Concepts of Normality/Abnormality Flashcards
Statistical approach to abnormality
Having an attribute or displaying a behaviour that deviates substantially from the statistical norm
Advantages of the statistical approach
Offers some subjectivity and measurability
e.g. IQ to assess learning disabilities
Disadvantages of the statistical approach
Measurement error
- Results are not likely to be the same when the test is taken again
Regression to the mean
- Extreme measures tend to regress to the mean when tested again
- People often present with extreme symptoms and things settle by the time treatment starts
Extreme values do not necessarily imply extreme problems
- Extremely high IQ is not looked at as a problem
Cut off problems
- Where do you draw the cut off, is 0.5% very different to 1%?
Normative approach to abnormality
Based on the assumption that socially normal and acceptable behaviours represent adaptive ways of behaving
Deviation from social norms is viewed as abnormal
Disadvantages of normative approach
Intolerance of individual differences
Norms are socially constructed and arbitrary
Can lead to an abuse of power
Functional approach to abnormality
Based on the notion that someone who is unable to function socially (pay bills, feed themselves, look after their hygiene, hold down a job etc.) may be maladapted or impaired in some way
Disadvantages to the functional approach
Assumes universal needs
- Who is to say that everyone should have a 9-5 job
Based on an individualistic world view
- Too much onus on the individual rather than a holistic view
Tends to expect conformity with societal expectations
Distress-based approach
Based on the individual’s distress or ability/inability to cope with their experiences or problems
Not based on the person’s conformity to societal norms, but their own perspective about what is normal and abnormal
Disadvantages of the distress-based approach
Lack of insight into the nature of their problems or experiences
- Children may struggle to have an insight into their own problems and so physicians may have to compare them to others of their age
Highly subjective
- Lose sight of societal issues
Risk of medicalising normal reactions to adverse circumstances
Why is it important to classify mental disorders?
Research into aetiology, epidemiology, and mechanisms of change
Enables a shared language to recognise and treat problems
Enables the selection of appropriate treatments
Enables us to evaluate interventions
Societal requirements
- Legal
- Organisational
- Financial
Some people don’t have access to treatment without diagnosis
Kraepelinian model
Classified mental disorders on the basis of symptomatology
Entered into the ICD in 1939
Went on to form the DSM in 1952
Merits of the DSM classification system
Specific criteria to diagnose qualitatively similar conditions
Provides diagnostic criteria that can be applied systematically
Provides diagnostic criteria that are theoretically neutral
- Not based on a specific theory such as psychoanalysis
Takes functional impairment into consideration
Enables differential diagnosis
Enabled considerable advanced in epidemiology
- Better understanding of which disorders are prevalent in the general population and what the risks for each of them are
Enabled considerable advancements in drug discovery and disorder-specific psychological treatments
Limitations of the DSM classification
Diagnosis based on the description of symptoms not aetiology
Can give false illusion of an explanation
- A diagnosis doesn’t alleviate distress
Different disorders have similar symptoms
Comorbidity of mental disorders is common
Within-category heterogeneity
- Even with a single label, people’s experience of mental disorders can be very different
Categorical methods does not account for degrees of severity
- This is important for treatment choice
False positives can pathologise normal distress
Can lead to stigmatisation
Can reinforce the sick role
- If you have a diagnosis you may be more likely to adopt the label and become worse than you would have been before the label
Dimensional models
Mental disorders on a continuum with normal experiences
Dimensional models advantages
Accounts for severity
Accounts for overlapping traits
