Objective. Over the past decade, various programs and reforms have targeted the issue of people aged ,65 years living in 'permanent' residential aged care (PRAC). As context for ongoing policy discourse, the aim of this study was to evaluate trends in rates of young people entering and leaving PRAC from 2008 to 2018. Methods. Counts of people aged ,65 years entering, remaining in and exiting PRAC were obtained from the National Aged Care Data Clearinghouse. Age standardisation was used to control for changes in the age and size of the Australian population. Annual age-standardised rates of admissions (subtracting transfers) and exits to the community were calculated. Linear regression models tested for a sustained increase or decrease in age-standardised rates nationally and within state and age subgroups. Results. Notwithstanding year-to-year variation, neither admissions (subtracting transfers) nor exits to the community showed statistically significant increasing or decreasing trends in the national age-standardised rates. Admission rates varied by age and state. Conclusions. Many more young people are admitted to PRAC each year than return to community living, with no sustained change between 2008 and 2018 at the national level. Age standardisation is crucial for evaluating systemic population-level change regarding younger people in PRAC. What is known about the topic? As at June 2018, over 6000 people aged ,65 years still live in PRAC in Australia. Previous research has demonstrated that this cohort experiences a much poorer quality of life on average than people of similar age and disability who reside in other community settings. Various strategies for improving outcomes have been trialled, many aiming to reduce the number of younger people living in aged care; the National Disability Insurance Scheme (NDIS) also has this among its aims. What does this paper add? This paper reports trends in the number of young people entering and exiting aged care, after statistically controlling for changes due to population growth and aging. The paper highlights that national admission rates did not increase or decrease in a sustained manner, and that most of those admitted never return to community living before turning 65 years of age. What are the implications for practitioners? Programs and policies aimed at reducing the number of young people in aged care must grapple with the scale of the issue and its apparent resistance to amelioration over the past 10 years. The results of this study provide a benchmark against which to judge the future impact of the NDIS.
This study compared spontaneous cognitive responses to a positively vs. negatively framed health message. Deakin University students (n = 51) read one of two versions of a message concerning a type of heart disease. In the negative condition, the message focused on the prospect of experiencing heart disease; in the positive condition, it focused on the prospect of avoiding heart disease. Participants completed a thought-listing task, reporting any thought that occurred to them while they were reading the message. Consistent with hypotheses derived from Prospect Theory, the negative condition prompted more extensive processing and more defensive processing. Participants in the negative condition were also more likely to consider taking protective action. Findings are discussed in the context of the health-framing literature.
People typically exhibit 'unrealistic optimism' (UO): they believe they have a lower chance of experiencing negative events and a higher chance of experiencing positive events than does the average person. UO has been found to be greater for negative than positive events. This 'valence effect' has been explained in terms of motivational processes. An alternative explanation is provided by the 'numerosity model', which views the valence effect simply as a by-product of a tendency for likelihood estimates pertaining to the average member of a group to increase with the size of the group. Predictions made by the numerosity model were tested in two studies. In each, UO for a single event was assessed. In Study 1 (n = 115 students), valence was manipulated by framing the event either negatively or positively, and participants estimated their own likelihood and that of the average student at their university. In Study 2 (n = 139 students), valence was again manipulated and participants again estimated their own likelihood; additionally, group size was manipulated by having participants estimate the likelihood of the average student in a small, medium-sized, or large group. In each study, the valence effect was found, but was due to an effect on estimates of own likelihood, not the average person's likelihood. In Study 2, valence did not interact with group size. The findings contradict the numerosity model, but are in accord with the motivational explanation. Implications for health education are discussed.
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