ADD5106- Week 2 Discussion 2: Reliability and Validity

IncrementalpredictivevalidityoftheAddictionSeverityIndexpsychiatriccompositescoreinaconsecutivecohortofpatientsinresidentialtreatmentfordrugusedisorders.pdf

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Addictive Behaviors

journal homepage: www.elsevier.com/locate/addictbeh

Incremental predictive validity of the Addiction Severity Index psychiatric composite score in a consecutive cohort of patients in residential treatment for drug use disorders

Birgitte Thylstrup, Kim Bloomfield, Morten Hesse⁎

Aarhus University, Centre for Alcohol and Drug Research, Bartholins Allé 10, 8000 Aarhus C, Denmark

H I G H L I G H T S

• Entering psychiatric care was common among patients in the years following residential treatment.

• Psychiatric care and suicide were associated with self-reported psychiatric symptoms on the ASI.

• Patients that entered psychiatric care had left treatment earlier, had fewer legal problems, and more alcohol problems.

A R T I C L E I N F O

Keywords: Comorbidity Suicide Psychiatric care Drug use disorders Residential treatment Addiction Severity Index

A B S T R A C T

Background: The Addiction Severity Index (ASI) is a widely used assessment instrument for substance abuse treatment that includes scales reflecting current status in seven potential problem areas, including psychiatric severity. The aim of this study was to assess the ability of the psychiatric composite score to predict suicide and psychiatric care after residential treatment for drug use disorders after adjusting for history of psychiatric care. Methods: All patients treated for drug use disorders in residential treatment centers in Denmark during the years 2000–2010 with complete ASI data were followed through national registers of psychiatric care and causes of death (N = 5825). Competing risks regression analyses were used to assess the incremental predictive validity of the psychiatric composite score, controlling for previous psychiatric care, length of intake, and other ASI composite scores, up to 12 years after discharge. Results: A total of 1769 patients received psychiatric care after being discharged from residential treatment (30.3%), and 27 (0.5%) committed suicide. After adjusting for all covariates, psychiatric composite score was associated with a higher risk of receiving psychiatric care after residential treatment (subhazard ratio [SHR] = 3.44, p < 0.001), and of committing suicide (SHR = 11.45, p < 0.001). Conclusions: The ASI psychiatric composite score has significant predictive validity and promises to be useful in identifying patients with drug use disorders who could benefit from additional mental health treatment.

1. Introduction

Substance use disorder is rarely the only problem identified in in- dividuals presenting for treatment. Individuals seeking care for sub- stance use disorders often experience financial difficulties, social and family troubles, general health problems, and legal issues (Kessler et al., 2012; Muller, Skurtveit, & Clausen, 2016; Scheurich et al., 2000). Fur- thermore, many patients experience comorbid mental health problems (Compton, Cottler, Jacobs, Ben-Abdallah, & Spitznagel, 2003; Grant et al., 2004). Traditionally, this overlap has been interpreted to reflect the negative effects of substances of abuse on mental health, a notion that is present in diagnostic manuals, clinical guidelines, and

assessment interviews (Delgadillo, Bohnke, Hughes, & Gilbody, 2016). It is well established that substance use disorders may exacerbate and complicate mental health problems, and that patients with comorbid substance use disorders utilize much more treatment compared to pa- tients with mental health problems only (Schmidt, Hesse, & Lykke, 2011). In addition, comorbid mental health problems are likely to in- crease the already high risk of suicide among individuals with sub- stance use disorders (Darke et al., 2016). Therefore, it is important that clinicians are able to identify patients with co-morbid psychiatric dis- orders during routine intake assessment in treatment services for sub- stance use disorders, so that appropriate additional treatment can be made available to patients.

http://dx.doi.org/10.1016/j.addbeh.2017.08.006 Received 21 February 2017; Accepted 10 August 2017

⁎ Corresponding author. E-mail addresses: [email protected] (B. Thylstrup), [email protected] (K. Bloomfield), [email protected] (M. Hesse).

Addictive Behaviors 76 (2018) 201–207

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One strategy for identifying patients with such comorbidity is to assess them with comprehensive psychopathology screening instru- ments. However, given the many tasks facing substance abuse treat- ment staff, a time-saving solution may be to use data that are already available for identifying patients who may also need treatment for mental health problems. Such tools must be feasible to administer in clinical practice and have predictive validity in terms of outcomes that are relevant and of concern for this group of patients.

