Optimization of a technology-supported physical activity promotion intervention for breast cancer survivors: Results from Fit2Thrive

Siobhan M Phillips, Frank J Penedo, Linda M Collins, Payton Solk, Juned Siddique, Jing Song, David Cella, Kerry S Courneya, Ronald T Ackermann, Whitney A Welch, Lisa A Auster-Gussman, Madelyn Whitaker, Erin Cullather, Emily Izenman, Bonnie Spring, Siobhan M Phillips, Frank J Penedo, Linda M Collins, Payton Solk, Juned Siddique, Jing Song, David Cella, Kerry S Courneya, Ronald T Ackermann, Whitney A Welch, Lisa A Auster-Gussman, Madelyn Whitaker, Erin Cullather, Emily Izenman, Bonnie Spring

Abstract

Background: The benefits of moderate to vigorous physical activity (MVPA) for breast cancer survivors are well established. However, most are insufficiently active. Fit2Thrive used the Multiphase Optimization Strategy methodology to determine the effect of 5 intervention components on MVPA in this population.

Methods: Two hundred sixty-nine participants (mean age, 52.5 years; SD, 9.9 years) received a core intervention (the Fit2Thrive self-monitoring app and Fitbit) and were randomly assigned to 5 intervention components set to on/off in a full factorial experiment: support calls, deluxe app, buddy, online gym, and text messages. The intervention was delivered over 12 weeks with a 12-week follow-up. MVPA was measured via accelerometry at the baseline (T1), at 12 weeks (T2), and at 24 weeks (T3). The main effects and interaction effects at each time point were examined for all components.

Results: Trial retention was high: 91.8% had valid accelerometer data at T2 or T3. Across all conditions, there were significant increases in MVPA (+53.6 min/wk; P < .001) and in the proportion of survivors meeting MVPA guidelines (+22.3%; P < .001) at T2 that were maintained but attenuated at T3 (MVPA, +24.6 min/wk; P < .001; meeting guidelines, +12.6%; P < .001). No individual components significantly improved MVPA, although increases were greater for the on level versus the off level for support calls, buddy, and text messages at T2 and T3.

Conclusions: The Fit2Thrive core intervention (the self-monitoring app and Fitbit) is promising for increasing MVPA in breast cancer survivors, but the components provided no additional increases in MVPA. Future research should evaluate the core intervention in a randomized trial and determine what components optimize MVPA behaviors in breast cancer survivors.

Keywords: behavior change; breast cancer survivors; digital health; intervention; physical activity.

Conflict of interest statement

The authors have no conflict of interests to report.

© 2021 American Cancer Society.

Figures

Figure 1.
Figure 1.
Consolidated Standards of Reporting Trials (CONSORT) diagram depicting participant flow through the study

