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Summary literature en lectures Clinical Assessment & Decision Making
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Clinical assessment & decision makingSamenvatting tentamenstof
Artikel Bayes
Bayes’ rule helps calculate the probability of an individual’s disorder from three elements: the
prevalence of that disorder in the population of that individual, the outcome of a test, and the
psychometric characteristics of that test: it’s sensitivity and specificity.
Prevalence = ‘base rate’ or pre-test probability
Sensitivity = the probability that a patient who actually has a disorder, has a positive score on the test
Specificity = the probability that a patient who does not have a disorder, scores negatively
Posterior or post-test probability = probability after the test has been taken and given the
outcome of the test
Whether a high level of certainty about the absence of presence of a disorder is used in
order to determine what the best goal of a test is → e.g. exclude a disorder or diagnose a
disorder (treatment indication).
,When the prevalence of the disorder is very low, a positive test result will never translate to
a very high probability of the disorder even when the sensitivity and specificity of a test are
good.
Patients with a certain disorder visit their GP more often than patients without a certain
disorder → thus the prevalence is higher among the patients who come for consultation → a
rough guideline is to double the prevalence based on practice registrations.
Lecture 1
4 basic questions of psychological assessment:
- Classification (does this person had disorder A?)
- Explanation (why does s/he refuse to eat?)
- Prediction and indication (will CBT help this person?)
- Evaluation (was the intervention successful?)
Psychological assessment: a shared decision-making process in which a clinician iteratively
defines a diagnostic question, formulates and tests hypotheses about the client’s cognitive
functions and behaviour, and integrates the information thus collected from a number of
sources and using different methods based on scientific psychology in a dynamic fashion,
resulting in a representation and understanding of the problem that is shared with the client
in such a way that relevant indications for treatment or care ensue.
Flowchart of the psychological assessment
1. Can you accept this referral?
2. Is there an emergency?
3. Is it useful to include an explanatory analysis?
Normal range is determined by boundaries → abnormality is 2 SD away from mean
Vulnerability hypothesis: certain personality traits make one vulnerable for the development
of disorders
Scar hypothesis: a disorder affects ones personality
Spectrum hypothesis: personality and disorders to be considered as a continuum
, Transference: behaviour that the patient is showing towards you
Countertransference: feelings and thoughts you have about the patient (don’t show_
Classifying is not diagnosing!
➔ Structural clinical interview (SCID) or shorter version (MINI)
➔ Not just ‘ticking boxes’, but also active thinking required
Personality disorders: organized in 3 main clusters
- Cluster A: Odd and Eccentric
o Show symptoms that others see as bizarre
- Cluster B: Dramatic and Erratic
o Display behaviours that are overly dramatic and difficult to predict
- Cluster C: Fearful and Anxious
o Cause interpersonal friction due to the individual’s inability to face certain
fears
Lecture 2
Classification: another way of representing the symptoms and disorders → networks
➔ Bit more concrete → psychopathology web: network graph of the correlational
relationships between 55 items (symptoms) of the Comprehensive Psychopathology
Rating Scale which form a 6-cluster structure
When use explanatory analysis:
- When there’s no standard treatment for the diagnosed disorder
- When there are several standard treatments for the diagnosed disorder
- More than one disorder has been diagnosed
- When a (standard) treatment has already been implemented but has not worked
- When a classification at a descriptive level is non-informative (e.g.
strength/weaknesses)
- When you want to foster the therapeutic alliance
➔ Otherwise, no → continue to prediction and indication
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