Mild cognitive impairment with Lewy bodies (MCI-LB) may be identified prospectively based on the presence of cognitive impairment and several core clinical features (visual hallucinations, cognitive fluctuations, parkinsonism, and REM sleep behavior disorder). MCI-LB may vary in its presenting features, which may reflect differences in underlying pathological pattern, severity, or comorbidity.

We aimed to assess how clinical features of MCI-LB accumulate over time, and whether this is associated with the rate of cognitive decline.

In this cohort study, 74 individuals seen with MCI-LB prospectively underwent repeated annual cognitive and clinical assessment up to nine years. Relationships between clinical features (number of core features present and specific features present) and cognitive change on the Addenbrooke’s Cognitive Examination–Revised (ACE-R) were examined with time-varying mixed models. The accumulation of core clinical features over time was examined with a multi-state Markov model.

When an individual with MCI-LB endorsed more clinical features, they typically experienced a faster cognitive decline (ACE-R Score Difference β = −1.1 [−1.7 to −0.5]), specifically when experiencing visual hallucinations (β = −2.1 [−3.5 to −0.8]) or cognitive fluctuations (β = −3.4 [−4.8 to −2.1]).

Individuals with MCI-LB typically acquired more clinical features with the passage of time (25.5% [20.0–32.0%] one-year probability), limiting the prognostic utility of baseline-only features.

The clinical presentation of MCI-LB may evolve over time. The accumulation of more clinical features of Lewy body disease, in particular visual hallucinations and cognitive fluctuations, may be associated with a worse prognosis in clinical settings.

Sleep problems are common among people with psychosis. Research suggests poor sleep is causally related to psychosis, anxiety and depression.

This review investigates the effectiveness and acceptability of cognitive–behavioural therapy (CBT) in targeting sleep problems in people with and at risk of psychosis.

Four databases were searched in line with PRISMA guidelines. Eligible studies either evaluated (a) CBT targeting sleep problems in people with or at risk of psychosis, or (b) subjective experiences of this treatment. Articles not published in peer-review journals were excluded. Treatment effectiveness was investigated for sleep, psychosis and other clinical outcomes. Acceptability was evaluated using qualitative data, drop-out rates, adverse events and relevant questionnaires. Adaptations to standard treatment protocols were described. Research quality was appraised using Cochrane Risk of Bias tools for randomised and non-randomised trials, and a checklist was developed for qualitative papers.

Of the 975 records identified, 14 were eligible. The most common CBT target was insomnia. Treatment protocols were typically adapted by omitting sleep restriction. Large effect sizes were reported for sleep outcomes; however, effects for other clinical outcomes were less clear. Qualitative data and acceptability outcomes suggest that treatment was received positively by participants.

CBT is an effective and acceptable treatment for sleep problems in people with and at risk of psychosis. However, our conclusions are limited by few good-quality studies and small samples. Further gold-standard research is required to inform evidence-based guidelines.

This study aims to identify fathers’ profiles integrating food parenting practices (FPP) and physical activity parenting practices (PAPP).

We analysed cross-sectional data. The fathers completed the reduced FPP and PAPP item banks and socio-demographic and family dynamics (co-parenting and household responsibility) questionnaires. We identified fathers’ profiles via latent profile analysis. We explored the influence of social determinants, child characteristics and family dynamics on fathers’ profiles using multinomial logistic regression.

Online survey in the USA.

Fathers of 5–11-year-old children.

We analysed data from 606 fathers (age = 38 ± 8·0; Hispanic = 37·5 %). Most fathers self-identified as White (57·9 %) or Black/African American (17·7 %), overweight (41·1 %) or obese (34·8 %); attended college (70 %); earned > $47 000 (62·7 %); worked 40 hrs/week (63·4 %) and were biological fathers (90·1 %). Most children (boys = 55·5 %) were 5–8 years old (65·2 %). We identified five fathers’ profiles combining FPP and PAPP: (1) Engaged Supporter Father (n 94 (15·5 %)); (2) Leveled Father (n 160 (26·4 %)); (3) Autonomy-Focused Father (n 117 (19·3 %)); (4) Uninvolved Father (n 113 (18·6 %)) and (5) Control-Focused Father (n 122 (20·1 %)). We observed significant associations with race, ethnicity, child characteristics, co-parenting and household responsibility but not with education level, annual income or employment status. We observed significant pairwise differences between profiles in co-parenting and household responsibility, with the Engaged Supporter Father presenting higher scores in both measures.

