Behavioural, Social and Public Health Sciences: Behaviour, Communication and Population Oral Health
Behaviour change and communication
The exam expects familiarity with the Health Belief Model (perceived susceptibility, severity, benefits, barriers, cues to action, self-efficacy), the Transtheoretical Model (precontemplation through maintenance, with relapse), and Motivational Interviewing (open questions, affirmation, reflection, summarising; rolling with resistance rather than arguing). The 5 A's - Ask, Advise, Assess, Assist, Arrange - structure smoking cessation counselling. Informed consent requires capacity, disclosure of material risks, and voluntariness; substitute decision-makers apply when capacity is absent.
Epidemiology
The core numeracy is a two-by-two table. Sensitivity and specificity are properties of the test; positive and negative predictive values depend on prevalence. Incidence counts new cases over time; prevalence counts existing cases at a point in time. Cohort studies suit rare exposures and give relative risk; case-control studies suit rare outcomes and give odds ratios; RCTs address efficacy but may lack generalisability.
Prevention and public health
Know fluoride mechanisms (topical remineralisation and bacterial enzyme inhibition dominate; systemic effects are minor), water fluoridation as a population-level measure that reduces inequalities, sealants for high-risk pits and fissures, and caries risk assessment combining diet, fluoride exposure, salivary flow, and past caries experience. Social determinants - income, education, food security, Indigenous status, rurality - explain oral health inequities and access barriers within Canada's publicly funded but largely privately delivered system.
Traps
- Recalculating sensitivity when prevalence changes - it stays constant; PPV does.
- Confusing incidence with prevalence in chronic, long-duration disease.
- Equating Motivational Interviewing with advice-giving or education.
- Judging a screening test by PPV alone without considering baseline prevalence.
Worked example
Sensitivity 90%, specificity 90%, prevalence 1% in 10,000 people: true positives 90, false positives 990, so PPV = 90 ÷ (90 + 990) = 8.3% - most positives are false.