Evidence map›Paper›PMID 40857091›Full record

Observational studyJournal of medical Internet research2025

Understanding Engagement With Digital Mental Health Technology in Mental Health Services: Multicenter Observational Study.

Luke J Borgnolo, Sarah McKenna, Ian B Hickie, Mathew Varidel, Ashlee Turner, Carla Gorban, Haley M LaMonica, Min K Chong, William Capon, Gina Dimitropoulos and 5 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

15 authors.

Luke J BorgnoloThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0009-0004-8221-2783
Sarah McKennaThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-8560-6399
Ian B HickieThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0001-8832-9895
Mathew VaridelThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-1648-8317
Ashlee TurnerThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-8919-4360
Carla GorbanThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0009-0003-9568-1792
Haley M LaMonicaThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-6563-5467
Min K ChongThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-4562-731X
William CaponThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0001-6500-9629
Gina DimitropoulosFaculty of Social Work, University of Calgary, Calgary, AB, Canada.ORCID https://orcid.org/0000-0001-9487-0290
Robert BattistiMind Plasticity, Sydney, Australia.ORCID https://orcid.org/0000-0001-9366-7872
Bradley WhitwellMind Plasticity, Sydney, Australia.ORCID https://orcid.org/0009-0004-8995-2696
Blake Hamiltonheadspace Camperdown, Sydney, Australia.ORCID https://orcid.org/0000-0001-6235-3264
Elizabeth M ScottThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-3907-0324
Frank IorfinoThe Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-1109-0972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital technologies can substantially improve mental health care by facilitating measurement-based care through routine outcome monitoring. However, their effectiveness is constrained by the extent to which these technologies are used by services, clinicians, and clients.

objectiveThis study aims to investigate engagement with the Innowell platform, a measurement-based digital mental health technology (DMHT), to gain insights into the individual- and service-level factors influencing engagement.

methodsParticipants were 2682 help-seeking clients from 12 Australian mental health services (11 headspace centers and 1 private practice, Mind Plasticity), wherein the Innowell platform was implemented. Although the initial implementation was standardized, services varied in their practical and continued use of the platform, as well as in the resources allocated to foster engagement. All participants completed an initial assessment during onboarding. Engagement was defined as their ensuing completion of the summary questionnaire, designed for routine outcome monitoring. Participants were classified as "initial assessment only," "single use" (1 completion of the summary questionnaire), or "≥2 uses" (≥2 completions). We analyzed engagement differences across services and associations between engagement and initial assessment scores.

resultsOf the 2682 help-seeking clients, 75.43% (n=2023) completed the initial assessment only, 11.56% (n=310) had 1 completion of the summary questionnaire, and 13.01% (n=349) had 2 or more completions. The service center was the strongest predictor of engagement, with Mind Plasticity participants showing >8 times higher engagement than other centers. At the individual level, higher scores in depression (P=.002), mania-like experiences (P=.047), suicide ideation (P=.004), hospitalization history for mental illness (P=.01), and physical activity (P<.001) were associated with increased engagement. In contrast, higher levels of anxiety symptoms (P=.01), alcohol use (P<.001), self-reported mental illness severity (P=.02), and social support (P=.047) predicted lower engagement. Age and several other clinical variables were not significant predictors when controlling for service-level factors.

conclusionsThis study reveals that both individual- and service-level factors significantly influence DMHT engagement, with the service center being the strongest predictor. This highlights the importance of service-level technology integration and support roles, such as digital navigators, in fostering engagement. Significant variation in engagement among user groups indicates the need for a nuanced approach to measurement-based care. While mental illness generally did not impede engagement, self-perceived severity and anxiety symptoms were barriers. These findings underscore the critical importance of systemic factors and service-level integration strategies in driving DMHT engagement. User-centered designs remain important, but effective integration of DMHTs into existing mental health services is paramount for improving engagement across diverse user groups and clinical presentations. This multilevel approach, encompassing individual, service, and system-wide considerations, is essential for realizing DMHTs' full potential in delivering effective measurement-based care.

Indexed as

Digital TechnologyMental Health ServicesAdultAustraliaFemaleHumansMaleMental DisordersMiddle AgedSurveys and QuestionnairesTelemedicinedigital mental health technologyimplementation sciencemeasurement-based caremental health servicesuser engagement

Identifiers

PMID40857091
PMCPMC12421206

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.