Health Research Research Articles

Factors associated with human papillomavirus infections among women living with HIV in public health facilities in Western Oromia, Ethiopia

BackgroundHuman Papillomavirus infection (HPV) is among the most common sexually transmitted infections with the highest incidence and prevalence worldwide. HPV has been established as the main cause of cervical cancer and remains a public health problem globally. In Western Oromia, Ethiopia cervical screening remains a major issue because of limited resources, and shortage of HPV testing technology. As a result, the prevalence of HPV and associated factors remain unknown among HIV-positive women. This study aimed to assess the prevalence of HPV and associated factors among women living with HIV attending Antiretroviral Therapy (ART) services in public health facilities of East Wollega and West Showa Zones, Ethiopia, 2022.MethodUsing a cross-sectional study design, a total of 415 women ≥ 18 years old were enrolled using systematic random sampling from five public health facilities. Cervical specimens were collected by a trained nurse from April 01 2022, to May 30, 2022, and tested at Nekemte Public Health Research and Referral Molecular Biology, a certified/accredited laboratory for HPV-DNA Polymerase Chain Reaction by expertise using Abbott m2000rt-PCR assays. Finally, Epi data version 4.6 was used for data entry and SPSS version 24.0 were used for data cleaning and analysis, and frequencies and prevalence of HPV were computed. Variables were identified using the multivariable model and statistically significant associations of variables were determined based on the adjusted odds ratio (AOR) with its 95% CI and P-value < 0.05 to determine the strength of association.ResultThe prevalence of HPV was 30.4% [95% CI: 26.0, 34.9]. Of HPV-infected women, 11.9% were positive for HPV-16, 9.5% for HPV-18, and 65.9% were positive for other hr-HPV . The odds of HPV infection among women aged beyond 48 years are 2.85 times the odds of HPV among people who were aged 18–27(AOR = 2.85, 95% CI: 1.16, 5.58). The odds of HPV infection among women who had three or more sexual partners is 4.12 times the odds of HPV infection among women with a single sexual partner(AOR = 4.12, 95% CI: 2.34–8.62). The odds of HPV infection among women who didn’t use condom during sexual intercourse are 4.73 times the odds of HPV among women who used condom during sexual intercourse. (AOR = 4.73, 95% CI: 1.98–9.33). The odds of HPV infection among women who had history of is 4.52 times the odds of HPV infection among women with no history of abortion. [AOR = 4.52, 95% CI: 2.04, 6.89] The odds of HPV infection among women with history of Sexually Transmitted Infection (STI) 3.62 times the odds of HPV among women with no history of STI (AOR = 3.62, 95%CI: 1.75, 5.83). The odd of HPV among women with abnormal vaginal discharge is 3.31 times the odds of the disease among women with normal vaginal discharge [AOR = 3.31, 95% CI: 2.87,7.35).Conclusion and recommendationThe prevalence of HPV infection among HIV-infected women was high in the study area. Given the above-associated factors, we recommend that the stakeholders integrate HPV prevention strategies into HIV /AIDS services. Furthermore, the study has provided essential information about the HIV link with hr-HPV infections, which may explain the high prevalence among HIV-infected women. This can contribute to policy development and planning of prevention strategies incorporating HPV infection prevention especially among youth and HIV-infected people.

Care settings of transient ischemic attack in the United States: A cohort study from the TriNetX health research network