Understanding how fathers’ FPP and PAPP interact can enhance assessments for a comprehensive understanding of fathers’ influences on children’s health. Recognising the characteristics and differences among fathers’ profiles may enable tailored interventions, potentially improving children’s health trajectories.

Early intervention in psychosis (EIP) services improve outcomes for young people, but approximately 30% disengage.

To test whether a new motivational engagement intervention would prolong engagement and whether it was cost-effective.

We conducted a multicentre, single-blind, parallel-group, cluster randomised controlled trial involving 20 EIP teams at five UK National Health Service (NHS) sites. Teams were randomised using permuted blocks stratified by NHS trust. Participants were all young people (aged 14–35 years) presenting with a first episode of psychosis between May 2019 and July 2020 (N = 1027). We compared the novel Early Youth Engagement (EYE-2) intervention plus standardised EIP (sEIP) with sEIP alone. The primary outcome was time to disengagement over 12–26 months. Economic outcomes were mental health costs, societal costs and socio-occupational outcomes over 12 months. Assessors were masked to treatment allocation for primary disengagement and cost-effectiveness outcomes. Analysis followed intention-to-treat principles. The trial was registered at ISRCTN51629746.

Disengagement was low at 15.9% overall in standardised stand-alone services. The adjusted hazard ratio for EYE-2 + sEIP (n = 652) versus sEIP alone (n = 375) was 1.07 (95% CI 0.76–1.49; P = 0.713). The health economic evaluation indicated lower mental healthcare costs linked to reductions in unplanned mental healthcare with no compromise of clinical outcomes, as well as some evidence for lower societal costs and more days in education, training, employment and stable accommodation in the EYE-2 group.

We found no evidence that EYE-2 increased time to disengagement, but there was some evidence for its cost-effectiveness. This is the largest study to date reporting positive engagement, health and cost outcomes in a total EIP population sample. Limitations included high loss to follow-up for secondary outcomes and low completion of societal and socio-occupational data. COVID-19 affected fidelity and implementation. Future engagement research should target engagement to those in greatest need, including in-patients and those with socio-occupational goals.

We aimed to co-design an intervention optimising the benefits of online arts and culture for mental health in young people for subsequent testing in a trial. Co-design followed the double diamond phases of design, discover, define, develop and deliver.

Navigating the views of all co-designers to produce a testable resource demanded in-depth understanding, and frequent iterations in multiple modalities of the theoretical basis of the intervention, amplification of youth voice and commitment to a common goal.

Co-design with a broad range of collaborators with a shared vision was valued by young co-designers and produced an effective intervention. Co-design allowed the theoretical basis to be followed and refined to create an engaging, practical and testable web experience, aiming to optimise the mental health benefits of online arts and culture for young people in a randomised controlled trial.

Terrorist incidents lead to a range of mental health outcomes for people affected, sometimes extending years after the event. Secondary stressors can exacerbate them, and social support can provide mitigation and aid recovery. There is a need to better understand distress and mitigating factors among survivors of the Manchester Arena attack in 2017.

We explored three questions. First, what experiences of distress did participants report? Second, how might secondary stressors have influenced participants’ psychosocial recoveries? Third, what part has social support played in the relationships between distress and participants’ recovery trajectories?

We conducted a cross-sectional online survey of a convenience sample of survivors of the Manchester Arena bombing (N = 84) in January 2021 (3 years 8 months post-incident), and a longitudinal study of the same participants’ scores on mental health measures over 3 years from September 2017.

Survivors’ mental well-being scores in early 2021 were significantly lower than general population norms. Longitudinal follow-up provided evidence of enduring distress. Secondary stressors, specifically disruptions to close relationships, were associated with greater post-event distress and slower recovery. We found an indirect relationship between identifying with, and receiving support from, others present at the event and mental well-being >3 years later.

