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Find video protocols related to scientific articles indexed in Pubmed.
Temporal and spatial variability of traffic-related noise in the City of Toronto, Canada.
Sci. Total Environ.
PUBLISHED: 10-24-2013
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The majority of studies that assessed population-level exposure to traffic-related noise were conducted in European countries and less is known about the exposure to traffic noise in North America, particularly in Canadian cities. This study explored the temporal and spatial variability of traffic noise in the City of Toronto, the largest city in Canada. We conducted two cycles of intensive field measurement campaign to collect real-time measurements of traffic noise at 554 locations across Toronto between June 2012 and January 2013. At each site, we collected measurements for a period of 30min during daytime. Repeated measurements were made in cycle two at 62 locations randomly selected from cycle one, which exhibited high correlation (Pearsons correlation coefficient (r): 0.79). In addition, continuous measurements of noise were recorded for seven days at ten sites. We observed that noise variability was predominantly spatial in nature, rather than temporal: spatial variability accounted for 60% of the total observed variations in traffic noise. Traffic volume, length of arterial road, and industrial area were three most important variables, explaining the majority of the spatial variability of noise (R(2)=0.68 to 0.74, depending on the cycle). In comparison to the 16-h equivalent sound level guideline for outdoor locations set out by the Ministry of the Environment of the Province of Ontario, 80% of our sampled locations exceeded this guideline (i.e. 55 dBA,16h). These findings suggested ubiquitous traffic noise exposure across Toronto and that noise variability was explained mostly by spatial characteristics.
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The effects of mindfulness-based stress reduction program on the mental health of family caregivers: a randomized controlled trial.
Psychother Psychosom
PUBLISHED: 05-27-2013
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Background: Caregivers of people with chronic conditions are more likely than non-caregivers to have depression and emotional problems. Few studies have examined the effectiveness of mindfulness-based stress reduction (MBSR) in improving their mental well-being. Methods: Caregivers of persons with chronic conditions who scored 7 or above in the Caregiver Strain Index were randomly assigned to the 8-week MBSR group (n = 70) or the self-help control group (n = 71). Validated instruments were used to assess the changes in depressive and anxiety symptoms, quality of life, self-efficacy, self-compassion and mindfulness. Assessments were conducted at baseline, post-intervention and at the 3-month follow-up. Results: Compared to the participants in the control group, participants in the MBSR group had a significantly greater decrease in depressive symptoms at post-intervention and at 3 months post-intervention (p < 0.01). The improvement in state anxiety symptoms was significantly greater among participants in the MBSR group than those of the control group at post-intervention (p = 0.007), although this difference was not statistically significant at 3 months post-intervention (p = 0.084). There was also a statistically significant larger increase in self-efficacy (controlling negative thoughts; p = 0.041) and mindfulness (p = 0.001) among participants in the MBSR group at the 3-month follow-up compared to the participants in the control group. No statistically significant group effects (MBSR vs. control) were found in perceived stress, quality of life or self-compassion. Conclusions: MBSR appears to be a feasible and acceptable intervention to improve mental health among family caregivers with significant care burden, although further studies that include an active control group are needed to make the findings more conclusive. © 2013 S. Karger AG, Basel.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.