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Designing a reliable pain drawing tool: avoiding interaction flaws by better tailoring to patients’ impairments

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Abstract

Patients with advanced cancer are influenced by the disease itself and by treatment side effects, both of which may have great impact on their lives. One of the most distressing symptoms is pain. However, pain in cancer patients can in most cases be relieved if the patient is able to communicate the nature and severity of the problem to the healthcare professionals through an effective assessment process. The main goal of this paper is to help form an understanding of central patient characteristics that should be taken into account when designing pain assessment tools for patients with advanced cancer. Traditionally, pain has been assessed by paper-based questionnaires and pain drawings. An iterative study was conducted based on repeated cycles of usability testing of a computerized pain body map for communicating pain by advanced cancer patients. Our aim was to provide a patient interface that most patients were able to interact with, collecting valuable, granular pain information with a minimum of strain on the patient. Through this process, we identified and solved design issues related to the sickest and frailest cancer patients. We further created a web-based solution for collecting individual pain drawings for evaluation by clinicians. The concept was appreciated by the patients, and the information provided was considered valuable by physicians. The main contribution of this paper is a list of suggestions to guide the design of an interactive tool for patients with advanced cancer.

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References

  1. Alsos OA, Das A, Svanæs D (2012) Mobile health it: the effect of user interface and form factor on doctor–patient communication. Int J Med Inf 81(1):12–28

    Article  Google Scholar 

  2. Andreassen HK, Kjekshus LE, Tjora A (2015) Survival of the project: a case study of ICT innovation in health care. Soc Sci Med 132(0):62–69. doi:10.1016/j.socscimed.2015.03.016, http://www.sciencedirect.com/science/article/pii/S0277953615001525

  3. Astell A, Alm N, Gowans G, Ellis M, Dye R, Vaughan P (2009) Involving older people with dementia and their carers in designing computer based support systems: some methodological considerations. Univers Access Inf Soc 8(1):49–58. doi:10.1007/s10209-008-0129-9

    Article  Google Scholar 

  4. Bennett M (2001) The LANSS Pain Scale: the Leeds assessment of neuropathic symptoms and signs. Pain. 92(12):147–157. doi:10.1016/S0304-3959(00)00482-6, http://www.sciencedirect.com/science/article/pii/S0304395900004826

  5. Bromley J, Emerson E, Caine A (1998) The development of a self-report measure to assess the location and intensity of pain in people with intellectual disabilities. J Intellect Disabil Res 42:72–80

    Article  Google Scholar 

  6. Caraceni A, Galbiati A, Brunelli C, Gorni G, Martini C, Zecca E, Conno FD (2004) Cancer patient compliance in the self-administration of a pain assessment tool. J Pain Symptom Manage 27(5):417–424. doi:10.1016/j.jpainsymman.2004.01.002, http://www.sciencedirect.com/science/article/pii/S0885392404000685

  7. Cleeland CS, Ryan KM (1994) Pain assessment: global use of the brief pain inventory. Ann Acad Med Singapore 23(2):129–138

    Google Scholar 

  8. Dahl Y, Svanæs D, Nytrø Ø (2006) Designing pervasive computing for hospitals: learning from the media affordances of paper-based medication charts. In: Pervasive health conference and workshops, pp 1–10

  9. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340. doi:10.2307/249008

    Article  Google Scholar 

  10. de la Vega R, Miro J (2014) mHealth: a strategic field without a solid scientific soul. A systematic review of pain-related apps. PLOS One 9(7):e101,312

    Article  Google Scholar 

  11. Folstein MF, Folstein SE, McHugh PR (1975) Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12(3):189–198

    Article  Google Scholar 

  12. Freynhagen R, Baron R, Gockel U, Tölle TR (2006) Pain DETECT: a new screening questionnaire to identify neuropathic components in patients with back pain. Curr Med Res Opin 22(10):1911–1920

    Article  Google Scholar 

  13. Fyllingen EH, Oldervoll LM, Loge JH, Hjermstad MJ, Haugen DF, Sigurdardottir KR, Paulsen Ø, Kaasa S (2009) Computer-based assessment of symptoms and mobility in palliative care: feasibility and challenges. J Pain Symptom Manage 38(6):827–836. doi:10.1016/j.jpainsymman.2009.05.015, http://www.sciencedirect.com/science/article/pii/S0885392409007465

  14. Haque M, Kawsar F, Adibuzzaman M, Uddin M, Ahamed S, Love R, Hasan R, Dowla R, Ferdousy T, Salim R (2014) e-ESAS: evolution of a participatory design-based solution for breast cancer (BC) patients in rural Bangladesh. Pers Ubiquitous Comput 1–19. doi:10.1007/s00779-014-0828-6

  15. Hjermstad MJ, Fayers PM, Haugen DF, Caraceni A, Hanks GW, Loge JH, Fainsinger R, Aass N, Kaasa S (2011) Studies comparing Numerical Rating Scales, Verbal Rating Scales, and Visual Analogue Scales for assessment of pain intensity in adults: a systematic literature review. J Pain Symptom Manage 41(6):1073–1093