The Addiction Severity Index (ASI), a multi-dimensional tool, has been developed to assess problems commonly associated with sub- stance use disorders and evaluates patients' recent and lifetime func- tional status within seven areas: general health, employment status, alcohol use, drug use, legal status, family and social relationships, and psychiatric health (Mclellan et al., 1992). The ASI is widely used and has been translated into a number of languages, including Japanese, (Ogai et al., 2015), Mandarin (Sun et al., 2012), German (Scheurich et al., 2000), and Danish (Pedersen, Hesse, & Thylstrup, 2013).

Among the most commonly used ASI metrics in the assessment of functional status are the composite scores (CSs). The CSs are sets of indices, which are calculated from the items within each of the seven ASI problem areas that refer to experiences in the past 30 days. CS scores range from 0.0 to 1.0, where higher scores represent more severe problems within the domain.

The ASI psychiatric CS has been shown to be associated with psy- chiatric status in a large number of cross-sectional studies. For instance, the ASI psychiatric CS is associated with lifetime stress (Mahoney, Newton, Omar, Ross, & De La Garza, 2013) as well as psychiatric di- agnoses assessed by the Structured Clinical Interview for the DSM, Axis I disorders (Cacciola, Pecoraro, & Alterman, 2008), and also correlates highly with the similar domain in the SF-36 health survey (Calsyn et al., 2004). Verthein and colleagues reported that the ASI psychiatric CS correlated strongly with concurrent mental health symptoms, but also that CS scores decreased in the most severe group at four-year follow-up (Verthein, Degkwitz, Haasen, & Krausz, 2005).

However, few studies have assessed the predictive validity of the ASI psychiatric CS in terms of its capacity to predict outcomes such as need for psychiatric care or suicide. A study by Wryobeck and collea- gues found that the ASI composite score predicted inpatient psychiatric episodes six months after admission to treatment, although after con- trolling for psychiatric diagnoses and demographic variables the results were no longer significant (Wryobeck, Chermack, Closser, & Blow, 2006). More recently, using a longitudinal design, Drymalski and Nunley were able to predict psychiatric inpatient admissions among a large group of substance use disorder patients from a single uptake area (Drymalski & Nunley, 2016). Based on a receiver operating character- istic analysis (ROC), they found that the ASI psychiatric CS significantly predicted inpatient treatment within 12 months of admission to drug treatment with an area under the ROC curve of 0.75. However, Dry- malski and Nunley also noted that the specificity of the ASI psychiatric CS was poor regardless of cut-point, indicating that a large proportion of the patients who reported psychiatric symptoms were never admitted to inpatient psychiatric care after treatment for substance use disorders. Finally, Olsson et al. used individual items from the ASI to predict psychiatric hospitalizations in a sample of prison inmates (Olsson, Ojehagen, Bradvik, & Hakansson, 2015). They tested individual items from the psychiatric CS, and found that even individual items predicted psychiatric care.

To our knowledge, no studies have as yet assessed the ASI psy- chiatric CS as a predictor of completed suicide, despite that roughly 90% of those dying by suicide have been reported to have a psychiatric disorder at the time of their death (Hawton, Comabella, Haw, & Saunders, 2013). Furthermore, suicide has been associated with a large number of life-years lost (Darke et al., 2016), especially in younger individuals. Identifying patients with drug use disorders [DUD] who are also at high risk of suicide is an important public health task (Johnsson & Fridell, 1997). Although suicide rates have been

steadily rising in some countries such as the US (Galynker et al., 2016), it presents a challenging task to study, as it is still a relatively rare event, and therefore requires relatively large samples and long follow- up times to adequately study such events. If patients with mental health needs can be easily identified using data that are available as part of routine intake assessment, including those at risk of suicide and/or in need of further mental health treatment, such analyses may help de- monstrate the need for faster and more effective interventions that can both improve patients, quality of life, and reduce risks of early death and disability.

Building on the work of Wryobeck et al. (2006) and Drymalski and Nunley (2016), the present study uses a consecutive cohort of in- dividuals undergoing residential treatment for drug use disorders [DUD]. The study elaborates upon the previous studies in three ways: first, it uses a longer period of observation of up to 12 years for time-to- event analyses; secondly, it increases the range of outcomes under study to include completed suicide in addition to psychiatric care; and thirdly it adjusts for previous history of hospital-based mental health care.

