characteristics of participants in a randomized trial of an internet intervention for depression (evident) in comparison to a national sample (degs1)
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2017
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Abstract
Background: While the efficacy of Internet interventions for depression has been demonstrated in numerous studies, there is concern that the participants in these studies may systematically differ from depressed subjects in the general population. The goal of this study was to compare participants in a large trial of an Internet intervention for depression with a population-based sample that reported depressive symptomatology in the same range of severity.
Methodology: The analysis is based on a sample of participants of a randomized controlled trial testing the effectiveness of an Internet intervention for depression in mild to moderate depression (EVIDENT, N = 1013) and a subsample of participants in a representative population-based sample (DEGS1, n = 1978). The DEGS1 subsample was chosen based on the score in the Patient Health Questionnaire-9 (PHQ-9, score 5–14) as this was the main inclusion criterion for the EVIDENT study. Both samples were compared with respect to a range of demographic and clinical variables.
Results: Compared with the DEGS1 subsample, participants in the EVIDENT sample were significantly more often female (68.6% vs. 56.3%), slightly older (mean age 42.9 vs. 40.4 years), had more often completed highest secondary education (51.3% vs. 22.4%), were clinically more severely affected (moderate depressive symptoms in 62.6% vs. 18.3%) and reported a lower quality of life.
Conclusion: These findings indicate that participants in this Internet trial were not just internet savvy young males without significant impairment. Future studies should aim to recruit participants with lower educational status to increase the reach of Internet interventions.
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spth2017internetcharacteristics
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| Authors | ;Christina Späth;Ulfert Hapke;Ulrike Maske;Johanna Schröder;Steffen Moritz;Thomas Berger;Björn Meyer;Matthias Rose;Sandra Nolte;Jan Philipp Klein |
| Journal | journal of electroanalytical chemistry |
| Year | 2017 |
| DOI |
10.1016/j.invent.2017.05.003
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