An analysis by KGG4 confirmed the gene IMMP2L and additionally identified a non-coding RNA INHBA- AS1 as significant hits. IMMP2L functions in the mitochondrion where it is involved with processing of signal peptides as a peptidase directing transport to the interior mitochondrial space. INHBA- AS1 and INHBA were previously associated with dental caries in a GWAS, and INHBA was postulated to influence the development of dental caries via its role in tooth morphology development. In support of this hypothesis Zeng et al. discuss that INHBA has been shown to be important for tooth development and knockout mice of INHBA have alterations in the eruption of new teeth. Attachment to the tooth surface is a part of the establishment of the oral micro-biome and disruption of this process could lead to changes in the community structure of oral biofilms. Ascribing functional significance to IMMP2L, INHBA-AS1, or LIN7A,cannabis grow facility layout is speculative in the absence of a replication experiment. Nevertheless, this study is among the first to use heritability to refine micro-biome phenotypes prior to GWAS testing and the findings will provide a basis for additional genetic studies in larger replication samples and in future molecular analyses. Of the 100 most significantly associated SNPs for each of the 6 GWAS analyses in the EUR sample, 7 SNPs were shared at least twice among Bray Curtis PCo2, Unweighted UniFrac PCo2, and Weighted UniFrac PCo2 analyses probably due to shared underlying variation of PCo2.
A comparison of SNPS from the Granulicatella GWAS and the PCo3 unweighted UniFrac Meta Analysis in our experiments with other published GWAS studies of the micro-biome found that the majority of overlapping SNPs followed a normal distribution, and those few that did deviate from expectation did not reach genome wide significance in either study. It is perhaps not surprising that genes showing influence in gut do not appear in salivary samples. There is very little overlap in organism composition between niches and it can be argued that one reason for this is that different genes influence each niche.Whereas twin studies are particularly powerful in differentiating between them, GWAS is poorly suited to teasing these factors apart. We show that tobacco/marijuana/alcohol use has little influence on the ability to detect associations of our top scoring loci. This is somewhat unexpected in that it is well known that some microbes either increase or decrease in response to tobacco. This is consistent with a hypothesis that the tobacco effects seen are mostly free of significant genetic influences and that conversely, the genetic effects we find do not dependent on environmental perturbations to be observed. The results point out a need for well-controlled gene by environment experiments to fully understand how genes work and how environmental factors actually influence microbial communities.Misuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Globally, 3.5 million people die from alcohol and illicit drug use each year. The disease burden of alcohol and illicit drug addiction is the highest in the United States. Over 20 million Americans had a substance use disorder in 2018, 73% had an alcohol use disorder, 40% had an illicit drug use disorder, and 13% had both alcohol and illicit drug use disorders. Approximately half of Americans with an SUD had a co-occurring mental illness. Treatment of depression and anxiety, the most common psychiatric comorbidities among patients with SUDs, may reduce craving and substance use and enhance overall outcomes. In 2018, less than 1 in 5 individuals with a SUD received addiction treatment.
Alcohol and illicit drug misuse and addiction cost the United States over US $440 billion annually in lost workplace productivity, health care expenses, and crime-related costs. Potential effects on individuals include an array of physical and mental health problems, overdose, trauma, and violence. Web-based interventions and digital health apps may reduce or eliminate common, significant barriers to traditional SUD treatment. Preliminary evidence suggests that digital SUD interventions affect substance use behavior and have the potential to reduce the population burden of SUDs. To date, most digital SUD interventions have been delivered on a web platform, rather than via mobile apps. The widespread use of smartphones makes app-based intervention delivery a viable and scalable medium. In 2019, about 8 out of 10 White, Black, and Latinx adults owned a smartphone. Although lower-income adults were less likely to own a smartphone than higher-income adults, they were more likely to rely on smartphones for internet access. In a 2015 survey, 58% of mobile phone owners reported downloading a health app. Texting is the most widely and frequently used app on a smartphone, with 97% of Americans texting at least once a day. Automated conversational agents can deliver a coach-like or sponsor-like experience and yet do not require human implementation assistance for in-the-moment treatment delivery. As recent meta-analytic work suggests, conversational text-based agents may increase engagement and enjoyment in digitized mental health care , whereas most general mental health care apps face difficulty sustaining engagement with high dropout. Conversational agents can provide real-time support to address substance use urges, unlike traditional in-person frameworks of weekly visits. The scale potential of conversational agents is unconstrained, immediate, and available to users in an instant. Being nonhuman based also reduces perceived stigma.
