Most young adult cancer survivors (YACS) do not meet physical activity (PA) guidelines. Although PA can improve health and quality of life (QOL), few randomized controlled trials (RCTs) of PA interventions for YACS exist. We conducted a pilot RCT to test feasibility of a PA intervention among YACS.
Methods:
We recruited 18–39-year-olds (≥1 and <5 years postcancer therapy) from Seattle Cancer Care Alliance. The 12-week intervention involved a wrist-worn PA-tracking device (Fitbit), a peer-based Facebook support group, step count goal setting, and a self-selected support “buddy.” Controls received Fitbit only. Baseline assessments occurred before randomization; follow-up assessments occurred during intervention weeks 10–12. Feasibility criteria are listed below. Exploratory outcomes included PA, sedentary time (ST), QOL measures (e.g., fatigue), and self-determination theory (SDT) construct measures.
Results:
All feasibility criteria were met: We recruited 50 YACS, intervention participants wore the Fitbit on the majority of intervention days (82.9%), ≥75% of participants completed questionnaires at baseline (100%) and follow-up (93.9%). Exploratory analyses, adjusted for wave, accelerometer wear time, race, and income, showed significant group differences for change in ST (−52.4 vs. 2.5 minutes/day; p = 0.002) but no change in moderate-to-vigorous intensity PA (0.0 vs. −0.2 minutes/day; p = 0.40), comparing intervention participants to controls. The intervention (vs. control) group had a greater increase in fatigue interference (p = 0.03). No other significant differences in SDT or QOL measures were found.
Conclusion:
This Fitbit and Facebook-based PA intervention was feasible to YACS, with promising effects on reducing ST, and warrants a fully powered RCT.
Clinical Trial Registration no.: NCT03233581.
Get full access to this article
View all access options for this article.
References
1.
SmithWA, NolanVG, RobisonLL, et al.Physical activity among cancer survivors and those with no history of cancer—a report from the National Health and Nutrition Examination Survey 2003–2006. Am J Transl Res. 2011; 3(4):342.
2.
SwainCT, NguyenNH, EaglesT, et al.Postdiagnosis sedentary behavior and health outcomes in cancer survivors: a systematic review and meta-analysis. Cancer. 2020; 126(4):861–9.
3.
FullerJT, HartlandMC, MaloneyLT, DavisonK. Therapeutic effects of aerobic and resistance exercises for cancer survivors: a systematic review of meta-analyses of clinical trials. Br J Sports Med. 2018; 52(20):1311.
4.
CormieP, ZopfEM, ZhangX, SchmitzKH. The impact of exercise on cancer mortality, recurrence, and treatment-related adverse effects. Epidemiol Rev. 2017; 39(1):71–92.
5.
RicciC, LeitzmannMF, FreislingH, et al.Diet and sedentary behaviour in relation to mortality in US adults with a cardiovascular condition: results from the National Health and Nutrition Examination Survey linked to the US mortality registry. Br J Nutr. 2020; 124(12):1329–37.
6.
GilchristSC, HowardVJ, AkinyemijuT, et al.Association of sedentary behavior with cancer mortality in middle-aged and older US adults. JAMA Oncol. 2020; 6(8):1210–7.
7.
BleyerA, O'learyM, BarrR, RiesL. Cancer epidemiology in older adolescents and young adults 15 to 29 years of age, including SEER incidence and survival: 1975–2000. National Cancer Institute, NIH Pub. No. 06–5767. Bethesda, MD; 2006.
8.
GroenWG, van HartenWH, VallanceJK. 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.
9.
BradfordNK, ChanRJ. Health promotion and psychological interventions for adolescent and young adult cancer survivors: a systematic literature review. Cancer Treat Rev. 2017; 55:57–70.
10.
PughG, GravestockHL, HoughRE, et al.Health behavior change interventions for teenage and young adult cancer survivors: a systematic review. J Adolesc Young Adult Oncol. 2016; 5(2):91–105.
11.
