Pathway-enhanced Transformer-based model for robust enumeration of cell types from the cell-free transcriptome (preprint)

Analysis cell types origin of cell-free RNA can enhance the resolution of liquid biopsies, thereby deepening the understanding of molecular and cellular changes in development and disease processes. Existing deconvolution methods typically rely on meticulously curated gene expression profiles or employ deep neural network with vast and complex solution spaces that are difficult to interpret. These approaches fail to leverage the synergistic and co-expression effects among genes in biological signaling pathways, compromising their generalizability and robustness. To address this issue, we have developed 'Deconformer', a Transformer-based deconvolution model that integrates biological signaling pathways at the embedding stage. Compared to popular methods on multiple datasets, Deconformer demonstrates superior performance and robustness, and is capable of tracking the developmental process of the placenta. Additionally, Deconformer's self-attention mechanism has identified a connection between platelet activation, dependencies with other pathways, and the severity of COVID-19. We believe that Deconformer will enable and accelerate the precise analysis of a wide range of cell-free RNA, describing disease progression and severity from the perspectives of originating cell fractions and pathway dependencies.

An ecological study of COVID-19 outcomes among Florida counties (preprint)

BackgroundDuring the COVID-19 pandemic, Florida reported some of the highest number of cases and deaths in the US; however, county-level variation in COVID-19 outcomes has not been comprehensively investigated. The present ecological study aimed to assess corelates of COVID-19 outcomes among Florida counties that explain variation in case rates, mortality rates, and case fatality rates (CFR) across pandemic waves. MethodWe obtained county-level administrative data and COVID-19 case reports from public repositories. We tested spatial autocorrelation to assess geographic clustering in COVID-19 outcomes: case rate, mortality rate, and CFR. Stepwise linear regression was employed to test the association between case, death, and CFR and 18 demographic, socioeconomic, and health-related county-level predictors. ResultsWe found mortality rate and CFR were significantly higher in rural counties compared to urban counties, among which significant differences in vaccination coverage was also observed. Multivariate analysis found that the percentage of the population aged over 65 years, the percentage of the obese people, and the percentage of rural population were significant predictors of COVID-19 case rate. Median age, vaccination coverage, percentage of people who smoke, and percentage of the population with diabetes were significant influencing factors for CFR. Importantly, vaccination coverage was significantly associated with a reduction in case rate (R = - 0.26, p = 0.03) and mortality (R = -0.51, p < 0.001). Last, we found that spatial dependencies play a role in explaining variations in COVID-19 CFR among Florida counties. ConclusionOur findings emphasize the need for targeted, equitable public health strategies to reduce disparities and enhance population resilience during public health crises. We further inform future spatial-epidemiological analyses and present actionable data for policies related to preparedness and response to current and future epidemics in Florida and elsewhere.

Reducing variation in the quality of long covid care: Lessons from a national quality improvement collaborative and multi-site ethnography (preprint)

Context Long covid (post covid-19 condition) is a complex condition with diverse manifestations and uncertain prognosis. There is wide variation in how patients are investigated and managed. There have been calls for formal quality standards so as to reduce a so-called “postcode lottery” of care. We aimed to examine the nature of quality in long covid care and reduce unwarranted variation in care provided by long covid services. Methods In a mixed-method study (2021-2023), we ran a quality improvement collaborative across 10 UK sites. We also gathered data on the origins and current context of each clinic, interviewed staff and patients, and observed 12 clinics (52 consultations) and 34 multidisciplinary team (MDT) meetings (230 patient cases). Data collection and analysis were informed by relevant lenses from clinical care (e.g. evidence-based guidelines), improvement science (e.g. quality improvement cycles, reducing unwarranted variation) and philosophy of knowledge. Results The collaborative made progress towards standardizing assessment and management in some topics, but much variation remained. Clinics had different histories and path-dependencies, occupied a different place in their healthcare ecosystem and served a varied caseload including (in most clinics) a high proportion of patients with comorbidities. Dimensions of quality prioritized by patients related to the service (e.g. accessibility, ease of navigation), and human qualities of staff (e.g. attentiveness, compassion). A key route to quality long covid care was when local MDTs deliberated on unusual, complex or challenging cases for which evidence-based guidelines provided no easy answers. In such cases, collective learning occurred through idiographic reasoning, in which practitioners build lessons from the particular to the general. This contrasts with the nomothetic reasoning implicit in evidence-based guidelines, in which reasoning is assumed to go from the general (e.g. findings of clinical trials) to the particular (management of individual patients). Conclusion Not all variation in long covid services is unwarranted. Largely because long covid’s manifestations are so varied, universal ‘evidence-based’ standards are hard to define and implement. In this complex condition, quality improvement resources may be better spent supporting team-based learning locally than attempting to standardize care across widely differing services. Trial registration NCT05057260, ISRCTN15022307.

