Underrepresentation of diverse populations in medical research undermines generalizability, exacerbates health disparities, and erodes trust in research institutions. This study aimed to identify a suitable survey instrument to measure trust in medical research among Black and Latino communities in Baltimore, Maryland.

Based on a literature review, a committee selected two validated instruments for community evaluation: Perceptions of Research Trustworthiness (PoRT) and Trust in Medical Researchers (TiMRs). Both were translated into Spanish through a standardized process. Thirty-four individuals participated in four focus groups (two in English, two in Spanish). Participants reviewed and provided feedback on the instruments’ relevance and clarity. Discussions were recorded, transcribed, and analyzed thematically.

Initial reactions to the instruments were mixed. While 68% found TiMR easier to complete, 74% preferred PoRT. Key discussion themes included the relevance of the instrument for measuring trust, clarity of the questions, and concerns about reinforcing negative perceptions of research. Participants felt that PoRT better aligned with the research goal of measuring community trust in research, though TiMR was seen as easier to understand. Despite PoRT’s lower reading level, some items were found to be more confusing than TiMR items.

Community feedback highlighted the need to differentiate trust in medical research, researchers, and institutions. While PoRT and TiMR are acceptable instruments for measuring trust in medical research, refinement of both may be beneficial. Development and validation of instruments in multiple languages is needed to assess community trust in research and inform strategies to improve diverse participation in research.

The calcitonin gene-related peptide monoclonal antibodies (CGRP MABs) erenumab, fremanezumab, and galcanezumab are reimbursed in Ireland under the High Tech Arrangement, subject to a managed access protocol (MAP), for the prophylaxis of chronic migraine in adults in whom three or more prophylactic treatments have failed. This study provides an overview of submitted reimbursement applications and the utilization of CGRP MABs.

The MAP for CGRP MABs was introduced on 1 September 2021 and is operated by the Health Service Executive (HSE) Medicines Management Programme. Individual patient reimbursement applications for CGRP MABs submitted through an online reimbursement application system between 1 September 2021 and 30 April 2023 were reviewed. Utilization data from 1 September 2021 to 30 April 2023 were extracted from the HSE Primary Care Reimbursement Service national pharmacy reimbursement claims database for the High Tech Arrangement. Analysis was performed using SAS® 9.4 software.

A total of 1,517 reimbursement applications were submitted in the study period. Reimbursement was approved for 96.1 percent (n=1,458) of the applications. A total of 1,399 individual patients (mean age 45 years) were dispensed a CGRP MAB under the High Tech Arrangement between September 2021 and April 2023, the majority of whom were women (n=1,141). Almost 90 percent of patients were considered treatment adherent. In April 2023, the market share of the individual CGRP MABs on the High Tech Arrangement was 56 percent (n=599) for fremanezumab, 38.3 percent (n=409) for erenumab, and 5.7 percent (n=61) for galcanezumab.

MAPs are part of the health technology management approach to drug reimbursement in the Irish healthcare setting, ensuring that reimbursement is in line with approved subgroups of the licensed indication. Used in conjunction with health technology assessment, MAPs enable access to high-cost drug treatments for patients with the greatest unmet need, while providing budgetary oversight and certainty for the payer.

Increasingly in Ireland, there are specific criteria attached to reimbursement approval for new medicines. Health technology assessment (HTA) identifies where uncertainty is greatest in relation to clinical and cost-effectiveness evidence and budget impact estimates; our health technology management (HTM) approach uses these outputs from HTA to design protocols to manage these uncertainties in the post-reimbursement phase.

A bespoke managed access protocol (MAP) is developed for each medicine reimbursed under this approach, informed by uncertainties highlighted in the HTA, directions from the decision-maker, and relevant particulars arising from commercial negotiations. Individual patient reimbursement applications are submitted via an online application system linked directly to the national pharmacy claims system. Pharmacists review the applications and approve reimbursement support where the patient meets the reimbursement criteria. The process is adaptive, allowing expansion of the criteria to include previously excluded patient cohorts, and the addition of new indications. It can also work across differing reimbursement arrangements (hospital/primary care).