RabinC.Barriers to increasing physical activity among young adult cancer survivors. J Adolesc Young Adult Oncol. 2017; 6(2):372–6.
HaberlinC, O'DwyerT, MocklerD, et al.The use of eHealth to promote physical activity in cancer survivors: a systematic review. Support Care Cancer. 2018; 26(10):3323–36.
KoppLM, GastelumZ, GuerreroCH, et al.Lifestyle behavior interventions delivered using technology in childhood, adolescent, and young adult cancer survivors: a systematic review. Pediatr Blood Cancer. 2017; 64(1):13–7.
17.
ValleCG, TateDF, MayerDK, et al.A randomized trial of a Facebook-based physical activity intervention for young adult cancer survivors. J Cancer Surviv. 2013; 7(3):355–68.
18.
RabinC, DunsigerS, NessKK, MarcusBH. Internet-based physical activity intervention targeting young adult cancer survivors. J Adolesc Young Adult Oncol. 2011; 1(4):188–94.
19.
MendozaJA, BakerKS, MorenoMA, et al.A Fitbit and Facebook mHealth intervention for promoting physical activity among adolescent and young adult childhood cancer survivors: a pilot study. Pediatr Blood Cancer. 2017; 64(12):e26660.
20.
FinkelsteinEA, HaalandBA, BilgerM, et al.Effectiveness of activity trackers with and without incentives to increase physical activity (TRIPPA): a randomised controlled trial. Lancet Diabetes Endocrinol. 2016; 4(12):983–95.
21.
TeixeiraPJ, CarraçaEV, MarklandD, et al.Exercise, physical activity, and self-determination theory: a systematic review. Int J Behav Nutr Phys Act. 2012; 9(1):78.
22.
BravataDM, Smith-SpanglerC, SundaramV, et al.Using pedometers to increase physical activity and improve health: a systematic review. JAMA. 2007; 298(19):2296–304.
23.
PumperM, MendozaJ, Arseniev-KoehlerA, et al.Using a Facebook group as an adjunct to a pilot mHealth physical activity intervention: a mixed methods approach. Stud Health Technol Inform. 2015; 219:97.
24.
MurciaJAM, de San RománML, GalindoCM, et al.Peers' influence on exercise enjoyment: a self-determination theory approach. J Sports Sci Med. 2008; 7(1):23.
25.
TamboriniR, BowmanND, EdenA, et al.Defining media enjoyment as the satisfaction of intrinsic needs. J Commun. 2010; 60(4):758–77.
26.
FarnellG, BarkleyJ. The effect of a wearable physical activity monitor (Fitbit One) on physical activity behaviour in women: a pilot study. J Hum Sport Exerc. 2017; 12(4):1230–1237.
27.
KorinekEV, PhatakSS, MartinCA, et al.Adaptive step goals and rewards: a longitudinal growth model of daily steps for a smartphone-based walking intervention. J Behav Med. 2018; 41(1):74–86.
28.
ButrynML, GodfreyKM, MartinelliMK, et al.Digital self-monitoring: does adherence or association with outcomes differ by self-monitoring target?. Obes Sci Pract. 2020; 6(2):126–33.
29.
KooimanTJ, de GrootM, HoogenbergK, et al.Self-tracking of physical activity in people with type 2 diabetes: a randomized controlled trial. Comput Inform Nurs. 2018; 36(7):340–9.
MeyerJ, WasmannM, HeutenW, et al. Identification and classification of usage patterns in long-term activity tracking. Paper presented at: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. Denver, Colorado, USA: Association for Computing Machinery, 2017.
32.
KellyR, JonesS, PriceB, et al.Measuring daily compliance with physical activity tracking in ambulatory surgery patients: comparative analysis of five compliance criteria. JMIR Mhealth Uhealth. 2021; 9(1):e22846.
33.
SushamesA, EdwardsA, ThompsonF, et al.Validity and reliability of Fitbit Flex for step count, moderate to vigorous physical activity and activity energy expenditure. PLoS One. 2016; 11(9):e0161224.
