Evaluating the translation process of an internet-based self-help intervention for prevention of depression: A cost-effectiveness analysis

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Abstract

Background: Depression is common and treatable with cognitive behavior therapy (CBT), for example. However, access to this therapy is limited. Internet-based interventions have been found to be effective in reducing symptoms of depression. The International Society for Research on Internet Interventions has highlighted the importance of translating effective Internet programs into multiple languages to enable worldwide dissemination. Objective: The aim of the current study was to determine if it would be cost effective to translate an existing English-language Internet-based intervention for use in a non-English-speaking country. Methods: This paper reports an evaluation of a trial in which a research group in NOR translated two English-language Internet-based interventions into Norwegian (MoodGYM and BluePages) that had previously been shown to reduce symptoms of depression. The translation process and estimates of the cost-effectiveness of such a translation process is described. Estimated health effect was found by using quality-adjusted life years (QALY). Results: Conservative estimates indicate that for every 1000 persons treated, 16 QALYs are gained. The investment is returned 9 times and the cost-effectiveness ratio (CER) is 3432. The costs of the translation project totaled to approximately 27% of the estimated original English-language version development costs. Conclusions: The economic analysis shows that the cost-effectiveness of the translation project was substantial. Hopefully, these results will encourage others to do similar analyses and report cost-effectiveness data in their research reports. © Filippo Castiglione.

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Lintvedt, O. K., Griffiths, K. M., Eisemann, M., & Waterloo, K. (2013). Evaluating the translation process of an internet-based self-help intervention for prevention of depression: A cost-effectiveness analysis. Journal of Medical Internet Research, 15(1). https://doi.org/10.2196/jmir.2422

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