Tuesday July 23, 2019

Childhood Violence May Spur Puberty, Depression: Study

The association between the ageing metrics and symptoms of depression may offer a way for doctors to identify children who need help, the researchers said

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Depression is a major issue affecting millions of people, especially the teenagers. Pixabay

Children who are exposed to violence such as physical, emotional, or sexual abuse are more likely to experience faster biological ageing, including pubertal development and increased symptoms of depression, finds a research.

The study showed that in children who experienced early life violence, accelerated epigenetic ageing was associated with increased symptoms of depression.

This means that faster biological ageing may be one way that early life adversity “gets under the skin” to contribute to later health problems.

Conversely, children exposed to forms of early life deprivation including neglect and food insecurity were more likely to experience their puberty at a later stage compared with their peers, the researchers said.

“The findings demonstrate that different types of early-life adversity can have different consequences for children’s development,” said Katie McLaughlin, postdoctoral student at the University of Washington.

350 million people are known to suffer depression Pixabay
The study showed that in children who experienced early life violence, accelerated epigenetic ageing was associated with increased symptoms of depression. Pixabay

For the study, published in the journal Biological Psychiatry, the team examined 247 children and adolescents aged eight to 16 years.

The results indicated that accelerated ageing following exposure to violence early in life can already be detected in children as young as eight years old.

In addition, the team found that there is a need for increased societal investment in reducing the exposure of children to violence and for biomedical and psychological research to reduce the impact of these experiences throughout the lives of these vulnerable individuals.

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The association between the ageing metrics and symptoms of depression may offer a way for doctors to identify children who need help, the researchers said.

“Accelerated epigenetic age and pubertal stage could be used to identify youth who are developing faster than expected given their chronological age and who might benefit from intervention,” McLaughlin noted. (IANS)

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Novel AI Tool to Detect Depression Via Sound of Your Voice

Such a tool could prove useful to support work with care providers or to help individuals reflect on their own moods over time

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Depression is a major issue affecting millions of people, especially the teenagers. Pixabay

India — the sixth most depressed country in the world — has an estimated 56 million people suffering from depression and 38 million from anxiety disorders, according to a recent report by the World Health Organisation (WHO).

To help identify depression early, scientists have now enhanced a technology that uses Artificial Intelligence (AI) to sift through sound of your voice to gauge whether you are depressed or not.

Computing science researchers from University of Alberta in Canada have improved technology for identifying depression through vocal cues.

The study, conducted by Mashrura Tasnim and Professor Eleni Stroulia, builds on past research that suggests that the timbre of our voice contains information about our mood.

Using standard benchmark data sets, Tasnim and Stroulia developed a methodology that combines several Machine Learning (ML) algorithms to recognize depression more accurately using acoustic cues.

A realistic scenario is to have people use an app that will collect voice samples as they speak naturally.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

“The app, running on the user’s phone, will recognize and track indicators of mood, such as depression, over time. Much like you have a step counter on your phone, you could have a depression indicator based on your voice as you use the phone,” said Stroulia.

Depression is ranked by WHO as the single largest contributor to global disability. It is also the major contributor to suicide deaths.

The ultimate goal, said researchers, is to develop meaningful applications from this technology.

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Such a tool could prove useful to support work with care providers or to help individuals reflect on their own moods over time.

“This work, developing more accurate detection in standard benchmark data sets, is the first step,” added Stroulia while presenting the paper at the Canadian Conference on Artificial Intelligence recently. (IANS)