Dataset Information

Sociodemographic Characteristics and the Stigmatization of Prescription Opioid Addiction.

ABSTRACT:

Objectives

The aim of this study was to investigate the relationship between participants' sociodemographic characteristics and the degree to which they stigmatize people with an opioid addiction.

Methods

A randomized, between-subjects case vignette study (n?=?2605) was conducted with a nationwide online survey. We investigated how the stigmatization toward a hypothetical individual who misused prescription opioids differed across participants' sociodemographic factors (ie, age, gender, education, race, and income).

Results

Our results showed that study participants who were male, white, low-income, college graduates, and younger rated the hypothetical individual with an opioid addiction with lower stigma. In addition, we showed that participant gender moderated the relationship between information given about initiation of opioid use (received prescription opioids from a doctor vs took prescription opioids from a friend) and opioid stigma perceptions.

Conclusions

Our results support previous findings that stigmatizing attitudes towards drug use vary across participant sociodemographic characteristics. The findings from our study provide a better understanding of how stigmatizing attitudes towards prescription opioid use differ across sociodemographic characteristics and can serve to improve negative perceptions of those with an opioid addiction.

SUBMITTER: Goodyear K

PROVIDER: S-EPMC7495887 | biostudies-literature | 2020 Mar/Apr

REPOSITORIES: biostudies-literature

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Publications

Sociodemographic Characteristics and the Stigmatization of Prescription Opioid Addiction.

Goodyear Kimberly K Chavanne David D

Journal of addiction medicine 20200301 2

<h4>Objectives</h4>The aim of this study was to investigate the relationship between participants' sociodemographic characteristics and the degree to which they stigmatize people with an opioid addiction.<h4>Methods</h4>A randomized, between-subjects case vignette study (n = 2605) was conducted with a nationwide online survey. We investigated how the stigmatization toward a hypothetical individual who misused prescription opioids differed across participants' sociodemographic factors (ie, age, g ...[more]

PMID: 31385847

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Project description:ImportancePrescription opioids are often used during pregnancy even though they are associated with neonatal opioid withdrawal syndrome (NOWS). Most studies of adverse outcomes of opioid use for pain have assessed only the class-wide outcome despite the pharmacodynamic and pharmacokinetic heterogeneity across opioid medications.ObjectiveTo compare the risk of NOWS across common types of opioids when prescribed as monotherapy during the last 3 months of pregnancy.Design, setting, and participantsThis cohort study analyzed administrative claims data of Medicaid-insured mothers and newborns in 46 states and Washington DC from January 1, 2000, through December 31, 2014. Participants were mothers with 2 or more dispensed opioid prescriptions within 90 days before delivery and their eligible live-born neonates. Data were analyzed from February 2020 to March 2021.ExposureDifferent types of opioid medications were compared by agonist strength (strong vs weak) and half-life (medium vs short and long vs short) of the opioid active ingredient.Main outcomes and measuresThe primary outcome was NOWS, which was identified using an International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic code in the 30 days after delivery. Relative risks (RRs) were adjusted for an exposure propensity score, including demographic characteristics, comorbidities, other medication use, and opioid treatment characteristics (including morphine milligram equivalents), using fine stratification.ResultsThe cohort comprised 48 202 opioid-exposed pregnancies with live newborns. A total of 1069 neonates (2.2%) had NOWS and 559 (1.2%) had severe NOWS. Opioid exposure during pregnancy included 16 202 pregnancies exposed to codeine, 4540 to oxycodone, 1244 to tramadol, 260 to methadone (dispensed for pain), 90 to hydromorphone, and 63 to morphine compared with 25 710 exposed to hydrocodone. Demographic characteristics varied across opioids, with tramadol, oxycodone, methadone, hydromorphone, and morphine being more commonly dispensed at older maternal age (≥35 years). Compared with hydrocodone, codeine had a lower adjusted RR of NOWS (0.57; 95% CI, 0.46-0.70), with a similar adjusted RR for tramadol (RR, 1.06; 95% CI, 0.73-1.56), and 2- to 3-fold higher adjusted RRs for oxycodone (1.87; 95% CI, 1.66-2.11), morphine (2.84; 95% CI, 1.30-6.22), methadone (3.02; 95% CI, 2.45-3.73), and hydromorphone (2.03; 95% CI, 1.09-3.78). Strong agonists were associated with a higher risk of NOWS than weak agonists (RR, 1.97; 95% CI, 1.78-2.17), and long half-life opioids were associated with an increased risk compared with short half-life products (RR, 1.33; 95% CI, 1.12-1.56). Findings were consistent across sensitivity and subgroup analyses.Conclusions and relevanceResults of this study show higher risk of NOWS and severe NOWS among neonates with in utero exposure to strong agonists and long half-life prescription opioids. Information on the opioid-specific risk of NOWS may help prescribers select opioids for pain management in late stages of pregnancy.

Project description:ImportanceAlthough prescription opioid use disorder is associated with substantial harms, strategies to identify patients with pain among whom prescription opioids can be safely prescribed have not been systematically reviewed.ObjectiveTo review the evidence examining factors associated with opioid addiction and screening tools for identifying adult patients at high vs low risk of developing symptoms of prescription opioid addiction when initiating prescription opioids for pain.Data sourcesMEDLINE and Embase (January 1946 to November 2018) were searched for articles investigating risks of prescription opioid addiction.Study selectionOriginal studies that were included compared symptoms, signs, risk factors, and screening tools among patients who developed prescription opioid addiction and those who did not.Data extraction and synthesisTwo investigators independently assessed quality to exclude biased or unreliable study designs and extracted data from higher quality studies. The Preferred Reporting Items for Systematic Reviews and Meta-analyses of Diagnostic Accuracy Studies (PRISMA-DTA) reporting guideline was followed.Main outcomes and measuresLikelihood ratios (LRs) for risk factors and screening tools were calculated.ResultsOf 1287 identified studies, 6 high-quality studies were included in the qualitative synthesis and 4 were included in the quantitative synthesis. The 4 high-quality studies included in the quantitative synthesis were all retrospective studies including a total of 2 888 346 patients with 4470 cases that met the authors' definitions of prescription opioid addiction. A history of opioid use disorder (LR range, 17-22) or other substance use disorder (LR range, 4.2-17), certain mental health diagnoses (eg, personality disorder: LR, 27; 95% CI, 18-41), and concomitant prescription of certain psychiatric medications (eg, atypical antipsychotics: LR, 17; 95% CI, 15-18) appeared useful for identifying patients at high risk of opioid addiction. Among individual findings, only the absence of a mood disorder (negative LR, 0.50; 95% CI, 0.45-0.52) was associated with a lower risk of opioid addiction. Despite their widespread use, most screening tools involving combinations of questions were based on low-quality studies or, when diagnostic performance was assessed among high-quality studies, demonstrated poor performance in helping to identify patients at high vs low risk.Conclusions and relevanceWhile a history of substance use disorder, certain mental health diagnoses, and concomitant prescription of certain psychiatric medications appeared useful for identifying patients at higher risk, few quality studies were available and no symptoms, signs, or screening tools were particularly useful for identifying those at lower risk.

Dataset Information

Sociodemographic Characteristics and the Stigmatization of Prescription Opioid Addiction.

Objectives

Methods

Results

Conclusions

Publications

Sociodemographic Characteristics and the Stigmatization of Prescription Opioid Addiction.

Similar Datasets

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