Identifying the Risks of Loneliness in the Netherlands

Loneliness is a growing societal problem that affects many people, and it has become even more prevalent in recent years due to the COVID-19 pandemic. One in ten Dutch adults is suffering from severe loneliness. Risk factors for loneliness are on the rise and expected to increase. Loneliness can raise a person’s risk of death by 45% – more than air pollution, obesity or alcohol abuse.

In January 2023, despite a wealth of relevant research already published, the Dutch National Organization for Research (NWO) has highlighted the issue once again and has issued a call for more research into the different types of loneliness, its causes and effects. Special attention is required towards the taboos that surround loneliness and to five prioritized target groups: minors (11-17), young adults (17-26), people with light mental or physical abilities, elders with a non-western migration background and caretakers of people with chronic illnesses or handicaps.

The goal for this challenge will be to shed more light on the issues highlighted above. Current research is mostly based on questionnaires issued by local health authorities. However, in light of the taboo around loneliness, these self-reported results may underrepresent or bias the true degree of loneliness. Using public datasets on risk factors, scraping social media or combining other datasets could ameliorate our current understanding. The research scope may also be focused on consequences or solutions.

For example, do social media posts reflect positively on anti-loneliness campaigns? Can we find patterns that indicate a taboo around loneliness? Can we predict an increase in loneliness or related health outcomes based on trends in risk factors?

Loneliness is a persistent, detrimental and growing health crisis in the Netherlands. Any new insights in the underlying causes, effects and successful intervention can support the battle.

• Map datasets that are relevant to the problem
• Formulate a problem that can be solved by AI research
• Analyze and present results in an understandable matter
• Potentially build a dashboard to explore different scenarios, e.g. different interventions or economic scenarios

1. Interacting with a real, tangible problem.
2. Complex reasoning.
3. Manipulation and analysis of multivariable datasets.