Onie Sandersan, Li Xun, Liang Morgan, Sowmya Arcot, Larsen Mark Erik
Black Dog Institute, University of New South Wales, Sydney, Sydney, Australia.
School of Computer Science and Engineering, University of New South Wales, Sydney, Sydney, Australia.
JMIR Ment Health. 2021 May 7;8(5):e27663. doi: 10.2196/27663.
Suicide is a recognized public health issue, with approximately 800,000 people dying by suicide each year. Among the different technologies used in suicide research, closed-circuit television (CCTV) and video have been used for a wide array of applications, including assessing crisis behaviors at metro stations, and using computer vision to identify a suicide attempt in progress. However, there has been no review of suicide research and interventions using CCTV and video.
The objective of this study was to review the literature to understand how CCTV and video data have been used in understanding and preventing suicide. Furthermore, to more fully capture progress in the field, we report on an ongoing study to respond to an identified gap in the narrative review, by using a computer vision-based system to identify behaviors prior to a suicide attempt.
We conducted a search using the keywords "suicide," "cctv," and "video" on PubMed, Inspec, and Web of Science. We included any studies which used CCTV or video footage to understand or prevent suicide. If a study fell into our area of interest, we included it regardless of the quality as our goal was to understand the scope of how CCTV and video had been used rather than quantify any specific effect size, but we noted the shortcomings in their design and analyses when discussing the studies.
The review found that CCTV and video have primarily been used in 3 ways: (1) to identify risk factors for suicide (eg, inferring depression from facial expressions), (2) understanding suicide after an attempt (eg, forensic applications), and (3) as part of an intervention (eg, using computer vision and automated systems to identify if a suicide attempt is in progress). Furthermore, work in progress demonstrates how we can identify behaviors prior to an attempt at a hotspot, an important gap identified by papers in the literature.
Thus far, CCTV and video have been used in a wide array of applications, most notably in designing automated detection systems, with the field heading toward an automated detection system for early intervention. Despite many challenges, we show promising progress in developing an automated detection system for preattempt behaviors, which may allow for early intervention.
自杀是一个公认的公共卫生问题，每年约有80万人死于自杀。在自杀研究中使用的不同技术中，闭路电视（CCTV）和视频已被广泛应用于一系列领域，包括评估地铁站的危机行为，以及使用计算机视觉识别正在进行的自杀企图。然而，尚未有对使用CCTV和视频进行自杀研究及干预的综述。
本研究的目的是回顾文献，以了解CCTV和视频数据如何用于理解和预防自杀。此外，为了更全面地了解该领域的进展，我们报告了一项正在进行的研究，该研究通过使用基于计算机视觉的系统来识别自杀企图之前的行为，以回应叙述性综述中发现的一个空白。
我们在PubMed、Inspec和科学网（Web of Science）上使用关键词“自杀”、“CCTV”和“视频”进行搜索。我们纳入了任何使用CCTV或视频片段来理解或预防自杀的研究。如果一项研究属于我们感兴趣的领域，我们将其纳入，无论其质量如何，因为我们的目标是了解CCTV和视频的使用范围，而不是量化任何特定的效应大小，但我们在讨论这些研究时指出了其设计和分析中的缺点。
综述发现，CCTV和视频主要用于以下三种方式：（1）识别自杀风险因素（例如，从面部表情推断抑郁），（2）在自杀企图后理解自杀情况（例如，法医应用），以及（3）作为干预措施的一部分（例如，使用计算机视觉和自动化系统识别自杀企图是否正在进行）。此外，正在进行的工作展示了我们如何能够在热点地区识别自杀企图之前的行为，这是文献中的论文所确定的一个重要空白。
到目前为止，CCTV和视频已被广泛应用于众多领域，最显著的是在设计自动检测系统方面，该领域正朝着用于早期干预的自动检测系统发展。尽管存在许多挑战，但我们在开发用于自杀企图前行为的自动检测系统方面显示出了有希望的进展，这可能实现早期干预。
