Health Promotion Monitoring and Evaluation Training Course

Participants can define a measurable health promotion problem and identify its principal determinants.

• Problem trees separating health outcomes, behaviours, determinants and root causes
• Behavioural, social and environmental determinants affecting priority population groups
• Epidemiological data interpreted alongside community perceptions and service-use evidence
• Equity analysis by sex, age, disability, geography and socioeconomic status
• Stakeholder mapping for communities, providers, authorities, funders and implementing partners
• Prioritisation criteria balancing burden, feasibility, equity and programme influence

Participants can construct a testable theory of change for a health promotion intervention.

• Theory of change components: interventions, mechanisms, outcomes, assumptions and context
• Causal pathways connecting communication, capability, opportunity, motivation and behaviour
• COM-B model applied to barriers affecting health-related behaviour
• Assumptions tested against social norms, service availability and policy conditions
• Feedback loops and unintended consequences identified within intervention pathways
• Outcome pathways differentiated for individuals, households, communities and institutions

Participants can prepare a results framework that aligns intervention activities with intended results.

• Logical framework hierarchy aligned with a health promotion theory of change
• Outputs specified as deliverables rather than meetings, sessions or materials distributed
• Outcome statements written with population, behaviour, direction and timeframe
• Impact statements linked to plausible population health changes
• External risks recorded with probability, consequence and response actions
• Vertical logic checked for sufficient conditions and realistic causal contribution

Participants can select valid indicators for programme reach, quality, behaviour and outcomes.

• Indicator selection criteria: validity, reliability, feasibility, utility and sensitivity
• Reach indicators measuring intended audiences, exposure and participation patterns
• Behaviour indicators measuring adoption, maintenance and self-reported practice
• Service uptake indicators linked to referral completion and care-seeking behaviour
• Outcome indicators distinguished from outputs and implementation process measures
• Disaggregation requirements specified for equity-sensitive health promotion indicators

Participants can produce indicator reference sheets and realistic performance targets.

• Indicator reference sheets defining numerator, denominator, unit and calculation method
• Data sources matched to indicator frequency, quality and access constraints
• Baseline values distinguished from targets, milestones and performance thresholds
• Target setting informed by historical trends, programme intensity and contextual constraints
• Proxy indicators assessed for validity when direct measurement remains impractical
• Metadata documented for indicator ownership, reporting deadlines and revision control

Participants can develop an operational monitoring plan for routine programme management.

• Monitoring plan linking indicators, sources, frequencies, responsibilities and users
• Data flow mapping from community workers through district and national reporting
• Reporting calendars aligned with management meetings, donor deadlines and supervision cycles
• Roles assigned using a RACI matrix for data collection and approval
• Routine review questions focused on coverage, quality, equity and implementation delays
• Escalation procedures defined for missing reports, anomalies and safeguarding concerns

Participants can assess routine data sources and specify appropriate digital collection arrangements.

• Routine health information system data assessed for completeness and timeliness
• DHIS2 aggregate reporting strengths and limitations for health promotion indicators
• Registers, referral forms and attendance records designed for minimum data burden
• KoboToolbox forms configured with validation rules, skip logic and constraints
• Unique identifiers considered for repeat contacts while protecting participant privacy
• Data dictionaries standardising variable names, response options and coding conventions

Participants can plan a baseline assessment that establishes credible starting values for key indicators.

• Baseline purpose defined against decisions, indicators, populations and intervention timing
• Secondary data review assessing relevance, recency, completeness and comparability
• Baseline protocols specifying instruments, sampling, fieldwork and analysis responsibilities
• Questionnaire items adapted from validated health and behaviour measurement instruments
• Pretesting procedures identifying unclear wording, cultural issues and response burden
• Baseline reports presenting values, limitations and implications for target refinement

Participants can select and document sampling approaches for monitoring and evaluation studies.

• Target populations, sampling frames and eligible respondents clearly specified
• Probability sampling methods: simple random, systematic, stratified and cluster sampling
• Purposive sampling applied to key informants, marginalised groups and programme implementers
• Sample size drivers include precision, expected prevalence, design effect and non-response
• Household selection procedures reducing interviewer discretion and selection bias
• Sampling limitations communicated without overstating population-level conclusions

Participants can establish data quality assurance procedures for routine and survey data.

• Data quality dimensions: accuracy, completeness, timeliness, consistency and integrity
• Routine data quality assessment verifies reported values against source documents
• Verification factors calculated for selected indicators and reporting periods
• Field supervision checklists assess consent, interviews, registers and observation practices
• Range checks, duplicate checks and missing-value checks applied before analysis
• Corrective action logs assign owners, deadlines and verification of resolution

Participants can apply ethical, safeguarding and data protection requirements to M&E activities.

