Modeling Substance Use and Mental Disorder Comorbidity Using Latent Variable and Network Approaches

Introduction. Substance use disorder (SUD) is a common condition that affects millions of Americans. Addressing SUD has been complicated by comorbid mental disorders and co-occurring substance use. Consequently, detailing and addressing SUD and comorbid SUD represent an important goal to improve the health of Americans. Objective. The research goal of this dissertation was to characterize the comorbidity between substance use, including tobacco use, and mental disorder symptoms measured as negative affect and externalizing symptoms in a population-based sample using latent variable and network approaches. Methods. Waves 1 – 3 from the Population Assessment of Tobacco and Health Study were used. Various statistical analyses were used to complete each project including multinomial and ordinal regression, latent class analysis, cumulative ROC curve analysis, and network analysis. Results. The associations between psychopathology (negative affect vs. externalizing severity) varied by different substance use combinations. Both latent class analysis and network analysis results identified relationships between (1) exclusive cigarette, dual cigarette and e-cigarette, marijuana, and PDNP with negative affect symptoms, and (2) alcohol with externalizing symptoms. The comorbidity structure remained stable with transition to lower severity groups but identification of stronger connections across three data points. Conclusions. This dissertation identified specific combinations of substance use behaviors and mental disorder symptoms, determined which sociodemographic factors play a role in specific comorbidity profiles, and assessed the patterns of comorbidity among three waves of data. The results can inform robust and targeted prevention strategies to effectively mitigate the substantial burden and societal costs of comorbidity in the U.S. population

The Association between Loneliness with Increased Mental Health Problems and Substance Use During the COVID-19 Pandemic in Richmond, Virginia

Background. The COVID-19 pandemic caused significant psychological distress among U.S. adults leading to increased rates of adverse mental health symptoms and substance use. This study aims to evaluate the consistency of the association between loneliness and increased mental health problems and substance use in Richmond, VA during the COVID-19 pandemic. Methods. Data were collected in two phases: 1) internet-based surveys from August 2020 to March 2021 (N=327) and 2) paper-pencil surveys from May to October 2021 (N=225). Logistic regression was used to test the association between loneliness and increased mental health and substance use, while adjusting for sociodemographic factors and pre-existing mental health conditions. Results. Both survey populations reported a high prevalence of increased loneliness (46.7% - 68.8%), mental health problems (50.2% - 67.3%), and substance use (22.2% - 29.4%) since the COVID-19 pandemic. Increased loneliness since the pandemic was significantly associated with increased mental health problems (Online survey: AOR=5.00, 95% CI=2.56 - 9.97; Paper-pencil survey: AOR=10.48, 95% CI=4.18 - 28.59) and increased substance use (Online survey: AOR=3.14, 95% CI=1.58 - 6.60; Paper-pencil survey: AOR=5.89, 95% CI=1.97 - 19.71). Conclusions. The association between increased loneliness and increased mental health problems and substance use during COVID-19 in Richmond, Virginia was consistent across the two survey populations and similar to the rest of the U.S

The use and potential impact of digital health tools at the community level: results from a multi-country survey of community health workers

Abstract Background Community health workers (CHWs) are increasingly viewed as a critical workforce to address health system strengthening and sustainable development goals. Optimizing and widening the capacity of this workforce through digital technology is currently underway, though there is skepticism regarding CHWs’ willingness and optimism to engage in digital health. We sought to understand CHWs’ perceptions on the use of digital health tools in their work. Methods We obtained survey data from 1,141 CHWs from 28 countries with complete study information. We conducted regression analyses to explore the relationship between CHWs’ training and perceived barriers to digital health access with current use of digital devices/tools and belief in digital impact while adjusting for demographic factors. Results Most of the CHWs worked in Kenya (n = 502, 44%) followed by the Philippines (n = 308, 27%), Ghana (n = 107, 9.4%), and the United States (n = 70, 6.1%). There were significant, positive associations between digital tools training and digital device/tool use (Adjusted Odds Ratio (AOR) = 2.92, 95% CI = 2.09–4.13) and belief in digital impact (AORhigh impact = 3.03, 95% CI = 2.04–4.49). CHWs were significantly less likely to use digital devices for their work if they identified cost as a perceived barrier (AORmobile service cost = 0.68, 95% CI = 0.49–0.95; AORphone/device cost = 0.66, 95% CI = 0.47–0.92). CHWs who were optimistic about digital health, were early adopters of technology in their personal lives, and found great value in their work believed digital health helped them to have greater impact. Older age and greater tenure were associated with digital device/tool use and belief in digital impact, respectively. Conclusions CHWs are not an obstacle to digital health adoption or use. CHWs believe that digital tools can help them have more impact in their communities regardless of perceived barriers. However, cost is a barrier to digital device/tool use; potential solutions to cost constraints of technological access will benefit from further exploration of reimbursement models. Digital health tools have the potential to increase CHW capacity and shape the future of community health work

Additional file 1 of The use and potential impact of digital health tools at the community level: results from a multi-country survey of community health workers

Supplementary Material 1