Evidence map›Paper›PMID 39182064›Full record

SynthesisBMC medical research methodology2024

User engagement in clinical trials of digital mental health interventions: a systematic review.

Jack Elkes, Suzie Cro, Rachel Batchelor, Siobhan O'Connor, Ly-Mee Yu, Lauren Bell, Victoria Harris, Jacqueline Sin, Victoria Cornelius

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 4 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

18 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Towards Human-Centered Digital Health Interventions.The Psychiatric clinics of North America · 2026
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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

9 authors.

Jack ElkesImperial Clinical Trials Unit, Imperial College London, White City Campus, Stadium House, 68 Wood Lane, London, W12 7RH, UK. j.elkes@imperial.ac.uk.
Suzie CroImperial Clinical Trials Unit, Imperial College London, White City Campus, Stadium House, 68 Wood Lane, London, W12 7RH, UK.
Rachel BatchelorUniversity of Oxford, Oxford, UK.
Siobhan O'ConnorFlorence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King's College London, London, UK.
Ly-Mee YuUniversity of Oxford, Oxford, UK.
Lauren BellLeeds Institute of Clinical Trials Research, University of Leeds, Leeds, LS2 9JT, UK.
Victoria HarrisUniversity of Oxford, Oxford, UK.
Jacqueline Sin *City St Geroge's, University of London, London, UK.
Victoria Cornelius *Imperial Clinical Trials Unit, Imperial College London, White City Campus, Stadium House, 68 Wood Lane, London, W12 7RH, UK.

Funding

NIHR Doctoral Fellowship NIHR301810
6 · The paper itself

Abstract

introductionDigital mental health interventions (DMHIs) overcome traditional barriers enabling wider access to mental health support and allowing individuals to manage their treatment. How individuals engage with DMHIs impacts the intervention effect. This review determined whether the impact of user engagement was assessed in the intervention effect in Randomised Controlled Trials (RCTs) evaluating DMHIs targeting common mental disorders (CMDs).

methodsThis systematic review was registered on Prospero (CRD42021249503). RCTs published between 01/01/2016 and 17/09/2021 were included if evaluated DMHIs were delivered by app or website; targeted patients with a CMD without non-CMD comorbidities (e.g., diabetes); and were self-guided. Databases searched: Medline; PsycInfo; Embase; and CENTRAL. All data was double extracted. A meta-analysis compared intervention effect estimates when accounting for engagement and when engagement was ignored.

resultsWe identified 184 articles randomising 43,529 participants. Interventions were delivered predominantly via websites (145, 78.8%) and 140 (76.1%) articles reported engagement data. All primary analyses adopted treatment policy strategies, ignoring engagement levels. Only 19 (10.3%) articles provided additional intervention effect estimates accounting for user engagement: 2 (10.5%) conducted a complier-average-causal effect (CACE) analysis (principal stratum strategy) and 17 (89.5%) used a less-preferred per-protocol (PP) population excluding individuals failing to meet engagement criteria (estimand strategies unclear). Meta-analysis for PP estimates, when accounting for user engagement, changed the standardised effect to -0.18 95% CI (-0.32, -0.04) from - 0.14 95% CI (-0.24, -0.03) and sample sizes reduced by 33% decreasing precision, whereas meta-analysis for CACE estimates were - 0.19 95% CI (-0.42, 0.03) from - 0.16 95% CI (-0.38, 0.06) with no sample size decrease and less impact on precision. DISCUSSION: Many articles report user engagement metrics but few assessed the impact on the intervention effect missing opportunities to answer important patient centred questions for how well DMHIs work for engaged users. Defining engagement in this area is complex, more research is needed to obtain ways to categorise this into groups. However, the majority that considered engagement in analysis used approaches most likely to induce bias.

Indexed as

Mental DisordersPatient ParticipationRandomized Controlled Trials as TopicHumansMental HealthMental Health ServicesTelemedicineDigital healthDigital mental health interventionsMental healthMeta-analysisRandomised controlled trialsSystematic reviewUser engagement

Identifiers

PMID39182064
PMCPMC11344322

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.