2. Methods

2.1. Study setting, data sources and sample

This retrospective cohort study used secondary data from DanRIS, the Danish national monitoring and quality assurance database for in- patient treatment of DUD (Pedersen et al., 2013). Patients were in- cluded if they received care within one of the 58 residential facilities, for which EuropASI data were available from 2000 to 2010, and were between 15 and 75 years of age at the time of admission. Patients were excluded if they did not have a valid Danish personal identification number, or if they did not have a valid date of admission or discharge from the unit at which they had been admitted for treatment.

The data for this study are stored on secure servers at Statistics Denmark, and all procedures were approved by the Danish Data Protection Agency. Since the data used for this study were collected and stored for monitoring and quality assurance, no ethics evaluation was needed under Danish law.

2.2. Registers

The DanRIS register is a national register of public and private in- patient treatment for DUD. The register began in 2000. All patients are registered by their personal identification number, and the register contains brief demographic information, the 30-day version of the EuropASI, as well as dates of admission and discharge. We continued to follow patients over the entire observation period beginning from their first admission to a residential treatment facility, although some pa- tients may have been in in-patient treatment prior to the introduction of the DanRIS. If a patient had multiple episodes of treatment, we ana- lyzed that patient's first episode.

The Danish Registry for Causes of Death was used to identify in- dividuals who died of suicide. Since 1875, the Danish National Board of Health has maintained the registries covering deaths among all Danish residents dying in Denmark, and since 1970 such records have been computerized. ICD-10 codes were used to classify deaths (Helweg- Larsen, 2011).

The Danish Central Psychiatric Research Register has recorded episodes of psychiatric care since 1970. These records include dates of beginning and end of treatment, diagnoses, type of referral, place of treatment, place of residence, and mode of admission (Mors, Perto, &Mortensen, 2011). A dummy code was created to indicate whether a patient had been admitted to psychiatric care in the ten years leading up to admission to in-patient DUD treatment.

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2.3. Measures

2.3.1. European Addiction Severity Index (EuropASI) The EuropASI is a multidimensional, semi-structured interview that

assesses nine substance-related problem areas that are often affected by substance use: medical, job situations, concerns about employment, legal, alcohol, drug use, family relationships, social functioning, and psychiatric status (Kokkevi & Hartgers, 1995). The EuropASI has nine sections instead of seven found in the original ASI: employment has been split into two sub-sections (economic situation and concerns about work), and the relationships area is replaced with two new sections (relationship with family and relationships with others).

Each of the nine sections provides a composite score based on three to 13 questions asked about the past 30 days. The EuropASI psychiatric CS is identical to the ASI psychiatric ASI, and is referred to here as the ASI CS.

2.3.2. Outcomes We chose to examine two outcome measures after in-patient DUD

treatment: psychiatric treatment episodes and completed suicide. For both variables, time-to-event was calculated as days since discharge from in-patient treatment to the respective event. A psychiatric treat- ment episode was counted if it began after the date of discharge, re- gardless of whether it was an in-patient, out-patient, or an emergency psychiatric episode. Patients who died without having received psy- chiatric care in the period between discharge and death were coded as “competing” observations (see Analyses section); patients who did not have any psychiatric care and did not die before December of 2012, were coded as “censored”. Deaths were counted as suicides if the un- derlying cause of death was registered as due to intentional self-harm (ICD-10 X6-X8).

Covariates were selected a priori and based on their availability in the national databases as well as their known or potential associations with both outcomes. Covariates included age, gender, history of psy- chiatric care in the past 10 years, and length of DUD treatment. In the final, fully adjusted model, all other ASI CSs were also included as covariates.

2.3.3. Analyses Descriptive statistics were calculated for the whole sample, as well

as for the subsets of those who had come into psychiatric care after DUD treatment discharge, or who had committed suicide within the ob- servation period. Cronbach's α was calculated for all ASI CSs using standardized item values.

We used cause-specific hazard modelling to estimate the association between baseline characteristics and the incidence rate of suicide and

psychiatric care. All analyses were performed using Stata, version 13.1(“Stata I/C,” 2016).