The Arena attack has had an enduring impact on mental health, even in survivors who had a mild response to the event. The quality of close relationships is pivotal to long-term outcome. Constructive support from family and friends, and people with shared experiences, are key to social cure processes that facilitate coping and recovery.

The objective of this research was to evaluate managed access policy in England, drawing upon the expertise of a range of stakeholders involved in its implementation.

Seven focus groups were conducted with payer and health technology assessment representatives, clinicians, and representatives from industry and patient/carer organizations within England. Transcripts were analyzed using framework analysis to identify stakeholders’ views on the successes and challenges of managed access policy.

Stakeholders discussed the many aims of managed access within the National Health Service in England, and how competing aims had affected decision making. While stakeholders highlighted a number of priorities within eligibility criteria for managed access agreements (MAAs), stakeholders agreed that strict eligibility criteria would be challenging to implement due to the highly variable nature of innovative technologies and their indications. Participants highlighted challenges faced with implementing MAAs, including evidence generation, supporting patients during and after the end of MAAs, and agreeing and reinforcing contractual agreements with industry.

Managed access is one strategy that can be used by payers to resolve uncertainty for innovative technologies that present challenges for reimbursement and can also deliver earlier access to promising technologies for patients. However, participants cautioned that managed access is not a “silver bullet,” and there is a need for greater clarity about the aims of managed access and how these should be prioritized in decision making. Discussions between key stakeholders involved in managed access identified challenges with implementing MAAs and these experiences should be used to inform future managed access policy.

Early access schemes (EASs) are approaches used by payers to balance and facilitate earlier patient access to innovative health technologies while evidence generation is ongoing. Schemes require investment from payers and are associated with significant risk since not all technologies will be routinely reimbursed. The purpose of this study was to gain the perspectives of policy experts about the key challenges for EASs and potential solutions for their optimal design and implementation.

Two virtual workshops were convened including (i) UK-based policy experts (England, Wales, and Scotland) and (ii) representatives from multiple healthcare systems (England, France, Sweden, Canada, Poland, and Norway). Participants were encouraged to share their experiences with EASs in their healthcare system and highlight key challenges for policy makers. Discussions were transcribed and analyzed using framework analysis.

Participants agreed that EASs have value when targeted toward innovative technologies with the potential for significant clinical benefit in an area of high unmet need. Participants discussed potential solutions to the challenges faced by payers implementing EASs, including defining eligibility criteria, supporting evidence generation, and approaches to reimbursement.

Participants agreed that EASs are one possible solution for their healthcare systems and have the potential to deliver significant clinical value to patients. However, widespread adoption of EASs is limited due to concerns about the risks for patients and healthcare budgets, further solutions are needed to deliver EASs for targeted therapies.

To describe national antibiotic prescribing for acute gastroenteritis (AGE).

Ambulatory care.

We included visits with diagnoses for bacterial and viral gastrointestinal infections from the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey (NAMCS/NHAMCS; 2006–2015) and the IBM Watson 2014 MarketScan Commercial Claims and Encounters Database. For NAMCS/NHAMCS, we calculated annual percentage estimates and 99% confidence intervals (CIs) of visits with antibiotics prescribed; sample sizes were too small to calculate estimates by pathogen. For MarketScan, we used Poisson regression to calculate the percentage of visits with antibiotics prescribed and 95% CIs, including by pathogen.

We included 10,210 NAMCS/NHAMCS AGE visits; an estimated 13.3% (99% CI, 11.2%–15.4%) resulted in antibiotic prescriptions, most frequently fluoroquinolones (28.7%; 99% CI, 21.1%–36.3%), nitroimidazoles (20.2%; 99% CI, 14.0%–26.4%), and penicillins (18.9%; 99% CI, 11.6%–26.2%). In NAMCS/NHAMCS, antibiotic prescribing was least frequent in emergency departments (10.8%; 99% CI, 9.5%–12.1%). Among 1,868,465 MarketScan AGE visits, antibiotics were prescribed for 13.8% (95% CI, 13.7%−13.8%), most commonly for Yersinia (46.7%; 95% CI, 21.4%–71.9%), Campylobacter (44.8%; 95% CI, 41.5%–48.1%), Shigella (39.7%; 95% CI, 35.9%–43.6%), typhoid or paratyphoid fever (32.7%; (95% CI, 27.2%–38.3%), and nontyphoidal Salmonella (31.7%; 95% CI, 29.5%–33.9%). Antibiotics were prescribed for 12.3% (95% CI, 11.7%–13.0%) of visits for viral gastroenteritis.

