Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

中文翻译：

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闭路电视和录像在预防自杀中的应用：叙事回顾和未来方向

背景：自杀是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）和视频已用于多种应用，包括评估地铁站的危机行为，并使用计算机视觉来识别正在进行的自杀企图。但是，尚未有关于使用闭路电视和录像进行自杀研究和干预的评论。客观的：这项研究的目的是回顾文献，以了解如何将CCTV和视频数据用于理解和预防自杀。此外，为了更全面地掌握该领域的进展，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在自杀未遂之前识别行为来回应叙述性评论中发现的差距。方法：我们在PubMed，Inspec和Web of Science上使用关键字“自杀”，“ cctv”和“视频”进行了搜索。我们纳入了所有使用闭路电视或录像了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，则无论其质量如何，我们都将其包括在内，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果大小，但是我们注意到其设计和应用的缺点。在讨论研究时进行分析。结果：审查发现，CCTV和视频主要用于3种方式：（1）识别自杀的危险因素（例如，从面部表情推断出抑郁症），（2）尝试后了解自杀（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来识别是否正在进行自杀企图）。此外，进行中的工作演示了如何在尝试热点之前识别行为，这是文献中论文所指出的重要差距。结论：迄今为止，闭路电视和视频已被用于各种各样的应用中，尤其是在设计自动检测系统时，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动尝试行为的自动检测系统方面显示出可喜的进展，该系统可以允许早期干预。