Abstract
Background and aim
High prevalence of anxiety symptoms has been reported globally in the university students. Cognitive behavioral therapy (CBT) is the recognized treatment for anxiety and is traditionally conducted face-to-face (f-CBT). The efficacy of internet-based CBT (i-CBT) for anxiety has been extensively studied, yet evidence on its cost-effectiveness is scarce. We aimed to evaluate the cost-effectiveness of guided low-intensity i-CBT for university students with mild anxiety symptoms from the societal perspective of Hong Kong.
Methods
A 5-year Markov model was designed to compare outcomes of guided i-CBT and f-CBT in a hypothetical cohort of university students with mild anxiety symptoms. Model inputs of cost and healthcare resources associated with anxiety were retrospectively collected from a cohort of university students with anxiety symptoms. Clinical and utility model inputs were retrieved from published literature. Model outcome measures were anxiety-related total cost (including direct medical and indirect costs) and quality-adjusted life-year (QALY). Sensitivity analyses were performed to examine the robustness of base-case results.
Results
In base-case analysis, i-CBT gained higher QALYs (2.9956 versus 2.9917) at lower total cost (US$6,101 versus US$6,246) than f-CBT. In one-way sensitivity analysis, the QALY gained by i-CBT was sensitive to the relative patient acceptance and adherence to CBT. In probabilistic sensitivity analysis, i-CBT was cost-effective in 90.9% of the time at the willingness-to-pay threshold of 138,210 per QALY (3× GDP per capita in Hong Kong). The probability of i-CBT to be cost-effective was 99.9% at a willingness-to-pay threshold of zero.
Conclusions
Guided i-CBT appears to be cost-saving and effective for management of university students with mild symptoms of anxiety from the societal perspective of Hong Kong. The cost-effectiveness of i-CBT is highly subject to the individual acceptance and adherence of CBT delivered by the internet platform.
Funder
Health and Medical Research Fund
Publisher
Public Library of Science (PLoS)
Cited by
10 articles.
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