Evidence map›Paper›PMID 36622747›Full record

ReviewJMIR mental health2023

Efficacy of Virtual Care for Depressive Disorders: Systematic Review and Meta-analysis.

Crystal Edler Schiller, Julianna Prim, Anna E Bauer, Linda Lux, Laura Claire Lundegard, Michelle Kang, Samantha Hellberg, Katherine Thompson, Theresa Webber, Adonay Teklezghi and 7 more

Abstract readReview
In one paragraph

Review in JMIR mental health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Adoption of Digital Therapeutics in Europe.Therapeutics and clinical risk management · 2024
    Review
  5. Understanding the potential of digital therapies in implementing the standard of care for depression in Europe.European psychiatry : the journal of the Association of European Psychiatrists · 2023
    Article
  6. Review
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

17 authors.

Crystal Edler SchillerDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0001-6186-701X
Julianna PrimDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0003-2894-0881
Anna E BauerDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-7771-930X
Linda LuxDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0003-2560-7362
Laura Claire LundegardDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-1202-6473
Michelle KangDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0003-2590-9950
Samantha HellbergDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-0302-2382
Katherine ThompsonDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-3841-2508
Theresa WebberDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-7285-6719
Adonay TeklezghiDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0003-3363-8062
Noah PetteeDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-5621-4847
Katherine GaffneyDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0003-1809-9662
Gabrielle HodginsDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0001-7329-233X
Fariha RahmanDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0001-6541-9003
J Nikki SteinsiekDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-4691-3724
Anita ModiDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-2006-1711
Bradley N GaynesDepartment of Psychiatry, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-8283-5030

Funding

Disentangling the Epidemiologic and Genetic Heterogeneity of Postpartum Depression to Predict Risk and PrognosisK01MH120352 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BAUER, ANNA ELIZABETH · 2019 to 2023
$761k
NIMH NIH HHS K01 MH120352
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has created an epidemic of distress-related mental disorders such as depression, while simultaneously necessitating a shift to virtual domains of mental health care; yet, the evidence to support the use of virtual interventions is unclear.

objectiveThe purpose of this study was to evaluate the efficacy of virtual interventions for depressive disorders by addressing three key questions: (1) Does virtual intervention provide better outcomes than no treatment or other control conditions (ie, waitlist, treatment as usual [TAU], or attention control)? (2) Does in-person intervention provide better outcomes than virtual intervention? (3) Does one type of virtual intervention provide better outcomes than another?

methodsWe searched the PubMed, EMBASE, and PsycINFO databases for trials published from January 1, 2010, to October 30, 2021. We included randomized controlled trials of adults with depressive disorders that tested a virtual intervention and used a validated depression measure. Primary outcomes were defined as remission (ie, no longer meeting the clinical cutoff for depression), response (ie, a clinically significant reduction in depressive symptoms), and depression severity at posttreatment. Two researchers independently selected studies and extracted data using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Risk of bias was evaluated based on Agency for Healthcare and Research Quality guidelines. We calculated odds ratios (ORs) for binary outcomes and standardized mean differences (SMDs) for continuous outcomes.

resultsWe identified 3797 references, 24 of which were eligible. Compared with waitlist, virtual intervention had higher odds of remission (OR 10.30, 95% CI 5.70-18.60; N=619 patients) and lower posttreatment symptom severity (SMD 0.81, 95% CI 0.52-1.10; N=1071). Compared with TAU and virtual attention control conditions, virtual intervention had higher odds of remission (OR 2.27, 95% CI 1.10-3.35; N=512) and lower posttreatment symptom severity (SMD 0.25, 95% CI 0.09-0.42; N=573). In-person intervention outcomes were not significantly different from virtual intervention outcomes (eg, remission OR 0.84, CI 0.51-1.37; N=789). No eligible studies directly compared one active virtual intervention to another.

conclusionsVirtual interventions were efficacious compared with control conditions, including waitlist control, TAU, and attention control. Although the number of studies was relatively small, the strength of evidence was moderate that in-person interventions did not yield significantly better outcomes than virtual interventions for depressive disorders.

Indexed as

depressiondepressive disorderdigital healthdigital interventiondigital mental healthefficacyeHealthhealth interventionhealth outcomemental healthmeta-analysisreviewtherapytreatmentvirtualvirtual carevirtual intervention

Identifiers

PMID36622747
PMCPMC9871881

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.