Reinhard Krausz


Relevant Thesis-Based Degree Programs


Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.


Michael is a truly inspirational, supportive, and understanding mentor. Thank you for everything you do!

James Wong (2019)


#GreatSupervisor #UBC: definitely Michael Krausz. I'm so fortunate to work with him!

Sanam Javidanbardan (2017)


#GreatSupervisor #UBC: I want to thank Michael Krausz for always being a kind, understanding, and supportive supervisor!

Mohammad (2017)


Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

A machine learning approach to overdose risk assessment (2024)

This project explores the escalating drug toxicity crisis in British Columbia, spotlighting the role of machine learning within eHealth solutions to combat this pressing public health issue. The crisis, rooted in a shift from prescription opioids to potent synthetic alternatives like fentanyl, necessitates innovative intervention strategies. The study leverages extensive data from 2015 to 2019, aiming to develop predictive models for overdoses to improve healthcare responses.The research begins with a systematic review and meta-analysis of machine learning models targeting opioid-related outcomes, demonstrating the predictive strengths of various algorithms in cohort studies. Results indicate these algorithms' effectiveness in forecasting opioid usage and overdose risks. Additionally, a review of clinical decision support systems in addiction and mental health care reveals their critical impact on enhancing diagnosis, treatment, and patient care, based on randomized controlled trials.Central to the thesis is an exploratory data analysis utilizing the British Columbia Provincial Overdose Cohort. This involves rigorous data preparation, including wrangling, addressing missing data, and correcting class imbalances. The study assesses several machine learning models, including ensemble approaches like Random Forest and XGBoost, for their predictive accuracy regarding fatal and general overdoses. Despite challenges, these models demonstrate significant potential, with the best performers achieving over 90% accuracy in predicting general overdoses, though models for fatal overdoses showed lower efficacy.The thesis concludes with an affirmation of machine learning's transformative potential in personalizing addiction psychiatry treatment through eHealth innovations such as the Risk Assessment and Management Platform (RAMP). This novel approach aims to individualize treatment and prevention strategies, contributing to global efforts in mitigating the mental health ramifications of the drug toxicity crisis and transforming healthcare practices. Through the strategic implementation of machine learning, the study underscores a promising avenue for advancing healthcare solutions tailored to the intricacies of addiction and overdose risks, reflecting a significant stride towards mitigating the public health impacts of the drug crisis.

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Opium tincture for opioid substitution treatment (2022)

Opioids have served as a dual-purpose substance throughout the human history. While they are listed as an essential medicine by the World Health Organization, on account of their effectiveness at treating pain, their harmful use also leaves a significant burden on societies. Among treatments developed to address the latter, opioid substitution treatment (OST) is a very well-documented and evidence-based treatment, which has shown to improve a multitude of treatment outcomes for patients with opioid dependence. Besides well-established medicines for OST, such as methadone and buprenorphine, opium tincture (OT), a hydro alcoholic preparation of opium, is used for this purpose on a large scale in Iran. The first step of this thesis, which was a systematic review, (2014 - 2016) did not find adequate evidence to make a conclusive recommendation about the safety and efficacy of OT for OST. Following this review, a non- inferiority randomized clinical trial (opium trial) with 204 participants and a 12-week follow-up period, compared the safety and efficacy of OT with methadone in treatment of opioid dependence. A comparison of international samples with participants of opium trial at baseline revealed that patterns of substance use and related risk behaviors differed significantly between Iran and other regions of the world, a factor which needs to be considered when generalizing the findings of the opium trial. Next, the comparison of outcomes between the two arms showed that OT was a clinically effective medication and that OT was more effective than methadone at reducing participants’ opioid use outside of treatment; however, the study could not conclude whether or not OT was non-inferior to methadone at retaining participants in treatment. The number of people with AEs (adverse events) were not significantly different between the two groups. There was no serious adverse event in the OT arm and one in the methadone arm. Substitution treatment with OT has expanded in Iran since its introduction and the results of this trial show potential for its further use. OT can serve as a culturally acceptable and widely available medication for OST, diversifying the treatment options for this condition.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Adherence in e-health interventions for substance use and the factors influencing it: systematic review, meta-analysis, and meta-regression (2022)