Time-to-event analyses were conducted for all independent vari- ables using Fine and Gray's method (Fine & Gray, 1999), in which the cumulative incidence function (CIF); i.e., Ce (t) gives the proportion of patients at time t who have experienced event e, while accounting for the fact that patients can experience another event that prevents event e from happening, labeled the competing event or competing risk (e.g., death will rule out later admission to psychiatric care).

Coefficients are expressed as cause-specific incidence ratios, also known as subhazard ratios, or the relative subhazard. In order to eliminate excess skewness, we log-transformed length of admission. We dummy-coded the variable of “objective employment situation” (0: no days of work in the past 30 days, not income from a salary, 1: any days of work or any income from salary), due to substantial skewness and an abundance of 1.00 values. Because models for two different outcome variables, were examined, we set statistical significance at p < 0.025.

3. Results

3.1. Sample description

A total of 8268 individuals were initially identified in the DanRIS register in the study period of 2000 through 2010. Of these patients, 2042 patients had not completed the ASI, and 401 were excluded for other reasons (i.e., 101 were outside the age range, 67 had invalid dates of discharge or invalid identification numbers, and 233 had missing data on the ASI psychiatric area). Thus, 5825 patients remained for the analyses. The average follow-up time for patients from DUD discharge to their first subsequent treatment admission or death or censoring was 6.38 years, and the total follow-up time was 37,193 person-years.

The descriptive statistics for the total cohort are summarized in Table 1. The sample was predominantly men (77%), and the mean age was almost 32 years. Nearly half had been in psychiatric care at least once in the ten years prior to their first DUD treatment admission (42%). The ASI composite scores had adequate internal consistency in this sample. The CS for financial problems had the highest value, fol- lowed by psychiatric issues and then the drugs score. The area scoring the lowest was employment issues. Following discharge from treatment admission, 1769 of the 5825 patients received psychiatric care at least once during the study follow-up period (30.4%). The most common type of such psychiatric care was outpatient (25.0%), followed by emergency services (23.1%), and in-patient care (20.8%) (data not shown). A total of 342 patients died before potentially receiving any psychiatric care after discharge from DUD treatment, and the remaining 3714 were censored.

Table 1 Descriptive statistics (N = 5825).

All patients, at outset

Cronbach's α Patients who subsequently committed suicide (n = 27)

Patients subsequently admitted for psychiatric care (n = 1769)

Men 4458 (76.5%) 26 (83.9%) 1314 (71.5%) Any psychiatric care in past 10 years 2557 (42.4%) 19 (70.4%) 1219 (65.1%) Mean age at admission (mean, standard

deviation) 31.71 (9.24) 30.81 (8.90) 30.89 (9.12)

ASI composite scores (mean, standard deviation)

Drugs 0.41 (0.21) 0.715 0.44(0.23) 0.42 (0.21) Alcohol 0.24 (0.30) 0.761 0.26(0.29) 0.27 (0.31) Legal 0.24 (0.26) 0.808 0.34(0.29) 0.24 (0.27) Work 1. Concerns about work 0.13 (0.25) 0.749 0.11 (0.26) 0.13 (0.25) Work 2. Financial 0.82 (0.34) 0.549 0.71 (0.36) 0.84 (0.31) Family 0.34 (0.30) 0.712 0.38 (0.28) 0.37 (0.30) Social 0.28 (0.28) 0.660 0.28 (0.27) 0.32 (0.28) Psychiatric 0.45 (0.26) 0.809 0.58 (0.22) 0.53 (0.25) Medical health 0.35 (0.38) 0.898 0.37 (0.35) 0.39 (0.38)

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The proportion of patients endorsing each item of past 30 days psychiatric ASI CS by follow-up status is given in Appendix Table 1, along with univariate log-rank tests for their associations with sub- sequent suicide and psychiatric care. The most common symptom was depressed mood, reported by 74%, and the least common was suicide attempts reported by 11.8%.

3.2. Hospital-based psychiatric care after discharge

The cumulative incidence function stratified by quartiles of severity on the ASI psychiatric CS is displayed in Fig. 1. Time is measured in days since discharge. As can be seen, the likelihood of utilization of psychiatric care increased approximately linearly across all quartiles of severity of ASI psychiatric CS.

