A study protocol for assessing the effects of intangible cultural heritage experiences on human well-being

While interventions have been designed which use extended reality (XR) technology in promoting physical, mental and social well-being through cultural heritage experiences, well-defined methodologies for the assessment of such interventions is lacking.

We present a protocol for evaluating the usability and effectiveness of an XR system that mediates and facilitates access to intangible cultural heritage experiences. We aim to assess the effects of these experiences on user well-being and attitudes across four case studies: ageing societies, sustainable tourism, disappearing communities, and immigration and multiculturalism.

Participants will be randomly assigned to control or intervention groups. The effects of the XR intervention on well-being will be assessed through statistical analysis of the participants' salivary cortisol and cortisone levels, physiological signals, and subjective ratings, both pre- and post-intervention and between control and intervention groups. Usability will be measured through a system usability scale. Speech will be recorded for qualitative and natural language processing analysis. Machine learning models will be developed for prediction of affect and well-being on multimodal data.

This is one of the first international and multidisciplinary studies to explore the effects of XR-mediated intangible cultural heritage experiences on well-being and attitudes towards issues of societal importance. One of the main strengths of this study is the range of data modalities it collects, and the range of methods it employs to analyse these data in a complementary manner, including qualitative, statistical and advanced machine learning methods.

This protocol offers a method and four case studies to assess the potential of immersive XR experiences and interventions of intangible cultural heritage as contributors to increased well-being and as actors of societal change. It stands as a reference model for further similar interventions in the field.