Employing a mobile health decision aid to improve decision-making for patients with advanced prostate cancer and their decision partners/proxies: the CHAMPION randomized controlled trial study design

Lourdes R Carhuapoma, Winter M Thayer, Catherine E Elmore, Jane Gildersleeve, Tanmay Singh, Farah Shaukat, Melissa K Uveges, Tamryn Gray, Crystal Chu, Daniel Song, Patricia J Hollen, Jennifer Wenzel, Randy A Jones, Lourdes R Carhuapoma, Winter M Thayer, Catherine E Elmore, Jane Gildersleeve, Tanmay Singh, Farah Shaukat, Melissa K Uveges, Tamryn Gray, Crystal Chu, Daniel Song, Patricia J Hollen, Jennifer Wenzel, Randy A Jones

Abstract

Background: Metastatic prostate cancer remains a lethal malignancy that warrants novel supportive interventions for patients and their decision partners and proxies. Decision aids have been applied primarily to patients with localized disease, with minimal inclusion of patients with advanced prostate cancer and their decision partners. The use of a community patient navigator (CPN) has been shown to have a positive supportive role in health care, particularly with individuals from minority populations. Research is needed to evaluate decision support interventions tailored to the needs of advanced prostate cancer patients and their decision partners in diverse populations.

Methods: Guided by Janis and Mann's Conflict Model of Decision Making, the Cancer Health Aid to Manage Preferences and Improve Outcomes through Navigation (CHAMPION) is a randomized controlled trial to assess the feasibility and acceptability of a mobile health (mHealth), CPN-administered decision support intervention designed to facilitate communication between patients, their decision partners, and the healthcare team. Adult prostate cancer patients and their decision partners at three mid-Atlantic hospitals in the USA were randomized to receive enhanced usual care or the decision intervention. The CHAMPION intervention includes a theory-based decision-making process tutorial, immediate and health-related quality of life graphical summaries over time (using mHealth), values clarification via a balance sheet procedure with the CPN support during difficult decisions, and facilitated discussions with providers to enhance informed, shared decision-making.

Discussion: The CHAMPION intervention is designed to leverage dynamic resources, such as CPN teams, mHealth technology, and theory-based information, to support decision-making for advanced prostate cancer patients and their decision partners. This intervention is intended to engage decision partners in addition to patients and represents a novel, sustainable, and scalable way to build on individual and community strengths. Patients from minority populations, in particular, may face unique challenges during clinical communication. CHAMPION emphasizes the inclusion of decision partners and CPNs as facilitators to help address these barriers to care. Thus, the CHAMPION intervention has the potential to positively impact patient and decision partner well-being by reducing decisional conflict and decision regret related to complex, treatment-based decisions, and to reduce cancer health disparities. Trial registration ClinicalTrials.gov NCT03327103 . Registered on 31 October 2017-retrospectively registered. World Health Organization Trial Registration Data Set included in Supplementary Materials.

Keywords: Advanced prostate cancer; Community patient navigator; Decision aid; Decision-making; Minorities; mHealth.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Trial design schematic for schedule of enrollment, interventions, and assessments
Fig. 2
Fig. 2
CHAMPION study design flow chart