34.
ChoiL, LiuZ, MatthewsCE, BuchowskiMS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011; 43(2):357.
35.
TroianoRP, BerriganD, DoddKW, et al.Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008; 40(1):181.
36.
Tudor-LockeC, CamhiSM, TroianoRP. Peer reviewed: a catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003–2006. Prev Chronic Dis. 2012; 9:E113.
37.
MullanE, MarklandD, IngledewDK. A graded conceptualisation of self-determination in the regulation of exercise behaviour: development of a measure using confirmatory factor analytic procedures. Pers Individ Dif. 1997; 23(5):745–52.
38.
WilsonPM, RodgersWM, LoitzCC, ScimeG. “It's Who I Am… Really!’The importance of integrated regulation in exercise contexts. J Appl Biobehav Res. 2006; 11(2):79–104.
39.
MarklandD, TobinV. A modification to the behavioural regulation in exercise questionnaire to include an assessment of amotivation. J Sport Exerc Psychol. 2004; 26(2):191–6.
40.
MotlRW, DishmanRK, SaundersR, et al.Measuring enjoyment of physical activity in adolescent girls. Am J Prev Med. 2001; 21(2):110–7.
41.
KendzierskiD, DeCarloKJ. Physical activity enjoyment scale: two validation studies. J Sport Exerc Psychol. 1991; 13(1):50–64.
42.
KendzierskiD, MorgansteinMS. Test, revision, and cross-validation of the physical activity self-definition model. J Sport Exerc Psychol. 2009; 31(4):484–504.
43.
RaedekeTD.The relationship between enjoyment and affective responses to exercise. J Appl Sport Psychol. 2007; 19(1):105–15.
44.
WilsonPM, RogersWT, RodgersWM, WildTC. The psychological need satisfaction in exercise scale. J Sport Exerc Psychol. 2006; 28(3):231–51.
45.
JensenRE, PotoskyAL, ReeveBB, et al.Validation of the PROMIS physical function measures in a diverse US population-based cohort of cancer patients. Qual Life Res. 2015; 24(10):2333–44.
46.
GarciaSF, CellaD, ClauserSB, et al.Standardizing patient-reported outcomes assessment in cancer clinical trials: a patient-reported outcomes measurement information system initiative. J Clin Oncol. 2007; 25(32):5106–12.
47.
DonovanKA, JacobsenPB. The Fatigue Symptom Inventory: a systematic review of its psychometric properties. Support Care Cancer. 2011; 19(2):169–85.
48.
CellaD, LaiJs, ChangCH, et al.Fatigue in cancer patients compared with fatigue in the general United States population. Cancer. 2002; 94(2):528–38.
49.
OkunML, KravitzHM, SowersMF, et al.Psychometric evaluation of the Insomnia Symptom Questionnaire: a self-report measure to identify chronic insomnia. J Clin Sleep Med. 2009; 5(1):41–51.
50.
YanH, KarmurBS, KulkarniAV. Comparing effects of treatment: controlling for confounding. Neurosurgery. 2020; 86(3):325–31.
51.
ThrulJ, KleinAB, RamoDE. Smoking cessation intervention on Facebook: which content generates the best engagement?. J Med Internet Res. 2015; 17(11):e244.
52.
CavalloDN, TateDF, WardDS, et al.Social support for physical activity—role of Facebook with and without structured intervention. Transl Behav Med. 2014; 4(4):346–54.
53.
MiropolskyEM, BakerKS, Abbey-LambertzM, et al.Participant perceptions on a Fitbit and Facebook intervention for young adult cancer survivors: a qualitative study. J Adolesc Young Adult Oncol. 2020; 9(3):410–7.
54.
BrownJC, Huedo-MedinaTB, PescatelloLS, et al.Efficacy of exercise interventions in modulating cancer-related fatigue among adult cancer survivors: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2011; 20(1):123–33.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
