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Background: Chinese family structure has undergone tremendous changes over the past few decades. Moreover, the association of the intergenerational structure with depression remains controversial. Aims: This study aimed to find out the association of the intergenerational structure and the onset of depressive symptoms among Chinese middle-aged and older adults. Methods: This study included 4,868 participants of the China Health and Retirement Longitudinal Study (CHARLS), who were enrolled in 2011 without depressive symptoms and followed up at least once later in 2013, 2015, 2018, and 2020. Taking the time-varying confounding effect into account, the time-dependent Cox regression models were used to estimate the association of the intergenerational structure and the onset of depressive symptoms. Results: Among the studied middle-aged and older adults, compared to one-generation households, higher hazard ratios (HR) of developing depressive symptoms were found in three-generation households in the study population (HR = 1.21, 95% CI [1.08, 1.36]). Further, for female participants, skipping-generation households (HR = 1.38, 95% CI [1.05, 1.83]) and three-generation lineal households (HR = 1.21, 95% CI [1.02, 1.43]) were found to be significantly associated with new-onset depressive symptoms compared to empty-nest couples. For male participants, living alone (HR = 1.65, 95% CI [1.30, 2.11]), living in standardized nuclear households (HR = 1.27, 95% CI [1.06, 1.54]), impaired nuclear households (HR = 1.80, 95% CI [1.18, 2.76]), or three-generation lineal households (HR = 1.34, 95% CI [1.12, 1.60]) were found to have a significant association with the onset of depressive symptoms. Conclusions: This study found that males living alone, with unmarried children, or in three-generation lineal households, and females living with grandchildren were more likely to suffer from depressive symptoms. Therefore, special attention should be paid to people in these intergenerational structure subtypes.

BACKGROUND: The Australian government has implemented a compulsory aged care accreditation system to guide and monitor the risk management approach in registered residential aged care (RAC) homes. This research assessed the contribution of electronic health records (EHR) to risk management in RAC homes in relation to the extent that aged care accreditation fulfils its role. METHODS: A convenience sample of 5560 aged care accreditation reports published from 2011 to 2018 was manually downloaded from the Accreditation Agency web site. A mixed-method approach of text data mining and manual content analysis was used to identify any significant differences in failure to meet accreditation outcomes among the RAC homes. This took account of whether EHR or paper records were used, year of accreditation, and size and location of the homes. RESULTS: It appears that aged care accreditation was focused on structure and process, with limited attention to outcome. There was a big variation between homes in their use of measurement indicators to assess accreditation outcomes. No difference was found in outcomes between RAC homes using EHR and those using paper records. Only 3% of the RAC homes were found to have failed some accreditation outcomes. Failure in monitoring mechanism was the key factor for failing many accreditation outcomes. The top five failed outcomes were Human Resource Management, Clinical Care, Information Systems, Medication Management and Behavioural Management. CONCLUSIONS: Sub-optimal outcomes have limited the effectiveness of accreditation in driving and monitoring risk management for care recipient safety in RAC homes. Although EHR is an important structure and process component for RAC services, it made a limited contribution to risk management for accreditation in Australian RAC homes. Either EHR was not effective, or the accreditation process was not robust enough to recognize its influence. Aged care accreditation in Australia needs to develop further outcome-based measures that are supported by ...

Current intrusion detection systems are mostly for detecting external attacks, but the "Prism Door" and other similar events indicate that internal staff may bring greater harm to organizations in information security. Traditional insider threat detection methods only consider the audit records of personal behavior and failed to combine it with business activities, which may miss the insider threat happened during a business process. The authors consider operators' behavior and correctness and performance of the business activities, propose a business process mining based insider threat detection system. The system firstly establishes the normal profiles of business activities and the operators by mining the business log, and then detects specific anomalies by comparing the content of real-time log with the corresponding normal profile in order to find out the insiders and the threats they have brought. The relating anomalies are defined and the corresponding detection algorithms are presented. The authors have performed experimentation using the ProM framework and Java programming, with five synthetic business cases, and found that the system can effectively identify anomalies of both operators and business activities that may be indicative of potential insider threat.