BackgroundEvaluation and hospitalization rates after a transient ischemic attack (TIA)-like presentation vary widely in clinical practice. This study aimed to examine variations in care settings at initial TIA diagnosis in the United States. MethodsWe retrospectively analyzed an adult cohort with a first TIA principal diagnosis between January 1, 2015, and December 31, 2019, from TriNetX Diamond Network. Care settings at TIA diagnosis were defined as hospital care (including inpatient services and observation unit care without admission) and outpatient care (including any outpatient or emergency department visits). We estimated the distribution of care settings at TIA diagnosis and examined the associations of the hospital care setting with baseline age, sex, race, ethnicity, region, and stroke history. ResultsAmong the 554,315 included patients, 38.8% received hospital care at their initial TIA diagnosis. A higher percentage of hospital care was observed in the age group of 50-64 years (40.3%), Black (46.0%), Hispanic (41.2%), South (40.9%), and Midwest (43.0%) Regions, and with a history of stroke (39.6%). Multivariable logistic regression consistently showed patients who were aged 50-64 years (Odds Ratio=1.09, 95% CI: [1.07, 1.11]), Black (1.28, [1.24, 1.32]), Hispanic (1.13, [1.09, 1.18]), from South (1.20, [1.18, 1.22]) and Midwest Region (1.33, [1.30, 1.35]), and had a history of stroke (1.02, [1.00, 1.04]) to more likely receive hospital care. ConclusionsAlthough there are TIA care disparities based on demographics, most patients with initial TIA received acute care in outpatient settings. It is imperative to ensure primary providers can risk-stratify TIA patients and provide rapid and proper management.

Building Bridges for Federated Learning in Healthcare: Review on Approaches for Common Data Model Development.

Common data models provide a standardized way to represent data used in federated learning tasks. The aim of this review was to explore the development and use of common data models to harmonize electronic health record data in health research. The data search yielded 724 records, of which 19 were included for this study. None of the research focused on nursing specific topics. All studies either utilized the Observational Medical Outcomes Partnership (OMOP) common data model, or developed a model partly based on the OMOP. A roadmap to guide research for the development of common data models for federated learning are warranted.

Mental health preparedness and response to epidemics focusing on COVID-19 pandemic: a qualitative study in Iran

BackgroundDuring epidemics, the number of individuals whose mental health is affected is greater than those affected by the infection itself. This is because psychological factors have a direct relationship with the primary causes of the disease and mortality worldwide. Therefore, an increasing investment in research and strategic actions for mental health is essential globally, given the prevalence of infectious diseases.The aim of this study was to elucidate and describe the strategies for mental health preparedness and response during epidemics, with a focus on the COVID-19 pandemic in Iran.MethodsA qualitative study was conducted in Iran from 2022 to 2023. Purposeful Sampling was employed, continuing until data saturation was achieved. Data collection involved semi-structured interviews and observational notes with 20 managers and experts possessing expertise, experience, and knowledge in mental health. Ultimately, the participants' opinions, based on their experiences, were analyzed using the qualitative content analysis method with a conventional approach, resulting in the categorization of data into codes, subcategories, and categories.ResultsThe study revealed participants' opinions and experiences, categorized into two overarching categories: Preparedness, Policy-Making, and Planning Strategies (with four subcategories), and Response Strategies (comprising thirteen subcategories).ConclusionThe opinions and experiences of managers and experts in this study revealed that an appropriate mental health response during pandemics requires preparedness before the occurrence of such crises and the implementation of suitable response strategies after the occurrence. Managers, policymakers, and decision-makers in this field should pay attention to the solutions derived from the experiences of such crises to respond more preparedly in the future.

Omaha System: An Integrative Literature Review from 2012 to 2022.

The Omaha System has been providing a useful clinical documentation structure for health practice, education, and research since 1975. To understand its current applications, we updated a literature review from 2013, using the same descriptors ('Omaha System') which resulted in 559 documents. After applying filters and different forms of screening, 35 papers published from 2012 to 2022 composed the final sample for the review. From its critical analysis we realized that the Omaha System is still a valuable tool for the evaluation of health care outcomes in a variety of settings. Its benefits include promoting communication, supporting evidence-based dec;ision-making, and improving the quality of care and it is interoperable with other classifications and terminologies in healthcare. The use of the Omaha System still enables a consistent integration between patient, community, and health professionals, ensuring the collection and analysis of data that contributes to holistic care in a multidisciplinary approach.

The Placebo Effect in Exercise and Mental Health Research.

This chapter describes the placebo effect in the context of physical activity and mental health. Following a brief historical overview, definitions for placebos, placebo effects, and related terminology are discussed. Next, three major methodological challenges posed from studying the placebo effect in the context of exercise are described. Additionally, the role of a primary psychological mechanism of placebo and nocebo effects - expectations - will be summarized through the lens of key terminology. Findings from relevant chronic and acute exercise studies that have measured or manipulated exercise-associated expectations will be presented. The chapter concludes with recommendations for controlling or quantifying the placebo effect in exercise and mental health research and its implications in clinical practice.

