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The Computerized Symptom Capture Tool (C-SCAT)
- 1. The Computerized Symptom Capture Tool (C-SCAT): A Novel Approach to Exploring Symptoms and Symptom Clusters In Adolescents and Young Adults with Cancer Lauri Linder, PhD, APRN, CPON Catherine Fiona Macpherson, PhD, RN, CPON University of Utah College of Nursing Seattle Children’s Hospital Primary Children’s Hospital University of Washington Kristin Stegenga, PhD, RN, CPON Suzanne Ameringer, PhD, RN Children’s Mercy Hospital Virginia Commonwealth University Jeanne Erickson, PhD, RN, AOCN Pamela Hinds, PhD, RN, FAAN University of Virginia Children’s National Medical Center Nancy Fugate Woods, PhD, RN, FAAN University of Washington
- 2. Speaker Disclosure Statement The authors have no financial relationships to disclose
- 3. Adolescents and Young Adults with Cancer Approximately 70,000 adolescents and young adults newly diagnosed each year (National Cancer Institute, 2012) 15 to 39 years of age (National Cancer Institute, 2012) Cancer types distinct from older and younger age groups Developmental characteristics Adolescents physically maturing, achieving independence from parents, and making significant decisions related to education and relationships Young adults achieving financial, residential, and emotional independence; assuming adult roles Both groups with access to electronic media and often prefer computers to paper for completing health surveys
- 4. Defining Symptom … “… a subjective experience reflecting changes in the biopsychosocial functioning, sensations, or cognition of an individual.” (Harver & Mahler, 1990) “The gold standard for the study of symptoms is based on the perception of the individual experiencing the symptom and his/her self-report.” (Dodd et al., 2001)
- 5. Symptoms in Adolescents and Young Adults with Cancer Adolescents and young adults receiving treatment for cancer report up to 12 concurrent symptoms (Baggott et al., 2010; Collins et al., 2000; Enskar & von Essen 2008; Hedstrom et al., 2006; Hedstrom et al., 2004; Yeh et al., 2009; Zhukovsky et al., 2009) Number of symptoms and associated symptom distress greatest while receiving treatment (Collins et al., 2000; Enskar & von Essen, 2007; Hinds et al., 2009) Severity of symptoms influences decision-making related to treatment (Docherty, Sandelowski, & Preisser, 2006; Woodgate, Degner, & Yanofsky, 2003)
- 6. What is a Symptom Cluster? Two or more symptoms that are related to each other and that occur together (Kim et al., 2005) Relationships between the symptoms are associative and not necessarily causal May share a common etiology or underlying mechanism (Barsevick, 2007) Hockenberry & Hooke, 2007
- 7. Why Study Symptom Clusters vs. Individual Symptoms? Identifying and understanding symptom clusters… Informs effective symptom management interventions (Kim et al., 2005; Miaskowski, Dodd, & Lee, 2004) May lead to prevention and relief of the complex and/or synergistic effects of multiple symptoms on patient outcomes (Kim et al., 2005; Miaskowski, Dodd, & Lee, 2004)
- 8. Symptom Clusters in Adolescents and Young Adults with Cancer Symptom cluster research is limited Adolescents frequently included in study samples with school-age children Young adults frequently included in study samples with older adults Research exploring whether and how AYAs cluster their symptoms or the meaning they attach to their symptoms and symptom clusters is limited
- 9. Approaches to Symptom Cluster Research Dominant approaches for studying symptom clusters include multivariate statistical methods to identify clusters from patient-reported symptoms (Baggott et al., 2012; Hockenberry et al., 2011; Miaskowski et al., 2006; Yeh et al., 2008) Symptom cluster heuristics is an alternate methodological approach that explores patients' interpretation and meaning of the symptom cluster experience
- 10. Aims Examine feasibility and acceptability of using the Computerized Symptom Capture Assessment Tool (C-SCAT) for exploring symptoms and symptom clusters in AYAs with cancer Describe the symptoms and symptom clusters from the perspectives of AYA with cancer
- 11. Participants 72 AYAs receiving myelosuppressive chemotherapy 40 adolescents (median 15 years; range 13-18) 32 young adults (median 21.5 years; range 19-29) Median of 3 months since diagnosis (range 1 – 156) 57% male; 79% White/Non- Hispanic ALL AML Hodgkin lymphoma Non- Hodgkin lymphoma Sarcoma Brain tumor Other solid tumor
- 12. Study Procedure Participants completed the C-SCAT app with a study team member present 24 to 96 hours after initiating a chemotherapy cycle Participants completed a questionnaire delivered via the iPad addressing the app’s acceptability Ethical considerations IRB approval granted from the five data collection sites Parental permission and participant assent obtained from participants 13 – 17 years Informed consent obtained from participants 18 years and older
