Subgroups Reporting Different Physical Activity and

Given the sizeable amount of variation observed in mean PA and SB trajectories, subgroups of breast cancer survivors following different trajectories were a better fit to the data than average trajectories. Two PA subgroups were identified: 1) 92% reported a consistent pattern of low PA from pre-diagnosis through ten years post-diagnosis (“Low but Increasing PA Subgroup”); and 2) 8% exceeded PA guidelines at all assessments but reported a significant decline at 6 months post-diagnosis that persisted through ten years post-diagnosis (“High But Declining PA Subgroup”).

My finding of two PA subgroups in a U.S. sample of breast cancer survivors is inconsistent with Brunet et al. (2014) who found five PA subgroups in Canadian survivors. Brunet et al. (2014) may have found more PA subgroups due to demographic differences between the samples and statistical issues. Demographically, the Canadian breast cancer

racial/ethnic, nationality, and educational differences. Statistically, Brunet et al. (2014) may have found a greater number of subgroups due to small sample size. Simulation studies have

confirmed that too many classes may be enumerated when model fit criteria are not adjusted for sample size (Enders, 2010b).

Three SB subgroups were identified: 1) 66% had a flat trajectory of watching TV 19-20 hours/week, which is consistent with the U.S. average (“U.S. Average TV Subgroup”); 2) 18% reported watching fewer TV hours/week than the U.S. average at pre-diagnosis and steadily increased through ten years post-diagnosis (“Low but Increasing TV subgroup”); and 3) 17% reported greater TV hours/week than the U.S. average at all assessments, with increases at six months and ten years post-diagnosis (“High but Decreasing TV Subgroup”). When PA and SB trajectories were estimated in the same model, two subgroups were observed: 1) 91% reporting low PA and TV watching consistent with the U.S. average across all time points (“Low but Increasing PA and Average TV Subgroup”); and 2) 9% reporting high PA declining over time and TV watching consistent with the U.S. average increasing over time (“High but declining PA and Average TV Subgroup”).

When PA and SB trajectories were estimated in the same model, two subgroups were observed: 1) 91% reporting low PA and TV watching consistent with the U.S. average across all time points (“Low but increasing PA and Average TV Subgroup”); and 2) 9% reporting high PA declining over time and TV watching consistent with the U.S. average increasing over time (“High but declining PA and Average TV Subgroup).

My subgroup results suggest that group means may be misleading in cancer survivors due to the presence of a small subgroup with high PA. For instance, if only the pre-diagnosis PA

engaging in 44 more minutes/week of PA (118.6 minutes/week) than 92% of the sample reported (74.3 minutes/week). Future cancer control researchers should be cognizant that means for PA and SB in cancer survivors may be misleading, and thus should consider examining subgroups when significant variance is observed.

My results of differing subgroup patterns for PA and SB also has implications for future intervention development. Specifically, breast cancer survivors with different PA and SB patterns from pre-diagnosis to ten years post-diagnosis may need tailored intervention strategies to increase (or maintain) PA to guideline levels and/or to decrease SB. For example, the “High but Declining PA and Average TV Subgroup” may need an intervention focusing on maintaining PA and decreasing SB (e.g., getting up and walking during commercial breaks or in between shows). However, the “Low but Increasing PA and Average TV Subgroup” may need an intervention focusing on both overcoming barriers to increasing PA and decreasing SB (e.g., walking during commercial or show breaks).

The next logical step toward informing potential intervention strategies is to determine whether PA and SB subgroups are predicted by the same or different theoretical constructs from health behavior theories. Toward an intervention goal, future cohort studies with cancer

survivors should consider adding questionnaires assessing theoretical constructs from health behavior theory.

Different theories may be needed to explain the health behaviors of subgroups of breast cancer survivors following different patterns. For instance, the largest subgroup in my study followed a pattern of low but increasing PA and TV watching consistent with the U.S. average. Theories targeting initiation of PA (or reduction of SB) may be best for changing health

randomized trials with breast cancer survivors (see Speck et al., 2010). Promising theoretical approaches include Social Cognitive Theory (Bandura, 1986), the Theory of Planned Behavior (Ajzen, 1991), and the Transtheoretical Model (Prochaska & DiClemente, 1983). However, no studies to date have tested an intervention targeting both increasing PA and decreasing SB.

A different theory may be necessary for the smaller subgroup who reported a pattern of high PA and TV watching lower than the U.S. average because these breast cancer survivors need to maintain PA, not initiate it. For instance, the Physical Activity Maintenance Theory (Nigg, Borrelli, Maddock, & Dishman, 2008) describes that PA maintenance is determined from individual psychosocial variables (e.g., goal-setting, motivation, barrier and relapse self-efficacy) and contextual constructs (e.g., PA environment and life stresses). More research is warranted to determine which health behavior theory constructs best predict subgroups when PA is estimated by itself, SB is estimated singly, and PA-SB are estimated in the same model.

Moving forward, observational and interventional research with cancer survivors would benefit from incorporating constructs from classic health behavior theories and the Transactional Model of Stress and Coping. Transactional Model constructs would enhance PA and SB research with cancer survivors because it assumes that emotions and affective reactions are influential predictors of health behavior (which allows for unconscious and non-rational explanations of behavior). It also includes individual-level constructs such as differences in the perception of a stressor and constructs assessing social, organizational, and cultural coping resources (e.g., perceived social support and religious coping resources), which may be able to be leveraged to change health behavior. These features of the Transactional Model allow for a richer