Effects of Actissist, a digital health intervention for early psychosis: A randomized clinical trial.

Schizophrenia affects 24 million people worldwide. Digital health interventions drawing on psychological principles have been developed, but their effectiveness remains unclear. This parallel, assessor-blinded, randomized clinical trial aimed to investigate whether a cognitive behaviour therapy-informed digital health intervention (Actissist app) confers added benefit on psychotic symptoms over and above remote symptom monitoring (ClinTouch app). Participants recruited from UK community health services were randomized 1:1 to receive either Actissist plus treatment as usual (TAU) or ClinTouch plus TAU. Eligible participants were adults with schizophrenia-spectrum psychosis within five years of first episode onset meeting a criterion level of positive symptoms severity. The primary outcome was Positive and Negative Syndrome Scale (PANSS) symptoms total score at 12 weeks post-randomization. Intention-to-treat analysis included 172 participants, with 149 participants (86.6 %) providing primary outcome data. Actissist plus TAU was not associated with greater reduction than an active control remote symptom monitoring app (ClinTouch) in PANSS total score at post-randomization. There were no significant effects between groups across secondary measures. There were no serious adverse reactions. Both groups improved on the primary psychotic symptoms measure at primary end-point and on secondary measures over time. The Actissist app is safe but not superior to digital symptom monitoring.

Interprofessional socialization of first-year medical and midwifery students: effects of an ultra-brief anatomy training.

BACKGROUND: Interprofessionalism is considered a key component in modern health profession education. Nevertheless, there remains ongoing debate about when and where to introduce interprofessional trainings in the curriculum. We identified anatomy, a subject commonly shared among health professionals, as a practical choice for initiating early intergroup-contact between first-year medical and midwifery students. Our study examined the effects of a four-hour block course in anatomy on interprofessional socialization and valuing, as well as long-term effects on intergroup contact. METHODS: Based on different concepts and theories of learning, we implemented 12 interprofessional learning stations. Several measures were taken to foster group cohesion: (1) self-directed working in interprofessional tandems on authentic obstetric tasks, (2) competing with other tandems, (3) creating positive interdependencies during task completion, and (4) allowing room for networking. In a pre-post design with a three-month follow-up, we assessed the outcomes of this ultra-brief training with qualitative essays and quantitative scales. RESULTS: After training, both groups improved in interprofessionalism scores with strong effect sizes, mean difference in ISVS-21 = 0.303 [95% CI: 0.120, 0.487], P < .001, η² = 0.171, while the scales measuring uniprofessional identity were unaffected, mean difference in MCPIS = 0.033 [95% CI: -0.236, 0.249], P = .789. A follow-up indicated that these positive short-term effects on the ISVS-21 scale diminished after 12 weeks to baseline levels, yet, positive intergroup contact was still reported. The qualitative findings revealed that, at this initial stage of their professional identity development, both medical and midwifery students considered interprofessionalism, teamwork and social competencies to be of importance for their future careers. CONCLUSION: This study advocates for an early implementation of interprofessional learning objectives in anatomical curricula. Young health profession students are receptive to interprofessional collaboration at this initial stage of their professional identity and derive strong advantages from a concise training approach. Yet, maintaining these gains over time may require ongoing support and reinforcement, such as through longitudinal curricula. We believe that an interprofessional socialization at an early stage can help break down barriers, and help to avoid conflicts that may arise during traditional monoprofessional curricula.

Measurement of Adverse Events in Studies of Digital Health Interventions for Psychosis: Guidance and Recommendations Based on a Literature Search and Framework Analysis of Standard Operating Procedures.

