Jennifer Fletcher

Thinking styles and decision making: A meta-analysis.

This meta-analysis examined whether tendencies to use reflective and intuitive thinking styles predicted decision performance (normatively correct responding) and decision experience (e.g., speed, enjoyment) on a range of decision-making tasks. A pooled sample of 17,704 participants (Mage = 25 years) from 89 samples produced small but significant weighted average effects for reflection on performance (r = .11) and experience (r = .14). Intuition was negatively associated with performance (r = -.09) but positively associated with experience (r = .06). Moderation analyses using 499 effect sizes revealed heterogeneity across task-theory match/mismatch, task type, description-based versus experience-based decisions, time pressure, age, and measure type. Effects of both thinking styles were strongest when the task matched the theoretical strengths of the thinking style (up to r = .29). Specific tasks that produced the largest thinking style effects (up to r = .35) were also consistent with system characteristics. Time pressure weakened the effects of reflection, but not intuition, on performance. Effect sizes for reflection on performance were largest for individuals aged either 12 to 18 years or 25+ (up to r = .18), and the effects of both reflection and intuition on experience were largest for adults aged 25+ (up to r = .27). Overall, our results indicate that associations between thinking styles and decision outcomes are context dependent. To improve decision performance and experience, decision architects and educators should carefully consider both individual differences in the decision maker and the nature of the decision task.

A Systematic Review of Interventions to Change Staff Care Practices in Order to Improve Resident Outcomes in Nursing Homes.

Background We systematically reviewed interventions that attempted to change staff practice to improve long-term care resident outcomes. Methods Studies met criteria if they used a control group, included 6 or more nursing home units and quantitatively assessed staff behavior or resident outcomes. Intervention components were coded as including education material, training, audit and feedback, monitoring, champions, team meetings, policy or procedures and organizational restructure. Results Sixty-three unique studies were broadly grouped according to clinical domain—oral health (3 studies), hygiene and infection control (3 studies), nutrition (2 studies), nursing home acquired pneumonia (2 studies), depression (2 studies) appropriate prescribing (7 studies), reduction of physical restraints (3 studies), management of behavioral and psychological symptoms of dementia (6 studies), falls reduction and prevention (11 studies), quality improvement (9 studies), philosophy of care (10 studies) and other (5 studies). No single intervention component, combination of, or increased number of components was associated with greater likelihood of positive outcomes. Studies with positive outcomes for residents also tended to change staff behavior, however changing staff behavior did not necessarily improve resident outcomes. Studies targeting specific care tasks (e.g. oral care, physical restraints) were more likely to produce positive outcomes than those requiring global practice changes (e.g. care philosophy). Studies using intervention theories were more likely to be successful. Program logic was rarely articulated, so it was often unclear whether there was a coherent connection between the intervention components and measured outcomes. Many studies reported barriers relating to staff (e.g. turnover, high workload, attitudes) or organizational factors (e.g. funding, resources, logistics). Conclusion Changing staff practice in nursing homes is possible but complex. Interventionists should consider barriers and feasibility of program components to impact on each intended outcome.

Models of home care services for persons with dementia: a narrative review

BACKGROUND Worldwide trends of increasing dementia prevalence, have put economic and workforce pressures to shifting care for persons with dementia from residential care to home care. METHODS We reviewed the effects of the four dominant models of home care delivery on outcomes for community-dwelling persons with dementia. These models are: case management, integrated care, consumer directed care, and restorative care. This narrative review describes benefits and possible drawbacks for persons with dementia outcomes and elements that comprise successful programs. RESULTS Case management for persons with dementia may increase use of community-based services and delay nursing home admission. Integrated care is associated with greater client satisfaction, increased use of community based services, and reduced hospital days however the clinical impacts on persons with dementia and their carers are not known. Consumer directed care increases satisfaction with care and service usage, but had little effect on clinical outcomes. Restorative models of home care have been shown to improve function and quality of life however these trials have excluded persons with dementia, with the exception of a pilot study. CONCLUSIONS There has been a little research into models of home care for people with dementia, and no head-to-head comparison of the different models. Research to inform evidence-based policy and service delivery for people with dementia needs to evaluate both the impact of different models on outcomes, and investigate how to best deliver these models to maximize outcomes.

Community care for the Elderly: Needs and Service Use Study (CENSUS): Who receives home care packages and what are the outcomes?

Investigate factors associated with waiting times for home care packages and outcomes for care recipients and carers.

Heritability of Preferred Thinking Styles and a Genetic Link to Working Memory Capacity

Genetic and environmental contributions to preferences for rational and experiential thinking were examined in 100 pairs of monozygotic and 73 pairs of same-sex dizygotic Australian twins. Univariate analyses for experiential thinking and working memory capacity (WMC) revealed genetic effects accounted for 44% and 39% of the variability respectively, with non-shared environmental effects accounting for the balance. For rational thinking, the univariate models produced ambiguous results about the relative roles of heritability and shared environment, but a subsequent Cholesky analysis suggested genetic effects accounted for 34%, with the balance, 66%, explained by the non-shared environment. The Cholesky analysis revealed that shared genetic effects accounted for 60%, and non-shared environment accounted for 40% of the relationship between preference for rational thinking and WMC.