    Article  Google Scholar 

  16. Hjermstad MJ, Lie HC, Caraceni A, Currow DC, Fainsinger RL, Gundersen OE, Haugen DF, Heitzer E, Radbruch L, Stone PC, Strasser F, Kaasa S, Loge JH (2012) Computer-based symptom assessment is feasible in patients with advanced cancer: results from an international multicenter study, the EPCRC-CSA. J Pain Symptom Manage 44:639–654

    Article  Google Scholar 

  17. Hølen JC, Hjermstad MJ, Loge JH, Fayers PM, Caraceni A, De Conno F, Forbes K, Fürst CJ, Radbruch L, Kaasa S (2006) Pain assessment tools: Is the content appropriate for use in palliative care? J Pain Symptom Manage 32(6):567–580. doi:10.1016/j.jpainsymman.2006.05.025, http://www.jpsmjournal.com/article/S0885-3924(06)00544-6/abstract

  18. Hummel JE (2001) Complementary solutions to the binding problem in vision: implications for shape perception and object recognition. Vis Cogn 8(3–5):489–517. doi:10.1080/13506280143000214

    Article  Google Scholar 

  19. Jaatun EA, Haugen DF, Dahl Y, Kofod-Petersen A (2013) Proceed with caution: transition from paper to computerized pain body maps. Proc Comput Sci 21(0):398–406. The 4th international conference on emerging ubiquitous systems and pervasive networks (EUSPN-2013) and the 3rd international conference on current and future trends of information and communication technologies in healthcare (ICTH). doi:10.1016/j.procs.2013.09.052, http://www.sciencedirect.com/science/article/pii/S1877050913008454

  20. Jaatun EAA, Haugen DF, Dahl Y, Kofod-Petersen A (2013) An improved digital pain body map. In: 2013 IEEE 15th international conference on e-Health networking, applications services (Healthcom), pp 697–701. doi:10.1109/HealthCom.6720765

  21. Jaatun EAA, Hjermstad MJ, Gundersen OE, Oldervoll L, Kaasa S, Haugen DF (2014) Development and testing of a computerized pain body map in patients with advanced cancer. J Pain Symptom Manage 47(1):45–56. doi:10.1016/j.jpainsymman.2013.02.025

    Article  Google Scholar 

  22. Jang A, MacLean DL, Heer J (2014) Bodydiagrams: improving communication of pain symptoms through drawing. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI ’14. ACM, New York, NY, USA, pp 1153–1162. doi:10.1145/2556288.2557223

  23. Jordhøy MS, Kaasa S, Fayers P, Ovreness T, Underland G, Ahlner-Elmqvist M (1999) Challenges in palliative care research; recruitment, attrition and compliance: experience from a randomized controlled trial. Palliat Med 13(4):299–310

    Article  Google Scholar 

  24. Kaasa S, Torvik K, Cherny N, Hanks G, de Conno F (2007) Patient demographics and centre description in European palliative care units. Palliat Med 21(1):15–22

    Article  Google Scholar 

  25. Karnofsky DA, Abelmann WH, Craver LF, Burchenal JH (1948) The use of the nitrogen mustards in the palliative treatment of carcinoma with particular reference to bronchogenic carcinoma. Cancer 1(4):634–656. doi:10.1002/1097-0142(194811)1:4<634:AID-CNCR2820010410>3.0.CO;2-L

    Article  Google Scholar 

  26. Kearney N, McCann L, Norrie J, Taylor L, Gray P, McGee-Lennon M, Sage M, Miller M, Maguire R (2009) Evaluation of a mobile phone-based, advanced symptom management system (ASyMS) in the management of chemotherapy-related toxicity. Suppor Care Cancer 17(4):437–444. doi:10.1007/s00520-008-0515-0

    Article  Google Scholar 

  27. Keele KD (1948) The pain chart. Lancet 2(6514):6–8

    Article  Google Scholar 

  28. Kurita GP, de Mattos Pimenta CA, Braga PE, Frich L, Jørgensen MM, Nielsen PR, Højsted J, Sjøgren P (2012) Cognitive function in patients with chronic pain treated with opioids: characteristics and associated factors. Acta Anaesthesiol Scand 56:1257–1266

    Article  Google Scholar 

  29. Kushniruk AW, Patel VL (2004) Cognitive and usability engineering methods for the evaluation of clinical information systems. J Biomed Inf 37(1):56–76. doi:10.1016/j.jbi.2004.01.003, http://www.sciencedirect.com/science/article/pii/S1532046404000206

  30. Marceglia S, Bonacina S, Zaccaria V, Pagliari C, Pinciroli F (2012) How might the iPad change healthcare? J R Soc Med 105(6):233–241

