Rethinking technology innovation for mental health: framework for multi-sectoral collaboration
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Most people lack access to much-needed mental health care.
“Most people lack access to much-needed mental health care.”
From Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers. (2025) · cites this paper as [135]
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- Authors
- Suh, J., Pendse, S. R., Lewis, R., Howe, E., Saha, K., Okoli, E., Amores, J., Ramos, G., Shen, J., Borghouts, J., Sharma, A., Pedrelli, P., Friedman, L., Jackman, C., Benhalim, Y., Ong, D. C., Segal, S., Althoff, T., & Czerwinski, M.
- Affiliations
- Microsoft (United States) (US)
- Georgia Institute of Technology (US)
- MIT Media Lab (US)
- University of California, Berkeley (US)
- University of Illinois Urbana-Champaign (US)
- Stony Brook University (US)
- University of California, Irvine (US)
- University of Washington (US)
- Harvard University (US)
- Optum (United States) (US)
- The University of Texas at Austin (US)
- Corresponding author
- Suh, Jina
- ORCID
- Venue
- Nature Mental Health
- Published
- 2024-05-03
- Volume
- 2
- Issue
- 5
- Pages
- 478-488
- ISSN
- 2731-6076 (ISSN-L)
- OpenAlex
- W4396615168
- Semantic Scholar
- 172896af5c73eede977e338bd63d84d1e188ad68
- Cited by
- 8
- References
- 88
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 1
- FWCI
- 3.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Mental Health (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- technological innovation, mental health, intersectoral collaboration, stakeholder alignment, technology governance, mental health assessment, technological literacy, user empowerment, clinician engagement, digital mental health
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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