Anna-Carlotta Zarski*, Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg, Lueneburg, Germany Dirk Lehr*, Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg, Lueneburg, Germany Matthias Berking*, Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg; Philipps University Marburg, Department of Psychology, Clinical Psychology and Psychotherapy, Marburg; Friedrich-Alexander University Erlangen-Nuernberg, Erlangen-Nuernberg, Germany Heleen Riper, Department of Clinical Psychology and EMGO Institute for Health and Care Research, VU University, Amsterdam, the Netherlands; Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg, Amsterdam, Netherlands Pim Cuijpers, Department of Clinical Psychology and EMGO Institute for Health and Care Research, VU University, Amsterdam, the Netherlands; Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg, Amsterdam, Netherlands Elena Heber*, Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg, Lueneburg, Germany David Daniel Ebert, Division of Online Health Training, Innovation Incubator, Leuphana University Lueneburg; Philipps University Marburg, Department of Psychology; Clinical Psychology and Psychotherapy, Marburg, Germany, Lueneburg, Germany Track: Research Presentation Topic: Web 2.0 approaches for clinical practice, clinical research, quality monitoring Presentation Type: Rapid-Fire Presentation Submission Type: Single Presentation Building: Sheraton Maui Resort Room: A - Wailuku Date: 2014-11-13 02:50 PM – 03:35 PM Last modified: 2014-09-04

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Background: GET.ON-Stress is a web-based stress-management intervention designed to improve stress related mental and emotional problems in employees with an elevated stress level. Based on problem solving and emotion regulation in theoretical accordance to the transactional stress model of Lazarus, the programme has proven effective in reducing health strains associated with stress including depression and anxiety. But as in other online-based interventions, low adherence to the treatment-programme is a major concern. Non-adherent participants, who drop out of the intervention, receive incomplete treatment, which is less efficacious. Identifying predictors of adherence provides the possibility to adapt future online-based stress-management programmes especially for the needs of non-adherent subgroups and enhance their effectiveness.

Objective: The goal of the current study is to identify predictors of adherence to an online cognitive-behavioural stress-management intervention (GET.ON Stress) that target work-related stress in employees.

Methods: Three randomized controlled trials evaluating the efficacy of GET-ON-Stress under varying conditions concerning treatment guidance have been conducted (guided self-help vs. waitlist-control, feedback on demand vs. waitlist-control, unguided self-help vs. waitlist control). For this secondary analyses, the data-sets of the three randomized controlled trials will be combined in order to examine predictors of adherence (N = 792). We will apply multi-level approaches to account for clustering of participants within and between studies. Adherence is defined by the number of modules completed in the programme. That comprises seven sessions each of a duration of approximately 45 – 60 minutes and one booster session available four weeks after completing the training. Predictor variables included demographic, treatment guidance, participant (e.g. emotional self-regulation) and symptom-related factors (e.g. perceived stress, symptoms of anxiety and depression).

Results: Research in progress.

Conclusions: Research in progress.