Statistical Machine Learning Meets High-Dimensional Spatiotemporal Challenges -- A Case Study of COVID-19 Modeling (preprint)

Diverse non-pharmacological interventions (NPIs), serving as the primary approach for COVID-19 control prior to pharmaceutical interventions, showed heterogeneous spatiotemporal effects on pandemic management. Investigating the dynamic compounding impacts of NPIs on pandemic spread is imperative. However, the challenges posed by data availability of high-dimensional human behaviors and the complexity of modeling changing and interrelated factors are substantial. To address these challenges, this study analyzed social media data, COVID-19 case rates, Apple mobility data, and the stringency of stay-at-home policies in the United States throughout the year 2020, aiming to (1) uncover the spatiotemporal variations in NPIs during the COVID-19 pandemic utilizing geospatial big data; (2) develop a statistical machine learning model that incorporates spatiotemporal dependencies and temporal lag effects for the detection of relationships; (3) dissect the impacts of NPIs on the pandemic across space and time. Three indices were computed based on Twitter (currently known as X) data: the Negative and Positive Sentiments Adjusted by Demographics (N-SAD and P-SAD) and the Ratio Adjusted by Demographics (RAD), representing negative sentiment, positive sentiment, and public awareness of COVID-19, respectively. The Multivariate Bayesian Structural Time Series Time Lagged model (MBSTS-TL) was proposed to investigate the effects of NPIs, accounting for spatial dependencies and temporal lag effects. The developed MBSTS-TL model exhibited a high degree of accuracy. Determinants of COVID-19 health impacts transitioned from an emphasis on human mobility during the initial outbreak period to a combination of human mobility and stay-at-home policies during the rapid spread phase, and ultimately to the compound of human mobility, stay-at-home policies, and public awareness of COVID-19.

Changes in emergency department utilization in vulnerable populations after COVID-19 shelter in place orders (preprint)

Purpose: To compare emergency department (ED) utilization and admission rates for patients with a history of mental health (MH), substance use disorder (SUD) and social determinants of health (SDOH) before and after implementing COVID-19's shelter-inplace (SIP) orders. Methods: This was a retrospective, multicenter study leveraging electronic medical record data from 20 EDs across a large Midwest integrated healthcare system from 5/2/2019 to 12/31/2019 (pre-SIP) and from 5/2/2020 to 12/31/2020 (post-SIP). Diagnoses were documented in the patient's medical records. Poisson and logistic regression models were used to evaluate ED utilization and admission rate changes. Results: 871,020 total ED encounters from 487,028 unique patients were captured. 2,572 (0.53%) patients had a documented Z code for SDOH. Patients with previously diagnosed MH or SUDs were more likely to seek ED care after the SIP orders were implemented (RR: 1.20, 95% CI: 1.18 - 1.22, p<0.001), as were patients with SDOH (RR: 2.37, 95% CI: 2.19 - 2.55, p<0.001). Patients with both previously diagnosed MH or SUD and a documented SDOH had even higher ED utilization (RR: 3.31, 95% CI: 2.83 - 3.88, p<0.001) than those with either condition alone. Patients with MH and SUDs (OR: 0.89, 95% CI: 0.86 - 0.92, p<0.001) or SDOH (OR: 0.67, 95% CI: 0.54, 0.83, p<0.001) were less likely to be admitted post-SIP orders while patients with a history of diseases of physiologic systems were more likely to be admitted. Conclusions: Vulnerable populations with a history of MH, SUD, and SDOH experienced increased ED utilization but a lower rate of hospital admissions after the implementation of SIP orders. The findings highlight the importance of addressing these needs to mitigate the impact of public health crises on these populations.

