Author: network

Seniors Neuropsychological Disorders Patients & EU Fundamental Rights
Proposal: Safeguarding dementia & other neuropsychological disorders patients’ and caregivers’ rights through strategic litigation in Europe

Proposed Implementation: 2026 to 2029

Call: CERV-2025-CHAR-LITI – Call for proposals to promote civil society organisations’ awareness of, capacity building and implementation of the EU Charter of Fundamental Rights

Proposed Budget: 421 359,58€

Keywords: dementia, Strategic litigation, EU Charter, rights, neuropsychological disorders, seniors

Objective: Seniors with dementia or other neuropsychological disorders face some of the highest risks of rights violations in the EU, ranging from unequal access to services and healthcare, to neglect, abuse, and discrimination. Despite the protection offered by the EU Charter of fundamental rights, their rights often remain unrecognized or unenforced. Caregivers, who can play a crucial role in safeguarding these rights, frequently lack adequate knowledge and support to act as advocates. Most civil society organizations working with them have not yet used the potential of strategic litigation, thus missing an important opportunity to defend and promote their rights.

The project addresses this gap by empowering seniors with dementia or other neuropsychological disorders and their caregivers, while strengthening the capacity of civil society organizations, human rights defenders, legal professionals & practitioners, Ombuds Institutions, equality bodies & national human rights institutions to use the EU Charter for advocacy and strategic litigation.

The project’s impact will be threefold:

-Empowerment and dignity for seniors with dementia or other neuropsychological disorders, who will gain accessible tools (home toolkit) and dedicated support (rights advocators) to make their voices heard.

-Strengthened advocacy and protection by caregivers, volunteers, and professionals, who will act as “rights advocators” and ensure continuity beyond the project’s lifespan.

-Systemic change through capacity building of organizations, institutions & professionals across Europe, making rights enforcement a shared and ongoing responsibility.

By combining empowerment of individuals with structural capacity-building, the project will help transform awareness into action and action into systemic change, ensuring that the rights of seniors with dementia or other neuropsychological disorders are not only recognized in principle but fully enforced in practice across the EU.

Partners:
- Challedu Astiki Mi Kerdoskopiki Etaireia
- Health Citizens – European Institute
- Koinofeles Somateio Arogis Kai Frontidas Ilikiomeel
- Kentro Evropaikou Syntagmatikou Dikaio Idryma
- Erevnitiko Idrima
- Cooperativa Sociale Cooss Marche Onlus Societa
- Komiteen for Sundhedsoplysning
Migrant & Vulnerable Group’s Health
Proposal: A Transnational Gateway for Access, Training, and Empowerment in Migrant Healthcare

Proposed Implementation: 2026 to 2030

Call: AMIF-2025-TF2-AG-INTE – Transnational Actions on Asylum, Migration and Integration 2025

Proposed Budget: 1 779 118,96€

Keywords: migrant health, integration, healthcare access, well-being, accessibility, health literacy, vulnerable groups

Objective: Address the critical gap between migrants’ legal entitlement to healthcare services and their actual ability to access those services, according to the EU Action Plan on Integration and Inclusion (2021-2027) and the Pact on Asylum and Migration.

Project has been designed on a transnational, evidence-based and participatory methodology, in order to:
- increase migrants’ awareness regarding their healthcare rights and accessibility to relevant services,
- build the capacity of healthcare professionals and public officials to deliver inclusive, culturally competent and trauma-informed care
- raise awareness of the special health needs of vulnerable groups,
- foster transnational mutual learning and knowledge transfer by leveraging on existing tools and practices and
- advocate for policy change, on a systemic level, finally achieving equitable access to healthcare.
These objectives will be achieved via needs analysis which will indicate the relevant barriers. Through a co-design methodology, a series of comprehensive resources will be developed and exploited, all hosted on an accessible e-Health Learning Platform. These resources will be piloted and delivered through a series of capacity-building activities for multiple stakeholders, including migrants, healthcare professionals and public officials, resulting in a relevant policy recommendation.

The project mobilizes a multi-disciplinary partnership, across EU member-states with varying levels of health system inclusiveness, promoting cross-border collaboration and transfer of knowledge and practice. And will involve more than 3.600 migrants and 300 healthcare professionals and public officials in 6 countries.

