Abstract
Objectives:
Alcohol use is one of the leading causes of death and disability globally; however, access to evidence-based care for alcohol use disorder (AUD) is limited. Although telemedicine-based interventions promise to expand treatment access, there are no validated telemedicine-based interventions for alcohol withdrawal management. In this single-arm study, we sought to determine the feasibility of delivering symptom-triggered alcohol withdrawal management over telemedicine.
Methods:
Thirty actively drinking participants with AUD and a history of alcohol withdrawal were recruited to participate. Participants were scheduled for 3 days of symptom-triggered withdrawal management using the Clinical Institute Withdrawal Assessment for Alcohol Scale Revised delivered by a trained clinician over a telemedicine platform. Primary outcomes were retention in treatment and need for transfer to a higher level of care (eg, the emergency room). Satisfaction with the treatment protocol and relapse to any alcohol use 30 days following treatment initiation were also assessed.
Results:
In total, 93.3% of participants completed all 3 days of alcohol withdrawal management. No participants required transfer to a higher level of care. Satisfaction with treatment was high, with an average Client Satisfaction Questionnaire-8 score of 30.9 (SD = 1.5) out of 32. After the follow-up period, 56.7% of participants remained abstinent from alcohol.
Conclusions:
Our study provides preliminary evidence that symptom-triggered alcohol withdrawal management over telemedicine is feasible and satisfactory for patients. If these findings are replicated, they could have important implications for access to alcohol withdrawal management services, especially in remote, rural, and underserved regions that lack specialized withdrawal management facilities.
Key Words: alcohol withdrawal, alcohol detoxification, alcohol use disorder, benzodiazepines, telemedicine
Alcohol use is one of the leading causes of death and disability globally1; however, access to care for alcohol use disorder (AUD) is limited. For example, in 2023, it is estimated that only 7.9% of Americans aged 12 and above with past-year AUD received any alcohol use treatment.2 There are also geographical disparities in access to AUD treatment. Individuals living in rural areas are less likely to receive alcohol-related treatment than those living in urban areas but are more likely to visit the emergency department for alcohol-related reasons.3,4 Rural residents have a lower probability of receiving outpatient psychiatric care following an alcohol-related hospitalization and a higher probability of dying in the year after discharge.5 Telemedicine-based treatments for AUD offer the possibility of improving access to care regardless of geographical location. There is evidence that telemedicine can be used to deliver psychotherapy for AUD6,7 and brief interventions8–10 with similar retention in treatment and patient satisfaction as usual care.7,10–12
Although there has been an expansion in telemedicine-based treatment for AUD, one area that has received little attention is withdrawal management. Alcohol withdrawal management is often the first step in the treatment of moderate to severe AUD. Untreated alcohol withdrawal can be life-threatening. Clinical practice guidelines recommend clinical monitoring and use of pharmacotherapy to prevent severe or complicated withdrawal.13 Benzodiazepines are recommended as a first-line treatment, given that they reduce withdrawal symptoms and can prevent the incidence of seizure and delirium.13 A particularly effective alcohol withdrawal treatment approach is symptom-triggered withdrawal management using benzodiazepines, in which an individual is monitored medically and only receives treatment when they experience withdrawal symptoms above a certain threshold. Most alcohol withdrawal patients present with mild to moderate symptoms; these patients may not need high doses of medication and symptom-triggered approaches can reduce the risk of overmedicating patients. When compared with nonmonitored approaches, symptom-triggered withdrawal management has been found to shorten treatment time and substantially reduce the amount of medication required for successful treatment.14 However, employing symptom-triggered withdrawal management is often expensive as it requires access to the necessary infrastructure to run ambulatory or inpatient medically supervised withdrawal units, including hospital beds and staff. A virtual approach could represent a new way to deliver symptom-triggered withdrawal management without the need for resource-intensive medically supervised withdrawal units.