References

    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA: Ca-Cancer J Clin 2019;69(1):7–34. PMID: 30620402 doi:10.3322/caac.21551.
    1. Howlader N, Noone A, Krapcho M, Miller D, Bishop K, Kosary C, et al., editors. SEER Cancer Statistics Review. Bethesda, Maryland: National Cancer Institute. 2017. . Accessed 24 Jul 2019.
    1. Kelly SP, Anderson WF, Rosenberg PS, Cook MB. Past, current, and future incidence rates and burden of metastatic prostate cancer in the United States. Eur Urol Focus. 2018;4(1):121–127. doi: 10.1016/j.euf.2017.10.014.
    1. Roviello G, Corona SP, Aieta M, Roudi R. Influence of age and the Gleason Score in the choice of novel hormonal therapies before and after chemotherapy. Cancer Biother Radio. 2019;34(3):141–146. doi: 10.1089/cbr.2018.2702.
    1. Wenzel JA, Mbah O, Xu J, Moscou-Jackson G, Saleem H, Sakyi K, Ford JG. A model of cancer clinical trial decision-making informed by African-American cancer patients. J Racial Ethn Health Disparities. 2015;2(2):192–199. doi: 10.1007/s40615-014-0063-x.
    1. Jones RA, Hollen PJ, Wenzel J, Weiss G, Song D, Sims T, et al. Understanding advanced prostate cancer decision making utilizing an interactive decision aid. Cancer Nurs. 2018;41(1):2–10. PMID: 27811543;PMCID: PMC5411342; doi:10.1097/NCC.0000000000000442.
    1. Gray TF, Nolan MT, Clayman ML, Wenzel JA. The decision partner in healthcare decision-making: a concept analysis. Int J Nurs. 2019; 92:79-89. PMID: 30743199; doi:10.1016/j.ijnurstu.2019.01.006.
    1. Meeker MA. Family surrogate decision making at the end of life: seeing them through with care and respect. Qualitative Health Research. 2004;14(2):204–225. PMID: 14768458; doi:10.1177/1049732303260501.
    1. Azoulay E, Pochard F, Kentish-Barnes N, Chevret S, Aboab J, Adrie C, Annane D, Bleichner G, Bollaert PE, Darmon M, Fassier T, Galliot R, Garrouste-Orgeas M, Goulenok C, Goldgran-Toledano D, Hayon J, Jourdain M, Kaidomar M, Laplace C, Larché J, Liotier J, Papazian L, Poisson C, Reignier J, Saidi F, Schlemmer B, FAMIREA Study Group. Risk of post-traumatic stress symptoms in family members of intensive care unit patients. Am J Resp Crit Care Med 2005;171(9):987–994. PMID: 15665319; doi:10.1164/rccm.200409-1295OC.
    1. Tilden VP, Tolle SW, Nelson CA, Fields J. Family decision-making to withdraw life-sustaining treatments from hospitalized patients. Nurs Res. 2001;50(2):105–115. PMID: 11302290; doi:10.1097/00006199-200103000-00006.
    1. Tang ST, McCorkle R. Use of family proxies in quality of life research for cancer patients at the end of life: a literature review. Cancer Invest 2002;20(7-8):1086–1104. PMID: 12449742; doi:10.1081/cnv-120005928.
    1. Sprangers MA, Aaronson NK. The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: a review. J Clin Epidemiol 1992;45(7):743–760. PMID: 1619454; doi:10.1016/0895-4356(92)90052-o.
    1. Noh H. Values important to terminally ill African American older adults in receiving hospice care. J Soc Work in end-of-life & palliative care 2014;10(4):338–355. PMID: 25494930; doi:10.1080/15524256.2014.975317.
    1. Bakitas M, Ahles TA, Skalla K, Brokaw FC, Byock I, Hanscom B, et al. Proxy perspectives regarding end-of-life care for persons with cancer. Cancer. 2008;112(8):1854–1861. PMID: 18306393; PMCID: PMC3638939; doi:10.1002/cncr.23381.
    1. Janis IL, Mann L. Decision making: a psychological analysis of conflict, choice, and commitment. Free press; 1977.
    1. Janis IL, Mann L. A theoretical framework for decision counseling. Counseling on personal decisions: theory and research on short-term helping relationships. 1982;47–72.
    1. O’Connor AM, Tugwell P, Wells GA, Elmslie T, Jolly E, Hollingworth G, et al. A decision aid for women considering hormone therapy after menopause: decision support framework and evaluation. Patient Educ Couns 1998;33(3):267–279. PMID: 9731164; doi:10.1016/s0738-3991(98)00026-3.