Partners:
- Ethniko Kai Kapodistriako Panepistimio Athinon
- Health Citizens – European Institute
- Giatri Tou Kosmou Elliniki Antiprosopia
- Technologiko Panepistimio Kyprou
- Friedrich-Alexander-Universitaet Erlangen-Nuernde
- Camara Municipal de Lisboa
- Elliniko Forum Metanaston – EFM
- Athens Lifelong Learning Institute Astiki Mi Kerdoel
- Magnetar Ltd
- I-Skills A.E.
- Pricewaterhousecoopers Business Solutions AE
- Centrul Pentru Promovarea Învățării Permanentero
- Socialiniu Inovaciju Fondas
- Institouto Anaptixis Apasxolisis
Mental Health Literacy for Kids
Proposal: Empowering Children with Mental Health Literacy Online

Proposed Implementation: 2026 to 2028

Call: CERV-2025-CHILD – Rights of the child and children’s participation

Proposed Budget: 341 576,10€

Keywords: Child mental health, Prevent cyberbullying, media literacy, online safety

Objective: The project aims to address the pressing issue of mental health among adolescents aged 14-17 in the context of digitalization. It focuses on developing strategies to support teenagers’ mental well-being in the face of various challenges exacerbated by digitalization, such as cyberbullying, exposure to harmful content, and excessive screen time.

The initiative entails mapping good practices across four countries, bringing together psychological experts to develop training formats aimed at preparing the educational staff and youth workers to support children’s mental health, both within and beyond school environments.

After training sessions, each partner organization is responsible for conducting local activities with parents and children to raise awareness and provide support. The project emphasizes the importance of promoting digital and media literacy skills among children and youth to navigate the digital world safely and responsibly.

Through collaborative efforts with stakeholders, the project seeks to foster a supportive environment for children’s mental health and well-being in the digital age.

Partners:
- Asociatia Umanista Romana
- Health Citizens – European Institute
- Loesje Bitola
- Society and Enterprise Development Institute
Developing personalized algorithms for sensing mental health symptoms in daily life

This study investigates algorithmic bias in AI tools that predict depression risk using smartphone-sensed behavioral data.

It finds that these tools underperform in larger, more diverse populations because the behavioral patterns used to predict depression are inconsistent across demographic and socioeconomic subgroups.

Specifically, the AI models often misclassify individuals from certain groups—such as older adults or those from different racial or gender backgrounds—as being at lower risk than they actually are. The authors emphasize the need for tailored, subgroup-aware approaches to improve reliability and fairness in mental health prediction tools. This work highlights the importance of addressing demographic bias to ensure equitable AI deployment in mental healthcare.

Learn more about this study here: https://doi.org/10.1038/s44184-025-00147-5

Reference

Timmons, A.C., Tutul, A.A., Avramidis, K. et al. Developing personalized algorithms for sensing mental health symptoms in daily life. npj Mental Health Res 4, 34 (2025).
Regulatory Effects of Probiotics on Anxiety and Depression‑Like Behaviors in H. pylori‑Infected Rats

In a recent experimental study, researchers used rats to explore whether the use of probiotics such as Lactobacillus can mitigate anxiety- and depression-like behaviors, counteracting the psychological and biological effects of H. pylori infection. Infected rats were treated with each probiotic alone or with the combination, and were then evaluated using standard behavioral tests for anxiety and depression.

Both probiotics, especially when co-administered, reversed the depressive and anxiogenic effects induced by H. pylori. Probiotic supplementation also corrected several brain changes linked to H. pylori, including oxidative stress, inflammation, reduced BDNF/serotonin, and elevated corticosterone.

The findings suggest that multi-strain probiotics may help manage psychiatric symptoms associated with H. pylori infection, and that they merit further clinical evaluation in patients with psychiatric comorbidities.

Learn more about this study here: https://doi.org/10.1007/s12602-025-10674-4

Reference

Ahmadi-Soleimani, S.M., Masoudi, M., Tabrizi, A.M.A. et al. Regulatory Effects of Probiotics on Anxiety and Depression-Like Behaviors in H. pylori-Infected Rats. Probiotics & Antimicro. Prot. (2025)
Racial bias in AI-mediated psychiatric diagnosis and treatment: a qualitative comparison of four large language models

The article investigates racial bias in psychiatric diagnosis and treatment recommendations across four large language models (LLMs): Claude, ChatGPT, Gemini, and NewMes-15. The study evaluates the models’ responses to ten psychiatric cases representing five diagnoses (depression, anxiety, schizophrenia, eating disorders, and ADHD) under three conditions: race-neutral, race-implied, and race-explicitly stated (African American).