Evaluation of Effectiveness of Pre-Training Method in Chest X-Ray Imaging Using Vision Transformer (preprint)

The limited availability of medical images is a major limitation when using deep learning, which requires large amounts of data to improve performance. To address this problem, transfer learning has become the de facto standard, using convolutional neural networks (CNNs) previously trained on natural images, such as ImageNet, and fine-tuned with medical images. Recently, vision transformers (ViT), which require large annotated medical images, have been studied from various perspectives. In this study, we investigated an effective pre-training method, especially for ViT. Specifically, an evaluation of the binary classification of COVID-19 and normal chest X-ray images was conducted. The following conclusions were drawn from the evaluation: (1) the fine-tuning method was more effective than the feature extraction method; (2) pre-trained natural images as a fine-tuning method are more effective than task-specific images, namely medical images; (3) the pre-trained natural images learned more Position Embeddings (PEs) with long-range dependencies than medical images; (4) ViT is more effective than CNNs when there are a large number of pre-training natural images, and vice versa when the number of pre-training natural images is limited. These results suggest that the fine-tuning method with a large number of natural images as pre-training data using ViT had the best discrimination performance for the binary classification in this study.

A Cross-sectional study of Challenges Faced by Under-Resourced Women with Substance Use Disorders during the COVID-19 Pandemic: Implications for Treatment and Care Delivery (preprint)

Background: The COVID-19 pandemic has exacerbated existing disparities in access to mental health care and treatment for substance use disorders (SUD), particularly in under-resourced communities. This study aimed to understand the experiences of under-resourced women with substance use disorders during the COVID-19 pandemic, their knowledge and attitudes towards the pandemic, and its impact on their substance use and access to treatment. Methods: This is a cross-sectional study of 66 under-resourced women receiving medically managed withdrawal treatment in a community residential SUD treatment center. Data were collected from November 2021 to August 2022 through a 75-item instrument covering topics related to COVID-19 exposure, pandemic impact on health, substance use, and access to treatment, COVID-19 vaccination status and attitudes, as well as knowledge and beliefs about the virus and pandemic risk mitigation measures. Descriptive analyses were conducted to summarize the data. Results: Results revealed that participants faced numerous challenges during the pandemic. Many reported increased substance use, particularly alcohol, opioids, benzodiazepines, and nicotine. Mental health stability was also negatively impacted, with a majority reporting the exacerbation of existing mental health disorders and difficulties accessing mental health care. Job loss, housing instability, and financial strain were prevalent among the participants. Half of the respondents received at least one dose of a COVID-19 vaccine, while 27.3% did not receive the COVID-19 vaccine and were not considering it. Vaccine hesitancy was observed due to concerns about lack of knowledge and religious beliefs. The majority (62.1%) of participants felt that their greatest worry was about challenges to securing basic needs such as groceries or medication, and (64.6%) reported a desire to cope using alcohol or drugs. Conclusions: These findings highlight the need for gender-responsive and culturally appropriate approaches to substance use disorders treatment. Additionally, efforts should focus on improving access to mental health care, reducing stigma, and providing resources and support to individuals with co-occurring mental health conditions during and after the pandemic. This study provides valuable insights to refine substance use care delivery and recovery services for under-resourced women, both in the early post-pandemic period and in preparation for future global crises.

COVID-19 incidence in the Republic of Ireland: A case study for network-based time series models (preprint)

Network-based Time Series models have experienced a surge in popularity over the past years due to their ability to model temporal and spatial dependencies such as arising from the spread of an infectious disease. As statistical models for network time series, generalised network autoregressive (GNAR) models have been introduced. GNAR models are vertex-based models which have an autoregressive component modelling temporal dependence and a spatial autoregressive component to incorporate dependence between neighbouring vertices in the network. This paper compares the performance of GNAR models with different underlying networks in predicting COVID-19 cases for the 26 counties in the Republic of Ireland. The dataset is separated into subsets according to inter-country movement regulations and categorized into two pandemic phases, restricted and unrestricted. Ten static networks are constructed based on either general or COVID-19 specific approaches. In these networks, vertices represent counties, and edges are built upon neighbourhood relations, such as railway lines. We find that while for the prediction task, no underlying static network is consistently superior for either restricted or unrestricted phase, for pandemic phases with restrictions sparse networks perform better while for unrestricted phases, dense networks explain the data better. GNAR models have higher predictive accuracy than ARIMA models, which ignore the network structure. ARIMA and GNAR models perform similarly in pandemic phases with more lenient or no COVID-19 regulation. These findings indicate evidence of network dependencies in the restricted phase, but not in the unrestricted phase. They also show some robustness regarding the network construction method. An analysis of the residuals justifies the model assumptions for the restricted phase but raises questions for the unrestricted phase.

