Kevin Criswell, Ph.D.
Introduction: Lung cancer is commonly associated with high levels of psychosocial distress and symptom burden. Healthcare professionals endeavor to meet complex needs, yet current research is sparse and presents an inconsistent picture of predictors of healthcare satisfaction in lung cancer. We examined psychosocial, physical functioning, demographic, and supportive care factors as predictors of healthcare satisfaction in a sample of lung cancer survivors.
Method: We conducted a cross-sectional secondary data analysis to examine psychosocial functioning, physical functioning, supportive care needs, healthcare satisfaction, and demographic and medical characteristics in lung cancer survivors sampled from two southern California hospitals (N = 187). Mean difference tests and Pearson correlations were utilized prior to entering significant predictors into a hierarchical regression model predicting healthcare satisfaction.
Results: A hierarchical regression model indicated that greater information needs (beta = -.43, p < .001), greater psychological needs (beta = -.18, p < .04), and more time since diagnosis of lung cancer (beta = -.13, p < .05) independently predicted a lower levels of healthcare satisfaction.
Conclusions: Clinicians working with lung cancer survivors are encouraged to assess for unmet supportive care needs at regular intervals. It is unclear whether demographic characteristics that were predictive of healthcare satisfaction in other studies (e.g., ethnic background) were not found in our study due to characteristics of the healthcare settings for our sample or possibly the cross-sectional nature of our study. Future research may expand on our findings by examining predictors of healthcare satisfaction in longitudinal studies.
Greene, Gladys; Zuniga, Marissa; and Criswell, Kevin R., "Healthcare satisfaction in lung cancer survivors: A cross-sectional secondary data analytic study" (2020). 2020 Symposium Posters. 48.
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