Evidence map›Paper›PMID 34842556›Full record

ReviewJMIR mental health2021

Self-directed Technology-Based Therapeutic Methods for Adult Patients Receiving Mental Health Services: Systematic Review.

Anthony Saad, Deanna Bruno, Bettina Camara, Josephine D'Agostino, Blanca Bolea-Alamanac

Open access · goldAbstract readReview
In one paragraph

Review in JMIR mental health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
3.7field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 38 citations in OpenAlex.

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  20. Real-World Evaluation of a Large-Scale Blended Care-Cognitive Behavioral Therapy Program for Symptoms of Anxiety and Depression.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2022
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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

5 authors at 2 institutions in 1 country.

Anthony Saad *Department of Psychiatry, Women's College Hospital, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-1890-1029
Deanna BrunoDepartment of Psychiatry, Women's College Hospital, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-9759-9472
Bettina CamaraDepartment of Immunology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-9579-3768
Josephine D'AgostinoDepartment of Psychiatry, Women's College Hospital, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-2180-4951
Blanca Bolea-AlamanacDepartment of Psychiatry, Women's College Hospital, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-6308-2731
University of Toronto · CAWomen's College Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTechnological interventions used to treat illnesses and promote health are grouped under the umbrella term of digital therapeutics. The use of digital therapeutics is becoming increasingly common in mental health. Although many technologies are currently being implemented, research supporting their usability, efficacy, and risk requires further examination, especially for those interventions that can be used without support.

objectiveThis review aims to identify the evidence-based, self-directed, technology-based methods of care that can be used in adult patients after they are discharged from mental health services. The interventions reviewed are automated with no human input required (either at the patient's or at the technology's end), so the patients can implement them without any support.

methodsA systematic review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines in 3 databases: PubMed, Web of Science, and OVID. The inclusion criteria were self-directed, automated, and technology-based interventions related to mental health, primarily for adults, having a solid evaluation process. The interventions had to be self-directed, in that the participants could use the technology without any external guidance.

resultsWe identified 36 papers that met the inclusion criteria: 26 randomized controlled trials, 9 nonrandomized controlled trial quantitative studies, and 1 qualitative study. The technologies used included websites, automated text messaging, phone apps, videos, computer software, and integrated voice response. There were 22 studies focused on internet-based cognitive behavioral therapies as a therapeutic paradigm compared with the waitlist, web-based human-delivered therapy, and other interventions. Among these studies, 14 used paradigms other than the internet-based cognitive behavioral therapy. Of the 8 studies comparing guided and unguided digital care, 3 showed no differences, 3 favored guided interventions, and 2 favored unguided interventions. The research also showed that dropout rates were as high as 80%, citing potential problems with the acceptability of the suggested technologies.

conclusionsThere is limited research on the efficacy and suitability of self-directed technology-based care options for mental health. Digital technologies have the potential to bridge the gap between ambulatory care and independent living. However, these interventions may need to be developed collaboratively with the users to encourage their acceptability and to avoid high dropout rates.

Indexed as

digital therapeuticsinternetmental healthmobile applicationsmobile phoneself-directedtechnologytelehealthtelemedicine

Identifiers

PMID34842556
PMCPMC8665378
OpenAlexW3195117850

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.