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DSM-III had aimed to improve the reliability of diagnosis and its field trials suggested that, through using structured clinical interviews, levels of reliability ranging from fair to satisfactory could be achieved between raters. However, this meant that symptoms had to be defined that were simple and obvious, with ‘personal and contextual factors’ omitted (Frances, 2013, p. 25). This raised the risk that the reliability of diagnosis had been prioritised over the validity of the categories. Some have argued that the use of the structured clinical interview for DSM-IV (commonly referred to as the SCID) has not improved reliability (Kutchins and Kirk, 1999). However, even if structured interviews did improve reliability, they are only used by researchers; they are not in everyday use by psychiatrists. Moreover, reliability is no guide to validity. We can all agree on the characteristics of a unicorn or of Santa Claus but that does not mean that either exists in the real world.

The problem of reliability reared its head again when the DSM-5 field trials were published by Freedman et al. (2013). Figure 4.1 shows their reliability results for categories for adults. DSM-5 aimed to develop categories that could be applied by ordinary clinicians with relatively little training and using unstructured clinical interviews. Reliability is measured by the kappa (κ) coefficient, where a score of −1 indicates complete disagreement and a score of 1 indicates complete agreement. Spitzer and Fleiss’s (1974) article implies that a kappa value of 0.4–0.7 is no better than fair agreement, but the DSM-5 field trial team labelled this range as running from ‘good agreement’ to ‘very good agreement’, as shown by the blue and green bars respectively in Figure 4.1. This decision was treated with derision by Allen Frances, the chair of DSM-IV, who argued that ‘DSM-5 announced it would accept agreements among raters that were sometimes barely better than two monkeys throwing darts at a diagnostic board’ (Frances, 2013, p. 175).

Figure 4.1 The results of the DSM-5 field trials (Source: adapted from Freedman et al., 2013, p. 2)

The poor reliability of DSM-5 categories was matched by their poor level of validity. This chapter began by explaining that psychiatric diagnosis is an attempt to use a medical approach to assess problems in living. Medical diagnosis is essentially a process of identifying patterns and comparing problems with the descriptions found in diagnostic manuals. In medicine, clinicians base diagnoses on signs and symptoms. These are often used interchangeably but they are quite different. A sign refers to something that is observable to others or some kind of objective evidence, such as the results of laboratory tests (e.g. of blood or urine). A symptom, on the other hand, refers to a person’s subjective self-report of something that is not observable by others and for which no objective test is available (e.g. a headache). Throughout the history of the DSM it has been rather embarrassing that, in comparison with many medical diagnoses, for most ‘functional’ psychiatric diagnoses there are no signs, only symptoms. This issue led to a remarkable public spat between the DSM-5 director David Kupfer and the NIMH director Thomas Insel. Just 18 days before the publication of DSM-5, Insel announced that the NIMH would be ‘re-orienting its research away from DSM categories’ because of their ‘lack of validity’ since they were not based on ‘any objective laboratory measure’ (Insel, 2013). Four days later, Kupfer released a statement noting that ‘We’ve been telling patients for several decades that we are waiting for biomarkers. We’re still waiting.’ (Kupfer, 2013).

Sixty years after the publication of DSM-I, psychiatrists appeared to agree that there were still no signs (i.e. objective measures) for most psychiatric diagnoses. As a result, disorders were constructed by clustering symptoms together largely on the basis of consensus among groups of psychiatrists. However, the psychiatrists involved in each edition of the DSM often grouped these symptoms and categories in different ways. Although both Insel and Kupfer identified a problem, neither entertained the idea that the conceptual framework used in medicine might not be applicable to problems in living – this issue will be discussed in greater detail in Chapter 8.

A continuing challenge for diagnosis has been that some socio-demographic groups are more likely to be given some diagnoses than others (Cromby, Harper and Reavey, 2013). How might we understand, for example, the fact that, according to DSM-5, women are more likely to be given a diagnosis of major depressive disorder while men are more likely to be given diagnoses of substance use disorders? Does this reveal bias on the part of clinicians? Are men and women exposed to different kinds of life events? Is it more socially acceptable for men to express distress through substance misuse and for women by becoming depressed, or are there other reasons?

Moreover, because diagnosis involves subjective judgement, it can be influenced by social norms. It could be argued, for example, that diagnosis involves comparing what a person says with an implicit idea of what it means to be ‘normal’. A lot depends, therefore, on the kinds of implicit assumptions the diagnoser makes. For example, DSM-5 warns about the dangers of cultural bias in diagnosing paranoid personality disorder. Rates of paranoia are higher in some BAME groups. It has been argued that, because these groups have often experienced racism, a wariness of others is an understandable response rather than a sign of pathology (Cromby, Harper and Reavey, 2013).