Technologies Supporting Self-Reflection on Social Interactions

A Systematic Review

Conference Paper (2025)
Author(s)

Chenxu Hao (TU Delft - Pattern Recognition and Bioinformatics)

Tiffany Matej Hrkalovic (Tilburg University, Jheronimus Academy of Data Science)

Daniel Balliet (Vrije Universiteit Amsterdam)

H.S. Hung (TU Delft - Pattern Recognition and Bioinformatics)

B.J.W. Dudzik (TU Delft - Pattern Recognition and Bioinformatics)

Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1145/3708359.3712158
More Info
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Publication Year
2025
Language
English
Research Group
Pattern Recognition and Bioinformatics
Pages (from-to)
1354-1365
ISBN (print)
979-8-4007-1306-4
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Abstract

As intelligent technology and applications have become an integral part of nearly all aspects of people's daily lives, many intelligent systems have been designed to help people navigate the complex space of social interactions. One prominent strategy for such intelligent support is providing meaningful Ad Hoc Interventions (ADI), e.g., through timely notifications. An alternative is Technology-Supported Reflection (TSR), e.g., by offering information about activities in one's past for personal insights. In contrast to straight-up interventions, the aim of the latter strategy is not to directly augment human skills but instead support learning and personal growth over time. However, while TSR has seen widespread interest in applications in some areas, such as physical fitness and mental health, its use for improving human social interactions has not yet been systematically explored. Concretely, it is currently unclear 1) what forms of self-reflection systems intend to support, 2) how their different technological components (e.g., data collection, information integration) are involved in providing support, and 3) what common limitations and design challenges they face. In this article, we present the results of a systematic literature review focusing on these questions to provide a structured foundation for targeted research. Concretely, we identified and analysed a collection of 23 relevant papers, each describing a system deploying TSR to support humans with elements of social interactions.We constructed a framework with a set of features to comprehensively describe and analyze the systems that support self-reflection, including their application domains, how they fit into the existing design framework, how they facilitate learning through reflection, how adaptive they are to individual users, and how they were evaluated. Finally, we propose a direction for designing systems that support individual's social interactions through self-reflection in an adaptive manner.