Development and Usability Testing of a Computer-Tailored Decision Support Tool for Lung Cancer Screening: Study Protocol

Lisa Carter-Harris, Robert Skipworth Comer, Anurag Goyal, Emilee Christine Vode, Nasser Hanna, DuyKhanh Ceppa, Susan M Rawl, Lisa Carter-Harris, Robert Skipworth Comer, Anurag Goyal, Emilee Christine Vode, Nasser Hanna, DuyKhanh Ceppa, Susan M Rawl

Abstract

Background: Awareness of lung cancer screening remains low in the screening-eligible population, and when patients visit their clinician never having heard of lung cancer screening, engaging in shared decision making to arrive at an informed decision can be a challenge. Therefore, methods to effectively support both patients and clinicians to engage in these important discussions are essential. To facilitate shared decision making about lung cancer screening, effective methods to prepare patients to have these important discussions with their clinician are needed.

Objective: Our objective is to develop a computer-tailored decision support tool that meets the certification criteria of the International Patient Decision Aid Standards instrument version 4.0 that will support shared decision making in lung cancer screening decisions.

Methods: Using a 3-phase process, we will develop and test a prototype of a computer-tailored decision support tool in a sample of lung cancer screening-eligible individuals. In phase I, we assembled a community advisory board comprising 10 screening-eligible individuals to develop the prototype. In phase II, we recruited a sample of 13 screening-eligible individuals to test the prototype for usability, acceptability, and satisfaction. In phase III, we are conducting a pilot randomized controlled trial (RCT) with 60 screening-eligible participants who have never been screened for lung cancer. Outcomes tested include lung cancer and screening knowledge, lung cancer screening health beliefs (perceived risk, perceived benefits, perceived barriers, and self-efficacy), perception of being prepared to engage in a patient-clinician discussion about lung cancer screening, occurrence of a patient-clinician discussion about lung cancer screening, and stage of adoption for lung cancer screening.

Results: Phases I and II are complete. Phase III is underway. As of July 15, 2017, 60 participants have been enrolled into the study, and have completed the baseline survey, intervention, and first follow-up survey. We expect to have results by December 31, 2017 and to have data analysis completed by March 1, 2018.

Conclusions: Results from usability testing indicate that the computer-tailored decision support tool is easy to use, is helpful, and provides a satisfactory experience for the user. At the conclusion of phase III (pilot RCT), we will have preliminary effect sizes to inform a future fully powered RCT on changes in (1) knowledge about lung cancer and screening, (2) perceived risk of lung cancer, (3) perceived benefits of lung cancer screening, (4) perceived barriers to lung cancer screening, (5) self-efficacy for lung cancer screening, and (6) perceptions of being adequately prepared to engage in a discussion with their clinician about lung cancer screening.

Keywords: decision making, computer-assisted; decision support techniques; early detection of cancer; informed decision making; lung cancer screening; lung neoplasms; patient decision aid; patient education; shared decision making.

Conflict of interest statement

Conflicts of Interest: None declared.

©Lisa Carter-Harris, Robert Skipworth Comer, Anurag Goyal, Emilee Christine Vode, Nasser Hanna, DuyKhanh Ceppa, Susan M Rawl. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 16.11.2017.

