Supervisor

Dr. Taufique Ahmed

Programme

HDIP in Data Analytics for Business

Subject

Computer Science

Abstract

Over the last two decades, technology has grown exponentially and has facilitated communication that helps individuals remain connected. However, this has also contributed to social isolation and lack of physical interaction. One consequence of this phenomenon is loneliness, which is understood as an unpleasant subjective state of discrepancy between the desired amount of companionship or emotional support and what is available in the person’s environment (Prohaska and Burholt, 2020). In the European context, Ireland has emerged as the loneliest country in Europe with 20% of its population that have reported feeling lonely most or all the time (Schnepf et al., 2024). Other than being a social issue, loneliness carries a risk for the physical and mental health. For example, it has been associated with an increase of 26% for the risk of mortality (Henriksen et al, 2019). Specifically, it has been shown to increase the risk of strokes or heart attacks (Valtorta et al., 2016), depression, anxiety and suicidal ideation (Beutel et al., 2017). In response, the HSE addresses loneliness through its Mental Health Promotion Plan 2022–2027, offering non-clinical, community-based supports designed to foster social connection (McHugh Power and Swader, 2025). Although this kind of interventions have proven to be efficient, it is crucial that they can be target to the population with higher incidence. This project uses machine learning algorithms applied to Wave 5 of the TILDA survey to predict loneliness among older adults in Ireland and to identify the key factors associated with it. The findings could serve as a valuable tool for policymakers and public health authorities, supporting more targeted and efficient allocation of social programmes and resources.

Date of Award

2026

Full Publication Date

2026

Access Rights

open access

Document Type

Capstone Project

Resource Type

thesis

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Included in

Data Science Commons

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