ArticleJournal of technology in behavioral science2022
Global Collaboration Around Digital Mental Health: The LAMP Consortium.
Article in Journal of technology in behavioral science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- SAFEGUARD: Transforming Military Suicide Prevention Through Predictive Analytics and Targeted Interventions.Current psychiatry reports · 2026Review
- Mobile cognitive remote assessment of schizophrenia: a global multi-site pilot study.Schizophrenia (Heidelberg, Germany) · 2025Article
- Towards clinical subtypes in schizophrenia: integrating cognitive, functional, and digital phenotyping assessments.Molecular psychiatry · 2025Article
- Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program.Schizophrenia (Heidelberg, Germany) · 2025Article
- Transforming Digital Phenotyping Raw Data Into Actionable Biomarkers, Quality Metrics, and Data Visualizations Using Cortex Software Package: Tutorial.Journal of medical Internet research · 2024Article
- Kenya Psychosis-Risk Outcomes Study (KePROS): Development of an Accelerated Medicine Partnership Schizophrenia-Aligned Project in Africa.Schizophrenia bulletin open · 2024Article
- Digital mental health for postpartum women: perils, pitfalls, and promise.NPJ digital medicine · 2023Article
- Evaluation of the Use of Digital Mental Health Platforms and Interventions: Scoping Review.International journal of environmental research and public health · 2022Article
- Digital Phenotyping Data to Predict Symptom Improvement and App Personalization: Protocol for a Prospective Study.JMIR research protocols · 2022Article
- Digital phenotyping correlations in larger mental health samples: analysis and replication.BJPsych open · 2022Article
- Usable Data Visualization for Digital Biomarkers: An Analysis of Usability, Data Sharing, and Clinician Contact.Digital biomarkersArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the great potential, there has been a lack of progress in the development of sharable and scalable tools for digital mental health due to difficulty in reproducibility and clinical application. The LAMP Platform was developed to address this gap by creating a single platform that works for a variety of clinical and research use cases. The study aims to understand how a consortium of clinical and research sites can help onboard, execute, and expand digital health research, software, and use cases. The Division of Digital Psychiatry implemented a formal consortium with goal of expanding the reach of mindLAMP as a digital mental health platform, enabling diverse studies and expanded use cases, and supportint growth of mindLAMP and consortium members' research. The LAMP Consortium has brought together 54 sites from across the world, encouraging collaboration and idea sharing. These sites' locations range from the USA to the Czech Republic to Australia, and apply the many features of LAMP to research, clinical, research and clinical, and industry use. The most popular features were surveys, sharing/viewing data, and GPS passive data collection. A user support network is necessary to encourage research and clinical use of the LAMP Platform. Resources like documentation, an online forum, and newsletters are essential to promote cooperation between many types of sites that is essential to advancing the field of digital mental health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.