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Paper-based and web-based intervention modeling experiments identified the same predictors of general practitioners' antibiotic-prescribing behavior

Paper-based and web-based intervention modeling experiments identified the same predictors of general practitioners' antibiotic-prescribing behavior
Paper-based and web-based intervention modeling experiments identified the same predictors of general practitioners' antibiotic-prescribing behavior
Objectives
To evaluate the robustness of the intervention modeling experiment (IME) methodology as a way of developing and testing behavioral change interventions before a full-scale trial by replicating an earlier paper-based IME.

Study Design and Setting
Web-based questionnaire and clinical scenario study. General practitioners across Scotland were invited to complete the questionnaire and scenarios, which were then used to identify predictors of antibiotic-prescribing behavior. These predictors were compared with the predictors identified in an earlier paper-based IME and used to develop a new intervention.

Results
Two hundred seventy general practitioners completed the questionnaires and scenarios. The constructs that predicted simulated behavior and intention were attitude, perceived behavioral control, risk perception/anticipated consequences, and self-efficacy, which match the targets identified in the earlier paper-based IME. The choice of persuasive communication as an intervention in the earlier IME was also confirmed. Additionally, a new intervention, an action plan, was developed.

Conclusion
A web-based IME replicated the findings of an earlier paper-based IME, which provides confidence in the IME methodology. The interventions will now be evaluated in the next stage of the IME, a web-based randomized controlled trial.
296-304
Treweek, Shaun
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Bonetti, Debbie
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MacLennan, Graeme
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Barnett, Karen
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Eccles, Martin
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Jones, Claire
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Pitts, Nigel
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Ricketts, Ian
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Sullivan, Frank
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Weal, Mark J.
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Francis, Jill
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Treweek, Shaun
2e309a54-c618-4a59-b0fd-2b878034cb98
Bonetti, Debbie
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MacLennan, Graeme
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Barnett, Karen
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Eccles, Martin
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Jones, Claire
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Pitts, Nigel
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Ricketts, Ian
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Sullivan, Frank
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Weal, Mark J.
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Francis, Jill
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Treweek, Shaun, Bonetti, Debbie, MacLennan, Graeme, Barnett, Karen, Eccles, Martin, Jones, Claire, Pitts, Nigel, Ricketts, Ian, Sullivan, Frank, Weal, Mark J. and Francis, Jill (2014) Paper-based and web-based intervention modeling experiments identified the same predictors of general practitioners' antibiotic-prescribing behavior. Journal of Clinical Epidemiology, 67 (3), 296-304. (doi:10.1016/j.jclinepi.2013.09.015). (PMID:24388292)

Record type: Article

Abstract

Objectives
To evaluate the robustness of the intervention modeling experiment (IME) methodology as a way of developing and testing behavioral change interventions before a full-scale trial by replicating an earlier paper-based IME.

Study Design and Setting
Web-based questionnaire and clinical scenario study. General practitioners across Scotland were invited to complete the questionnaire and scenarios, which were then used to identify predictors of antibiotic-prescribing behavior. These predictors were compared with the predictors identified in an earlier paper-based IME and used to develop a new intervention.

Results
Two hundred seventy general practitioners completed the questionnaires and scenarios. The constructs that predicted simulated behavior and intention were attitude, perceived behavioral control, risk perception/anticipated consequences, and self-efficacy, which match the targets identified in the earlier paper-based IME. The choice of persuasive communication as an intervention in the earlier IME was also confirmed. Additionally, a new intervention, an action plan, was developed.

Conclusion
A web-based IME replicated the findings of an earlier paper-based IME, which provides confidence in the IME methodology. The interventions will now be evaluated in the next stage of the IME, a web-based randomized controlled trial.

Text
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More information

Accepted/In Press date: 24 September 2013
e-pub ahead of print date: 31 December 2013
Published date: March 2014
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 386537
URI: https://eprints.soton.ac.uk/id/eprint/386537
PURE UUID: 40ebd72a-7ed0-422c-a5f4-d03fab996975
ORCID for Mark J. Weal: ORCID iD orcid.org/0000-0001-6251-8786

Catalogue record

Date deposited: 02 Feb 2016 11:26
Last modified: 06 Jun 2018 13:08

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Contributors

Author: Shaun Treweek
Author: Debbie Bonetti
Author: Graeme MacLennan
Author: Karen Barnett
Author: Martin Eccles
Author: Claire Jones
Author: Nigel Pitts
Author: Ian Ricketts
Author: Frank Sullivan
Author: Mark J. Weal ORCID iD
Author: Jill Francis

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