Raymond Javan Chan1,2,3, Bruce Cooper4, Bogda Koczwara5, Alexandre Chan6, Chia Jie Tan7,8, Louisa Gordon9,10, Steven M Paul4, Laura B Dunn11, Yvette P Conley12, Kord M Kober4, Gary Abrams13, Jon D Levine13, Christine Miaskowski4. 1. Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Bedford Park, SA5042, Australia. raymond.chan@flinders.edu.au. 2. School of Nursing, Queensland University of Technology, Kelvin Grove, Australia. raymond.chan@flinders.edu.au. 3. Princess Alexandra Hospital, Metro South Hospital and Health Services, Woolloongabba, QLD, Australia. raymond.chan@flinders.edu.au. 4. School of Nursing, University of California, San Francisco, San Francisco, CA, USA. 5. Flinders Centre for Innovation in Cancer, Flinders Medical Centre, Flinders University, Bedford Park, Australia. 6. Department of Clinical Pharmacy Practice, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, CA, USA. 7. Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Singapore. 8. Department of Pharmacy, National Cancer Centre, Singapore, Singapore. 9. School of Nursing, Queensland University of Technology, Kelvin Grove, Australia. 10. QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. 11. School of Medicine, Stanford University, Stanford, CA, USA. 12. School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA. 13. School of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Abstract
PURPOSE: To evaluate for inter-individual differences in financial distress and identify demographic, clinical, and symptom characteristics associated with higher levels of financial distress. METHODS: Patients (n = 387) were enrolled prior to breast cancer surgery and followed for 12 months. Financial distress was measured using a 0 (no problem) to 10 (severe problem) numeric rating scale. Hierarchical linear modeling was used to evaluate for inter-individual differences in trajectories of financial distress and characteristics associated with financial distress at enrollment and over 12 months. RESULTS: Patients' mean age was 55.0 (± 11.7) years and the majority underwent breast conservation surgery (80.6%). Mean financial distress score prior to surgery was 3.3 (± 3.4; range 0 to 10). Unconditional model for financial distress demonstrated no significant changes over time (-0.006/month). Younger age, lower income, receipt of an axillary lymph node dissection and adjuvant chemotherapy, and lower attentional function were associated with higher preoperative levels of financial distress. CONCLUSION: Risk factors identified in this study can be used to inform clinicians regarding the need to initiate financial discussions and social work referrals for some patients. Additional clinical or system level interventions should be considered for vulnerable groups with these risk factors.
PURPOSE: To evaluate for inter-individual differences in financial distress and identify demographic, clinical, and symptom characteristics associated with higher levels of financial distress. METHODS: Patients (n = 387) were enrolled prior to breast cancer surgery and followed for 12 months. Financial distress was measured using a 0 (no problem) to 10 (severe problem) numeric rating scale. Hierarchical linear modeling was used to evaluate for inter-individual differences in trajectories of financial distress and characteristics associated with financial distress at enrollment and over 12 months. RESULTS: Patients' mean age was 55.0 (± 11.7) years and the majority underwent breast conservation surgery (80.6%). Mean financial distress score prior to surgery was 3.3 (± 3.4; range 0 to 10). Unconditional model for financial distress demonstrated no significant changes over time (-0.006/month). Younger age, lower income, receipt of an axillary lymph node dissection and adjuvant chemotherapy, and lower attentional function were associated with higher preoperative levels of financial distress. CONCLUSION: Risk factors identified in this study can be used to inform clinicians regarding the need to initiate financial discussions and social work referrals for some patients. Additional clinical or system level interventions should be considered for vulnerable groups with these risk factors.
Authors: Erin E Kent; Laura P Forsythe; K Robin Yabroff; Kathryn E Weaver; Janet S de Moor; Juan L Rodriguez; Julia H Rowland Journal: Cancer Date: 2013-07-31 Impact factor: 6.860
Authors: Birha McCann; Christine Miaskowski; Theresa Koetters; Christina Baggott; Claudia West; Jon D Levine; Charles Elboim; Gary Abrams; Deborah Hamolsky; Laura Dunn; Hope Rugo; Marylin Dodd; Steven M Paul; John Neuhaus; Bruce Cooper; Brian Schmidt; Dale Langford; Janine Cataldo; Bradley E Aouizerat Journal: J Pain Date: 2012-04-18 Impact factor: 5.820
Authors: K Robin Yabroff; William F Lawrence; Steven Clauser; William W Davis; Martin L Brown Journal: J Natl Cancer Inst Date: 2004-09-01 Impact factor: 13.506
Authors: Raymond Javan Chan; Bruce Cooper; Bogda Koczwara; Alexandre Chan; Chia Jie Tan; Steven M Paul; Laura B Dunn; Yvette P Conley; Kord M Kober; Jon D Levine; Christine Miaskowski Journal: Support Care Cancer Date: 2020-01-18 Impact factor: 3.603
Authors: Christine Miaskowski; Bruce Cooper; Steven M Paul; Claudia West; Dale Langford; Jon D Levine; Gary Abrams; Deborah Hamolsky; Laura Dunn; Marylin Dodd; John Neuhaus; Christina Baggott; Anand Dhruva; Brian Schmidt; Janine Cataldo; John Merriman; Bradley E Aouizerat Journal: J Pain Date: 2012-12 Impact factor: 5.820