IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i23p15792-d985819.html
   My bibliography  Save this article

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

Author

Listed:
  • Erika Obikane

    (Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
    Department of Social Medicine, National Center for Child Health and Development, Tokyo 157-0074, Japan
    These authors contributed equally to this work.)

  • Natsu Sasaki

    (Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
    These authors contributed equally to this work.)

  • Kotaro Imamura

    (Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
    Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, 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)

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.

Suggested Citation

  • Erika Obikane & Natsu Sasaki & Kotaro Imamura & Kyosuke Nozawa & Rajesh Vedanthan & Pim Cuijpers & Taichi Shimazu & Masamitsu Kamada & Norito Kawakami & Daisuke Nishi, 2022. "Usefulness of Implementation Outcome Scales for Digital Mental Health (iOSDMH): Experiences from Six Randomized Controlled Trials," IJERPH, MDPI, vol. 19(23), pages 1-17, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15792-:d:985819
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/23/15792/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/23/15792/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    2. Weijters, Bert & Geuens, Maggie & Schillewaert, Niels, 2009. "The proximity effect: The role of inter-item distance on reverse-item bias," International Journal of Research in Marketing, Elsevier, vol. 26(1), pages 2-12.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aziz Barhmi & Omar Hajaji, 2023. "Multidisciplinary Approach to Supply Chain Resilience: Conceptualization and Scale Development," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 43-69.
    2. Venugopal Gopalakrishna-Remani & Robert Paul Jones & Kerri M. Camp, 2019. "Levels of EMR Adoption in U.S. Hospitals: An Empirical Examination of Absorptive Capacity, Institutional Pressures, Top Management Beliefs, and Participation," Information Systems Frontiers, Springer, vol. 21(6), pages 1325-1344, December.
    3. Elbanna, Amany & Newman, Mike, 2022. "The bright side and the dark side of top management support in Digital Transformaion –A hermeneutical reading," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    5. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    6. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    7. Schweizer, T.S., 2002. "Managing interactions between technological and stylistic innovation in the media industries, insights from the introduction of ebook technology in the publishing industry," ERIM Report Series Research in Management ERS-2002-16-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Severin Oesterle & Arne Buchwald & Nils Urbach, 2022. "Investigating the co-creation of IT consulting service value: empirical findings of a matched pair analysis," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 571-597, June.
    9. Neus Vila-Brunet & Josep Llach, 2020. "OSS-Qual: Holistic Scale to Assess Customer Quality Perception When Buying Secondhand Products in Online Platforms," Sustainability, MDPI, vol. 12(21), pages 1-15, November.
    10. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    11. Zhang, Qingyu & Vonderembse, Mark A. & Cao, Mei, 2009. "Product concept and prototype flexibility in manufacturing: Implications for customer satisfaction," European Journal of Operational Research, Elsevier, vol. 194(1), pages 143-154, April.
    12. Hajiheydari, Nastaran & Delgosha, Mohammad Soltani & Olya, Hossein, 2021. "Scepticism and resistance to IoMT in healthcare: Application of behavioural reasoning theory with configurational perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    13. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    14. Riffat Ara Zannat Tama & Md Mahmudul Hoque & Ying Liu & Mohammad Jahangir Alam & Mark Yu, 2023. "An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh," Agriculture, MDPI, vol. 13(2), pages 1-22, February.
    15. Sara Moussawi & Marios Koufaris & Raquel Benbunan-Fich, 2021. "How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 343-364, June.
    16. Wanda J. Orlikowski & C. Suzanne Iacono, 2001. "Research Commentary: Desperately Seeking the “IT” in IT Research—A Call to Theorizing the IT Artifact," Information Systems Research, INFORMS, vol. 12(2), pages 121-134, June.
    17. Rogier van de Wetering & Sherah Kurnia & Svyatoslav Kotusev, 2020. "The Effect of Enterprise Architecture Deployment Practices on Organizational Benefits: A Dynamic Capability Perspective," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
    18. Petschnig, Martin & Heidenreich, Sven & Spieth, Patrick, 2014. "Innovative alternatives take action – Investigating determinants of alternative fuel vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 68-83.
    19. Buvár Ágnes & Gáti Mirkó, 2023. "Digital marketing adoption of microenterprises in a technology acceptance approach," Management & Marketing, Sciendo, vol. 18(2), pages 127-144, June.
    20. Yan, Ruihe & Gong, Xiang, 2022. "Peer-to-peer accommodation platform affordance: Scale development and empirical investigation," Journal of Business Research, Elsevier, vol. 144(C), pages 922-938.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15792-:d:985819. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.