Community Psychiatry
This domain tests how services are organised outside hospital: sectorisation, multidisciplinary team working, rehabilitation, recovery and stigma reduction. Questions typically probe the shift from institutional to community care and the evidence for specific community models.
Core models
- Community mental health teams: multidisciplinary, sector-based, provide assessment, treatment and care coordination with a named care coordinator.
- Assertive community treatment: high-fidelity model with small caseloads, shared caseload across a team, frequent contact, 24-hour cover and outreach, shown to reduce hospitalisation in severe illness with frequent admissions.
- Early intervention in psychosis: specialised teams for first-episode psychosis, aiming to shorten duration of untreated psychosis and improve functional outcome.
- Crisis resolution and home treatment: an alternative to admission for acute relapse where risk allows.
- Recovery model: emphasises personal goals, strengths, hope and service-user involvement rather than symptom elimination alone.
- Psychoeducation and family work: reduce relapse and family burden.
- Supported employment using the individual placement and support model outperforms train-then-place vocational schemes.
Key service principles
Care should be delivered in the least restrictive setting, integrated with primary care, and coordinated across transitions because discharge is the highest-risk period for readmission and suicide. Physical health monitoring is a community responsibility, since people with severe mental illness die years earlier than the general population. Stigma reduction requires contact-based interventions, not information alone. Peer support workers add value to engagement. In low-resource settings, task-shifting using supervised non-specialist workers, as in WHO mhGAP, extends reach.
Worked example
A 35-year-old with schizophrenia has had four admissions in two years and repeatedly disengages. Reasoning: frequent admissions plus poor engagement is the classic indication for assertive community treatment with a shared caseload, outreach and medication support, rather than another brief outpatient appointment or long-term inpatient care.
Traps that cost marks
Assuming community care removes coercion. Discharging without a written follow-up plan and named coordinator. Neglecting physical health screening. Confusing rehabilitation with long-stay institutional care. Ignoring carers' needs and burden.
Epidemiology and Mental Health Services
This domain tests whether you can read and criticise numbers: measures of frequency and association, screening statistics, study design and the organisation of services. Questions often give a screening test in a low-prevalence population and ask for the predictive value.
Measures and designs
Incidence is the number of new cases per population at risk per unit time. Prevalence is the proportion of cases at a point or over a period; it rises with longer duration and better survival. Relative risk comes from cohort studies, odds ratio from case-control studies. Cross-sectional studies give prevalence and associations but not causality. Randomised controlled trials answer efficacy questions. DALYs combine years of life lost with years lived with disability and are used in burden-of-disease estimates.
Screening statistics
Sensitivity is the proportion of true cases detected; specificity is the proportion of non-cases correctly excluded. Positive predictive value depends on prevalence: even with high sensitivity and specificity, a rare condition produces many false positives. This is why screening programmes target high-risk groups and require confirmatory assessment.
Service organisation
Services are tiered: primary care, general hospital and community teams, and specialist tertiary units. The treatment gap is the proportion of people needing care who do not receive it, and it is largest in low- and middle-income countries. Cost-effectiveness uses measures such as cost per QALY. Excess mortality in severe mental illness is largely from cardiovascular disease and is a service-quality indicator.
Worked example
A screening test with 90% sensitivity and 90% specificity is applied where prevalence is 1%. Reasoning: in 1,000 people there are 10 true cases, of whom 9 are detected, and 990 non-cases, of whom 99 are falsely positive. The positive predictive value is therefore 9 out of 108, about 8%. Most positives are false, so the test must be followed by diagnostic assessment and should not be applied to the general population without a risk-based strategy.
Traps that cost marks
Confusing incidence with prevalence. Assuming that high sensitivity implies a high predictive value. Drawing causal conclusions from cross-sectional data. Committing the ecological fallacy by applying group-level associations to individuals. Forgetting selection, recall and Berkson bias when appraising studies.