SARS-CoV-2 Nsp1 regulates translation start site fidelity to promote infection (preprint)

A better mechanistic understanding of virus-host interactions can help reveal vulnerabilities and identify opportunities for therapeutic interventions. Of particular interest are essential interactions that enable production of viral proteins, as those could target an early step in the virus lifecycle. Here, we use subcellular proteomics, ribosome profiling analyses and reporter assays to detect changes in polysome composition and protein synthesis during SARS-CoV-2 (CoV2) infection. We identify specific translation factors and molecular chaperones whose inhibition impairs infectious particle production without major toxicity to the host. We find that CoV2 non-structural protein Nsp1 selectively enhances virus translation through functional interactions with initiation factor EIF1A. When EIF1A is depleted, more ribosomes initiate translation from an upstream CUG start codon, inhibiting translation of non-structural genes and reducing viral titers. Together, our work describes multiple dependencies of CoV2 on host biosynthetic networks and identifies druggable targets for potential antiviral development.

Alternative cell entry mechanisms for SARS-CoV-2 and multiple animal viruses (preprint)

The cell entry mechanism of SARS-CoV-2, the causative agent of the COVID-19 pandemic, is not fully understood. Most animal viruses hijack cellular endocytic pathways as an entry route into the cell. Here, we show that in cells that do not express serine proteases such as TMPRSS2, genetic depletion of all dynamin isoforms blocked the uptake and strongly reduced infection with SARS-CoV-2 and its variant Delta. However, increasing the viral loads partially and dose-dependently restored infection via a thus far uncharacterized entry mechanism. Ultrastructural analysis by electron microscopy showed that this dynamin-independent endocytic processes appeared as 150-200 nm non-coated invaginations and was efficiently used by numerous mammalian viruses, including alphaviruses, influenza, vesicular stomatitis, bunya, adeno, vaccinia, and rhinovirus. Both the dynamin-dependent and dynamin-independent infection of SARS-CoV-2 required a functional actin cytoskeleton. In contrast, the alphavirus Semliki Forest virus, which is smaller in diameter, required actin only for the dynamin-independent entry. The presence of TMPRSS2 protease rescued SARS-CoV-2 infection in the absence of dynamins. Collectively, these results indicate that some viruses such as canine parvovirus and SARS-CoV-2 mainly rely on dynamin for endocytosis-dependent infection, while other viruses can efficiently bypass this requirement harnessing an alternative infection entry route dependent on actin.

Psychoactive substances, anatomy and pre-pandemic COVID-19 students: prevalence of use and comparison of cross-sectional studies from the period 2011-2019 / Sustancias psicoactivas, alumnos de anatomía y prepandemia COVID-19: prevalencia de uso y comparación de estudios transversales del periodo 2011-2019

En estudios preliminares objetivamos alta prevalencia de uso de sustancias psicoactivas (SP) entre alumnos de Anatomía, con mayor impacto entre los recursantes o aquellos con actividades laborales. La causa del uso es multifactorial, pero se destacan factores de riesgo y precipitantes como la carga horaria de la currícula, exigencias de estudio, el distrés por el afrontamiento cadavérico negativo, el nuevo contexto educativo y la cantidad de horas de sueño. El objetivo fue comparar la prevalencia de uso de SP entre las cohortes de 2011-2019, con focalización en los factores determinantes conductuales. Estudio observacional, transversal y comparativo mediante encuesta estandarizada y anónima en 945 alumnos (año 2011= 122; año 2013= 158; año 2015=204; año 2017= 228; año 2019= 233). Se aplicaron parámetros estadísticos, se definió la significación como p -0.84; AA: r> -0.71). En el caso de ansiolíticos benzodiacepínicos, se asoció con falta de sueño y distrés por el afrontamiento negativo al estudio con cadáveres. En las cohortes comparadas por el lapso de 9 años hallamos alta prevalencia de uso de sustancias psicoactivas con tendencia al incremento. Las variables actividad laboral y recursante fueron determinantes para el uso de sustancias, y se asociaron cuestiones relativas a la adaptabilidad universitaria y afrontamiento de estudio negativo con el cadáver; todos con incidencia pedagógica en el proceso de enseñanza y aprendizaje.

