Monti, et al., 2004), cocaine-dependent patients rated how confident they would be to refrain from substance use in each of 11 high-risk situations. The score demonstrated high internal consistency and concurrent validity, and it predicted quantity and frequency of drug use 3 months after treatment (Dolan, Martin, & Rohsenow, 2008).

Fourth, a simple 4-point rating of confidence that the person would not use drugs again during a specific period of time predicts treatment outcome for opiate addicts (Gossop, Green, Phillips, & Bradley, 1990). However, there is insufficient information on this measure to rate it in the table, and the broader situation-specific measures are preferable because they can be used to individualize relapse prevention and/or coping skills training by focusing on the types of situations in which the patient would be most tempted to use or least confident about abstaining from use.

Assessing Coping Skills

Only a few studies investigating coping to predict outcome for opiate abusers used measures with substantial evidence of reliability and validity. In one such study, 10 items were selected from the psychometrically sound Processes of Change Questionnaire (POC; Prochaska, Velicer, DiClemente, & Fava, 1988). Among opiate-dependent individuals, abstinence was related to an increase in the 10 processes of change assessed (POC-10; Gossop, Stewart, Browne, & Marsden, 2002). These items were categorized into Avoidance (“remove things from my home that remind me of drugs,” “stay away from people who remind me of drugs,” and “stay with people who remind me not to use”), Cognitive (“I tell myself I can choose not to use drugs,” “I can keep from using if I try hard enough,” “I am able to avoid using if I want to,” and “I must not use to be content with myself”), and Distraction (“physical activity,” “do something to help me relax,” and “think about something else when tempted to use”). Scores for these three categories had adequate to good internal consistency reliability in this study, and all three types of coping were significantly greater in abstainers, suggesting that only these 10 items are needed for use with opiate-dependent patients.

Because existing measures tapped only a limited number of the specific skills taught in many treatment programs, we developed measures of coping skills to be used in high-risk situations (the Urge-Specific Strategies Questionnaire [USS]) and of lifestyle change skills designed to maintain abstinence (the General Change Strategies Questionnaire [GSC]). The measures were developed, found to each consist of a single factor with excellent internal consistency, and validated first with alcohol-dependent patients in treatment, with the summary scores for each differentiating between coping skills treatment versus control treatment and correlating with treatment outcome 3 to 6 months later (Monti et al., 2001). In analysis of the value of individual strategies, 13 of the urge-specific strategies and 18 general lifestyle change strategies correlated with successful treatment outcome 3 to 6 months after treatment, whereas other common strategies did not (Dolan, Rohsenow, Martin, & Monti, 2013), thus indicating the most important coping skills to focus treatment on. The measure was then adapted for use with cocaine-dependent patients in treatment with 21 strategies in each measure, with each forming scales that demonstrated substantial reliability and validity estimates (Rohsenow et al., 2005). These were used to determine the specific skills that were correlated with less cocaine use at 3 and 6 months post-treatment, with results indicating that 13 of the USS strategies and 12 of the GSC strategies were effective in this regard (Rohsenow et al., 2005). Thus, the measures were found to be heuristic across two types of substance use disorders. The open-ended section can be used to elicit patients’ free recall of all the strategies they plan to use, and the frequency ratings are used to assess how often they say they have used each strategy. By identifying the skills the patients already know or use, gaps in knowledge or use of effective skills can be targeted for treatment.

Overall Evaluation

There are a variety of clinically useful instruments that can be used in treatment planning. There is a choice of scientifically sound measures that provide an evaluation of the patient’s ability to function across major life areas. Whether or not problems in some of these areas result from drug use, these areas may need to be addressed in treatment so as to maximize the individual’s structural and functional support for abstinence, motivation to stay clean and sober, and quality of life. Drug-specific consequences an individual experienced can be particularly useful in sustaining or increasing the person’s motivation to become or stay abstinent from drugs by highlighting what he or she has to gain from abstinence, whereas expected acute effects can be used in functional analyses to focus on alternative ways to achieve many of (p. 372) the desired outcomes (e.g., negative affect reduction or social facilitation). The measures of situations in which the patient would be more tempted to use or have less confidence about staying abstinent can be used to target relapse-prevention treatment toward helping the patient learn to better avoid or cope with unavoidable high-risk situations without using. Measures of both urge-specific and general lifestyle coping have been developed to assess a range of coping skills that have been shown to be related to reduced alcohol or cocaine use after treatment and can be used to identify gaps in individual patients’ needed skills. Good measures of social support for abstinence may not be needed because such support is easy to evaluate informally in a way that predicts outcome (e.g., better treatment outcome for cocaine-dependent patients was predicted by number of people in one’s network regardless of their support for treatment and by replacing substance-involved with substance-free daily contacts in one’s network [Zywiak et al., 2009]).

