CHL 640 Week 3 Indicators and Data Sources Example

Scales, Sign-In Sheets, Store Receipts and Path Counts: Selecting Indicators and Data Sources for the Walk and Eat Well Evaluation

[Student Name]

University of Phoenix

CHL/640: Evaluating Community Health Initiatives

Week 3 Assignment

[Instructor Name]

[Date]

The initiative, indicators, baselines, targets, data systems and store agreements are composites written for a model paper modeled on Yakima, Washington; city estimates come from CDC PLACES, and research findings come from the sources cited.

At a planning session, a resident on the evaluation team said the goal was simple: to know whether people were healthier. The evaluator agreed that was the goal but warned that "healthier" could not be measured as stated. Each priority question needed an indicator, a specific, measurable sign, and a source that could supply it. This paper selects indicators and data sources for the eight priority questions.

What Makes a Good Indicator

The team used six criteria. An indicator should be relevant to its question, precisely defined with a numerator, denominator and time frame, valid in measuring what it claims, reliable when measured repeatedly, feasible with available resources and sensitive enough to show change during the evaluation.

Question One: Reach

Indicator: the number of enrolled lifestyle participants, broken down by language, age group, sex and home neighborhood and set against the makeup of the health center's prediabetes registry for east side patients. Sources: enrollment forms and the health center's prediabetes registry. Frequency: quarterly.

Rejected Indicators

Several tempting indicators were rejected. Self-reported fruit and vegetable intake was dropped because short questions are unreliable and a full dietary recall would burden participants. A1c testing for all participants was considered but dropped because of cost and the need for clinic visits; it will be collected from clinic records for participants who consent. Neighborhood diabetes rates were rejected as outcomes because the program is too small to change them in three years.

Question Two: Fidelity

Indicator: the percentage of core elements delivered in observed sessions, using a 12-item checklist covering goal setting, self-monitoring review, weigh-in, the session topic and action planning. Source: observation of one session per group per month by the lead promotora, with 10% observed jointly by the evaluator to check agreement. Target: 85% or higher.

Question Three: Attendance

Indicator: the percentage of enrolled participants attending at least 12 of 16 core sessions. Source: sign-in sheets entered into the program database weekly. Baseline from the original program: 38%. Target: 64%.

Question Four: Participant Experience

Indicators: mean ratings of usefulness, respect and convenience on a five-point scale, and themes from exit interviews. Sources: a short bilingual survey after each cohort and interviews with 15 participants a year, including some who stopped attending.

Question Five: Weight

Indicator: mean percent change in body weight from enrollment to twelve months among completers, and the percentage losing 5% or more. Source: weights on a calibrated scale at sessions, recorded privately. Target: mean loss of 5%, with 40% losing 5% or more.

Question Six: Physical Activity

Indicator: the percentage of participants reporting at least 150 minutes of moderate activity per week, plus average daily steps. Sources: a validated short activity questionnaire at enrollment, six and twelve months and a two-week step count from pedometers. Target: from 25% to 60%.

Measuring Path Use

To capture walking beyond enrolled participants, the team adopted a systematic observation tool. The System for Observing Play and Recreation in Communities was tested by observing 16,244 people in 165 park areas; correlations between independent observers on the number of users were 0.99, and agreement on age, race and ethnicity and activity level met acceptable criteria (McKenzie et al., 2006). Trained observers will count path users by sex, age group and activity level on set evenings each month. A validated count of walkers on the path turns a feeling that the path is busier into evidence.

Question Seven: Store Availability and Sales

Indicators: the number of the 20 agreed healthy items stocked and visibly placed at each store, measured by monthly audits; and monthly produce sales, from store records. Sources: audit forms and owners' sales summaries under data agreements.

Why These Store Indicators

The small-store trials that Gittelsohn and colleagues reviewed most often measured success by what shelves held and what customers bought, and those were the outcomes that moved; following their lead keeps the east side's results comparable with that evidence (Gittelsohn et al., 2012). Shopper intercept surveys twice a year will add information on purchases.

Question Eight: Cost

Indicators: total cost, cost per enrolled participant and cost per completer, including in-kind contributions separately. Sources: the fiscal agent's financial reports and the in-kind log.

Population Context

Population indicators provide context but will not measure program effects. CDC's city estimates for 2023 show adult inactivity at 28.1%, obesity at 39.7% and diagnosed diabetes at 12.9% (Centers for Disease Control and Prevention [CDC], 2025). The team will track these annually as background, not as outcomes, since the program is too small to move citywide rates quickly.

Pilot Testing the Tools

Before full use, the team tested each tool. Five participants tried the activity questionnaire and flagged a confusing item about work activity, which was reworded for farmworkers whose jobs are physically demanding. Two observers practiced path counts together until their totals matched closely. Store owners tried the monthly summary form and asked for a simpler version, which the team provided.

Baselines and Targets

Each indicator has a baseline, from the original program, enrollment data or the first month of observation, and a target based on the logic model and published evidence. Targets are reviewed with the initiative committee so that they are ambitious but realistic.

Disaggregation

All participant indicators will be reported by language, age group, sex and neighborhood, and store indicators by store, so that differences are visible.

Burden

The team weighed burden. Participants complete no more than 15 minutes of surveys at each of three points. Promotoras spend about one hour a week on data entry. Store owners provide monthly summaries rather than daily data.

Qualitative Data Sources

Numbers alone cannot explain why results look the way they do. The plan pairs each quantitative indicator with a qualitative source: exit interviews explain attendance patterns, store owner conversations explain sales changes and short conversations with walkers during path counts explain who uses the path and why. These stories will help the committee interpret the numbers and decide what to change.

Indicators for Equity

For each participant indicator, the team set an equity check: the gap between Spanish-speaking and English-speaking participants, and between adults over and under 60, should be no more than ten percentage points. A larger gap triggers a review of how the program serves the group that lags.

Data Management

Data are stored in a secure database managed by the health district, with identifiers kept separately. Only the evaluator and coordinator see identified data. Reports show only combined results.

The Indicator Table

The final table lists each question, its indicators, definitions, sources, frequency, responsible person, baseline and target in one page, used at every monthly review.

Conclusion

"Healthier" became measurable through precise indicators for reach, fidelity, attendance, experience, weight, activity, store change and cost. A validated observation system measures path use, store indicators follow the evidence from small-store trials and CDC city estimates provide context without being mistaken for program effects. Baselines, targets, disaggregation and attention to burden make the plan usable.

References

Centers for Disease Control and Prevention. (2025). PLACES: Place data (GIS friendly format), 2025 release [Data set]. data.cdc.gov. https://data.cdc.gov/d/vgc8-iyc4

Gittelsohn, J., Rowan, M., & Gadhoke, P. (2012). Interventions in small food stores to change the food environment, improve diet, and reduce risk of chronic disease. Preventing Chronic Disease, 9, Article E59. https://doi.org/10.5888/pcd9.110015

McKenzie, T. L., Cohen, D. A., Sehgal, A., Williamson, S., & Golinelli, D. (2006). System for Observing Play and Recreation in Communities (SOPARC): Reliability and feasibility measures. Journal of Physical Activity and Health, 3(Suppl. 1), S208-S222. https://doi.org/10.1123/jpah.3.s1.s208