Text messages exchanged between individuals with opioid use disorder and their mHealth e-coaches: Content analysis study

BACKGROUND: Opioid use disorder (OUD) has affected 2.2 million people in the United States. About 7.2 million people reported using illicit drugs in 2019, which contributed to over 70,000 overdose deaths. SMS text messaging interventions have been shown to be effective in OUD recovery. However, the interpersonal communication between individuals in OUD treatment and a support team on digital platforms has not been well examined. OBJECTIVE: This study aims to understand the communication between participants undergoing OUD recovery and their e-coaches by examining the SMS text messages exchanged from the lens of social support and the issues related to OUD treatment. METHODS: A content analysis of messages exchanged between individuals recovering from OUD and members of a support team was conducted. Participants were enrolled in a mobile health intervention titled uMAT-R, a primary feature of which is the ability for patients to instantly connect with a recovery support staff or an e-coach via in-app messaging. Our team analyzed dyadic text-based messages of over 12 months. In total, 70 participants\u27 messages and 1196 unique messages were analyzed using a social support framework and OUD recovery topics. RESULTS: Out of 70 participants, 44 (63%) were between the ages of 31 and 50 years, 47 (67%) were female, 41 (59%) were Caucasian, and 42 (60%) reported living in unstable housing conditions. An average of 17 (SD 16.05) messages were exchanged between each participant and their e-coach. Out of 1196 messages, 64% (n=766) messages were sent by e-coaches and 36% (n=430) by participants. Messages of emotional support occurred the most, with 196 occurrences (n=9, 0.8%) and e-coaches (n=187, 15.6%). Messages of material support had 110 occurrences (participants: n=8, 0.7%; e-coaches: n=102, 8.5%). With OUD recovery topics, opioid use risk factors appeared in most (n=72) occurrences (patient: n=66, 5.5%; e-coach: n=6, 0.5%), followed by a message of avoidance of drug use 3.9% (n=47), which occurred mainly from participants. Depression was correlated with messages of social support (r=0.27; P=.02). CONCLUSIONS: Individuals with OUD who had mobile health needs tended to engage in instant messaging with the recovery support staff. Participants who are engaged in messaging often engage in conversations around risk factors and avoidance of drug use. Instant messaging services can be instrumental in providing the social and educational support needs of individuals recovering from OUD

Spatial navigation in autism spectrum disorders: a critical review

On the basis of relative strengths that have been attributed to the Autistic cognitive profile, it has been suggested by a number of theorists that people with Autism Spectrum Disorders (ASD) excel at spatial navigational tasks. However, many of these claims have been made in the absence of a close inspection of extant data in the scientific literature, let alone anecdotal reports of daily navigational experiences. The present review gathers together published studies that have attempted to explicitly address functional components of navigation in ASD populations, including assays of wayfinding, large-scale search, and path integration. This inspection reveals a pattern of apparent strengths and weaknesses in navigational abilities, thus illustrating the necessity for a more measured and comprehensive approach to the understanding of spatial behaviour in ASD

Impact of the COVID-19 pandemic on burnout and perceived workplace quality among addiction treatment providers

Abstract Background This study examines the impact of the COVID-19 pandemic on work satisfaction, work-related stress, and perceived work quality among substance use treatment providers to better understand challenges faced among this group during the pandemic. Methods Participants of this study were 91 addiction treatment providers (e.g., therapists, physicians, community support specialists, administrative staff) recruited from various treatment facilities (e.g., inpatient and outpatient settings). Mixed method analyses were conducted to assess self-reported burnout, sources of work-related stress, and perceived work quality during the pandemic. Responses from providers reporting COVID-19 related decreases in work quality were compared to responses from providers who reported their quality of work had increased or remained the same. Results Results demonstrated half of providers (51%) reported their quality of work had decreased. This perceived decrease in quality of work was associated with higher levels of emotional exhaustion (M = 17.41 vs. M = 12.48, p = 0.002), workplace stress (M = 42.80 vs. M = 30.84, p = 0.001), as well as decreased enjoyment of work (83% vs. 51%, p = 0.001) and decreased personal accomplishment (M = 20.64 vs. M = 23.05 p = 0.001). Qualitative investigations further illustrated that increased hours, changes in work schedules, work-life balance challenges, difficulties with client communication, and increased client needs were contributing factors increasing stress/burnout and decreasing perceived work quality. Conclusions Addiction treatment providers experience high levels of burnout and workplace stress. Additionally, many individuals perceived a decrease in their quality of work during the COVID-19 pandemic. Addiction treatment facility administration should address these challenges to support the well-being of clinical staff and the clients they serve both during and after the COVID-19 pandemic