The measures selected for inclusion in this section are all ones that could be good clinical tools, although some require considerably more training and time than others, and time is often of short supply in many treatment contexts. Some of the measures in Table 17.2 with good psychometric properties are not highly recommended simply due to the amount of time and training required for administration and the complexity of the scoring (i.e., SDSS and ASI-6). Other measures were not highly recommended because they were specific to only one substance (e.g., CNCC-87 and CEQ). The ones rated as highly recommended are the ones with good psychometric qualities and seeming utility for treatment planning that are also relatively easy to administer.

Assessment for Treatment Monitoring and Treatment Outcome

There are several assessment measures and strategies that can be used to track the effects of treatment on substance use and problem severity. In addition to the IDUC, SIP-AD, and MPS described previously, the main options are indices of symptom severity and toxicology analyses. Details of the psychometric properties of these measures are presented in Table 17.3.

Table 17.3 Ratings of Instruments Used for Treatment Monitoring and Treatment Outcome Evaluation

Instrument

Norms

Internal Consistency

Inter-Rater Reliability

Test–Retest Reliability

Content Validity

Construct Validity

Validity Generalization

Treatment Sensitivity

Clinical Utility

Highly Recommended

ASI-6 30-day

NA

G

G

G

A

A

G

NR

NR

TLFB

NA

NA

G

G

NA

E

E

E

A

IDUC

NA

E

NA

G

G

A

A

A

A

SIP-AD

NA

E

NA

G

G

A

A

A

A

MPS

NA

NR

NA

NR

NR

A

NR

A

NR

GAIN 90 Day M

NA

G

NA

NA

G

G

A

A

A

Urine screens

NR

NA

NA

NA

NA

A

E

L

Aa

Urinalysis

G

NA

NA

NA

NA

G

E

E

Ea

a Utility is excellent during the time a program requires 3 to 7 days/week of attendance, but with high cost.

Note: ASI = Addiction Severity Index 30-day form; TLFB = Timeline Followback Interview; IDUC = Inventory of Drug Use Consequences, four scales; SIP-AD = Short Inventory of Problems–Alcohol and Drugs; MPS = Marijuana Problems Scale; GAIN 90 Day M = Global Appraisal of Individual Needs–90-Day Monitoring version; urine screens = drug screening with on-site test kits; urinalyses = urine drug toxicology analyses using standard commercial laboratory methods such as EMIT or gas chromatography; L = Less Than Adequate; A = Adequate; G = Good; E = Excellent; NR = Not Reported; NA = Not Applicable.

Assessing Areas of Life Function

A briefer (118-item) form of the ASI-6 (ASI-30 day; described previously) that includes only the questions with a 30-day time frame is commonly used for tracking progress. However, there are few psychometric data on the value of using the ASI to predict outcome or track progress. Although this measure can be used to track changes in functioning on a monthly basis, it is unclear the extent to which changes in ASI-6 scores correlate with changes in drug use during the same time period. Changes in life functioning could be somewhat independent from changes in substance use, depending on the extent to which these are direct targets of treatment. However, increase in future crime at 2 years was predicted by change in alcohol use from 0 to 6 months and not by (p. 373) the legal, drug, or other ASI Version 5 scores (Alterman et al., 1998), contrary to what one would expect.

The GAIN Monitoring 90-Day version (Dennis, Scott, Godley, & Funk, 1999; (http://www.chestnut.org/li/gain) is designed to evaluate change over time in living arrangements, substance use (frequency, situational antecedents, withdrawal, and problematic consequences), treatment (use, satisfaction, and medications), physical health, risk behaviors, emotional health, legal system events, vocation, and finances. The full measure takes 60 minutes and core questions take 25 minutes, with a 10-minute Quick Monitoring version available. The measure has excellent statistics on change over time in the most relevant areas across a variety of types of substance treatment settings.

