Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study

Marie-Therése Crafoord, Maria Fjell, Kay Sundberg, Marie Nilsson, Ann Langius-Eklöf, Marie-Therése Crafoord, Maria Fjell, Kay Sundberg, Marie Nilsson, Ann Langius-Eklöf

Abstract

Background: Using mobile technology for symptom management and self-care can improve patient-clinician communication and clinical outcomes in patients with cancer. The interactive app Interaktor has been shown to reduce symptom burden during cancer treatment. It includes symptom assessment, an alert system for contact with health care professionals, access to self-care advice, and visualization of symptom history. It is essential to understand how digital interventions operate; one approach is to examine engagement by assessing usage and exploring user experiences. Actual usage in relation to the intended use-adherence-is an essential factor of engagement.

Objective: This study aimed to describe engagement with the Interaktor app among patients with breast or prostate cancer during treatment.

Methods: Patients from the intervention groups of two separate randomized controlled trials were included: patients with breast cancer receiving neoadjuvant chemotherapy (n=74) and patients with locally advanced prostate cancer receiving treatment with radiotherapy (n=75). The patients reported their symptoms daily. Sociodemographic and clinical data were obtained from baseline questionnaires and medical records. Logged data usage was retrieved from the server and analyzed descriptively and with multiple regression analysis. Telephone interviews were conducted with patients about their perceptions of using the app and analyzed using content analysis.

Results: The median adherence percentage to daily symptom reporting was 83%. Most patients used the self-care advice and free text message component. Among the patients treated for breast cancer, higher age predicted a higher total number of free text messages sent (P=.04). Among the patients treated for prostate cancer, higher age (P=.01) and higher education level (P=.04), predicted an increase in total views on self-care advice, while higher comorbidity (P=.004) predicted a decrease in total views on self-care advice. Being married or living with a partner predicted a higher adherence to daily symptom reporting (P=.02). Daily symptom reporting created feelings of having continuous contact with health care professionals, being acknowledged, and safe. Being contacted by a nurse after a symptom alert was considered convenient and highly valued. Treatment and time-related aspects influenced engagement. Daily symptom reporting was perceived as particularly meaningful at the beginning of treatment. Requests were made for advice on diet and psychological symptoms, as well as for more comprehensive and detailed information as the patient progressed through treatment.

Conclusions: Patient engagement in the interactive app Interaktor was high. The app promoted patient participation in their care through continuous and convenient contact with health care professionals. The predictive ability of demographic variables differed between patient groups, but higher age and a higher educational level predicted higher usage of specific app functions for both patient groups. Patients' experience of relevance and interactivity influenced their engagement positively.

Keywords: adherence; breast cancer; cancer supportive care; engagement; mHealth; mobile app; prostate cancer; symptom management; usage metrics.

Conflict of interest statement

Conflicts of Interest: None declared.

©Marie-Therése Crafoord, Maria Fjell, Kay Sundberg, Marie Nilsson, Ann Langius-Eklöf. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 10.08.2020.

Figures

Figure 1
Figure 1
CONSORT diagram.
Figure 2
Figure 2
Adherence to symptom reporting over time.

