ObjectiveTo compare the disability conditions in different elderly populations in Sichuan province in order to get baseline data for further analyses in the future. MethodFrom October 2011 to August 2012, face-to-face interviews were performed by trained investigators in different elderly populations from urban communities, rural communities, acute care wards and rehabilitation wards. The main content of the investigation was the Elderly Disability Assessment Scale (EDAS). ResultsTotally, 1406 subjects were interviewed, among which, 1387 subjects completed the questionnaires. The response rate was 98.7%. The mean age of the participants was (73.8±8.2) years old. Elderly people dwelling in rural areas had a highest disability rate (81.4%), while the correspondent rate in subjects in acute care wards, rehabilitation wards, and urban community were 79.2%, 64.5%, and 53.8%, respectively (P<0.001). In each population, the disability rate increased with age. In the whole sample, most disabled subjects were of mild disability (80.5%). However, those in acute care wards or rehabilitation wards were more likely to have severe or profound disability. ConclusionsThe disability rate and the severity of disability increase with age in different elderly populations in Sichuan province, although most of them are of mild disability. The disability rate is conspicuously higher in the elderly dwelling in rural areas.
ObjectiveTo discuss the demands for nursing knowledge among family caregivers for elderly people, in order to provide a basis for nurses to provide effective education for these people. MethodsBetween May and June 2012, a questionnaire which contained the condition of demands for nursing knowledge and the burden of care was used to investigate 1 600 family caregivers for the elderly people. ResultsThe caregivers had a demand for nursing knowledge, which may include the knowledge on medicine, disease and caregiving. The demand for knowledge was correlated with relationship between the caregivers and care recipients, health condition of the caregivers and care burden. ConclusionThe demands for nursing knowledge are higher in those who have spouse and high burden of care, without disease and symptom; we should pay more attention on them and take measures to reduce their burden of care.
Objective To broaden the current understanding of the usage willingness about artificial intelligence (AI) robots and relevant influence factors for elderly patients. Methods The elderly patients in the inpatient ward, outpatient department and physical examination of the Department of Geriatrics, West China Hospital of Sichuan University were selected by convenient sampling for investigation between February and April 2020, to explore the willingness of elderly patients to use AI robots and related influencing factors. Results A total of 446 elderly patients were included. There were 244 males and 202 females. The willingness to use AI robots was (14.40±3.62) points. There were statistically significant differences among the elderly patients with different ages, marital status, living conditions, educational level, current health status, current vision status, current hearing status, self-care ability and family support in their willingness to use AI robots (P<0.05). Multiple linear regression analysis showed that age, education level and family support were the influencing factors of use intention (P<0.05). Among the elderly patients, 60.76% had heard of AI robots, but only 28.03% knew the medical application of AI robots, and only 13.90% had used AI robot services. Most elderly patients (>60%) thought that some adverse factors may reduce their usage willingness, like “the price is too expensive” and “the use is complex, or I don’t know how to use”. Conclusions Elderly patients’ cognition of AI robots is still at a low level, and their willingness to use AI robots is mainly affected by age, education level and family support. It is suggested to consider the personalized needs of the elderly in terms of different ages, education levels and family support, and promote the cheap and user-friendly AI robots, so as to improve the use of AI robots by elderly patients.
Objective To systematically review injury, death, and their causes in elderly people in China from 2000 to 2020 and to prevent and reduce the occurrence of injuries and death. Methods The CNKI, VIP, WanFang Data, PubMed, SinoMed, and Web of Science databases were searched to collect studies on injury and death among elderly people over 60 years of age who resided in China from January 2000 to December 2020. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. A meta-analysis was then performed using R 4.1.2 software. Results A total of 41 studies with 187 488 subjects were included, including 125 million elderly individuals. The pooled injury mortality rate was 135.58/105 (95%CI 113.36/105 to 162.14/105, P<0.001). Subgroup analysis showed that male injury death (146.00/105, 95%CI 116.00 to 183.74, P=0.001) was significantly higher than that of females (127.90/105, 95%CI 102.31 to 159.88, P=0.001) and that overall injury mortality increased exponentially with age (R2=0.957), especially in those over 80 years old. The spatial distribution showed that the injury death rate in the central region was higher than that in the east and west and higher in the countryside than in the city. The time of death distribution showed that after China became an aging society (2000-2020), the time of death was significantly later than before (1990-2000). There were more than 12 types of injuries that caused death, the top three of which were falling, traffic accidents, and suicide. Conclusion From 2000 to 2020, the injury mortality rate of the elderly people in China initially increase and then slightly decrease. The phenomenon affects more men than women, especially those beyond the age of 80. Regional differences are identified, and the types of injuries that cause death are mainly falls, traffic accidents, and suicide. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.