Assessing Drug and Alcohol Use Frequency

Although Timeline Followback (TLFB; Ehrman & Robbins, 1994; Sobell & Sobell, 1980), a method of asking about daily drug or alcohol use, is used primarily in research, when retrospective self-report of days of use is desired, this method has been found to be the least subject to memory problems. The TLFB is a calendar-assisted structured interview that provides a way to cue memory so that recall is more accurate. For the period of time of interest, the person is asked to fill in all days with special events such as holidays, birthdays, and days in jail or hospital. The person is then asked about alcohol/drug use on those days and the days immediately before and after those days, with other days gradually filled in from there. Although social drinkers cannot easily do this, people with alcohol or drug use disorders are better at remembering this information. The TLFB has been found to yield good to excellent reliability and validity estimates (Ehrman & Robbins, 1994; Sobell et al., 1996) when the previous caveats about self-report measures of substance use (see the section titled Increasing Honest Reporting) are taken into account. This method has been found to be sensitive to SUD treatment effects across a great many studies (e.g., McKay et al., 1997; Rohsenow, Monti, et al., 2004).

Assessing Consequences of Drug or Alcohol Use

The IDUC (Tonigan & Miller, 2002), a 50-item self-report measure of the consequences of drug or alcohol use, has a version asking about the past 3 months that can be used for tracking progress using the four scales with evidence of substantial reliability (physical problems, social relationships, interpersonal problems, and impulse control). These scales were sensitive to changes in drug use behavior over 3 months so that a 40% decrease in drug use was paralleled by a 33% decrease in drug-related consequences (Tonigan & Miller, 2002). The short form reviewed previously, the SIP-AD (Blanchard et al., 2003), is sensitive to treatment change, decreasing from pre- to post-treatment, and with post-treatment SIP-AD scores correlating as expected with post-treatment number of substance use days (Blanchard et al., 2003). Both measures are rated in Table 17.3. Because of the demonstrated sensitivity of these measures to change combined with ease of administration, they are highly recommended.

The MPS (Stephens et al., 2000), in the 19-item 90-day version, may be used to track change in marijuana-related problems. The MPS was sensitive to change in problems during a 4-month period among marijuana-dependent patients in active treatment versus delayed-treatment condition that paralleled changes reported for frequency of marijuana use and number of dependence symptoms (Stephens et al., 2000). The 26-item checklist version showed no effects of treatment in one study (Budney et al., 2000) but showed a significant decrease from before to after treatment independent of type of treatment in two other studies (Budney, Moore, Rocha & Higgins, 2006; Stephens, Roffman, & Simpson, 1994). Although change over time paralleled change in frequency of use, no attempt was made to validate the measure in terms of change in other measures of problems from cannabis use. Therefore, the 19-item measure may provide a basis for seeing reduction over time in problems as a function of treatment, but replication in a second study and information on correlations of change in this measure to change in other indicators of problems are needed before the actual value of this measure is known. The limited available psychometric information prevents a high recommendation from being made for this measure.

Urine and Hair Toxicology Analyses

Urine toxicology drug analyses for substances of abuse other than alcohol are the gold standard for monitoring patients, but they require that patients still be enrolled in a program that provides them with some reason to come in for such testing 3 to 7 days per week. Urine screens and toxicology analyses test for the presence of the drugs themselves and/or of the metabolites of the drugs (metabolites permit longer detection). The drugs most commonly screened for include benzodiazepines, cocaine, opiates, amphetamines, phencyclidine, and cannabinoids. Commercial laboratories usually provide (p. 374) a standard panel of substances to be analyzed and the option of testing for other drugs upon request. The assay methodologies used in most laboratory testing methods (e.g., enzyme-multiplied immunoassay technique [EMIT] or gas chromatography–mass spectrometry [GC-MS]) yield data that are highly reliable and valid. On-site screening tests (strips or cups with detection strips built in) are far less expensive and agree 97% of the time with GC-MS results. They do, however, have increased false positives because they are designed to be highly sensitive, so positive readings generally need to be confirmed with a laboratory test. A comparison of laboratory-analyzed urine toxicology data and self-reports of days of use 12 months after treatment entry for 337 patients with SUDs found that neither urine tests nor self-reports were without their problems as a method of detection (Lennox et al., 2006). Higher validity was seen, in general, for self-reported recency of use of cocaine, opioid, and marijuana use (Lennox et al., 2006), indicating that it is of value also simply to ask patients how recently they used drugs when monitoring their use (when using the guidelines described under the section titled Increasing Honest Reporting).

