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Nursing assistants: “He seems to be ill” – a reason for nurses to take action: validation of the Early Detection Scale of Infection (EDIS)

Overview of attention for article published in BMC Geriatrics, October 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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1 blog
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Title
Nursing assistants: “He seems to be ill” – a reason for nurses to take action: validation of the Early Detection Scale of Infection (EDIS)
Published in
BMC Geriatrics, October 2015
DOI 10.1186/s12877-015-0114-0
Pubmed ID
Authors

P. Tingström, A. Milberg, N. Rodhe, J. Ernerud, E. Grodzinsky, M. Sund-Levander

Abstract

Signs and symptoms of infection in frail elderly are atypical, causing delay in diagnosis and treatment. To improve communication between healthcare staff of signs and symptoms of infection we developed an instrument, using qualitative data from observations by nursing assistants when they suspected infection. The aim of this study was to assess the validity of nursing assistants observations by developing and testing the instrument for early detection of infection in elderly nursing home residents. The early detection of infection (EDIS) instrument was based on data from focus interviews with nursing assistants. Over one year the nursing assistants used EDIS to document episodes of suspected early signs and symptoms of infection in 204 nursing home residents. Two physicians classified documented episodes as "no infection", "possible infection", and "infection". The content validity of the 13 items of the EDIS was established to explore the relationships between the items. The construct validity was used to explore the relationship between the items and the presence or absence of infection. The predictive value of the developed model was evaluated by the percentage of correct classifications of the observed cases. Generalized linear model (ordinal multinomial distribution and logit link) was used. Of the 388 events of suspected infection, 20 % were assessed as no infection, 31 % as possible infection and 49 % as infection. Content validity analysis showed that 12/13 of the items correlated significantly with at least one other statement. The range in number of significant inter-correlations was from 0 ("pain") to 8 ("general signs and symptoms of illness"). The construct validity showed that the items "temperature" , "respiratory symptoms" and "general signs and symptoms of illness" were significantly related to "infection", and these were also selected in the model-building. These items predicted correct alternative responses in 61 % of the cases. The validation of EDIS suggests that the observation of "general signs and symptoms of illness", made by nursing assistants should be taken seriously in detecting early infection in frail elderly. Also, the statement "He/She is not as usual" should lead to follow-up.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 18%
Student > Ph. D. Student 7 11%
Student > Master 6 9%
Student > Bachelor 6 9%
Librarian 3 5%
Other 17 26%
Unknown 15 23%
Readers by discipline Count As %
Nursing and Health Professions 17 26%
Medicine and Dentistry 13 20%
Computer Science 4 6%
Social Sciences 2 3%
Psychology 2 3%
Other 10 15%
Unknown 18 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 15 May 2016.
All research outputs
#3,171,819
of 22,830,751 outputs
Outputs from BMC Geriatrics
#821
of 3,188 outputs
Outputs of similar age
#45,960
of 279,097 outputs
Outputs of similar age from BMC Geriatrics
#11
of 35 outputs
Altmetric has tracked 22,830,751 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,188 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has gotten more attention than average, scoring higher than 74% of its peers.
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 279,097 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.