Statistical considerations
skin cancer, sunburn
REGRESSION, SECONDARY, SKIN CANCER
We calculated the sample size to achieve high power for the primary outcome (sun habit score) while also maintaining moderate power for experience of a sunburn during the intervention period, a key secondary outcome. A sample size of 314 randomized achieves 95% power to detect an effect size of 0.4 between intervention and control groups using a two-sided two-sample t-test assuming a significance level of 0.05. This sample size also achieves 70% power to detect 20% of the control participants reporting a sunburn and 10% of the intervention participants reporting a sunburn as statistically significant at a significance level of 0.05. We estimated that 85% of those randomized would complete the 12-week follow-up survey, resulting in a final calculated sample size of 368.Participant demographic characteristics and sun behaviors reported at baseline were summarized using descriptive statistics. The main analysis of the primary outcome, total sun habit scores, was analyzed using two-sided two-sample t-test comparing scores at the end of the intervention period (12 weeks) between intervention and control groups. A secondary analysis explored changes in the total sun habit scores over the intervention period (baseline, weeks 4, 8 and 12) using a linear mixed effects regression model with fixed effects of time, group and time-group interactions, assuming that data were missing at random (MAR) [Comparisons of secondary outcomes—including experience of sunburn, self-report sun behaviors, skin cancer knowledge, emotional health, and physical activity—by randomization group were conducted using Chi-squared and t-tests as appropriate. Individual objective UVR data were summarized as minutes of UVR exposure per day, exposure per weekday, exposure per weekend day, and per day between 10am and 4pm (peak hours). Because the UVR data were skewed to the right with a few large exposures, median exposure levels were calculated and compared by randomization group using Wilcoxon rank sum tests and within the intervention group using Wilcoxon signed rank test. Descriptive statistics were used to summarize satisfaction and usability. Surveys had minimal missing data, and with little loss-to-follow-up, we analyzed the complete data only. All tests were two-sided. Data were analyzed using SAS 9.4 and p-values <0.05 were considered statistically significant.