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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Research square - (2024) vom: 12. Jan. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Swartz, James A [VerfasserIn] |
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| Links: |
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| Themen: |
Homelessness |
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| Anmerkungen: |
Date Revised 02.02.2024 published: Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.21203/rs.3.rs-3834948/v1 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM367508257 |
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| 100 | 1 | |a Swartz, James A |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Associations among Drug Acquisition and Use Behaviors, Psychosocial Attributes, and Opioid-Involved Overdoses |b A SEM Analysis |
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| 500 | |a Date Revised 02.02.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Preprint | |
| 650 | 4 | |a SEM | |
| 650 | 4 | |a homelessness | |
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| 700 | 1 | |a Zhao, Peipei |e verfasserin |4 aut | |
| 700 | 1 | |a Jacobucci, Ross |e verfasserin |4 aut | |
| 700 | 1 | |a Watson, Dennis |e verfasserin |4 aut | |
| 700 | 1 | |a Mackesy-Amiti, Mary Ellen |e verfasserin |4 aut | |
| 700 | 1 | |a Franceschini, Dana |e verfasserin |4 aut | |
| 700 | 1 | |a Jimenez, A David |e verfasserin |4 aut | |
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