References

    1. Ibrahim EM, Al-Homaidh A. Physical activity and survival after breast cancer diagnosis: meta-analysis of published studies. Med Oncol. 2011;28:753–765.
    1. McNeely ML, Campbell KL, Rowe BH, Klassen TP, Mackey JR, Courneya KS. Effects of exercise on breast cancer patients and survivors: a systematic review and meta-analysis. CMAJ. 2006;175:34–41.
    1. Speck RM, Courneya KS, Masse LC, Duval S, Schmitz KH. An update of controlled physical activity trials in cancer survivors: a systematic review and meta-analysis. J Cancer Surviv. 2010;4:87–100.
    1. Ballard-Barbash R, Friedenreich CM, Courneya KS, Siddiqi SM, McTiernan A, Alfano CM. Physical activity, biomarkers, and disease outcomes in cancer survivors: a systematic review. J Natl Cancer Inst. 2012;104:815–840.
    1. Arem H, Mama SK, Duan X, Rowland JH, Bellizzi KM, Ehlers DK. Prevalence of healthy behaviors among cancer survivors in the United States: how far have we come? Cancer Epidemiol Biomarkers Prev. 2020;29:1179–1187.
    1. Thraen-Borowski KM, Gennuso KP, Cadmus-Bertram L. Accelerometer-derived physical activity and sedentary time by cancer type in the United States. PLoS One.2017;12:e0182554.
    1. Jones LW, Alfano CM. Exercise-oncology research: past, present, and future. Acta Oncologica. 2013;52:195–215.
    1. Phillips SM, Alfano CM, Perna FM, Glasgow RE. Accelerating translation of physical activity and cancer survivorship research into practice: recommendations for a more integrated and collaborative approach. Cancer Epidemiol Biomarkers Prev. 2014;23:687–699.
    1. Hardcastle SJ, Maxwell-Smith C, Kamarova S, Lamb S, Millar L, Cohen PA. Factors influencing non-participation in an exercise program and attitudes towards physical activity amongst cancer survivors. Suppor Care Cancer. 2018;26: 1289–1295.
    1. Blaney J, Lowe-Strong A, Rankin-Watt J, Campbell A, Gracey J. Cancer survivors’ exercise barriers, facilitators and preferences in the context of fatigue, quality of life and physical activity participation: a questionnaire–survey. Psychooncology. 2013;22:186–194.
    1. Groen WG, van Harten WH, Vallance JK. Systematic review and meta-analysis of distance-based physical activity interventions for cancer survivors (2013–2018): We still haven’t found what we’re looking for. Cancer Treat Rev. 2018;69: 188–203.
    1. Dorri S, Asadi F, Olfatbakhsh A, Kazemi A. A systematic review of electronic health (eHealth) interventions to improve physical activity in patients with breast cancer. Breast Cancer. 2020:1–22.
    1. Phillips SM, Conroy DE, Keadle SK, et al. Breast cancer survivors’ preferences for technology-supported exercise interventions. Support Care Cancer. 2017;25:3243–3252.
    1. Nguyen NH, Hadgraft NT, Moore MM, et al. A qualitative evaluation of breast cancer survivors’ acceptance of and preferences for consumer wearable technology activity trackers. Support Care Cancer. 2017:1–10.
    1. Pew Research Center. U.S. Smartphone Use in 2015.
    1. Coughlin SS, Caplan LS, Stone R. Use of consumer wearable devices to promote physical activity among breast, prostate, and colorectal cancer survivors: a review of health intervention studies. J Cancer Surviv. 2020;14:386–392.
    1. Lynch BM, Nguyen NH, Moore MM, et al. A randomized controlled trial of a wearable technology-based intervention for increasing moderate to vigorous physical activity and reducing sedentary behavior in breast cancer survivors: The ACTIVATE Trial. Cancer. 2019;125: 2846–2855.
    1. Martin Payo R, Harris J, Armes J. Prescribing fitness apps for people with cancer: a preliminary assessment of content and quality of commercially available apps. J Cancer Surviv. 2019;13: 397–405.
    1. Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med. 2007;32:S112–S118.
    1. Collins LM, Kugler KC, Gwadz MV. Optimization of multicomponent behavioral and biobehavioral interventions for the prevention and treatment of HIV/AIDS. AIDS Behav. 2016;20:197–214.
    1. Collins LM. Optimization of behavioral, biobehavioral, and biomedical interventions: The multiphase optimization strategy (MOST). Springer, 2018.
    1. Collins LM, Dziak JJ, Li R. Design of experiments with multiple independent variables: a resource management perspective on complete and reduced factorial designs. Psychol Methods. 2009;14:202–224.