References

    1. McKenzie H, Hayes L, White K, Cox K, Fethney J, Boughton M, Dunn J. Chemotherapy outpatients' unplanned presentations to hospital: a retrospective study. Support Care Cancer. 2011 Jul;19(7):963–9. doi: 10.1007/s00520-010-0913-y.
    1. Lai XB, Ching SSY, Wong FKY. A qualitative exploration of the experiences of patients with breast cancer receiving outpatient-based chemotherapy. J Adv Nurs. 2017 Oct;73(10):2339–2350. doi: 10.1111/jan.13309.
    1. Hinami K, Alkhalil A, Chouksey S, Chua J, Trick WE. Clinical significance of physical symptom severity in standardized assessments of patient reported outcomes. Qual Life Res. 2016 Sep;25(9):2239–43. doi: 10.1007/s11136-016-1261-2.10.1007/s11136-016-1261-2
    1. Basch E, Deal AM, Kris MG, Scher HI, Hudis CA, Sabbatini P, Rogak L, Bennett AV, Dueck AC, Atkinson TM, Chou JF, Dulko D, Sit L, Barz A, Novotny P, Fruscione M, Sloan JA, Schrag D. Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. J Clin Oncol. 2016 Feb 20;34(6):557–65. doi: 10.1200/JCO.2015.63.0830.JCO.2015.63.0830
    1. Kearney N, McCann L, Norrie J, Taylor L, Gray P, McGee-Lennon M, Sage M, Miller M, Maguire R. Evaluation of a mobile phone-based, advanced symptom management system (ASyMS) in the management of chemotherapy-related toxicity. Support Care Cancer. 2009 Apr;17(4):437–44. doi: 10.1007/s00520-008-0515-0.
    1. Ruland CM, Andersen T, Jeneson A, Moore S, Grimsbø GH, Børøsund E, Ellison MC. Effects of an internet support system to assist cancer patients in reducing symptom distress: a randomized controlled trial. Cancer Nurs. 2013;36(1):6–17. doi: 10.1097/NCC.0b013e31824d90d4.
    1. Rincon E, Monteiro-Guerra F, Rivera-Romero O, Dorronzoro-Zubiete E, Sanchez-Bocanegra CL, Gabarron E. Mobile phone apps for quality of life and well-being assessment in breast and prostate cancer patients: systematic review. JMIR Mhealth Uhealth. 2017 Dec 04;5(12):e187. doi: 10.2196/mhealth.8741. v5i12e187
    1. Giunti G, Giunta DH, Guisado-Fernandez E, Bender JL, Fernandez-Luque L. A biopsy of Breast Cancer mobile applications: state of the practice review. Int J Med Inform. 2018 Feb;110:1–9. doi: 10.1016/j.ijmedinf.2017.10.022. S1386-5056(17)30402-1
    1. Warrington L, Absolom K, Conner M, Kellar I, Clayton B, Ayres M, Velikova G. Electronic systems for patients to report and manage side effects of cancer treatment: systematic review. J Med Internet Res. 2019 Jan 24;21(1):e10875. doi: 10.2196/10875. v21i1e10875
    1. Osborn J, Ajakaiye A, Cooksley T, Subbe CP. Do mHealth applications improve clinical outcomes of patients with cancer? a critical appraisal of the peer-reviewed literature. Support Care Cancer. 2020 Mar;28(3):1469–1479. doi: 10.1007/s00520-019-04945-4. 10.1007/s00520-019-04945-4
    1. Richards R, Kinnersley P, Brain K, McCutchan G, Staffurth J, Wood F. Use of mobile devices to help cancer patients meet their information needs in non-inpatient settings: systematic review. JMIR Mhealth Uhealth. 2018 Dec 14;6(12):e10026. doi: 10.2196/10026. v6i12e10026
    1. Boulos MNK, Brewer AC, Karimkhani C, Buller DB, Dellavalle RP. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform. 2014;5(3):229. doi: 10.5210/ojphi.v5i3.4814. ojphi-05-e229
    1. Gomolin A, Lebouché B, Engler K, Vedel I. Optimizing smartphone intervention features to improve chronic disease management: A rapid review. Health Informatics J. 2019 Dec 12;:1460458219891377. doi: 10.1177/1460458219891377.
    1. Doherty K, Doherty G. Engagement in HCI. ACM Comput. Surv. 2018 Jan 23;51(5):1–39. doi: 10.1145/3234149.
    1. Perski Olga, Blandford Ann, West Robert, Michie Susan. Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis. Transl Behav Med. 2017 Jun;7(2):254–267. doi: 10.1007/s13142-016-0453-1. 10.1007/s13142-016-0453-1
    1. O'Brien HL, Toms EG. What is user engagement? A conceptual framework for defining user engagement with technology. J. Am. Soc. Inf. Sci. 2008 Apr 28;59(6):938–955. doi: 10.1002/asi.20801.