BACKGROUND: Given the rapid expansion of research into digital health interventions (DHIs) for severe mental illness (SMI; eg, schizophrenia and other psychosis diagnoses), there is an emergent need for clear safety measures. Currently, measurement and reporting of adverse events (AEs) are inconsistent across studies. Therefore, an international network, iCharts, was assembled to systematically identify and refine a set of standard operating procedures (SOPs) for AE reporting in DHI studies for SMI. DESIGN: The iCharts network comprised experts on DHIs for SMI from seven countries (United Kingdom, Belgium, Germany, Pakistan, Australia, United States, and China) and various professional backgrounds. Following a literature search, SOPs of AEs were obtained from authors of relevant studies, and from grey literature. RESULTS: A thorough framework analysis of SOPs (n = 32) identified commonalities for best practice for certain domains, along with significant gaps in others; particularly around the classification of AEs during trials, and the provision of training/supervision for research staff in measuring and reporting AEs. Several areas which could lead to the observed inconsistencies in AE reporting and handling were also identified. CONCLUSIONS: The iCharts network developed best-practice guidelines and a practical resource for AE monitoring in DHI studies for psychosis, based on a systematic process which identified common features and evidence gaps. This work contributes to international efforts to standardize AE measurement and reporting in this emerging field, ensuring that safety aspects of DHIs for SMI are well-studied across the translational pathway, with monitoring systems set-up from the outset to support safe implementation in healthcare systems.

Adverse Events Reporting in Digital Interventions Evaluations for Psychosis: A Systematic Literature Search and Individual Level Content Analysis of Adverse Event Reports.

BACKGROUND: Digital health interventions (DHIs) have significant potential to upscale treatment access to people experiencing psychosis but raise questions around patient safety. Adverse event (AE) monitoring is used to identify, record, and manage safety issues in clinical trials, but little is known about the specific content and context contained within extant AE reports. This study aimed to assess current AE reporting in DHIs. STUDY DESIGN: A systematic literature search was conducted by the iCharts network (representing academic, clinical, and experts by experience) to identify trials of DHIs in psychosis. Authors were invited to share AE reports recorded in their trials. A content analysis was conducted on the shared reports. STUDY RESULTS: We identified 593 AE reports from 18 DHI evaluations, yielding 19 codes. Only 29 AEs (4.9% of total) were preidentified by those who shared AEs as being related to the intervention or trial procedures. While overall results support the safety of DHIs, DHIs were linked to mood problems and psychosis exacerbation in a few cases. Additionally, 27% of studies did not report information on relatedness for all or at least some AEs; 9.6% of AE reports were coded as unclear because it could not be determined what had happened to participants. CONCLUSIONS: The results support the safety of DHIs, but AEs must be routinely monitored and evaluated according to best practice. Individual-level analyses of AEs have merit to understand safety in this emerging field. Recommendations for best practice reporting in future studies are provided.

Methodological Characteristics and Feasibility of Ecological Momentary Assessment Studies in Psychosis: a Systematic Review and Meta-Analysis.

BACKGROUND: Ecological momentary assessment (EMA) involves completing multiple surveys over time in daily life, capturing in-the-moment experiences in real-world contexts. EMA use in psychosis studies has surged over several decades. To critically examine EMA use in psychosis research and assist future researchers in designing new EMA studies, this systematic review aimed to summarize the methodological approaches used for positive symptoms in psychosis populations and evaluate feasibility with a focus on completion rates. METHODS: A systematic review of PubMed, PsycINFO, MEDLINE, Web of Science, EBSCOhost, and Embase databases using search terms related to EMA and psychosis was conducted. Excluding duplicate samples, a meta-analysis was conducted of EMA survey completion rates and meta-regression to examine predictors of completion. RESULTS: Sixty-eight studies were included in the review. Characteristics and reporting of EMA methodologies were variable across studies. The meta-mean EMA survey completion computed from the 39 unique studies that reported a mean completion rate was 67.15% (95% CI = 62.3, 71.9), with an average of 86.25% of the sample meeting a one-third EMA completion criterion. No significant predictors of completion were found in the meta-regression. A variety of EMA items were used to measure psychotic experiences, of which few were validated. CONCLUSIONS: EMA methods have been widely applied in psychosis studies using a range of protocols. Completion rates are high, providing clear evidence of feasibility in psychosis populations. Recommendations for reporting in future studies are provided.

Generating EQ-5D-3L health utility scores from the Edinburgh Postnatal Depression Scale: a perinatal mapping study.

