mental health

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Many autistic children perceive the sensory world around us differently. Some autistic children for example are overwhelmed by sounds or touch. This can make everyday situations such as visiting a busy supermarket a challenging task for families, and being overly sensitive has also been linked to anxiety.

A new project being conducted at the University of Reading’s Centre for Autism and funded by the charity MQ  will explore if sensory reactivity, such as being oversensitive to sounds, can predict later anxiety and related mental health symptoms.

The team will follow autistic children for 2 years, starting at age 4, asking caregivers questions about how their child reacts to the sensory world around them, such as sounds and lights. Children’s reactions towards sensory stimuli directly will also be observed, such as different sounds or a touch by a feather. Using questions about anxiety and related symptoms at all time points, the team will look at whether the relationship between sensory reactivity and anxiety and related mental health issues is stable over time. In addition, they will test if early sensory reactivity can predict later mental health symptoms.

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The ‘language of depression’ can be spotted using computer analysis which looks for patterns of words used by those who are suffering from the disorder, explains Dr Mohammed Al-Mosaiwi in a new post for The Conversation.

Kurt Cobain by Maia Valenzuela/Flickr, CC BY-SA

From the way you move and sleep, to how you interact with people around you, depression changes just about everything. It is even noticeable in the way you speak and express yourself in writing. Sometimes this “language of depression” can have a powerful effect on others. Just consider the impact of the poetry and song lyrics of Sylvia Plath and Kurt Cobain, who both killed themselves after suffering from depression.

Scientists have long tried to pin down the exact relationship between depression and language, and technology is helping us get closer to a full picture. Our new study, published in Clinical Psychological Science, has now unveiled a class of words that can help accurately predict whether someone is suffering from depression.

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