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Randomized Controlled Trial
. 2025 Sep;30(3):e70020.
doi: 10.1111/bjhp.70020.

The effects of communicating illness diagnostic and treatment information and C-reactive protein test results on people's antibiotic expectations

Andriana Theodoropoulou  1   2 , Matteo Lisi  3 , Jonathan Rolision  1 , Miroslav Sirota  1
Affiliations
Randomized Controlled Trial

The effects of communicating illness diagnostic and treatment information and C-reactive protein test results on people's antibiotic expectations

Andriana Theodoropoulou et al. Br J Health Psychol. 2025 Sep.

Abstract

Objectives: Patients' expectations for antibiotics are among the strongest predictors of clinicians' decisions to overprescribe antibiotics. In this registered report, we used a signal detection theory framework to investigate the experimental effects of the communication interventions that family physicians can use to reduce patients' diagnostic uncertainty, and consequently, their antibiotic expectations. VSports手机版.

Methods: UK participants (N = 769) read hypothetical consultations for respiratory tract infections and were randomly assigned to one of three conditions: standard information (control), recommended information about the nature of the illness and antibiotic efficacy (recommended communication) or recommended information accompanied by point-of-care test results (recommended communication and CRP) V体育安卓版. Using a multilevel Bayesian probit regression, we estimated both decision bias (criterion) and sensitivity (d-prime). .

Results: Aligned with our bias hypotheses, participants displayed a more liberal antibiotic bias in the control condition compared to both the recommended communication (Δc = -1. 34, 95% CI [-1. 57, -1. 11]) and the recommended communication and CRP (Δc = -1. 73, 95% CI [-1. 99, -1. 48]) conditions. They also showed greater liberal bias in the recommended communication condition compared to the recommended communication and CRP condition (Δc = -0. 39, 95% CI [-0. 65, 0. 13]). Aligned with our sensitivity hypotheses, participants displayed significantly higher sensitivity in both the recommended communication (Δd' = 2. 34, 95% CI [1. 92, 2. 79]) and the recommended communication and CRP (Δd' = 2. 49, 95% CI [2 V体育ios版. 08, 2. 95]) conditions compared to control. .

Conclusions: Simple, evidence-based communication strategies-particularly when combined with diagnostic test results-can reduce antibiotic expectations, offering practical tools for clinicians to support appropriate prescribing VSports最新版本. .

Keywords: antibiotic expectations; communication strategies; diagnostic uncertainty; point‐of‐care tests; respiratory tract infections; signal detection theory V体育平台登录. .

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Conflict of interest statement

The authors declare that there are no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Figures

FIGURE 1
FIGURE 1
CONSORT diagram of participant flow.
FIGURE 2
FIGURE 2
Posterior predictive checks across conditions. The figure shows the mean posterior probability of responding that antibiotics are needed across the three conditions. The vertical bars show the observed means, while the histograms show the posterior predictive samples.
FIGURE 3
FIGURE 3
Distribution of antibiotic responses across scenarios and conditions. The figure shows the distribution of antibiotic responses (1 = ‘no’, 2 = ‘yes’) in the four scenario types: certain antibiotics are not needed (NN), uncertain antibiotics are not needed (UN), uncertain antibiotics are needed (UY) and certain antibiotics are needed (YY) in the control, recommended communication and recommended communication and CRP conditions. The black error bars represent the standard error of the mean.
FIGURE 4
FIGURE 4
Deviations from the optimal criterion across conditions. The figure shows the mean posterior deviations from the optimal criterion across the three conditions. The dashed grey line represents the optimal criterion location, the black dots represent the mean deviations, while the bold black lines represent the 95% credible intervals.
FIGURE 5
FIGURE 5
Posterior estimates for bias and sensitivity across conditions. The figure shows the posterior mean estimates for bias (criterion, the distance of the decision criterion from the noise distribution; a higher criterion value denotes a less liberal bias) and sensitivity (d‐prime, the distance between the signal and noise distribution; a higher d‐prime value denotes higher sensitivity) across the three conditions. The black dots represent the mean estimates, while the bold black lines represent the 95% credible intervals.
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