Background: Advanced breast cancer (ABC) is affecting substantial number of Chinese women in Hong Kong. Understanding their unmet supportive care needs (SCNs) is important for health care system to precisely allocate resources to areas demanded for help the most and for patients to achieve better quality of life.
Objectives: (1) To validate Chinese version of Supportive Care Needs Survey Questionnaire (SCNS-SF34), (2) to address the prevalence of unmet SCNs at baseline (newly diagnosis of ABC) and explore relevant factors associating with baseline unmet SCNs, (3) to identify the trajectories of unmet SCNs from baseline, 6-week, 12-week, 18-week to one-year post-diagnosis of ABC among Hong Kong Chinese women and identify the predictors related to individual resources.
Methods: The study consisted of two phases. In Phase I, breast cancer (BC) patients were recruited from six public hospitals and the SCNS-SF34 (which covers five domains of needs) was administered concurrently with measures of psychological distress CHQ-12 (Chinese Health Questionnaire-12), HADS (Hospital Anxiety and Depression Scale), symptom distress (MSAS-SF), and patient satisfaction (ChPSQ-9) to explore factor structure by using Exploratory Factor Analysis (EFA) and to examine internal consistency, and convergent, divergent and discriminant validities of the identified factor structure. In phase II, women newly diagnosed with ABC were recruited and followed up to assess their unmet SCN trajectories one year after diagnosis. Prevalence of initial baseline SCNs and associated demographic, medical and psychological factors were identified. Linear Mixed Modeling (LMM) was performed to assess trajectories for each SCNs domain. Hypothesized variables reflecting personal and social resources (optimism, trait hope, social support, psychological distress and patient satisfaction) were examined for association with the changes of unmet SCNs after adjusting for demographic and medical characteristics.
Results: Instead of five-factor structure identified in the original SCNS-SF34, a four-factor structure with 33 items was identified, comprising: 1) Health system, information and patient support needs (HSIPS), 2) Psychological needs (PSYC), 3) Physical and daily living needs (PDL) and 4) Sexuality needs (SEX). The SCNS-SF33-C demonstrated moderate-to-good internal consistency (Cronbach’s alphas=0.75-0.92) across all domains. Acceptable convergent and divergent validity were demonstrated. Discriminant validity was demonstrated in the SCNS-SF33-C’s ability to differentiate between clinically distinct patient groups (ABC vs. localized BC and active treatment vs. no active treatment). Of the top 15 unmet SCNs, all belonged to the HSIPS domain. There were significant linear declines in unmet HSIPS and PSYC needs over the year after diagnosis, but not in PDL and SEX. After adjusting for demographic and medical factors, LMM identified symptom distress, patient satisfaction and patient satisfaction x time are predictors of HSIP. Total symptom distress, optimism, anxiety and anxiety x time predicted PSYC. Total symptom distress was predictor of PDL. Anxiety was predictor of SEX.
Conclusions: The SCNS-SF33-C has a suitable factor structure and psychometric properties for the use in assessing unmet psychosocial SCN among Chinese women with BC. Generally, unmet HSIP and PSYC tended to decline, while levels of unmet PDL and SEX tended to persist over time. Specific individual resources predicted the future change of unmet SCNs. / published_or_final_version / Community Medicine / Master / Master of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/179990 |
| Date | January 2012 |
| Creators | Au, Ho-yee, Angel., 區可兒. |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B48521814 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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