Student Blog: “One in four people have been diagnosed with a mental illness”

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This article from the website ‘Wired’ explains that one in four adults suffer from and are diagnosed with mental illness in England. This conditioned behaviours surveyed include; anxiety, phobias, eating disorders, depressing, alcohol dependency etc. The study fails to add a single time period to the statistical claim to explain if the diagnosis was given in a month, year or during their whole lifetime. This therefore means that the findings can be misinterpreted for one in four people being diagnosed with mental illness over a life time.

This article used statistics from a survey which was conducted by National Centre of Social Research which had found similar results to Health Survey for England 2014. The survey asked 5000 adults about their experience about mental health where they were asked about their mental illness diagnosis and if it has fit into one or more of the 17 different diagnoses options. This approach of quantifying mental illness to categories has limitation as certain illness are just labelled with an umbrella term which narrows the diagnosis. Additionally those surveyed may not always see their diagnoses fitting into one category and may believe that they fit into two or more different types of mental health disorder. This can therefore produce incorrect and invalid statistics. An example of this is depression where there are many different forms of depression and each respondent may interpret this diagnoses different compared to another.

The sample size can be seen as representative to the wider population however few of the respondent who were diagnosed with a mental illness was self-diagnosed (18%). This survey therefore relies on the individual’s perception and personal judgement of mental illness symptoms rather than a profession/ expert opinion. Respondents who were self-diagnosed and diagnosed by experts also were required to use their memories to answer questions which can make the findings inaccurate leading to an unreliable statistical claim.

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