References

    1. Moyer VA, U.S. Preventive Services Task Force Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2014 Mar 4;160(5):330–8. doi: 10.7326/M13-2771.
    1. National Lung Screening Trial Research Team. Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395–409. doi: 10.1056/NEJMoa1102873.
    1. Centers for Medicare & Medicaid Services Decision memo for screening for lung cancer with low-dose computed tomography (LDCT) 2017. [2017-08-09]. .
    1. Carter-Harris L, Ceppa DP, Hanna N, Rawl SM. Lung cancer screening: what do long-term smokers know and believe? Health Expect. 2017 Feb;20(1):59–68. doi: 10.1111/hex.12433.
    1. Stacey D, Légaré F, Lewis K, Barry MJ, Bennett CL, Eden KB, Holmes-Rovner M, Llewellyn-Thomas H, Lyddiatt A, Thomson R, Trevena L. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2017 Dec 12;4:CD001431. doi: 10.1002/14651858.CD001431.pub5.
    1. Carter-Harris L, Tan ASL, Salloum RG, Young-Wolff KC. Patient-provider discussions about lung cancer screening pre- and post-guidelines: Health Information National Trends Survey (HINTS) Patient Educ Couns. 2016 Nov;99(11):1772–1777. doi: 10.1016/j.pec.2016.05.014.
    1. Carter-Harris L, Brandzel S, Wernli KJ, Roth JA, Buist DSM. A qualitative study exploring why individuals opt out of lung cancer screening. Fam Pract. 2017 Dec 01;34(2):239–244. doi: 10.1093/fampra/cmw146.
    1. Volk RJ, Linder SK, Leal VB, Rabius V, Cinciripini PM, Kamath GR, Munden RF, Bevers TB. Feasibility of a patient decision aid about lung cancer screening with low-dose computed tomography. Prev Med. 2014 May;62:60–3. doi: 10.1016/j.ypmed.2014.02.006.
    1. Lau YK, Caverly TJ, Cherng ST, Cao P, West M, Arenberg D, Meza R. Development and validation of a personalized, web-based decision aid for lung cancer screening using mixed methods: a study protocol. JMIR Res Protoc. 2014 Dec 19;3(4):e78. doi: 10.2196/resprot.4039.
    1. Memorial Sloan Kettering Cancer Center Lung cancer screening decision tool. [2017-08-09]. .
    1. Veterans Health Administration . Screening for lung cancer pamphlet. Washington, DC: [2017-08-09]. .
    1. Krebs P, Prochaska JO, Rossi JS. A meta-analysis of computer-tailored interventions for health behavior change. Prev Med. 2010;51(3-4):214–21. doi: 10.1016/j.ypmed.2010.06.004.
    1. Albada A, Ausems MGEM, Bensing JM, van Dulmen S. Tailored information about cancer risk and screening: a systematic review. Patient Educ Couns. 2009 Nov;77(2):155–71. doi: 10.1016/j.pec.2009.03.005.
    1. Noar SM, Benac CN, Harris MS. Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychol Bull. 2007 Jul;133(4):673–93. doi: 10.1037/0033-2909.133.4.673.
    1. Velicer WF, Prochaska JO, Redding CA. Tailored communications for smoking cessation: past successes and future directions. Drug Alcohol Rev. 2006 Jan;25(1):49–57. doi: 10.1080/09595230500459511.
    1. Revere D, Dunbar Pj. Review of computer-generated outpatient health behavior interventions: clinical encounters 'in absentia'. J Am Med Inform Assoc. 2001;8(1):62–79.
    1. Kreuter M, Farrell D, Brennan L, Olevitch L. Tailoring Health Messages: Customizing Communication With Computer Technology. Mahwah, NJ: Lawrence Erlbaum Associates; 2000.
    1. Carter-Harris L, Slaven JE, Monahan P, Rawl SM. Development and psychometric evaluation of the lung cancer screening health beliefs scales. Cancer Nurs. 2017;40(3):237–244. doi: 10.1097/NCC.0000000000000386.
    1. Chapple A, Ziebland S, McPherson A. Stigma, shame, and blame experienced by patients with lung cancer: qualitative study. BMJ. 2004 Jun 19;328(7454):1470. doi: 10.1136/bmj.38111.639734.7C.
    1. Joseph-Williams N, Newcombe R, Politi M, Durand M, Sivell S, Stacey D, O'Connor A, Volk RJ, Edwards A, Bennett C, Pignone M, Thomson R, Elwyn G. Toward minimum standards for certifying patient decision aids: a modified Delphi consensus process. Med Decis Making. 2014 Aug;34(6):699–710. doi: 10.1177/0272989X13501721.
    1. Carter-Harris L, Davis LL, Rawl SM. Lung cancer screening participation: a conceptual model to guide research. Res Theory Nurs Pract. 2016 Nov 01;30(4):333–352. doi: 10.1891/1541-6577.30.4.333.
    1. Triacca L, Bolchini D, Botturi L. MiLE: systematic usability evaluation for e-learning web applications. AACE J. 2004;12(4):1–8.
    1. Bangor A, Kortum PT, Miller JT. An empirical evaluation of the System Usability Scale. Int J Hum Comput Interact. 2008 Jul 30;24(6):574–594. doi: 10.1080/10447310802205776.
    1. Brooke J. SUS: a quick and dirty usability scale. In: Jordan PW, Thomas B, McClelland IL, Weerdmeester B, editors. Usability Evaluation in Industry. London, UK: Taylor & Francis; 1996. pp. 189–194.
    1. Hertzog MA. Considerations in determining sample size for pilot studies. Res Nurs Health. 2008 Apr;31(2):180–91. doi: 10.1002/nur.20247.
    1. Feeley N, Cossette S, Côté J, Héon M, Stremler R, Martorella G, Purden M. The importance of piloting an RCT intervention. Can J Nurs Res. 2009 Jun;41(2):85–99.
    1. Moore CG, Carter RE, Nietert PJ, Stewart PW. Recommendations for planning pilot studies in clinical and translational research. Clin Transl Sci. 2011 Oct;4(5):332–7. doi: 10.1111/j.1752-8062.2011.00347.x.
    1. Simon S. Who should be screened for lung cancer? American Cancer Society; [2017-08-09]. .
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377–81. doi: 10.1016/j.jbi.2008.08.010.
    1. Weinstein N, Sandman P, Blalock S. The precaution adoption process model. In: Glanz K, Rimer BK, Viswanath K, editors. Health Behavior and Health Education: Theory, Research, and Practice. 4th edition. San Francisco, CA: Jossey-Bass; 2008.
    1. Enders C. Applied Missing Data Analysis. New York, NY: Guilford Press; 2010.

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