Evidence map›Paper›PMID 37143171›Full record

SynthesisSystematic reviews2023

The impact of technology systems and level of support in digital mental health interventions: a secondary meta-analysis.

Maxime Sasseville, Annie LeBlanc, Jack Tchuente, Mylène Boucher, Michèle Dugas, Mbemba Gisèle, Romina Barony, Maud-Christine Chouinard, Marianne Beaulieu, Nicolas Beaudet and 6 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Systematic reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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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

16 authors.

Maxime SassevilleUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada. maxime.sasseville@fsi.ulaval.ca.ORCID 0000-0003-1694-1414
Annie LeBlancUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada.
Jack TchuenteVITAM Research Center on Sustainable Health, Quebec City, Canada.
Mylène BoucherUniversité Laval, Quebec City, Canada.
Michèle DugasVITAM Research Center on Sustainable Health, Quebec City, Canada.
Mbemba GisèleUniversité Laval, Quebec City, Canada.
Romina BaronyUniversité Laval, Quebec City, Canada.
Maud-Christine ChouinardUniversité de Montréal, Montréal, Canada.
Marianne BeaulieuUniversité Laval, Quebec City, Canada.
Nicolas BeaudetUniversité de Sherbrooke, Omnimed, Sherbrooke, Quebec, Canada.
Becky SkidmoreUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada.
Pascale CholetteCentre Intégré Universitaire de Santé et de Services Sociaux de la Capitale Nationale, Quebec City, Canada.
Christine AspirosUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada.
Alain LaroucheUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada.
Guylaine ChabotUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada.
Marie-Pierre GagnonUniversité Laval-VITAM Research Center on Sustainable Health, Quebec City, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe majority of people with a chronic disease (e.g., diabetes, hypertension, COPD) have more than one concurrent condition and are also at higher risk for developing comorbidities in mental health, including anxiety and depression. There is an urgent need for more relevant and accurate data on digital interventions in this area to prepare for an increase demand for mental health services. The aim of this study was to conduct a meta-analysis of the digital mental health interventions for people with comorbid physical and mental chronic diseases to compare the effect of technology systems and level of support.

methodsThis secondary meta-analysis follows a rapid review of systematic reviews, a virtual workshop with knowledge users to identify research questions and a modified Delphi study to guide research methods: What types of digital health interventions (according to a recognized categorization) are the most effective for the management of concomitant mental health and chronic disease conditions in adults? We conducted a secondary analysis of the primary studies identified in the rapid review. Two reviewers independently screened the titles and abstracts and applied inclusion criteria: RCT design using a digital mental health intervention in a population of adults with another chronic condition, published after 2010 in French or English, and including an outcome measurement of anxiety or depression.

resultsSeven hundred eight primary studies were extracted from the systematic reviews and 84 primary studies met the inclusion criteria Digital mental health interventions were significantly more effective than in-person care for both anxiety and depression outcomes. Online messaging was the most effective technology to improve anxiety and depression scores; however, all technology types were effective. Interventions partially supported by healthcare professionals were more effective than self-administered.

conclusionsWhile our meta-analysis identifies digital intervention's characteristics are associated with better effectiveness, all technologies and levels of support could be used considering implementation context and population.

trial registrationThe protocol for this review is registered in the National Collaborating Centre for Methods and Tools (NCCMT) COVID-19 Rapid Evidence Service (ID 75).

Indexed as

COVID-19Mental HealthAdultAnxietyChronic DiseaseHumansSystematic Reviews as TopicChronic diseasesDigital interventionsMental healthMeta-analysisRapid review

Identifiers

PMID37143171
PMCPMC10157597

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.