Patient preferences for a guided self-help programme to prevent relapse in anxiety or depression: A discrete choice experiment

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Abstract

Background Anxiety and depressive disorders are increasingly being viewed as chronic conditions with fluctuating symptom levels. Relapse prevention programmes are needed to increase self-management and prevent relapse. Fine-tuning relapse prevention programmes to the needs of patients may increase uptake and effectiveness. Materials and methods A discrete choice experiment (DCE) was conducted amongst patients with a partially or fully remitted anxiety or depressive disorder. Patients were presented 20 choice tasks with two hypothetical treatment scenarios for relapse prevention, plus a “no treatment” option. Each treatment scenario was based on seven attributes of a hypothetical but realistic relapse prevention programme. Attributes considered professional contact frequency, treatment type, delivery mode, programme flexibility, a personal relapse prevention plan, time investment and effectiveness. Choice models were estimated to analyse the data. Results A total of 109 patients with a partially or fully remitted anxiety or depressive disorder completed the DCE. Attributes with the strongest impact on choice were high effectiveness, regular contact with a professional, low time investment and the inclusion of a personal prevention plan. A high heterogeneity in preferences was observed, related to both clinical and demographic characteristics: for example, a higher number of previous treatment episodes was related to a preference for a higher frequency of contact with a professional, while younger age was related to a stronger preference for high effectiveness. Conclusions This study using a DCE provides insights into preferences for a relapse prevention programme for anxiety and depressive disorders that can be used to guide the development of such a programme.
Original languageEnglish
Article numbere0219588
JournalPLOS ONE
Volume14
Issue number7
DOIs
Publication statusPublished - 2019

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