Obesity in urban Indonesia: evidence from the 2007 and 2018 Basic Health Research

BACKGROUND The prevalence of obesity in urbanizing Indonesia is rising, where the double burden of malnutrition poses a significant challenge. This study aimed to examine the prevalence and increment of obesity-related noncommunicable diseases (NCDs) of diabetes and hypertension. METHODS Secondary data from the latest 2018 Basic Health Research (RISKESDAS) were used to analyze the obesity rate and its associations with lifestyle, sociodemographics, and certain comorbidities among urban Indonesians. This study included non-pregnant adults aged ≥18 years who lived in the urban area and whose blood pressure and glucose levels were measured in the survey. Results were compared to a similar study using data from 2007. RESULTS The proportion of obesity among Indonesia’s urban population was more than doubled from 23.0% in 2007 to 50.1% in 2018 for obesity and 28.0% to 57.2% for central obesity. Additionally, females, individuals with higher socioeconomic status, and higher education levels exhibited a higher obesity prevalence. CONCLUSIONS Urban Indonesia has witnessed a dramatic rise in obesity prevalence. Our findings highlighted the urgent need for policymakers to consider the escalating prevalence of NCDs associated with obesity. Strengthening and concretizing health promotion and prevention policies at the community level are crucial to combat this alarming public health challenge.

Using natural language processing to facilitate the harmonisation of mental health questionnaires: a validation study using real-world data

BackgroundPooling data from different sources will advance mental health research by providing larger sample sizes and allowing cross-study comparisons; however, the heterogeneity in how variables are measured across studies poses a challenge to this process.MethodsThis study explored the potential of using natural language processing (NLP) to harmonise different mental health questionnaires by matching individual questions based on their semantic content. Using the Sentence-BERT model, we calculated the semantic similarity (cosine index) between 741 pairs of questions from five questionnaires. Drawing on data from a representative UK sample of adults (N = 2,058), we calculated a Spearman rank correlation for each of the same pairs of items, and then estimated the correlation between the cosine values and Spearman coefficients. We also used network analysis to explore the model’s ability to uncover structures within the data and metadata.ResultsWe found a moderate overall correlation (r = .48, p < .001) between the two indices. In a holdout sample, the cosine scores predicted the real-world correlations with a small degree of error (MAE = 0.05, MedAE = 0.04, RMSE = 0.064) suggesting the utility of NLP in identifying similar items for cross-study data pooling. Our NLP model could detect more complex patterns in our data, however it required manual rules to decide which edges to include in the network.ConclusionsThis research shows that it is possible to quantify the semantic similarity between pairs of questionnaire items from their meta-data, and these similarity indices correlate with how participants would answer the same two items. This highlights the potential of NLP to facilitate cross-study data pooling in mental health research. Nevertheless, researchers are cautioned to verify the psychometric equivalence of matched items.

Researchers' perceptions of the trustworthiness, for reuse purposes, of government health data in Victoria, Australia: Implications for policy and practice.

In 2022 the Australian Data Availability and Transparency Act (DATA) commenced, enabling accredited "data users" to access data from "accredited data service providers." However, the DATA Scheme lacks guidance on "trustworthiness" of the data to be utilised for reuse purposes. Objectives: To determine: (i) Do researchers using government health datasets trust the data? (ii) What factors influence their perceptions of data trustworthiness? and (iii) What are the implications for government and data custodians? Method: Authors of published studies (2008-2020) that utilised Victorian government health datasets were surveyed via a case study approach. Twenty-eight trust constructs (identified via literature review) were grouped into data factors, management properties and provider factors. Results: Fifty experienced health researchers responded. Most (88%) believed that Victorian government health data were trustworthy. When grouped, data factors and management properties were more important than data provider factors in building trust. The most important individual trust constructs were: "compliant with ethical regulation" (100%) and "monitoring privacy and confidentiality" (98%). Constructs of least importance were knowledge of "participant consent" (56%) and "major focus of the data provider was research" (50%). Conclusion: Overall, the researchers trusted government health data, but data factors and data management properties were more important than data provider factors in building trust. Implications: Government should ensure the DATA Scheme incorporates mechanisms to validate those data utilised by accredited data users and data providers have sufficient quality (intrinsic and extrinsic) to meet the requirements of "trustworthiness," and that evidentiary documentation is provided to support these "accredited data."