    1. Eysenbach G. The law of attrition. J Med Internet Res. 2005;7(1):e11. doi: 10.2196/jmir.7.1.e11. v7e11
    1. Olsson L, Jakobsson UE, Swedberg K, Ekman I. Efficacy of person-centred care as an intervention in controlled trials - a systematic review. J Clin Nurs. 2013 Feb;22(3-4):456–65. doi: 10.1111/jocn.12039.
    1. Frank C, Asp M, Fridlund B, Baigi A. Questionnaire for patient participation in emergency departments: development and psychometric testing. J Adv Nurs. 2011 Mar;67(3):643–51. doi: 10.1111/j.1365-2648.2010.05472.x.
    1. Langius-Eklöf A, Crafoord M, Christiansen M, Fjell M, Sundberg K. Effects of an interactive mHealth innovation for early detection of patient-reported symptom distress with focus on participatory care: protocol for a study based on prospective, randomised, controlled trials in patients with prostate and breast cancer. BMC Cancer. 2017 Jul 04;17(1):466. doi: 10.1186/s12885-017-3450-y. 10.1186/s12885-017-3450-y
    1. Gustavell T, Langius-Eklöf A, Wengström Y, Segersvärd R, Sundberg K. Development and feasibility of an interactive smartphone app for early assessment and management of symptoms following pancreaticoduodenectomy. Cancer Nurs. 2018 Mar 27;:e1–e10. doi: 10.1097/NCC.0000000000000584.
    1. Göransson C. Developing and evaluating an interactive app to support self-care among older persons receiving home care. Örebro: Örebro University; 2019. Developing and evaluating an interactive app to support self-care among older persons receiving home care. Doctoral dissertation.
    1. Blomberg K, Wengström Y, Sundberg K, Browall M, Isaksson A, Nyman MH, Langius-Eklöf A. Symptoms and self-care strategies during and six months after radiotherapy for prostate cancer - scoping the perspectives of patients, professionals and literature. Eur J Oncol Nurs. 2016 Apr;21:139–45. doi: 10.1016/j.ejon.2015.09.004.S1462-3889(15)30027-2
    1. Sundberg K, Wengström Y, Blomberg K, Hälleberg-Nyman M, Frank C, Langius-Eklöf A. Early detection and management of symptoms using an interactive smartphone application (Interaktor) during radiotherapy for prostate cancer. Support Care Cancer. 2017 Feb 24;:2195–2204. doi: 10.1007/s00520-017-3625-8.10.1007/s00520-017-3625-8
    1. Gustavell T, Sundberg K, Frank C, Wengström Y, Browall M, Segersvärd R, Langius-Eklöf A. Symptoms and self-care following pancreaticoduodenectomy: perspectives from patients and healthcare professionals - Foundation for an interactive ICT application. Eur J Oncol Nurs. 2017 Feb;26:36–41. doi: 10.1016/j.ejon.2016.12.002.S1462-3889(16)30146-6
    1. Langius-Eklöf A, Christiansen M, Lindström V, Blomberg K, Hälleberg Nyman M, Wengström Y, Sundberg K. Adherence to report and patient perception of an interactive app for managing symptoms during radiotherapy for prostate cancer: descriptive study of logged and interview data. JMIR Cancer. 2017 Oct 31;3(2):e18. doi: 10.2196/cancer.7599. v3i2e18
    1. Portenoy RK, Thaler HT, Kornblith AB, Lepore JM, Friedlander-Klar H, Kiyasu E, Sobel K, Coyle N, Kemeny N, Norton L. The Memorial Symptom Assessment Scale: an instrument for the evaluation of symptom prevalence, characteristics and distress. Eur J Cancer. 1994;30A(9):1326–36.
    1. Egbring M, Far E, Roos M, Dietrich M, Brauchbar M, Kullak-Ublick GA, Trojan A. A mobile app to stabilize daily functional activity of breast cancer patients in collaboration with the physician: a randomized controlled clinical trial. J Med Internet Res. 2016 Sep 06;18(9):e238. doi: 10.2196/jmir.6414. v18i9e238
    1. Beck SL, Eaton LH, Echeverria C, Mooney KH. SymptomCare@Home: developing an integrated symptom monitoring and management system for outpatients receiving chemotherapy. Comput Inform Nurs. 2017 Oct;35(10):520–529. doi: 10.1097/CIN.0000000000000364.