SUMMARY: In preliminary studies, we observed a high prevalence of the use of psychoactive substances (PS) among Anatomy students, with a greater impact among recurrent students or those with work activities. The cause of use is multifactorial, but risk and precipitating factors stand out, such as the workload of the curriculum, study demands, distress due to negative cadaveric coping, the new educational context and the number of hours of sleep. The objective was to compare the prevalence of SP use between the 2011-2019 cohorts, with a focus on behavioral determinants. Observational, cross-sectional and comparative study using a standardized and anonymous survey in 945 students (year 2011= 122; year 2013= 158; year 2015=204; year 2017= 228; year 2019= 233). Statistical parameters were applied, significance was defined as p -0.84; AA: r> -0.71). In the case of benzodiazepine anxiolytics, it was associated with lack of sleep and distress due to negative coping with the study with cadavers. In the cohorts compared for a period of 9 years, we found a high prevalence of psychoactive substance use with an increasing trend. The variables work activity and recurrence were determinants for the use of substances, and issues related to university adaptability and negative study coping with the corpse were associated; all with pedagogical impact on the teaching and learning process.

Alcohol Misuse, Binge Drinking, and their Associations with Psychosocial Factors during COVID-19 among Harlem Residents in New York City.

This study examined alcohol misuse and binge drinking prevalence among Harlem residents, in New York City, and their associations with psycho-social factors such as substance use, depression symptom severity, and perception of community policing during COVID-19. An online cross-sectional study was conducted among 398 adult residents between April and September 2021. Participants with a score of at least 3 for females or at least 4 for males out of 12 on the Alcohol Use Disorders Identification Test were considered to have alcohol misuse. Binge drinking was defined as self-reporting having six or more drinks on one occasion. Modified Poisson regression models were used to examine associations. Results showed that 42.7% used alcohol before COVID-19, 69.1% used it during COVID-19, with 39% initiating or increasing alcohol use during COVID-19. Alcohol misuse and binge drinking prevalence during COVID-19 were 52.3% and 57.0%, respectively. Higher severity of depression symptomatology, history of drug use and smoking cigarettes, and experiencing housing insecurity were positively associated with both alcohol misuse and binge drinking. Lower satisfaction with community policing was only associated with alcohol misuse, while no significant associations were found between employment insecurity and food insecurity with alcohol misuse or binge drinking. The findings suggest that Harlem residents may have resorted to alcohol use as a coping mechanism to deal with the impacts of depression and social stressors during COVID-19. To mitigate alcohol misuse, improving access to mental health and substance use disorder services, and addressing public safety through improving relations with police could be beneficial.

Hospital Use and Mortality Among Decarcerated Individuals With Substance Use Disorder After a Large-scale COVID-19 Emergency Prison Release Program.

This cohort study examines hospital use and mortality among persons with substance use disorder (SUD) who were released from New Jersey state prisons after a COVID-19 emergency prison release program.

Insights from Drug Checking Programs: Practicing Bootstrap Public Health Whilst Tailoring to Local Drug User Needs.

The year 2021 was the most deadly year for overdose deaths in the USA and Canada. The stress and social isolation stemming from the COVID-19 pandemic coupled with a flood of fentanyl into local drug markets created conditions in which people who use drugs were more susceptible to accidental overdose. Within territorial, state, and local policy communities, there have been longstanding efforts to reduce morbidity and mortality within this population; however, the current overdose crisis clearly indicates an urgent need for additional, easily accessible, and innovative services. Street-based drug testing programs allow individuals to learn the composition of their substances prior to use, averting unintended overdoses while also creating low threshold opportunities for individuals to connect to other harm reduction services, including substance use treatment programs. We sought to capture perspectives from service providers to document best practices around fielding community-based drug testing programs, including optimizing their position within a constellation of other harm reduction services to best serve local communities. We conducted 11 in-depth interviews from June to November 2022 via Zoom with harm reduction service providers to explore barriers and facilitators around the implementation of drug checking programs, the potential for integration with other health promotion services, and best practices for sustaining these programs, taking the local community and policy landscape into account. Interviews lasted 45-60 min and were recorded and transcribed. Thematic analysis was used to reduce the data, and transcripts were discussed by a team of trained analysts. Several key themes emerged from our interviews: (1) the instability of drug markets amid an inconsistent and dangerous drug supply; (2) implementing drug checking services in dynamic environments in response to the rapidly changing needs of local communities; (3) training and ongoing capacity building needed to create sustainable programs; and (4) the potential for integrating drug checking programs into other services. There are opportunities for this service to make a difference in overdose deaths as the contours of the drug market itself have changed over time, but a number of challenges remain to implement them effectively and sustain the service over time. Drug checking itself represents a paradox within the larger policy context, putting the sustainability of these programs at risk and challenging the potential to scale these programs as the overdose epidemic worsens.

