Deficits in visuospatial attention, known as neglect, are common following brain injury, but underdiagnosed and poorly treated, resulting in long-term cognitive disability. In clinical settings, neglect is often assessed using simple pen-and-paper tests. While convenient, these cannot characterise the full spectrum of neglect. This protocol reports a research programme that compares traditional neglect assessments with a novel virtual reality attention assessment platform: The Attention Atlas (AA).

The AA was codesigned by researchers and clinicians to meet the clinical need for improved neglect assessment. The AA uses a visual search paradigm to map the attended space in three dimensions and seeks to identify the optimal parameters that best distinguish neglect from non-neglect, and the spectrum of neglect, by providing near-time feedback to clinicians on system-level behavioural performance. A series of experiments will address procedural, scientific, patient, and clinical feasibility domains.

Analyses focuses on descriptive measures of reaction time, accuracy data for target localisation, and histogram-based raycast attentional mapping analysis; which measures the individual’s orientation in space, and inter- and intra-individual variation of visuospatial attention. We will compare neglect and control data using parametric between-subjects analyses. We present example individual-level results produced in near-time during visual search.

The development and validation of the AA is part of a new generation of translational neuroscience that exploits the latest advances in technology and brain science, including technology repurposed from the consumer gaming market. This approach to rehabilitation has the potential for highly accurate, highly engaging, personalised care.

Automated virtual reality therapies are being developed to increase access to psychological interventions. We assessed the experience with one such therapy of patients diagnosed with psychosis, including satisfaction, side effects, and positive experiences of access to the technology. We tested whether side effects affected therapy.

In a clinical trial 122 patients diagnosed with psychosis completed baseline measures of psychiatric symptoms, received gameChange VR therapy, and then completed a satisfaction questionnaire, the Oxford-VR Side Effects Checklist, and outcome measures.

79 (65.8%) patients were very satisfied with VR therapy, 37 (30.8%) were mostly satisfied, 3 (2.5%) were indifferent/mildly dissatisfied, and 1 (0.8%) person was quite dissatisfied. The most common side effects were: difficulties concentrating because of thinking about what might be happening in the room (n = 17, 14.2%); lasting headache (n = 10, 8.3%); and the headset causing feelings of panic (n = 9, 7.4%). Side effects formed three factors: difficulties concentrating when wearing a headset, feelings of panic using VR, and worries following VR. The occurrence of side effects was not associated with number of VR sessions, therapy outcomes, or psychiatric symptoms. Difficulties concentrating in VR were associated with slightly lower satisfaction. VR therapy provision and engagement made patients feel: proud (n = 99, 81.8%); valued (n = 97, 80.2%); and optimistic (n = 96, 79.3%).

Patients with psychosis were generally very positive towards the VR therapy, valued having the opportunity to try the technology, and experienced few adverse effects. Side effects did not significantly impact VR therapy. Patient experience of VR is likely to facilitate widespread adoption.

Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities.

We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases (n = 77) and controls (n = 52) aged 8–18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities.

While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample.

Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.

Adverse drug reactions (ADRs) are associated with increased morbidity, mortality, and resource utilization. Drug interactions (DDIs) are among the most common causes of ADRs, and estimates have cited that up to 22% of patients take interacting medications. DDIs are often due to the propensity for agents to induce or inhibit enzymes responsible for the metabolism of concomitantly administered drugs. However, this phenomenon is further complicated by genetic variants of such enzymes. The aim of this study is to quantify and describe potential drug-drug, drug-gene, and drug-drug-gene interactions in a community-based patient population.

A regional pharmacy with retail outlets in Arkansas provided deidentified prescription data from March 2020 for 4761 individuals. Drug-drug and drug-drug-gene interactions were assessed utilizing the logic incorporated into GenMedPro, a commercially available digital gene-drug interaction software program that incorporates variants of 9 pharmacokinetic (PK) and 2 pharmacodynamic (PD) genes to evaluate DDIs and drug-gene interactions. The data were first assessed for composite drug-drug interaction risk, and each individual was stratified to a risk category using the logic incorporated in GenMedPro. To calculate the frequency of potential drug-gene interactions, genotypes were imputed and allocated to the cohort according to each gene’s frequency in the general population. Potential genotypes were randomly allocated to the population 100 times in a Monte Carlo simulation. Potential drug-drug, gene-drug, or gene-drug-drug interaction risk was characterized as minor, moderate, or major.