The predictors of post-DUD treatment psychiatric care are sum- marized in Table 2. In all models, the ASI psychiatric CS was sig- nificantly associated with increased likelihood of entering post-treat- ment psychiatric care (p < 0.001) The Wald χ2 for the full model was 1162.21 (degrees of freedom = 14, p < 0.001). In addition to the ASI

psychiatric CS, younger age at DUD residential treatment intake, ad- mission to residential treatment earlier in the period, shorter length of time in treatment, previous psychiatric care, a higher score on alcohol CS, and a lower score on legal CS, were all associated with a higher likelihood of psychiatric care in the full model.

3.3. Completed suicide after discharge

Following discharge, 27 of the 5825 patients committed suicide, 551 patients died of other causes, and 5247 were censored. Of the 27 suicides, 17 were by self-poisoning (63%, ICD-10 X60-X69), 9 were by violent means, such as hanging or firearms (33%, X70-X79), and one was by jumping or lying before a moving object (4%, X81) (data not shown).

The cumulative incidence plot for time to suicide after DUD-treat- ment discharge is shown in Fig. 2, stratified by quartiles of severity on the ASI psychiatric CS. As can be seen, the likelihood of suicide in- creases approximately linearly over quartiles, although the two top quartiles are very close to each other.

Predictors of suicide are summarized in Table 3. In all Models, ASI

Fig. 1. Cumulative incidence estimates for psychiatric care after discharge from re- sidential treatment based on ASI psychiatric health composite scores (CS).

Table 2 Predictors of psychiatric hospitalizations using competing risks regression (N = 5825).

Model 1 Model 2 Model 3

SHR 95% CI SHR 95% CI SHR 95% CI

ASI Psychiatric 4.400 3.48 to 5.57 2.950 2.34 to 3.72 3.444 2.66 to 4.46 Gender – 1.122 1.02 to 1.23 1.114 1.00 to 1.24 Age at intake – 0.985 0.98 to 0.99 0.984 0.98 to 0.99 Year of admission – 0.967 0.94 to 0.99 0.960 0.94 to 0.98 Length of admission 0.878 0.81 to 0.95 0.878 0.81 to 0.95 Any psychiatric care in past 10 years – 2.954 2.56 to 3.42 2.886 2.52 to 3.31 Other ASI composite scores Drug – 0.817 0.61 to 1.09 Alcohol – 1.260 1.04 to 1.53 Legal – 0.727 0.61 to 0.87 Work 1. Concerns about employment – 1.036 0.80 to 1.34 Any work – 0.779 0.60 to 1.02 Family – 0.875 0.76 to 1.00 Social – 1.015 0.84 to 1.23 Medical – 0.927 0.81 to 1.06

ASI: Addiction Severity Index. SHR: Subhazard ratio. CI: 95% Confidence intervals. Coefficients in boldface are significant at p < 0.025. Model 1: Unadjusted subhazard ratio. Model 2: Adjusted for gender, age, previous psychiatric care, length of admission, and year of admission. Model 3: Adjusted for all covariates in Model 2 and all other ASI composite scores.

Fig. 2. Cumulative incidence estimates for suicide after discharge from residential treatment based on ASI psychiatric health composite scores (CS).

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psychiatric CS was associated with increased risk of suicide (p < 0.001). The Wald χ2 for Model 3 was 125.29 (degrees of freedom = 14, p < 0.001). In addition to the ASI psychiatric CS, previous psychiatric care was the only other variable associated with a higher likelihood of completed suicide after DUD treatment discharge.

4. Discussion

This study has demonstrated with longitudinal data the predictive validity of the ASI psychiatric CS for two objectively measured psy- chiatric outcomes: use of psychiatric care and suicide after discharge from in-patient treatment. Baseline Psychiatric CS scores had a positive association with both outcomes over the follow-up period. In addition, the association between ASI psychiatric CS and psychiatric care was a clear dose-response association, in which the higher the quartile of scores, the greater the risk of post-DUD treatment care. For suicide, the dose-response association was somewhat less clear. This could well be because the total number of suicides in the cohort was only 27, and thus when sub-dividing the cohort into four subgroups, the number of sui- cides in each would necessarily be very small, reducing the power to observe a dose-response relationship.

Associations for both outcomes remained significant, even after controlling for psychiatric care prior to admission for in-patient treat- ment, as well as other ASI CSs, and demographic characteristics. This suggests that the ASI psychiatric CS has incremental validity by re- maining significant after controlling for important potential con- founders, in particular psychiatric treatment history.