Impacts of COVID-19 on family violence in Thailand: prevalence and influencing factors.

BACKGROUND: The COVID-19 pandemic drastically affected societies globally, prompting rising unemployment, insufficient household incomes, and stress and undermining women's and children's health within families. This study examined family violence and identified influencing factors during the COVID-19 pandemic in Thailand. METHODS: A mixed-method design was used, entailing a questionnaire followed by focus group interviews. A cross-sectional survey was administered to investigate family violence among 1285 female respondents aged 15 years and above who were recruited through stratified sampling. The Cronbach alpha and and inter-raters Kappa coefficient values for the questionnaire were 0.67 and 1.00, respectively. In addition, a descriptive qualitative instrument was employed to analyze the data sets from four focus group interviews held with 32 staff members from agencies that deal with family violence. The researchers jointly developed the focus group questions, which focused on the impacts of the COVID-19 pandemic on family violence. They independently analyzed data using content analysis. RESULTS: The majority of the study participants were aged above 45 years (>50%), married (61.1%), lived in single-family settings (52.5%), had lost their jobs (64.4%), and had economic constraints that were moderate (37.8%) to severe (40.6%). The prevalence of family violence, which was primarily physical, was 42.2%. Family income, stress, and substance abuse were the main factors associated with family violence. These findings were correlated with those from the qualitative interviews. CONCLUSIONS: The COVID-19 pandemic had indirect impacts through family violence. Women were subjected to family violence behaviors, which were associated with household income, economic status, stress, and substance abuse. These behaviors included psychological and physical violence, as well as sexual abuse. Future interventions should focus on financial support and stress reduction.

An epigenetic synopsis of parental substance use.

The rate of substance use is rising, especially among reproductive-age individuals. Emerging evidence suggests that paternal pre-conception and maternal prenatal substance use may alter offspring epigenetic regulation (changes to gene expression without modifying DNA) and outcomes later in life, including neurodevelopment and mental health. However, relatively little is known due to the complexities and limitations of existing studies, making causal interpretations challenging. This review examines the contributions and influence of parental substance use on the gametes and potential transmissibility to the offspring's epigenome as possible areas to target public health warnings and healthcare provider counseling of individuals or couples in the pre-conception and prenatal periods to ultimately mitigate short- and long-term offspring morbidity and mortality.

More people, especially those of reproductive age, are using substances, and there is growing evidence to suggest that parental substance use before and during pregnancy may adversely affect offspring and result in issues later in life, including mental health challenges. Such relationships have been demonstrated with nicotine, alcohol, cannabis, opioids and illegal drugs (e.g., heroin, cocaine, methamphetamines). Some of these adverse impacts on offspring can potentially be passed down in families even after parents have quit using the substance. Because more individuals are using drugs, especially during the COVID-19 pandemic, it is important that families learn more about the potential impact of substance use on their future offspring before they try to get pregnant.

Mental health and adherence to antiretroviral therapy among Mexican people living with HIV during the COVID-19 pandemic.

