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Frameworks for self-management support for chronic disease: a cross-country comparative document analysis

Overview of attention for article published in BMC Health Services Research, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

1 news outlet
9 tweeters


23 Dimensions

Readers on

126 Mendeley
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Frameworks for self-management support for chronic disease: a cross-country comparative document analysis
Published in
BMC Health Services Research, July 2018
DOI 10.1186/s12913-018-3387-0
Pubmed ID

Selena O’Connell, Vera J. C. Mc Carthy, Eileen Savage


In a number of countries, frameworks have been developed to improve self-management support (SMS) in order to reduce the impact of chronic disease. The frameworks potentially provide direction for system-wide change in the provision of SMS by healthcare systems. Although policy formulation sets a foundation for health service reform, little is currently known about the processes which underpin SMS framework development as well as the respective implementation and evaluation plans. The aim of this study was to conduct a cross-country comparative document analysis of frameworks on SMS for chronic diseases in member countries of the Organisation for Economic Cooperation and Development. SMS frameworks were sourced through a systematic grey literature search and compared through document analysis using the Health Policy Triangle framework focusing on policy context, contents, actors involved and processes of development, implementation and evaluation. Eight framework documents published from 2008 to 2017 were included for analysis from: Scotland, Wales, Ireland, Manitoba, Queensland, Western Australia, Tasmania and the Northern Territory. The number of chronic diseases identified for SMS varied across the frameworks. A notable gap was a lack of focus on multimorbidity. Common courses of action across countries included the provision of self-management programmes for individuals with chronic disease and education to health professionals, though different approaches were proposed. The 'actors' involved in policy formulation were inconsistent across countries and it was only clear from two frameworks that individuals with chronic disease were directly involved. Half of the frameworks had SMS implementation plans with timelines. Although all frameworks referred to the need for evaluation of SMS implementation, few provided a detailed plan. Differences across frameworks may have implications for their success including: the extent to which people with chronic disease are involved in policy making; the courses of action taken to enhance SMS; and planned implementation processes including governance and infrastructure. Further research is needed to examine how differences in frameworks have affected implementation and to identify the critical success factors in SMS policy implementation.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters 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 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 126 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 17%
Student > Ph. D. Student 14 11%
Student > Bachelor 14 11%
Other 8 6%
Researcher 7 6%
Other 20 16%
Unknown 42 33%
Readers by discipline Count As %
Nursing and Health Professions 29 23%
Medicine and Dentistry 26 21%
Social Sciences 7 6%
Psychology 5 4%
Business, Management and Accounting 4 3%
Other 11 9%
Unknown 44 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 21 December 2021.
All research outputs
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Outputs from BMC Health Services Research
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Outputs of similar age
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Outputs of similar age from BMC Health Services Research
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Altmetric has tracked 21,377,679 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,102 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done particularly well, scoring higher than 90% 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 299,117 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 86% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them