Psychological profiles of mindfulness and tourist fatigue: a latent profile analysis in a digital travel context.
Scientific Reports April 16, 2026 DOI: 10.1038/s41598-026-45414-3 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational survey study using Latent Profile Analysis Peer reviewed |
|---|---|
| Sample size | 646 |
| Population | Tourists in China using digitally mediated or AI-mediated travel systems |
| Measures | Mindful Attention Awareness Scale (MAAS), Generalized Anxiety Disorder 7-item scale (GAD-7), positive fantasy engagement measure, tourist fatigue measure |
| Topics | Meditation |
| Key findings | Tourist fatigue varied significantly across four psychological profiles (η² = 0.254), with the emotionally distressed group reporting the highest fatigue and the high positive psychological capital group the lowest. Demographic predictors were mostly insignificant, which the authors argue indicates that psychological configuration, rather than structural characteristics, drives fatigue in digital tourism. |
Abstract
The study examined how the different psychological constructs of mindfulness, anxiety, and positive fantasy engagement influence tourist fatigue in digitally mediated tourism experiences. In response to the increasing anxiety regarding cognitive overload in AI-driven travel ecosystems, the study reconceptualizes fatigue as configuration-dependent, but not uniformly experienced. Composite measures of mindfulness (MAAS), anxiety (GAD-7), positive fantasy engagement, and tourist fatigue were determined using survey data of 646 tourists. Latent Profile Analysis was used to identify psychological subgroups, after which ANOVA and multinomial logistic regression were run to test the differences in fatigue and demographic predictors. It is a framework that combines self-control theory, conservation of resources theory, and broaden-and-build theory in the digitally accelerated tourism context. There were four different types of profiles of mindfulness-dominated positive fantasy, emotionally distressed, high-positive psychological capital, and balanced-average. The profiles had a significant difference in fatigue levels (η² = 0.254), with the highest fatigue reported by the Emotionally Distressed group and the lowest by the High Positive Psychological Capital group. Mostly, the demographic predictors were insignificant, which emphasized the importance of psychological configuration rather than the structural characteristics. The findings advance tourism psychology by showing that fatigue is a result of the interaction between attentional regulation, emotional load, imaginative engagement, and the intensity of the digital environment. The study will add a multi-level psychological architecture of tourist fatigue by combining person-centered modeling with digital tourism scholarship. In the context of smart tourism system in China and AI-mediated traveling systems that continue to grow worldwide, the application of digital mindfulness and attentional scaffolding systems within platform design can potentially help reduce the fatigue of psychologically vulnerable users. This work goes beyond variable-based models to uncover the interaction of internal regulatory systems, tourism infrastructures that are mediated by digital technologies, to provide a worldwide applicable model of maintaining experiential well-being as technologically enhanced travel environments are experienced.
Comparable studies
Other cross-sectional and survey studies on meditation, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Construct Validity of the Five Facet Mindfulness Questionnaire in Meditating and Nonmeditating Samples Experienced meditators and nonmeditating comparison groups | 2008 | Cross-sectional study | |
| Neural Correlates of Dispositional Mindfulness During Affect Labeling Adult participants | 2007 | Observational cross-sectional | n = 27 |
| Assessing mindfulness in children and adolescents: Development and validation of the Child and Adolescent Mindfulness Measure (CAMM). School-aged children and adolescents | 2011 | Cross-sectional validation study | n = 1,413 |
| Mindfulness and self-compassion as predictors of psychological wellbeing in long-term meditators and matched nonmeditators Experienced meditators and demographically matched nonmeditators | 2012 | Cross-sectional study | n = 152 |
| Mechanisms of Action in the Inverse Relationship Between Mindfulness and Psychological Distress Undergraduates | 2008 | Cross-sectional, correlational |
Citations in the library
Cites 3
- The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology 2003
- Latent Profile Analysis of the Five Facet Mindfulness Questionnaire (FFMQ) Subscales in a Naturalistic Sample of Patients with Past or Present Major Depression: A Replication and Extension Study Mindfulness February 1, 2024
- The more mindfulness practice, the more post-trauma stress symptoms? Trait mindfulness and PTSS during the COVID-19 pandemic. Current Psychology March 15, 2022