Definitions of abnormality: statistical infrequency
The statistical infrequency definition of abnormality sees behaviours that are statistically rare as being abnormal. Data are collected about various behaviours and personal characteristics, so that their distributions throughout the general population can be calculated and plotted. This then allows the formation of normal distributions for these behaviours and characteristics. Normal distribution concerns the idea that for any given behaviour or characteristic there will be a spread of scores that forms a bell-shaped curve. Most people’s scores occur on or around the mean and a decreasing amount of scores occur on either side of the mean, further away from the norm. This means there will be a symmetrical distribution of scores (as many scores below the mean as above the mean). Any scores that fall outside of normal distribution, which is usually seen as being 2 standard deviation points away from the mean (about 5 per cent of a population, which is 1 in 20 people), are regarded as abnormal in this definition. So taking intelligence, for example, data are collected on an individual’s IQ scores (seen as being a valid measurement of intelligence, though this is disputed by many psychologists) and then used to plot the distribution of IQ scores on and around the mean. The mean score for IQ is supposed to be 100 IQ points and most individuals will be seen to score on or around this amount of measured intelligence. Decreasing amounts of people will have IQ scores that are further away from the norm (either above or below it) and therefore the data form the classic bell-shaped (also known as the Gaussian) curve. Two standard deviation points below the norm brings us to a score of 70 IQ points and 2 standard deviation points above the norm brings us to 130 IQ points. In terms of the definition, the 5 per cent of people in total who score below and above these levels are classed as abnormal, as they fall outside the normal distribution.
The statistical infrequency definition does nothing more than create the statistical criteria upon which behaviours and personal characteristics can be deemed to be normal or abnormal; it makes no judgements about quality of life or the nature of mental disorders.
Fig 4.3 Standard deviation
The definition makes no value judgements about what is or is not abnormal. So, for example, homosexuality, once defined as a mental disorder under earlier versions of diagnostic criteria, would not be seen under this definition as ’morally wrong’ or ’unacceptable’ — instead it would be viewed merely as less statistically frequent than heterosexuality.
There are definite examples of situations where statistically determined criteria can be used to decide abnormality — for example, with mental retardation, where individuals will suffer with severe learning difficulties and thus need assistance with day-to-day living.
The definition is a very objective one, as it relies on real, unbiased data. Once data about a behaviour or personal characteristic have been collected, the information becomes a very non-subjective and value-free means of deciding who is abnormal and who is not.
The definition also permits an overall view of which particular behaviours and characteristics are infrequent within the population and so can help us determine which behaviours and characteristics can be regarded as abnormal.
A major weakness of the definition is that not all statistically infrequent behaviours are actually abnormal. Many statistically rare behaviours and characteristics are desirable rather than undesirable ones. For example, being highly intelligent (determined by normal distribution, as being above around 130 IQ points) is indeed statistically rare, but would be regarded as desirable.
Although the definition claims to be objective in not using value judgements, but instead statistical data, to determine what deviations in behaviour and characteristics are to be considered abnormal, a judgement is made about where exactly to draw the line. Indeed some mental disorders, like depression, vary greatly between individuals in terms of severity, but the definition does not account for this.
Not all abnormal behaviours are statistically infrequent. Some statistically frequent and therefore ’normal’ behaviours are actually abnormal. For instance, about 10 per cent of people are chronically depressed at some point in their lives, which would be so common as not to be seen as statistically rare and hence abnormal.
A practical application of the definition is that as it is based purely on objective data, with no subjective judgements made about what is and what is not abnormal, it gives mental health practitioners a clear indication of when an individual needs clinical help. It can therefore be used as objective evidence to decide when an individual needs treatment.