Factors influencing usage of urban blue spaces: A systems-based approach to identify leverage points

How do weather conditions and environmental characteristics influence aesthetic preferences of freshwater environments?

Freshwater (inland) blue space environments provide a range of public health benefits to visitors. However, health related exposure outcomes are dynamic and can vary depending on several factors, including the environmental characteristics of freshwater environments and their surroundings. Developing and managing inland blue spaces to promote health and wellbeing therefore requires an understanding of whether specific freshwater attributes, and prevailing weather conditions, enhance or devalue landscape aesthetics. The aim of this study was to utilise a mixed-methods research approach to investigate aesthetic preferences of inland blue spaces. A three-phase data collection method was adopted involving (i) analysis of a national-scale landscape image dataset; in combination with (ii) a national-scale online survey; and (iii) a series of in-person focus groups. We found environmental characteristics associated with the waterbody itself, as well as the characteristics of the nearby green space, to have a significant impact on the overall aesthetic appeal of inland blue spaces. Strong preference was demonstrated for inland blue spaces perceived to be of a high environmental quality and which have a natural, rather than human-modified, appearance. The findings highlight the need to conserve the quality of both the waterbody and waterside environment to encourage frequent recreational use and maintain the beneficial public health outcomes associated with inland blue spaces.

Using network analysis to identify leverage points based on causal loop diagrams leads to false inference

Network analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)-mental models that graphically represent causal relationships between a system's factors-are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure-finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect-possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.

Using a human-centered, mixed methods approach to understand the patient waiting experience and its impact on medically underserved Populations

PURPOSE

To use a mixed methods approach to investigate the patient waiting experience for a medically underserved population at an outpatient surgical clinic.

METHODS

We used lean methodology to perform 96 time-tracked observations of the patient journey in clinic, documenting the duration of activities from arrival to departure. We also used human-centered design (HCD) to perform and analyze 43 semi-structured interviews to understand patients' unmet needs.

RESULTS

Patients spent an average of 68.5% of their total clinic visit waiting to be seen. While the average visit was 95.8 minutes, over a quarter of visits (27%) were over 2 hours. Patients waited an average of 24.4 minutes in the waiting room and 41.2 minutes in the exam room; and only spent 19.7% of their visit with an attending provider and 11.8% with a medical assistant. Interviews revealed that patients arrive to their visit already frustrated due to difficulties related to scheduling and attending their appointment. This is exacerbated during the visit due to long wait times, perceived information opacity, and an uncomfortable waiting room, resulting in frustration and anxiety.

CONCLUSIONS

While time tracking demonstrated that patients spend a majority of their visit waiting to be seen, HCD revealed that patient frustrations span the waiting experience from accessing the appointment to visit completion. These combined findings are crucial for intervention design and implementation for medically underserved populations to improve the quality and experience with healthcare and also address system inefficiencies such as long wait times.

Urban Blue Spaces as Therapeutic Landscapes: "A Slice of Nature in the City"

Urban blue spaces are defined as all natural and manmade surface water in urban environments. This paper draws on how the concepts of experienced, symbolic, social, and activity space combine to position urban blue spaces as therapeutic landscapes. We conducted 203 intercept interviews between 12 October 2019 and 10 November 2019. Although safety concerns had health-limiting impacts, interacting with the Glasgow Canal and surrounding landscape was predominantly perceived as health-enhancing. Our findings build on current evidence, which has suggested that urban blue spaces, particularly canals, may foster therapeutic properties, contributing to healthier city environments. Further research is required to understand better the interconnectedness of urban blue spaces and health and how such spaces can be best developed and managed to improve the health outcomes of local populations.

A population-based retrospective study of the modifying effect of urban blue space on the impact of socioeconomic deprivation on mental health, 2009-2018

The incidence of mental health disorders in urban areas is increasing and there is a growing interest in using urban blue spaces (urban waterways, canals, lakes, ponds, coasts, etc.) as a tool to manage and mitigate mental health inequalities in the population. However, there is a dearth of longitudinal evidence of the mechanisms and impact of blue spaces on clinical markers of mental health to support and inform such interventions. We conducted a 10-year retrospective study, following STROBE guidelines, using routinely collected population primary care health data within the National Health Service (NHS) administrative area of Greater Glasgow and Clyde for the North of Glasgow city area. We explored whether living near blue space modifies the negative effect of socio-economic deprivation on mental health during the regeneration of an urban blue space (canal) from complete dereliction and closure. A total of 132,788 people (65,351 female) fulfilling the inclusion criteria were entered in the analysis. We established a base model estimating the effect of deprivation on the risk of mental health disorders using a Cox proportional hazards model, adjusted for age, sex and pre-existing comorbidities. We then investigated the modifying effect of living near blue space by computing a second model which included distance to blue space as an additional predicting variable and compared the results to the base model. Living near blue space modified the risk of mental health disorders deriving from socio-economic deprivation by 6% (hazard ratio 2.48, 95% confidence interval 2.39–2.57) for those living in the most deprived tertile (T1) and by 4% (hazard ratio 1.66, 95% confidence interval 1.60–1.72) for those in the medium deprivation tertile (T2). Our findings support the notion that living near blue space could play an important role in reducing the burden of mental health inequalities in urban populations.