| Course | HD440 Health Education Program Assessment and Planning |
|---|---|
| Unit | Unit 4 |
| Paper type | Priority setting matrix |
| Length | About 630 words, 5 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | BS in Health and Wellness |
| Updated | October 2026 |
Free sample paper for HD440 Unit 4
Five Problems In, One Out: A Unit 4 Priority Setting Matrix Using the Hanlon Method for Composite Ridley County
[Student Name]
Purdue University Global
HD440: Health Education Program Assessment and Planning
Unit 4 Priority Setting Matrix
[Instructor Name]
[Date]
Ridley County and every score are composite; the Hanlon method and PEARL test are described as published, and the planning text and the reviews cited are real.
The Method
The Hanlon method rates each problem on three components. A is the size of the problem, scored 0 to 10 by how many people it affects. B is its seriousness, scored 0 to 10 by urgency, severity, economic loss and how many others it affects. C is the effectiveness of available interventions, scored 0 to 10. The basic priority rating is calculated as A plus twice B, all multiplied by C, so seriousness and effectiveness weigh more than size. Before the ranking, the PEARL screen asks five yes-or-no questions, about propriety, economics, acceptability, resources and legality, and any problem answering no to one of them drops out regardless of its score (Issel & Wells, 2018).
The Scores
Alcohol-involved crashes. A, size: 4, since about [15] people a year are killed or injured, a small share of the population. B, seriousness: 9, since deaths are of younger adults and each crash harms others. C, effectiveness: 7, since several interventions have strong evidence of reducing crashes (Shults et al., 2001). Rating: (4 plus 18) times 7, or 154.
Overdose. A: 5. B: 9. C: 5, since treatment access works but the county has few providers. Rating: (5 plus 18) times 5, or 115.
Smoking in pregnancy. A: 3. B: 7. C: 6. Rating: (3 plus 14) times 6, or 102.
Obesity in adults. A: 9. B: 6. C: 3, since community interventions show modest effects. Rating: (9 plus 12) times 3, or 63.
Falls among residents over 65. A: 6. B: 6. C: 7. Rating: (6 plus 12) times 7, or 126.
PEARL Screen
All five pass. Each is a proper concern for the health department, has economic sense, is acceptable to the community, can be addressed with resources the county could gather, and is legal to address. Overdose was discussed at length under acceptability, since some residents oppose harm reduction services, but treatment and prevention approaches are acceptable, so it passes.
Ranking
1. Alcohol-involved crashes: 154.
2. Falls among older residents: 126.
3. Overdose: 115.
4. Smoking in pregnancy: 102.
5. Obesity in adults: 63.
Crashes rank first not because they are the largest problem, they are not, but because they combine high seriousness with interventions known to work, which is exactly what the Hanlon formula rewards.
Does the Winner Survive a Change in Weights?
If size, seriousness and effectiveness were weighted equally, with the rating calculated as A plus B, times C, the ranking would be: crashes (4 plus 9) times 7, or 91; falls (6 plus 6) times 7, or 84; overdose (5 plus 9) times 5, or 70; smoking in pregnancy (3 plus 7) times 6, or 60; obesity (9 plus 6) times 3, or 45. Crashes stay first, though the gap over falls narrows.
If community concern were added as a factor, overdose would rise, since most survey respondents named it first. The planning group noted this and agreed to track overdose closely for the next cycle.
Judgment Behind the Numbers
The scores are judgments, made by a group of six that included the health officer, a nurse, a sheriff's deputy, a tavern owner, a school counselor and a resident. Their main disagreement was over the effectiveness score for crashes, which the deputy rated lower because of staffing. The group settled on 7 after reviewing the evidence on enforcement and media campaigns (Elder et al., 2004).
References
Elder, R. W., Shults, R. A., Sleet, D. A., Nichols, J. L., Thompson, R. S., & Rajab, W. (2004). Effectiveness of mass media campaigns for reducing drinking and driving and alcohol-involved crashes. American Journal of Preventive Medicine, 27(1), 57-65. https://doi.org/10.1016/j.amepre.2004.03.002
Issel, L. M., & Wells, R. (2018). Health program planning and evaluation: A practical, systematic approach for community health (4th ed.). Jones & Bartlett Learning.
