2.50
Hdl Handle:
http://hdl.handle.net/10755/164651
Category:
Abstract
Type:
Presentation
Title:
Unmet Needs in Symptomatic Patients With Advanced Cancer
Author(s):
Moraless, E.; Duque, L.; Davis, C.; Cogswell, J.; Chang, V.
Author Details:
E. Moraless, Dept. of Veteran Affairs, New Jersey Healthcare System, East Orange, New Jersey, USA; L. Duque; C. Davis; J. Cogswell; V. Chang
Abstract:
Identify the multidimensional unmet needs in symptomatic advanced cancer patients is important to oncology nurses. The unmet needs of veteran cancer patients is unknown. Purpose: We hypothesized that different predictors will be identified for different unmet needs domain and the total unmet needs would predict overall QOL independently. Theoretical/Scientific Framework: We adapted the multidimensional QOL framework to assess the prevalence and to identify independent predictors of multidimensional unmet needs and examined the association between unmet needs and quality of life (QOL) Methods: We used 14-item multidimensional unmet needs questionnaire and Functional Assessment of Cancer Therapy (FACT-G) to assess patients' unmet needs and QOL outcomes. The independent variables were categorized into six dimensions: individual characteristics, social support status, psychological status, physical symptoms, functional status, and health state. The validated instruments were used to measure each dimension. Methods: The multiple linear regression models were used to identify independent predictors of each unmet needs domain and of total unmet needs. The relationships between total unmet needs, QOL and multidimensional variables were also explored. Findings and Implications: There were 296 patients with median age of 68 years (range 29 - 96), median of 13(range 2-32) symptoms and 3 unmet needs (range 0-12). Physical (80.0%), activities of daily living (53.3%), nutrition (46.1%) and emotional (32.5%) were the most frequently reported unmet needs areas. There were five unmet needs domains and the different predictors of each domain were identified, which accounted for 7% to 36% of the variance. Psychological symptom distress was predictive in emotional/social, economic and medical domains. Physical symptom distress, extent of disease and health measure were only significant to the physical domain. For total unmet needs, the independent predictors included psychological symptom distress (p<0.0001), depression (p<0.0001), physical symptom distress (p=0.001), age (p=0.003), functional status (p=0.003), and extent of disease (R2 = 49%, p<0.00001). For FACT-G total QOL score, in addition to the known predictors such as depression (p<0.0001), psychological (p<0.0001) and physical symptom distress (p=0.03), confident (p=0.003) and affective social support (p=0.005), the total unmet needs (p=0.04) was also predictive (R2=63%, p<0.00001). The results from this study will assist nurses and administrators of health care system to identify the factors that are amenable for interventions in order to decrease patients' unmet needs, which may subsequently improve patients' QOL.
Repository Posting Date:
27-Oct-2011
Date of Publication:
27-Oct-2011
Conference Date:
2004
Conference Name:
29th Annual Oncology Nursing Society Congress
Conference Host:
Oncology Nursing Society
Conference Location:
Anaheim, California, USA

Full metadata record

DC FieldValue Language
dc.type.categoryAbstracten_US
dc.typePresentationen_GB
dc.titleUnmet Needs in Symptomatic Patients With Advanced Canceren_GB
dc.contributor.authorMoraless, E.en_US
dc.contributor.authorDuque, L.en_US
dc.contributor.authorDavis, C.en_US
dc.contributor.authorCogswell, J.en_US
dc.contributor.authorChang, V.en_US
dc.author.detailsE. Moraless, Dept. of Veteran Affairs, New Jersey Healthcare System, East Orange, New Jersey, USA; L. Duque; C. Davis; J. Cogswell; V. Changen_US
dc.identifier.urihttp://hdl.handle.net/10755/164651en
dc.description.abstractIdentify the multidimensional unmet needs in symptomatic advanced cancer patients is important to oncology nurses. The unmet needs of veteran cancer patients is unknown. Purpose: We hypothesized that different predictors will be identified for different unmet needs domain and the total unmet needs would predict overall QOL independently. Theoretical/Scientific Framework: We adapted the multidimensional QOL framework to assess the prevalence and to identify independent predictors of multidimensional unmet needs and examined the association between unmet needs and quality of life (QOL) Methods: We used 14-item multidimensional unmet needs questionnaire and Functional Assessment of Cancer Therapy (FACT-G) to assess patients' unmet needs and QOL outcomes. The independent variables were categorized into six dimensions: individual characteristics, social support status, psychological status, physical symptoms, functional status, and health state. The validated instruments were used to measure each dimension. Methods: The multiple linear regression models were used to identify independent predictors of each unmet needs domain and of total unmet needs. The relationships between total unmet needs, QOL and multidimensional variables were also explored. Findings and Implications: There were 296 patients with median age of 68 years (range 29 - 96), median of 13(range 2-32) symptoms and 3 unmet needs (range 0-12). Physical (80.0%), activities of daily living (53.3%), nutrition (46.1%) and emotional (32.5%) were the most frequently reported unmet needs areas. There were five unmet needs domains and the different predictors of each domain were identified, which accounted for 7% to 36% of the variance. Psychological symptom distress was predictive in emotional/social, economic and medical domains. Physical symptom distress, extent of disease and health measure were only significant to the physical domain. For total unmet needs, the independent predictors included psychological symptom distress (p<0.0001), depression (p<0.0001), physical symptom distress (p=0.001), age (p=0.003), functional status (p=0.003), and extent of disease (R2 = 49%, p<0.00001). For FACT-G total QOL score, in addition to the known predictors such as depression (p<0.0001), psychological (p<0.0001) and physical symptom distress (p=0.03), confident (p=0.003) and affective social support (p=0.005), the total unmet needs (p=0.04) was also predictive (R2=63%, p<0.00001). The results from this study will assist nurses and administrators of health care system to identify the factors that are amenable for interventions in order to decrease patients' unmet needs, which may subsequently improve patients' QOL.en_GB
dc.date.available2011-10-27T12:04:33Zen
dc.date.issued2011-10-27en_GB
dc.date.accessioned2011-10-27T12:04:33Zen
dc.conference.date2004en_US
dc.conference.name29th Annual Oncology Nursing Society Congressen_US
dc.conference.hostOncology Nursing Societyen_US
dc.conference.locationAnaheim, California, USAen_US
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