BACKGROUND: Perinatal depression (PND) describes depression experienced by parents during pregnancy or in the first year after a baby is born. The EQ-5D instrument (a generic measure of health status) is not often collected in perinatal research, however disease-specific measures, such as the Edinburgh Postnatal Depression Scale (EPDS) are widely used. Mapping can be used to estimate generic health utility index values from disease-specific measures like the EPDS. OBJECTIVE: To develop a mapping algorithm to estimate EQ-5D utility index values from the EPDS. METHODS: Patient-level data from the BaBY PaNDA study (English observational cohort study) provided 1068 observations with paired EPDS and EQ-5D (3-level version; EQ-5D-3L) responses. We compared the performance of six alternative regression model types, each with four specifications of covariates (EPDS score and age: base, squared, and cubed). Model performance (ability to predict utility values) was assessed by ranking mean error, mean absolute error, and root mean square error. Algorithm performance in 3 external datasets was also evaluated. RESULTS: There was moderate correlation between EPDS score and utility values (coefficient: - 0.42). The best performing model type was a two-part model, followed by ordinary least squared. Inclusion of squared and cubed covariates improved model performance. Based on graphs of observed and predicted utility values, the algorithm performed better when utility was above 0.6. CONCLUSIONS: This direct mapping algorithm allows the estimation of health utility values from EPDS scores. The algorithm has good external validity but is likely to perform better in samples with higher health status.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics.

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Digital tools to support mental health: a survey study in psychosis.

BACKGROUND: There is a notable a gap between promising research findings and implementation of digital health tools. Understanding and addressing barriers to use is key to widespread implementation. METHODS: A survey was administered to a self-selecting sample in-person (n = 157) or online (n = 58), with questions examining: i) ownership and usage rates of digital devices among people with psychosis; ii) interest in using technology to engage with mental health services; and iii) facilitators of and barriers to using digital tools in a mental healthcare context. RESULTS: Device ownership: Virtually all participants owned a mobile phone (95%) or smartphone (90%), with Android phones slightly more prevalent than iPhones. Only a minority owned a fitness tracker (15%) or smartwatch (13%). Device ownership was significantly lower in unemployed people and those without secondary education. Device cost and paranoid ideation were barriers to ownership. Technology and mental health services: Most participants (88%) said they would willingly try a mental health app. Symptom monitoring apps were most popular, then appointment reminders and medication reminders. Half the sample would prefer an app alongside face-to-face support; the other half preferred remote support or no other mental health support. Facilitators: Participants thought using a mental health app could increase their understanding of psychosis generally, and of their own symptoms. They valued the flexibility of digital tools in enabling access to support anywhere, anytime. Barriers: Prominent barriers to using mental health apps were forgetting, lack of motivation, security concerns, and concerns it would replace face-to-face care. Overall participants reported no substantial effects of technology on their mental health, although a quarter said using a phone worsened paranoid ideation. A third used technology more when psychotic symptoms were higher, whereas a third used it less. Around half used technology more when experiencing low mood. CONCLUSIONS: Our findings suggest rapidly increasing device ownership among people with psychosis, mirroring patterns in the general population. Smartphones appear appropriate for delivering internet-enabled support for psychosis. However, for a sub-group of people with psychosis, the sometimes complex interaction between technology and mental health may act as a barrier to engagement, alongside more prosaic factors such as forgetting.

An economic evaluation of universal and targeted case-finding strategies for identifying antenatal depression: a model-based analysis comparing common case-finding instruments.

Half of women with depression in the perinatal period are not identified in routine care, and missed cases reflect inequalities in other areas of maternity care. Case finding (screening) for depression in pregnant women may be a cost-effective strategy to improve identification, and targeted case finding directs finite resources towards the greatest need. We compared the cost-effectiveness of three case-finding strategies: no case finding, universal (all pregnant women), and targeted (only pregnant women with risk factors for antenatal depression, i.e. history of anxiety/depression, age < 20 years, and adverse life events). A decision tree model was developed to represent case finding (at around 20 weeks gestation) and subsequent treatment for antenatal depression (up to 40 weeks gestation). Costs include case finding and treatment. Health benefits are measured as quality-adjusted life years (QALYs). The sensitivity and specificity of case-finding instruments and prevalence and severity of antenatal depression were estimated from a cohort study of pregnant women. Other model parameters were derived from published literature and expert consultation. The most cost-effective case-finding strategy was a two-stage strategy comprising the Whooley questions followed by the PHQ-9. The mean costs were £52 (universal), £61 (no case finding), and £62 (targeted case finding). Both case-finding strategies improve health compared with no case finding. Universal case finding is cost-saving. Costs associated with targeted case finding are similar to no case finding, with greater health gains, although targeted case finding is not cost-effective compared with universal case finding. Universal case finding for antenatal depression is cost-saving compared to no case finding and more cost-effective than targeted case finding.