BACKGROUND: The mental health and medical follow-up of people living with HIV (PLWH) have been disrupted by the COVID-19 pandemic. The objectives of this study were to assess anxiety, depression and substance use in Mexican PLWH during the pandemic; to explore the association of these symptoms with adherence to antiretroviral therapy (ART), and to compare patients with and without vulnerability factors (low socioeconomic level, previous psychological and/or psychiatric treatment). METHODS: We studied 1259 participants in a cross-sectional study, PLWH receiving care at the HIV clinic in Mexico City were contacted by telephone and invited to participate in the study. We included PLWH were receiving ART; answered a structured interview on sociodemographic data and adherence to ART; and completed the psychological instruments to assess depressive and anxiety symptoms and substance use risk. Data collection was performed from June 2020 to October 2021. RESULTS: 84.7% were men, 8% had inadequate ART adherence, 11% had moderate-severe symptoms of depression, and 13% had moderate-severe symptoms of anxiety. Adherence was related to psychological symptoms (p < 0.001). Vulnerable patients were more likely to be women, with low educational level and unemployed (p < 0.001). CONCLUSIONS: It is important to address mental health of PLWH during the COVID-19 pandemic, with special attention to the most vulnerable individuals. Future studies are needed to understand the relationship between mental health and ART adherence.

Examining outcomes for service users accessing the Breaking Free Online computer-assisted therapy program for substance use disorders via a 'telehealth' approach: protocol for a two arm, parallel group randomized controlled trial.

BACKGROUND: Breaking Free Online (BFO), a computer-assisted therapy (CAT) program for substance use disorders (SUD), has been available across UK treatment services for the past decade and has demonstrated efficacy. The Covid-19 pandemic has contributed to digital and 'telehealth' approaches to healthcare delivery becoming more common and accepted, and has in parallel, increased numbers of referrals to SUD services because of the impact pandemic-related stress has had on substance using habits in the general population. Digital and telehealth approaches, such as BFO, have the potential to support the treatment system to meet this increased demand for SUD services. METHODS: Parallel-group randomized controlled trial of eight-week BFO as an adjunct to standard treatment for SUD, in comparison to standard treatment only, at a National Health Service (NHS) Mental Health Trust in North-West England. Participants will be service users aged 18 years and over with demonstrable SUD for at least 12-months. Interventional and control groups will be compared on multiple measures from baseline to post-treatment assessment at eight-weeks, and then three and six-months follow-up. Primary outcome will be self-reported substance use, with secondary outcomes being standardized assessments of substance dependence, mental health, biopsychosocial functioning and quality of life. DISCUSSION: This study will examine whether BFO and telehealth support, when delivered as an adjunct to standard SUD interventions, improves outcomes for services users receiving NHS SUD treatment. Findings from the study will be used to inform both developments to the BFO program and guidance around augmenting the delivery of CAT programs via telehealth. Trial registration registered with ISRCTN on 25th May 2021-registration number: 13694016. PROTOCOL VERSION: 3.0 05th April 2022. TRIAL STATUS: This trial is currently open to recruitment-estimated to be completed in May 2023.

Was retrospective change measurement conducted with Covid-19 containment inconsistent? Comparing prospective and retrospective change measures using data from a national survey on substance use and addictive behaviors.

Single-measurement-point data collection to assess change has increased with studies assessing the impact of the Covid-19 pandemic and of its containment, despite evidence of its lack of validity. Retrospective change is not equivalent to change in repeated self-reported measures giving raise to questions about the validity of the former. This paper purports to investigate inconsistencies between change measures by confronting retrospective change to information from longitudinally self-reported measures from the C-SURF cohort study. The study sample consists of 2,279 young men who participated in C-SURF between 2020 and 2021, and completed between May and June 2021 a survey covering change in alcohol, cigarette, cannabis and other addictive behaviors related to the pandemic. The aforementioned behaviors were assessed longitudinally at two time points using self-reports, and retrospective change since the onset of the Covid-19 crisis was also assessed at the second measurement time. Information from both prospective and retrospective change measures were confronted to identify inconsistent information for each behavior. Additionally, multiple logistic regressions were performed to assess associations between socioeconomic status, impulsivity, depression, and different indicators of motivation to complete the study and inconsistency between both measures for each behavior of interest. Importantly, inconsistent information in at least one of the investigated behaviors was found in about 90% of the participants. Small associations were found between inconsistency and different factors with a consistent effect of impulsivity. In the absence of evidence of the validity of retrospective change measures, studies relying on retrospective change should be interpreted with caution.

A multicomponent psychosocial intervention to reduce substance use by adolescents involved in the criminal justice system: the RISKIT-CJS RCT.

