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Table 4 Categories of respondent comments

From: Why do hospital prescribers continue antibiotics when it is safe to stop? Results of a choice experiment survey

CategoryDescription of category content
Importance of clinical information, especially response to treatmentThis category highlighted the importance to review and revise decisions of signs that patients are improving or deteriorating following treatment. Such comments referred, for example, to the importance of the information provided by clinical assessment and observations, such as temperature, culture results and inflammatory markers.
Somebody else’s problemThis category expressed the view that antibiotic use in secondary care contributes relatively little to antibiotic resistance and that the focus of antibiotic stewardship should be elsewhere, such as primary care, agriculture or in other countries.
Critique of the studyComments in this category criticised elements of the choice questions. Examples included an assertion that chest X-rays produce clear results and that describing the results in our factor-level description as indicating ‘possible infiltrates’ was ‘daft’.
Didactic guidelinesThis category contained comments on the guidelines being too risk averse and reluctance not to follow the guidelines ‘when the stakes are high’ unless advised by a senior colleague.
The role of external pressure depends on the context and on where the pressure is coming fromA comment suggested that whether external pressure to continue antibiotics had an effect on review and revise decisions depends on where the pressure is coming from—for example, pressure from a consultant would have much more impact than pressure from patients’ relatives.
In real-life levels of harm from continuing/discontinuing antibiotics are harder to quantifyThis category expressed the view that in real clinical practice, the actual risk levels of continuing/discontinuing antibiotics are not clear-cut as presented in our choice experiment. Instead, they are ambiguous and must be inferred, for example, the degree of confidence in the diagnosis.