An implementation and effectiveness study evaluating Conflict Analysis in VA residential substance abuse services: Whole Health informed self-guided online care.

CONTEXT: Whole Health is an emerging healthcare framework that emphasizes wellbeing in place of illness. Conflict Analysis (CA), an online self-guided assessment, leverages innovative diagnostic and therapeutic resources that shares Whole Health objectives, including helping users explore their identity and develop a personalized health plan and helping users develop resources to optimize their health. OBJECTIVES: Paper presents CA implementation-effectiveness study in a Veteran Affairs inpatient substance recovery care. DESIGN: Patients were randomized to CA or mindfulness control. Patients completed Whole Health outcomes measures at baseline, completion (post), and three-week follow-up. Interventions took 2.5 h. Attending psychologist assessed CA protocols and completed outcome evaluation. Due to Coronavirus, recruitment and follow-up were curtailed. SETTING: Study took place in a rural northern New England Veteran Affairs inpatient substance recovery unit. OUTCOME MEASURES: Measures include The Personal Growth Initiative Scale, The Beck Cognitive Insight Scale, Perceived Stress Scale, The Patient Health Questionnaire, Perceived Psychological Wellbeing, and Perceived Therapeutic and Diagnostic Benefit. RESULTS: 12 patients were randomized, 11 completed post measures (CA=5; Mindfulness = 6), and 7 completed follow-up measures (CA=3; Mindfulness=4). CA offered significant Whole Health benefits when compared to control. Additionally, participant and clinician evaluations indicated that CA can be personally relevant, meaningful, and motivate therapeutic growth. Implications include extending CA research and expanding Whole Health related interventions. Although initial results suggest implementation feasibility and Whole Health benefit, more research is necessary to establish CA's utility within inpatient substance recovery care in particular and psychiatric rehabilitation in general.

Rapid disinfection of radiology treatment rooms using an autonomous ultraviolet germicidal irradiation robot.

BACKGROUND: Ultraviolet germicidal irradiation (UVGI) technologies have emerged as a promising adjunct to manual cleaning, however, their potential to shorten cleaning times remains unexplored. METHODS: A <10-minute disinfection procedure was developed using a robotic UVGI platform. The efficacy and time to perform the UVGI procedure in a CT scan treatment room was compared with current protocols involving manual disinfection using biocides. For each intervention, environmental samples were taken at 12 locations in the room before and after disinfection on seven distinct occasions. RESULTS: The mean UVC dose at each sample location was found to be 13.01 ± 4.36 mJ/cm2, which exceeded published UVC thresholds for achieving log reductions of many common pathogens. Significant reductions in microbial burden were measured after both UVGI (P≤.001) and manual cleaning (P≤.05) conditions, with the UVGI procedure revealing the largest effect size (r = 0.603). DISCUSSION: These results support the hypothesis that automated deployments of UVGI technology can lead to germicidal performance that is comparable with, and potentially better than, current manual cleaning practices. CONCLUSIONS: Our findings provide early evidence that the incorporation of automated UVGI procedures into cleaning workflow could reduce turnaround times in radiology, and potentially other hospital settings.

Hospital surface disinfection using ultraviolet germicidal irradiation technology: A review.

Ultraviolet germicidal irradiation (UVGI) technologies have emerged as a promising alternative to biocides as a means of surface disinfection in hospitals and other healthcare settings. This paper reviews the methods used by researchers and clinicians in deploying and evaluating the efficacy of UVGI technology. The type of UVGI technology used, the clinical setting where the device was deployed, and the methods of environmental testing that the researchers followed are investigated. The findings suggest that clinical UVGI deployments have been growing steadily since 2010 and have increased dramatically since the start of the COVID-19 pandemic. Hardware platforms and operating procedures vary considerably between studies. Most studies measure efficacy of the technology based on the objective measurement of bacterial bioburden reduction; however, studies conducted over longer durations have examined the impact of UVGI on the reduction of healthcare associated infections (HCAIs). Future trends include increased automation and the use of UVGI technologies that are safer for use around people. Although existing evidence seems to support the efficacy of UVGI as a tool capable of reducing HCAIs, more research is needed to measure the magnitude of these effects and to establish recommended best practices.

Location, location, location: a discrete choice experiment to inform COVID-19 vaccination programme delivery in the UK.