Allofus: an R package to facilitate use of the All of Us Researcher Workbench.

Despite easy-to-use tools like the Cohort Builder, using All of Us Research Program data for complex research questions requires a relatively high level of technical expertise. We aimed to increase research and training capacity and reduce barriers to entry for the All of Us community through an R package, allofus. In this article, we describe functions that address common challenges we encountered while working with All of Us Research Program data, and we demonstrate this functionality with an example of creating a cohort of All of Us participants by synthesizing electronic health record and survey data with time dependencies. All of Us Research Program data are widely available to health researchers. The allofus R package is aimed at a wide range of researchers who wish to conduct complex analyses using best practices for reproducibility and transparency, and who have a range of experience using R. Because the All of Us data are transformed into the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), researchers familiar with existing OMOP CDM tools or who wish to conduct network studies in conjunction with other OMOP CDM data will also find value in the package. We developed an initial set of functions that solve problems we experienced across survey and electronic health record data in our own research and in mentoring student projects. The package will continue to grow and develop with the All of Us Research Program. The allofus R package can help build community research capacity by increasing access to the All of Us Research Program data, the efficiency of its use, and the rigor and reproducibility of the resulting research.

An auto-ethnographic study of co-produced health research in a patient organisation: unpacking the good, the bad, and the unspoken

BackgroundIn rare diseases, limited access to services and rare disease experts may force families to act as medical advocates for their child; they can volunteer to support clinician-initiated research or initiate and lead research themselves. Ketotic Hypoglycemia International (KHI) is a new, global organization for families affected by idiopathic ketotic hypoglycemia (IKH) and is run solely by volunteers. Doing research together, families and international experts in a collaborative process such as at KHI, also referred to as patient and public involvement and engagement (PPIE) or extreme citizen science, is often praised for its positive effects on the research and the stakeholders involved.MethodsWe used auto-ethnographic narratives from parents and medical professionals in KHI to report on their experiences with co-produced health research. All co-authors wrote down their experiences in relation to three topics: time invested, work invested and power dynamics.ResultsWhilst the parents and health care professionals felt a new hope for (their) children with IKH, they also felt pressure to contribute time or to be flexible in how and when they dedicated time towards the organization. The power dynamics were characterised by a change in the relationship between the parents and medical experts; the parent being taught by the expert shifted to the expert learning from the lived experience of the parent. Both parents and medical experts struggled with maintaining boundaries and safeguarding their mental health.ConclusionOur findings call for the need to secure and prioritize funding for patient organizations, to enable them to create the sustainable architecture required for meaningful PPIE within these organizations. The morals and often deeply personal reasons for engaging with voluntary work in health research, can lead to overstepping of boundaries. As a result of our research, we call for the development of ethics of care guidelines within collaborative health research.

Centering Communities in Global Health: Using Human-Centered Design to Facilitate Collaboration and Intervention Development.

Utilizing iterative and collaborative tools, Human-centered Design (HCD) facilitates the creation of tailored solutions for multifaceted issues by fostering empathy and a deep understanding of human behaviors. This paper presents insights gleaned from employing HCD tools to center communities in global health intervention development. The study team collaborated with community members in Dailekh, Nepal to co-design interventions to address harms associated with menstrual seclusion, known as chhaupadi. A Community Design Team, comprising 10 women representing various castes and ages convened for a four-day intervention co-design workshop in the community. A Community Validation Team, comprising 12 individuals from diverse occupational and caste backgrounds provided feedback on the interventions. Additionally, six village leaders participated in Key Informant Interviews to garner additional insights. In the study's initial "discovery" phase, the Community Design Team employed HCD tools to generate a nuanced understanding of the context, stakeholders, and community experiences. Subsequently, in the second "design" phase, the Community Design Team crafted interventions to address harms associated with chhaupadi. Invaluable lessons gained from this study underscore the necessity of crafting contextually suitable tools, checklists, and prompts for participants, allocating sufficient staff, time, and resources, and adapting to participants' literacy levels and engagement preferences, whether through group or individual activities. Reflecting on these insights, our experience suggests HCD offers promising tools to authentically and equitably involve participants with diverse backgrounds in articulating their own ideas for community-based solutions in Nepal. Health practitioners, researchers, and intervention development experts are encouraged to consider adopting HCD methodologies to prioritize community voices in devising solutions for complex health challenges.

