Who changed and who maintained their urban bike-sharing mobility after the COVID-19 outbreak? A within-subjects study

Outdoor recreation's association with mental health and well-being during the COVID-19 pandemic

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.

A person-centered approach to cognitive performance analysis in primary school children: Comparisons through self-organizing maps

The objective of this study was to identify distinct student profiles based on physical, psychological, and social characteristics, and examine their impact on cognitive performance. A total of 194 children participated in this cross-sectional design study (mean age = 10.61 years, SD = 0.45; 48.96% girls). The study included participants from diverse racial backgrounds. Using Self-Organizing Maps, an unsupervised neural network clustering technique, six distinct profiles were identified. These profiles revealed significant effects in daily physical activity, self-reported physical, social, and psychological factors, and physical performance. Profiles characterized by higher physical activity levels and positive social and psychological factors were associated with better cognitive performance, in contrast to profiles with lower levels in these domains. These findings suggest that students' cognitive outcomes may be linked to their physical, psychological, and social characteristics, which interact to shape cognitive functioning. The recognition of the diversity of student profiles in specific educational settings may facilitate the design of more targeted programs that address individual needs and strengths, thereby enhancing their development in these domains within similar educational contexts.

Investigating the potential of aggregated mobility indices for inferring public transport ridership changes

Aggregated mobility indices (AMIs) derived from information and communications technologies have recently emerged as a new data source for transport planners, with particular value during periods of major disturbances or when other sources of mobility data are scarce. Particularly, indices estimated on the aggregate user concentration in public transport (PT) hubs based on GPS of smartphones, or the number of PT navigation queries in smartphone applications have been used as proxies for the temporal changes in PT aggregate demand levels. Despite the popularity of these indices, it remains largely untested whether they can provide a reasonable characterisation of actual PT ridership changes. This study aims to address this research gap by investigating the reliability of using AMIs for inferring PT ridership changes by offering the first rigorous benchmarking between them and ridership data derived from smart card validations and tickets. For the comparison, we use monthly and daily ridership data from 12 cities worldwide and two AMIs shared globally by Google and Apple during periods of major change in 2020-22. We also explore the complementary role of AMIs on traditional ridership data. The comparative analysis revealed that the index based on human mobility (Google) exhibited a notable alignment with the trends reported by ridership data and performed better than the one based on PT queries (Apple). Our results differ from previous studies by showing that AMIs performed considerably better for similar periods. This finding highlights the huge relevance of dealing with methodological differences in datasets before comparing. Moreover, we demonstrated that AMIs can also complement data from smart card records when ticketing is missing or of doubtful quality. The outcomes of this study are particularly relevant for cities of developing countries, which usually have limited data to analyse their PT ridership, and AMIs may offer an attractive alternative.

Who changed and who maintained their urban bike-sharing mobility after the COVID-19 outbreak? A within-subjects study

The COVID-19 pandemic has remarkably impacted urban mobility. All non-essential movements were restricted in Valencia (Spain) to contain the virus. Thus, the transport usage patterns of Valencia's bike-sharing system (BSS) users changed during this emergency situation. The primary objective of this study was to analyse the behaviour patterns of BSS users in Valencia before and after the COVID-19 outbreak, specifically those who maintained or changed their transport routines. A within-subjects comparison design was developed using a group of BSS users before and after the onset of the pandemic. Data mining techniques were used on a sample of 4355 regular users and 25 variables were calculated to classify users by self-organising maps analysis. The results show a significant reduction (40 %) in BSS movements after the outbreak during the entire post-outbreak year. There was some recovery during the rest of 2020; however, this has yet to reach the pre-pandemic levels, with variations observed based on the activities performed in different areas of the city. Of the users, 63 % changed their BSS use patterns after the onset of the pandemic (LEAVE group), while 37 % maintained their patterns (REMAIN group). The user profile of the REMAIN group was characterised by a general reduction of approximately 35 % of journeys during 2020, with a slight increase in morning movements compared to those made in the evening. These users also presented an equivalent number of cycling days to those of the previous year, reduced the number of connections and increased the network's density and the travelling speed. These results can be useful in estimating the percentage of people who do not vary their usual behaviour during emergencies. Finally, several policy implications are outlined based on the findings.