The MAP for liraglutide for weight management confines reimbursement to patients with a body mass index greater than or equal to 35 kg/m², prediabetes, and high risk for cardiovascular disease. Phase I reimbursement support lasts for six months; patients not attaining greater than or equal to five percent weight loss are deemed non-responders as per the HTA, and reimbursement support is discontinued. The MAP for dupilumab confined reimbursement support to adults with refractory moderate-to-severe atopic dermatitis, where cost-effectiveness was plausible in the HTA. The MAP for calcitonin-gene-related-peptides monoclonal antibodies confines reimbursement support to patients with chronic migraine, refractory to at least three prophylactic treatments, where cost-effectiveness was plausible in the HTA.

Across these MAPs, over 3,000 patients accessed novel treatments for chronic illnesses in September 2023. HTM provides an effective mechanism to facilitate access to high-cost medicines for targeted patient groups, while providing increased oversight and budgetary certainty. Key to acceptance is utilization of HTA outputs to implement evidence-based HTM measures targeting specific uncertainties as highlighted in the HTA report.

Black and Latino individuals are underrepresented in COVID-19 treatment and vaccine clinical trials, calling for an examination of factors that may predict willingness to participate in trials.

We administered the Common Survey 2.0 developed by the Community Engagement Alliance (CEAL) Against COVID-19 Disparities to 600 Black and Latino adults in Baltimore City, Prince George’s County, Maryland, Montgomery County, Maryland, and Washington, DC, between October and December 2021. We examined the relationship between awareness of clinical trials, social determinants of health challenges, trust in COVID-19 clinical trial information sources, and willingness to participate in COVID-19 treatment and vaccine trials using multinomial regression analysis.

Approximately half of Black and Latino respondents were unwilling to participate in COVID-19 treatment or vaccine clinical trials. Results showed that increased trust in COVID-19 clinical trial information sources and trial awareness were associated with greater willingness to participate in COVID-19 treatment and vaccine trials among Black and Latino individuals. For Latino respondents, having recently experienced more challenges related to social determinants of health was associated with a decreased likelihood of willingness to participate in COVID-19 vaccine trials.

The willingness of Black and Latino adults to participate in COVID-19 treatment and vaccine clinical trials is influenced by trial awareness and trust in trial information sources. Ensuring the inclusion of these communities in clinical trials will require approaches that build greater awareness and trust.

While loss of insight into one’s cognitive impairment (anosognosia) is a feature in Alzheimer’s disease dementia, less is known about memory self-awareness in cognitively unimpaired (CU) older adults or mild cognitive impairment (MCI) or factors that may impact self-awareness. Locus of control, specifically external locus of control, has been linked to worse cognitive/health outcomes, though little work has examined locus of control as it relates to self-awareness of memory functioning or across cognitive impairment status. Therefore, we examined associations between locus of control and memory self-awareness and whether MCI status impacted these associations.

Participants from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (mean age=73.51; 76% women; 26% Black/African American) were classified as CU (n=2177) or MCI (amnestic n=313; non-amnestic n=170) using Neuropsychological Criteria. A memory composite score measured objective memory performance and the Memory Functioning Questionnaire measured subjective memory. Memory self-awareness was defined as objective memory minus subjective memory, with positive values indicating overreporting of memory difficulties relative to actual performance (hypernosognosia) and negative values indicating underreporting (hyponosognosia). Internal (i.e., personal skills/attributes dictate life events) and external (i.e., environment/others dictate life events) locus of control scores came from the Personality in Intellectual Aging Contexts Inventory. General linear models, adjusting for age, education, sex/gender, depressive symptoms, general health, and vocabulary examined the effects of internal and external locus of control on memory self-awareness and whether MCI status moderated these associations.