In the present single-arm study, we sought to determine the feasibility and acceptability of delivering symptom-triggered alcohol withdrawal management over telemedicine. We hypothesized that the majority of patients would complete the entire telemedicine-delivered symptom-triggered alcohol withdrawal management protocol without the need for a higher level of care. We also assessed patient satisfaction with treatment and relapse to alcohol use during the 30 days after initiation of withdrawal management. If virtual symptom-triggered alcohol withdrawal management were found to be feasible and acceptable for patients and is then found to be comparable to in-person care in larger comparative effectiveness trials, it could be used to improve access to care, especially for individuals living in rural, remote, and underserved communities.
METHODS
Study Design
Participants were recruited for this single-arm open-label feasibility trial from the Centre for Addiction and Mental Health (CAMH), a tertiary care center in Toronto, Ontario. Participants were referred primarily by clinicians working in CAMH’s outpatient addiction clinic. Our target sample size for the study was 30; this sample size was based on feasibility given the study timeline. Those interested in the study were prescreened by phone. Potentially eligible participants provided informed consent and were invited for an in-person eligibility visit. At the eligibility visit, the study nurse or physician delivered a ∼15-minute educational PowerPoint presentation to the participant that reviewed symptoms of alcohol withdrawal and possible treatment complications (see Supplemental Materials for details, Supplemental Digital Content 1, http://links.lww.com/JAM/A628). Eligible participants were scheduled for 3 days of telemedicine-delivered symptom-triggered alcohol withdrawal management, typically beginning within the week following the eligibility assessment. Before starting medical withdrawal management, we requested that participants remove all remaining alcohol from their homes. After completion of withdrawal management, participants met with study staff and completed the Client Satisfaction Questionnaire-8 and Telemedicine Satisfaction Scale. Participants were offered the opportunity to start or switch to an evidence-based medication for AUD and the option to complete 4 sessions of weekly psychotherapy for AUD aimed at preventing relapse. Participants were assessed again ∼30 days after initiation of withdrawal management to assess return to alcohol use (any drinking after initiation of withdrawal management was considered return to alcohol use). This study was approved by CAMH’s Research Ethics Board (2020/137). Patients were compensated for their participation in the study ($230 CAD total compensation).
Eligibility Criteria
Participants needed to be 18 years of age or older, actively using alcohol, and have previously met DSM-5 criteria B for alcohol withdrawal to be eligible. Participants were excluded from the study if they had a history of complicated withdrawal (withdrawal seizures, hallucinosis, or withdrawal delirium); current use of opioids or sedatives, a positive urine drug screen for sedatives or opioids, or a diagnosis of opioid or sedative-hypnotic use disorder within the past year; contraindications to the safe use of diazepam; a positive urine pregnancy test; or lack of stable housing. The full list of inclusion and exclusion criteria can be found in the Supplemental Materials, Supplemental Digital Content 1, http://links.lww.com/JAM/A628.
Telemedicine-Delivered Symptom-Triggered Withdrawal Management
Participants were prescribed a limited initial supply of diazepam (usually eight 10 mg pills) on the day before withdrawal management to prevent medication misuse; this was renewed if the participant ran out of medication by faxing or calling in an additional prescription. On each day of withdrawal management, participants signed into the video conferencing platform (Webex) at ∼9:00 am. Participants were then assessed by a clinician (either a registered nurse or study physician) using a modified version of the Clinical Institute Withdrawal Assessment for Alcohol Scale Revised (CIWA-Ar)15 adapted for use over a telemedicine platform (Supplemental Materials, Supplemental Digital Content 1, http://links.lww.com/JAM/A628). If participants scored ≥ 10 on the CIWA-Ar, they were instructed to take either 10 mg or 20 mg of diazepam at the clinician’s discretion and were reassessed in an hour (the amount of diazepam taken was recorded by the clinician). If the CIWA-Ar score was below 10, participants were reassessed every 1–4 hours at the clinician’s discretion through scheduled Webex meetings. Although vital signs are often monitored in addition to CIWA-Ar scores during inpatient withdrawal management, we made the decision not to issue at-home blood pressure cuffs so that the intervention would be more scalable (since it was felt that clinics would be less likely to adopt an intervention which required purchasing and sending out blood pressure cuffs to patients). Participants were monitored over telemedicine until ∼4:00 pm every day. Telemedicine check-ins typically lasted 5–10 minutes, but could be longer depending on the needs of the participant. At the end of each day, participants were assessed by a study physician and were instructed that they could use as-needed doses of diazepam overnight should they develop withdrawal symptoms. The amount of diazepam taken overnight was recorded on the following day. This procedure was repeated on day 2 and day 3 of withdrawal management. On day 3 of withdrawal management, participants needed to have 3 consecutive CIWA-Ar scores < 10 for withdrawal management to be considered complete. For those who continued to score ≥ 10 on the final assessments of day 3, the length of withdrawal management could be extended by an additional 1–2 days. Participants were only allowed to complete the protocol a single time.
