ArticleJMIR formative research2021
Implementation Outcome Scales for Digital Mental Health (iOSDMH): Scale Development and Cross-sectional Study.
Article in JMIR formative research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- An mHealth Intervention Promoting Physical Activity to Reduce Psychological Distress Among Workers: Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Assessing the Efficacy of the INTELLECT Cognitive Behavioral Therapy Mobile App for Anxiety and Depressive Symptoms Among At-Risk Japanese Employees: Randomized Controlled Trial.JMIR mHealth and uHealth · 2025Trial
- Artificial Intelligence Discontinuation Effects (AI-DICE): An Emerging Phenomenon in Mental Health Applications.JMIR AI · 2026Article
- Article
- Guided internet-delivered compassion-focused therapy for women with recurrent pregnancy loss: A protocol of a randomized controlled trial.PCN reports : psychiatry and clinical neurosciences · 2026Article
- Acceptability, Feasibility, and Appropriateness of Mobile Phone Messaging-Based Message-Framing Intervention for Promoting Maternal and Newborn Care Practices.International journal of environmental research and public health · 2025Article
- Effectiveness and Implementation Outcomes of an mHealth App Aimed at Promoting Physical Activity and Improving Psychological Distress in the Workplace Setting: Cluster-Level Nonrandomized Controlled Trial.JMIR mHealth and uHealth · 2025Article
- Effectiveness of an online text-based stress management program for employees who work in micro- and small-sized enterprises: A randomized controlled trial.Internet interventions · 2024Article
- Effects of the Modified version of the Mental Health Supporter Training Program on mental-health-related public stigma among Japanese people: A pretest/posttest study.PCN reports : psychiatry and clinical neurosciences · 2024Article
- Implementation of an internet-based stress management program in micro- and small-sized enterprises: a study protocol for a pre-post feasibility study of the effectiveness-implementation hybrid type 2 trial.Pilot and feasibility studies · 2024Article
- Effects of the Mental Health Supporter Training Program on mental health-related public stigma among Japanese people: A pretest/posttest study.PCN reports : psychiatry and clinical neurosciences · 2024Article
- Multifaceted ORganizational InterventiONs (M-ORION) project for prevention of depression and anxiety among workers: study protocol for a five-arm cluster randomized controlled trial.BMC public health · 2024Article
- mHealth Intervention to Promote Physical Activity Among Employees Using a Deep Learning Model for Passive Monitoring of Depression and Anxiety: Single-Arm Feasibility Trial.JMIR formative research · 2023Article
- Cultural Adaptation of the Actionable Health App Evaluation in Japan: Protocol for a Web-Based Modified Delphi Expert Consensus Study.JMIR research protocols · 2023Article
- Usefulness of Implementation Outcome Scales for Digital Mental Health (iOSDMH): Experiences from Six Randomized Controlled Trials.International journal of environmental research and public health · 2022Article
- Effectiveness of an Online Peer Gatekeeper Training Program for Postsecondary Students on Suicide Prevention in Japan: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2022Article
- Facilitating stress prevention in micro and small-sized enterprises: protocol for a mixed method study to evaluate the effectiveness and implementation process of targeted web-based interventions.BMC public health · 2022Article
- The Effect of the Imacoco Care Psychoeducation Website on Improving Psychological Distress Among Workers During the COVID-19 Pandemic: Randomized Controlled Trial.JMIR formative research · 2022Article
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Authors and funding
9 authors.
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Abstract
backgroundDigital mental health interventions are being used more than ever for the prevention and treatment of psychological problems. Optimizing the implementation aspects of digital mental health is essential to deliver the program to populations in need, but there is a lack of validated implementation outcome measures for digital mental health interventions.
objectiveThe primary aim of this study is to develop implementation outcome scales of digital mental health for different levels of stakeholders involved in the implementation process: users, providers, and managers or policy makers. The secondary aim is to validate the developed scale for users.
methodsWe developed English and Japanese versions of the implementation outcome scales for digital mental health (iOSDMH) based on the literature review and panel discussions with experts in implementation research and web-based psychotherapy. The study developed acceptability, appropriateness, feasibility, satisfaction, and harm as the outcome measures for users, providers, and managers or policy makers. We conducted evidence-based interventions via the internet using UTSMeD, a website for mental health information (N=200). Exploratory factor analysis (EFA) was conducted to assess the structural validity of the iOSDMH for users. Satisfaction, which consisted of a single item, was not included in the EFA.
resultsThe iOSDMH was developed for users, providers, and managers or policy makers. The iOSDMH contains 19 items for users, 11 items for providers, and 14 items for managers or policy makers. Cronbach α coefficients indicated intermediate internal consistency for acceptability (α=.665) but high consistency for appropriateness (α=.776), feasibility (α=.832), and harm (α=.777) of the iOSDMH for users. EFA revealed 3-factor structures, indicating acceptability and appropriateness as close concepts. Despite the similarity between these 2 concepts, we inferred that acceptability and appropriateness should be used as different factors, following previous studies.
conclusionsWe developed iOSDMH for users, providers, and managers. Psychometric assessment of the scales for users demonstrated acceptable reliability and validity. Evaluating the components of digital mental health implementation is a major step forward in implementation science.
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