- 13. Goals of the C-SCAT Integrate innovative and developmentally meaningful technology in a novel approach to study symptoms and symptom clusters in AYAs with cancer Elicit interpretive guidance from adolescents as to the meaning of their symptoms and symptom clusters by allowing the AYAs to identify: Symptoms, possible causes, alleviating/exacerbating factors, attempted self-management strategies, and effects of symptoms on daily activities Perceived causal and temporal relationships among symptoms Names for symptom clusters and key symptoms within clusters
- 14. Steps to C-SCAT Completion Drag and drop symptoms experienced in past 24 hours into designated area of screen Identify symptom cause, characteristics, attempted self-management, and effect on daily activities Draw lines and arrows to indicate relationships between symptoms Draw boxes around groups of related symptoms Identify priority symptom within each group
- 15. Results - Feasibility 100% fully completed C-SCAT within 24 – 96 hours of starting a new chemotherapy cycle Mean of 25 minutes to complete the app (SD=17; range 2 – 83) 70% indicated final image was accurate representation of their symptom experience 3 cases of technical difficulties with lost/missing data Participants completed app with minimal questions for clarification
- 16. Results - Acceptability 0 10 20 30 40 50 60 70 80 90 100 Acceptable amount of time to complete app Bored while completing the app App asked important questions Easy to type or draw in the app App instructions easy to follow App questions clear or very clear Percent of respondents in agreement
- 17. Results - Acceptability Increased self-awareness of symptom experience Appreciation for ability to create pictorial representation of symptoms Preference for using technology over paper and pencil instruments Familiarity with technology Novelty of the application Appreciation of speed and flexibility for editing responses Ease of using touchscreens rather than writing responses Suggestions for improvement Additional symptoms Focused questions More engaging color graphics
- 18. Results - Acceptability How did it feel to think about your symptoms while completing the app? “It made me understand my own symptoms a little better, actually” “It was fine. It certainly didn’t make my symptoms worse.” “It was kind of hard because I’ve had so many different symptoms that I can’t remember if they happened within the time period you asked about.” “Not good to [be] reminded [of] all [the] bad things.” “Painful” “Sucky”
- 19. Results - Acceptability 83% expressed a preference for the app vs a paper- and-pencil version “Doing it on paper would be boring and a lot more work to do. And most people my age are lazy and wouldn't want to do it.” “It's incredible technology, there's nothing exciting about paper” “No erasing, and the iPad had autocorrect, and also I’m used to typing on touchscreens.” “Because of my hands and neuropathy easier to do on iPad”
- 20. Results – Symptoms & Symptom Clusters Median of 8 symptoms (range 1-21) Most frequently reported individual symptoms Nausea, lack of appetite, lack of energy, feeling drowsy 65% of AYAs identified symptom clusters (median 2 clusters; range 1-4) Cluster name examples “chemo effects,” “not fun treatment,” “troublesum (sic),” “crap”
- 21. Future Directions Refinements to the C-SCAT app Additional symptoms, more engaging graphics, more focused questions Address technical difficulties Use the C-SCAT to facilitate a personalized approach to symptom management as a mobile health resource Enhance adolescent-healthcare provider communication Prioritize symptom management interventions
- 22. Conclusion C-SCAT shifts paradigm of symptom and symptom cluster assessment from deductive to inductive approach that considers how individuals interpret and give meaning to symptoms C-SCAT demonstrated: feasibility acceptability capacity to generate rich data reflecting the individual’s experience C-SCAT has potential for use in clinical care to foster patient- provider communication about complex symptom experiences to facilitate symptom management: for AYAs with cancer across other age and disease groups
- 23. Funding for adolescents at Primary Children’s Hospital, Seattle Children’s Hospital, and Children’s Mercy Hospital St. Baldrick’s Foundation Supportive Care Grant 2011-2013 (Linder, PI) Funding for young adults: Primary Children’s Hospital University of Utah College of Nursing Faculty Research Grant (Linder, PI); Seattle Children’s Hospital Seattle Children’s Guild Association Teen Cancer Grant (Macpherson, PI); Children’s Mercy Hospital Hyundai Hope on Wheels {(Stegenga), Fulbright, PI}, University of Virginia Health System University of Virginia School of Nursing (Erickson, PI); Virginia Commonwealth University Health System Grant # P30 NR011403 Center of Excellence for Biobehavioral Approaches to Symptom Management; NINR, NIH {(Ameringer), Grap, PI} C-SCAT Programming: Intermountain Healthcare Homer Warner Center for Informatics Research Acknowledgements