The finding that the psychiatric CS had incremental predictive va- lidity in terms of psychiatric care after treatment contradicts with the findings of Wryobeck and colleagues, who found that the ASI psy- chiatric CS was no longer significant after adjusting for psychiatric di- agnoses and other confounders. However, in their study, patients were assessed using diagnostic interviews at the same time that they were administered the ASI. It is thus possible that the two different measures could cancel each other out, because the variance in the ASI psychiatric CS was already captured in the diagnoses (Wryobeck et al., 2006).

Given the adequate sample size and length of follow-up of our study, we were able to test the predictive validity of the psychiatric CS for completed suicide. Our results demonstrate that the psychiatric CS identifies individuals at significantly elevated risk for suicide. This is

indeed the most important strength of the present study: that we have been able to employ a longitudinal design of adequate length and have been able to analyze “hard” objectively assessed measures as our study outcomes. Nordic registry data have long enjoyed a reputation for their solid validity (Helweg-Larsen, 2011).

A number of other findings from this study deserve comment. It is interesting that no other independent variables were associated with the risk of completed suicide. This reinforces previous research, which has found that depression is the most important risk factor associated with suicide (Hawton et al., 2013; Miret, Ayuso-Mateos, Sanchez- Moreno, & Vieta, 2013), and the ASI psychiatric CS contains questions on depression. In contrast, regarding post-DUD treatment psychiatric care, several factors were associated with its utilization, allowing for a characterization of the type of patients who are likely to receive such care after discharge from residential substance abuse treatment. These patients are more likely to be young, to have low scores on legal pro- blems in ASI, to have spent a short time in treatment, and to be more likely to have severe alcohol problems. Young patients with high legal severity may be more likely to display behavior that will exclude them from psychiatric care at comparable levels of psychiatric severity. However, the findings also suggest that a longer stay in treatment may have some protective effects in terms of mental health.

4.1. Implications for practice

The findings of this study are significant, because they point to the potential usefulness of the ASI psychiatric CS, which is often routinely collected as part of clinical intake at treatment centers for substance use, where resources for quality assurance are often limited. Furthermore, the findings may have important implications for im- provement of services, or for clinical administrators interested in monitoring outcomes in populations of patients after intensive treat- ment for drug use problems. If patients with elevated symptom scores on ASI psychiatric scores can be referred to mental health treatment during or immediately after intensive drug abuse treatment, it could potentially result in less need for costly hospital-based treatment, assure a better quality of life, or even prevent suicide.

There is indeed evidence that patients with mental health problems, in addition to DUD, may be helped by treatment for mental health problems that is integrated with treatment for alcohol and DUD. At

Table 3 Predictors of suicide using competing risks regression (N = 5825).

Model 1 Model 2 Model 3

SHR 95% CI SHR 95% CI SHR 95% CI

ASI Psychiatric 7.829 2.07 to 29.61 5.937 1.41 to 25.07 11.453 1.99 to 65.99 Gender – – 0.438 0.17 to 1.12 0.478 0.19 to 1.20 Age at intake – – 0.988 0.94 to 1.04 0.996 0.95 to 1.04 Year of admission – – 0.876 0.78 to 0.99 0.877 0.78 to 0.98 Length of admission – – 1.133 0.76 to 1.68 1.114 0.75 to 1.65 Any psychiatric care in past 10 years – – 2.810 1.22 to 6.47 2.496 1.18 to 5.28 Other ASI composite scores Drug – – – – 0.612 0.07 to 5.04 Alcohol – – – – 0.840 0.27 to 2.59 Legal – – – – 2.959 0.46 to 18.87 Work 1. Concerns about employment – – – – 0.665 0.13 to 3.55 Any work – – – – 1.361 0.38 to 4.93 Family – – – – 0.937 0.23 to 3.89 Social 0.316 0.06 to 1.59 Medical 0.770 0.25 to 2.35

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least one meta-analysis (Hesse, 2009), as well as clinical trial research (Baker et al., 2014; Delgadillo et al., 2015; Watkins et al., 2011), in- dicate that both mental health problems and substance abuse can re- spond to psychotherapy. Moreover, there is robust evidence that anti- depressants can be helpful, even if the effects are larger when patients are abstinent before being treated (Hesse, 2004; Nunes & Levin, 2004). Finally, the findings point to a subset of patients at high risk of not receiving psychiatric care, possibly indicating that these patients have difficulty accessing care (i.e., patients with significant criminality who terminated treatment early). Special strategies may be needed to in- clude these patients in mental health services, such as psychoeducation for antisocial personality disorder (Hesse & Thylstrup, 2016; Thylstrup &Hesse, 2016).