Incidence of diabetes after SARS-CoV-2 infection in England and the implications of COVID-19 vaccination: a retrospective cohort study of 16 million people

Some studies have shown that the incidence of type 2 diabetes increases after a diagnosis of COVID-19, although the evidence is not conclusive. However, the effects of the COVID-19 vaccine on this association, or the effect on other diabetes subtypes, are not clear. We aimed to investigate the association between COVID-19 and incidence of type 2, type 1, gestational and non-specific diabetes, and the effect of COVID- 19 vaccination, up to 52 weeks after diagnosis. In this retrospective cohort study, we investigated the diagnoses of incident diabetes following COVID-19 diagnosis in England in a pre-vaccination, vaccinated, and unvaccinated cohort using linked electronic health records. People alive and aged between 18 years and 110 years, registered with a general practitioner for at least 6 months before baseline, and with available data for sex, region, and area deprivation were included. Those with a previous COVID-19 diagnosis were excluded. We estimated adjusted hazard ratios (aHRs) comparing diabetes incidence after COVID-19 diagnosis with diabetes incidence before or in the absence of COVID-19 up to 102 weeks after diagnosis. Results were stratified by COVID-19 severity (categorised as hospitalised or non-hospitalised) and diabetes type. 16 669 943 people were included in the pre-vaccination cohort (Jan 1, 2020-Dec 14, 2021), 12 279 669 in the vaccinated cohort, and 3 076 953 in the unvaccinated cohort (both June 1-Dec 14, 2021). In the pre-vaccination cohort, aHRs for the incidence of type 2 diabetes after COVID-19 (compared with before or in the absence of diagnosis) declined from 4·30 (95% CI 4·06-4·55) in weeks 1-4 to 1·24 (1·14-1.35) in weeks 53-102. aHRs were higher in unvaccinated people (8·76 [7·49-10·25]) than in vaccinated people (1·66 [1·50-1·84]) in weeks 1-4 and in patients hospitalised with COVID-19 (pre-vaccination cohort 28·3 [26·2-30·5]) in weeks 1-4 declining to 2·04 [1·72-2·42] in weeks 53-102) than in those who were not hospitalised (1·95 [1·78-2·13] in weeks 1-4 declining to 1·11 [1·01-1·22] in weeks 53-102). Type 2 diabetes persisted for 4 months after COVID-19 in around 60% of those diagnosed. Patterns were similar for type 1 diabetes, although excess incidence did not persist beyond 1 year after a COVID-19 diagnosis. Elevated incidence of type 2 diabetes after COVID-19 is greater, and persists for longer, in people who were hospitalised with COVID-19 than in those who were not, and is markedly less apparent in people who have been vaccinated against COVID-19. Testing for type 2 diabetes after severe COVID-19 and the promotion of vaccination are important tools in addressing this public health problem. UK National Institute for Health and Care Research, UK Research and Innovation (UKRI) Medical Research Council, UKRI Engineering and Physical Sciences Research Council, Health Data Research UK, Diabetes UK, British Heart Foundation, and the Stroke Association.

Incorporation of Trauma-Informed Care Into Entrustable Professional Activities for Medical Student Assessment.

