Life experiences and the roles people play in society affect the way people express emotion. Nurses must be skilled communicators because they interact continually with all sorts of people-different personalities, different occupations, varying states of health-so the nature of the job affects the way nurses express emotion, especially on the attentiveness. In this study, the attentiveness toward others (patients, younger siblings, and their own children) was noticed and the relationship between attentiveness-related parameters and speech-related parameters were investigated. For the study, we created a meaningless eight-syllable sample word, then had the participants enunciate the made-up word simulating five emotional states: neutral, joy, sadness, anger, and surprise. We conducted a sound analysis of the different emotions by measuring the fundamental frequency F0 (Hz), the max sound pressure frequency Fmax (Hz), max sound pressure MaxdB (dB), and the average sound pressure AvedB (dB), we also measured the phonation time in seconds. We then statistically analyzed the variation from the neutral state in each emotion. Twenty-two women took part in the study (mean age 29.6 ± 6.4), including 12 women with nursing experience (mean age 32.4 ± 6.0) and ten women without nursing experience (mean age 26.1 ± 5.1). The results revealed significant differences in speech parameters correlated with differences in attentiveness-related parameters-nursing experience, and whether the participant had younger siblings and/or child/children-thus suggesting a relationship between nursing experience and emotional expressiveness.

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Interruptions have been shown in medical settings to result in errors with serious and sometimes fatal consequences. The authors conducted an observational, time-motion study to examine the pattern of changes in workflow through the drawing of flowcharts based on different timings of interruption occurrences. Nurses were observed during their day-shift operations for two weekdays in two hospital wards of a public cancer treatment hospital. Among the total of 14,453 records, 1,413 represented interruptions (9.8%). Of these, 687 records (4.8%) represented the observed nurse interrupting someone else. The analysis focuses on 703 recordings (4.9%) representing someone interrupting the observed nurse and 23 recordings (0.2%) representing self-interruptions. Nurses were interrupted an average of 6 times per hour. To understand the effect of interruptions on the workflow, the timings of the interruptions were examined. Most interruptions, 70.8%, occurred during the transition between tasks, while 24.2% while the nurse was doing a task that did not directly involve the patient. Only 5.0% of the interruptions occurred during tasks in which the nurse directly dealt with the patient. Interruptions during indirect tasks and between tasks caused nurses to perform a task in response to the interruption 95.4% and 96.9% of the time, respectively. However, only approximately half (55.6%) of interruptions during direct tasks were responded to immediately; the remaining half were postponed. There was a significant difference in the occurrences of tasks stemming from an interruption (58.3% during direct care, 32.4% during indirect care, and 23.3% between tasks). There were three times more clinical decision points in the workflow during direct care and during indirect care than during scheduled transitions between tasks.The impact of an interruption depends on its timing. To manage interruptions effectively, it is crucial to understand this timing dependence.

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Cancer is the primary cause of death in Japan. Understanding the regional cancer incidence trends is fundamental for helping to plan numerical targets for cancer control in the prefecture. Unfortunately, incidence has not been recorded in every prefecture because of weaknesses in the legal infrastructure for cancer registration in Japan. Presenting a cancer incidence reference by prefecture, especially for areas where population-based cancer registries have not been started or have not achieved sufficient accuracy, would be useful.In this study, we predicted the incidence of major cancers for each prefecture based on the results reported by Utada et al. As a result, different projection tendencies were observed for different prefectures. We believe it is possible to estimate the number of cancer cases by prefectures that have different demographics. However, when we compared the estimated cancer cases with the reported cancer cases, differences were observed. It was difficult to judge whether this was due to characteristics of the prefectural populations or whether this reflected registration patterns for each type of cancer. It is necessary to continuously observe variations in cancer cases.

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