Reducing Loneliness through the Power of Practicing Together: A Randomized Controlled Trial of Online Dyadic Socio-Emotional vs. Mindfulness-Based Training

Hannah Matthaeus, Malvika Godara, Sarita Silveira, Martin Hecht, Manuel Voelkle and Tania Singer ()
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Hannah Matthaeus: Social Neuroscience Lab, Max Planck Society, 10557 Berlin, Germany
Malvika Godara: Social Neuroscience Lab, Max Planck Society, 10557 Berlin, Germany
Sarita Silveira: Social Neuroscience Lab, Max Planck Society, 10557 Berlin, Germany
Martin Hecht: Faculty of Humanities and Social Sciences, Helmut Schmidt University, 22043 Hamburg, Germany
Manuel Voelkle: Department of Psychology, Humboldt-Universität zu Berlin, 12489 Berlin, Germany
Tania Singer: Social Neuroscience Lab, Max Planck Society, 10557 Berlin, Germany

IJERPH, 2024, vol. 21, issue 5, 1-14

Abstract: Loneliness has become a pressing topic, especially among young adults and during the COVID-19 pandemic. In a randomized controlled trial with 253 healthy adults, we evaluated the differential efficacy of two 10-week app-delivered mental training programs: one based on classic mindfulness and one on an innovative partner-based socio-emotional practice (Affect Dyad). We show that the partner-based training resulted in greater reductions in loneliness than the mindfulness-based training. This effect was shown on three measures of loneliness: general loneliness assessed with the 20-item UCLA Loneliness Scale, state loneliness queried over an 8-day ecological momentary assessment in participants’ daily lives, and loneliness ratings required before and after daily practice. Our study provides evidence for the higher efficacy of a mental training approach based on a 12 min practice conducted with a partner in reducing loneliness and provides a novel, scalable online approach to reduce the increasing problem of loneliness in society.

Keywords: mental training; social connectedness; app-delivered intervention; randomized controlled trial; mental health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
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