Trauma-informed care (TIC) provides a medical framework for addressing and mitigating the negative consequences of trauma. In response to student and faculty advocacy, medical schools are developing trauma-informed curricular content. However, medical education literature does not present a comprehensive assessment rubric to evaluate medical students' acquisition of trauma-informed clinical skills. A committee of medical students, trainees, and faculty developed a longitudinal TIC curricular theme at Harvard Medical School (HMS). Guided by the National Collaborative on Trauma-Informed Health Care Education and Research competencies, the committee created a set of medical student TIC competencies from July to December 2019. From November 2021 to November 2022, 3 committee subgroups generated new TIC descriptors for each HMS entrustable professional activity (EPA), then circulated these to other subgroups, external experts, and stakeholders for review and feedback. From April to June 2023, the committee iteratively reviewed the materials until reaching consensus for content and pedagogy. The committee integrated TIC content into HMS's existing EPAs expected of students, provided anchoring descriptions of each level, and achieved consensus using a process of iterative review with TIC content experts. The committee identified 10 TIC competencies and revised all 13 general HMS EPAs to include specific items based on these competencies. The committee incorporated at least 1 trauma-informed competency into each HMS EPA. This novel set of HMS EPAs provides a framework for assessment of TIC clinical skills. Faculty will be trained to correctly and reliably incorporate TIC competencies into patient care and to use the TIC-inclusive EPAs for student assessment, ensuring that TIC is standard medical practice at HMS. This work may facilitate the adoption of trauma-inclusive EPAs by other institutions to educate the next generation of physicians to practice TIC and thus promote a more accessible, safe, and equitable health care system.

The contribution of intimate partner violence to vertical HIV transmission: a modelling analysis of 46 African countries

Addressing gender inequities could be key to the elimination of vertical transmission of HIV. Women experiencing intimate partner violence (IPV) might be at an increased risk of vertical transmission due to their vulnerability to HIV acquisition and barriers to access to and retention in care. Sub-Saharan Africa, where IPV burden is among the highest globally, accounts for most new paediatric HIV infections. We aimed to examine the proportion of excess vertical transmission attributable to IPV in this region. In this modelling analysis, we created a probability tree model of vertical HIV transmission among women aged 15-49 years in 46 African countries. We estimated the proportion of vertical transmission attributable to past-year physical or sexual IPV, or both, as an age-standardised population attributable fraction (PAF) and as excess vertical transmission risk per 1000 births among women experiencing IPV. We incorporated perinatal and postnatal vertical transmission among women who acquired HIV before pregnancy, during pregnancy, and during breastfeeding. Fertility, HIV prevalence, HIV incidence, antiretroviral therapy (ART) uptake, and ART retention varied in the model by women's IPV experience. The model was parameterised using UNAIDS' 2023 Spectrum model data, WHO's Global Database on Violence Against Women, and the peer-reviewed literature. Uncertainty intervals (95% UI) were calculated through 1000 Monte Carlo simulations. Across 46 countries 13% (95% UI 6-21) of paediatric HIV infections in 2022 were attributed to IPV, corresponding to over 22 000 paediatric infections. The PAF ranged from 4% (2-7) in Niger to 28% (13-43) in Uganda. The PAF was highest among girls aged 15-19 years (20%, 8-33) and lowest among women aged 45-49 years (6%, 3-9). In southern Africa, where women's HIV prevalence is highest (23%), IPV led to 11 (5-20) additional infections per 1000 births among women affected by IPV. IPV might be responsible for one in eight paediatric HIV infections in sub-Saharan Africa. Ending IPV could accelerate vertical transmission elimination, especially among young women who bear the highest burden of violence. Canadian Institutes of Health Research, Canada Research Chair, and Fonds de recherche du Québec-Santé. For the French, Georgian and Spanish translations of the abstract see Supplementary Materials section.

A new horizon for health research: Strengthening our roots and exploring new frontiers

A new horizon for health research: Strengthening our roots and exploring new frontiers

Applied artificial intelligence in dentistry: emerging data modalities and modeling approaches.

Artificial intelligence (AI) is increasingly applied across all disciplines of medicine, including dentistry. Oral health research is experiencing a rapidly increasing use of machine learning (ML), the branch of AI that identifies inherent patterns in data similarly to how humans learn. In contemporary clinical dentistry, ML supports computer-aided diagnostics, risk stratification, individual risk prediction, and decision support to ultimately improve clinical oral health care efficiency, outcomes, and reduce disparities. Further, ML is progressively used in dental and oral health research, from basic and translational science to clinical investigations. With an ML perspective, this review provides a comprehensive overview of how dental medicine leverages AI for diagnostic, prognostic, and generative tasks. The spectrum of available data modalities in dentistry and their compatibility with various methods of applied AI are presented. Finally, current challenges and limitations as well as future possibilities and considerations for AI application in dental medicine are summarized.

