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No alarms and no surprises: how qualitative data informs Bayesian inference of anticipated alarm sounds

机译：没有警报，没有任何意外：定性数据如何通知贝叶斯人的预期警报声

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Operators of control rooms may become desensitized when they are exposed to a large number of alarms. Minimizing the number of non-actionable alarms can reduce this safety hazard. However, existing practice fails to address how operators anticipate system events, and discards valuable feedback signals. We observed five operators in three satellite control rooms to assess the functionality of their alarm design. We recorded 140 auditory signals, of which 31 were labeled as alarms. Two of these alarms were actionable. Transitional Journey Maps were used to represent qualitative interview data and observation data. Statement analysis revealed that operators anticipated the majority of the alarms. Bayesian inference related anticipation to response behavior. Case-by-case analysis identified various non-actionable anticipated alarms as feedback signals. Existing practice marks these signals as nuisance, which seems inappropriate. Therefore, this study shows that qualitative data analysis is essential for interpreting quantitative data on alarm responses.
机译：当它们暴露于大量警报时，控制室的操作员可能会脱敏。最小化不可动作警报的数量可以减少这种安全危险。但是，现有的做法未能解决运营商如何预期系统事件，并丢弃有价值的反馈信号。我们在三个卫星控制室中观察了五个运营商，以评估其报警设计的功能。我们记录了140个听觉信号，其中31个被标记为警报。这些警报中的两个是可操作的。过渡旅程地图用于代表定性访谈数据和观察数据。声明分析显示，运营商预计大多数警报。贝叶斯推断相关的预期响应行为。逐个案例分析确定了各种不可动作的预期警报作为反馈信号。现有的练习将这些信号标记为滋扰，似乎不合适。因此，本研究表明，定性数据分析对于解释报警响应的定量数据至关重要。

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