Overall, ∼13% of AGE visits resulted in antibiotic prescriptions. Antibiotics were unnecessarily prescribed for viral gastroenteritis and some bacterial infections for which antibiotics are not recommended. Antibiotic stewardship assessments and interventions for AGE are needed in ambulatory settings.

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.

Impaired olfaction may be a biomarker for early Lewy body disease, but its value in mild cognitive impairment with Lewy bodies (MCI-LB) is unknown. We compared olfaction in MCI-LB with MCI due to Alzheimer’s disease (MCI-AD) and healthy older adults. We hypothesized that olfactory function would be worse in probable MCI-LB than in both MCI-AD and healthy comparison subjects (HC).

Cross-sectional study assessing olfaction using Sniffin’ Sticks 16 (SS-16) in MCI-LB, MCI-AD, and HC with longitudinal follow-up. Differences were adjusted for age, and receiver operating characteristic (ROC) curves were used for discriminating MCI-LB from MCI-AD and HC.

Participants were recruited from Memory Services in the North East of England.

Thirty-eight probable MCI-LB, 33 MCI-AD, 19 possible MCI-LB, and 32HC.

Olfaction was assessed using SS-16 and a questionnaire.

Participants with probable MCI-LB had worse olfaction than both MCI-AD (age-adjusted mean difference (B) = 2.05, 95% CI: 0.62–3.49, p = 0.005) and HC (B = 3.96, 95% CI: 2.51–5.40, p < 0.001). The previously identified cutoff score for the SS-16 of ≤ 10 had 84% sensitivity for probable MCI-LB (95% CI: 69–94%), but 30% specificity versus MCI-AD. ROC analysis found a lower cutoff of ≤ 7 was better (63% sensitivity for MCI-LB, with 73% specificity vs MCI-AD and 97% vs HC). Asking about olfactory impairments was not useful in identifying them.

MCI-LB had worse olfaction than MCI-AD and normal aging. A lower cutoff score of ≤ 7 is required when using SS-16 in such patients. Olfactory testing may have value in identifying early LB disease in memory services.

The present study aimed to clarify the neuropsychological profile of the emergent diagnostic category of Mild Cognitive Impairment with Lewy bodies (MCI-LB) and determine whether domain-specific impairments such as in memory were related to deficits in domain-general cognitive processes (executive function or processing speed).

Patients (n = 83) and healthy age- and sex-matched controls (n = 34) underwent clinical and imaging assessments. Probable MCI-LB (n = 44) and MCI-Alzheimer’s disease (AD) (n = 39) were diagnosed following National Institute on Aging-Alzheimer’s Association (NIA-AA) and dementia with Lewy bodies (DLB) consortium criteria. Neuropsychological measures included cognitive and psychomotor speed, executive function, working memory, and verbal and visuospatial recall.

MCI-LB scored significantly lower than MCI-AD on processing speed [Trail Making Test B: p = .03, g = .45; Digit Symbol Substitution Test (DSST): p = .04, g = .47; DSST Error Check: p < .001, g = .68] and executive function [Trail Making Test Ratio (A/B): p = .04, g = .52] tasks. MCI-AD performed worse than MCI-LB on memory tasks, specifically visuospatial (Modified Taylor Complex Figure: p = .01, g = .46) and verbal (Rey Auditory Verbal Learning Test: p = .04, g = .42) delayed recall measures. Stepwise discriminant analysis correctly classified the subtype in 65.1% of MCI patients (72.7% specificity, 56.4% sensitivity). Processing speed accounted for more group-associated variance in visuospatial and verbal memory in both MCI subtypes than executive function, while no significant relationships between measures were observed in controls (all ps > .05)

MCI-LB was characterized by executive dysfunction and slowed processing speed but did not show the visuospatial dysfunction expected, while MCI-AD displayed an amnestic profile. However, there was considerable neuropsychological profile overlap and processing speed mediated performance in both MCI subtypes.