Based on prescription data only, the probability of a DDI of any impact (mild, moderate, or major) was 26% [95% CI: 0.248-0.272] in the population. This probability increased to 49.6% [95% CI: 0.484-0.507] when simulated genetic polymorphisms were additionally assessed. When assessing only major impact interactions, there was a 7.8% [95% CI: 0.070-0.085] probability of drug-drug interactions and 10.1% [95% CI: 0.095-0.108] probability with the addition of genetic contributions. The probability of drug-drug-gene interactions of any impact was correlated with the number of prescribed medications, with an approximate probability of 77%, 85%, and 94% in patients prescribed 5, 6, or 7+ medications, respectively. When stratified by specific drug class, antidepressants (19.5%), antiemetics (21.4%), analgesics (16%), antipsychotics (15.6%), and antiparasitics (49.7%) had the highest probability of major drug-drug-gene interaction.

In a community-based population of outpatients, the probability of drug-drug interaction risk increases when genetic polymorphisms are attributed to the population. These data suggest that pharmacogenetic testing may be useful in predicting drug interactions, drug-gene interactions, and severity of interactions when proactively evaluating patient medication profiles.

Genomind, Inc.

Many patients with mental health disorders become increasingly isolated at home due to anxiety about going outside. A cognitive perspective on this difficulty is that threat cognitions lead to the safety-seeking behavioural response of agoraphobic avoidance.

We sought to develop a brief questionnaire, suitable for research and clinical practice, to assess a wide range of cognitions likely to lead to agoraphobic avoidance. We also included two additional subscales assessing two types of safety-seeking defensive responses: anxious avoidance and within-situation safety behaviours.

198 patients with psychosis and agoraphobic avoidance and 1947 non-clinical individuals completed the item pool and measures of agoraphobic avoidance, generalised anxiety, social anxiety, depression and paranoia. Factor analyses were used to derive the Oxford Cognitions and Defences Questionnaire (O-CDQ).

The O-CDQ consists of three subscales: threat cognitions (14 items), anxious avoidance (11 items), and within-situation safety behaviours (8 items). Separate confirmatory factor analyses demonstrated a good model fit for all subscales. The cognitions subscale was significantly associated with agoraphobic avoidance (r = .672, p < .001), social anxiety (r = .617, p < .001), generalized anxiety (r = .746, p < .001), depression (r = .619, p < .001) and paranoia (r = .655, p < .001). Additionally, both the O-CDQ avoidance (r = .867, p < .001) and within-situation safety behaviours (r = .757, p < .001) subscales were highly correlated with agoraphobic avoidance. The O-CDQ demonstrated excellent internal consistency (cognitions Cronbach’s alpha = .93, avoidance Cronbach’s alpha = .94, within-situation Cronbach’s alpha = .93) and test–re-test reliability (cognitions ICC = 0.88, avoidance ICC = 0.92, within-situation ICC = 0.89).

The O-CDQ, consisting of three separate scales, has excellent psychometric properties and may prove a helpful tool for understanding agoraphobic avoidance across mental health disorders.

The use of older data and references is becoming increasingly disfavored for publication. A myopic focus on newer research risks losing sight of important research questions already addressed by now-invisible older studies. This creates a ‘Groundhog Day’ effect as illustrated by the 1993 movie of this name in which the protagonist has to relive the same day (Groundhog Day) over and over and over within a world with no memory of it. This article examines the consequences of the recent preference for newer data and references in current publication practices and is intended to stimulate new consideration of the utility of selected older data and references for the advancement of scientific knowledge.

Examples from the literature are used to exemplify the value of older data and older references. To illustrate the recency of references published in original medical research articles in a selected sample of recent academic medical journals, original research articles were examined in recent issues in selected psychiatry, medicine, and surgery journals.

