Using text and charts to provide social norm feedback to general practices with high overall and high broad-spectrum antibiotic prescribing: a series of national randomised controlled trials

BACKGROUND

Sending a social norms feedback letter to general practitioners who are high prescribers of antibiotics has been shown to reduce antibiotic prescribing. The 2017-9 Quality Premium for primary care in England sets a target for broad-spectrum prescribing, which should be at or below 10% of total antibiotic prescribing. We tested a social norm feedback letter that targeted broad-spectrum prescribing and the addition of a chart to a text-only letter that targeted overall prescribing.

METHODS

We conducted three 2-armed randomised controlled trials, on different groups of practices: Trial A compared a broad-spectrum message and chart to the standard-practice overall prescribing letter (practices whose percentage of broad-spectrum prescribing was above 10% and who had relatively high overall prescribing). Trial C compared a broad-spectrum message and a chart to a no-letter control (practices whose percentage of broad-spectrum prescribing was above 10% and who had relatively moderate overall prescribing). Trial B compared an overall-prescribing message with a chart to the standard practice overall letter (practices whose percentage of broad-spectrum prescribing was below 10% but who had relatively high overall prescribing). Letters were posted to general practitioners, timed to be received on 1 November 2018. The primary outcomes were practices' percentage of broad-spectrum prescribing (trials A and C) and overall antibiotic prescribing (trial B) each month from November 2018 to April 2019 (all weighted by the number and characteristics of patients registered in the practice).

RESULTS

We randomly assigned 1909 practices; 58 closed or merged during the trial, leaving 1851 practices: 385 in trial A, 674 in trial C, and 792 in trial B. AR(1) models showed that there were no statistically significant differences in our primary outcome measures: trial A β = - .199, p = .13; trial C β = .006, p = .95; trial B β = - .0021, p = .81. In all three trials, there were statistically significant time trends, showing that overall antibiotic prescribing and total broad-spectrum prescribing were decreasing.

CONCLUSION

Our broad-spectrum feedback letters had no effect on broad-spectrum prescribing; adding a bar chart to a text-only letter had no effect on overall antibiotic prescribing. Broad-spectrum and overall prescribing were both decreasing over time.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03862794. March 5, 2019.

Messenger effects in COVID-19 communication: Does the level of government matter?

Public efforts to limit the spread of the coronavirus rely on motivating people to cooperate with the government. We test the effectiveness of different governmental messengers to encourage preventive health actions. We administered a survey experiment among a sample (n = 1,545) of respondents across the United States, presenting them with the same social media message, but experimentally varying the government sender (i.e., Federal, State, County, a combination of Federal + County, and a control condition) to test whether local relevance influences messaging efficacy. We find that in an information saturated environment the messenger does not matter. There is, however, variation in treatment response by partisanship, education, income, and the degree to which respondents are affected by the pandemic. While the main effect of the level of government on intended behavior is null, public health organizations are universally perceived as more trustworthy, relevant, and competent than anonymous messengers.