Primary and Secondary Outcomes
Our primary outcomes were retention in treatment, measured as the total percentage of participants who completed all 3 days of remote symptom-triggered withdrawal management, and transfer to a higher level of care, defined as the proportion of participants needing to go to the emergency room due to complications (eg, seizure, failure to respond to treatment), need for intensive monitoring (eg, severe sedation), or acute intoxication. Participants were deemed not to be retained in treatment if they returned to alcohol use during the withdrawal management period, needed a higher level of care, or were persistently unreachable (eg, missed multiple consecutive check-ins and could not be reached by the treatment team or did not present for treatment on a given day). We set a priori benchmarks, with a retention rate ≥ 70% retention and ≤ 20% transfer rate selected as showing adequate evidence of feasibility. These benchmarks were selected as reasonable feasibility endpoints based on the consensus of the study team. Secondary outcomes included patient satisfaction with remote withdrawal management using the Client Satisfaction Questionnaire-816 (range 8–32; higher scores indicate greater satisfaction), satisfaction with the telemedicine platform using a modified version of the Telehealth Satisfaction Scale17 (range 12–48; higher scores indicate greater satisfaction), mean peak withdrawal severity score and diazepam dose on each day of treatment, the percentage of participants requiring benzodiazepine treatment, and the duration of active withdrawal treatment (days in which patients required medication treatment) among patients who received benzodiazepines. Adverse events that occurred during withdrawal treatment were recorded with an adverse event log that was completed at each assessment. This log assessed common side effects of diazepam (eg, drowsiness, clumsiness, falls) and withdrawal-related complications (eg, seizures, hallucinations). Finally, we looked at the proportion of patients who returned to any alcohol use based on recall data using the timeline followback interview (TLFB)18 at the end of the follow-up period. We also assessed changes in alcohol use before and after treatment among individuals who returned to any use. For participants who completed their final follow-up visit in person (N=26; some participants completed their final visit remotely due to scheduling conflicts), we collected urine ethyl glucuronide (EtG). This was used to confirm the absence of recent alcohol intake in participants who endorsed abstinence following treatment.
Statistical Analysis
Primary outcomes were reported as percentages with 95% CIs. Due to the small sample size and large proportions, exact binomial tests from the R package mosaic19 were used to determine whether outcomes were significantly greater than preselected benchmarks for retention and transfer to a higher level of care. For secondary outcomes, measures of central tendency and variability (mean and SD or median and interquartile range [IQR]) were used to describe patient satisfaction with treatment, patient satisfaction with the telemedicine platform, dose of diazepam used (including overnight medication), peak CIWA-Ar scores on each day of treatment, and duration of active withdrawal treatment (days in which patients required medication treatment). Return to any alcohol use based on self-report was depicted graphically using a Kaplan-Meier curve and reported as the percentage of people who returned to any alcohol use by the end of the follow-up period. Change in alcohol use (average drinks per day) in the 30 days before and after treatment initiation among individuals who returned to use was assessed using a paired sample t test. All analyses were carried out using R or SPSS.