User engagement in a randomised controlled trial for a digital health intervention for early psychosis (Actissist 2.0 trial).

Digital Health Interventions (DHIs) can help support people with mental health problems. Achieving satisfactory levels of patient engagement is a crucial, yet often underexplored, pre-requisite for health improvement. Actissist is a co-produced DHI delivered via a smartphone app for people with early psychosis, based on Cognitive Behaviour Therapy principles. This study describes and compares engagement patterns among participants in the two arms of the Actissist 2.0 randomised controlled trial. Engagement frequency and duration were measured among participants using the Actissist app in the intervention arm (n = 87) and the ClinTouch symptom monitoring only app used as the control condition (n = 81). Overall, 47.1 % of Actissist and 45.7 % of ClinTouch users completed at least a third of scheduled alerts while active in the study. The mean frequency (77.1 versus 60.2 total responses) and the median duration (80 versus 75 days until last response) of engagement were not significantly higher among Actissist users compared to ClinTouch users. Older age, White ethnicity, using their own smartphone device and, among Actissist users, an increased sense of therapeutic alliance were significantly associated with increased engagement. Through exploiting detailed usage data, this study identifies possible participant-level and DHI-level predictors of engagement to inform the practical implementation of future DHIs.

Sleep problems and referral intentions in mental health services: service user self-report and staff proxy report surveys.

BACKGROUND: Sleep problems are common in mental health service users, but few non-pharmacological therapies are offered. Therapies are being developed and tested, but there may be barriers to these therapies reaching those who need them. METHODS: Light-Dark and Activity Rhythm Therapy (L-DART), is a new sleep therapy delivered by an occupational therapist, which has been feasibility tested in people with schizophrenia spectrum diagnoses. This paper presents two surveys, conducted with mental health staff and service users, on sleep problems, treatment wishes; and barriers and facilitators to uptake of L-DART or similar therapies. Descriptive statistics, single-level and multi-level ordinal logistic regression were used to examine factors associated with sleep problems and referral intentions. FINDINGS: Sleep problems were commonly identified by staff and service users, there was demand for non-pharmacological intervention across diagnostic and demographic categories, but staff readiness to refer differed according to NHS Trust and service user diagnosis. Staff and service user reports differed in awareness of sleep disordered breathing and parasomnias, and wish for referral. Staff were more confident identifying sleep problems than addressing them, but more training was associated with greater confidence concerning both assessment and treatment. CONCLUSIONS: A range of sleep problems are prevalent and recognised in mental health service users, and there is an unmet need for non-pharmacological sleep interventions. Improving suitable resources to support self-management in this group may help; Staff and service users also reported a high readiness to refer or be referred for sleep interventions. Staff training to improve identification of sleep problems, and differentiation between types of sleep problems, would support access to the most appropriate treatments.

An economic evaluation of targeted case-finding strategies for identifying postnatal depression: A model-based analysis comparing common case-finding instruments.

