Normality- ‘being within certain limits that define the range of normal functioning’.
In the psychological and psychiatric domain, this concept has been the topic of much debate in recent years, especially when related to changing definitions in the DSM IV. When does just being sad for a while become ‘depression’ (DSM definition: depressed mood most of the day, nearly every day, for 2 weeks alongside two other symptoms) and why can we only suffer from the completely normal act of bereavement for 2 months (The symptoms are not better accounted for by Bereavement, i.e., after the loss of a loved one, the symptoms persist for longer than 2 months) before it becomes ‘abnormal’?
‘Normality’ causes a problem for psychiatric research because when looking at a clinical population ‘controls’ should be anyone without the disorder you are investigating, however this is often not the case and we tend to study ‘hyper-normal’ people, with no history of Any mental health problems. This is a problem because one in four of us will suffer from a mental health problem in our lifetimes, therefore making it a lot more ‘normal’ than many people realise. So when investigating how often a particular symptom is present in the ‘normal, healthy population’ we are potentially lessening the prevalence of experiences from the healthy population by poor sampling methods.
This is discussed nicely in the following paper by Schwartz and Susser.
Realistically people should slot into one category or another. For example, in a Psychosis study you could either be classed as a patient ‘one who has suffered a psychotic symptom that is clinically significant’ or you can be a control ‘one who has NOT suffered from a psychotic symptom’.
Hopefully, research in the future will go more by this way of thinking to get a better idea of the ‘general population’.