Detecting risk level in individuals misusing fentanyl utilizing posts from an online community on Reddit

Funding Information: Funding for this work was provided by the National Institutes of Health (NIH) [Grant No: K02 DA043657 (Dr. Cavazos-Rehg) and Grant No: R01MH117172 (Dr. De Choudhury)], and through a postdoctoral fellowship to Dr. Aledavood from the James S. McDonnell Foundation . We would also like to acknowledge Vivian Agbonavbare and Nnenna Anako for their work to manually code posts and comments for this study. Publisher Copyright: © 2021 The AuthorsIntroduction: Opioid misuse is a public health crisis in the US, and misuse of synthetic opioids such as fentanyl have driven the most recent waves of opioid-related deaths. Because those who misuse fentanyl are often a hidden and high-risk group, innovative methods for identifying individuals at risk for fentanyl misuse are needed. Machine learning has been used in the past to investigate discussions surrounding substance use on Reddit, and this study leverages similar techniques to identify risky content from discussions of fentanyl on this platform. Methods: A codebook was developed by clinical domain experts with 12 categories indicative of fentanyl misuse risk, and this was used to manually label 391 Reddit posts and comments. Using this data, we built machine learning classification models to identify fentanyl risk. Results: Our machine learning risk model was able to detect posts or comments labeled as risky by our clinical experts with 76% accuracy and 76% sensitivity. Furthermore, we provide a vocabulary of community-specific, colloquial words for fentanyl and its analogues. Discussion: This study uses an interdisciplinary approach leveraging machine learning techniques and clinical domain expertise to automatically detect risky discourse, which may elicit and benefit from timely intervention. Moreover, our vocabulary of online terms for fentanyl and its analogues expands our understanding of online “street” nomenclature for opiates. Through an improved understanding of substance misuse risk factors, these findings allow for identification of risk concepts among those misusing fentanyl to inform outreach and intervention strategies tailored to this at-risk group.Peer reviewe

Data from: Evolutionary and demographic history of the Californian scrub white oak species complex: an integrative approach

Understanding the factors promoting species formation is a major task in evolutionary research. Here, we employ an integrative approach to study the evolutionary history of the Californian scrub white oak species complex (genus Quercus). To infer the relative importance of geographical isolation and ecological divergence in driving the speciation process, we (i) analyzed inter- and intra-specific patterns of genetic differentiation and employed an approximate Bayesian computation (ABC) framework to evaluate different plausible scenarios of species divergence. In a second step, we (ii) linked the inferred divergence pathways with current and past species distribution models, and (iii) tested for niche differentiation and phylogenetic niche conservatism across taxa. ABC analyses showed that the most plausible scenario is the one considering the divergence of two main lineages followed by a more recent pulse of speciation. Genotypic data in conjunction with species distribution models and niche differentiation analyses support that different factors (geography vs. environment) and modes of speciation (parapatry, allopatry and maybe sympatry) have played a role in the divergence process within this complex. We found no significant relationship between genetic differentiation and niche overlap, which probably reflects niche lability and/or that multiple factors have contributed to speciation. Our study shows that different mechanisms can drive divergence even among closely related taxa representing early stages of species formation and exemplifies the importance of adopting integrative approaches to get a better understanding of the speciation process