Background: Substance use and offending are related in the context of other disinhibitory behaviours. Adolescents involved in the criminal justice system constitute a particularly vulnerable group, with a propensity to engage in risky behaviour that has long-term impact on their future health and well-being. Previous research of the RISKIT programme provided evidence of a potential effect in reducing substance use and risky behaviour in adolescents. Objectives: To evaluate the clinical effectiveness and cost-effectiveness of a multicomponent psychosocial intervention compared with treatment as usual in reducing substance use for substance-using adolescents involved in the criminal justice system. Design: A mixed-methods, prospective, pragmatic, two-arm, randomised controlled trial with follow-up at 6 and 12 months post randomisation. Setting: The study was conducted across youth offending teams, pupil referral units and substance misuse teams across four areas of England (i.e. South East, London, North West, North East). Participants: Adolescents aged between 13 and 17 years (inclusive), recruited between September 2017 and June 2020. Interventions: Participants were randomised to treatment as usual or to treatment as usual in addition to the RISKIT-Criminal Justice System (RISKIT-CJS) programme. The RISKIT-CJS programme was a multicomponent intervention and consisted of two individual motivational interviews with a trained youth worker (lasting 45 minutes each) and two group sessions delivered over half a day on consecutive weeks. Main outcome measures: At 12 months, we assessed per cent days abstinent from substance use over the previous 28 days. Secondary outcome measures included well-being, motivational state, situational confidence, quality of life, resource use and fidelity of interventions delivered. Results: A total of 693 adolescents were assessed for eligibility, of whom 505 (73%) consented. Of these, 246 (49%) were allocated to the RISKIT-CJS intervention and 259 (51%) were allocated to treatment as usual only. At month 12, the overall follow-up rate was 57%: 55% in the RISKIT-CJS arm and 59% in the treatment-as-usual arm. At month 12, we observed an increase in per cent days abstinent from substances in both arms of the study, from 61% to 85%, but there was no evidence that the RISKIT-CJS intervention was superior to treatment as usual. A similar pattern was observed for secondary outcomes. The RISKIT-CJS intervention was not found to be any more cost-effective than treatment as usual. The qualitative research indicated that young people were positive about learning new skills and acquiring new knowledge. Although stakeholders considered the intervention worthwhile, they expressed concern that it came too late for the target population. Limitations: Our original aim to collect data on offences was thwarted by the onset of the COVID-19 pandemic, and this affected both the statistical and economic analyses. Although 214 (87%) of the 246 participants allocated to the RISKIT-CJS intervention attended at least one individual face-to-face session, 98 (40%) attended a group session and only 47 (19%) attended all elements of the intervention. Conclusions: The RISKIT-CJS intervention was no more clinically effective or cost-effective than treatment as usual in reducing substance use among adolescents involved in the criminal justice system. Future research: The RISKIT-CJS intervention was considered more acceptable, and adherence was higher, in pupil referral units and substance misuse teams than in youth offending teams. Stakeholders in youth offending teams thought that the intervention was too late in the trajectory for their population. Trial registration: This trial is registered as ISRCTN77037777. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 11, No. 3. See the NIHR Journals Library website for further project information.

We explored how useful a psychological intervention was in reducing substance use among young people who had some involvement in the criminal justice system. We recruited young people aged between 13 and 17 years in four areas of England (i.e. South East, London, North West and North East). Young people were recruited from youth offending teams, pupil referral units and substance misuse teams. Those young people who were willing to participate were offered usual treatment and half, chosen at random, were offered an opportunity to take part in the RISKIT-Criminal Justice System (RISKIT-CJS) programme. The RISKIT-CJS programme had four distinct parts. The first was a 1-hour session that used an approach called motivational interviewing to explore the young person's substance use and discuss different strategies to change their behaviour. This was followed by two group sessions delivered over 2 consecutive weeks. These group sessions addressed risks associated with substance use, what triggers use and the health and social consequences. In addition, young people were taught new skills to help them manage in situations in which they might normally use substances. At the end of the group sessions, the young people had another motivational interview. Twelve months after participants started, we found that the frequency of substance use had decreased in both groups; however, the RISKIT-CJS intervention was no better than treatment as usual. When we spoke with young people who had taken part and staff involved with this population, we got a mixed picture. In some settings, particularly pupil referral units, the RISKIT-CJS intervention was well received by young people and staff, and staff felt that it was a useful additional resource to the work that they were currently undertaking. On the other hand, in the youth offending teams, the staff thought that the programme was too different from their normal work to be implemented easily and they considered the population they work with too established in their substance use and criminal activity to benefit from the programme.