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General practitioner views on the determinants of test ordering: a theory-based qualitative approach to the development of an intervention to improve immunoglobulin requests in primary care

Overview of attention for article published in Implementation Science, July 2016
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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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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16 X users

Citations

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Title
General practitioner views on the determinants of test ordering: a theory-based qualitative approach to the development of an intervention to improve immunoglobulin requests in primary care
Published in
Implementation Science, July 2016
DOI 10.1186/s13012-016-0465-8
Pubmed ID
Authors

S. L. Cadogan, S. M. McHugh, C. P. Bradley, J. P. Browne, M. R. Cahill

Abstract

Research suggests that variation in laboratory requesting patterns may indicate unnecessary test use. Requesting patterns for serum immunoglobulins vary significantly between general practitioners (GPs). This study aims to explore GP's views on testing to identify the determinants of behaviour and recommend feasible intervention strategies for improving immunoglobulin test use in primary care. Qualitative semi-structured interviews were conducted with GPs requesting laboratory tests at Cork University Hospital or University Hospital Kerry in the South of Ireland. GPs were identified using a Health Service Executive laboratory list of GPs in the Cork-Kerry region. A random sample of GPs (stratified by GP requesting patterns) was generated from this list. GPs were purposively sampled based on the criteria of location (urban/rural); length of time qualified; and practice size (single-handed/group). Interviews were carried out between December 2014 and February 2015. Interviews were transcribed verbatim using NVivo 10 software and analysed using the framework analysis method. Emerging themes were mapped to the theoretical domains framework (TDF), which outlines 12 domains that can enable or inhibit behaviour change. The behaviour change wheel and behaviour change technique (BCT) taxonomy were then used to identify potential intervention strategies. Sixteen GPs were interviewed (ten males and six females). Findings suggest that intervention strategies should specifically target the key barriers to effective test ordering, while considering the context of primary care practice. Seven domains from the TDF were perceived to influence immunoglobulin test ordering behaviours and were identified as 'mechanisms for change' (knowledge, environmental context and resources, social/professional role and identity, beliefs about capabilities, beliefs about consequences, memory, attention and decision-making processes and behavioural regulation). Using these TDF domains, seven BCTs emerged as feasible 'intervention content' for targeting GPs' ordering behaviour. These included instructions on how to effectively request the test (how to perform behaviour), information on GPs' use of the test (feedback on behaviour), information about patient consequences resulting from not doing the test (information about health consequences), laboratory/consultant-based advice/education (credible source), altering the test ordering form (restructuring the physical environment), providing guidelines (prompts/cues) and adding interpretive comments to the results (adding objects to the environment). These BCTs aligned to four intervention functions: education, persuasion, environmental restructuring and enablement. This study has effectively applied behaviour change theory to identify feasible strategies for improving immunoglobulin test use in primary care using the TDF, 'behaviour change wheel' and BCT taxonomy. The identified BCTs will form the basis of a theory-based intervention to improve the use of immunoglobulin tests among GPs. Future research will involve the development and evaluation of this intervention.

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 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 86 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 25%
Researcher 11 13%
Student > Ph. D. Student 7 8%
Student > Doctoral Student 5 6%
Student > Bachelor 5 6%
Other 18 21%
Unknown 19 22%
Readers by discipline Count As %
Medicine and Dentistry 21 24%
Psychology 13 15%
Social Sciences 9 10%
Nursing and Health Professions 8 9%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 10 11%
Unknown 24 28%
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 13 December 2016.
All research outputs
#3,258,853
of 22,881,154 outputs
Outputs from Implementation Science
#704
of 1,722 outputs
Outputs of similar age
#62,577
of 363,105 outputs
Outputs of similar age from Implementation Science
#11
of 26 outputs
Altmetric has tracked 22,881,154 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,722 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has gotten more attention than average, scoring higher than 59% 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 363,105 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 82% of its contemporaries.
We're also able to compare this research output to 26 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 57% of its contemporaries.