    1. Brehaut JC, O’Connor AM, Wood TJ, Hack TF, Siminoff L, Gordon E, et al. Validation of a decision regret scale. Med Decis Making 2003;23(4):281–292. PMID: 12926578; doi:10.1177/0272989X03256005
    1. Zeelenberg M. The use of crying over spilled milk: a note on the rationality and functionality of regret. Philos Psychol. 1999;12(3):325–340. doi: 10.1080/095150899105800.
    1. Joseph-Williams N, Edwards A, Elwyn G. The importance and complexity of regret in the measurement of ‘good’ decisions: a systematic review and a content analysis of existing assessment instruments. Health Expect. 2011;14(1):59–83. doi: 10.1111/j.1369-7625.2010.00621.x.
    1. Stacey D, Légaré F, Lewis K, Barry MJ, Bennett CL, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2017;4(4). PMID: 28402085; PMCID: PMC6478132; doi:10.1002/14651858.CD001431.pub5.
    1. Bakitas M, Kryworuchko J, Matlock DD, Volandes AE. Palliative medicine and decision science: the critical need for a shared agenda to foster informed patient choice in serious illness. J Palliat Med. 2011;14(10):1109–1116. PMID: 21895453; PMCID: PMC3236099; doi:10.1089/jpm.2011.0032.
    1. Pickard AS, Hung SY, McKoy JM, Witt WP, Arseven A, Sharifi R, et al. Opportunities for disease state management in prostate cancer. Disease Management 2005;8(4):235–244. PMID: 16117718; doi:10.1089/dis.2005.8.235.
    1. Violette PD, Agoritsas T, Alexander P, Riikonen J, Santti H, Agarwal A, Bhatnagar N, Dahm P, Montori V, Guyatt GH, Tikkinen KAO. Decision aids for localized prostate cancer treatment choice: systematic review and meta-analysis. CA: Cancer J Clin. 2015;65(3):239–251. doi: 10.3322/caac.21272.
    1. Wicher CP, Meeker MA. What influences African American end-of-life preferences? J Health Care Poor Underserved. 2012;23(1):28–58. doi: 10.1353/hpu.2012.0027.
    1. Mack JW, Paulk ME, Viswanath K, Prigerson HG. Racial disparities in the outcomes of communication on medical care received near death. Arch Intern Med. 2010;170(17):1533–1540. PMID: 20876403; PMCID: PMC3739279; doi:10.1001/archinternmed.2010.322.
    1. Loggers ET, Maciejewski PK, Paulk E, DeSanto-Madeya S, Nilsson M, Viswanath K, et al. Racial differences in predictors of intensive end-of-life care in patients with advanced cancer. J Clin Oncol. 2009;27(33):5559. PMID: 19805675; PMCID: PMC2792953; doi:10.1200/JCO.2009.22.4733
    1. Freeman HP, Rodriguez RL. History and principles of patient navigation. Cancer. 2011;117(Suppl15):3537–3540. doi: 10.1016/j.soncn.2013.02.002.
    1. Pérez LM, Martinez J. Community health workers: social justice and policy advocates for community health and well-being. Am J Public Health. 2008;98(1):11–14. PMID: 18048789; PMCID: PMC2156047; doi:10.2105/AJPH.2006.100842.
    1. Earp JA, Eng E, O’Malley MS, Altpeter M, Rauscher G, Mayne L, et al. Increasing use of mammography among older, rural African American women: results from a community trial. Am J Public Health. 2002;92(4):646–654. PMID: 11919066; PMCID: PMC1447131; doi:10.2105/ajph.92.4.646.
    1. Eng E, Smith J. Natural helping functions of lay health advisors in breast cancer education. Breast Cancer Res Treatment. 1995;35(1):23–29. doi: 10.1007/BF00694741.
    1. Paré G, Sicotte C, Moreault MP, Poba-Nzaou P, Templier M, Nahas G. Effects of mobile computing on the quality of homecare nursing practice. In: 2011 44th Hawaii International Conference on System Sciences. IEEE; 2011;1–11. doi:10.1109/HICSS.2011.179.
    1. Kaiser Family Foundation. Mobile Technology: Smart Tools to Increase Participation in Health Coverage. 2011. . Accessed 27 Jan 2020.
    1. Ruland CM, Holte HH, Røislien J, Heaven C, Hamilton GA, Kristiansen J, et al. Effects of a computer-supported interactive tailored patient assessment tool on patient care, symptom distress, and patients' need for symptom management support: a randomized clinical trial. J Am Med Inform Assoc. 2010;17(4):403–410. PMID: 20595307; PMCID: PMC2995659; doi:10.1136/jamia.2010.005660.