    1. Escriva Boulley G, Leroy T, Bernetière C, Paquienseguy F, Desfriches-Doria O, Préau M. Digital health interventions to help living with cancer: a systematic review of participants' engagement and psychosocial effects. Psychooncology. 2018 Dec;27(12):2677–2686. doi: 10.1002/pon.4867.
    1. Hernandez Silva E, Lawler S, Langbecker D. The effectiveness of mHealth for self-management in improving pain, psychological distress, fatigue, and sleep in cancer survivors: a systematic review. J Cancer Surviv. 2019 Feb;13(1):97–107. doi: 10.1007/s11764-018-0730-8.10.1007/s11764-018-0730-8
    1. McCann L, Maguire R, Miller M, Kearney N. Patients' perceptions and experiences of using a mobile phone-based advanced symptom management system (ASyMS) to monitor and manage chemotherapy related toxicity. Eur J Cancer Care (Engl) 2009 Mar;18(2):156–64. doi: 10.1111/j.1365-2354.2008.00938.x.ECC938
    1. Bock M, Moore D, Hwang J, Shumay D, Lawson L, Hamolsky D, Esserman L, Rugo H, Chien AJ, Park J, Munster P, Melisko M. The impact of an electronic health questionnaire on symptom management and behavior reporting for breast cancer survivors. Breast Cancer Res Treat. 2012 Aug;134(3):1327–35. doi: 10.1007/s10549-012-2150-1.
    1. Judson TJ, Bennett AV, Rogak LJ, Sit L, Barz A, Kris MG, Hudis CA, Scher HI, Sabattini P, Schrag D, Basch E. Feasibility of long-term patient self-reporting of toxicities from home via the internet during routine chemotherapy. J Clin Oncol. 2013 Jul 10;31(20):2580–5. doi: 10.1200/JCO.2012.47.6804. JCO.2012.47.6804
    1. Berry DL, Hong F, Halpenny B, Partridge A, Fox E, Fann JR, Wolpin S, Lober WB, Bush N, Parvathaneni U, Amtmann D, Ford R. The electronic self report assessment and intervention for cancer: promoting patient verbal reporting of symptom and quality of life issues in a randomized controlled trial. BMC Cancer. 2014;14:513. doi: 10.1186/1471-2407-14-513. 1471-2407-14-513
    1. Short C, Rebar A, Plotnikoff R, Vandelanotte C. Health Psychol Rev. European Health Psychology Society; 2015. [2020-07-22]. Designing engaging online behaviour change interventions: a proposed model of user engagement. .
    1. Sieverink F, Kelders SM, van GJE. Clarifying the concept of adherence to ehealth technology: systematic review on when usage becomes adherence. J Med Internet Res. 2017 Dec 06;19(12):e402. doi: 10.2196/jmir.8578. v19i12e402
    1. Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N. A systematic review of the impact of adherence on the effectiveness of e-therapies. J Med Internet Res. 2011;13(3):e52. doi: 10.2196/jmir.1772. v13i3e52
    1. Early Breast Cancer Trialists' Collaborative Group (EBCTCG) Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials. Lancet Oncol. 2018 Jan;19(1):27–39. doi: 10.1016/S1470-2045(17)30777-5. S1470-2045(17)30777-5
    1. Van de Wiel M, Dockx Y, Van den Wyngaert T, Stroobants S, Tjalma WAA, Huizing MT. Neoadjuvant systemic therapy in breast cancer: challenges and uncertainties. Eur J Obstet Gynecol Reprod Biol. 2017 Mar;210:144–156. doi: 10.1016/j.ejogrb.2016.12.014.S0301-2115(16)31076-4
    1. Swain SM. Chemotherapy: updates and new perspectives. Oncologist. 2011;16 Suppl 1:30–9. doi: 10.1634/theoncologist.2011-S1-30. doi: 10.1634/theoncologist.2011-S1-30.16/suppl_1/30
    1. Steenbruggen TG, van Ramshorst MS, Kok M, Linn SC, Smorenburg CH, Sonke GS. Neoadjuvant therapy for breast cancer: established concepts and emerging strategies. Drugs. 2017 Aug;77(12):1313–1336. doi: 10.1007/s40265-017-0774-5.10.1007/s40265-017-0774-5
    1. . Stockholm, Sweden: Regional cancercentrum i samverkan; 2020. May 21, [2019-01-30]. Nationellt vårdprogram bröstcancer.
    1. Regionala Cancercentrum i Samverkan. Stockholm, Sweden: 2020. Mar 03, [2020-04-01]. Prostatacancer Nationellt vårdprogram (National Care Program Prostate Cancer)
    1. Fjell M, Langius-Eklöf A, Nilsson M, Wengström Y, Sundberg K. Reduced symptom burden with the support of an interactive app during neoadjuvant chemotherapy for breast cancer - A randomized controlled trial. Breast. 2020 Jun;51:85–93. doi: 10.1016/j.breast.2020.03.004. S0960-9776(20)30083-7