BACKGROUND: Half of women with postnatal depression (PND) are not identified in routine care. We aimed to estimate the cost-effectiveness of PND case-finding in women with risk factors for PND. METHODS: A decision tree was developed to represent the one-year costs and health outcomes associated with case-finding and treatment for PND. The sensitivity and specificity of case-finding instruments, and prevalence and severity of PND, for women with ≥1 PND risk factor were estimated from a cohort of postnatal women. Risk factors were history of anxiety/depression, age < 20 years, and adverse life events. Other model parameters were derived from published literature and expert consultation. Case-finding for high-risk women only was compared with no case-finding and universal case-finding. RESULTS: More than half of the cohort had one or more PND risk factor (57.8 %; 95 % CI 52.7 %-62.7 %). The most cost-effective case-finding strategy was the Edinburgh Postnatal Depression Scale with a cut-off of ≥10 (EPDS-10). Among high-risk women, there is a high probability that EPDS-10 case-finding for PND is cost-effective compared to no case-finding (78.5 % at a threshold of £20,000/QALY), with an ICER of £8146/QALY gained. Universal case-finding is even more cost-effective at £2945/QALY gained (versus no case-finding). There is a greater health improvement with universal rather than targeted case-finding. LIMITATIONS: The model includes costs and health benefits for mothers in the first year postpartum, the broader (e.g. families, societal) and long-term impacts are also important. CONCLUSIONS: Universal PND case-finding is more cost-effective than targeted case-finding which itself is more cost-effective than not case-finding.

Exploring engagement with the CBT-informed Actissist smartphone application for early psychosis.

BACKGROUND: Individuals with psychosis report favourable attitudes towards psychological interventions delivered via smartphone apps. Evidence for acceptability, safety, feasibility and efficacy is promising but in-depth reporting of app engagement in trials is sparse. AIMS: To examine how people with psychosis engaged with the cognitive behaviour therapy (CBT)-informed Actissist app over a 12-week intervention period, and to examine factors associated with app engagement. METHODS: Secondary data from participants in the intervention arm (n = 24) of a proof-of-concept randomised controlled trial of the Actissist app were analysed. The app prompted participants to engage with app-based CBT-informed material in five domains (voices, socialization, cannabis use, paranoia, perceived criticism) at pseudo-random intervals (three notifications per day, six days per week). Participants could self-initiate use any time. App use was financially incentivised. RESULTS: Participants responded to 47% of app notifications. Most app engagements (87%) were app-initiated rather than self-initiated. Participants engaged most with the voices domain, then paranoia. Age and employment status were significantly associated with overall app engagement. CONCLUSION: Individuals with psychosis engaged well with Actissist, particularly with areas focussing on voice-hearing and paranoia. App-generated reminders successfully prompted app engagement. As financial incentives may have increased app engagement, future studies of non-incentivized engagement in larger samples are needed.

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings.

A promising approach to help students safely return to in person learning is through the application of sentinel cards for accurate high resolution environmental monitoring of SARS-CoV-2 traces indoors. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface materials, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, Wet Wipes, RNase Away) at three different viral loads: "high" (4 × 104 GE/mL), "medium" (1 × 104 GE/mL), and "low" (2.5 × 103 GE/mL). RNase Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet Wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. IMPORTANCE Because SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are a persistent signal or new infectious cases and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning "sentinel cards" to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.

Implementation of Practical Surface SARS-CoV-2 Surveillance in School Settings.

Surface sampling for SARS-CoV-2 RNA detection has shown considerable promise to detect exposure of built environments to infected individuals shedding virus who would not otherwise be detected. Here, we compare two popular sampling media (VTM and SDS) and two popular workflows (Thermo and PerkinElmer) for implementation of a surface sampling program suitable for environmental monitoring in public schools. We find that the SDS/Thermo pipeline shows superior sensitivity and specificity, but that the VTM/PerkinElmer pipeline is still sufficient to support surface surveillance in any indoor setting with stable cohorts of occupants (e.g., schools, prisons, group homes, etc.) and may be used to leverage existing investments in infrastructure. IMPORTANCE The ongoing COVID-19 pandemic has claimed the lives of over 5 million people worldwide. Due to high density occupancy of indoor spaces for prolonged periods of time, schools are often of concern for transmission, leading to widespread school closings to combat pandemic spread when cases rise. Since pediatric clinical testing is expensive and difficult from a consent perspective, we have deployed surface sampling in SASEA (Safer at School Early Alert), which allows for detection of SARS-CoV-2 from surfaces within a classroom. In this previous work, we developed a high-throughput method which requires robotic automation and specific reagents that are often not available for public health laboratories such as the San Diego County Public Health Laboratory (SDPHL). Therefore, we benchmarked our method (Thermo pipeline) against SDPHL's (PerkinElmer) more widely used method for the detection and prediction of SARS-CoV-2 exposure. While our method shows superior sensitivity (false-negative rate of 9% versus 27% for SDPHL), the SDPHL pipeline is sufficient to support surface surveillance in indoor settings. These findings are important since they show that existing investments in infrastructure can be leveraged to slow the spread of SARS-CoV-2 not in just the classroom but also in prisons, nursing homes, and other high-risk, indoor settings.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp.

