Evidence map›Paper›PMID 41851725›Full record

ArticleBMC public health2026

The use of smart surveillance technologies for suicide prevention in public spaces: a professional stakeholder survey from the United Kingdom.

Laura Joyner, Bethany Cliffe, Jay-Marie Mackenzie, Elizabeth Pettersen, Ian Marsh, Penny Phillips, Lisa Marzano

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

7 authors.

Laura JoynerDepartment of Psychology, Middlesex University, London, UK. l.joyner@mdx.ac.uk.
Bethany CliffeDepartment of Psychology, University of Westminster, London, UK.
Jay-Marie MackenzieDepartment of Psychology, University of Westminster, London, UK.
Elizabeth PettersenSamaritans, Ewell, UK.
Ian MarshFaculty of Medicine, Health and Social Care, Canterbury Christ Church University, Canterbury, UK.
Penny PhillipsNSPA Lived Experience Advisory Group, Ewell, UK.
Lisa MarzanoDepartment of Psychology, Middlesex University, London, UK.

Funding

National Institute for Health and Care Research NIHR151521
6 · The paper itself

Abstract

backgroundAround a third of suicides in the United Kingdom occur in public spaces, such as on the railways, at bridges, or coastal locations. Increasingly, the use of Artificial Intelligence and other smart technologies are being proposed as a means of optimising or automating aspects of the surveillance process in these environments. Yet relatively little is known about how they are being used for suicide prevention and the realities of deploying these systems in public spaces.

methods108 professional stakeholders across the UK completed an online survey to understand how smart surveillance technologies are being deployed across different types of public spaces to (also) prevent suicides. Through a series of multiple choice and open-ended questions, participants were also asked about the perceived benefits, limitations, and biggest barriers of implementing these technologies for suicide prevention reasons.

results72 examples of smart surveillance technology were identified, with around two-thirds at “high-risk” locations. Motion-activated CCTV, cameras with AI analytics, and Automatic Number Plate Recognition (ANPR) cameras were the most commonly identified technologies. More than half of systems alerted a control room when activated (58%), and the majority of all identified systems (80%) initiated a human-led response. Qualitative analysis suggests that these technologies can help guide real-time or future rescue responses. However, the importance of ensuring technology met the needs of a location was raised, with many originally designed for other purposes (e.g., crime prevention). Furthermore, several participants indicated technology alone could not prevent suicides, and felt a human response was still required. This, however, presented challenges such as the feasibility of delivering rapid responses. Barriers to installation and other challenges, including ethical and legal concerns, were also raised.

conclusionsThe present findings suggest that smart surveillance technologies have the potential to aide suicide prevention efforts but are unlikely to replace other measures. The findings highlight the importance of engaging with other stakeholders, including staff who lead the response or work with the systems day-to-day and people with lived experience of suicide. Furthermore, environmental factors, existing infrastructure and the processes surrounding the use of these tools may also influence their effectiveness as a suicide prevention measure when deployed in real-world settings.

Indexed as

Artificial IntelligencePopulation SurveillanceSuicide PreventionFemaleHumansIntelligent SystemsMaleStakeholder ParticipationSurveys and QuestionnairesUnited KingdomArtificial intelligenceCCTVHotspotsHuman factorsPublic safetyReal-world applicationSmart surveillanceSuicideSuicide preventionSurveillance technology

Identifiers

PMID41851725
PMCPMC13123109

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.