Research generally has supported the link between psychopathology and severity of dependence. However, we agree with Delgadillo and colleagues, that assuming that scores on the ASI psychiatric CS are al- ways drug-induced is ethically questionable, especially if such practices hamper a timely diagnosis and access to mental health care. At present, a large number of instruments are already used to assess psycho- pathology in patients with substance use disorders, including symptom- specific self-report measures and brief screeners (Delgadillo et al., 2016; Watkins et al., 2011), clinical rating scales (Mehtry, Nizamie, Parvez, & Pradhan, 2014), as well as structured diagnostic interviews (Mackesy-Amiti, Donenberg, & Ouellet, 2014). The ASI-5 constitutes just one such instrument, and although the psychiatric CS differs somewhat from the psychiatric Recent Status Score [RSS] in the re- cently published ASI-6 (Cacciola, Alterman, Habing, &McLellan, 2011), the two instruments are significantly correlated and share approxi- mately 49% of their variance. Furthermore, both the psychiatric RSS and the psychiatric CS are significantly correlated with psychiatric validity measures (Denis, Cacciola, & Alterman, 2013). In sum, we be- lieve that the present findings support the view that psychopathology can be validly assessed among people undergoing treatment for DUD with use of self-report instruments (Delgadillo et al., 2016; Hesse, Guldager, & Linneberg, 2012).

This study has several limitations. Firstly, it should be noted that the study sample are patients in residential care, a treatment usually

reserved for the most severe and unstable DUD patients (Harris et al., 2015), and findings may not be generalizable to outpatients. Secondly, suicides were recorded only from registered deaths rather than full autopsies, and there is some evidence that, despite their overall ac- ceptable validity, registers may underestimate the number of suicides in patients with substance use disorders (Nyhlen, Fridell, Hesse, & Krantz, 2011). Thirdly, a number of patients did not complete the ASI, or had to be excluded due to missing data, so that around 30% of patients could not be included in the study. Finally, the findings may not be gen- eralizable to other assessment instruments, including the ASI-6 (Cacciola et al., 2011).

Nevertheless, this study demonstrates the consistent predictive va- lidity of the ASI psychiatric CS for two varied, but objectively mea- sured, mental health-related outcomes. The findings thus support the use of the ASI psychiatric CS to identify patients in need of monitoring and treatment for mental health problems during and after DUD treatment.

Conflict of interest

No conflict declared.

Role of funding source

All authors were supported by the Danish Ministry for Social Affairs and the Interior with a general grant. The ministry had no role in the study design; collection, analysis, and interpretation of data; writing the manuscript; or decision to submit the manuscript for publication.

Contributors

Authors Hesse and Thylstrup designed the study and wrote the protocol. Authors Hesse, Thylstrup and Bloomfield conducted literature searches. Author Hesse conducted statistical analysis, and authors Hesse and Thylstrup wrote the first draft of the manuscript and all authors contributed to and have approved the final manuscript.

Appendix A

Table 1 Specific symptoms by psychiatric care after treatment and suicide.

Total sample

Post-discharge psychiatric care

Log-rank χ2(1)

Post-discharge suicide

Log-rank χ2(1)

Symptom No psychiatric treatment Psychiatric care

No suicide Suicide

Depression 73.6% 71.0% 79.8% 43.2** 73.6% 90.3% 4.80* Anxiety 49.0% 44.9% 59.2% 100.3** 49.2% 61.3% 3.24 Cognitive

problems 64.5% 61.9% 71.3% 57.1** 64.7% 74.2% 1.11

Hallucinations 20.0% 18.2% 25.8% 68.0** 20.4% 32.3% 4.99* Violent behavior 38.6% 36.9% 43.4% 30.7** 38.9% 41.9% 0.41 Medication 33.3% 29.1% 44.6% 208.9** 33.7% 58.1% 6.40* Suicidal ideation 33.5% 29.5% 44.2% 144.0** 33.8% 54.8% 2.52 Suicide attempts 12.6% 11.8% 16.0% 50.0** 13.0% 16.1% 1.08

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