    1. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.
    1. Altman D. Practical statistics for medical research. London: Chapman and Hall; 1990. p. 9780412276309.
    1. Hsieh H, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005 Nov;15(9):1277–88. doi: 10.1177/1049732305276687.15/9/1277
    1. Kelders SM, Kok RN, Ossebaard HC, Van GJEWC. Persuasive system design does matter: a systematic review of adherence to web-based interventions. J Med Internet Res. 2012;14(6):e152. doi: 10.2196/jmir.2104. v14i6e152
    1. Beatty L, Binnion C. A systematic review of predictors of, and reasons for, adherence to online psychological interventions. Int J Behav Med. 2016 Dec;23(6):776–794. doi: 10.1007/s12529-016-9556-9.10.1007/s12529-016-9556-9
    1. Waibel S, Henao D, Aller M, Vargas I, Vázquez M. What do we know about patients' perceptions of continuity of care? a meta-synthesis of qualitative studies. Int J Qual Health Care. 2012 Feb;24(1):39–48. doi: 10.1093/intqhc/mzr068.mzr068
    1. Børøsund E, Cvancarova M, Ekstedt M, Moore SM, Ruland CM. How user characteristics affect use patterns in web-based illness management support for patients with breast and prostate cancer. J Med Internet Res. 2013;15(3):e34. doi: 10.2196/jmir.2285. v15i3e34
    1. Moradian S, Voelker N, Brown C, Liu G, Howell D. Effectiveness of internet-based interventions in managing chemotherapy-related symptoms in patients with cancer: a systematic literature review. Support Care Cancer. 2018 Feb;26(2):361–374. doi: 10.1007/s00520-017-3900-8.10.1007/s00520-017-3900-8
    1. Yardley L, Spring BJ, Riper H, Morrison LG, Crane DH, Curtis K, Merchant GC, Naughton F, Blandford A. Understanding and promoting effective engagement with digital behavior change interventions. Am J Prev Med. 2016 Nov;51(5):833–842. doi: 10.1016/j.amepre.2016.06.015.S0749-3797(16)30243-4
    1. Rai A, Chen L, Pye J, Baird A. Understanding determinants of consumer mobile health usage intentions, assimilation, and channel preferences. J Med Internet Res. 2013 Aug 02;15(8):e149. doi: 10.2196/jmir.2635. v15i8e149
    1. Ryan C, Bergin M, Wells JS. Theoretical perspectives of adherence to web-based interventions: a scoping review. Int J Behav Med. 2017 Jul 20;:17–29. doi: 10.1007/s12529-017-9678-8.10.1007/s12529-017-9678-8
    1. Thórarinsdóttir K, Kristjánsson K. Patients' perspectives on person-centred participation in healthcare: a framework analysis. Nurs Ethics. 2014 Mar;21(2):129–47. doi: 10.1177/0969733013490593.0969733013490593
    1. Florin J, Ehrenberg A, Ehnfors M. Clinical decision-making: predictors of patient participation in nursing care. J Clin Nurs. 2008 Nov;17(21):2935–44. doi: 10.1111/j.1365-2702.2008.02328.x.
    1. Kolovos P, Kaitelidou D, Lemonidou C, Sachlas A, Sourtzi P. Patients’ perceptions and preferences of participation in nursing care. Journal of Research in Nursing. 2016 Mar 08;21(4):290–303. doi: 10.1177/1744987116633498.
    1. Lalmas M, O'Brien H, Yom-Tov E. Measuring User Engagement. Synthesis Lectures on Information Concepts, Retrieval, and Services. 2014 Nov;6(4):1–132. doi: 10.2200/s00605ed1v01y201410icr038.
    1. Alkhaldi G, Hamilton FL, Lau R, Webster R, Michie S, Murray E. The effectiveness of technology-based strategies to promote engagement with digital interventions: a systematic review protocol. JMIR Res Protoc. 2015;4(2):e47. doi: 10.2196/resprot.3990. v4i2e47
    1. Beatty L, Kemp E, Binnion C, Turner J, Milne D, Butow P, Lambert S, Yates P, Yip D, Koczwara B. Uptake and adherence to an online intervention for cancer-related distress: older age is not a barrier to adherence but may be a barrier to uptake. Support Care Cancer. 2017 Jun;25(6):1905–1914. doi: 10.1007/s00520-017-3591-1.10.1007/s00520-017-3591-1

Source: PubMed

3
구독하다