Classification & Research. The study of mental disorder involves: Definition: What do we mean by mental disorder? Classification: How do we distinguish.

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Presentation transcript:

Classification & Research

The study of mental disorder involves: Definition: What do we mean by mental disorder? Classification: How do we distinguish between different mental disorders? Explanation: How do we understand mental disorder? Treatment: How do we treat mental disorder?

Example Animal Dog Cat

LINNAEAN CLASSIFICATION Kingdom: Animalia Phylum: Chordata Subphylum: Vertebrata Class: Mammalia Subclass: Theria Infraclass: Eutheria Order: Primates Suborder: Anthropoidea Superfamily: Hominoidea Family: Hominidae Genus: Homo Species: sapiens

Why is it important to classify mental disorders? Scientific communication and research Treatment

Classification and Diagnosis Classification systems exists before and independently any individual Individual people are said to be diagnosed or put into the classification system based on a psychological assessment

Evaluating classification systems and assessment tools? Reliability: Gives the same answer with repeated measurement or assessment Test re-test Inter-rater or inter-judge

Evaluating classification systems and assessment tools? Validity: Measures or assesses what it claims to measure Descriptive, construct Predictive

Three broad ways to classify mental disorder Categorical Approach Dimensional Approach Prototypal Approach

Categorical Approach Characteristic of medical diagnostic systems. Assumptions: Behavior can be divided into categories of “healthy” and “disordered”. There are discreet, non-overlapping types of “disorder” Members of each diagnostic group share the same features.

Dimensional Approach Characteristic of personality assessment approaches. Assumptions: Behavior comes from different strengths/intensities of underlying attributes (e.g., aggressiveness, introversion). People differ along a continuum of normality to abnormality on these dimensions.

Prototypal Approach There are imperfect but recognizable combinations of characteristics that cluster together. These imperfect clusters define abnormal behavior. Assumptions: No people share all of the features of the prototype. All people share most of the features of the prototype.

Defines what is abnormal Classifies mental disorders into different sub- types and provides defining criteria Medical tradition: Categorical in intention Prototypal in practice

DSM-IV Created with assumptions of the categorical approach BUT… Central features of Dx categories are sometimes unclear. Many shared features between Dx categories. Large amount of co-morbidity.

DSM-IV DSM-IV classification is prototypal because... Fuzzy boundaries between categories. Overlap of categories themselves.

DSM-IV: A short history DSM = Diagnostic and Statistical Manual (of mental disorders) Currently in 4th edition (May, 1994).

DSM I and II: Included a lot of jargon. Narrative categories. Categories not well defined. Generally not reliable. DSM III (1980): Radically new approach...

DSM-III Precise definitions of Dx categories. Necessary requirements to meet Dx category. First attempts to establish reliability and validity for Dx categories.

DSM-IV Latest edition (1994) Five Axis structure: Axis I - Clinical Syndromes Axis II - Personality Disorders Axis III - Related Medical Conditions Axis IV - Psychosocial and Environmental Problems Axis V - Global Assessment of Functioning.

DSM-IV criticisms: 1. Long-term outcome of disorders is largely unknown. 2. Still little known about etiology. 3. High co-morbidity among Dx. 4. Reliability emphasized at expense of validity (?)

DSM-IV criticisms cont. 5. Perpetuation of flawed Dx categories (from past DSMs). 6. Too many dimensions require rating.

Classification Problems Labeling Pseudo-explanations Lack of reliability

Classification Advantages: Communication shorthand Treatment planning Etiology Aid to scientific investigation

Further Exploration: Classification Millon, T. (1991). Classification in Psychopathology: Rationale, Alternatives, and Standards. Journal of Abnormal Psychology, 100(3), Krueger, R., Piasecki, T., M. (2002). Toward a dimensional and psychometrically-informed approach to conceptualizing psychopathology. Behaviour Research and Therapy, 40,

Research Methods and Critical Thinking

Observation Like all sciences the “bedrock” is observation/description Observation as theory free or theory laden Description determines what we can then later say about a phenomenon Reliability and Validity

Hypotheses & Predictions Hypothesis: A claim about observations/descriptions that could be true or false that attempts to explain or understand the world Tested by making predictions Prediction: also important from a clinical point of view, not just to test hypotheses Can predict without understanding

Understanding Understanding: Usually means “what causes X” could also mean “what is it like, or what does it mean to a person to have X”

Causality: Requirements for inferring causality: 1) Covariation - purported cause and observed effect vary together. 2) Temporal Precedence - purported cause occurs before the observed effect. 3) Exclusivity - the purported cause is the only thing that can explain the observed effect.

Correlation / Covariation vs. Causation Hypothesis: Stress causes depression Need to show that depressed people (Criterion Group) had higher stress levels, before becoming depressed, than other people who do not become depressed (Control Group).

Control / Intervention Without understanding it is hard to control or intervene

Research Designs Intensive observation of a single case Observation of groups

Internal and External Validity Internal validity The study can make accurate conclusions because there are no confounds or alternative explanations External validity The results can be generalized to people outside the study

Sampling and Generalization Population: Everyone who has the mental disorder that you want to make claims about Sample: A smaller group of people from the lager population of interest Random Sampling: Everyone in the population has an equal chance of being in the sample

Sampling and Generalization If the sample is not random, or not a good mix of all the people that have the mental disorder then the conclusions may not have external validity or may not generalize

Methods of Control Manipulating or systematically changing one variable while controlling or holding constant other variables Allows us to conclude that any observed effects of changing a variable are really due to it and not other variable