Evidence map›Paper›PMID 40789172›Full record

ReviewJMIR human factors2025

Human-Centered Design and Digital Transformation of Mental Health Services.

William Fleming, Adam Coutts, Diane Pochard, Daksha Trivedi, Kristy Sanderson

Abstract readReview
In one paragraph

Review in JMIR human factors, 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

5 authors.

William FlemingWellbeing Research Centre, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4724-9837
Adam CouttsNIHR Applied Research Collaboration East of England, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-5167-6591
Diane PochardCentre for Science and Policy, University of Cambridge, Cambridge, United Kingdom.ORCID 0009-0001-5268-9060
Daksha TrivediCentre for Research in Public Health and Community Care, School of Health, Medicine and Life Sciences, University of Hertfordshire, Hatfield, United Kingdom.ORCID 0000-0002-7572-4113
Kristy SandersonNIHR Applied Research Collaboration East of England, University of East Anglia, Norwich, United Kingdom.ORCID 0000-0002-3132-2745

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mental health services face a multitude of challenges, such as increasing demand, underfunding, and limited workforce capacity. The accelerated digital transformation of public services is positioned by government, the private sector, and some academic researchers as the solution. Alongside this, human-centered design has emerged as a guiding paradigm for this transformation to ensure user needs are met. We define what digital transformation and human-centered design are, how they are implemented in the UK policy context, and their role within the evolving delivery of mental health services. The involvement of one of our coauthors (DP) in the design and delivery of these policies over the past 5 years provides unique insights into the decision-making process and policy story. We review the promises, pitfalls, and ongoing challenges identified across a multidisciplinary literature. Finally, we propose future research questions and policy options to ensure that services are designed and delivered to meet the mental health needs of the population.

Indexed as

Mental Health ServicesUser-Centered DesignHealth PolicyHumansUnited Kingdomdigital mental healthdigital transformationhuman-centred designmental health policymental health servicespatient and public involvement

Identifiers

PMID40789172
PMCPMC12378389

What OpenQuestion holds

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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.