| Title |
Quality of life in elderly people at the start of using in-home care
|
|---|---|
| Published in |
SpringerPlus, July 2015
|
| DOI | 10.1186/s40064-015-1161-x |
| Pubmed ID | |
| Authors |
Miyuki Imanishi, Hisao Tomohisa, Kazuo Higaki |
| Abstract |
Quality of life (QOL) among 200 elderly people planning to use in-home care services available to those with severe illness was surveyed to identify the most effective method of improving QOL of the elderly through such care services. QOL was surveyed using a PGC Morale Scale, and factors related to QOL were verified by multivariate analysis. The most relevant factors for QOL among the 11 analyzed were the client's reason for choosing to use in-home care services and the client's family structure. The average PGC-MS score was 9.09 ± 2.6 (mean ± standard deviation). Analysis of factors significantly affecting PGC-MS score identified treatment history and job type (p < 0.001), family structure (p < 0.009), age (p < 0.008), and years of education (p < 0.029). In addition, after performing multiple regression analysis using treatment history, years of education, employment history, and family structure as independent variables, treatment history (visiting a hospital and receiving treatment but deciding to use in-home care services later) remained significantly related to PGC-MS score (p < 0.001), as did family structure (three-generation families; p < 0.001). Further, with regard to treatment history, PGC-MC scores were higher in those who visited a hospital and received treatment but decided to use in-home care services later than in those who decided to enroll in the care service while still in the hospital. In contrast, with regard to family structure, PGC-MS scores decreased in the order of three-generation families, those living alone, couples, and two-generation families. QOL of elderly people might be improved by the provision of in-home care services with consideration of consumers' intentions and factors known to influence QOL. |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 7 | 20% |
| Student > Bachelor | 6 | 17% |
| Student > Ph. D. Student | 3 | 9% |
| Other | 2 | 6% |
| Researcher | 2 | 6% |
| Other | 6 | 17% |
| Unknown | 9 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 17% |
| Nursing and Health Professions | 5 | 14% |
| Computer Science | 4 | 11% |
| Social Sciences | 3 | 9% |
| Psychology | 2 | 6% |
| Other | 5 | 14% |
| Unknown | 10 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 25 August 2015.
All research outputs
#15,344,095
of 22,824,164 outputs
Outputs from SpringerPlus
#932
of 1,851 outputs
Outputs of similar age
#153,895
of 263,404 outputs
Outputs of similar age from SpringerPlus
#53
of 110 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,851 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.