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BACKGROUND: Little research effort has been devoted to examining the role of patient enablement in alleviating health anxiety in primary care. In this study, we examined the role of patient enablement as a moderator in the relationship between health anxiety, psychological distress, and treatment seeking in traditional Chinese medicine (TCM). METHODS: The participants were 634 patients of a government-subsidized Chinese medicine outpatient clinic in Hong Kong. They were asked to complete a series of questionnaires on patient enablement, health anxiety, anxiety, depression, physical distress, annual clinic visits, and service satisfaction and provided various demographic details. Descriptive statistics, correlations, and general linear models were used to analyze the data. RESULTS: We found that patient enablement correlated positively with service satisfaction. Patient enablement also interacted significantly with health anxiety in affecting indices of psychological distress (depression, anxiety) and treatment seeking (annual visits). Among highly enabled patients, the positive association between health anxiety and indices of psychological distress was weakened, and they also showed more health anxiety–driven treatment seeking as measured by annual clinic visits. CONCLUSION: These findings suggest a moderating mechanism by which patient enablement weakens the relationship between health anxiety on psychological well-being and increases treatment-seeking behavior in TCM. Practitioners are encouraged to provide sufficient information to patients to foster self-care and disease self-management using complementary and alternative medicine (CAM).

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.