No abstract

Purpose Over half of young adult cancer survivors do not meet physical activity (PA) guidelines. PA interventions can enhance health and quality of life among young adult cancer survivors. However, few exercise interventions have been designed and tested in this population. This study evaluated the feasibility and preliminary efficacy of a 12-week, Facebook-based intervention (FITNET) aimed at increasing moderate-to-vigorous intensity PA compared to a Facebook-based self-help comparison (SC) condition. Methods Young adult cancer survivors (n=86) were randomly assigned to the FITNET or SC group. All participants were asked to complete self-administered online questionnaires at baseline and after 12 weeks. Results Seventy-seven percent of participants completed post-intervention assessments, and most participants reported using intervention components as intended. Participants in both groups would recommend the program to other young adult cancer survivors (FITNET: 46.9% vs. SC: 61.8%; p=0.225). Over 12 weeks, both groups increased self-reported weekly minutes of moderate-to-vigorous PA (FITNET: 67 minutes/week, p=0.009 vs. SC: 46 minutes/week, p=0.045), with no significant difference between groups. Increases in light PA were 135 minutes/week greater in the FITNET group relative to the SC group (p=0.032), and the FITNET group reported significant weight loss over time (−2.1 kg, p=0.004; p=0.083 between groups). Conclusions Facebook-based intervention approaches demonstrated potential for increasing PA in young adult cancer survivors. Implications for Cancer Survivors Social networking sites may be a feasible way for young adult cancer survivors to receive health information and support to promote PA and healthy behaviors.

In many biomedical studies, the event of interest can occur more than once in a participant. These events are termed recurrent events. However, the majority of analyses focus only on time to the first event, ignoring the subsequent events. Several statistical models have been proposed for analysing multiple events. In this paper we explore and illustrate several modelling techniques for analysis of recurrent time-to-event data, including conditional models for multivariate survival data (AG, PWP-TT and PWP-GT), marginal means/rates models, frailty and multi-state models. We also provide a tutorial for analysing such type of data, with three widely used statistical software programmes. Different approaches and software are illustrated using data from a bladder cancer project and from a study on lower respiratory tract infection in children in Brazil. Finally, we make recommendations for modelling strategy selection for analysis of recurrent event data.

Hypertension is associated with increased odds of WML, and treated uncontrolled hypertensive subjects have greater odds of WML than those with treated controlled hypertension. The data suggest that the level of blood pressure, especially systolic blood pressure, is related to WML, additional to the effects of categorically defined hypertension and its treatment and control status.