↓ Skip to main content

What are the core predictors of ‘hassles’ among patients with multimorbidity in primary care? A cross sectional study

Overview of attention for article published in BMC Health Services Research, July 2015
Altmetric Badge

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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
1 news outlet
twitter
16 X users
facebook
1 Facebook page

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
123 Mendeley
citeulike
2 CiteULike
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
What are the core predictors of ‘hassles’ among patients with multimorbidity in primary care? A cross sectional study
Published in
BMC Health Services Research, July 2015
DOI 10.1186/s12913-015-0927-8
Pubmed ID
Authors

Charles Adeniji, Cassandra Kenning, Peter A. Coventry, Peter Bower

Abstract

A limitation of service delivery in primary care in the United Kingdom is that services are often organised to manage discrete long-term conditions, using guidelines related to single conditions, and managed in clinics organised around single conditions. However, many older patients have more than one condition (so called multimorbidity). Qualitative research suggests that these patients experience 'hassles' in their care, including multiple appointments, poor co-ordination, and conflicting recommendations. However, there is limited quantitative evidence on the 'hassles' that patients with multimorbidity experience, or factors predicting 'hassles' in patients with multimorbidity. We conducted a cross sectional study, mailing questionnaires to 1460 patients with multimorbidity identified from the disease registers of four general practices in the UK. Patients were asked to complete a range of self-report measures including measures of multimorbidity, measures of their experience of multimorbidity and service delivery. Data were analysed using regression modelling to assess the factors predicting 'hassles' in patients with multimorbidity. In total 33 % (n = 486) of patients responded to the baseline survey. The 'hassles' most often reported by patients related to lack of information about conditions and treatment options, poor communication among health professionals, and poor access to specialist care. There was a significant relationship between numbers of conditions, and reports of 'hassles'. In multivariate analysis, 5 variables predicted more 'hassles': more long-term conditions, symptoms of anxiety and depression, younger age, being in paid employment, and not having a discussion with their GP in the last 12 months. Hassles are frequently reported by patients with multimorbidity in primary care. A priority for future research should be on the development of new models of care that better cater for these patients. This research highlights core hassles that need to be addressed, and the patient groups that are most at risk, which may aid in the design of these new models.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Switzerland 1 <1%
Unknown 120 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 14%
Researcher 16 13%
Student > Ph. D. Student 13 11%
Student > Postgraduate 8 7%
Student > Bachelor 8 7%
Other 27 22%
Unknown 34 28%
Readers by discipline Count As %
Medicine and Dentistry 39 32%
Nursing and Health Professions 19 15%
Psychology 10 8%
Social Sciences 10 8%
Computer Science 2 2%
Other 10 8%
Unknown 33 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 16 August 2023.
All research outputs
#1,835,258
of 25,205,864 outputs
Outputs from BMC Health Services Research
#636
of 8,559 outputs
Outputs of similar age
#22,381
of 268,818 outputs
Outputs of similar age from BMC Health Services Research
#10
of 103 outputs
Altmetric has tracked 25,205,864 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,559 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 92% 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 268,818 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.