| Course | MPH 507 Public Health Program Planning and Evaluation |
|---|---|
| Week | 3 |
| Paper type | Logic model with narrative |
| Length | About 1,130 words, 5 pages |
| Format | APA 7 student paper |
| School | Chamberlain University |
| Program | Master of Public Health (MPH) |
| Updated | October 2026 |
Free sample paper for MPH 507 Week 3
Logic Model: Screen at Home, a Community Health Worker Program Offering HPV Self-Collection Kits to Overdue Women in Tolliver County
Student Name
Chamberlain University
MPH 507: Public Health Program Planning and Evaluation
Instructor Name
Month Day, Year
Logic Model: Screen at Home, a Community Health Worker Program Offering HPV Self-Collection Kits to Overdue Women in Tolliver County
Purpose of the Model
This logic model sets out how Screen at Home, a program planned by Laurel Valley Community Health Center in Tolliver County, a composite rural county, is expected to work. The program will offer overdue women in the 30 to 65 age band a kit to collect their own vaginal sample for high-risk HPV testing, delivered in person by community health workers, with navigation to follow-up for women with positive results. The model reads left to right as a chain of claims, each of which could prove false, so that the evaluation can test them in order.
Inputs, as Things the Program Consumes
Inputs are what the program uses up or occupies. They are three community health workers at 0.5 full-time each for two years; one patient navigator at 0.5 full-time; 1,200 self-collection kits; laboratory testing under the existing regional contract; a part-time data coordinator; mileage for home visits; and protected slots at the regional hospital's monthly colposcopy clinic, agreed in a memorandum with the hospital.
Activities, as Things Someone Does on a Working Day
Activities are written concretely enough to be pictured. Community health workers pull the list of overdue women from the record each month. They call or visit each woman, explain the kit and screening intervals, and either leave a kit with a prepaid return envelope or wait while the woman collects the sample. They also offer kits at monthly church food distributions. The data coordinator logs every kit given and returned. The patient navigator calls every woman with a positive result within three working days, books colposcopy, arranges transport and tracks attendance.
Outputs, as Counts
Outputs count what the activities produce. They are not changes in people. Outputs include the number of overdue women contacted, the number offered a kit, the number of kits distributed, the number returned with a valid result and the number of women with positive results who receive a navigator call within three days.
Outcomes, by Time Horizon
Short-term outcomes, within six months of contact, are changes in individuals: more overdue women are up to date with screening, and more women know the current screening interval. Intermediate outcomes, within the two-year funding period, are changes in the health center's population: the share of the panel aged 30 to 65 that is up to date rises, and the share of women with positive results who complete colposcopy within 90 days rises. Long-term outcomes, beyond the program period, are fewer cases of invasive cervical cancer diagnosed among county women and more cases found at an early stage. The long-term outcomes cannot be measured within the program's life, because the number of cases is small and precancer takes years to progress; they are included to show where the chain is meant to lead.
Table 1
Screen at Home Logic Model
| Resources used | What staff do | Countable products | Change within six months | Change by mid-2028 | Change beyond the grant |
|---|---|---|---|---|---|
| Three CHWs at 0.5 FTE; navigator; kits; lab contract; colposcopy slots | Monthly list; calls and visits; kits left or collected; food distribution offers; navigator follow-up | Women contacted; kits given; kits returned; positives called within 3 days | Overdue women screened; interval known | Panel up to date rises; colposcopy completion rises | Fewer invasive cancers; earlier stage at diagnosis |
Note. Note. CHW = community health worker; FTE = full-time equivalent.
Assumptions That Could Be False
The chain rests on assumptions, each of which could fail and each of which the evaluation should test. That women who avoid the speculum exam will accept self-collection: supported by the community interviews and by trials in which offering devices directly reached most underscreened women (Arbyn et al., 2018), but not tested in this county. That kits left at home will come back: in a large U.S. trial of mailed kits, only about one woman in four who was sent a kit had been screened by the half-year mark, though that was still more than with reminders alone (Winer et al., 2019); in-person delivery is expected to do better, but this is an assumption. That women with positive results will go to colposcopy: women in a U.S. trial reported confusion and strong emotions after a positive home result (Tiro et al., 2019), and the county's attendance at colposcopy was already poor. That the regional laboratory can process the volume without delay. That community health workers can add this work to their other programs.
Narrative of the Links
The links work as follows. The health center has the staff, kits and laboratory contract to reach overdue women. Community health workers, who are trusted and already in the women's homes, remove the barriers women named: the exam, the trip, the need for a weekday appointment and the absence of a female clinician. When those barriers fall, more women are screened. Because high-risk HPV testing on self-collected samples detects precancer about as well as clinician samples, screening by kit is real screening, not a lesser substitute. The navigator then closes the gap after a positive result, which the needs assessment identified as a separate failure. More women screened and followed up leads, over years, to fewer and earlier cancers.
The weakest link is the step from a positive result to completed colposcopy, because it depends on a hospital outside the program's control and on women acting after an upsetting result. The model gives that link its own staff member for this reason.
Who Will Use This Model
Three groups will treat the model as a working document Program staff will use the activities and outputs columns as a monthly checklist: if outputs fall behind, the problem is in delivery, not in the theory. The evaluator will test the assumptions in order, starting with kit acceptance and return, because if those links fail, nothing further along the chain can be judged. And the health center's board will use the outcomes columns to decide in the second year whether to fund the program from its own budget. The model will be revised if the first quarter shows that a link works differently than expected; for example, if most women prefer to collect the sample during the visit rather than keep the kit, the reminder activities can shrink and the visit can lengthen. A model that is never revised after the program starts is a diagram, not a plan, and the health center has agreed to review this one each quarter alongside the process data.