    Article  Google Scholar 

  31. Margolis RB, Chibnall JT, Tait RC (1988) Test–retest reliability of the pain drawing instrument. Pain 33(1):49–51

    Article  Google Scholar 

  32. Melzack R (1975) The McGill Pain Questionnaire: major properties and scoring methods. Pain 1(3):277–299

    Article  Google Scholar 

  33. Melzack R, Torgerson WS (1971) On the language of pain. Anesthesiology 34(1):50–59

    Article  Google Scholar 

  34. Mirkovic J, Kaufman DR, Ruland CM (2014) Supporting cancer patients in illness management: usability evaluation of a mobile app. JMIR mHealth uHealth 2(3):e33. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147703

  35. Nilsen CM, Overgaard M, Pedersen MB, Stage J, Stenild S (2006) It’s worth the hassle! The added value of evaluating the usability of mobile systems in the field. In: Proceedings of the 4th Nordic conference on human–computer interaction: changing roles, pp 272–280. ACM

  36. Radbruch L, Sabatowski R, Loick G, Jonen-Thielemann I, Kasper M, Gondek B, Lehmann KA (2000) Cognitive impairment and its influence on pain and symptom assessment in a palliative care unit: development of a minimal documentation system. Palliat Med 14:266–276

    Article  Google Scholar 

  37. Rogers Y, Sharp H, Preece J (2011) Interaction design: beyond human–computer interaction, 3rd edn. Wiley, London

    Google Scholar 

  38. Sabes-Figuera R, Maghiros I (2013) European hospital survey: benchmarking deployment of e-Health services (2012–2013)—synthesis of outcomes. http://ipts.jrc.ec.europa.eu/publications/pub.cfm?id=6813

  39. Salthouse TA (2011) What cognitive abilities are involved in trail-making performance? Intelligence 39:222–232

    Article  Google Scholar 

  40. Sun VC, Borneman T, Ferrell B, Piper B, Koczywas M, Choi K (2007) Overcoming barriers to cancer pain management: an institutional change model. J Pain Symptom Manage 34(4):359–369

    Article  Google Scholar 

  41. Svanæs D, Alsos OA, Dahl Y (2008) Usability testing of mobile ICT for clinical settings: methodological and practical challenges. Int J Med Inf 79(4):24–34

    Article  Google Scholar 

  42. TechSmith—Camtasia, Screen Recorder and Video Editor (2015). http://www.techsmith.com/camtasia.html

  43. Teunissen SC, Wesker W, Kruitwagen C, de Haes HC, Voest EE, de Graeff A (2007) Symptom prevalence in patients with incurable cancer: a systematic review. J Pain Symptom Manage 34:94–104

    Article  Google Scholar 

  44. Van Someren MW, Barnard YF, Sandberg JAC (1994) The think aloud method: a practical guide to modelling cognitive processes. Academic Press, San Diego

    Google Scholar 

  45. Weiner D, Peterson B, Keefe F (1998) Evaluating persistent pain in long term care residents: what role for pain maps? Pain 76(1–2):249–257

    Article  Google Scholar 

  46. WHO: Cancer (2015) Factsheet No 297. http://www.who.int/mediacentre/factsheets/fs297/en/

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Acknowledgments

Thanks to Telltale Solutions LLC for diligence, professionalism and flexibility in developing the iPad-based Pain Body Map. Also thanks to Vivit AS for help with usability testing. Thanks to all patients and medical personnel who participated in the various aspects of the study. We also thank M.G. Jaatun for invaluable technical support through the study and writing process. The funding of this project was provided by the Liaison Committee between the Central Norway Regional Health Authority (RHA) and the Norwegian University of Science and Technology (NTNU) (Samarbeidsorganet).

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Authors and Affiliations

  1. European Palliative Care Research Centre, Norwegian University of Science and Technology, Trondheim, Norway

    Ellen Anna Andreassen Jaatun & Dagny Faksvåg Haugen

  2. Department of Otorhinolaryngology, Head and Neck Surgery, St. Olavs Hospital, Trondheim, Norway

    Ellen Anna Andreassen Jaatun

  3. Regional Centre of Excellence for Palliative Care, Western Norway, Haukeland University Hospital, Bergen, Norway

    Dagny Faksvåg Haugen

  4. Department of Clinical Medicine K1, University of Bergen, Bergen, Norway

    Dagny Faksvåg Haugen

  5. SINTEF ICT, Trondheim, Norway

    Yngve Dahl

  6. Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway

    Yngve Dahl & Anders Kofod-Petersen

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  1. Ellen Anna Andreassen Jaatun
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Correspondence to Ellen Anna Andreassen Jaatun.

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Jaatun, E.A.A., Haugen, D.F., Dahl, Y. et al. Designing a reliable pain drawing tool: avoiding interaction flaws by better tailoring to patients’ impairments. Pers Ubiquit Comput 19, 635–648 (2015). https://doi.org/10.1007/s00779-015-0850-3

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  • DOI: https://doi.org/10.1007/s00779-015-0850-3

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