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

Digital screening for postnatal depression: mixed methods proof-of-concept study.

BACKGROUND: Depression during the postnatal year is prevalent in mothers (17%) and fathers (9%), and suicide is the leading cause of maternal death in this period. Lifelong costs and consequences of untreated postnatal depression (PND) are high due to impacts on infants as well as parents. We aimed to improve access to PND treatment using digital screening. We developed a smartphone app (ClinTouch DAWN-P) that allows parents to monitor their mood daily with the Edinburgh Postnatal Depression Scale (EPDS), uploading responses in real-time to a secure server. We evaluated the app's feasibility, acceptability, validity and safety in a proof-of-concept study. METHODS: Pregnant women (≥ 36 weeks gestation) and partners were recruited from antenatal services and invited to complete daily EPDS assessments via the ClinTouch DAWN-P app until 6 weeks postpartum. Participants completed standard paper-based EPDS at two time points for validity comparisons. We examined app acceptability and usability at 6 weeks postpartum with qualitative interviews, examined using framework analysis, and the abridged Mobile App Rating Scale (convergent mixed methods design). RESULTS: Most (96%) eligible pregnant women approached were keen to try the app. Participating mothers (n = 15) and partners/fathers (n = 8) found the app easy to use, and 91% continued to use it for the full study period. Overall, 67% of daily app-based assessments were completed, with a history of depression predicting lower app usage. Participants suggested modifications to the app and its deployment to improve usability (e.g., extending the response window and including feedback and parenting advice). The validity of app-based responses was confirmed by high agreement with standard EPDS. App-based and paper-based ratings showed perfect agreement in identifying cases of likely PND. There were no serious adverse events relating to app use. CONCLUSIONS: Digital PND screening appears feasible, acceptable, valid and safe. It also benefits from being remotely delivered: we enrolled all participants remotely during the first COVID-19 lockdown. Use of digital screening could address known shortcomings of conventional health visitor-delivered screening such as limited staff time, parental unwillingness to disclose difficulties to a professional, lack of partner/father screening, and language barriers. TRIAL REGISTRATION: The study was prospectively registered (Clinicaltrials.gov: NCT04279093 ).

Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Fear of relapse in schizophrenia: a mixed-methods systematic review.

INTRODUCTION: Fears of relapse in people diagnosed with schizophrenia have long been recognised as an impediment to recovery and wellbeing. However, the extent of the empirical basis for the fear of relapse concept is unclear. A systematic review is required to collate available evidence and define future research directions. METHODS: A pre-registered systematic search (PROSPERO CRD42020196964) of four databases (PubMED, MEDLINE-Ovid, PsycINFO-Ovid, and Cochrane Central Register of Controlled Trials) was conducted from their inception to 05/04/2021. RESULTS: We found nine eligible studies. Five were quantitative (4 descriptive and 1 randomised controlled trial), and four were qualitative. The available quantitative evidence suggests that fear of relapse may have concurrent positive relationships with depression (r = 0.72) and suicide ideation (r = 0.48), and negative relationship with self-esteem (r = 0.67). Qualitative synthesis suggests that fear of relapse is a complex phenomenon with behavioural and emotional components which has both direct and indirect effects on wellbeing. CONCLUSIONS: Evidence in this area is limited and research with explicit service user and carer involvement is urgently needed to develop new and/or refine existing measurement tools, and to measure wellbeing rather than psychopathology. Nonetheless, clinicians should be aware that fear of relapse exists and appears to be positively associated with depression and suicide ideation, and negatively associated with self-esteem. Fear of relapse can include fears of losing personal autonomy and/or social/occupational functioning. It appears to impact carers as well as those diagnosed with schizophrenia.