References
Arbyn, M., Smith, S. B., Temin, S., Sultana, F., & Castle, P. (2018). Detecting cervical precancer and reaching underscreened women by using HPV testing on self samples: Updated meta-analyses. BMJ, 363, k4823. https://doi.org/10.1136/bmj.k4823
Tiro, J. A., Betts, A. C., Kimbel, K., Buist, D. S., Mao, C., Gao, H., Shulman, L., Malone, C., Beatty, T., Lin, J., Thayer, C., Miglioretti, D. L., & Winer, R. L. (2019). Understanding patients' perspectives and information needs following a positive home human papillomavirus self-sampling kit result. Journal of Women's Health, 28(3), 384-392. https://doi.org/10.1089/jwh.2018.7070
Winer, R. L., Lin, J., Tiro, J. A., Miglioretti, D. L., Beatty, T., Gao, H., Kimbel, K., Thayer, C., & Buist, D. S. M. (2019). Effect of mailed human papillomavirus test kits vs usual care reminders on cervical cancer screening uptake, precancer detection, and treatment: A randomized clinical trial. JAMA Network Open, 2(11), e1914729. https://doi.org/10.1001/jamanetworkopen.2019.14729
Reading the MPH 507 Week 3 instructions
In the third week you build a logic model for the program your needs assessment points to. Write inputs as resources the program actually uses, activities as things staff do, concretely enough to picture, and outputs as countable products of those activities. Separate outcomes by time horizon, from short-term changes in individuals to long-term changes in health. Keep outputs out of the outcome columns. State the assumptions the chain depends on, especially those that could prove false. Add a short narrative that explains why each link should hold, with evidence where it exists. The model should read left to right as a set of claims someone could challenge.
How this MPH 507 Week 3 example is built
The model lists three community health workers at half time, a navigator, 1,200 kits, a laboratory contract and colposcopy slots as inputs. Activities describe the monthly overdue list, calls and visits, kits left or collected on the spot, offers at food distributions and navigator calls. Outputs are counts of contacts, kits and timely calls. Outcomes run from overdue women screened within six months, through a rising panel rate and colposcopy completion, to fewer and earlier cancers beyond the grant. A table shows the chain. Five assumptions are tested against the Arbyn meta-analysis, the Winer trial and the Tiro interviews, and the narrative names follow-up after a positive result as the weakest link.
Where the points sit in the MPH 507 Week 3 rubric
The most common way to lose points on a logic model is placing outputs in the outcome column, presenting sessions or kits distributed as a change in people. Rubrics check for it directly. An implausible chain, where a few activities are shown producing a fall in a population rate within months, is the second frequent weakness. Inputs written as vague support and activities written as goals also cost marks. Models that list no assumptions, or only ones that cannot fail, miss the narrative credit. Strong models keep each column true to its definition, separate outcomes by horizon, state assumptions that could be false with evidence, and explain the links in prose.
MPH 507 Week 3 help from the desk
Logic models look simple, and that is why errors in them are easy to miss. If you share the program from your needs assessment, we can help you sort what belongs in each column, write activities concretely and keep outputs out of the outcomes. We can also help you find evidence for each link and write assumptions that the evaluation could test. Your program and the model's content remain yours. Some instructors hand out a model template with their own column labels; if yours did, attach it and the custom sample will use those labels in that order. We can also read your draft model left to right and flag any link that would be hard to defend, so you can fix it before the evaluation weeks depend on it.
Get a MPH-507 Week 3 example written to your instructions
Send the Week 3 instructions with the template your section supplies and your program idea, and a custom example is built into that format and returned inside 24 to 48 hours. The first one is free. Which outcomes you commit the model to stays yours.
More MPH 507 papers and MPH samples
- MPH 507 Week 1: Failed Program Post
- MPH 507 Week 2: Community Needs Assessment
- MPH 507 Week 4: Program Objectives Write-up
- MPH 507 Week 5: Intervention Plan
- MPH 507 Week 6: Evaluation Design Paper
- MPH 507 Week 7: Data Collection Plan
- MPH 507 Week 8: Program Evaluation Proposal
- MPH 506 Week 3: Exposure Pathway Analysis
- MPH 505 Week 3: Audience Analysis
- MPH 504 Week 3: Disease Burden Analysis
- MPH 503 Week 3: Legal Authority Write-Up
MPH 507 Week 3 questions, answered
What is the difference between an output and an outcome?
An output is what the program produced; an outcome is what changed in people because of it. Twenty workshops delivered is an output. Participants using a skill three months later is an outcome. Almost every logic model assignment plants this confusion, and getting it right across the whole model is worth more than any other single thing in the grade.
How far should the long-term outcome reach?
Far enough to matter and close enough to be plausible from your activities. A mortality reduction is rarely defensible from a small program, and claiming one weakens the whole model. Naming a long-term outcome your chain could realistically influence, and saying what else would have to happen, reads as competent rather than modest.
Do assumptions really need their own section?
Yes, and they are the section most often skipped. Every arrow depends on something: that people will attend, that staff will deliver as designed, that the setting stays stable. Writing those as statements that could turn out false is what turns a model into something testable, and instructors read that section closely.
Where can I find a free MPH 507 Week 3 sample paper?
The complete MPH 507 Week 3 logic model for a program that puts HPV self-collection kits in women's hands, with a narrative and tested assumptions, is on this page.
Which link does the MPH 507 Week 3 sample call weakest?
The step from a positive result to completed colposcopy, because it depends on an outside hospital and on women acting after upsetting news.