LINA -- A social augmented reality game around mental health, supporting real-world connection and sense of belonging for early adolescents
April 27, 2022 ยท Declared Dead ยท ๐ Proc. ACM Hum. Comput. Interact.
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Gloria Mittmann, Adam Barnard, Ina Krammer, Diogo Martins, Joรฃo Dias
arXiv ID
2204.12917
Category
cs.HC: Human-Computer Interaction
Citations
31
Venue
Proc. ACM Hum. Comput. Interact.
Last Checked
3 months ago
Abstract
Early adolescence is a time of major social change; a strong sense of belonging and peer connectedness is an essential protective factor in mental health during that period. In this paper we introduce LINA, an augmented reality (AR) smartphone-based serious game played in school by an entire class (age 10+) together with their teacher, which aims to facilitate and improve peer interaction, sense of belonging and class climate, while creating a safe space to reflect on mental health and external stressors related to family circumstance. LINA was developed through an interdisciplinary collaboration involving a playwright, software developers, psychologists, and artists, via an iterative co-development process with young people. A prototype has been evaluated quantitatively for usability and qualitatively for efficacy in a study with 91 early adolescents (agemean=11.41). Results from the Game User Experience Satisfaction Scale (GUESS-18) and data from qualitative focus groups showed high acceptability and preliminary efficacy of the game. Using AR, a shared immersive narrative and collaborative gameplay in a shared physical space offers an opportunity to harness adolescent affinity for digital technology towards improving real-world social connection and sense of belonging.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Human-Computer Interaction
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
๐ป
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
๐ป
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
๐ป
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
๐ป
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted