scholarly journals Understanding the engagement of key decision support persons in patient decision making around breast cancer treatment

Cancer ◽  
2019 ◽  
Vol 125 (10) ◽  
pp. 1709-1716 ◽  
Author(s):  
Christine M. Veenstra ◽  
Lauren P. Wallner ◽  
Paul H. Abrahamse ◽  
Nancy K. Janz ◽  
Steven J. Katz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Cancer Treatment ◽  
Breast Cancer Treatment ◽  
Patient Decision Making ◽  
Patient Decision

Impact of an Educational Video on Patient Decision Making in Early Breast Cancer Treatment

2006 ◽  
Vol 26 (6) ◽  
pp. 589-598 ◽  
Author(s):  
Edwin G. Wilkins ◽  
Julie C. Lowery ◽  
Laurel A. Copeland ◽  
Sherry L. Goldfarb ◽  
Patricia A. Wren ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Cancer Treatment ◽  
Early Breast Cancer ◽  
Breast Cancer Treatment ◽  
Educational Video ◽  
Patient Decision Making ◽  
Patient Decision

Variations in objective knowledge among decision-support persons of patients with early stage breast cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19110-e19110
Author(s):  
Victoria A Wytiaz ◽  
Christine M Veenstra ◽  
Sarah T. Hawley
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Cancer Treatment ◽  
Early Stage ◽  
Treatment Options ◽  
Breast Cancer Treatment ◽  
Objective Knowledge ◽  
Level Of Education ◽  
High Knowledge

e19110 Background: Patients with breast cancer face complex decisions regarding treatment options, and frequently involve family, friends, and other decision supporters in decision-making. A high-quality decision is one that is both informed and values-concordant. While much has been done to evaluate the quality of decision-making among patients, very little is known about how decision supporters fit within that framework. Thus, we sought to understand variations in objective knowledge among decision supporters. Methods: Patients with stage 0-II breast cancer reported to Georgia and LA SEER registries in 2014-15 and their key decision support person (DSP) were surveyed separately. DSPs were asked 4 objective knowledge questions regarding breast cancer treatment with responses dichotomized into high/low knowledge. Bivariate analyses and multivariable regression models were used to assess associations between DSP knowledge and important DSP characteristics (type of DSP, age, race, education), level of DSP engagement in 3 domains of patients’ decision-making (feeling informed about decisions, extent of and satisfaction with their involvement in decisions, and being aware of patients’ values/preferences), and patient clinical factors (stage, chemotherapy receipt, radiation receipt, type of surgery). Results: 2502 patients (68% RR) and 1203 eligible DSPs (70% RR) responded. Most DSPs were husbands or daughters. 21% were Latino, 17% were black, 20% had <high school education. Overall,53% DSPs had high objective knowledge. DSPs with high knowledge were more likely to be non-Black, non-Spanish-speaking Latinos, have a higher level of education, and report high engagement in the domains of satisfaction with their involvement in patients’ decision-making and awareness of patients’ values/preferences (all p < 0.05). After adjustment, high objective knowledge among DSPs was associated a higher level of education (OR = 2.44; 95% CI = 1.67-3.57) and high awareness of patients’ values/preferences (OR = 1.40; 95% CI = 1.06-1.84). Conclusions: Objective knowledge about breast cancer treatment was varied among DSPs of patients with breast cancer. Highly engaged DSPs (aware and satisfied) were more likely to have high knowledge, suggesting that involving DSPs may be an untapped mechanism for improving patients’ understanding of treatment options. These finding suggest that DSPs can play a role in improving decision quality in patients, and that interventions focused on decision-making may benefit from modules directed to DSPs as well as patients.

scholarly journals Decision support networks of women newly diagnosed with breast cancer.

2017 ◽  
Vol 35 (8_suppl) ◽  
pp. 157-157
Author(s):  
Lauren P. Wallner ◽  
Yun Li ◽  
Chandler McLeod ◽  
Ann S. Hamilton ◽  
Kevin C. Ward ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Cancer Treatment ◽  
Treatment Decision ◽  
Breast Cancer Treatment ◽  
Network Size ◽  
Support Networks ◽  
Newly Diagnosed ◽  
Treatment Decision Making

157 Background: Prior studies suggest that women often involve a network of family and friends in their cancer treatment decision making, yet very little is known about the size and characteristics of these decision support networks and whether their involvement leads to high-quality breast cancer treatment decisions. Methods: A weighted random sample of patients newly diagnosed with breast cancer in 2014-15 as reported to the Georgia and Los Angeles SEER registries were surveyed approximately 6 months after diagnosis (N = 2,502, 70% response rate). Network size was estimated by asking women to list up to 3 of the most important decision support people (DSP) who helped them make their locoregional therapy decisions. Decision deliberation was measured using 4-items assessing degree to which patients thought through the decision, with higher scores reflecting more deliberative breast cancer treatment decisions. We compared the size of the network (0-3+ people) across patient-level characteristics and estimated the adjusted mean deliberation scores across levels of network size using multivariable linear regression. Results: Of the 2,502 women included in this analysis, 51% reported having at least 3 DSPs, 20% reported 2, 18% reported 1, and 10% reported not having any DSPs. Among women who were not partnered (N = 961), 51% had 3 DSPs, 18% had 2, 16% had 1 and 16% had 0 DSPs. Of the DSPs that the respondents identified, the majority were children (30%), followed by partners/spouses (23%), friends (15%), siblings (10%), other family members (6%), and parents (5%). Married/partnered women (p < 0.001), those younger than 45 years old (p < 0.001), those with more than 1 comorbidity (p < 0.001), and black women (p = 0.02) were all more likely to report larger networks on average. Larger support networks were associated with more deliberative surgical decisions (p < 0.001). Conclusions: In this population-based sample, the majority of women engaged DSPs in their treatment decision making and for non-partnered patients, DSPs still played a key role in decision making. Larger size decision support networks were associated with higher quality decisions, underscoring the importance of efforts to identify and engage DSPs in the breast cancer decision making process.

Size and influence of the decision support networks of women newly diagnosed with breast cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18012-e18012
Author(s):  
Lauren P. Wallner ◽  
Yun Li ◽  
Chandler McLeod ◽  
Ann S Hamilton ◽  
Kevin C. Ward ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Breast Cancer Treatment ◽  
Network Size ◽  
Support Networks ◽  
Newly Diagnosed ◽  
Treatment Decision Making

e18012 Background: Little is known about the size and characteristics of informal decision support networks of women diagnosed with breast cancer and whether involvement of informal decision supporters (DSP) influences breast cancer treatment decisions. Methods: A population-based sample of newly diagnosed breast cancer patients reported to the Georgia and Los Angeles SEER registries in 2014-15 were surveyed approximately 6 months after diagnosis (N = 2,502, 68% response rate). Network size was estimated by asking women to list up to 3 of the most important DSPs who helped them with locoregional therapy decisions. For each individual DSP listed, respondents reported how important each DSP’s opinion was in treatment decision making, and how satisfied they were with their involvement (5 pt. scales, “not at all” to “very”). Decision deliberation was measured using 5-items assessing degree patients thought through the decision, with higher scores reflecting more deliberative treatment decisions. We compared network size (0-3 or more) across patient-level characteristics and estimated the association between network size and deliberation using multivariable linear regression. Results: Of the 2,502 women in this analysis, 51% reported having 3 or more DSPs, 20% reported 2, 18% reported 1, and 11% reported not having any DSPs. Married/partnered women, those younger than 45 years old, and black women were all more likely to report larger networks (all p < 0.001). Partnered women most often reported their partner as their main DSP (37.9%), whereas not partnered/unmarried women most often reported children (38.4%). The majority of women were highly satisfied with their DSP being involved in their decisions (76.5%) and 68.6% felt their DSP was very important in their decision making. Larger support networks were associated with more deliberative surgical treatment decision-making (p < 0.001). Conclusions: Most women engaged multiple DSPs in their treatment decision making, including spouses, children, and friends. Involving more DSPs was associated with more deliberative treatment decisions. Future initiatives to improve breast cancer treatment decision making should acknowledge and engage informal DSPs.

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