NSG7020 - Week 9 project

Week 8 Project: Outcome Measures and Analysis

Elizabeth Hernandez

South University

Dr. Crystal Dodson

NSG7020

May 8th , 2025

PICOT Question: In adults with obesity (P), how does participation in a structured weight management program (I), compared to self-directed weight loss efforts (C), affect long-term weight maintenance (O) over a 12-month period (T)?

Outcome Measures Narrative

The outcome measures selected for this project reflect key indicators of weight maintenance in adults with obesity. These include body mass index, weight change from baseline, waist circumference, HbA1c levels, and patient satisfaction with the intervention. The combination of biometric and subjective outcomes ensures a comprehensive view of both physical health and participant perception.

To analyze the data, several statistical methods will be used. Continuous variables like BMI, weight, waist circumference, and HbA1c levels will be analyzed using paired t-tests or repeated measures ANOVA. These techniques are appropriate for comparing changes over time within the same group of participants and are commonly used in healthcare research (Kim & Park, 2020). Repeated measures ANOVA will allow for the detection of trends across multiple time points, which is ideal for evaluating the 12-month progression targeted by this intervention (Schober, Boer, & Schwarte, 2021).

Patient satisfaction will be measured using a survey distributed after program completion. Responses will be analyzed using descriptive statistics to summarize ratings and thematic analysis for open-ended feedback. This mixed-methods approach will capture both the quantitative impact and the personal experiences of participants. Using qualitative data alongside quantitative metrics enhances the overall strength and reliability of the outcome evaluation (Polit & Beck, 2021).

To ensure consistent data collection, all clinical staff involved will receive training on standardized protocols. Clear instructions and demonstration of measurement techniques will help reduce variation and error. Nurses and support staff will be encouraged to participate by emphasizing the importance of accurate data in demonstrating the program’s success and securing future funding. Recognizing their contributions during team meetings and sharing early successes from the data will help sustain motivation.

Overall, these outcome measures and analysis plans provide a reliable and meaningful way to evaluate the effectiveness of the structured weight management program.

References

Kim, T. K., & Park, J. H. (2020). Guidelines for reporting statistical methods and results. Annals of Rehabilitation Medicine, 44(4), 301–309. https://doi.org/10.5535/arm.2020.44.4.301

Polit, D. F., & Beck, C. T. (2021). Nursing research: Generating and assessing evidence for nursing practice (11th ed.). Wolters Kluwer.

Schober, P., Boer, C., & Schwarte, L. A. (2021). Repeated measures analysis for longitudinal studies: A practical guide for clinical researchers. BMC Medical Research Methodology, 21, 100. https://doi.org/10.1186/s12874-021-01266-3

Outcome Table

Variable of Interest	Data Needed	Frequency of Data Collection	Methods of Data Collection	Who Will Collect	Analysis
Body Mass Index (BMI)	BMI measurements at baseline, 6, and 12 months	Baseline, 6 months, 12 months	Electronic Health Records (EHR), clinical assessment	Registered nurse or provider	Mean BMI change analyzed using paired t-tests
Weight change (%) from baseline	Weight recorded at baseline and 12 months	Baseline and 12 months	Clinical scale and EHR documentation	Registered nurse	Percentage weight change, compared with t-test or ANOVA
Waist circumference	Waist circumference at baseline and 12 months	Baseline and 12 months	Tape measurement by clinical staff	Nursing assistant or medical technician	Change from baseline analyzed using t-test
HbA1c level	HbA1c lab results at baseline and 12 months	Baseline and 12 months	Laboratory results recorded in EHR	Lab technician, documented by provider	HbA1c trend over time, using repeated measures ANOVA
Patient satisfaction with program	Survey responses post-intervention	12 months	Patient satisfaction survey	Nurse or study coordinator	Descriptive statistics and thematic coding for open responses