Correlates of nonfatal overdose among treatment-seeking individuals with non-heroin opioid use disorder: Findings from a pragmatic, pan-Canadian, randomized control trial

Associations among drug acquisition and use behaviors, psychosocial attributes, and opioid-involved overdoses

AIMS

This study sought to develop and assess an exploratory model of how demographic and psychosocial attributes, and drug use or acquisition behaviors interact to affect opioid-involved overdoses.

DESIGN

We conducted exploratory and confirmatory factor analysis (EFA/CFA) to identify a factor structure for ten drug acquisition and use behaviors. We then evaluated alternative structural equation models incorporating the identified factors, adding demographic and psychosocial attributes as predictors of past-year opioid overdose.

SETTING AND PARTICIPANTS

We used interview data collected for two studies recruiting opioid-misusing participants receiving services from a community-based syringe services program. The first investigated current attitudes toward drug-checking (N = 150). The second was an RCT assessing a telehealth versus in-person medical appointment for opioid use disorder treatment referral (N = 270).

MEASUREMENTS

Demographics included gender, age, race/ethnicity, education, and socioeconomic status. Psychosocial measures were homelessness, psychological distress, and trauma. Self-reported drug-related risk behaviors included using alone, having a new supplier, using opioids with benzodiazepines/alcohol, and preferring fentanyl. Past-year opioid-involved overdoses were dichotomized into experiencing none or any.

FINDINGS

The EFA/CFA revealed a two-factor structure with one factor reflecting drug acquisition and the second drug use behaviors. The selected model (CFI = .984, TLI = .981, RMSEA = .024) accounted for 13.1% of overdose probability variance. A latent variable representing psychosocial attributes was indirectly associated with an increase in past-year overdose probability (β = .234, p = .001), as mediated by the EFA/CFA identified latent variables: drug acquisition (β = .683, p < .001) and drug use (β = .567, p = .001). Drug use behaviors (β = .287, p = .04) but not drug acquisition (β = .105, p = .461) also had a significant, positive direct effect on past-year overdose. No demographic attributes were significant direct or indirect overdose predictors.

CONCLUSIONS

Psychosocial attributes, particularly homelessness, increase the probability of an overdose through associations with risky drug acquisition and drug-using behaviors. Further research is needed to replicate these findings with populations at high-risk of an opioid-related overdose to assess generalizability and refine the metrics used to assess psychosocial characteristics.

Characterising individuals with a substance use disorder accessing hospital-based addiction care: Preliminary description of the outcomes for patients accessing addiction care prospective cohort study

INTRODUCTION

Individuals with a substance use disorder (SUD) often face barriers to accessing health care, resulting in unmet needs and delayed care. Hospital-based services have the potential to engage individuals with a SUD in ongoing treatment, but there is limited literature characterising this population.

METHODS

The Outcomes for Patients Accessing Addiction Care study was a prospective hospital-based cohort study conducted at St. Paul's Hospital in Vancouver, Canada. Participants were recruited from January 2018 to March 2020. Data were collected through an interviewer-administered questionnaire, including socio-demographic information, substance use history and mental health screening.

RESULTS

The cohort included 536 participants, with 31% aged 30-39 years, 63% identifying as White and 74% reporting male sex at birth. Nearly half of the participants were either homeless or living in single room occupancy. Use of substances more than once per week was reported for tobacco/nicotine (86%), marijuana (43%), non-medical use of prescription drugs (29%), illicit stimulants (52%) and illicit opioids (61%).

DISCUSSION AND CONCLUSION

This preliminary report provides a description of a hospital-based cohort of individuals with a SUD accessing addiction care. The findings highlight demographic characteristics, mental health issues, substance use patterns and barriers to accessing services. Understanding these factors can inform the development of patient-centred interventions and improve engagement and retention in addiction care. Further research is needed to explore interventions and program effectiveness in this population.

Associations among Drug Acquisition and Use Behaviors, Psychosocial Attributes, and Opioid-Involved Overdoses: A SEM Analysis

Aims

This study sought to develop and assess an exploratory model of how demographic and psychosocial attributes, and drug use or acquisition behaviors interact to affect opioid-involved overdoses.

Methods

We conducted exploratory and confirmatory factor analysis (EFA/CFA) to identify a factor structure for ten drug acquisition and use behaviors. We then evaluated alternative structural equation models incorporating the identified factors, adding demographic and psychosocial attributes as predictors of past-year opioid overdose. We used interview data collected for two studies recruiting opioid-misusing participants receiving services from a community-based syringe service program. The first investigated current attitudes toward drug-checking (N = 150). The second was an RCT assessing a telehealth versus in-person medical appointment for opioid use disorder treatment referral (N = 270). Demographics included gender, age, race/ethnicity, education, and socioeconomic status. Psychosocial measures were homelessness, psychological distress, and trauma. Self-reported drug-related risk behaviors included using alone, having a new supplier, using opioids with benzodiazepines/alcohol, and preferring fentanyl. Past-year opioid-involved overdoses were dichotomized into experiencing none or any.

Results

The EFA/CFA revealed a two-factor structure with one factor reflecting drug acquisition and the second drug use behaviors. The selected model (CFI = .984, TLI = .981, RMSEA = .024) accounted for 13.1% of overdose probability variance. A latent variable representing psychosocial attributes was indirectly associated with an increase in past-year overdose probability (β=.234, p = .001), as mediated by the EFA/CFA identified latent variables: drug acquisition (β=.683, p < .001) and drug use (β=.567, p = .001). Drug use behaviors (β=.287, p = .04) but not drug acquisition (β=.105, p = .461) also had a significant, positive direct effect on past-year overdose. No demographic attributes were significant direct or indirect overdose predictors.

Conclusions

Psychosocial attributes, particularly homelessness, increase the probability of an overdose through associations with risky drug acquisition and drug-using behaviors. To increase effectiveness, prevention efforts might address the interacting overdose risks that span multiple functional domains.