Clinical Assessment and Diagnosis
What to know
Clinical assessment moves from broad data gathering to a defensible formulation. Candidates must understand the difference between screening (brief, rule-out), diagnostic assessment (confirmatory), and ongoing monitoring (treatment response). Know the DSM-5-TR organizing logic: criteria sets, duration and severity specifiers, exclusion of substance/medical causes, and the requirement of clinically significant distress or impairment. Understand psychometric basics - reliability, validity, sensitivity (true positive rate), specificity (true negative rate), base rates, and how prevalence changes predictive values. Be able to distinguish differential diagnosis from comorbidity and to describe structured interviews (e.g., SCID) versus unstructured clinical judgment.
Traps in questions
- Equating a positive screen with a diagnosis; screens generate false positives in low-prevalence settings.
- Forgetting the impairment/distress criterion or the duration threshold.
- Confusing rule-out with rule-in: a good screening tool has high sensitivity, not high specificity.
- Attributing symptoms to a primary disorder when a substance or medical condition better explains them.
- Overlooking cultural idioms of distress and norm-referenced behavior.
Rule of thumb
Diagnose only when criteria are met, alternative explanations are excluded, and impairment is documented. When a stem gives you prevalence and test characteristics, compute predictive value rather than guessing.
Worked example: A screen with 90% sensitivity and 80% specificity is applied where prevalence is 5%. Of 1,000 people, 50 have the disorder; 45 are correctly flagged and 190 are false positives. Positive predictive value is 45/(45+190) ≈ 19% - most positives are false. This is why screens are not diagnoses.