RESULTS
Sample Characteristics
Thirty participants were recruited for this study (Fig. 1). The mean age of the sample was 44.0 years (SD=11.3; range: 24–72) and 40.0% of our participants were female (Table 1). All participants met the diagnostic criteria for severe AUD. The average daily alcohol consumption in the 30 days preceding the eligibility visit was 10.4 standard drinks for males and 6.3 standard drinks for females.
FIGURE 1.
Screening and enrollment.
TABLE 1.
Demographic Characteristics of the Sample
| Variable | Overall (N=30) | Male (N=18) | Female (N=12) |
|---|---|---|---|
| Age (mean [SD]) | 44.0 (11.3) | 45.1 (10.8) | 42.4 (12.4) |
| Income (<60,000, %) | 36.7 | 50.0 | 18.1 |
| Race (White, %) | 66.7 | 66.7 | 66.7 |
| Marital status (married or common law, %) | 40.0 | 44.4 | 33.3 |
| PACS score (mean [SD]) | 22.7 (5.4) | 21.4 (6.1) | 24.6 (3.6) |
| AUDIT score (mean [SD]) | 29.9 (4.2) | 30.4 (3.9) | 29.2 (4.8) |
| TLFB drinks/day (mean [SD]) | 8.8 (2.9) | 10.4 (1.9) | 6.3 (2.1) |
AUDIT indicates alcohol use disorders identification test (range: 0–40); PACS, Penn Alcohol Craving Scale (range 0–30); TLFB, 30-day timeline followback interview.
Retention in Treatment and Need for a Higher Level of Care
Twenty-eight of 30 participants (93.3%, 95% CI: 80.4%–1.00%) completed all 3 days of medical withdrawal management, which was significantly higher than 70% (P=0.0021), our preselected benchmark for retention. The 2 participants who were not retained in treatment relapsed to alcohol use on day 1 of withdrawal management (one before starting medication, the other in the evening after receiving treatment). No participants (0%, 95% CI: 0%–11.5%) required transfer to a higher level of care, which was significantly lower than 20% (P=0.0012), our preselected benchmark.
Diazepam Dose and Peak Withdrawal Severity Score on Each Withdrawal Management Day
The median daily doses of diazepam received were 30 mg (IQR=20), 20 mg (IQR=20), and 10 mg (IQR=10) on withdrawal management day 1, 2, and 3, respectively (Fig. 2A). Doses ranged anywhere from 0 to 80 mg on day 1 and 2 of treatment and 0 to 50 mg on day 3 of treatment. The mean peak CIWA-Ar scores on each day of treatment were 12.1 (SD=4.3), 9.4 (SD=4.7), and 6.6 (SD=4.2), on day 1, 2, and 3, respectively (Fig. 2B). Only 9/28 participants (32.1%) had a CIWA-Ar score at or above 10 on day 3 of treatment, indicating that the majority of participants did not require symptom-triggered withdrawal management on this day (although one participant deviated from the protocol and took an extra 10 mg dose of diazepam during the day against the team’s recommendation and 6 additional participants took as needed diazepam on the evening of day 3). The average number of daily check-ins during withdrawal management was 5.9 (SD=1.4) for day 1, 5.1 (SD=1.1) for day 2, and 4.3 (SD=0.9) for day 3.
FIGURE 2.
Diazepam dose and peak withdrawal severity over the course of withdrawal management. (A) Box plots demonstrating the dose of diazepam in milligrams received during each day of telemedicine-delivered symptom-triggered alcohol withdrawal management. The darker line in the box represents the median dose of diazepam received and the edges of the box represent the first and third quartiles, respectively. Each diamond represents a specific participant’s diazepam dose for that day and triangles next to the diamond indicate that a given value is an outlier. (B) Colored lines represent each participant’s trajectory of peak withdrawal severity scores (as measured using the CIWA-Ar) over the course of withdrawal management. The dashed line represents the mean peak CIWA-Ar score over the course of withdrawal management across the sample.