Evolution and Paradigm Shift in Forest Health Research: A Review on of Global Trends and Knowledge Gaps

Forest health is an attractive concept in forestry research, which environmental, social, and political interests have shaped. Assessing forest health is crucial, but finding a single definition of the concept is complex. It is determined by the aim of the forest study, different areas of knowledge, scales of work, technology, methodologies, the historical moment, or the source of funding, among others. With almost a century of scientific evidence, the aim is to identify and contextualise temporal changes in the relevance of this key concept. Trends are analysed through the construction of three main descriptors (state variables, drivers, and methods) and the main conceptual subdomains (themes). This review reveals the significant geographical bias driven by diverse needs and interests. Methodologies have evolved from traditional inventories to the use of advanced tools such as remote sensing or ecophysiology, improving forest characterisation at both global and individual scales. Research has evolved from unicausality towards holistic and multidisciplinary approaches, influencing research to date and future scenarios. We identified key knowledge gaps in the scientific literature, particularly the concepts of ecosystem services, Essential Biodiversity Variables (EBVs) and the concept of “one health”. These findings highlight the need for a research assessment, future directions, and scenarios for forest health research.

Sex and mental health are related to subcortical brain microstructure

Some mental health problems such as depression and anxiety are more common in females, while others such as autism and attention deficit/hyperactivity (AD/H) are more common in males. However, the neurobiological origins of these sex differences are poorly understood. Animal studies have shown substantial sex differences in neuronal and glial cell structure, while human brain imaging studies have shown only small differences, which largely reflect overall body and brain size. Advanced diffusion MRI techniques can be used to examine intracellular, extracellular, and free water signal contributions and provide unique insights into microscopic cellular structure. However, the extent to which sex differences exist in these metrics of subcortical gray matter structures implicated in psychiatric disorders is not known. Here, we show large sex-related differences in microstructure in subcortical regions, including the hippocampus, thalamus, and nucleus accumbens in a large sample of young adults. Unlike conventional T1-weighted structural imaging, large sex differences remained after adjustment for age and brain volume. Further, diffusion metrics in the thalamus and amygdala were associated with depression, anxiety, AD/H, and antisocial personality problems. Diffusion MRI may provide mechanistic insights into the origin of sex differences in behavior and mental health over the life course and help to bridge the gap between findings from experimental, epidemiological, and clinical mental health research.

What public health challenges and unmet medical needs would benefit from interdisciplinary collaboration in the EU? A survey and multi-stakeholder debate.

In the past decade, significant European calls for research proposals have supported translational collaborative research on non-communicable and infectious diseases within the biomedical life sciences by bringing together interdisciplinary and multinational consortia. This research has advanced our understanding of disease pathophysiology, marking considerable scientific progress. Yet, it is crucial to retrospectively evaluate these efforts' societal impact. Research proposals should be thoughtfully designed to ensure that the research findings can be effectively translated into actionable policies. In addition, the choice of scientific methods plays a pivotal role in shaping the societal impact of research discoveries. Understanding the factors responsible for current unmet public health issues and medical needs is crucial for crafting innovative strategies for research policy interventions. A multistakeholder survey and a roundtable helped identify potential needs for consideration in the EU research and policy agenda. Based on survey findings, mental health disorders, metabolic syndrome, cancer, antimicrobial resistance, environmental pollution, and cardiovascular diseases were considered the public health challenges deserving prioritisation. In addition, early diagnosis, primary prevention, the impact of environmental pollution on disease onset and personalised medicine approaches were the most selected unmet medical needs. Survey findings enabled the formulation of some research-policies interventions (RPIs), which were further discussed during a multistakeholder online roundtable. The discussion underscored recent EU-level activities aligned with the survey-derived RPIs and facilitated an exchange of perspectives on public health and biomedical research topics ripe for interdisciplinary collaboration and warranting attention within the EU's research and policy agenda. Actionable recommendations aimed at facilitating the translation of knowledge into transformative, science-based policies are also provided.