PHE 423 Module 3 Logic Model Short Paper Example

Knock, Install, Test, Survive: A Logic Model and Evaluation Questions for a Smoke Alarm Installation Program

[Student Name]

Southern New Hampshire University

PHE 423: Evaluation Methods in Public Health

Module Three Short Paper

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Knock, Install, Test, Survive: A Logic Model and Evaluation Questions for a Smoke Alarm Installation Program

A logic model lays out, step by step, the chain a program expects to run from resources to results. It connects what a program uses and does to what it hopes to change, and in doing so it exposes the assumptions on which success depends. The Kellogg guide presents the model as useful at every stage, from design through management to evaluation, linking inputs, activities, outputs, outcomes and impact in a chain of if-then statements (W. K. Kellogg Foundation, 2004). This paper builds a logic model for the smoke alarm installation program run by the fire department and county health department in a composite Missouri river city, names the assumption behind each link and turns the weakest links into evaluation questions. Building one before choosing measures keeps the evaluation focused on how the program is meant to work.

Inputs

The program's inputs are four two-person crews from the fire department working two afternoons a week, a state grant that pays for sealed ten-year lithium alarms and some hush-button models for kitchens, health department staff who keep records and recruit landlords, agreements with landlords who own about half of the older rental homes in the two neighborhoods, door hangers and a short tenant handout in English and Spanish and the neighborhood associations' help in spreading the word. Without the landlord agreements, crews could not enter half of the target homes.

Activities and Outputs

Crews go door to door in the target neighborhoods, ask tenants for permission, install alarms in each bedroom, outside sleeping areas and on each level, test each alarm, explain how it works and what to do when it sounds and leave a handout. They record the address, the number of alarms installed, whether any working alarm was present before and whether the home has risk factors such as space heaters, smokers, older residents living alone or a past fire. The outputs are the number of homes reached, homes where installation was accepted, alarms installed and tenants given the explanation. These records become the evaluation's baseline.

Outcomes

Short-term outcomes, within weeks, are that installed homes have working alarms in the right places and that tenants know how to respond to an alarm, including planning two ways out. Over the following one to two years, the intermediate outcomes are that alarms remain installed and working, that tenants do not disable them after false alarms and that more landlords request installation in their other properties. Long-term outcomes, over several years, are fewer fire injuries and deaths in the target neighborhoods. Yellman et al. (2018) found that a similar installation program in Dallas was associated with far fewer medically treated fire injuries among residents of program homes over several years, which supports the long-term link. Each outcome has a time frame so progress can be checked.

Assumptions at Each Link

Behind each arrow sits a belief about cause and effect. From inputs to activities, the model assumes crews have time and landlords give permission. From activities to outputs, it assumes tenants answer the door and agree. From outputs to short-term outcomes, it assumes alarms are installed correctly and tenants understand the explanation. From short-term to intermediate outcomes, it assumes tenants keep alarms in place, which the sealed batteries and kitchen hush buttons are meant to help. From intermediate to long-term outcomes, it assumes that working alarms lead to earlier escape and fewer injuries, which research supports. The link from installation to working alarms a year later is exactly where a London giveaway program broke down (DiGuiseppi et al., 2002): alarms were provided but few were installed or kept working.

Where the Evidence Is Weakest

Some links are well supported. Research shows that working alarms reduce deaths and that installation programs can reduce injuries. Others are uncertain in this city. No one knows how many tenants answer the door or refuse, whether the homes reached are the highest-risk ones, whether alarms are removed after cooking false alarms or whether crews install alarms consistently. These local unknowns are where evaluation adds the most value, because they decide whether the well-supported long-term links will come into play.

External Factors

Logic models also note influences outside the program's control. Several matter here. Housing turnover is high in the target neighborhoods, so tenants who received the explanation may move out within a year, leaving alarms with new tenants who never heard it. Some landlords may replace or remove alarms during renovations. Weather affects fire risk, since space heater use rises in cold winters. Other efforts, such as a separate city code enforcement campaign, could change alarm coverage in the comparison neighborhood and blur any comparison. Recording these factors in the model reminds the evaluation team to measure them where possible, for example by asking at follow-up whether the household is the same one that was there at installation, and to interpret results with them in mind. An evaluation that ignored turnover could wrongly credit or blame the program for changes that came from people moving in and out.

Evaluation Questions

Five questions follow from the model, ordered by importance to stakeholders and by how much they test weak links. First, what share of homes with installed alarms still have working alarms in sleeping areas one year later? Second, does the program reach the highest-risk homes, and who is missed when tenants do not answer or refuse? Third, are crews installing and testing alarms as specified? Fourth, do tenants know how to respond to an alarm and have an escape plan? Fifth, over several years, do fire injuries and deaths fall in program neighborhoods compared with similar neighborhoods not yet served? The first three can be answered within a year; the fifth will take longer.

Conclusion

The logic model shows a simple program resting on several untested local assumptions. Its evaluation questions focus on those assumptions, especially whether alarms stay working, because the program's long-term promise depends on them. Module Four will consider which design can answer these questions. Each question also names who will use the answer.

References

DiGuiseppi, C., Roberts, I., Wade, A., Sculpher, M., Edwards, P., Godward, C., Pan, H., & Slater, S. (2002). Incidence of fires and related injuries after giving out free smoke alarms: Cluster randomised controlled trial. BMJ, 325(7371), 995-998. https://doi.org/10.1136/bmj.325.7371.995

W. K. Kellogg Foundation. (2004). Logic model development guide. W. K. Kellogg Foundation.

Yellman, M. A., Peterson, C., McCoy, M. A., Stephens-Stidham, S., Caton, E., Barnard, J. J., Padgett, T. O., Florence, C., & Istre, G. R. (2018). Preventing deaths and injuries from house fires: A cost-benefit analysis of a community-based smoke alarm installation programme. Injury Prevention, 24(1), 12-18. https://doi.org/10.1136/injuryprev-2016-042247