Background: Globally, around 36 million people have a drug use disorder, while only one in eight receive the treatment they need. Research and development of e-health interventions targeting substance use have been becoming increasingly popular in the last decade, due to their unique ability to reach wide populations. Low exposure of participants and adherence to interventions and their content has been a widely dis-cussed issue in the literature of e-health interventions. Adherence in e-health interven-tions is defined as “the degree to which individuals experience the content of the Inter-net intervention”. Although adherence may be an important factor in determining the effectiveness of an intervention targeting substance use, not many studies have been specifically focusing on this aspect.Objectives: In this review, we set out to analyze the data on adherence from studies on e-health interventions targeting substance use and assess four predictors of ad-herence. The four factors that were hypothesized to predict adherence were guidance, blended treatment, recruitment, and treatment duration.Methods: A systematic review of published literature from 2009-2020 was conducted and data on two adherence measures and predictors of adherence were extracted. The two adherence measures were (1) the mean proportion of modules completed across the intervention group and (2) the proportion of participants that completed all modules.Results: The overall pooled adherence rate was 0.60 (95%-CI: 0.52-0.67) for the mean proportion of modules completed across 30 intervention arms and 0.47 (95%-CI: 0.35-0.59) for the proportion of participants that completed all modules across nine in-tervention arms. Four meta-regression models assessed each covariate. The three variables guidance, blended treatment, and recruitment were statistically significant predictors of adherence. Treatment duration was not a significant predictor of adher-ence. Conclusion: The results of the present review suggest that there may be some predic-tors of adherence that should be considered in further investigations and develop-ments of interventions. Future studies should put a greater emphasis on reporting ad-herence, as that would allow for more accurate meta-analyses and predictor models to help improve understanding of adherence and its predictors.

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A paradigm shift in the treatment of high-risk substance use and overdose among youth (2021)

Mental and substance use disorders are the leading cause of disability and overall burden of disease in children and youth worldwide. Further, overdose and suicide are the leading contributors to mortality among youth in North America. The need for effective healthcare systems for youth will only become more substantial, especially in the context of the opioid overdose crisis and the COVID-19 pandemic. This research investigated the current paradigm surrounding substance use disorder treatment among youth and aimed to contribute a more innovative and effective response to high-risk substance use and overdose among youth. Firstly, a narrative review assessed the current reality of treatment approaches for high-risk opioid use among youth by means of narrative review. Findings revealed a dearth of academic effort and clinical research on interventions for youth with high-risk substance use, which demonstrates the many gaps within the field of addiction psychiatry and adolescent medicine. Secondly, a rapid review evaluated the clinical guidance in place for youth with high-risk opioid use. The clinical practice guidelines available, or lack thereof, reaffirms the systematic failure in addressing the mental health and substance use needs of youth. Lastly, to inform service development and ameliorate the standard of care for youth, a multidisciplinary panel of clinicians and researchers in the field of youth substance use disorder developed 60 recognized statements through Delphi process. This international collaborative project provides a basis for education and establishes an infrastructure for research by outlining clinical risks, determining target populations, defining intervention goals, recognizing evidence-based strategies, and identifying appropriate treatment settings and expertise. Comprehensively, this research identifies critical problems in the current systems of care for adolescents and young adults internationally and provides a framework for the improved prevention, treatment, and management of high-risk substance use and overdose among this vulnerable group. Healthcare systems must strive to support youth through their development with tailored and stigma-free evidence-based approaches. High-quality studies are needed to further determine the safety and effectiveness of treatment options for youth.

