Evidence map›Paper›PMID 37145257›Full record

ArticleThe Psychiatric quarterly2023

Evaluating the Use of Online Self-Report Questionnaires as Clinically Valid Mental Health Monitoring Tools in the Clinical Whitespace.

Kaitlyn Arrow, Philip Resnik, Hanna Michel, Christopher Kitchen, Chen Mo, Shuo Chen, Carol Espy-Wilson, Glen Coppersmith, Colin Frazier, Deanna L Kelly

Open access · hybridAbstract read
In one paragraph

Article in The Psychiatric quarterly, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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  8. Psychometric Evaluation of Two Adult Autism Screening Tools in Brazil.Autism research : official journal of the International Society for Autism Research · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Kaitlyn Arrow *Maryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Philip Resnik *Institute for Advanced Computer Studies, Department of Linguistics, University of Maryland College Park, College Park, MD, USA.
Hanna MichelMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Christopher KitchenJohns Hopkins University, Baltimore, MD, USA.
Chen MoMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Shuo ChenMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Carol Espy-WilsonInstitute for Systems Research, University of Maryland College Park, College Park, MD, USA.
Glen CoppersmithMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Colin FrazierMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA.
Deanna L KellyMaryland Psychiatric Research Center, University of Maryland School of Medicine, Catonsville, MD, USA. dlkelly@som.umaryland.edu.
University of Maryland, Baltimore · USUniversity of Maryland, College Park · USJohns Hopkins University · US

Funding

Aim-HI Aim-HIAmazon Web Services Amazon Web ServicesNational Science Foundation 212470
6 · The paper itself

Abstract

Although digital health solutions are increasingly popular in clinical psychiatry, one application that has not been fully explored is the utilization of survey technology to monitor patients outside of the clinic. Supplementing routine care with digital information collected in the "clinical whitespace" between visits could improve care for patients with severe mental illness. This study evaluated the feasibility and validity of using online self-report questionnaires to supplement in-person clinical evaluations in persons with and without psychiatric diagnoses. We performed a rigorous in-person clinical diagnostic and assessment battery in 54 participants with schizophrenia (N = 23), depressive disorder (N = 14), and healthy controls (N = 17) using standard assessments for depressive and psychotic symptomatology. Participants were then asked to complete brief online assessments of depressive (Quick Inventory of Depressive Symptomatology) and psychotic (Community Assessment of Psychic Experiences) symptoms outside of the clinic for comparison with the ground-truth in-person assessments. We found that online self-report ratings of severity were significantly correlated with the clinical assessments for depression (two assessments used: R = 0.63, p < 0.001; R = 0.73, p < 0.001) and psychosis (R = 0.62, p < 0.001). Our results demonstrate the feasibility and validity of collecting psychiatric symptom ratings through online surveys. Surveillance of this kind may be especially useful in detecting acute mental health crises between patient visits and can generally contribute to more comprehensive psychiatric treatment.

Indexed as

DepressionHealth SurveysInternetPsychotic DisordersSelf ReportAdultFemaleHumansInternet-Based InterventionMaleMental HealthReproducibility of ResultsSchizophreniaYoung AdultDepressionInternetSchizophreniaSelf-reportTechnology

Identifiers

PMID37145257
PMCPMC10160731
OpenAlexW4372335256

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.