Following the COVID-19 pandemic, there has been a significant global increase in mental health disorders, predicted to rise even further. University students are particularly affected due to their high prevalence of and sensitivity to mental health-related problems. Specifically in the Netherlands, this is further exacerbated by the ongoing housing crisis, which forces many students into poor-quality, cramped accommodations. This research explores how phenomenological principles can inform student housing design to enhance mental well-being. Using a literature review, case studies, interviews, and participatory sketching, the study identifies key architectural elements that support mental well-being. Among these, the most important findings highlight the importance of accessible and visible greenery from the dwelling, ample direct sunlight, quiet bedrooms, communal spaces and the presence of a courtyard.

The assignment for the graduation studio Dwelling Designing for Health and Care focuses on designing a health- or care-related building that promotes an inclusive and supportive living environment for the lonely in society. Tarwewijk, an urban neighborhood in Rotterdam South, serves as the central case study.

Loneliness is a growing social and health issue that needs to be addressed in Western cities, particularly in urban neighbourhoods. While occasional loneliness is not inherently harmful, chronic loneliness poses serious health risks, including depression, heart disease, and increased mortality (Cacioppo et al., 2006; Thurston en Kubzansky, 2009; Penninx et al., 1997, Coalitie Erbij, 2018; Holt-Lunstad et al., 2015). In the Netherlands, elderly individuals are especially vulnerable due to declining physical and cognitive health, which hinders social connections (Campen et al., 2018). The Campaign to End Loneliness emphasizes its severity, equating its health impact to smoking 15 cigarettes daily (Holt-Lunstad et al., 2015).
However, young adults aged 16 and 24 are also at high risk of loneliness, according to international surveys, especially in Western countries (e.g., Hammond et al., 2018; Nemecek, 2020; DiJulio et al., 2018; Pyle & Evans, 2018; Payne, 2021; Ibbetson, 2019). Factors, such as relocation for education or work (Kaplan etal., 2020), or reliance on digital communication, rather than socializing in person with friends, family, neighbours or colleagues (Roe & McCay, 2021), contribute to this trend. Urban contexts further amplify loneliness in this group when feelings of distrust, insecurity, or lack of belonging arise (Pyle & Evans, 2018). This shows the complexity of loneliness because it is multifaceted, multigenerational and context-specific (Moore et al., 2023), requiring tailored urban interventions to promote inclusion and social engagement.

In conclusion, loneliness among elderly people and young adults is increasingly prevalent and detrimental to health in urban neighborhoods. This study investigates how urban neighbourhoods, like Tarwewijk, can incorporate multigenerational communal spaces that foster social wellbeing, social engagement and a sense of belonging in the neighbourhood, hypothesizing that such designs are an architectural means to alleviate loneliness.

RESEARCH QUESTIONS
In what way can the design of
communal spaces in urban neighbourhoods, such as the Tarwewijk, help reduce loneliness among residents of different age groups?
1. What specific factors contribute to feelings of loneliness among residents in the Tarwewijk?
2. What roles do the current communal spaces play regarding combating loneliness in the Tarwewijk?
3. How can the design of (future) intergenerational communal spaces be catered to the social needs of the elderly and young adults?

How to deal with the abundance of abandoned mega-structures in a city and where do these structures fit in modern society?

Rather than repelling or demolishing, this project deals with the structure of the abandoned factory of Belgrade by redefining its relationship to the human scale. The use of the age-old approach of roman and medieval village structures serves as the main strategy to allow for change and resilience. With the tools of excavation and fragmentation, the former Cotton Factory is transformed into a village community along with parameters to allow the 'anonymous' users to develop a variety of functions.

Dutch Housing associations (HA’s) are responsible for producing, maintaining, and managing about 30% of all Dutch housing stock. HA’s draw up their investment forecasts yearly for the next 5 years to construct, improve or maintain homes and other real estate investments. Since 2013, the realization rate of new construction plans by HA’s, which is the comparison of forecasts (dPi) against realized plans (dVi) decreased due to HA’s not realizing new build homes within the time they propose to realize them in their forecast plans. HA’s currently use valuation methods which assist them to mitigate emerging risks that affect new build plans of HA’s. However, valuation methods have been found to focus on indexable risks and capture financial loss while excluding time effect of risks. This means that new build investment forecast as currently conducted yields inaccurate results and are considered too optimistic. Forecasts that are too optimistic lead to disappointments from tenant organizations and municipalities, reduced financial guarantees from lenders, long waiting times for tenants and affects financial feasibilities which rely on accurate prediction of time to completion of projects.
The aim of the research is to explore how new build plans can be made more realistic by accurately predicting the delivery time of investment forecasts. The study results in the identification of risks that lead to delay of new build investment plans and their subsequent indicators. The risks include long permit procedures, long land acquisition processes or lack of land positions to build, long tendering procedures, contractor related delays, rise in construction costs and lack of capacity at municipal level in dealing with development projects. The indicators of risks which statistically significantly predicted project time are construction costs, change in input price index of material and labour costs as of date when decision was made to tender, municipal location, and type of construction i.e., on empty ground or existing site that needs demolition. The project indicators can be used by HA's to accurately predict project time via stochastic decision tree models (SDTA) that rely on multiple linear regression (MLR) and Monte Carlo simulations (MCS). Supervisory bodies can also use these to gauge realism of new build investment forecast.