Prioritizing Patient Assessment Data (PAD) Using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©

The study identified priorities of the Patient Assessment Data (PAD) using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS©) derived from 644 psychiatric nurses’ responses who were practicing in specific units: Acute Care Units (ACU), General Care Units (GCU), Long-term Care Units (LCU), physically Complicated Disease Care Units (CDCU), and Dementia Care Units (DCU). Secondary analysis of the PsyNACS©on-line survey data using four levels of “importance” was used to determine the priorities: 1) unnecessary;2) quite important;3) important and 4) very important. The Mean Factor Points (MFP) and the Welch’s ANOVA were calculated. PsyNACS©score of 3 or higher indicates the PAD as priority. The results showed that in the ACU PAD1, “Psychological symptom”, “Stress coping”, and “Mood disorder and aggression”, and PAD2 “Information of adherence”, and “Information of the psychiatry rehabilitation”, and PAD7 “Situation of the family and social life”, “Relationship to the health care providers”, and “Relationships with others” are high priority (high importance). Other PADs showed results below PsyNACS©score of 3. The GCU had PAD 3 “Balance of water”, the LCU had PAD 4 “Intention/Point of view”, and “Thoughts of the patient” and PAD 7 “Disease and family”. The CDCU showed PAD 2 “Blood test”, PAD 3 “Excretion situation”, and PAD 5 “General health condition”, “Respiratory and chest symptom”, and “Vital signs”, and the DCU had PAD 1 “Cognition function”, and “Delirium and derangement capacity to register failure”, PAD 3 “Function of eating”, PAD 6 “Egestion and cleanliness” and PAD 8 “Activity and sleeping”, and “Mobility capability”. These classifications indicated levels of importance in the CAD comprising the PAD below the score of “2”. Japanese psychiatric hospitals specify assessments according to functional areas. By prioritizing the CAD for each PAD, more effective and efficient assessments can be performed according to practice unit.

Application of quantification theory in risk assessment of mine flooding

Hundreds of mine flooding accidents have occurred in China since the 1950s. These flooding accidents result in submerged working faces, even entire coal mines, leading to tremendous economic losses. It is reported that among 601 state-owned mines in China, 285 mines are exposed to water-inrush risks. The water pressure is becoming larger and larger with the increase of mining depth, leading to an increase of water-inrush hazards. Only when the risk of mine flooding is predicted in a reasonable manner, can we take timely and effective measures to prevent mine flooding from taking place. In our investigation quantification（H） theory is used to study the risk prediction problem about mine flooding. By investigating the main factors which affect mine flooding, eight risk assessment items have been identified. The extent of risk is classified into 4 grades. Given the data from different periods in the Feicheng mining area, a prediction model for the risk of mine flooding is established. The test analysis indicates a model correlation coefficient of 0.97 and the incidence of discrimination is as high as 97.37%, which implies that the effect of the model is quite satisfactory. With the help of computers, this method can be widely applied.

Safety Assesment Model for Fully-Mechanized Coalface

In this paper, the problem of safety assessment for fully\|mechanized coalface is studied by using the theory of quantification (model (Ⅱ)), and an applied assessment model is also established, which finds a new way for mines safety assessment.