Duration of Active Withdrawal Treatment
Twenty-seven of 30 participants (90.0%) required treatment with benzodiazepines during remote medical withdrawal management. One participant required an extra day of withdrawal management (4 days total) due to the absence of 3 consecutive CIWA-Ar scores < 10 by the end of day 3, although that participant did not have any CIWA-Ar scores ≥ 10 on day 4 of treatment. The average number of days in which medication treatment was required among participants who received benzodiazepines was 2.4 days (SD=0.8).
Client Satisfaction With Remote Withdrawal Management and the Telemedicine Platform
The mean Client Satisfaction Questionnaire-8 score among participants was 30.9 (SD=1.5) out of 32; all participants rated the intervention in the excellent range20 (range=27–32). The mean reported satisfaction with the telemedicine platform was also high, with an average score of 45.1 out of 48 (SD=2.5, range=41–48).
Pharmacotherapy and Psychotherapy Following Withdrawal Management
In terms of optional treatment following withdrawal management, 90% of patients were prescribed medication for AUD (36.7% naltrexone, 33.3% acamprosate, 13.3% gabapentin, and 6.6% topiramate) and 83.3% of participants received at least one session of psychotherapy. The majority of the medication prescriptions were new prescriptions (i.e., the participant was not on medication for AUD before or was on a different medication at the eligibility assessment); only 2 participants (6.6%) were prescribed the same medication for AUD that they were taking at the eligibility assessment. The participants who received psychotherapy attended a mean of 3.4 (SD=1.0) therapy sessions out of 4 possible sessions. Only 2 participants were not treated with either psychotherapy or medication for AUD following withdrawal management.
Return to Alcohol Use and Change in Alcohol Use Following Treatment
Seventeen of 30 participants (56.7%) reported remaining abstinent during the 30-day follow-up period following treatment initiation (Fig. 3). Of the 17 participants who reported remaining abstinent, 15 completed their final visit in person and provided a urine sample; none of these participants tested positive for urine ethyl glucuronide, a marker of recent alcohol use. Of the 13 participants who returned to alcohol use, most (69.2%) relapsed within the first 10 days of treatment initiation. Among participants who relapsed, the mean number of standard drinks per day decreased significantly from 8.3 (SD=3.7) in the 30 days before the eligibility assessment to 3.9 (SD=3.3) in the 30 days after treatment (t (12)=3.9, P=0.002, Fig. 4).
FIGURE 3.
Kaplan-Meier curve showing return to any alcohol use in the days following treatment initiation. Overall, 56.7% (N=17) remained abstinent during the follow-up period, and 43.3% (N=13) returned to any alcohol use.
FIGURE 4.
Drinking levels before and after treatment in participants who returned to any alcohol use. Change in total alcohol consumption in standard drinks (one standard drink was defined as any beverage containing 14 g of pure ethanol) from the 30 days before the eligibility assessment to the 30 days following treatment initiation among the 13 participants who returned to any alcohol use. Each line represents an individual participant.
Adverse Events
There were no recorded episodes of seizure, hallucinosis, or delirium during the study. No participants required transfer to the emergency department. The most common medication-related side effect was mild sedation. Additional details can be found in the Supplemental Materials, Supplemental Digital Content 1, http://links.lww.com/JAM/A628.
DISCUSSION
To our knowledge, our study is the first to demonstrate the feasibility and acceptability of delivering symptom-triggered alcohol withdrawal management over a telemedicine platform. We found that the majority of participants were able to complete the entire treatment from home in three days, with no participants requiring transfer to a higher level of care. Participants reported high levels of satisfaction with both the treatment protocol and the telemedicine platform. As expected based on the typical course of alcohol withdrawal management, both CIWA-Ar scores and diazepam dose gradually decreased over the course of treatment. There were no instances of severe complications related to alcohol withdrawal, such as seizures or delirium tremens.