Key findings include:

1) Bias in Treatment Recommendations: LLMs often proposed inferior or divergent treatments when racial characteristics were explicitly or implicitly indicated, particularly for schizophrenia and anxiety cases. Diagnostic decisions showed minimal bias overall.

2) Model Performance: NewMes-15 exhibited the highest degree of racial bias, while Gemini demonstrated the least bias across conditions.

3) Statistical Analysis: A Kruskal–Wallis H-test revealed significant differences in bias among the LLMs, with Gemini being significantly less biased than ChatGPT and NewMes-15.

4) Challenges in AI Development: The study highlights that LLMs trained on biased datasets may perpetuate racial disparities in psychiatric care, even when specialized medical training data is used. Local LLMs, despite their cost and privacy advantages, showed higher susceptibility to bias compared to larger, online models.

Learn more about this study here: https://doi.org/10.1038/s41746-025-01746-4

Reference

Bouguettaya, A., Stuart, E.M. & Aboujaoude, E. Racial bias in AI-mediated psychiatric diagnosis and treatment: a qualitative comparison of four large language models. npj Digit. Med. 8, 332 (2025).
Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detection

A domain adversarial training (DAT) was developed in a study as a method to reduce gender bias in AI models for depression and PTSD detection using speech data (E-DAIC dataset).

DAT improved F1-scores up to +13% and reduced gender gaps in detection accuracy, improving generalization across male and female participants, specially addressing the effects of the latter’s underrepresentation.

Learn more about this study here: https://doi.org/10.48550/arXiv.2505.03359

Reference

Kim, J., Yoon, H., Oh, W., Jung, D., Yoon, S., Kim, D., Lee, D., Lee, S., & Yang, C. (2025). Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detection. 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1-7.
Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders

Although depression is often linked to digestive disorders, the biological connection behind this phenomenon has remained unclear.

A recent genome-wide association study analyzed genetic data from hundreds of thousands of people to explore potential links between major depressive disorder (MDD) and gastrointestinal conditions such as peptic ulcers (mainly caused by H. pylori infection), acid reflux, irritable bowel disease, and inflammatory bowel disease.

The researchers found that depression shares genetic risk factors with most digestive disorders, meaning that some of the same genes and genetic regions influence both mental and gut health. The study also suggested that genetic susceptibility to certain gut conditions may increase the risk of depression, once again highlighting the strong gut-brain connection.

These findings could help scientists better understand the gut-brain connection and may point to new ways to treat gastrointestinal symptoms in patients with depression.

Learn more about this study here: https://doi.org/10.1016/j.jad.2025.01.048

Reference

Zhou, S., Zi, J., Hu, Y., Wang, X., Cheng, G., & Xiong, J. (2025). Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders. Journal of affective disorders, 374, 84–90.
Minding the Gaps: Neuroethics, AI, and Depression

In this article, the author highlights the benefits and potential issues regarding the use of AI in depression diagnosis/treatment, focusing on the prevalent gender, racial and ethnicity biases.

It is mentioned that, given the historical, inherent biases in society generally and healthcare specifically, AI-driven advancements are not going to serve minority groups as a matter of course. Unless they are tailored to represent and serve all communities equally, they will exacerbate existing biases and disparities.

Learn more about this article here: https://nonprofitquarterly.org/minding-the-gaps-neuroethics-ai-and-depression/

Reference

Boothroyd, Gemma (2024), “Minding the Gaps: Neuroethics, AI, and Depression”, in Nonprofit Quarterly Magazine, winter 2024, “Health Justice in the Digital Age: Can We Harness AI for Good?”
Bias and Fairness in AI-Based Mental Health Models

The paper examines bias and fairness issues in AI-based mental health applications, including diagnostic tools, chatbots, and suicide risk prediction models. It reports how unrepresentative datasets lead to misdiagnosis and unequal outcomes across different socioeconomic, gender and racial groups – namely concerning women, local ethnic minorities or non-Western societies -, and presents mitigation strategies such as diverse datasets, fairness metrics, and human-in-the-loop approaches.

Learn more about this paper here: https://www.researchgate.net/publication/389214235_Bias_and_Fairness_in_AI-Based_Mental_Health_Models

Reference

Barnty, Barnabas & Joseph, Oloyede & Ok, Emmanuel. (2025). Bias and Fairness in AI-Based Mental Health Models.