In this paper, we report on a series of placements for clinical exercise physiology students in a simulation-based education environment with older, independent adults. The purpose of these placement opportunities was to help prepare students to work confidently and competently with older adults in primary healthcare settings. The effectiveness of these placements was measured through semi-structured interviews with the students, their supervisors and the volunteer patients, and also by analysing the content of the students' written reflection assignments. A combination of directed content analysis, informed by the research objectives and imposed upon the data, and conventional content analysis, in which codes were developed from themes emerging from the data, was adopted. Coding was based on units of meaning. Overall, the placement aims were met. Students reported increased confidence in communicating with older adults and in using the tools of their trade. This innovative simulation-based education experience helped students gain an understanding of their developing professional identities. However, the data show that some students still failed to recognise the value and importance of communication when working with older adults. The older adults reported that they enjoyed interacting with the students and believed that they had helped the students gain a positive impression of the cognitive and physical abilities of older adults. These older adults had also gained insight into the benefits of exercise physiology in terms of their own wellbeing. This paper demonstrates the benefits of engaging community support in developing healthcare workers and provides guidelines for replication of these innovative simulation-based education experiences. The paper is limited to reporting the social and community engagement benefits for older adults and the learning opportunities for the clinical exercise physiology students. Further research is needed to demonstrate the health gains for older adults who participate in such programmes.
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 October 2020.
All research outputs
#10,187,303
of 34,387,656 outputs
Outputs from Advances in Simulation
#249
of 383 outputs
Outputs of similar age
#104,861
of 339,141 outputs
Outputs of similar age from Advances in Simulation
#5
of 7 outputs
Altmetric has tracked 34,387,656 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 383 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,141 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.
