Sex differences in the prevalence of ADHD are well reported in the literature, with childhood ADHD being diagnosed 7–8 times more frequently in males than females, despite a population sex ratio of 3–4:1. A recent consensus statement argued that ADHD is under-identified and under-diagnosed in the UK, and this is especially concerning with regards to females. This systematic review aims to investigate specific symptoms characterising the manifestation of ADHD in females compared with both males with ADHD and females without ADHD.

A systematic search of eligible studies was conducted using predefined search criteria across six databases (Ovid MEDLINE, Ovid EMBASE, Ovid APA PsycINFO, ProQuest, EBSCO ERIC and EBSCO British Education Index), in line with a registration protocol on PROSPERO. Eligible studies included those with statistical analysis comparing ADHD, impact or co-occurring mental health difficulties at the item level, which compared ADHD symptoms in both sexes, or contrasted females with and without ADHD. Studies that exclusively reported total scores without item-level statistical results were excluded. A total of 5,378 articles were identified in the search and 13 studies met the criteria for inclusion.

Outcomes from 13 studies were analysed thematically. 7 studies looked at ADHD at an item level, while 7 studies explored disparities in impairment or other items. Of the eligible studies, 12 compared males and females with ADHD and 4 compared females with and without ADHD. 7 studies focussed on children with ADHD and 6 on adults. Preliminary results from 3 studies of ADHD symptoms in children indicated sex differences in hyperactive and impulsive symptoms: males were more likely to exhibit symptoms such as fidgeting and difficulty remain seated, while females exhibited higher rates of excessive talking and interrupting. Sex differences in impairment showed mixed results. Females with ADHD endorsed self-reported items related to mind-wandering and parent-reported impairment, including friendship difficulties, more than females without ADHD. Overall, the analysis of the results suggested that most studies do show some sex differences in ADHD and impairment items.

While current studies of individuals diagnosed with ADHD highlight important sex differences, the limited number of direct investigations and predominant focus on total symptoms underscore the need for further research. Item-level analysis of symptoms and their impact is essential in exploring how sex influences the associations between ADHD, risk factors and functional outcomes. Recognising potential sex differences is essential for improving ADHD assessment in females and later life outcomes.

INDUCT (Interdisciplinary Network for Dementia Using Current Technology), and DISTINCT (Dementia Inter-sectorial strategy for training and innovation network for current technology) are two Marie Sklodowska-Curie funded International Training Networks that aimed to develop a multi-disciplinary, inter-sectorial educational research framework for Europe to improve technology and care for people with dementia, and to provide the evidence to show how technology can improve the lives of people with dementia.

In INDUCT (2016-2020) 15 Early Stage Researchers worked on projects in the areas of Technology to support everyday life; technology to promote meaningful activities; and healthcare technology. In DISTINCT (2019-2023) 15 Early Stage Researchers worked on technology to promote Social health in three domains: fulfilling ones potential and obligations in society, managing one’s own life, and participation in social and other meaningful activities.

Both networks adopted three transversal objectives: 1) To determine practical, cognitive and social factors needed to make technology more useable for people with dementia; 2) To evaluate the effectiveness of specific contemporary technology; 3) To trace facilitators and barriers for implementation of technology in dementia care.

The main recommendations resulting from all research projects are integrated in a web-based digital Best Practice Guidance on Human Interaction with Technology in Dementia which was recently updated (Dec 2022 and June 2023) and will be presented at the congress. The recommendations are meant for different target groups, i.e. people in different stages of dementia, their (in)formal carers, policy makers, designers and researchers, who can easily find the recommendations relevant to them in the Best Practice Guidance by means of a digital selection tool.

The INDUCT/DISTINCT Best Practice Guidance informs on how to improve the development, usage, impact and implementation of technology for people with dementia in various technology areas. This Best Practice Guidance is the result of intensive collaborative partnership of INDUCT and DISTINCT with academic and non-academic partners as well as the involvement of representatives of the different target groups throughout the projects.

Primary health care (PHC) supported long-term care facilities (LTCFs) in attending COVID-19 patients. The aim of this study is to describe the role of PHC in LTCFs in Europe during the early phase of the pandemic.

Retrospective descriptive study from 30 European countries using data from September 2020 collected with an ad hoc semi-structured questionnaire. Related variables are SARS-CoV-2 testing, contact tracing, follow-up, additional testing, and patient care.

Twenty-six out of the 30 European countries had PHC involvement in LTCFs during the COVID-19 pandemic. PHC participated in initial medical care in 22 countries, while, in 15, PHC was responsible for SARS-CoV-2 test along with other institutions. Supervision of individuals in isolation was carried out mostly by LTCF staff, but physical examination or symptom’s follow-up was performed mainly by PHC.

PHC has participated in COVID-19 pandemic assistance in LTCFs in coordination with LTCF staff, public health officers, and hospitals.

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.

To review existing publications using Household Consumption and Expenditure Survey (HCES) data to estimate household dietary nutrient supply to (1) describe scope of available literature, (2) identify the metrics reported and parameters used to construct these metrics, (3) summarise comparisons between estimates derived from HCES and individual dietary assessment data and (4) explore the demographic and socio-economic sub-groups used to characterise risks of nutrient inadequacy.

This study is a systematic review of publications identified from online databases published between 2000 to 2019 that used HCES food consumption data to estimate household dietary nutrient supply. Further publications were identified by ‘snowballing’ the references of included database-identified publications.

Publications using data from low- and lower-middle income countries.

In total, fifty-eight publications were included. Three metrics were reported that characterised household dietary nutrient supply: apparent nutrient intake per adult-male equivalent per day (n 35), apparent nutrient intake per capita per day (n 24) and nutrient density (n 5). Nutrient intakes were generally overestimated using HCES food consumption data, with several studies finding sizeable discrepancies compared with intake estimates based on individual dietary assessment methods. Sub-group analyses predominantly focused on measuring variation in household dietary nutrient supply according to socio-economic position and geography.

HCES data are increasingly being used to assess diets across populations. More research is needed to inform the development of a framework to guide the use of and qualified interpretation of dietary assessments based on these data.