Furthering the reliable and valid measurement of mental health screening, diagnoses, treatment and outcomes through health information technology
Open accessAbstract
Introduction Measurement of mental health is challenging; however, many solutions may be found through the use of health information technology.Method This article reviews current approaches to measuring mental health, focusing on screening, diagnosis, treatment, and outcomes. It then identifies several key areas in which health information technology may advance the field and provide reliable and valid measurements that are readily available to and manageable for providers, as well as acceptable, feasible, and sustainable for selected populations.Result and conclusions Although new technologies must overcome many challenges, including privacy, efficiency, cost, and scalability, it is an exciting and fast-growing field with many potential applications and clinical benefit.
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The flawed approach fails to take into account the complexity of neurobehavioural disorders in three ways.
“This flawed approach fails to take into account the complexity of neurobehavioural disorders in 3 ways.9,34–37”
From Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders (2021) · cites this paper as [37]
Patient subgroups in precision medicine RCTs are defined by baseline pre-randomization markers hypothesized to modulate the effect size of the intervention.
“First, patient subgroups are defined by baseline pre-randomization markers that are hypothesized to modulate the effect size of the intervention (i.e., modulators), an approach commonly used in cardiovascular disease, for example.”
From Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders (2021) · cites this paper as [37]
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- Authors
- Haberer, J. E., Trabin, T., & Klinkman, M.
- Affiliations
- Harvard University (US)
- University of Michigan (US)
- Venue
- General Hospital Psychiatry
- Publisher
- Elsevier BV
- Published
- 2013-07
- Volume
- 35
- Issue
- 4
- Pages
- 349-353
- ISSN
- 0163-8343 (ISSN-L)
- PMC
- PMC3692579
- OpenAlex
- W2019196399
- Cited by
- 39
- References
- 79
- Citations by year
- 2025: 4 · 2024: 5 · 2023: 4 · 2021: 5 · 2020: 6 · 2019: 5 · 2018: 1 · 2017: 1 · 2016: 2 · 2015: 5 · 2014: 1
- FWCI
- 0.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- General Hospital Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Public Health Service (#290-09-00036U)
- National Institute of Mental Health (K23MH087228)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- mental health measurement, mental health screening, psychiatric diagnosis, psychotherapy, treatment outcomes, health information technology, reliability and validity, privacy, scalability, feasibility
- MeSH terms
- Mental Disorders, Humans, Mass Screening, Medical Informatics, Outcome and Process Assessment, Health Care, Reproducibility of Results
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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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