Leisure engagement has risen as a salient societal issue during the COVID-19 pandemic, not only because it provides a pathway for people to continue meeting their physical, cognitive, and social-emotional needs, but also due to the phenomenal juxtaposition of general increases in leisure time and unparalleled constraints. This study reports the results of the first investigation of U.S. adults’ overall leisure engagement and its association with mental health amidst the major disruptions and sustained stress of the COVID-19 pandemic. Qualitative and quantitative data were collected through an online survey in February 2021 through Prolific from a sample representative of the U.S. adult population in age, gender, and race (n = 503) and analyzed using a mixed-method approach. A total of 104 unique leisure activities in 19 categories and 3 domains were identified through iterative thematic coding. Participants reported general increases in home-based traditional leisure and digital/online activities and decreases in physical and nature-based activities. Multiple regression analyses controlling for socio-demographic and context-specific covariates revealed distinct associations between changes in leisure engagement and different aspects of mental health (perceived stress, depressive symptoms, and mental wellbeing), supporting leisure’s dual role in facilitating stress alleviation and wellbeing enhancement during taxing events, such as COVID-19.

Tourism and recreation managers rely on spatial-temporal data to measure visitors’ behavior for gauging carrying capacity and sustainable management. Location-based service (LBS) data, which passively record location data based on mobile devices, may enable managers to measure behaviors while overcoming constraints in labor, logistics, and cost associated with in-person data collection. However, further validation of LBS data at more refined spatial and temporal scales within tourism attractions is needed. We compared observations of salient spatial–temporal measures from a stratified sample of onsite visitors’ GPS traces in a popular U.S. National Park during peak season over two years with a sample of visitors’ traces collected during the same period by a third-party LBS data provider. We described trip characteristics and behaviors within 34 points of interest (POIs) and then pre-processed both datasets into weighted, directed networks that treated POIs as nodes and flow between POIs as edges. Both datasets reported similar proportions of day-use visitors (~79%) and had moderate-to-strong correlations across networks depicting visitor flow (r = 0.72–0.85, p < 0.001). However, relative to the onsite data, LBS data underestimated the number of POIs the visitors stopped by and differed in its rank of popular POIs, underestimating the length of time visitors spent in POIs (z = 1, p ≤ 0.001) and overestimating visitation to the most popular POIs (z = 180, p = 0.044). Our findings suggest that LBS data may be helpful for identifying trends or tracking tourist movement in aggregate and at crude spatial and temporal scales, but they are too sparse and noisy to reliably measure exact movement patterns, visitation rates, and stay time within attractions.

Outdoor recreation provided a crucial way to maintain physical activity, reduce stress, and preserve a sense of normalcy during the COVID-19 pandemic. This study assessed the relationship between outdoor recreation and mental health in the context of COVID-19. Cross-sectional online survey data were collected in early 2021 from a sample (n = 503) representative of the U.S. adult population in age, gender, and race. We observed prevalent engagement in near-home outdoor activities, widespread reductions in outdoor engagement relative to the pre-COVID period, and significant age, financial, and racial differences in engagement patterns. Regression models suggested that reduced outdoor recreation was associated with higher levels of perceived stress and depressive symptoms, whereas more frequent outdoor activities predicted better well-being. The health implications of adaptive engagement versus cumulative exposure during times of significant disruptions are discussed, along with the need to address structural inequities in accessing outdoor recreation as a health behavior.

Maintaining engagement in outdoor recreation during COVID-19 required adaptation as the pandemic continuously reshaped risk perceptions, use of outdoor space, and interpersonal contact. This study examined the role of four main adaptive strategies in outdoor recreation engagement among U.S. adults during one of the nation’s largest waves of COVID-19 cases and death. Cross-sectional data were collected through an online survey in February 2021 ( N = 503) from an online panel representative of the U.S. adult population in age, gender, and race. Multiple linear regression results suggested that increasing effort and temporal adjustment were associated with higher outdoor recreation frequency controlling for the effects of nearby green space access and attributes, COVID risk perception, and demographic variables. Binary logistic regression results revealed that these same strategies were also associated with increased odds of maintaining or increasing outdoor engagement relative to pre-COVID level. The prominent role of individual adaptive strategies relative to the impact of nearby green space access and attributes highlighted the value of behavioral adaptation at the individual level in times of major disruptions and constraints and the need to prioritize recreation programming to facilitate adaptation and healthy behaviors during future stressful events.

Purpose: Data sources for monitoring tourists are prolific and growing. This phenomenon presents increasing opportunities for researchers and practitioners to diversify and enhance monitoring approaches; however, it also creates a complex landscape for developing rigorous methodology. The tourist monitoring compass is a conceptual framework that visualizes the suitability of traditional quantitative data and big data collection approaches for measuring salient social science constructs in nature-based tourism destinations. Design/methodology/approach: Prominent quantitative data collection sources were placed on a matrix. The x-axis ranged from tourist attributes to tourist behavior. The y-axis rated sources based on their ability to measure phenomena ranging from psychological to observable. Findings: Most data collection methods were well-suited for measuring observable phenomena – both behaviors and attributes. Relatively fewer sources measure psychological phenomena. The gaps among existing tools highlight the value of well-conceptualized theoretical models and the integration of multiple data sources using mixed methods for measuring complex phenomena. Practical implications: Inspection of the framework can facilitate understanding of nature-based tourism monitoring measurement tools and constructs. The framework visualizes constructs to identify the current versatility, limitations and gaps of existing measurement approaches, revealing potential areas for innovation in how to use existing tools and prioritizing innovation in new approaches. Originality/value: The present framework associates construct validity with measurement approaches to serve as a simple tool for practitioners and researchers to identify appropriate data collection sources based on their common uses. The framework may facilitate the initial step of designing tourist monitoring methodology – data selection – in an increasingly complex methodological landscape.

Artificial Intelligence (AI) agents can be understood as the system that performs tasks autonomously, typically using large language models (LLMs) coupled with reasoning (Gutowska, 2026). There are...