    1. Phillips SM, Collins LM, Penedo FJ, et al. Optimization of a technology-supported physical activity intervention for breast cancer survivors: Fit2Thrive study protocol. Contemp Clin Trials. 2018;66:9–19.
    1. Thomas S, Reading J, Shephard RJ. Revision of the physical activity readiness questionnaire (PAR-Q). Can J Sport Sci. 1992;17:338–345.
    1. Phillips SM, Conroy DE, Keadle SK, et al. Breast cancer survivors’ preferences for technology-supported exercise interventions. Suppor Care Cancer. 2017:25:3243–3252.
    1. Welch WA, Solk P, Auster-Gussman L, et al. User-centered development of a smartphone application (Fit2Thrive) to promote physical activity in breast cancer survivors. Transl Behav Med. 2021.
    1. Bandura A. The explanatory and predictive scope of self-efficacy theory. J Soc Clin Psychol. 1986;4:359–373.
    1. Phillips SM, McAuley E. Social cognitive influences on physical activity participation in long-term breast cancer survivors. Psychooncology. 2012;22:783–791.
    1. Stacey FG, James EL, Chapman K, Courneya KS, Lubans DR. A systematic review and meta-analysis of social cognitive theory-based physical activity and/or nutrition behavior change interventions for cancer survivors. J Cancer Surviv. 2015;9:305–338.
    1. Goode AD, Lawler SP, Brakenridge CL, Reeves MM, Eakin EG. Telephone, print, and Web-based interventions for physical activity, diet, and weight control among cancer survivors: a systematic review. J Cancer Surviv. 2015;9:660–682.
    1. McEwan D, Harden SM, Zumbo BD, et al. The effectiveness of multi-component goal setting interventions for changing physical activity behaviour: a systematic review and meta-analysis. Health Psychol Rev. 2016;10:67–88.
    1. Gilliam MB, Madan-Swain A, Whelan K, Tucker DC, Demark-Wahnefried W, Schwebel DC. Cognitive influences as mediators of family and peer support for pediatric cancer survivors’ physical activity. Psychooncology. 2013;22: 1361–1368.
    1. Su JA, Yeh DC, Chang CC, et al. Depression and family support in breast cancer patients. Neuropsychiatr Dis Treat. 2017;13:2389–2396.
    1. Barber FD. Social support and physical activity engagement by cancer survivors. Clin J Oncol Nursi. 2012;16:E84–E98.
    1. Bluethmann SM, Vernon SW, Gabriel KP, Murphy CC, Bartholomew LK. Taking the next step: a systematic review and meta-analysis of physical activity and behavior change interventions in recent post-treatment breast cancer survivors. Breast Cancer Res Treat. 2015;149: 331–342.
    1. Bassett DR. Validity of four motion sensors in measuring moderate intensity physical activity. Med Sci Sports Exerc. 2000;32:S471.
    1. Tudor-Locke C, Ainsworth B, Thompson R, Matthews C. Comparison of pedometer and accelerometer measures of free-living physical activity. Med Sci Sports Exercise. 2002;34:2045–2041.
    1. Choi L, Liu Z, Matthews CE, Buchowski MS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011;43:357–364.
    1. Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008;40:181–188.
    1. Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30:777–781.
    1. Hedeker D, Gibbons RD, Waternaux C. Sample size estimation for longitudinal designs with attrition: comparing time-related contrasts between two groups. Journal of Educational and Behavioral Statistics. 1999;24:70–93.
    1. SAS Institute Inc 2013. SAS/ACCESS® 9.4 Interface to ADABAS: Reference. Cary NSII.
    1. SAS Institute Inc 2013. SAS/ACCESS® 9.4 Interface to ADABAS: Reference. Cary NSII. Available from URL: .
    1. Rogers LQ, Courneya KS, Anton PM, et al. Effects of the BEAT Cancer physical activity behavior change intervention on physical activity, aerobic fitness, and quality of life in breast cancer survivors: a multicenter randomized controlled trial. Breast Cancer Res Treat. 2015;149:109–119.
    1. Li T, Wei S, Shi Y, et al. The dose–response effect of physical activity on cancer mortality: findings from 71 prospective cohort studies. Br J Sports Med. 2016;50:339–345.
    1. Collins LM, Baker TB, Mermelstein RJ, et al. The multiphase optimization strategy for engineering effective tobacco use interventions. Ann Behav Med. 2011;41:208–226.

Source: PubMed

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