Amnestic and non-amnestic MCI participants reported lower internal and higher external locus of control than CU participants. There was a main effect of MCI status on memory self-awareness such that amnestic MCI participants showed the greatest degree of hyponosognosia/underreporting, followed by non-amnestic MCI, and CU participants slightly overreported their memory difficulties. While, on average, participants were fairly accurate at reporting their degree of memory difficulty, internal locus of control was negatively associated with self-awareness such that higher internal locus of control was associated with greater underreporting (ß=-.127, 95% CI [-.164, -.089], p<.001). MCI status did not moderate this association. External locus of control was positively associated with self-awareness such that higher external locus of control was associated with greater hypernosonosia/overreporting (ß=.259, 95% CI [.218, .300], p<.001). Relative to CU, amnestic, but not non-amnestic, MCI showed a stronger association between external locus of control and memory self-awareness. Specifically, higher external locus of control was associated with less underreporting of cognitive difficulties in amnestic MCI (ß=.107, 95% CI [.006, .208], p=.038).

In CU participants, higher external locus of control was associated with greater hypernosognosia/overreporting. In amnestic MCI, the lower external locus of control associations with greater underreporting of objective cognitive difficulties suggests that perhaps reduced insight in some people with MCI may result in not realizing the need for external supports, and therefore not asking for help from others. Alternatively, in amnestic participants with greater external locus of control, perhaps the environmental cues/feedback translate to greater accuracy in their memory self-perceptions. Longitudinal analyses are needed to determine how memory self-awareness is related to future cognitive declines.

This national pre-pandemic survey compared demand and capacity of adult community eating disorder services (ACEDS) with NHS England (NHSE) commissioning guidance.

Thirteen services in England and Scotland responded (covering 10.7 million population). Between 2016–2017 and 2019–2020 mean referral rates increased by 18.8%, from 378 to 449/million population. Only 3.7% of referrals were from child and adolescent eating disorder services (CEDS-CYP), but 46% of patients were aged 18–25 and 54% were aged >25. Most ACEDS had waiting lists and rationed access. Many could not provide full medical monitoring, adapt treatment for comorbidities, offer assertive outreach or provide seamless transitions. For patient volume, the ACEDS workforce budget was 15%, compared with the NHSE workforce calculator recommendations for CEDS-CYP. Parity required £7 million investment/million population for the ACEDS.

This study highlights the severe pressure in ACEDS, which has increased since the COVID-19 pandemic. Substantial investment is required to ensure NHS ACEDS meet national guidance, offer evidence-based treatment, reduce risk and preventable deaths, and achieve parity with CEDS-CYP.

Children with CHD are at risk for neurodevelopmental delays, and length of hospitalisation is a predictor of poorer long-term outcomes. Multiple aspects of hospitalisation impact neurodevelopment, including sleep interruptions, limited holding, and reduced developmental stimulation. We aimed to address modifiable factors by creating and implementing an interdisciplinary inpatient neurodevelopmental care programme in our Heart Institute.

In this quality improvement study, we developed an empirically supported approach to neurodevelopmental care across the continuum of hospitalisation for patients with CHD using three plan-do-study-act cycles. With input from multi-level stakeholders including parents/caregivers, we co-designed interventions that comprised the Cardiac Inpatient Neurodevelopmental Care Optimization (CINCO) programme. These included medical/nursing orders for developmental care practices, developmental kits for patients, bedside developmental plans, caregiver education and support, developmental care rounds, and a specialised volunteer programme. We obtained data from the electronic health record for patients aged 0–2 years admitted for at least 7 days to track implementation.

There were 619 admissions in 18 months. Utilisation of CINCO interventions increased over time, particularly for the medical/nursing orders and caregiver handouts. The volunteer programme launch was delayed but grew rapidly and within six months, provided over 500 hours of developmental interaction with patients.

We created and implemented a low-cost programme that systematised and expanded upon existing neurodevelopmental care practices in the cardiac inpatient units. Feasibility was demonstrated through increasing implementation rates over time. Key takeaways include the importance of multi-level stakeholder buy-in and embedding processes in existing clinical workflows.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.