• Informed consent procedures matched to respondent age, literacy and study risk
• Confidentiality protections for sensitive health, sexual behaviour and violence-related information
• Data minimisation applied when collecting personally identifiable participant information
• Safeguarding referral pathways prepared before interviews with at-risk populations
• Ethical review requirements distinguished from routine programme monitoring approvals
• Secure storage, access controls and retention schedules documented for collected data

Participants can assess whether a health promotion intervention was delivered as planned.

• Process evaluation questions address reach, dose, fidelity, adaptation and acceptability
• Implementation fidelity assessed against protocols, session plans and service standards
• Dose delivered and dose received measured for multi-component interventions
• Adaptations classified as planned, reactive, beneficial or potentially harmful
• RE-AIM dimensions used to structure implementation and reach assessment
• Implementation findings translated into corrective actions for delivery teams

Participants can select evaluation designs appropriate to intervention maturity, resources and decision needs.

• Evaluation questions framed around effectiveness, equity, contribution, efficiency and sustainability
• Pre-post designs used cautiously when comparison groups remain unavailable
• Quasi-experimental designs include difference-in-differences, matching and interrupted time series
• Comparison groups assessed for similarity, contamination risk and ethical feasibility
• Contribution analysis tests causal claims through evidence, assumptions and alternative explanations
• OECD DAC criteria adapted for health promotion evaluation questions

Participants can analyse and interpret common quantitative health promotion indicators.

• Descriptive statistics summarise frequencies, proportions, means and distribution patterns
• Percentage-point changes distinguished from relative percentage changes in reporting
• Cross-tabulations compare outcomes by sex, age, location and vulnerability status
• Confidence intervals interpreted without confusing statistical significance and programme importance
• Trend charts display progress, seasonality, targets and data quality concerns
• Denominator checks prevent misleading coverage, uptake and completion rate claims

Participants can plan and use qualitative inquiry to explain programme results and implementation experience.

• Focus group discussions explore norms, perceptions, barriers and intervention acceptability
• Key informant interviews gather perspectives from providers, leaders and decision-makers
• Topic guides align questions with theory of change assumptions
• Framework analysis codes responses against predefined and emergent themes
• Triangulation compares qualitative accounts, monitoring data and survey findings
• Participant quotations selected ethically without exposing identities or sensitive details

Participants can integrate equity, gender and participation into health promotion M&E systems.

• Equity-focused questions identify who benefits, who misses out and why
• PROGRESS-Plus characteristics guide systematic analysis of health inequities
• Gender analysis examines roles, power, access, norms and decision-making
• Community feedback mechanisms document concerns, preferences, complaints and response actions
• Participatory monitoring includes community-defined indicators and local interpretation of findings
• Disaggregated results interpreted carefully where small samples threaten confidentiality

Participants can prepare decision-focused reports and visual displays for programme stakeholders.

• Performance dashboards prioritise decision-critical indicators rather than reporting every measure
• Charts selected according to comparison, trend, composition and distribution questions
• Data stories connect findings, explanation, implications and recommended management actions
• Traffic-light ratings supported by transparent thresholds and source documentation
• Donor reports reconcile narrative claims with indicator tables and evidence
• Management briefs distinguish confirmed findings, plausible explanations and information gaps

Participants can organise evidence review processes that lead to documented programme decisions.

• After-action reviews identify what happened, why and what changes follow
• Pause-and-reflect sessions convert monitoring findings into implementation decisions
• Decision logs record evidence considered, actions approved, owners and deadlines
• Learning agendas prioritise unresolved assumptions and high-value evidence gaps
• Recommendation tracking monitors management response and completion of agreed actions
• Stakeholder dissemination plans tailor messages, formats and timing to information needs

Participants can commission and manage a credible external or internal health promotion evaluation.

• Terms of reference define purpose, scope, questions, methods and deliverables
• Evaluation budgets account for fieldwork, translation, analysis, dissemination and contingencies
• Evaluator selection criteria assess technical expertise, independence and contextual knowledge
• Inception reports reviewed for methodological alignment, feasibility and ethical safeguards
• Quality assurance plans specify review points, evidence standards and acceptance criteria
• Management responses convert evaluation recommendations into accountable implementation plans

Participants can build, review and present a complete monitoring and evaluation package for a health promotion intervention.

• Health promotion problem statement refined using evidence and equity considerations
• Theory of change presented with assumptions, pathways and measurable outcomes
• Results framework and indicator reference sheets checked for internal consistency
• Monitoring plan specifies data flows, responsibilities, quality controls and reporting cycles
• Evaluation design justifies methods, sampling, ethics and analysis approach
• Peer review applies structured criteria to feasibility, utility and measurement quality
• Final presentation defends evidence choices, implementation priorities and management use