Shults, R. A., Elder, R. W., Sleet, D. A., Nichols, J. L., Alao, M. O., Carande-Kulis, V. G., Zaza, S., Sosin, D. M., & Thompson, R. S. (2001). Reviews of evidence regarding interventions to reduce alcohol-impaired driving. American Journal of Preventive Medicine, 21(4 Suppl.), 66-88. https://doi.org/10.1016/S0749-3797(01)00381-6
HD440 Unit 4 instructions, in plain terms
Unit 4 usually asks you to rank several health problems using a named prioritization method, show each score with its reasoning, and explain the result. Matrices often fill two to three pages. Credit goes to the method described accurately, each score justified with evidence, the arithmetic shown, any screening step such as PEARL applied, and a recalculation under different weights to see if the top choice survives. Many sections reward describing who did the scoring and where they disagreed. Anchor score points to evidence where possible so the numbers do not look arbitrary. Cite a planning text for the method and evidence for the effectiveness scores.
How this HD440 Unit 4 example is built
A method section explains the three Hanlon components, the formula that doubles seriousness and the PEARL screen, citing a planning text. Each problem then gets its size, seriousness and effectiveness scores with a reason and the resulting rating, citing reviews of crash interventions. A PEARL section explains why all five pass, including a discussion of overdose and acceptability. The ranking follows; the highlighted sentence explains why crashes won despite not being largest. A sensitivity section recalculates with equal weights and considers community concern. A closing section describes the six scorers and the disagreement over crash effectiveness, settled by reviewing the evidence on enforcement and media.
Where the points sit in the HD440 Unit 4 rubric
Priority setting matrices are typically graded on correct use of the method, justification of scores, transparency of arithmetic, sensitivity testing and interpretation. Justification and sensitivity testing usually carry the largest share, because a ranking that rests on unexplained scores or collapses under a different weighting is weak evidence for a decision. Method credit rewards correct components and formula. Arithmetic should be shown for every problem. Interpretation earns points when the writer explains why the top problem won. Describing the scoring group and its disagreements shows the judgment behind the numbers. Citing the method and evidence for effectiveness completes the expected support. A short note on how ties would be broken shows the group thought ahead.
Common HD440 Unit 4 mistakes, and how to avoid them
A common gap is scores with no reasons, which makes the ranking look like preference dressed as arithmetic. Another is misusing the formula, for example adding components that should be multiplied. Some students skip the screening step. Others present the result without checking whether it changes under different weights. Leaving out who scored and how disagreements were settled hides the most important part of the process. If your candidate problems differ, share the list and the assessment data, and each score can be built with a reason attached. Using a scoring scale without saying what each point means invites the charge of arbitrariness. Ranking only two or three problems gives the method little to do.
Get an HD440 Unit 4 example written to your instructions
List the candidate problems your HD440 assessment produced for your county, then attach the Unit 4 prompt and rubric along with any prioritization method your section names. A first custom sample arrives free in 24-48h with criteria defined, every score sourced, the arithmetic shown, and a sensitivity check on the result. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
More HD440 papers and BS in Health and Wellness samples
- HD440 Unit 1: Community Priorities Discussion Post
- HD440 Unit 2: Data Source Review
- HD440 Unit 3: Community Assessment Summary
- HD440 Unit 5: Goal and Objective Set
- HD440 Unit 6: Seminar Reflection
- HD440 Unit 7: Intervention Selection Paper
- HD440 Unit 8: Resource and Partner Plan
- HD440 Unit 9: Program Plan Draft
- HD440 Unit 10: Planning Document
- HD420 Unit 4: Community Profile
HD440 Unit 4 questions, answered
Which prioritization method should I use?
Whichever your prompt specifies. The Hanlon method, simple multi-voting, a weighted criteria matrix and the strategy grid are all common in health education planning. Hanlon suits data-rich decisions because it forces explicit scores for size, seriousness and effectiveness. Whatever you use, cite its source and define each criterion before scoring anything.
What if my scores feel arbitrary?
Anchor each scale point to evidence. For example, size might score ten when more than a fifth of residents are affected and five near one in twenty. Once anchors are written, scores follow from data rather than impression. Some arbitrariness remains, which is exactly why a sensitivity check on the weights is worth including.
Can community concern be a criterion?
Many planners include it, and it is especially relevant for health education, where participation depends on residents caring about the issue. Add it as a separate criterion with its own evidence, such as survey rankings, rather than folding it into seriousness. Showing how the result changes when concern is counted makes the decision easier to defend.
Where can I find a free HD440 Unit 4 sample paper?
You will find the whole Unit 4 matrix here, ranking five county problems with the Hanlon method and testing the result.
What is the PEARL test?
A screen applied alongside the Hanlon method that asks whether addressing a problem is proper, economically sensible, acceptable, resourced and legal. A problem failing any factor is set aside.