There are problems that can be encountered with urine drug testing. One such problem pertains to the window of detection. For example, although methadone programs routinely require daily testing, most drugs of abuse can be detected with certainty over a 2- or 3-day window even with qualitative methods of detection (just a positive or negative answer, as opposed to quantitative methods that give the amount detected). However, because most drugs can stay in the tissues for approximately 7 days after abstinence begins, and marijuana can be detectable (50 ng/L) for 2 weeks after heavy use (Hawks & Chiang, 1986), readings may be positive for some time after abstinence begins. Therefore, programs often allow an initial washout period for the urine to become clean before imposing any consequences or before contingency management programs start voucher reinforcement based on abstinent readings (e.g., Budney et al., 2006). A second problem is the potential for false-positive test results. The methodologies involved in most laboratory tests greatly decrease the chance of false positives, yet a person can still have reason to claim that a test showed a false positive for opiates if, for example, he or she had eaten a large amount of poppy seeds. When not used for legal purposes, it may be enough to require that patients avoid all non-illicit sources of positive readings. A third problem is related to the introduction of contaminants by patients. Patients who expect unpleasant consequences from positive readings may go to great lengths to “beat” the test. This can include bringing a hidden sample of urine from a clean person, adding contaminants (e.g., soap, vinegar, lemon juice, salt, and bleach) to invalidate the test, or drinking large quantities of water before giving a sample to make the sample too dilute for a valid test. Other evasion methods have been developed, including an artificial penis or hidden plastic tubing and an IV bag with heating strips. Some of these can be overcome by requiring carefully monitored testing and requiring some hours at the site without drinking before obtaining the sample.

Testing hair for the presence of drugs of abuse has raised some interest because hair will contain residue of drugs over the length of the hair, thus providing a detection window of months or years, depending on the length of the hair. Drugs enter the hair at the follicle level via blood, sebum (from glands in the scalp), and sweat (Huestis, 2001). However, several problems limit the adoption of this method more widely to date, including two serious ones: hair color bias and environmental factors. First, drugs are more strongly detectable in darker hair than in lighter hair (Joseph, Tsai, Tsao, Su, & Cone, 1997), leading to more false negatives among blond or white-haired people than among people with brown or black hair. In addition, because the higher lipid content in curlier hair (Cruz et al., 2013) may affect absorption of lipid-soluble drugs, there is a serious concern that this would lead to racial or ethnic differences in accuracy of detection. Second, drugs also can be absorbed into the hair via environmental exposure, especially smoke, and repeated shampoo treatments or solvent washes do not completely remove environmental cocaine from the hair (e.g., Wang, Darwin, & Cone, 1994). Therefore, someone can test positive despite remaining abstinent. A third problem is that there are few places where hair testing for drugs is available. A fourth is that hair testing is less sensitive to detecting marijuana than is urine toxicology analysis, and there is great individual variability in the sweat that affects hair testing (Baron, Baron, & Baron, 2005). Therefore, hair analysis has more pitfalls than advantages at the present time. Given that urine detection is highly reliable and fully adequate for within-treatment monitoring, it remains the preferred biological method.

Overall Evaluation

For monitoring of progress in terms of drug use, urine drug analyses at least three times per week remain the gold standard. Although urine drug screens are poor at detecting alcohol use, due to the rapid metabolism (p. 375) of alcohol, these are excellent for monitoring all other drugs of abuse when the precautions described previously are handled. For monitoring of monthly change in problems resulting from drug or alcohol use or function in terms of family, legal, and psychological problems, the GAIN-90 Day M is developed for this purpose and is scientifically sound. Both methods can identify when the person might be using substances and, therefore, be in need of some additional booster counseling. The IDUC is effective in showing change in problems that result from drug use over time and so is recommended for this purpose.

Conclusions and Future Directions

The clinician treating patients with SUDs has a number of tools available for screening, diagnosis, assessment of problem severity, assessment of risk factors for relapse to address in treatment, and monitoring of treatment progress and outcomes. Some of the tools (particularly the diagnostic and some problem severity tools) are time-consuming and require extensive training: These may be more difficult to adopt into clinic practices that are short on time. Other tools are quicker and/or easier to administer and score for rapid use in treatment planning or monitoring of progress. It is hoped that future work will focus more on developing instruments that clinicians can use easily and with minimal time to provide useful guidance for treatment planning and evaluation.

Future development work with assessment instruments needs to include more of a focus on determining validity and treatment sensitivity, in particular. For example, although the ASI is widely used for monitoring treatment progress, there is very little information to demonstrate that it validly tracks changes in other indicators of progress. Given such a widely used face-valid instrument, such information would be valuable. Future work should also focus on making instruments that do not require extensive training, long administration time, and complex scoring procedures. Not only do these factors drive up costs, and often prevent use due to busy schedules, but also when extensive training is needed, it is too easy for assessors’ abilities to drift over time unless regular retraining or testing of their abilities is conducted. A number of instruments in the future will probably be available not only via computer but also via Web-based applications, allowing interactive responses with patients, computerized scoring, and access to expert help at the touch of a mouse.

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