The only other investigation of withdrawal management over telemedicine was a case series of four patients with opioid, alcohol, and/or sedative-hypnotic use disorder.21 Patients received withdrawal management over a 4–11 day period consisting of 1–4 daily telephone check-ins with the study physician and peripheral blood pressure and oxygen saturation monitoring. As in our larger and more structured trial, patients did not experience any serious medical complications.
There are several strengths to our treatment approach. Our protocol allows specialized care providers to deliver treatment remotely even if there are limited addiction specialists in a given community. Evidence from the United Kingdom suggests that the quality of medical alcohol withdrawal management is improved when addiction specialists are involved in care, including higher rates of prescription of medication for AUD and higher rates of continuing care.22 In our protocol, withdrawal management was paired seamlessly with psychotherapy and medication for AUD, so linkage to relapse prevention treatment was high, with 83.3% of participants completing a mean of 3.4 therapy sessions and 90% of participants being prescribed medication for AUD. Our protocol led to high rates of satisfaction with treatment, which may be due in part to a preference for telehealth in patients with SUDs. For example, a survey study found that 48% of patients with SUDs prefer telehealth for outpatient medication management, 22% prefer a mix of telehealth and in-person care, and 22% prefer in-person care.23 Another study found that participants were willing to pay slightly more for SUD counselling delivered to their home by videoconference than in-person counseling.24 These data suggest that there would be a high uptake of telemedicine-delivered alcohol withdrawal management were it to become widely available.
There are important limitations to our study. Firstly, there was no comparator group; therefore, it is unclear how telemedicine-based symptom-triggered alcohol withdrawal management compares to in-person symptom-triggered alcohol withdrawal management. A randomized controlled trial comparing these interventions would be informative to determine whether the treatments are equivalent or whether one intervention is superior to the other. However, it is important to note that many people do not have immediate access to in-person symptom-triggered withdrawal management; therefore, this intervention could still play an important role in enhancing access to care even were it to prove inferior. It should be noted that the studies showing superiority of symptom-triggered versus nonmonitored withdrawal management approaches were conducted in monitored settings (i.e., inpatient or partial hospitalization settings) rather than outpatient settings. It will be important to assess how our protocol compares to other at-home approaches. This includes unmonitored fixed-dose approaches as well as approaches that use self-reported withdrawal severity to guide treatment, which have been found to have similar outcomes to fixed-dose approaches.25 Our approach also did not use at-home vital sign monitoring to guide treatment, which could have potentially provided additional information about withdrawal severity but may have been more burdensome for participants. Secondly, our intervention only tested the use of diazepam, which is a benzodiazepine that generates metabolites with long half-lives. We selected this medication as it is less likely to lead to rebound withdrawal symptoms than benzodiazepines with a shorter half-life and is safer than other sedatives like phenobarbital. However, guidelines recommend considering lorazepam and oxazepam for individuals with significant liver disease13 and it is unclear from our study whether these medications would be equally effective or safe for telemedicine-delivered symptom-triggered withdrawal management. Thirdly, although our patients consumed alcohol at relatively high levels (10.4 standard drinks per day for males, 6.3 standard drinks per day for females on average), some individuals consume much higher levels of alcohol. These individuals are at increased risk of both withdrawal seizures26 and delirium tremens.27 We excluded patients with a history of seizures, hallucinosis, and delirium as well as patients with severe liver disease or current opioid or sedative use disorder from our study. Telemedicine-based medical withdrawal management should not be used for patients with a history of these conditions without further study.
CONCLUSIONS
Evidence from this study suggests that telemedicine-delivered symptom-triggered alcohol withdrawal management is feasible and acceptable to patients. If our results are confirmed in future studies, telemedicine-based withdrawal management could be used to deliver specialized addiction treatment to patients in rural, remote, and underserved communities. Some patients may prefer to receive symptom-triggered medical withdrawal management treatment in the comfort of their own homes, and this treatment provides patients with that option. Given the low rates of uptake of medical treatment for AUD, interventions that expand access and reduce barriers to care such as this one are urgently needed.
