Evidence map›Paper›PMID 38664738›Full record

ArticleBMC health services research2024

Predictive modeling of initiation and delayed mental health contact for depression.

Vanessa Panaite, Dezon K Finch, Paul Pfeiffer, Nathan J Cohen, Amy Alman, Jolie Haun, Susan K Schultz, Shannon R Miles, Heather G Belanger, F Andrew F Kozel and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 16% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
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

14 authors at 7 institutions in 1 country.

Vanessa PanaiteResearch & Development Service, James A. Haley Veterans' Hospital, Tampa, FL, USA. vanessa.panaite2@va.gov.
Dezon K FinchCenter of Innovation for Complex Chronic Healthcare (CINCCH), Edward Hines Jr. VA Hospital, Hines, IL, USA.
Paul PfeifferVA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Nathan J CohenDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Amy AlmanCollege of Public Health, University of South Florida, Tampa, FL, USA.
Jolie HaunResearch & Development Service, James A. Haley Veterans' Hospital, Tampa, FL, USA.
Susan K SchultzDepartment of Veterans Affairs VISN 23 Clinical Resource Hub, Minneapolis, MN, USA.
Shannon R MilesMental Health and Behavioral Sciences, James A. Haley Veterans' Hospital, Tampa, FL, USA.
Heather G BelangerDepartment of Psychology, University of South Florida, Tampa, FL, USA.
F Andrew F KozelDepartment of Behavioral Sciences and Social Medicine, Florida State University, Tallahassee, FL, USA.
Jonathan RottenbergDepartment of Psychology, University of South Florida, Tampa, FL, USA.
Andrew R DevendorfDepartment of Psychology, University of South Florida, Tampa, FL, USA.
Blake BarrettResearch & Development Service, James A. Haley Veterans' Hospital, Tampa, FL, USA.
Stephen L LutherResearch & Development Service, James A. Haley Veterans' Hospital, Tampa, FL, USA.
James A. Haley Veterans' Hospital · USUniversity of South Florida · USEdward Hines, Jr. VA Hospital · USFlorida State University · USIcahn School of Medicine at Mount Sinai · USVA Center for Clinical Management Research · USVA Midwest Health Care Network · US

Funding

An eHealth intervention to increase depression treatment initiation and adherence among Veterans referred for mental health servicesIK2HX002899 · VA · JAMES A. HALEY VA MEDICAL CENTER · PI Vanessa Panaite · 2021 to 2026
–
HSRD VA IK2 HX002899
6 · The paper itself

Abstract

backgroundDepression is prevalent among Operation Enduring Freedom and Operation Iraqi Freedom (OEF/OIF) Veterans, yet rates of Veteran mental health care utilization remain modest. The current study examined: factors in electronic health records (EHR) associated with lack of treatment initiation and treatment delay; the accuracy of regression and machine learning models to predict initiation of treatment.

methodsWe obtained data from the VA Corporate Data Warehouse (CDW). EHR data were extracted for 127,423 Veterans who deployed to Iraq/Afghanistan after 9/11 with a positive depression screen and a first depression diagnosis between 2001 and 2021. We also obtained 12-month pre-diagnosis and post-diagnosis patient data. Retrospective cohort analysis was employed to test if predictors can reliably differentiate patients who initiated, delayed, or received no mental health treatment associated with their depression diagnosis.

results108,457 Veterans with depression, initiated depression-related care (55,492 Veterans delayed treatment beyond one month). Those who were male, without VA disability benefits, with a mild depression diagnosis, and had a history of psychotherapy were less likely to initiate treatment. Among those who initiated care, those with single and mild depression episodes at baseline, with either PTSD or who lacked comorbidities were more likely to delay treatment for depression. A history of mental health treatment, of an anxiety disorder, and a positive depression screen were each related to faster treatment initiation. Classification of patients was modest (ROC AUC = 0.59 95%CI = 0.586-0.602; machine learning F-measure = 0.46).

conclusionsHaving VA disability benefits was the strongest predictor of treatment initiation after a depression diagnosis and a history of mental health treatment was the strongest predictor of delayed initiation of treatment. The complexity of the relationship between VA benefits and history of mental health care with treatment initiation after a depression diagnosis is further discussed. Modest classification accuracy with currently known predictors suggests the need to identify additional predictors of successful depression management.

Indexed as

DepressionVeteransAdultAfghan Campaign 2001-Electronic Health RecordsFemaleHumansIraq War, 2003-2011Machine LearningMaleMental Health ServicesMiddle AgedPatient Acceptance of Health CareRetrospective StudiesTime-to-TreatmentUnited StatesClassificationDepressionMental healthTreatment delayTreatment initiation

Identifiers

PMID38664738
PMCPMC11046938
OpenAlexW4395445749

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.