↓ Skip to main content

The Patient Assessment of Chronic Illness Care produces measurements along a single dimension: results from a Mokken analysis

Overview of attention for article published in Health and Quality of Life Outcomes, April 2017
Altmetric Badge

Mentioned by

twitter
1 tweeter
facebook
1 Facebook page
reddit
1 Redditor

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
14 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The Patient Assessment of Chronic Illness Care produces measurements along a single dimension: results from a Mokken analysis
Published in
Health and Quality of Life Outcomes, April 2017
DOI 10.1186/s12955-017-0638-4
Pubmed ID
Authors

C. J. Gibbons, N. Small, J. Rick, J. Burt, M. Hann, P. Bower

Abstract

As the worldwide prevalence of chronic illness increases so too does the demand for novel treatments to improve chronic illness care. Quantifying improvement in chronic illness care from the patient perspective relies on the use of validated patient-reported outcome measures. In this analysis we examine the psychometric and scaling properties of the Patient Assessment of Chronic Illness Care (PACIC) questionnaire for use in the United Kingdom by applying scale data to the non-parametric Mokken double monotonicity model. Data from 1849 patients with long-term conditions in the UK who completed the 20-item PACIC were analysed using Mokken analysis. A three-stage analysis examined the questionnaire's scalability, monotonicity and item ordering. An automated item selection procedure was used to assess the factor structure of the scale. Analysis was conducted in an 'evaluation' dataset (n = 956) and results were confirmed using an independent 'validation' (n = 890) dataset. Automated item selection procedures suggested that the 20 items represented a single underlying trait representing "patient assessment of chronic illness care": this contrasts with the multiple domains originally proposed. Six items violated invariant item ordering and were removed. The final 13-item scale had no further issues in either the evaluation or validation samples, including excellent scalability (Ho = .50) and reliability (Rho = .88). Following some modification, the 13-items of the PACIC were successfully fitted to the non-parametric Mokken model. These items have psychometrically robust and produce a single ordinal summary score. This score will be useful for clinicians or researchers to assess the quality of chronic illness care from the patient's perspective.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 21%
Unspecified 2 14%
Student > Ph. D. Student 2 14%
Other 1 7%
Student > Master 1 7%
Other 5 36%
Readers by discipline Count As %
Psychology 4 29%
Nursing and Health Professions 3 21%
Medicine and Dentistry 3 21%
Unspecified 2 14%
Social Sciences 1 7%
Other 1 7%

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 04 April 2017.
All research outputs
#6,884,443
of 9,424,035 outputs
Outputs from Health and Quality of Life Outcomes
#660
of 1,120 outputs
Outputs of similar age
#172,754
of 261,476 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#36
of 69 outputs
Altmetric has tracked 9,424,035 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,120 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 23rd percentile – i.e., 23% 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 261,476 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.