Usefulness of Implementation Outcome Scales for Digital Mental Health (iOSDMH): Experiences from Six Randomized Controlled Trials

Erika Obikane, Natsu Sasaki, Kotaro Imamura, Kyosuke Nozawa, Rajesh Vedanthan, Pim Cuijpers, Taichi Shimazu, Masamitsu Kamada, Norito Kawakami and Daisuke Nishi ()
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Erika Obikane: Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
Natsu Sasaki: Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
Kotaro Imamura: Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
Kyosuke Nozawa: Department of Psychiatric Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
Rajesh Vedanthan: Department of Population Health, Grossman School of Medicine, New York University, New York, NY 10016, USA
Pim Cuijpers: Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, 1081 Amsterdam, The Netherlands
Taichi Shimazu: Division of Behavioral Sciences, Institute for Cancer Control, National Cancer Center, Tokyo 04-0045, Japan
Masamitsu Kamada: Department of Health Education and Health Sociology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
Norito Kawakami: Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
Daisuke Nishi: Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan

IJERPH, 2022, vol. 19, issue 23, 1-17

Abstract: Objectives: Measuring implementation outcomes for digital mental health interventions is essential for examining the effective delivery of these interventions. The “Implementation Outcome Scale of Digital Mental Health” (iOSDMH) has been validated and used in several trials. This study aimed to compare the iOSDMH for participants in six randomized controlled trials (RCTs) involving web-based interventions and to discuss the implications of the iOSDMH for improving the interventions. Additionally, this study examined the associations between iOSDMH scores and program completion rate (adherence). Methods: Variations in total scores and subscales of the iOSDMH were compared in six RCTs of digital mental health interventions conducted in Japan. The web-based intervention programs were based on cognitive behavioral therapy (2 programs), behavioral activation (1 program), acceptance and commitment (1 program), a combination of mindfulness, behavioral activation, and physical activity (1 program), and government guidelines for suicide prevention (1 program). Participants were full-time employees (2 programs), perinatal women (2 programs), working mothers with children (1 program), and students (1 program). The total score and subscale scores were tested using analysis of variance for between-group differences. Results: Total score and subscale scores of the iOSDMH among six trials showed a significant group difference, reflecting users’ perceptions of how each program was implemented, including aspects such as acceptability, appropriateness, feasibility, overall satisfaction, and harm. Subscale scores showed positive associations with completion rate, especially in terms of acceptability and satisfaction (R-squared = 0.93 and 0.89, respectively). Conclusions: The iOSDMH may be a useful tool for evaluating participants’ perceptions of features implemented in web-based interventions, which could contribute to improvements and further development of the intervention.

Keywords: implementation outcomes; acceptability; appropriateness; feasibility; satisfaction (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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