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In order to improve the participation from local residents during the decision-making about their public’s life, participatory budgeting is one of the most prevalent system of civic engagement recently. In this project, the site selected in Taiwan is a span space under expressway, is open to use as a park and physical fitness facility for the local residents. The action plan through explanatory presentation, empowerment and proposal workshop, project exhibition and voting, and preferred solution implementation. Using participatory budgeting as a tool of governance allows people to participate in the politics, and the government also wins the trust and obtain a higher satisfaction level from the public.

Elderly patients living in long-term care facilities have been restricted from leaving to comply with social distancing guidelines during the COVID-19 pandemic. This has led to a worsening of disorders, such as anxiety and depression. This study aims to understand the health benefits of an immersive garden experience to elderly nursing home residents with mild-to-moderate cognitive impairments. Virtual reality devices were used to provide immersive garden experiences for the residents who were unable to go outside. The heart rate and heart rate variability (HRV) data of the participants of the participants were collected using biofeedback instruments, and changes in the low frequency/high frequency (LF/HF) and the standard deviation of the NN interval (SDNN) values caused by immersive garden experiences were discussed. The results show that the immersive garden experiences were beneficial to these elderly residents. Within 6 min of completing the experiment, we found that the heart rates of participants had dropped slightly, while SDNN and HF values continued to rise. SDNN values before and after the experiment demonstrated a statistically significant improvement. Furthermore, participants expressed their satisfaction with the video intervention program. The results indicated that nursing homes can provide immersive landscape experiences to help increase HRV and SDNN of their elderly residents. This will not only help these residents recall beautiful memories of their past, but will also improve their quality of life. Supplementary Information The online version contains supplementary material available at 10.1007/s11355-021-00480-9.

The number of people with dementia is increasing rapidly worldwide. Developing strategies to improve quality of life for those with dementia is crucial and is receiving more attention. Natural environments are known for their healing effects on most people. This pilot study aimed to understand the benefits that natural environments, such as gardens, can provide for people with dementia. In total, 42 staff members in nine dementia care facilities were recruited as participants in this study and answered a semistructured questionnaire. One-way analysis of variance with repeated measures and the Mann–Whitney U test were used to compare the effects of garden visits on evaluated characteristics and the differences in evaluated characteristics between free garden use and unfree garden use groups. Data from open-ended questions underwent text analysis to obtain the principal beliefs of the participants. The staff members reported that garden visits had positive effects on mood, social interaction, depression, and agitation in people with dementia because of the multisensory, gentle stimuli of the natural environment. Of the evaluated cognitive characteristics, attention and orientation to time were improved the most after residents with dementia had spent time in a garden. Additionally, staff members in the free garden use group scored the effects of garden visits on the mood, long-term memory, language abilities, spatial ability, aggression, and agitation of patients with dementia as significantly higher than staff members in the unfree garden use group. Recommendations for future studies are discussed.

The easy availability and widespread use of remotely-sensed imagery, especially Google Earth satellite imagery, makes it simple for urban forestry professionals to assess a site and measure tree cover density without visiting the site. Remotely-sensed tree cover density has become the dominant criterion for urban forestry regulations in many countries, but it is unclear how much such measures match the eye-level tree cover density that people experience; or the information gained through site visits, eye-level photography, or from consulting with citizens. To address this uncertainty, we assessed associations among two remotely-sensed and three eye-level tree cover density measures for 140 community street sites across the Midwestern United States with low, medium, or high tree cover coverage by using linear regression analysis. We found significant associations among the two remotely-sensed measures and the three eye-level measures across the three levels of tree cover. The associations between any pair of remotely-sensed and eye-level measures, however, diminish dramatically as canopy cover increased. At high levels of canopy cover, all associations between the remotely-sensed measures and the eye-level measures became statistically insignificant. These findings suggest that measures from remotely-sensed imagery fail to represent the amount of tree cover people perceive at eye-level when canopy cover is medium or high at the site scale. Therefore, the current urban forestry planning regulations, which rely heavily on remotely-sensed tree cover density measurements, need to be revised. We suggest strategic spots where eye-level measures of tree cover density should be emphasized.

This paper considers the effect of non-differential outcome misclassification on the population attributable fraction and the population prevented fraction. I examine the bias in the attributable and the prevented fraction derived from a risk ratio estimate as a function of the sensitivity and specificity of the outcome classification, the true risk ratio, the prevalence of the exposure, and the baseline disease frequency. With outcome misclassified, disease frequency is an important determinant of the magnitude of the bias; the rarer the disease, the more severe is the bias. For both the attributable and the prevented fraction, the specificity of the outcome classification has a greater influence on the magnitude of the bias than the sensitivity; this is in contrast to the dominant effect of sensitivity in situations of exposure misclassification. Also, unlike the findings in the exposure misclassification, the bias due to outcome misclassification does not increase monotonically with increased prevalence of exposure. For the attributable and prevented fraction derived from an odds ratio estimate, the specificity of the outcome classification does not have a greater influence on bias than the sensitivity, and a perfect specificity alone does not lead to unbiased effect estimates if the sensitivity of the outcome classification is imperfect.