BACKGROUND: Large-scale vaccination is fundamental to combatting COVID-19. In March 2021, the UK's vaccination programme had delivered vaccines to large proportions of older and more vulnerable population groups; however, there was concern that uptake would be lower among young people. This research was designed to elicit the preferences of 18-29-year-olds regarding key delivery characteristics and assess the influence of these on intentions to get vaccinated, to inform planning for this cohort. METHODS: From 25 March to 2 April 2021, an online sample of 2012 UK adults aged 18-29 years participated in a Discrete Choice Experiment. Participants made six choices, each involving two SMS invitations to book a vaccination appointment and an opt-out. Invitations had four attributes (1 × 5 levels, 3 × 3 levels): delivery mode, appointment timing, proximity, and sender. These were systematically varied according to a d-optimal design. Responses were analysed using a mixed logit model. RESULTS: The main effects logit model revealed a large alternative-specific constant (ß = 1.385, SE = 0.067, p < 0.001), indicating a strong preference for 'opting in' to appointment invitations. Pharmacies were dispreferred to the local vaccination centre (ß = - 0.256, SE = 0.072, p < 0.001), appointments in locations that were 30-45 min travel time from one's premises were dispreferred to locations that were less than 15 min away (ß = - 0.408, SE = 0.054, p < 0.001), and, compared to invitations from the NHS, SMSs forwarded by 'a friend' were dispreferred (ß = - 0.615, SE = 0.056, p < 0.001) but invitations from the General Practitioner were preferred (ß = 0.105, SE = 0.048, p = 0.028). CONCLUSIONS: The results indicated that the existing configuration of the UK's vaccination programme was well-placed to deliver vaccines to 18-29-year-olds; however, some adjustments might enhance acceptance. Local pharmacies were not preferred; long travel times were a disincentive but close proximity (0-15 min from one's premises) was not necessary; and either the 'NHS' or 'Your GP' would serve as adequate invitation sources. This research informed COVID-19 policy in the UK, and contributes to a wider body of Discrete Choice Experiment evidence on citizens' preferences, requirements and predicted behaviours regarding COVID-19.

Mapping the proteo-genomic convergence of human diseases.

Characterization of the genetic regulation of proteins is essential for understanding disease etiology and developing therapies. We identified 10,674 genetic associations for 3892 plasma proteins to create a cis-anchored gene-protein-disease map of 1859 connections that highlights strong cross-disease biological convergence. This proteo-genomic map provides a framework to connect etiologically related diseases, to provide biological context for new or emerging disorders, and to integrate different biological domains to establish mechanisms for known gene-disease links. Our results identify proteo-genomic connections within and between diseases and establish the value of cis-protein variants for annotation of likely causal disease genes at loci identified in genome-wide association studies, thereby addressing a major barrier to experimental validation and clinical translation of genetic discoveries.

Exploring the Applicability of Robot-Assisted UV Disinfection in Radiology.

The importance of infection control procedures in hospital radiology departments has become increasingly apparent in recent months as the impact of COVID-19 has spread across the world. Existing disinfectant procedures that rely on the manual application of chemical-based disinfectants are time consuming, resource intensive and prone to high degrees of human error. Alternative non-touch disinfection methods, such as Ultraviolet Germicidal Irradiation (UVGI), have the potential to overcome many of the limitations of existing approaches while significantly improving workflow and equipment utilization. The aim of this research was to investigate the germicidal effectiveness and the practical feasibility of using a robotic UVGI device for disinfecting surfaces in a radiology setting. We present the design of a robotic UVGI platform that can be deployed alongside human workers and can operate autonomously within cramped rooms, thereby addressing two important requirements necessary for integrating the technology within radiology settings. In one hospital, we conducted experiments in a CT and X-ray room. In a second hospital, we investigated the germicidal performance of the robot when deployed to disinfect a CT room in <15 minutes, a period which is estimated to be 2-4 times faster than current practice for disinfecting rooms after infectious (or potentially infectious) patients. Findings from both test sites show that UVGI successfully inactivated all of measurable microbial load on 22 out of 24 surfaces. On the remaining two surfaces, UVGI reduced the microbial load by 84 and 95%, respectively. The study also exposes some of the challenges of manually disinfecting radiology suites, revealing high concentrations of microbial load in hard-to-reach places. Our findings provide compelling evidence that UVGI can effectively inactivate microbes on commonly touched surfaces in radiology suites, even if they were only exposed to relatively short bursts of irradiation. Despite the short irradiation period, we demonstrated the ability to inactivate microbes with more complex cell structures and requiring higher UV inactivation energies than SARS-CoV-2, thus indicating high likelihood of effectiveness against coronavirus.

Longitudinal Examination of COVID-19 Public Health Measures on Mental Health for Rural Patients With Serious Mental Illness.

INTRODUCTION: There is emerging evidence to support that the COVID-19 pandemic and related public health measures may be associated with negative mental health sequelae. Rural populations in particular may fair worse because they share many unique characteristics that may put them at higher risk for adverse outcomes with the pandemic. Yet, rural populations may also be more resilient due to increased sense of community. Little is known about the impact of the pandemic on the mental health and well-being of a rural population pre- and post-pandemic, especially those with serious mental illness. MATERIAL AND METHODS: We conducted a longitudinal, mixed-methods study with assessments preceding the pandemic (between October 2019 and March 2020) and during the stay-at-home orders (between April 23, 2020, and May 4, 2020). Changes in hopelessness, suicidal ideation, connectedness, and treatment engagement were assessed using a repeated-measures ANOVA or Friedman test. RESULTS: Among 17 eligible participants, 11 people were interviewed. Overall, there were no notable changes in any symptom scale in the first 3-5 months before the pandemic or during the stay-at-home orders. The few patients who reported worse symptoms were significantly older (mean age: 71.7 years, SD: 4.0). Most patients denied disruptions to treatment, and some perceived telepsychiatry as beneficial. CONCLUSIONS: Rural patients with serious mental illness may be fairly resilient in the face of the COVID-19 pandemic when they have access to treatment and supports. Longer-term outcomes are needed in rural patients with serious mental illness to better understand the impact of the pandemic on this population.