The literature examined reflected this article's initial assertion that journals are emphasizing the publication of research with newer data and more recent references.

The current valuation of newer data above older data fails to appreciate the fact that new data eventually become old, and that old data were once new. The bias demonstrated in arbitrary policies pertaining to older data and older references can be addressed by instituting comparable treatment of older and newer data and references.

During the SARS-CoV-2 virus pandemic, University Hospital Birmingham NHS Trust Oncology Department incorporated the ultrahypofractionated regime of 26Gy/5 fractions alongside the moderate hypofractionated regime of 40Gy/15 fractions as part of local adjuvant breast radiotherapy treatment (RT) for eligible patients. We conducted a local study to assess the real-life experience of patients undergoing ultrahypofractionated schedule to compare feasibility and toxicity to the fast-forward trial during the COVID − 19 pandemic.

A single institution, retrospective, qualitative study. Patients included had early-stage breast cancer and received adjuvant radiotherapy between 23 March 2020 and 31 May 2020, a total of 211 patients. Inclusion was irrespective of any other neoadjuvant/adjuvant treatments. Data were collected retrospectively for treatment dose, boost dose and toxicity.

Of the total 211 patients, 85 were treated with 26Gy in 5# and 19 patients received a boost as per the fast-forward protocol. Of these 85 patients, 15·9% did not report any skin toxicity post-treatment. 63·5% of patients reported RTOG Grade 1, 15·9% had RTOG Grade 2, and 1·6% reported RTOG Grade 3 skin toxicity. 3·2% of the patients could not be contacted for follow-up. Of the 19 patients who received a breast boost, 10·53% reported no skin changes. 78·9% reported Grade 1 skin toxicity. Both Grades 2a and 2b skin toxicity were reported by 5·26% each. The patient demographics and tumour characteristics in our study cohort were comparable to those within the fast-forward trial. In terms of post-RT skin toxicity, fewer patients reported any toxicity in the UHB patient cohort versus those in the trial, and the number of Grade 2/3 toxicities reported was also low. A delay in toxicity reporting from 2 weeks for 40Gy/15 to 3 weeks for 26Gy/5 was observed.

Our study concluded that offering ultrahypofractionation was convenient for patients; reducing the number of hospital visits during the SARS-CoV-2 virus pandemic appeared safe in terms of acute post-RT-related skin toxicity. The reduced hospital visits limited exposure of patients and staff to the SARS-CoV-2 virus while also ensuring efficient use of Radiotherapy Department resources. Local follow-up protocols have been amended to ensure review at 3 weeks for the 26Gy/5 schedule to acknowledge the delay in acute toxicity development. To date, there is only 5-year toxicity and relapse data available from the fast-forward trial; therefore, hypofractionation schedules should be offered to patients as long as they fulfil the criteria and understand the limitations of the study as well as accelerated peer review processes in the face of the pandemic.

Deliberative processes for health technology assessment (HTA) are intended to facilitate participatory decision making, using discussion and open dialogue between stakeholders. Increasing attention is being given to deliberative processes, but guidance is lacking for those who wish to design or use them. Health Technology Assessment International (HTAi) and ISPOR—The Professional Society for Health Economics and Outcomes Research initiated a joint Task Force to address this gap.

The joint Task Force consisted of fifteen members with different backgrounds, perspectives, and expertise relevant to the field. It developed guidance and a checklist for deliberative processes for HTA. The guidance builds upon the few, existing initiatives in the field, as well as input from the HTA community following an established consultation plan. In addition, the guidance was subject to two rounds of peer review.

A deliberative process for HTA consists of procedures, activities, and events that support the informed and critical examination of an issue and the weighing of arguments and evidence to guide a subsequent decision. Guidance and an accompanying checklist are provided for (i) developing the governance and structure of an HTA program and (ii) informing how the various stages of an HTA process might be managed using deliberation.

The guidance and the checklist contain a series of questions, grouped by six phases of a model deliberative process. They are offered as practical tools for those wishing to establish or improve deliberative processes for HTA that are fit for local contexts. The tools can also be used for independent scrutiny of deliberative processes.