    1. O'Leary DP, Zaheer A, Redmond HP, Corrigan MA. Integration of advances in social media and mHealth technology are pivotal to successful cancer prevention and control. mHealth. 2016;2. PMID: 28293611; PMCID: PMC5344161; doi:10.21037/mhealth.2016.09.02.
    1. Boceta J, Samper D, de la Torre A, Sánchez-de la Rosa R, González G. Usability, acceptability, and usefulness of an mHealth app for diagnosing and monitoring patients with breakthrough cancer pain. JMIR Cancer. 2019;5(1):e10187. PMID: 30932862; PMCID: PMC6462894; doi:10.2196/10187.
    1. Witmer A, Seifer SD, Finocchio L, Leslie J, O’Neil EH. Community health workers: integral members of the health care work force. Am J Public Health. 1995;85(8 Pt 1):1055–1058. PMID: 7625495; PMCID: PMC1615805; doi:10.2105/ajph.85.8_pt_1.1055.
    1. Giblin PT. Effective utilization and evaluation of indigenous health care workers. Public Health Rep. 1989;104(4):361. PMID: 2502807; PMCID: PMC1579943.
    1. Jones RA, Steeves R, Ropka ME, Hollen P. Capturing treatment decision making among patients with solid tumors and their caregivers. Oncol Nurs Forum. 2013;40(1):E24. PMID: 23269778; PMCID: PMC3634347; doi:10.1188/13.ONF.E24-E31.
    1. Hollen PJ, Gralla RJ, Jones RA, Thomas CY, Brenin DR, Weiss GR, et al. A theory-based decision aid for patients with cancer: results of feasibility and acceptability testing of DecisionKEYS for cancer. Support Care Cancer. 2013;21(3):889–899. PMID: 23052911; PMCID: PMC3625630; doi:10.1007/s00520-012-1603-8.
    1. University of Virginia: Cancer Control & Population Health. . Accessed: 27 Jan 2020.
    1. Virginia Commonwealth University: Cancer Disparities. . Accessed: 1 Apr 2020.
    1. Wang A, Wheeler DC. Catchment area analysis using Bayesian regression modeling. Cancer Inform 2015;14 Suppl 2:71–79 PMID: 25983542; PMCID: PMC4403915; doi:10.4137/CIN.S17297.
    1. Mor V, Laliberte L, Morris JN, Wiemann M. The Karnofsky performance status scale: an examination of its reliability and validity in a research setting. Cancer 1984;53(9):2002–2007. PMID: 6704925. 10.1002/1097-0142(19840501)53:9<2002::aid-cncr2820530933>;2-w.
    1. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401. doi: 10.1177/014662167700100306.
    1. Zarin DA, Tse T, Williams RJ, Califf RM, Ide NC. The ClinicalTrials. gov results database—update and key issues. N England J Med. 2011;364(9):852-860. PMID: 21366476; PMCID: PMC3066456; doi:10.1056/NEJMsa1012065
    1. Saldanha IJ, Dickersin K, Wang X, Li T. Outcomes in Cochrane systematic reviews addressing four common eye conditions: an evaluation of completeness and comparability. PloS One. 2014;9(10):e109400. PMID: 25329377; PMCID: PMC4199623; doi:10.1371/journal.pone.0109400
    1. Hulley SB, Cummings SR, Browner WS, Grady D, Hearst N, Newman TB. Designing clinical research. Philadelphia: Lippincott Williams & Wilkins; 2001.
    1. Denzin NK. The research act: a theoretical introduction to sociological methods. Routledge; 2017.
    1. Smedley BD, Stith AY, Nelson AR. Assessing potential sources of racial and ethnic disparities in care: the clinical encounter. In: Unequal treatment: confronting racial and ethnic disparities in health care. National Academies Press (US). 2003.
    1. Mack JW, Paulk ME, Viswanath K, Prigerson HG. Racial disparities in the outcomes of communication on medical care received near death. Arch Intern Med. 2010;170(17):1533-1540. PMID: 20876403; PMCID: PMC3739279; doi:10.1001/archinternmed.2010.322
    1. Song L, Hamilton JB, Moore AD. Patient-healthcare provider communication: perspectives of African American cancer patients. Health Psychol. 2012;31(5):539–547. doi: 10.1037/a0025334.
    1. Manfredi C, Kaiser K, Matthews AK, Johnson TP. Are racial differences in patient–physician cancer communication and information explained by background, predisposing, and enabling factors? J Health Commun. 2010;15(3):272-292. PMID: 20432108; PMCID: PMC2862581; doi:10.1080/10810731003686598

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