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Background Patient safety culture is a core factor in increasing patient safety, is related to the quality of medical service, and can lower the risk of patient safety accidents. However, in dentistry, research has previously focused mostly on reporting of patient safety accidents. Dental professionals’ patient safety culture must therefore first be assessed, and related factors analyzed to improve patient safety. Methods This cross-sectional study completed a survey on 377 dental hygienists working in dental settings. To assess patient safety culture, we used a survey with proven validity and reliability by translating the Hospital Survey on Patient Safety Culture (HSOPS) developed by Agency for Healthcare Research and Quality (AHRQ) into Korean. Response options on all of the items were on 5-point Likert-type scales. SPSS v21 was used for statistical analysis. The relationships between workplace factors and patient safety culture were examined using t-tests and one-way analysis of variance (ANOVA) tests( p < 0.05). Results The work environment of dental hygienists has a close relationship with patient safety. Dental hygienists working ≥40 h/week in Korea had a significantly lower for patient safety grade than those working < 40 h/week. When the number of patients per day was less than 8, the safety level of patients was significantly higher. And significant differences were found depending on institution type, institution size. Conclusions In order to establish high-quality care and patient safety system practical policies must be enacted. In particular, assurance in the quality of work environment such as sufficient staffing, appropriate work hours, and enough rest must first be realized before patient safety culture can easily be formed.

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.