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A pilot study on risk and protective factors for opioid overdose among people who use street fentanyl during the COVID-19 pandemic (2021)

North America is in the midst of an opioid overdose epidemic. British Columbia has been particularly impacted by the epidemic, as over 7,000 have died from illicit drug overdoses since the crisis was declared a public health emergency in 2016. These deaths have largely been fueled by the widespread prevalence of illicitly manufactured fentanyl. Moreover, the crisis has now been exacerbated by the COVID-19 pandemic, as several jurisdictions have experienced record numbers of overdose deaths in 2020. We undertook a narrative review to describe the risk and protective factors for opioid overdose examined in the current literature. While a range of factors have been studied, it remains unclear how factors previously identified in those using heroin, and how novel fentanyl-related factors are influencing the risk of overdose in those using fentanyl. We thereby conducted a cross-sectional pilot study to investigate the risk and protective factors for non-fatal opioid overdose among 36 participants using street fentanyl during the COVID-19 pandemic. We found that 86.1% reported the intentional use of fentanyl, and 47.2% reported having overdosed in the past six months. These findings add to the growing evidence base that more individuals are intentionally using fentanyl, rather than unintentionally using it. Gender, history of opioid overdose, and suicidal ideation were identified as risk factors for recent overdose. Route of administration, receiving opioid agonist treatment, and receiving safe supply were not significantly associated with overdose. This suggests that risk and protective factors previously identified in individuals who use heroin should be re-examined as their contributions to overdose risk may be different in individuals who use fentanyl. Novel factors related to fentanyl and the pandemic should be further investigated to examine their roles in overdose risk. Future studies in this urgently needed area of research will improve the identification of individuals at risk of overdose, and inform the development of tailored interventions and policies to improve health outcomes in this vulnerable population.

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Impact of opioid agonists on mental health in substitution treatment for opioid use disorder: a systematic review and Bayesian network meta-analysis of randomized clinical trials (2020)

Background: Concurrent mental health problems is a major issue in opioid use disorder. As the first step in developing effective interventions, a clear understanding of factors that potentially contribute to the improvement of mental health in this population, most prominently the role of opioid medications, is required. Previous reviews did not isolate the impact of opioid agonists on mental health from those of psychosocial interventions in substitution treatment of opioid use disorder. We compared mental health outcomes between opioid medications and control conditions, i.e. placebo or waitlist, to isolate these effects.Methods: Embase, MEDLINE, PsychInfo, CINAHL Complete, Web of Science Core Collection and RCT registries were among the systematically searched databases. RCTs were included if they com- pared any opioids with each other or with a placebo/waitlist in substitution treatment of patients with opioid use disorder and reported mental health outcomes using a validated measure. Individual study-level data were extracted from all available sources. Primary outcomes included difference in standardized mean score changes (SMD) for depressive symptoms and overall mental health symptomatol- ogy between opioid agonists and placebo/waitlist. Random effects model was used for both the direct pairwise meta-analysis and network meta-analysis. (Registered at pero/, CRD42018109375)Results: Out of 6034 citations, 19 studies were included in the qualitative synthesis and 16 in the quantitative synthesis. Out of 19 studies, 18 had high overall risk of bias. Direct pairwise meta-analysis indicated that diacetylmorphine (DAM) outperformed methadone on overall mental health (SMD (CI95%)= -0.23 (-0.34, -0.13)). Buprenorphine outperformed waitlist or placebo on improvement of depressive symptoms (SMD (CI95%)= -0.95 (-1.53, -0.36)) and overall mental health (SMD (CI95%)= -0.68 (-1.33, -0.03)). Based on network meta-analysis for primary outcomes, buprenorphine (SMD (CI95%)= -0.61 (-1.20, -0.11)), DAM (SMD (CI95%)= -1.40 (-2.70, -0.23)), and methadone (SMD (CI95%)= -1.20 (-2.30, -0.11)) were superior to waitlist/placebo on overall mental health symp- tomatology, but none of the medications were superior to waitlist in improving depressive symptoms.Conclusions: Opioid agonists used in substitution treatment improve overall mental health, and DAM outperforms methadone in this regard which has implications for treatment guidelines. Future trials will benefit from stricter control for sources of bias.

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