Supplementary Material
Footnotes
This trial was funded by the Ontario Ministry of Health and Long-Term Care and the Canadian Institutes of Health Research (CIHR).
M.E.S.: writing—original draft; writing—reviewing and editing; conceptualization; data curation; formal analysis; investigation; supervision. A.N.: writing—reviewing and editing; data curation; formal analysis; investigation. K.B.X.: writing—reviewing and editing; data curation; investigation. B.B., L.B., K.H., C.S.H., M.K., S.L.F., and B.L.F.: writing—reviewing and editing. M.F., M.M., E.S., V.M.T.: writing—reviewing and editing; investigation. M.S.: writing—reviewing and editing; data curation; formal analysis. L.C.Q. and J.W.: writing—reviewing and editing. N.B.: writing—reviewing and editing; conceptualization; investigation.
M.E.S. has received research support from the Canadian Institutes of Health Research, the Ontario Ministry of Health and Longterm Care, the CAMH Foundation, and the Academic Health Sciences Centre AFP Innovation Fund. M.E.S. is also supported in part by an Academic Scholar Award from the Department of Psychiatry, University of Toronto. M.E.S. has received travel support from the Society of Biological Psychiatry and the International Society for CNS Clinical Trials and Methodology. He has received an honorarium for giving a talk at the McGill University Health Centre. N.B. has received salary support from the US National Institute on Drug Abuse (NIDA) grant R25-DA037756, unrelated to this work. B.L.F. has obtained funding from Indivior for a clinical trial sponsored by Indivior. B.L.F. has received in-kind donations of placebo edibles from Indivia. B.L.F. has obtained industry funding from Canopy Growth Corporation (through research grants handled by the Centre for Addiction and Mental Health and the University of Toronto). He has participated in a session of a National Advisory Board Meeting (Emerging Trends BUP-XR) for Indivior Canada and is part of the Steering Board for a clinical trial for Indivior. He has been a consultant for Shinogi and ThirdBridge. He received travel support to attend an event by Bioprojet. He is supported by CAMH, Waypoint Centre for Mental Health Care, a clinician-scientist award from the Department of Family and Community Medicine of the University of Toronto and a Chair in Addiction Psychiatry from the Department of Psychiatry of the University of Toronto. The remaining authors report no conflicts of interest.
Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal’s website, www.journaladdictionmedicine.com.
Contributor Information
Matthew E. Sloan, Email: matthew.sloan@camh.ca.
Anthony Ngoy, Email: Anthony.Ngoy@camh.ca.
Ke Bin Xiao, Email: Kelly.Xiao@camh.ca.
Bryce Barker, Email: bbarker@ccsa.ca.
Leslie Buckley, Email: Leslie.Buckley@camh.ca.
Marina Fodor, Email: m.fodor@live.com.
Kate Hardy, Email: kate.hardy@wchospital.ca.
Christian S. Hendershot, Email: christian.hendershot@usc.edu.
Meldon Kahan, Email: Meldon.Kahan@wchospital.ca.
Sandra La Fleur, Email: slafleur@hotmail.com.
Bernard Le Foll, Email: Bernard.LeFoll@camh.ca.
Mitchell Manicone, Email: Mitchell.Manicone@camh.ca.
Marcos Sanches, Email: Marcos.Sanches@camh.ca.
Emily Simpkin, Email: Emily.Simpkin@camh.ca.
Lena C. Quilty, Email: Lena.Quilty@camh.ca.
Jennifer Wyman, Email: jennifer.wyman@wchospital.ca.
Victor M. Tang, Email: Victor.Tang@camh.ca.
Nikki Bozinoff, Email: Nikki.Bozinoff@camh.ca.
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