A study found that people were significantly more likely to disclose personal information to artificial intelligence when they believed it was computer- rather than human-monitored. Users can develop a strong therapeutic alliance in the absence of face-to-face contact, even with a nonhuman app. Digital environments can promote honest disclosure due to greater ease of processing thoughts and reduced risk of embarrassment. Finally, although conversational agents can present in different modalities, including text, verbal, and animation, preliminary research on modality for psychoeducation delivery specifically found that text-based presentation resulted in higher program adherence than verbal presentation. Evidence for conversational agent interventions for addressing mental health problems is growing quickly and appears promising with regard to acceptability and efficacy. Developed as a mental health digital app, Woebot is a text-based conversational agent available to check in with users whenever they have smartphone access. Using conversational tones, Woebot is designed to encourage mood tracking and to deliver general psycho education as well as tailored empathy, cognitive behavioral therapy –based behavior change tools, and behavioral pattern insight. Among a sample of adults randomly assigned to Woebot or an information only control group, Woebot users had statistically and clinically significant reductions in depressive symptoms after 2 weeks of use,indoor grow shelves whereas those in the control group did not. Engagement with the app was high. However, the efficacy of conversational agents for treating SUDs remains unknown. Woebot’s app-based platform and user-centered design philosophy make it a promising modality for SUD treatment delivery; it offers immediate, evidence-based tailored support in the peak moment of craving. An informal poll of Woebot users indicated that 63% had interest in content addressing SUDs; 22% of surveyed users reported having 5 or more alcoholic drinks in a row within a couple of hours, and 5% endorsed using nonprescription drugs. Although the efficacy of automated conversational agent digital therapeutics for SUDs is still untested, such products are commercially available, and few consumers are aware that the products lack evidence. This study aims to adapt the original Woebot for the treatment of SUDs , and test the feasibility, acceptability, and preliminary efficacy in a single-group pre-/post treatment design. Participants were recruited via the Woebot app, social media , Craigslist, and Stanford staf and student wellness listservs. In addition, study flyers were posted in the San Francisco Bay Area, and email invitations were sent to participants from previous studies. Recruitment materials included the URL on a web page describing the study for people with substance use concerns. Informed consent was required to screen for eligibility. Those who screened as eligible were asked to provide informed consent for participation in the study. Inclusion criteria were all genders, aged 18 years to 65 years, residing in the United States, screening positive on the 4-item Cut down, Annoyed, Guilty, Eye opener-Adapted to Include Drugs , owning a smartphone for accessing Woebot, available for the 8-week study, willing to provide an email address, and English literate. The CAGE-AID has demonstrated validity, with high internal consistency in screening for problematic drug and alcohol use; a cutoff point of 2+ on the CAGE-AID has a sensitivity of 70% and specificity of 85% for identifying individuals with SUDs.
Study exclusion criteria were current pregnancy, history of severe alcohol or drug-related medical problems , opioid overdose requiring Narcan , current opioid misuse without medication-assisted treatment, or attempted suicide within the past year. For this study, the target sample size was 50 participants; however, due to a high level of response and efficiency, enrollment was more than double our recruitment goal. Between March 27, 2020 and May 6, 2020, 3597 individuals were screened for study participation, with 3422 ineligible and 175 eligible individuals. Figure 1 shows the reasons for study exclusion, most frequently residing outside of the United States and endorsing fewer than 2 criteria on the CAGE-AID . Of the 175 eligible participants, 141 provided informed consent to participate in the study, of whom 128 completed the baseline survey. The analytic sample consisted of 101 participants who ultimately registered with W-SUDs and initiated use. Among the 101 participants enrolled, 11 reported previous use of the Woebot app. Described in detail previously, Woebot is an automated conversational agent that delivers CBT in the format of brief, daily text-based conversations. The Woebot program is deployed through its own native apps on both iPhone and Android smartphones or devices. The app on boarding process introduces the automated conversational agent, explains the intended use of the device, how data are treated, and the limitations of the service . The user experience is centered around mood tracking and goal-oriented, tailored conversations that can, depending on user input and choice, focus on CBT psychoeducation, application of psychotherapeutic skills for change , mindfulness exercises, gratitude journaling, and/or reflecting upon patterns and lessons already covered. Each interaction begins with a general inquiry about context and mood to ascertain affect in the moment. Additional therapeutic process-oriented features of Woebot include delivery of empathic responses with tailoring to users’stated mood, goal setting with regular check-ins for maintaining accountability, a focus on motivation and engagement, and individualized weekly reports to foster reflection. Users become familiar with Woebot, which is a friendly, helpful character that is explicitly not a human or a therapist but rather a guided self-help coach. Daily push notifications prompt users to check in. We adapted W-SUDs, drawing upon motivational interviewing principles, mindfulness training, dialectical behavior therapy, and CBT for relapse prevention. Sample screenshots from the W-SUDs app are shown in Figure 2. In total, the W-SUDs intervention was developed as an 8-week program with tracking of mood, substance use craving, and pain, with over 50 psycho educational lessons and psychotherapeutic skills. CBT evidence-based, guided self-help treatments have ranged in length from 2 to 12 weeks, and the National Institutes for Clinical Excellence describes guided self-help as including 6 to 8 face-to-face sessions. Early responsiveness to SUD treatment is predictive of long-term outcomes, and brief addiction treatments are efficacious. Brief intervention can minimize potential dropout, a problem common to SUD treatment;therefore, we designed W-SUDs as an 8-week treatment. Woebot is not designed to address active suicidal ideation or overdose, and this was stated in the study informed consent. In addition, Woebot conversationally informs first-time users that it is not a crisis service. Woebot also has safety net detection that uses natural language processing algorithms to detect and flag several hundred possible harm-to-self phrases with 98% accuracy . Woebot detects crisis language and asks to confirm it with the user. If the user confirms, Woebot offers resources , carefully curated with expert consultation. Woebot data indicate that users do not use Woebot for crisis management; approximately 6.3% trigger the safety net protocol, with 27% of those confirming that it is indeed a crisis when Woebot asks to confirm . Demographic items were assessed at pretreatment; substance use, mental health, and pain measures were administered at preand post treatment; serious adverse events and W-SUDs feasibility and acceptability were assessed at post treatment; andW-SUDs use data were collected via the Woebot app over the 8-week intervention.