Purpose
The increase in agitated or aggressive behaviour amongst nursing home residents with dementia is a challenging problem. Such behaviour causes stress for both resident and caregiver. Many non‐pharmacological interventions have been studied, but these interventions disregard the resident's unfulfilled needs and are executed by a single, designated caregiver. This study tests a non‐pharmacological intervention, applied by the entire team and based on the resident's underlying needs.
Design
A pretest and post‐test interventional study design was used, in which 65 residents with dementia who expressed agitated or aggressive behaviour. Data were collected from December 2016 until March 2017.
Methods
The ABC method and the Senses Framework were used to assign residents to either therapeutic touch, group music sessions or a meaningful individual activity. All staff members applied the interventions. Data were collected by use of the Neuropsychiatric Inventory‐Nursing Home version (NPI‐NH) and the Cohen‐Mansfield Agitation Inventory (CMAI).
Results
The frequency of aggression, loss of decorum, depression and the severity of aggression decreased for all three interventions. However, the overall severity of fear also increased. The overall prevalence of agitated of residents decreased for the therapeutic touch, group music sessions and individual activities.
Conclusions
This study shows the possibilities of designing individualised interventions on the Senses Framework and the ABC method for addressing agitated and aggressive behaviour amongst nursing home residents with dementia. The framework presented in this study should be further explored.
Implications for practice
A team‐based approach is effective to reduce agitated or aggressive behaviour amongst nursing home residents.
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For the algorithmic construction of optimal experimental designs, it is important to be able to evaluate small modifications of given designs in terms of the optimality criteria at a low computational cost. This can be achieved by using powerful update formulas for the optimality criteria during the design construction. The derivation of such update formulas for evaluating the impact of changes to the levels of easy-to-change factors and hard-tochange factors in split-plot designs as well as the impact of a swap of points between blocks or whole plots in block designs or split-plot designs is described.
In industrial experiments, there are often restrictions in randomization caused by equipment and resource constraints, as well as budget and time restrictions. Next to the split-plot and the split-split-plot design, the staggered-level design is an interesting design option for experiments involving two hard-to-change factors. The staggered-level design allows both hard-to-change factors to be reset at different points in time, resulting in a typical staggering pattern of factor level resettings. It has been shown that, for two-level designs, this staggering pattern leads to statistical benefits in comparison to the split-plot and the split-split-plot design. In this paper, we investigate whether the benefits of the staggered-level design carry over to situations where the objective is to optimize a response, and where a second-order response surface model is in place. To this end, we study several examples of Dand I-optimal staggered-level response surface designs.
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