Every behavioral health program, educational intervention, and human services initiative deserves rigorous evaluation. Program evaluation bridges research and practice — it uses scientific methodology not for knowledge generation alone, but to answer the practical question: "Is this program working, for whom, under what conditions, and at what cost?" PSY5140 trains psychologists to be evaluation practitioners who can design, conduct, and communicate evaluations that inform real decisions.
The logic model: foundation of program evaluation
A logic model is a visual representation of the theory connecting a program's resources and activities to its expected outcomes. Developed extensively by the W.K. Kellogg Foundation (Logic Model Development Guide, 2004) and the United Way, logic models typically show: Inputs (staff, funding, facilities, partners) → Activities (what the program does) → Outputs (direct products: number of sessions delivered, clients served, materials distributed) → Short-term Outcomes (immediate changes in knowledge, attitudes, or skills) → Medium-term Outcomes (changes in behavior, practice, or decision-making) → Long-term Outcomes (changes in conditions, status, or systems). Logic models operationalize the program's theory of change — the causal pathway through which inputs and activities are hypothesized to produce outcomes. A well-constructed logic model is the evaluator's first and most important document: it aligns stakeholder expectations, identifies measurable indicators for each component, and exposes faulty causal assumptions before the program launches.
Types of program evaluation
- Needs assessment: Before designing a program, what evidence exists that a problem requires intervention, who is affected, and what resources already exist? Needs assessment methods include: surveys, focus groups, key informant interviews, epidemiological data analysis, community asset mapping, and services utilization data. Needs assessments anchor program design in evidence rather than assumption.
- Process (formative) evaluation: Ongoing data collection during program implementation to assess fidelity (is the program being delivered as designed?), reach (is it reaching the intended population?), and dosage (are participants receiving sufficient exposure?). Process evaluation identifies implementation problems early enough to correct them. Fidelity checklists and participant attendance records are common process evaluation tools.
- Outcome (summative) evaluation: Does the program achieve its intended short- and medium-term outcomes? Pre-post designs (single-group pre-test/post-test), quasi-experimental designs (comparison group without randomization), and experimental designs (RCT with random assignment) answer outcome questions with increasing rigor. Each design has different feasibility and validity trade-offs that evaluators must navigate in real-world settings.
- Cost analysis: Cost-effectiveness analysis (cost per unit of outcome achieved, e.g., cost per client who achieves abstinence), cost-benefit analysis (monetizing both costs and benefits to calculate ROI), and budget analysis. Funders increasingly require cost data alongside outcome data.
- Utilization-focused evaluation (Patton, 1997): Evaluation designed explicitly to be used — stakeholders and intended users are involved throughout to ensure findings are relevant, credible, and actionable. The most technically rigorous evaluation is worthless if it answers questions nobody asked and is delivered in a format nobody reads.
The American Evaluation Association (AEA) Program Evaluation Standards
- Utility: Evaluations must serve the information needs of intended users — evaluation questions, methods, and reporting formats should be negotiated with stakeholders, not imposed by evaluators.
- Feasibility: Evaluations must be realistic, prudent, diplomatic, and frugal — methodological rigor must be balanced against resource constraints and organizational capacity.
- Propriety: Evaluations must be conducted legally, ethically, and with due regard for the welfare of those involved — including informed consent of participants, IRB review for research, and attention to power dynamics in the evaluator-program relationship.
- Accuracy: Evaluations must produce and communicate technically accurate information — including transparency about limitations, alternative interpretations, and threats to validity.
- Evaluation Accountability: Evaluations must be accountable to their own standards — documenting decisions, being transparent about methods, and following through on commitments to stakeholders.
Qualitative methods in program evaluation
Not all important program outcomes are quantifiable. Qualitative methods — interviews, focus groups, ethnographic observation, document analysis, and participant narratives — capture the "how" and "why" behind quantitative findings. A program may show pre-post score improvement on a depression measure, but qualitative interviews with participants may reveal that the mechanism of change was peer support (not the CBT curriculum as intended), which has major implications for program theory and replication. PSY5140 covers qualitative data collection (semi-structured interview guides, focus group facilitation), analysis (thematic analysis, grounded theory, content analysis), and integration with quantitative data in mixed-methods evaluation designs.
PSY5140 assignments include logic model construction, evaluation plan design, and stakeholder report writing
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Logic model development, evaluation plan design, needs assessment analysis, outcome measurement, stakeholder reports.
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Frequently asked questions
The distinction is often framed as purpose and generalizability. Research aims to generate new knowledge that generalizes beyond the immediate study context — it asks, "What is true about this phenomenon across settings, populations, and times?" Program evaluation aims to inform decisions about a specific program in a specific context — it asks, "Is THIS program, implemented HERE, working for THESE clients?" Research is driven by scientific questions; evaluation is driven by stakeholder information needs. Methodologically, they overlap substantially — both use surveys, experimental designs, interviews, and statistical analysis. But evaluation must navigate practical constraints (programs cannot be paused or randomized for the sake of evaluation), political realities (programs have funders and advocates who care about findings), and ethical obligations that differ from pure research contexts. IRB review requirements for program evaluation are more context-dependent than for research — evaluation conducted by a program to improve its own services may not require IRB review, while evaluation conducted by external researchers that generates generalizable knowledge usually does. PSY5140 trains students to navigate these distinctions in real settings.