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Full-Text Articles in Medical Biomathematics and Biometrics
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Paula Diehr
As a "thought experiment," the authors used a modified stages of change model for smoking to define homogeneous segments within various hypothetical populations. The authors then estimated the population effect of public health interventions that targeted the different segments. Under most assumptions, interventions that emphasized primary and secondary prevention, by targeting the Never Smoker, Maintenance, or Action segments, resulted in the highest nonsmoking life expectancy. This result is consistent with both social marketing and public health principles. Although the best thing for an individual smoker is to stop smoking, the greatest public health benefit is achieved by interventions that target …
Reliability, Effect Size, And Responsiveness Of Health Status Measures In The Design Of Randomized And Cluster-Randomized Trials, Paula Diehr
Paula Diehr
BACKGROUND: New health status survey instruments are often described by their psychometric (measurement) properties, such as Validity, Reliability, Effect Size, and Responsiveness. For cluster-randomized trials, another important statistic is the Intraclass Correlation (ICC) for the instrument within clusters. Studies using better instruments can be performed with smaller sample sizes, but better instruments may be more expensive in terms of dollars, opportunity cost, or poorer data quality due to the response burden of longer instruments. METHODS: We defined the psychometric statistics in terms of a mathematical model, and examined the power of a two-sample test as a function of the test-retest …
Optimal Survey Design For Community Intervention Evaluations: Cohort Or Cross-Sectional?, Paula Diehr
Optimal Survey Design For Community Intervention Evaluations: Cohort Or Cross-Sectional?, Paula Diehr
Paula Diehr
Community intervention evaluations that measure changes over time may conduct repeated cross-sectional surveys, follow a cohort of residents over time, or (often) use both designs. Each survey design has implications for precision and cost. To explore these issues, we assume that two waves of surveys are conducted, and that the goal is to estimate change in behavior for people who reside in the community at both times. Cohort designs are shown to provide more accurate estimates (in the sense of lower mean squared error) than cross-sectional estimates if (1) there is strong correlation over time in an individual's behavior at …
Breaking The Matches In A Paired T-Test For Community Interventions When The Number Of Pairs Is Small, Paula Diehr
Breaking The Matches In A Paired T-Test For Community Interventions When The Number Of Pairs Is Small, Paula Diehr
Paula Diehr
There is considerable interest in community interventions for health promotion, where the community is the experimental unit. Because such interventions are expensive, the number of experimental units (communities) is usually small. Because of the small number of communities involved, investigators often match treatment and control communities on demographic variables before randomization to minimize the possibility of a bad split. Unfortunately, matching has been shown to decrease the power of the design when the number of pairs is small, unless the matching variable is very highly correlated with the outcome variable (in this case, with change in the health behaviour). We …
Do Communities Differ In Health Behaviors?, Paula Diehr
Do Communities Differ In Health Behaviors?, Paula Diehr
Paula Diehr
Communities differ in the prevalence of various health behaviors, but it is not known to what extent these differences are due to "different types" of people living in them. We used data from the evaluation of the Henry J Kaiser Family Foundation Community Health Promotion Grant Program to study individual-level and community-level variation in health behaviors for 15 communities. Our results show (1) there was significant variation among these communities in prevalences of smoking, consumption of alcohol and dietary fat, and use of seatbelts; (2) these differences persisted after control for demographic, health status, and other health behavioral characteristics of …