How stress management improves quality of life after treatment for breast cancer

Abstract

The range of effects of psychosocial interventions on quality of life among women with breast cancer remains uncertain. Furthermore, it is unclear which components of multimodal interventions account for such effects. To address these issues, the authors tested a 10-week group cognitive-behavioral stress management intervention among 199 women newly treated for nonmetastatic breast cancer, following them for 1 year after recruitment. The intervention reduced reports of social disruption and increased emotional well-being, positive states of mind, benefit finding, positive lifestyle change, and positive affect for up to 12 months (indeed, some effects strengthened over time). With respect to mechanisms tested, the intervention increased confidence in being able to relax at will. There was also evidence that effects of the intervention on the various outcomes examined were mediated by change in confidence about being able to relax. Thus, this intervention had beneficial effects on diverse aspects of quality of life after treatment for breast cancer, which appear linked to a specific stress management skill taught in the intervention.

Figure 1

Experimental design and flow diagram of participation. T = Time.

Figure 2

Structural model of latent growth curves using outcome variables at three assessments (at 6-month intervals) to define two latent variables (intercept and slope) and using experimental condition (intervention vs. control) to predict those latent variables. M_I is the differential effect of the intervention on the intercept of the growth curves. M_S is the differential effect of the intervention on change over time. An asterisk indicates that in some models tested, this loading was estimated rather than specified as 12. T = Time.

Figure 3

Mediational model, in which experimental condition predicts the slope of an outcome variable across three time points (M_S-Outcome), experimental condition predicts the slope of the Measure of Current Status (MOCS) Relaxation scale across three time points (M_S-Mocs), and the slope of the MOCS predicts the slope of the dependent variable. Mediation is suggested if M_S-Outcome no longer is significant in this model and if setting the M_S-Outcome path to zero does not significantly change model fit. M_I is the differential effect of the intervention on the intercept of the respective growth curves. M_S is the differential effect of the intervention on change over time. An asterisk indicates that in some models tested, this loading was estimated rather than specified as 12. T = Time; M_I-Outcome = mediational path of intervention effect on outcome intercept; M_I-MOCS = mediational path of intervention effect on MOCS intercept.