Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8–2323), posts (29–28,684), and Gini coefficients (0.15–0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527–0.835, p < .001), and Gini coefficients and number of posts (0.342–0.725, p < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p < .036). Linear regression models had positive but mixed R2 results (0.333–0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant (t = 3.346–7.381, p < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks (t = −4.305 and −5.934, p < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required

Current quality of life and its determinants among opiate-dependent individuals five years after starting methadone treatment

This study explores the current QoL of opiate-dependent individuals who started outpatient methadone treatment at least 5 years ago and assesses the influence of demographic, psychosocial, drug and health-related variables on individuals' QoL. Participants (n = 159) were interviewed about their current QoL, psychological distress and severity of drug-related problems, using the Lancashire Quality of Life Profile, the Brief Symptom Inventory and the Addiction Severity Index. Potential determinants of QoL were assessed in a multiple linear regression analysis. Five years after the start of methadone treatment, opiate-dependent individuals report low QoL scores on various domains. No association was found between drug-related variables and QoL, but a significant negative impact of psychological distress was identified. Severity of psychological distress, taking medication for psychological problems and the inability to change one's living situation were associated with lower QoL. Having at least one good friend and a structured daily activity had a significant, positive impact on QoL. Opiate-dependent individuals' QoL is mainly determined by their psychological well-being and a number of psychosocial variables. These findings highlight the importance of a holistic approach to treatment and support in methadone maintenance treatment, which goes beyond fixing the negative physical consequences of opiate dependence

Policy Changes and the Methadone Maintenance Treatment System for Opioid Dependence in Ontario, 1996 to 2001

Background. Until recently, the availability of methadone treatment in Ontario, Canada was limited. In 1996, policy changes Methods. For these census data, descriptive statistics were used to examine changes in the patient and provider populations over time using data from the College of Physicians and Surgeons of Ontario Methadone Maintenance Registry of Patients and the Registry of Methadone Prescribing Physicians. Results. Between 1996 and 2001, the total number of clients in treatment increased substantially from: 1595 to 7787. Over this time period, the number of physicians prescribing methadone increased from 60 to 161. Interpretation. Policy changes resulted in substantial increases in the patient and provider populations across Ontario. However, the estimated low proportion of opiate users in treatment indicates that more efforts are needed to address the potential demand for treatment

Factors predicting 2-year retention in methadone maintenance treatment for opioid dependence

Factors predicting 2-year retention in methadone maintenance and the impact of repeat treatment episodes on retention are examined. Data (n=9555 episodes) were drawn from a population-based treatment registry and analyses were performed using episode-weighted data. We estimated a binary logistic regression model with a duration of 730 days or greater as the dependent variable. The odds of remaining in treatment for 730 days or more increase with age and vary by region and provider type, but decrease with increasing number of treatment episodes. In comparison with other studies, these analyses show much higher rates of retention in methadone treatment but suggest that repeat episodes may not be as beneficial as existing research suggests

Prescribed safer supply during dual public health emergencies: a qualitative study examining service providers perspectives on early implementation

Abstract Background Within North America and worldwide, drug related overdoses have increased dramatically over the past decade. COVID-19 escalated the need for a safer supply to replace unregulated substances and to reduce toxicity and overdoses. Service providers play an integral role in the delivery of safer supply but there is little empirical evidence that conceptualizes effective safer supply from their perspectives. This study explored early implementation and impacts of a safer supply program, capturing the perspectives of an interdisciplinary team of service providers on tensions and issues encountered in the development of the SAFER program. Methods Using a community-based participatory approach, we conducted individual interviews with program providers (n = 9). The research team was composed of researchers from a local drug user organization, a local harm reduction organization, and academic researchers. The Consolidated Framework for Implementation Research (CFIR) informed the interview guide. Data was analyzed using thematic analysis. Results There are six themes describing early implementation: (1) risk mitigation prescribing as context for early implementation; (2) developing SAFER specific clinical protocols; (3) accessibility challenges and program innovations; (4) interdisciplinary team and wraparound care; (5) program tensions between addiction medicine and harm reduction; (6) the successes of safer supply and future visions. Conclusion Early implementation issues and tensions included prescriber concerns about safer supply prescribing in a highly politicized environment, accessibility challenges for service users such as stigma, encampment displacement, OAT requirements, program capacity and costs, and tensions between addiction medicine and harm reduction. Navigating these tensions included development of clinical protocols, innovations to reduce accessibility challenges such as outreach, wraparound care, program coverage of medication costs and prescribing safer supply with/without OAT. These findings contribute important insights for the development of prescribed safer supply programs