How can a robot help your mental health?

2020 ◽  

Cath Kitchen, Head Teacher and Project Manager for the DoE AV1 project, and Zoe Johnson ‘Zobot’ explain how this innovative device is helping young people with long term physical and mental health issues to ‘virtually’ attend school.

2020 ◽  

Cath Kitchen, Head Teacher and Project Manager for the DoE AV1 project, and Zoe Johnson 'Zobot' explain how this innovative device is helping young people with long term physical and mental health issues to 'virtually' attend school.


2019 ◽  
pp. 125-142
Author(s):  
Usha S. Nayar ◽  
Priya Nayar

The new media is characterized by the convergence of technologies that allow information to be acquired, sorted, packaged and transmitted in multiple ways. This chapter focusses on how new media use has provided an opportunity to young people and affected their everyday lives. It also draws attention to the risk behaviours among young people associated with excessive television viewing. Some of the examples include physical and mental health issues around aggression, cyberbullying, addiction, violence, obesity, and loss of values. The empowerment potential of new media tools and technologies for adolescent self-identity is also examined. The problem of accessibility to new media and the increasing socio-economic divide are also examined. The issue of media policies for regulation vs. human rights is also discussed. The authors note the paucity of research in this area and indicate the need for further research.


SecEd ◽  
2020 ◽  
Vol 2020 (2) ◽  
pp. 17-23
Author(s):  
Pooky Knightsmith

Every day, school staff will encounter students struggling with issues of mental health. In this practical guide, Dr Pooky Knightsmith looks at spotting the signs, the common mental health issues, how to intervene, talk and listen to young people, referring successfully to CAMHS, and eight tips for supporting young people


2019 ◽  
pp. 94-104
Author(s):  
Spencer James Zeiger

How does one know when it’s time to leave the academy and begin The Next Chapter? Some will have the luxury of planning their transition months or even years in advance. Others will reach a point where work conditions become intolerable. Still others may be rudely sacked with little or no notice, perhaps through no fault of their own. Some participants believed physical and mental health issues are motivating factors. For others, taking advantage of a university early retirement was an incentive. Some viewed moving to the next chapter as a natural progression. And for a few, it may be a way to end the misery; they’ve left angry. Categories discussed in this chapter include fear, timing, planning, recognizing when the thrill is gone, burnout, and reduced energy.


2002 ◽  
Vol 26 (4) ◽  
pp. 19-25 ◽  
Author(s):  
Annabelle Bundle

Annabelle Bundle presents the results of a qualitative study, undertaken in a mixed residential children's home, which aimed to identify what looked after young people see as important in terms of health information. The young people wanted information particularly on mental health issues, keeping fit, substance use and sexual health. Many were reluctant to request appointments for personal matters and did not feel they were encouraged to ask about personal health concerns during medical examinations.


2012 ◽  
Vol 48 (6) ◽  
pp. 965-973 ◽  
Author(s):  
James D. Livingston ◽  
Andrew Tugwell ◽  
Kimberly Korf-Uzan ◽  
Michelle Cianfrone ◽  
Connie Coniglio

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 95-95
Author(s):  
Taylor Jansen ◽  
Richard Chunga ◽  
Chae Man Lee ◽  
Shuangshuang Wang ◽  
Haowei Wang ◽  
...  

Abstract Mental health issues in older adults are prevalent, yet often undetected or untreated and can contribute to poor physical health, increased disability, and higher mortality rates. The current study describes state and local community rates of mental health indicators of older adults 65+ in MA, NH, and RI. Data sources used to calculate rates were: the American Community Survey (2009-2013 RI, 2012-2016 MA and NH), the Medicare Current Beneficiary Summary File (2012-2013 RI, 2015 MA and NH), and the Behavioral Risk Factor Surveillance System (2012-2014 RI, 2013-2015 MA, and 2014-2016 NH). Small area estimation techniques were used to calculate age-sex adjusted community rates for more than 150 health indicators. This research examines disparities in rates for 3 mental health indicators depression, self-reported poor mental health, and self-reported poor/fair health status. Depression rates: MA 31.5% (19.91-48.82%), RI 30% (19.7-38.5%), and NH 28.8% (18.26-40.56%). Self-reported poor mental health: RI 7.5% (4.8-12.5%), MA 7.0% (2.10-16.59%), and NH 6.9% (3.42-10.13%). Self-reported fair/poor health: RI 20.4% (8.6-38.8%), MA 18.0%, (7.2-34.38%), and NH 16.5% (13.31-21.60%). Results showed variability in rates across states. MA had the highest rates of depression, the greatest differences in rates, and access to the most mental health providers. RI had the highest community rates for poor physical and mental health, and the highest percentage of residents age 85+. Understanding the distribution of community rates makes disparities evident, and may help practitioners and policymakers to allocate resources to areas of highest need. Research funded by the Tufts Health Plan Foundation.


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