Evidence map›Paper›PMID 28566267›Full record

SynthesisJournal of medical Internet research2017

Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis.

Fabian Wahle, Lea Bollhalder, Tobias Kowatsch, Elgar Fleisch

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of medical Internet research, 2017. 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
–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

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

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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

4 authors.

Fabian WahleCenter for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zürich, Zürich, Switzerland.ORCID 0000-0003-1377-9239
Lea BollhalderInstitute of Technology Management, University of St Gallen, St Gallen, Switzerland.ORCID 0000-0003-3215-0110
Tobias KowatschCenter for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland.ORCID 0000-0001-5939-4145
Elgar FleischInstitute of Technology Management, University of St Gallen, St Gallen, Switzerland.ORCID 0000-0002-4842-1117

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExisting research postulates a variety of components that show an impact on utilization of technology-mediated mental health information systems (MHIS) and treatment outcome. Although researchers assessed the effect of isolated design elements on the results of Web-based interventions and the associations between symptom reduction and use of components across computer and mobile phone platforms, there remains uncertainty with regard to which components of technology-mediated interventions for mental health exert the greatest therapeutic gain. Until now, no studies have presented results on the therapeutic benefit associated with specific service components of technology-mediated MHIS for depression.

objectiveThis systematic review aims at identifying components of technology-mediated MHIS for patients with depression. Consequently, all randomized controlled trials comparing technology-mediated treatments for depression to either waiting-list control, treatment as usual, or any other form of treatment for depression were reviewed. Updating prior reviews, this study aims to (1) assess the effectiveness of technology-supported interventions for the treatment of depression and (2) add to the debate on what components in technology-mediated MHIS for the treatment of depression should be standard of care.

methodsSystematic searches in MEDLINE, PsycINFO, and the Cochrane Library were conducted. Effect sizes for each comparison between a technology-enabled intervention and a control condition were computed using the standard mean difference (SMD). Chi-square tests were used to test for heterogeneity. Using subgroup analysis, potential sources of heterogeneity were analyzed. Publication bias was examined using visual inspection of funnel plots and Begg's test. Qualitative data analysis was also used. In an explorative approach, a list of relevant components was extracted from the body of literature by consensus between two researchers.

resultsOf 6387 studies initially identified, 45 met all inclusion criteria. Programs analyzed showed a significant trend toward reduced depressive symptoms (SMD -0.58, 95% CI -0.71 to -0.45, P<.001). Heterogeneity was large (I2≥76). A total of 15 components were identified.

conclusionsTechnology-mediated MHIS for the treatment of depression has a consistent positive overall effect compared to controls. A total of 15 components have been identified. Further studies are needed to quantify the impact of individual components on treatment effects and to identify further components that are relevant for the design of future technology-mediated interventions for the treatment of depression and other mental disorders.

Indexed as

DepressionHealth Information SystemsHumansMental HealthTreatment Outcomedepressiondesign featureinformation systemsliterature reviewmental health

Identifiers

PMID28566267
PMCPMC5471345

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.